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Kim S, Lee SW, Lee H, Lee HJ, Lee SJ, Chang Y. Disrupted cognitive network revealed by task-induced brain entropy in schizophrenia. Brain Imaging Behav 2024:10.1007/s11682-024-00909-3. [PMID: 39222212 DOI: 10.1007/s11682-024-00909-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/12/2024] [Indexed: 09/04/2024]
Abstract
Brain entropy (BEN), which measures the amount of information in brain activity, provides a novel perspective for evaluating brain function. Recent studies using resting-state functional magnetic resonance imaging (fMRI) have shown that BEN during rest can help characterize brain function alterations in schizophrenia (SCZ). However, there is a lack of research on BEN using task-evoked fMRI to explore task-dependent cognitive deficits in SCZ. In this study, we evaluate whether the reduced working memory (WM) capacity in SCZ is possibly associated with dynamic changes in task BEN during tasks with high cognitive demands. We analyzed data from 15 patients with SCZ and 15 healthy controls (HC), calculating task BEN from their N-back task fMRI scans. We then examined correlations between task BEN values, clinical symptoms, 2-back task performance, and neuropsychological test scores. Patients with SCZ exhibited significantly reduced task BEN in the cerebellum, hippocampus, parahippocampal gyrus, thalamus, and the middle and superior frontal gyrus (MFG and SFG) compared to HC. In HC, significant positive correlations were observed between task BEN and 2-back accuracy in several brain regions, including the MFG and SFG; such correlations were absent in patients with SCZ. Additionally, task BEN was negatively associated with scores for both positive and negative symptoms in areas including the parahippocampal gyrus among patients with SCZ. In conclusion, our findings indicate that a reduction in BEN within prefrontal and hippocampal regions during cognitively demanding tasks may serve as a neuroimaging marker for SCZ.
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Affiliation(s)
- Seungho Kim
- Department of Medical & Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Sang Won Lee
- Department of Psychiatry, Kyungpook National University Chilgok Hospital, Daegu, Korea
- Department of Psychiatry, School of Medicine, Kyungpook National University, 680 Gukchaebosang-ro, Jung-gu, Daegu, 41944, Korea
| | - Hansol Lee
- Department of Medical & Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Hui Joong Lee
- Department of Radiology, Kyungpook National University Hospital, Daegu, Korea
- Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Seung Jae Lee
- Department of Psychiatry, School of Medicine, Kyungpook National University, 680 Gukchaebosang-ro, Jung-gu, Daegu, 41944, Korea.
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea.
| | - Yongmin Chang
- Department of Radiology, Kyungpook National University Hospital, Daegu, Korea.
- Department of Molecular Medicine, School of Medicine, Kyungpook National University, 680 Gukchaebosang-ro, Jung-gu, Daegu, 41944, Korea.
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Wang F, Liu Z, Yang J, Sun F, Cheng P, Pan Y, Cheng Y, Tan W, Huang D, Zhang J, Li J, Zhang W, Yang J. The neural compensation phenomenon in schizophrenia with mild attention deficits during working memory task. Asian J Psychiatr 2024; 97:104077. [PMID: 38781692 DOI: 10.1016/j.ajp.2024.104077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 04/27/2024] [Accepted: 05/13/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Working memory (WM) and attention are essential cognitive processes, and their interplay is critical for efficient information processing. Schizophrenia often exhibits deficits in both WM and attention, contributing to function impairments. This study aims to investigate the neural mechanisms underlying the relationship between WM impairments and attention deficits in schizophrenia. METHODS We assessed the functional-MRI scans of the 184 schizophrenias with different attention deficits (mild=133; severe=51) and 146 controls during an N-back WM task. We explored their whole-brain functional connectome profile by adopting the voxel-wise degree centrality (DC). Linear analysis was conducted to explore the associations among attention deficit severity, altered DC, and WM performance in patients. RESULTS We observed that all patients showed decreased DC in the pre-supplementary area (pre-SMA), and posterior cerebellum compared to the controls, and schizophrenia patients with mild attention deficits showed decreased DC in the supramarginal gyrus, insula, and precuneus compared with the other 2 groups. DC values of the detected brain regions displayed U-shaped or inverted U-shaped curves, rather than a linear pattern, in response to increasing attention deficits. The linear analysis indicated that altered DC of the pre-SMA can modulate the relationship between attention deficits and WM performance. CONCLUSION The U-shaped or inverted U-shaped pattern in response to increasing attention deficits may reflect a compensation mechanism in schizophrenia with mild attention deficits. This notion is also supported by the linear analysis that schizophrenia patients with mild attention deficits can improve their WM performance by increasing the DC value of the pre-SMA.
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Affiliation(s)
- Feiwen Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Zhening Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jun Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Fuping Sun
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Peng Cheng
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Yunzhi Pan
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Yixin Cheng
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Wenjian Tan
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Danqing Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jiamei Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jinyue Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Wen Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jie Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
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3
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Tubiolo PN, Williams JC, Van Snellenberg JX. A tale of two n-backs: Diverging associations of dorsolateral prefrontal cortex activation with n-back task performance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595597. [PMID: 38826388 PMCID: PMC11142179 DOI: 10.1101/2024.05.23.595597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background In studying the neural correlates of working memory (WM) ability via functional magnetic resonance imaging (fMRI) in health and disease, it is relatively uncommon for investigators to report associations between brain activation and measures of task performance. Additionally, how the choice of WM task impacts observed activation-performance relationships is poorly understood. We sought to illustrate the impact of WM task on brain-behavior correlations using two large, publicly available datasets. Methods We conducted between-participants analyses of task-based fMRI data from two publicly available datasets: the Human Connectome Project (HCP; n = 866) and the Queensland Twin Imaging (QTIM) Study (n = 459). Participants performed two distinct variations of the n-back WM task with different stimuli, timings, and response paradigms. Associations between brain activation ([2-back - 0-back] contrast) and task performance (2-back % correct) were investigated separately in each dataset, as well as across datasets, within the dorsolateral prefrontal cortex (dlPFC), medial prefrontal cortex, and whole cortex. Results Global patterns of activation to task were similar in both datasets. However, opposite associations between activation and task performance were observed in bilateral pre-supplementary motor area and left middle frontal gyrus. Within the dlPFC, HCP participants exhibited a significantly greater activation-performance relationship in bilateral middle frontal gyrus relative to QTIM Study participants. Conclusions The observation of diverging activation-performance relationships between two large datasets performing variations of the n-back task serves as a critical reminder for investigators to exercise caution when selecting WM tasks and interpreting neural activation in response to a WM task.
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Affiliation(s)
- Philip N Tubiolo
- Department of Biomedical Engineering, Stony Brook University
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University
| | - John C Williams
- Department of Biomedical Engineering, Stony Brook University
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University
| | - Jared X Van Snellenberg
- Department of Biomedical Engineering, Stony Brook University
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University
- Department of Psychology, Stony Brook University
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Tubiolo PN, Williams JC, Van Snellenberg JX. Characterization and Mitigation of a Simultaneous Multi-Slice fMRI Artifact: Multiband Artifact Regression in Simultaneous Slices. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.25.573210. [PMID: 38234755 PMCID: PMC10793397 DOI: 10.1101/2023.12.25.573210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Simultaneous multi-slice (multiband) acceleration in fMRI has become widespread, but may be affected by novel forms of signal artifact. Here, we demonstrate a previously unreported artifact manifesting as a shared signal between simultaneously acquired slices in all resting-state and task-based multiband fMRI datasets we investigated, including publicly available consortium data from the Human Connectome Project (HCP) and Adolescent Brain Cognitive Development (ABCD) Study. We propose Multiband Artifact Regression in Simultaneous Slices (MARSS), a regression-based detection and correction technique that successfully mitigates this shared signal in unprocessed data. We demonstrate that the signal isolated by MARSS correction is likely non-neural, appearing stronger in neurovasculature than grey matter. Additionally, we evaluate MARSS both against and in tandem with sICA+FIX denoising, which is implemented in HCP resting-state data, to show that MARSS mitigates residual artifact signal that is not modeled by sICA+FIX. MARSS correction leads to study-wide increases in signal-to-noise ratio, decreases in cortical coefficient of variation, and mitigation of systematic artefactual spatial patterns in participant-level task betas. Finally, MARSS correction has substantive effects on second-level t-statistics in analyses of task-evoked activation. We recommend that investigators apply MARSS to multiband fMRI datasets with moderate or higher acceleration factors, in combination with established denoising methods.
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Affiliation(s)
- Philip N. Tubiolo
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY 11794
| | - John C. Williams
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY 11794
| | - Jared X. Van Snellenberg
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY 11794
- Department of Psychology, Stony Brook University, Stony Brook, NY 11794
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Li L, Liu C, Pan W, Wang W, Jin W, Ren Y, Ma X. Repetitive Transcranial Magnetic Stimulation for Working Memory Deficits in Schizophrenia: A Systematic Review of Randomized Controlled Trials. Neuropsychiatr Dis Treat 2024; 20:649-662. [PMID: 38528855 PMCID: PMC10962363 DOI: 10.2147/ndt.s450303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/15/2024] [Indexed: 03/27/2024] Open
Abstract
Working memory (WM) deficits are a significant component of neurocognitive impairment in individuals with schizophrenia (SCZ). Two previous meta-analyses, conducted on randomized controlled trials (RCTs), examined the effectiveness of repetitive transcranial magnetic stimulation (rTMS) in addressing WM deficits in individuals diagnosed with SCZ. However, the conclusions drawn from these analyses were inconsistent. Additionally, the commonly used random effects (RE) models might underestimate statistical errors, attributing a significant portion of perceived heterogeneity between studies to variations in study quality. Therefore, this review utilized both RE and quality effects (QE) models to assess relevant RCTs comparing TMS with sham intervention in terms of clinical outcomes. A comprehensive literature search was conducted using PubMed and Scopus databases, resulting in the inclusion of 13 studies for data synthesis. Overall, regardless of whether the RE or QE model was used, eligible RCTs suggested that the TMS and sham groups exhibited comparable therapeutic effects after treatment. The current state of research regarding the use of rTMS as a treatment for WM deficits in patients with SCZ remains in its preliminary phase. Furthermore, concerning the mechanism of action, the activation of brain regions focused on the dorsolateral prefrontal cortex and alterations in gamma oscillations may hold significant relevance in the therapeutic application of rTMS for addressing WM impairments. Finally, we believe that the application of closed-loop neuromodulation may contribute to the optimization of rTMS for WM impairment in patients with SCZ.
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Affiliation(s)
- Li Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Chaomeng Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Weigang Pan
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Wen Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Wenqing Jin
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Yanping Ren
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Xin Ma
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
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6
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Ghaneirad E, Borgolte A, Sinke C, Čuš A, Bleich S, Szycik GR. The effect of multisensory semantic congruency on unisensory object recognition in schizophrenia. Front Psychiatry 2023; 14:1246879. [PMID: 38025441 PMCID: PMC10646423 DOI: 10.3389/fpsyt.2023.1246879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Multisensory, as opposed to unisensory processing of stimuli, has been found to enhance the performance (e.g., reaction time, accuracy, and discrimination) of healthy individuals across various tasks. However, this enhancement is not as pronounced in patients with schizophrenia (SZ), indicating impaired multisensory integration (MSI) in these individuals. To the best of our knowledge, no study has yet investigated the impact of MSI deficits in the context of working memory, a domain highly reliant on multisensory processing and substantially impaired in schizophrenia. To address this research gap, we employed two adopted versions of the continuous object recognition task to investigate the effect of single-trail multisensory encoding on subsequent object recognition in 21 schizophrenia patients and 21 healthy controls (HC). Participants were tasked with discriminating between initial and repeated presentations. For the initial presentations, half of the stimuli were audiovisual pairings, while the other half were presented unimodal. The task-relevant stimuli were then presented a second time in a unisensory manner (either auditory stimuli in the auditory task or visual stimuli in the visual task). To explore the impact of semantic context on multisensory encoding, half of the audiovisual pairings were selected to be semantically congruent, while the remaining pairs were not semantically related to each other. Consistent with prior studies, our findings demonstrated that the impact of single-trial multisensory presentation during encoding remains discernible during subsequent object recognition. This influence could be distinguished based on the semantic congruity between the auditory and visual stimuli presented during the encoding. This effect was more robust in the auditory task. In the auditory task, when congruent multisensory pairings were encoded, both participant groups demonstrated a multisensory facilitation effect. This effect resulted in improved accuracy and RT performance. Regarding incongruent audiovisual encoding, as expected, HC did not demonstrate an evident multisensory facilitation effect on memory performance. In contrast, SZs exhibited an atypically accelerated reaction time during the subsequent auditory object recognition. Based on the predictive coding model we propose that this observed deviations indicate a reduced semantic modulatory effect and anomalous predictive errors signaling, particularly in the context of conflicting cross-modal sensory inputs in SZ.
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Affiliation(s)
- Erfan Ghaneirad
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
| | - Anna Borgolte
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
| | - Christopher Sinke
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Division of Clinical Psychology and Sexual Medicine, Hannover Medical School, Hannover, Germany
| | - Anja Čuš
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
| | - Stefan Bleich
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
- Center for Systems Neuroscience, University of Veterinary Medicine, Hanover, Germany
| | - Gregor R. Szycik
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
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Paunova R, Ramponi C, Kandilarova S, Todeva-Radneva A, Latypova A, Stoyanov D, Kherif F. Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes. Front Psychiatry 2023; 14:1272933. [PMID: 37908595 PMCID: PMC10614636 DOI: 10.3389/fpsyt.2023.1272933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/02/2023] [Indexed: 11/02/2023] Open
Abstract
Introduction In this study, we applied multivariate methods to identify brain regions that have a critical role in shaping the connectivity patterns of networks associated with major psychiatric diagnoses, including schizophrenia (SCH), major depressive disorder (MDD) and bipolar disorder (BD) and healthy controls (HC). We used T1w images from 164 subjects: Schizophrenia (n = 17), bipolar disorder (n = 25), major depressive disorder (n = 68) and a healthy control group (n = 54). Methods We extracted regions of interest (ROIs) using a method based on the SHOOT algorithm of the SPM12 toolbox. We then performed multivariate structural covariance between the groups. For the regions identified as significant in t term of their covariance value, we calculated their eigencentrality as a measure of the influence of brain regions within the network. We applied a significance threshold of p = 0.001. Finally, we performed a cluster analysis to determine groups of regions that had similar eigencentrality profiles in different pairwise comparison networks in the observed groups. Results As a result, we obtained 4 clusters with different brain regions that were diagnosis-specific. Cluster 1 showed the strongest discriminative values between SCH and HC and SCH and BD. Cluster 2 had the strongest discriminative value for the MDD patients, cluster 3 - for the BD patients. Cluster 4 seemed to contribute almost equally to the discrimination between the four groups. Discussion Our results suggest that we can use the multivariate structural covariance method to identify specific regions that have higher predictive value for specific psychiatric diagnoses. In our research, we have identified brain signatures that suggest that degeneracy shapes brain networks in different ways both within and across major psychiatric disorders.
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Affiliation(s)
- Rositsa Paunova
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Cristina Ramponi
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Anna Todeva-Radneva
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Adeliya Latypova
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Drozdstoy Stoyanov
- Department of Psychiatry and Medical Psychology, Medical University Plovdiv, Plovdiv, Bulgaria
- Research Institute, Medical University Plovdiv, Plovdiv, Bulgaria
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Selvaggi P, Fazio L, Toro VD, Mucci A, Rocca P, Martinotti G, Cascino G, Siracusano A, Zeppegno P, Pergola G, Bertolino A, Blasi G, Galderisi S. Effect of anticholinergic burden on brain activity during Working Memory and real-world functioning in patients with schizophrenia. Schizophr Res 2023; 260:76-84. [PMID: 37633126 DOI: 10.1016/j.schres.2023.08.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 06/30/2023] [Accepted: 08/13/2023] [Indexed: 08/28/2023]
Abstract
Cognitive impairment has been associated with poor real-world functioning in patients with Schizophrenia. Previous studies have shown that pharmacological treatment with anticholinergic properties may contribute to cognitive impairment in Schizophrenia. We investigated the effect of the anticholinergic burden (ACB) on brain activity, cognition, and real-world functioning in Schizophrenia. We hypothesized that greater ACB would be associated with altered brain activity along with poorer cognitive performance and lower real-world functioning. A sample of 100 patients with a diagnosis of schizophrenia or schizoaffective disorder was recruited in the naturalistic multicenter study of the Italian Network for Research on Psychoses (NIRP) across 7 centres. For each participant, ACB was evaluated using the Anticholinergic Cognitive Burden scale. The association of ACB with brain function was assessed using BOLD fMRI during the N-Back Working Memory (WM) task in a nested cohort (N = 31). Real-world functioning was assessed using the Specific Level of Functioning (SLOF) scale. Patients with high ACB scores (≥3) showed lower brain activity in the WM frontoparietal network (TFCE corrected alpha <0.05) and poorer cognitive performance (p = 0.05) than patients with low ACB scores (<3). Both effects were unaffected by demographic characteristics, clinical severity, and antipsychotic dosage. Moreover, patients with high ACB showed poorer real-world functioning than patients with lower ACB (p = 0.03). Our results suggest that ACB in Schizophrenia is associated with impaired WM and abnormal underlying brain function along with reduced real-world functioning. Clinical practice should consider the potential adverse cognitive effects of ACB in the treatment decision-making process.
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Affiliation(s)
- Pierluigi Selvaggi
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Leonardo Fazio
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy; Department of Medicine and Surgery, LUM University, Casamassima, Bari, Italy
| | - Veronica Debora Toro
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy
| | - Armida Mucci
- Department of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Paola Rocca
- Department of Neuroscience, Section of Psychiatry, University of Turin, Turin, Italy
| | - Giovanni Martinotti
- Department of Neuroscience and Imaging, G. D'Annunzio University, Chieti, Italy
| | - Giammarco Cascino
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Section of Neuroscience, University of Salerno, Salerno, Italy
| | - Alberto Siracusano
- Department of Systems Medicine, Psychiatry and Clinical Psychology Unit, Tor Vergata University of Rome, Rome, Italy
| | - Patrizia Zeppegno
- Department of Translational Medicine, Psychiatric Unit, University of Eastern Piedmont, Novara, Italy
| | - Giulio Pergola
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy
| | - Giuseppe Blasi
- Department of Translational Biomedicine and Neuroscience, University of Bari "Aldo Moro", Bari, Italy.
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy
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9
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Williams JC, Zheng ZJ, Tubiolo PN, Luceno JR, Gil RB, Girgis RR, Slifstein M, Abi-Dargham A, Van Snellenberg JX. Medial Prefrontal Cortex Dysfunction Mediates Working Memory Deficits in Patients With Schizophrenia. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:990-1002. [PMID: 37881571 PMCID: PMC10593895 DOI: 10.1016/j.bpsgos.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 10/04/2022] [Accepted: 10/11/2022] [Indexed: 02/18/2023] Open
Abstract
Background Schizophrenia (SCZ) is marked by working memory (WM) deficits, which predict poor functional outcome. While most functional magnetic resonance imaging studies of WM in SCZ have focused on the dorsolateral prefrontal cortex (PFC), some recent work suggests that the medial PFC (mPFC) may play a role. We investigated whether task-evoked mPFC deactivation is associated with WM performance and whether it mediates deficits in SCZ. In addition, we investigated associations between mPFC deactivation and cortical dopamine release. Methods Patients with SCZ (n = 41) and healthy control participants (HCs) (n = 40) performed a visual object n-back task during functional magnetic resonance imaging. Dopamine release capacity in mPFC was quantified with [11C]FLB457 in a subset of participants (9 SCZ, 14 HCs) using an amphetamine challenge. Correlations between task-evoked deactivation and performance were assessed in mPFC and dorsolateral PFC masks and were further examined for relationships with diagnosis and dopamine release. Results mPFC deactivation was associated with WM task performance, but dorsolateral PFC activation was not. Deactivation in the mPFC was reduced in patients with SCZ relative to HCs and mediated the relationship between diagnosis and WM performance. In addition, mPFC deactivation was significantly and inversely associated with dopamine release capacity across groups and in HCs alone, but not in patients. Conclusions Reduced WM task-evoked mPFC deactivation is a mediator of, and potential substrate for, WM impairment in SCZ, although our study design does not rule out the possibility that these findings could relate to cognition in general rather than WM specifically. We further present preliminary evidence of an inverse association between deactivation during WM tasks and dopamine release capacity in the mPFC.
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Affiliation(s)
- John C. Williams
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York
| | - Zu Jie Zheng
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
| | - Philip N. Tubiolo
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York
| | - Jacob R. Luceno
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
| | - Roberto B. Gil
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, Presbyterian/Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York, New York
| | - Ragy R. Girgis
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, Presbyterian/Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York, New York
| | - Mark Slifstein
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, Presbyterian/Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York, New York
| | - Anissa Abi-Dargham
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, Presbyterian/Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York, New York
| | - Jared X. Van Snellenberg
- Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, Presbyterian/Columbia University Irving Medical Center, New York, New York
- New York State Psychiatric Institute, New York, New York
- Department of Psychology, Stony Brook University, Stony Brook, New York
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10
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Feng N, Palaniyappan L, Robbins TW, Cao L, Fang S, Luo X, Wang X, Luo Q. Working memory processing deficit associated with a nonlinear response pattern of the anterior cingulate cortex in first-episode and drug-naïve schizophrenia. Neuropsychopharmacology 2023; 48:552-559. [PMID: 36376466 PMCID: PMC9852448 DOI: 10.1038/s41386-022-01499-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/12/2022] [Accepted: 10/31/2022] [Indexed: 11/16/2022]
Abstract
Impaired working memory (WM) is a core neuropsychological dysfunction of schizophrenia, however complex interactions among the information storage, information processing and attentional aspects of WM tasks make it difficult to uncover the psychophysiological mechanisms of this deficit. Thirty-six first-episode and drug-naïve schizophrenia and 29 healthy controls (HCs) were enrolled in this study. Here, we modified a WM task to isolate components of WM storage and WM processing, while also varying the difficulty level (load) of the task to study regional differences in load-specific activation using mixed effects models, and its relationship to distributed gene expression. Comparing patients with HCs, we found both attentional deficits and WM deficits, with WM processing being more impaired than WM storage in patients. In patients, but not controls, a linear modulation of brain activation was observed mainly in the frontoparietal and dorsal attention networks. In controls, an inverted U-shaped response pattern was identified in the left anterior cingulate cortex. The vertex of this inverted U-shape was lower in patients than controls, and a left-shifting axis of symmetry was associated with better WM performance in patients. Both the above linear and U-shaped modulation effects were associated with the expressions of the genes enriched in the dopamine neurotransmitter system across all cortical brain regions. These findings indicate that a WM processing deficit is evident in schizophrenia from an early stage before antipsychotic treatment, and associated with a dopamine pathway related aberration in nonlinear response pattern at the cingulate cortex when processing WM load.
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Affiliation(s)
- Nana Feng
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, PR China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
- Robarts Research Institute, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Trevor W Robbins
- Department Psychology and the Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, 200032, PR China
| | - Luolong Cao
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, PR China
| | - Shuanfeng Fang
- Department of Children Health Care, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, 450007, PR China
| | - Xingwei Luo
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, PR China.
- China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China.
| | - Qiang Luo
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, PR China.
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, 200032, PR China.
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11
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Kassim FM. Systematic reviews of the acute effects of amphetamine on working memory and other cognitive performances in healthy individuals, with a focus on the potential influence of personality traits. Hum Psychopharmacol 2023; 38:e2856. [PMID: 36251504 PMCID: PMC10078276 DOI: 10.1002/hup.2856] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 09/27/2022] [Accepted: 09/28/2022] [Indexed: 02/06/2023]
Abstract
OBJECTIVES This research aimed to systematically review the acute effects of amphetamine (AMP), a dopamine-releasing agent, on working memory (WM) and other cognitive performances. The investigation also aimed to review the impact of personality traits on the subjective and objective effects of AMP and possible links between personality traits and effects of AMP. METHODS Previous double-blind controlled studies assessing the main effects of AMP on WM and other cognitive performances in healthy volunteers were systematically reviewed. An electronic search was performed in the PUBMED and SCOPUS databases. Narrative reviews of the influence of personality traits on the subjective and objective effects of AMP were included. RESULTS Nineteen WM studies were included in the current review. Seven studies found effects of AMP on spatial WM, but only one study found the effect of AMP on verbal WM. Thirty-seven independent studies on other aspects of cognitive performance were identified. Twenty-two reported effects of AMP on cognitive functions. Studies also showed that personality traits are associated with the subjective effects of AMP. However, few studies reported the impacts of personality traits on the objective (such as WM) effects of AMP. CONCLUSION Overall, findings indicate that AMP has mixed-effects on spatial WM and other cognitive functions, but it lacks effects on verbal WM. Although there are insufficient studies on objective measures, studies also indicated that the subjective effects of AMP administration are linked to between-person variations in personality traits.
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Affiliation(s)
- Faiz M Kassim
- Pharmacology, School of Biomedical Sciences, University of Western Australia, Perth, Western Australia, Australia.,Department of Psychiatry, St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
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12
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Chauvière L. Early cognitive comorbidities before disease onset: A common symptom towards prevention of related brain diseases? Heliyon 2022; 8:e12259. [PMID: 36590531 PMCID: PMC9800323 DOI: 10.1016/j.heliyon.2022.e12259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 12/01/2022] [Accepted: 12/02/2022] [Indexed: 12/15/2022] Open
Abstract
Brain diseases are very heterogeneous; however they also display multiple common risk factors and comorbidities. With a paucity of disease-modifying therapies, prevention became a health priority. Towards prevention, one strategy is to focus on similar symptoms of brain diseases occurring before disease onset. Cognitive deficits are a promising candidate as they occur across brain diseases before disease onset. Based on recent research, this review highlights the similarity of brain diseases and discusses how early cognitive deficits can be exploited to tackle disease prevention. After briefly introducing common risk factors, I review common comorbidities across brain diseases, with a focus on cognitive deficits before disease onset, reporting both experimental and clinical findings. Next, I describe network abnormalities associated with early cognitive deficits and discuss how these abnormalities can be targeted to prevent disease onset. A scenario on brain disease etiology with the idea that early cognitive deficits may constitute a common symptom of brain diseases is proposed.
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13
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Gallucci J, Pomarol-Clotet E, Voineskos AN, Guerrero-Pedraza A, Alonso-Lana S, Vieta E, Salvador R, Hawco C. Longer illness duration is associated with greater individual variability in functional brain activity in Schizophrenia, but not bipolar disorder. Neuroimage Clin 2022; 36:103269. [PMID: 36451371 PMCID: PMC9723315 DOI: 10.1016/j.nicl.2022.103269] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/24/2022] [Accepted: 11/14/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Individuals with schizophrenia exhibit greater inter-patient variability in functional brain activity during neurocognitive task performance. Some studies have shown associations of age and illness duration with brain function; however, the association of these variables with variability in brain function activity is not known. In order to better understand the progressive effects of age and illness duration across disorders, we examined the relationship with individual variability in brain activity. METHODS Neuroimaging and behavioural data were extracted from harmonized datasets collectively including 212 control participants, 107 individuals with bipolar disorder, and 232 individuals with schizophrenia (total n = 551). Functional activity in response to an N-back working memory task (2-back vs 1-back) was examined. Individual variability was quantified via the correlational distance of fMRI activity between participants; mean correlational distance of one participant in relation to all others was defined as a 'variability score'. RESULTS Greater individual variability was found in the schizophrenia group compared to the bipolar disorder and control groups (p = 1.52e-09). Individual variability was significantly associated with aging (p = 0.027), however, this relationship was not different across diagnostic groups. In contrast, in the schizophrenia sample only, a longer illness duration was associated with increased variability (p = 0.027). CONCLUSION An increase in variability was observed in the schizophrenia group related to illness duration, beyond the effects of normal aging, implying illness-related deterioration of cognitive networks. This has clinical implications for considering long-term trajectories in schizophrenia and progressive neural and cognitive decline which may be amiable to novel treatments.
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Affiliation(s)
- Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Benito Menni Complex Assistencial en Salut Mental, Barcelona, Catalonia, Spain
| | - Silvia Alonso-Lana
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain,Research Centre and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades – Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Eduard Vieta
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain,Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, Barcelona, Catalonia, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada,Corresponding authors at: Centre for Addiction and Mental Health, 250 College Street, Toronto, ON, Spain.
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14
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Gallucci J, Tan T, Schifani C, Dickie EW, Voineskos AN, Hawco C. Greater individual variability in functional brain activity during working memory performance in Schizophrenia Spectrum Disorders (SSD). Schizophr Res 2022; 248:21-31. [PMID: 35908378 DOI: 10.1016/j.schres.2022.07.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 06/14/2022] [Accepted: 07/17/2022] [Indexed: 10/16/2022]
Abstract
Heterogeneity has been a persistent challenge in understanding Schizophrenia Spectrum Disorders (SSD). Traditional case-control comparisons often show variable results, and may not map well onto individuals. To better understand heterogeneity and group differences in SSD compared to typically developing controls (TDC), we examined variability in functional brain activity during a working memory (WM) task with known deficits in SSD. Neuroimaging and behavioural data were extracted from two datasets collectively providing 34 TDC and 56 individuals with SSD (n = 90). Functional activity in response to an N-Back WM task (3-Back vs 1-Back) was examined between and within groups. Individual variability was calculated via the correlational distance of fMRI activity maps between participants; mean correlational distance from one participant to all others was defined as a 'variability score'. Greater individual variability in functional activity was found in SSD compared to TDC (p = 0.00090). At the group level, a case-control comparison suggested SSD had reduced activity in task positive and task negative networks. However, when SSD were divided into high and low variability subgroups, the low variability groups showed no differences relative to TDC while the high variability group showed little activity at the group level. Our results imply prior case-control differences may be driven by a subgroup of SSD who do not show specific impairments but instead show more 'idiosyncratic' activity patterns. In SSD but not TDC, variability was also related to cognitive performance and age. This novel approach focusing on individual variability has important implications for understanding the neurobiology of SSD.
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Affiliation(s)
- Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Thomas Tan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Christin Schifani
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
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15
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Lucia M, Romanella SM, Di Lorenzo G, Demchenko I, Bhat V, Rossi S, Santarnecchi E. Neural correlates of N-back task performance and proposal for corresponding neuromodulation targets in psychiatric and neurodevelopmental disorders. Psychiatry Clin Neurosci 2022; 76:512-524. [PMID: 35773784 PMCID: PMC10603255 DOI: 10.1111/pcn.13442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 06/21/2022] [Accepted: 06/23/2022] [Indexed: 11/29/2022]
Abstract
AIM Working memory (WM) deficit represents the most common cognitive impairment in psychiatric and neurodevelopmental disorders, making the identification of its neural substrates a crucial step towards the conceptualization of restorative interventions. We present a meta-analysis focusing on neural activations associated with the most commonly used task to measure WM, the N-back task, in patients with schizophrenia, depressive disorder, bipolar disorder, and attention-deficit/hyperactivity disorder. Showing qualitative similarities and differences in WM processing between patients and healthy controls, we propose possible targets for cognitive enhancement approaches. METHODS Selected studies, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, were analyzed through the activation likelihood estimate statistical framework, with subsequent generation of disorder-specific N-back activation maps. RESULTS Despite similar WM deficits shared across all disorders, results highlighted different brain activation patterns for each disorder compared with healthy controls. In general, results showed brain activity in frontal, parietal, subcortical, and cerebellar regions; however, reduced engagement of specific nodes of the fronto-parietal network emerged in patients compared with healthy controls. In particular, neither bipolar nor depressive disorders showed detectable activations in the dorsolateral prefrontal cortices, while their parietal activation patterns were lateralized to the left and right hemispheres, respectively. On the other hand, patients with attention-deficit/hyperactivity disorder showed a lack of activation in the left parietal lobe, whereas patients with schizophrenia showed lower activity over the left prefrontal cortex. CONCLUSION These results, together with biophysical modeling, were then used to discuss the design of future disorder-specific cognitive enhancement interventions based on noninvasive brain stimulation.
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Affiliation(s)
- Mencarelli Lucia
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy
- Precision Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Sara M Romanella
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy
- Precision Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Giorgio Di Lorenzo
- IRCCS Fondazione Santa Lucia, Rome, Italy
- Laboratory of Psychophysiology and Cognitive Neuroscience, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Ilya Demchenko
- Interventional Psychiatry Program, Centre for Depression & Suicide Studies, St. Michael’s Hospital, Toronto, Ontario, Canada
| | - Venkat Bhat
- Interventional Psychiatry Program, Centre for Depression & Suicide Studies, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Simone Rossi
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy
- Human Physiology Section, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Emiliano Santarnecchi
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy
- Precision Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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16
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Wang F, Xi C, Liu Z, Deng M, Zhang W, Cao H, Yang J, Palaniyappan L. Load-dependent inverted U-shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study. J Psychiatry Neurosci 2022; 47:E341-E350. [PMID: 36167413 PMCID: PMC9524478 DOI: 10.1503/jpn.220053] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 06/28/2022] [Accepted: 08/05/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain. METHODS We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set. RESULTS Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the "2-back versus 0-back" contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%. LIMITATIONS We used a limited n-back paradigm that precluded the examination of higher working-memory loads. CONCLUSION Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia.
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Affiliation(s)
| | | | | | | | | | | | - Jie Yang
- From the Department of Psychiatry, Second Xiangya Hospital of Central South University, Changsha, Hunan, China (Wang, Xi, Liu, Deng, Zhang, Yang); the National Clinical Research Centre for Mental Disorders, Changsha, Hunan, China (Wang, Xi, Liu, Deng, Zhang, Yang); the Centre for Psychiatric Neuroscience, Feinstein Institutes for Medical Research, Manhasset, New York (Cao); the Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, New York (Cao); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que. (Palaniyappan); the Department of Medical Biophysics, Western University, London, Ont. (Palaniyappan); the Robarts Research Institute, Western University, London, Ont. (Palaniyappan)
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17
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Network hub centrality and working memory performance in schizophrenia. SCHIZOPHRENIA 2022; 8:76. [PMID: 36151201 PMCID: PMC9508261 DOI: 10.1038/s41537-022-00288-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 09/12/2022] [Indexed: 11/08/2022]
Abstract
Cognitive impairment, and working memory deficits in particular, are debilitating, treatment-resistant aspects of schizophrenia. Dysfunction of brain network hubs, putatively related to altered neurodevelopment, is thought to underlie the cognitive symptoms associated with this illness. Here, we used weighted degree, a robust graph theory metric representing the number of weighted connections to a node, to quantify centrality in cortical hubs in 29 patients with schizophrenia and 29 age- and gender-matched healthy controls and identify the critical nodes that underlie working memory performance. In both patients and controls, elevated weighted degree in the default mode network (DMN) was generally associated with poorer performance (accuracy and reaction time). Higher degree in the ventral attention network (VAN) nodes in the right superior temporal cortex was associated with better performance (accuracy) in patients. Degree in several prefrontal and parietal areas was associated with cognitive performance only in patients. In regions that are critical for sustained attention, these correlations were primarily driven by between-network connectivity in patients. Moreover, a cross-validated prediction analysis showed that a linear model using a summary degree score can be used to predict an individual’s working memory accuracy (r = 0.35). Our results suggest that schizophrenia is associated with dysfunctional hubs in the cortical systems supporting internal and external cognition and highlight the importance of topological network analysis in the search of biomarkers for cognitive deficits in schizophrenia.
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18
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Larsen NY, Vihrs N, Møller J, Sporring J, Tan X, Li X, Ji G, Rajkowska G, Sun F, Nyengaard JR. Layer III pyramidal cells in the prefrontal cortex reveal morphological changes in subjects with depression, schizophrenia, and suicide. Transl Psychiatry 2022; 12:363. [PMID: 36064829 PMCID: PMC9445178 DOI: 10.1038/s41398-022-02128-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 08/15/2022] [Accepted: 08/18/2022] [Indexed: 11/09/2022] Open
Abstract
Brodmann Area 46 (BA46) has long been regarded as a hotspot of disease pathology in individuals with schizophrenia (SCH) and major depressive disorder (MDD). Pyramidal neurons in layer III of the Brodmann Area 46 (BA46) project to other cortical regions and play a fundamental role in corticocortical and thalamocortical circuits. The AutoCUTS-LM pipeline was used to study the 3-dimensional structural morphology and spatial organization of pyramidal cells. Using quantitative light microscopy, we used stereology to calculate the entire volume of layer III in BA46 and the total number and density of pyramidal cells. Volume tensors estimated by the planar rotator quantified the volume, shape, and nucleus displacement of pyramidal cells. All of these assessments were carried out in four groups of subjects: controls (C, n = 10), SCH (n = 10), MDD (n = 8), and suicide subjects with a history of depression (SU, n = 11). SCH subjects had a significantly lower somal volume, total number, and density of pyramidal neurons when compared to C and tended to show a volume reduction in layer III of BA46. When comparing MDD subjects with C, the measured parameters were inclined to follow SCH, although there was only a significant reduction in pyramidal total cell number. While no morphometric differences were observed between SU and MDD, SU had a significantly higher total number of pyramidal cells and nucleus displacement than SCH. Finally, no differences in the spatial organization of pyramidal cells were found among groups. These results suggest that despite significant morphological alterations in layer III of BA46, which may impair prefrontal connections in people with SCH and MDD, the spatial organization of pyramidal cells remains the same across the four groups and suggests no defects in neuronal migration. The increased understanding of pyramidal cell biology may provide the cellular basis for symptoms and neuroimaging observations in SCH and MDD patients.
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Affiliation(s)
- Nick Y. Larsen
- grid.7048.b0000 0001 1956 2722Core Centre for Molecular Morphology, Section for Stereology and Microscopy, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark ,grid.7048.b0000 0001 1956 2722Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark ,Sino-Danish Center for Education and Research, Aarhus, Denmark ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, Beijing, China ,grid.5117.20000 0001 0742 471XCentre for Stochastic Geometry and Advanced Bioimaging, Aalborg University, Aarhus University and University of Copenhagen, Aarhus, Denmark
| | - Ninna Vihrs
- grid.5117.20000 0001 0742 471XDepartment of Mathematical Sciences, Aalborg University, Aalborg, Denmark
| | - Jesper Møller
- grid.5117.20000 0001 0742 471XCentre for Stochastic Geometry and Advanced Bioimaging, Aalborg University, Aarhus University and University of Copenhagen, Aarhus, Denmark ,grid.5117.20000 0001 0742 471XDepartment of Mathematical Sciences, Aalborg University, Aalborg, Denmark
| | - Jon Sporring
- grid.5117.20000 0001 0742 471XCentre for Stochastic Geometry and Advanced Bioimaging, Aalborg University, Aarhus University and University of Copenhagen, Aarhus, Denmark ,grid.5254.60000 0001 0674 042XDepartment of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Xueke Tan
- grid.418856.60000 0004 1792 5640National Key Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China ,grid.418856.60000 0004 1792 5640Center for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Xixia Li
- grid.5254.60000 0001 0674 042XDepartment of Computer Science, University of Copenhagen, Copenhagen, Denmark ,grid.418856.60000 0004 1792 5640National Key Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Gang Ji
- grid.5254.60000 0001 0674 042XDepartment of Computer Science, University of Copenhagen, Copenhagen, Denmark ,grid.418856.60000 0004 1792 5640National Key Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Grazyna Rajkowska
- grid.410721.10000 0004 1937 0407Department of Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS USA
| | - Fei Sun
- Sino-Danish Center for Education and Research, Aarhus, Denmark ,grid.410726.60000 0004 1797 8419University of the Chinese Academy of Sciences, Beijing, China ,grid.418856.60000 0004 1792 5640National Key Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China ,grid.418856.60000 0004 1792 5640Center for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Jens R. Nyengaard
- grid.7048.b0000 0001 1956 2722Core Centre for Molecular Morphology, Section for Stereology and Microscopy, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark ,Sino-Danish Center for Education and Research, Aarhus, Denmark ,grid.5117.20000 0001 0742 471XCentre for Stochastic Geometry and Advanced Bioimaging, Aalborg University, Aarhus University and University of Copenhagen, Aarhus, Denmark ,grid.154185.c0000 0004 0512 597XDepartment of Pathology, Aarhus University Hospital, Aarhus, Denmark
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Sarpal DK, Tarcijonas G, Calabro FJ, Foran W, Haas GL, Luna B, Murty VP. Context-specific abnormalities of the central executive network in first-episode psychosis: relationship with cognition. Psychol Med 2022; 52:2299-2308. [PMID: 33222723 PMCID: PMC9805803 DOI: 10.1017/s0033291720004201] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Cognitive impairments, which contribute to the profound functional deficits observed in psychotic disorders, have found to be associated with abnormalities in trial-level cognitive control. However, neural tasks operate within the context of sustained cognitive states, which can be assessed with 'background connectivity' following the removal of task effects. To date, little is known about the integrity of brain processes supporting the maintenance of a cognitive state in individuals with psychotic disorders. Thus, here we examine background connectivity during executive processing in a cohort of participants with first-episode psychosis (FEP). METHODS The following fMRI study examined background connectivity of the dorsolateral prefrontal cortex (DLPFC), during working memory engagement in a group of 43 patients with FEP, relative to 35 healthy controls (HC). Findings were also examined in relation to measures of executive function. RESULTS The FEP group relative to HC showed significantly lower background DLPFC connectivity with bilateral superior parietal lobule (SPL) and left inferior parietal lobule. Background connectivity between DLPFC and SPL was also positively associated with overall cognition across all subjects and in our FEP group. In comparison, resting-state frontoparietal connectivity did not differ between groups and was not significantly associated with overall cognition, suggesting that psychosis-related alterations in executive networks only emerged during states of goal-oriented behavior. CONCLUSIONS These results provide novel evidence indicating while frontoparietal connectivity at rest appears intact in psychosis, when engaged during a cognitive state, it is impaired possibly undermining cognitive control capacities in FEP.
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Affiliation(s)
- Deepak K. Sarpal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Goda Tarcijonas
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Finnegan J. Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gretchen L. Haas
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vishnu P. Murty
- Department of Psychology, Temple University, Philadelphia, PA, USA
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Abstract
Working memory (WM) refers to the ability to maintain a small number of representations in an activated, easily accessible state for a short period of time in the service of ongoing cognitive processing and behavior. Because WM is a resource critical for multiple forms of complex cognition and executive control of behavior, it is of central interest in the study of disorders such as schizophrenia that involve a broad compromise of cognitive function and in the regulation of goal-directed behavior. There is now robust evidence that WM impairment is characteristic of people with schizophrenia. The impairment includes both elementary storage capacity as well as more complex forms of WM that involve the manipulation and updating of WM representations. These impairments appear to underlie a substantial portion of the generalized cognitive deficit in schizophrenia. Neuroimaging studies have implicated widespread abnormalities in the broad neural system that subserves WM performance, consistent with the evidence of broad cognitive impairment seen in PSZ.
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Affiliation(s)
- James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Steven J Luck
- Center for Mind & Brain and Department of Psychology, University of California, Davis, CA, USA
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21
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Lin Y, Shu IW, Hsu SH, Pineda JA, Granholm EL, Singh F. Novel EEG-Based Neurofeedback System Targeting Frontal Gamma Activity of Schizophrenia Patients to Improve Working Memory. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:4031-4035. [PMID: 36085679 DOI: 10.1109/embc48229.2022.9870878] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Patients with schizophrenia (SCZ) exhibit working memory (WM) deficits that are associated with deficient dorsal-lateral prefrontal cortical activity, including decreased frontal gamma power. We thus hypothesized that training SCZ patients to increase frontal gamma activity would improve their WM performance. We administered electroencephalographic (EEG) neurofeedback (NFB) to 31 participants with SCZ for 12 weeks (24 sessions), which provides real-time visual and auditory feedback related to frontal gamma activity. The EEG-NFB training significantly improved EEG markers of optimal working memory, e.g., frontal P3 amplitude and gamma power. Based on these promising results, we developed a novel, EEGLAB/MATLAB-based brain-computer interface (BCI) that delivers F3-F4 gamma coherence NFB with a dynamic threshold to SCZ patients randomized in a double-blind, placebo-controlled clinical trial. The BCI significantly increased F3-F4 gamma coherence after 12 weeks (24 sessions) of training, according to data from the first 12 subjects ( n=6 /group) who completed gamma- or placebo-NFB training.
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22
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Combining fMRI and DISC1 gene haplotypes to understand working memory-related brain activity in schizophrenia. Sci Rep 2022; 12:7351. [PMID: 35513527 PMCID: PMC9072540 DOI: 10.1038/s41598-022-10660-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 04/11/2022] [Indexed: 11/30/2022] Open
Abstract
The DISC1 gene is one of the most relevant susceptibility genes for psychosis. However, the complex genetic landscape of this locus, which includes protective and risk variants in interaction, may have hindered consistent conclusions on how DISC1 contributes to schizophrenia (SZ) liability. Analysis from haplotype approaches and brain-based phenotypes can contribute to understanding DISC1 role in the neurobiology of this disorder. We assessed the brain correlates of DISC1 haplotypes associated with SZ through a functional neuroimaging genetics approach. First, we tested the association of two DISC1 haplotypes, the HEP1 (rs6675281-1000731-rs999710) and the HEP3 (rs151229-rs3738401), with the risk for SZ in a sample of 138 healthy subjects (HS) and 238 patients. This approach allowed the identification of three haplotypes associated with SZ (HEP1-CTG, HEP3-GA and HEP3-AA). Second, we explored whether these haplotypes exerted differential effects on n-back associated brain activity in a subsample of 70 HS compared to 70 patients (diagnosis × haplotype interaction effect). These analyses evidenced that HEP3-GA and HEP3-AA modulated working memory functional response conditional to the health/disease status in the cuneus, precuneus, middle cingulate cortex and the ventrolateral and dorsolateral prefrontal cortices. Our results are the first to show a diagnosis-based effect of DISC1 haplotypes on working memory-related brain activity, emphasising its role in SZ.
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23
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Adam Yaple Z, Tolomeo S, Yu R. Spatial and chronic differences in neural activity in medicated and unmedicated schizophrenia patients. Neuroimage Clin 2022; 35:103029. [PMID: 35569228 PMCID: PMC9112098 DOI: 10.1016/j.nicl.2022.103029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 04/10/2022] [Accepted: 04/28/2022] [Indexed: 11/07/2022]
Abstract
The medicated schizophrenia group yielded concordant activity among three right lateralized frontal clusters and a left lateralized parietal cluster. The unmedicated schizophrenia group yielded concordant activity among right lateralized frontal-parietal regions. A neural compensatory mechanism in schizophrenia.
A major caveat with investigations on schizophrenic patients is the difficulty to control for medication usage across samples as disease-related neural differences may be confounded by medication usage. Following a thorough literature search (632 records identified), we included 37 studies with a total of 740 medicated schizophrenia patients and 367 unmedicated schizophrenia patients. Here, we perform several meta-analyses to assess the neurofunctional differences between medicated and unmedicated schizophrenic patients across fMRI studies to determine systematic regions associated with medication usage. Several clusters identified by the meta-analysis on the medicated group include three right lateralized frontal clusters and a left lateralized parietal cluster, whereas the unmedicated group yielded concordant activity among right lateralized frontal-parietal regions. We further explored the prevalence of activity within these regions across illness duration and task type. These findings suggest a neural compensatory mechanism across these regions both spatially and chronically, offering new insight into the spatial and temporal dynamic neural differences among medicated and unmedicated schizophrenia patients.
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Affiliation(s)
| | - Serenella Tolomeo
- Social and Cognitive Computing Department, Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore, Singapore
| | - Rongjun Yu
- Department of Management, Hong Kong Baptist University, Hong Kong, China; Department of Sport, Physical Education and Health, Hong Kong Baptist University, Hong Kong, China; Department of Physics, Hong Kong Baptist University, Hong Kong, China.
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24
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Huang Y, Wang W, Hei G, Yang Y, Long Y, Wang X, Xiao J, Xu X, Song X, Gao S, Shao T, Huang J, Wang Y, Zhao J, Wu R. Altered regional homogeneity and cognitive impairments in first-episode schizophrenia: A resting-state fMRI study. Asian J Psychiatr 2022; 71:103055. [PMID: 35303593 DOI: 10.1016/j.ajp.2022.103055] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 01/11/2022] [Accepted: 02/27/2022] [Indexed: 01/18/2023]
Abstract
BACKGROUND Patients with schizophrenia consistently present pervasive cognitive deficits, but the neurobiological mechanism of cognitive impairments remains unclear. By analyzing regional homogeneity (ReHo) of resting-state functional Magnetic Resonance Imaging, this study aimed to explore the association between brain functional alterations and cognitive deficits in first-episode schizophrenia (FES) with a relatively large sample. METHODS A total of 187 patients with FES and 100 healthy controls from 3 independent cohorts underwent resting-state functional magnetic resonance scans. The MATRICS Consensus Cognitive Battery (MCCB) was used to assess cognitive function. Partial correlation analysis was performed between abnormal ReHo values and the severity of symptoms and cognitive deficits. RESULTS Compared with healthy controls, ReHo values increased in right superior frontal cortex and decreased in right anterior cingulate cortex (ACC), left middle occipital gyrus (MOG), left cuneus, right posterior cingulate cortex (PCC), and right superior occipital gyrus in schizophrenia patients. ReHo values in ACC, PCC and superior occipital gyrus were correlated with PANSS scores. In addition, ReHo values in ACC and MOG were negatively correlated with working memory; left cuneus was positively correlated with multiple cognitive domains (speed of processing, attention/vigilance and social cognition); PCC was positively correlated with verbal learning; right superior occipital gyrus was positively correlated with speed of processing and social cognition. CONCLUSION In conclusion, we found widespread ReHo alterations and cognitive dysfunction in FES. And the pathophysiology mechanism of a wide range of cognitive deficits may be related to abnormal spontaneous brain activity.
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Affiliation(s)
- Yuyan Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Weiyan Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Gangrui Hei
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China
| | - Ye Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Yujun Long
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xiaoyi Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Jingmei Xiao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xijia Xu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210000, Jiangsu, China
| | - Xueqin Song
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China
| | - Shuzhan Gao
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210000, Jiangsu, China
| | - Tiannan Shao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Jing Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Ying Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Jingping Zhao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Renrong Wu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
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25
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Wang L, Li Q, Wu Y, Ji GJ, Wu X, Xiao G, Qiu B, Hu P, Chen X, He K, Wang K. Intermittent theta burst stimulation improved visual-spatial working memory in treatment-resistant schizophrenia: A pilot study. J Psychiatr Res 2022; 149:44-53. [PMID: 35231791 DOI: 10.1016/j.jpsychires.2022.02.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 02/05/2022] [Accepted: 02/18/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Visual-spatial working memory (vsWM) impairment in treatment-resistant schizophrenia (TRS) currently has no satisfactory treatment. Our study aimed to improve vsWM function in TRS through intermittent theta burst stimulation (iTBS) using neuronavigation equipment to target the left dorsolateral prefrontal cortex. METHOD TRS patients (n = 59) were randomly allocated to receive iTBS (n = 33) or a sham treatment (n = 26) over 2 weeks. The participants including TRS patients and healthy controls (HCs) performed the vsWM n-back task, and TRS patients' neuroimaging data were acquired before and after treatment. All patients also underwent a battery of symptom measures to assess the severity of illness. The main outcome measure was the accuracy (ACC) of n-back target responses, particularly 3-back ACC. RESULTS The iTBS group showed considerable improvement in n-back ACC compared to the sham group, especially 3-back ACC. After iTBS, performance on the n-back task was comparable to that of HCs. The interaction (group × time) results showed increased fractional amplitude of low frequency fluctuations (fALFF) in the right occipital areas and decreased fALFF in the right precuneus. However, there was a negative correlation between the 3-back ACC and improved clinical symptoms scores. Improvements in 3-back ACC were positively correlated with activity in the right visual cortex. CONCLUSIONS Our study suggested that 2 weeks of iTBS intervention may be a novel, efficacious treatment for vsWM deficits in TRS, which can modulate the activity of local brain regions. iTBS can provide a solution for clinical treatment of TRS and may help patients approach normalcy.
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Affiliation(s)
- Lu Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Qianqian Li
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China; Department of Psychiatry, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yang Wu
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Gong-Jun Ji
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Xingqi Wu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Guixian Xiao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Bensheng Qiu
- Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Xingui Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China.
| | | | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Provincial Institute of Translational Medicine, Anhui Medical University, Hefei, China.
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26
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Korda A, Ventouras E, Asvestas P, Toumaian M, Matsopoulos G, Smyrnis N. Convolutional neural network propagation on electroencephalographic scalograms for detection of schizophrenia. Clin Neurophysiol 2022; 139:90-105. [DOI: 10.1016/j.clinph.2022.04.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 02/11/2022] [Accepted: 04/01/2022] [Indexed: 11/28/2022]
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Abstract
OBJECTIVE Cognitive tasks are used to probe neuronal activity during functional magnetic resonance imaging (fMRI) to detect signs of aberrant cognitive functioning in patients diagnosed with schizophrenia (SZ). However, nonlinear (inverted-U-shaped) associations between neuronal activity and task difficulty can lead to misinterpretation of group differences between patients and healthy comparison subjects (HCs). In this paper, we evaluated a novel method for correcting these misinterpretations based on conditional performance analysis. METHOD Participants included 25 HCs and 27 SZs who performed a working memory (WM) task (N-back) with 5 load conditions while undergoing fMRI. Neuronal activity was regressed onto: 1) task load (i.e., parametric task levels), 2) marginal task performance (i.e., performance averaged over all load conditions), or 3) conditional task performance (i.e., performance within each load condition). RESULTS In most regions of interest, conditional performance analysis uniquely revealed inverted-U-shaped neuronal activity in both SZs and HCs. After accounting for conditional performance differences between groups, we observed few difference in both the pattern and level of neuronal activity between SZs and HCs within regions that are classically associated with WM functioning (e.g., posterior dorsolateral prefrontal and parietal association cortices). However, SZs did show aberrant activity within the anterior dorsolateral prefrontal cortex. CONCLUSIONS Interpretations of differences in neuronal activity between groups, and of associations between neuronal activity and performance, should be considered within the context of task performance. Whether conditional performance-based differences reflect compensation, dedifferentiation, or other processes is not a question that is easily resolved by examining activation and performance data alone.
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28
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Lack of neural load modulation explains attention and working memory deficits in first-episode schizophrenia. Clin Neurophysiol 2022; 136:206-218. [DOI: 10.1016/j.clinph.2022.02.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 01/29/2022] [Accepted: 02/02/2022] [Indexed: 11/23/2022]
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Rezayat E, Clark K, Dehaqani MRA, Noudoost B. Dependence of Working Memory on Coordinated Activity Across Brain Areas. Front Syst Neurosci 2022; 15:787316. [PMID: 35095433 PMCID: PMC8792503 DOI: 10.3389/fnsys.2021.787316] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/06/2021] [Indexed: 11/15/2022] Open
Abstract
Neural signatures of working memory (WM) have been reported in numerous brain areas, suggesting a distributed neural substrate for memory maintenance. In the current manuscript we provide an updated review of the literature focusing on intracranial neurophysiological recordings during WM in primates. Such signatures of WM include changes in firing rate or local oscillatory power within an area, along with measures of coordinated activity between areas based on synchronization between oscillations. In comparing the ability of various neural signatures in any brain area to predict behavioral performance, we observe that synchrony between areas is more frequently and robustly correlated with WM performance than any of the within-area neural signatures. We further review the evidence for alteration of inter-areal synchrony in brain disorders, consistent with an important role for such synchrony during behavior. Additionally, results of causal studies indicate that manipulating synchrony across areas is especially effective at influencing WM task performance. Each of these lines of research supports the critical role of inter-areal synchrony in WM. Finally, we propose a framework for interactions between prefrontal and sensory areas during WM, incorporating a range of experimental findings and offering an explanation for the observed link between intra-areal measures and WM performance.
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Affiliation(s)
- Ehsan Rezayat
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Kelsey Clark
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
| | - Mohammad-Reza A. Dehaqani
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Cognitive Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Behrad Noudoost
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
- *Correspondence: Behrad Noudoost,
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30
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Binkowska AA, Jakubowska N, Krystecka K, Galant N, Piotrowska-Cyplik A, Brzezicka A. Theta and Alpha Oscillatory Activity During Working Memory Maintenance in Long-Term Cannabis Users: The Importance of the Polydrug Use Context. Front Hum Neurosci 2021; 15:740277. [PMID: 34733146 PMCID: PMC8558244 DOI: 10.3389/fnhum.2021.740277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 09/23/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Impairments in various subdomains of memory have been associated with chronic cannabis use, but less is known about their neural underpinnings, especially in the domain of the brain's oscillatory activity. Aims: To investigate neural oscillatory activity supporting working memory (WM) in regular cannabis users and non-using controls. We focused our analyses on frontal midline theta and posterior alpha asymmetry as oscillatory fingerprints for the WM's maintenance process. Methods: 30 non-using controls (CG) and 57 regular cannabis users-27 exclusive cannabis users (CU) and 30 polydrug cannabis users (PU) completed a Sternberg modified WM task with a concurrent electroencephalography recording. Theta, alpha and beta frequency bands were examined during WM maintenance. Results: When compared to non-using controls, the PU group displayed increased frontal midline theta (FMT) power during WM maintenance, which was positively correlated with RT. The posterior alpha asymmetry during the maintenance phase, on the other hand, was negatively correlated with RT in the CU group. WM performance did not differ between groups. Conclusions: Both groups of cannabis users (CU and PU), when compared to the control group, displayed differences in oscillatory activity during WM maintenance, unique for each group (in CU posterior alpha and in PU FMT correlated with performance). We interpret those differences as a reflection of compensatory strategies, as there were no differences between groups in task performance. Understanding the psychophysiological processes in regular cannabis users may provide insight on how chronic use may affect neural networks underlying cognitive processes, however, a polydrug use context (i.e., combining cannabis with other illegal substances) seems to be an important factor.
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Affiliation(s)
| | - Natalia Jakubowska
- SWPS University of Social Sciences and Humanities, Warsaw, Poland.,Polish-Japanese Academy of Information Technology, Warsaw, Poland
| | | | | | | | - Aneta Brzezicka
- SWPS University of Social Sciences and Humanities, Warsaw, Poland
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Serrano-Sosa M, Van Snellenberg JX, Meng J, Luceno JR, Spuhler K, Weinstein JJ, Abi-Dargham A, Slifstein M, Huang C. Multitask Learning Based Three-Dimensional Striatal Segmentation of MRI: fMRI and PET Objective Assessments. J Magn Reson Imaging 2021; 54:1623-1635. [PMID: 33970510 PMCID: PMC9204799 DOI: 10.1002/jmri.27682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/22/2021] [Accepted: 04/23/2021] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Recent studies have established a clear topographical and functional organization of projections to and from complex subdivisions of the striatum. Manual segmentation of these functional subdivisions is labor-intensive and time-consuming, and automated methods are not as reliable as manual segmentation. PURPOSE To utilize multitask learning (MTL) as a method to segment subregions of the striatum consisting of pre-commissural putamen (prePU), pre-commissural caudate (preCA), post-commissural putamen (postPU), post-commissural caudate (postCA), and ventral striatum (VST). STUDY TYPE Retrospective. POPULATION Eighty-seven total data sets from patients with schizophrenia and matched controls. FIELD STRENGTH/SEQUENCE 1.5 T and 3.0 T, T1 -weighted (SPGR SENSE, 3D BRAVO). ASSESSMENT MTL-generated segmentations were compared to the Imperial College London Clinical Imaging Center (CIC) atlas. Dice similarity coefficient (DSC) was used to compare the automated methods to manual segmentations. Positron emission tomography (PET) imaging: 60 minutes of emission data were acquired using [11 C]raclopride. Data were reconstructed by filtered back projection (FBP) with computed tomography (CT) used for attenuation correction. Binding potential values, BPND , and region of interest (ROI) time series and whole-brain connectivity using functional magnetic resonance imaging (fMRI) images were compared between manual and both automated segmentations. STATISTICAL TESTS Pearson correlation and paired t-test. RESULTS MTL-generated segmentations showed excellent spatial agreement with manual (DSC ≥0.72 across all striatal subregions). BPND values from MTL-generated segmentations were shown to correlate well with manual segmentations with R2 ≥ 0.91 in all caudate and putamen subregions, and R2 = 0.69 in VST. Mean Pearson correlation coefficients of the fMRI data between MTL-generated and manual segmentations were also high in time series (≥0.86) and whole-brain connectivity (≥0.89) across all subregions. DATA CONCLUSION Across both PET and fMRI task-based assessments, results from MTL-generated segmentations more closely corresponded to results from manually drawn ROIs than CIC-generated segmentations did. Therefore, the proposed MTL approach is a fast and reliable method for three-dimensional striatal subregion segmentation with results comparable to manually segmented ROIs. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Mario Serrano-Sosa
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY
| | - Jared X. Van Snellenberg
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY
- Department of Psychiatry, Stony Brook Medicine, Stony Brook, NY
| | - Jiayan Meng
- Department of Psychiatry, Stony Brook Medicine, Stony Brook, NY
| | - Jacob R. Luceno
- Department of Psychiatry, Stony Brook Medicine, Stony Brook, NY
| | - Karl Spuhler
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY
| | | | | | - Mark Slifstein
- Department of Psychiatry, Stony Brook Medicine, Stony Brook, NY
| | - Chuan Huang
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY
- Department of Psychiatry, Stony Brook Medicine, Stony Brook, NY
- Department of Radiology, Stony Brook Medicine, Stony Brook, NY
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Murphy CE, Walker AK, Weickert CS. Neuroinflammation in schizophrenia: the role of nuclear factor kappa B. Transl Psychiatry 2021; 11:528. [PMID: 34650030 PMCID: PMC8516884 DOI: 10.1038/s41398-021-01607-0] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 08/22/2021] [Accepted: 09/03/2021] [Indexed: 12/12/2022] Open
Abstract
Neuroinflammation, particularly in the dorsolateral prefrontal cortex, is well-established in a subset of people with schizophrenia, with significant increases in inflammatory markers including several cytokines. Yet the cause(s) of cortical inflammation in schizophrenia remains unknown. Clues as to potential microenvironmental triggers and/or intracellular deficits in immunoregulation may be gleaned from looking further upstream of effector immune molecules to transcription factors that control inflammatory gene expression. Here, we focus on the 'master immune regulator' nuclear factor kappa B (NF-κB) and review evidence in support of NF-κB dysregulation causing or contributing to neuroinflammation in patients. We discuss the utility of 'immune biotyping' as a tool to analyse immune-related transcripts and proteins in patient tissue, and the insights into cortical NF-κB in schizophrenia revealed by immune biotyping compared to studies treating patients as a single, homogenous group. Though the ubiquitous nature of NF-κB presents several hurdles for drug development, targeting this key immunoregulator with novel or repurposed therapeutics in schizophrenia is a relatively underexplored area that could aid in reducing symptoms of patients with active neuroinflammation.
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Affiliation(s)
- Caitlin E. Murphy
- grid.250407.40000 0000 8900 8842Neuroscience Research Australia, Randwick, NSW 2031 Australia
| | - Adam K. Walker
- grid.250407.40000 0000 8900 8842Neuroscience Research Australia, Randwick, NSW 2031 Australia ,grid.1005.40000 0004 4902 0432School of Psychiatry, University of New South Wales, Randwick, NSW 2031 Australia ,grid.1002.30000 0004 1936 7857Drug Discovery Biology Theme, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052 Australia
| | - Cynthia Shannon Weickert
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia. .,School of Psychiatry, University of New South Wales, Randwick, NSW, 2031, Australia. .,Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY, 13210, USA.
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Wang Y, Jiang Y, Collin G, Liu D, Su W, Xu L, Wei Y, Tang Y, Zhang T, Tang X, Hu Y, Zhang J, Cui H, Wang J, Yao D, Luo C, Wang J. The effects of antipsychotics on interactions of dynamic functional connectivity in the triple-network in first episode schizophrenia. Schizophr Res 2021; 236:29-37. [PMID: 34365083 DOI: 10.1016/j.schres.2021.07.038] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 05/08/2021] [Accepted: 07/28/2021] [Indexed: 11/15/2022]
Abstract
BACKGROUND Brain dynamics abnormalities in the triple-network, which involves the salience network (SN), the default mode network (DMN) and the central executive network (CEN), have been reported in schizophrenia. However, it remains to be clarified how antipsychotics affect dynamic functional connectivity (DFC) within the triple-network and whether differences in clinical outcomes are associated with varying levels of network model dysfunction. METHODS Resting-state functional magnetic resonance imaging scans were obtained from 64 first-episode schizophrenia patients (SZ) and 67 healthy controls (HC). All patients were scanned before and after 12-week antipsychotic treatment and the HC were scanned only at baseline. RESULTS At baseline, SZ participants showed significantly reduced dynamic functional interactions across the triple-network compared to HC. The SZ group displayed a pattern of reduction in resting-state DFC among the triple-network compared with HC. After medication, the mean dynamic network interaction index (dNII) value was improved. A significant quadratic relation was observed between longitudinal change of mean dNII and the reduction ratio of PANSS total score within the SZ group. The DFC within inter-network (between DMN and SN, and between DMN and CEN) and intra-network connections of DMN were significantly higher relative to baseline. Intra-SN DFC, intra-DMN DFC and DFC between SN and DMN were found to be predictive of clinical features at baseline. Intra-CEN DFC and DFC between DMN and CEN were predictive of treatment response. CONCLUSIONS Aberrant brain dynamics in the triple-network could be regulated with medication. DFC organization in the triple network was found to predict the clinical outcome.
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Affiliation(s)
- Yingchan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
| | - Guusje Collin
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Dengtang Liu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Wenjun Su
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yanyan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Xiaochen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Yegang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Jianye Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Huiru Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Jinhong Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China.
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, PR China.
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, PR China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai 200031, PR China; Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, PR China.
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Wang X, Cheng B, Roberts N, Wang S, Luo Y, Tian F, Yue S. Shared and distinct brain fMRI response during performance of working memory tasks in adult patients with schizophrenia and major depressive disorder. Hum Brain Mapp 2021; 42:5458-5476. [PMID: 34431584 PMCID: PMC8519858 DOI: 10.1002/hbm.25618] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 07/02/2021] [Accepted: 07/13/2021] [Indexed: 02/05/2023] Open
Abstract
Working memory (WM) impairments are common features of psychiatric disorders. A systematic meta-analysis was performed to determine common and disorder-specific brain fMRI response during performance of WM tasks in patients with SZ and patients with MDD relative to healthy controls (HC). Thirty-four published fMRI studies of WM in patients with SZ and 18 published fMRI studies of WM in patients with MDD, including relevant HC, were included in the meta-analysis. In both SZ and MDD there was common stronger fMRI response in right medial prefrontal cortex (MPFC) and bilateral anterior cingulate cortex (ACC), which are part of the default mode network (DMN). The effects were of greater magnitude in SZ than MDD, especially in prefrontal-temporal-cingulate-striatal-cerebellar regions. In addition, a disorder-specific weaker fMRI response was observed in right middle frontal gyrus (MFG) in MDD, relative to HC. For both SZ and MDD a significant correlation was observed between the severity of clinical symptoms and lateralized fMRI response relative to HC. These findings indicate that there may be common and distinct anomalies in brain function underlying deficits in WM in SZ and MDD, which may serve as a potential functional neuroimaging-based diagnostic biomarker with value in supporting clinical diagnosis, measuring illness severity and assessing the efficacy of treatments for SZ and MDD at the brain level.
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Affiliation(s)
- Xiuli Wang
- Department of Psychiatry, the Fourth People's Hospital of Chengdu, Chengdu, China
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, China
| | - Neil Roberts
- Edinburgh Imaging Facility, Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Song Wang
- Department of Radiology, Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Ya Luo
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Fangfang Tian
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Suping Yue
- Department of Psychiatry, the Fourth People's Hospital of Chengdu, Chengdu, China
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Sanford N, Woodward TS. Functional Delineation of Prefrontal Networks Underlying Working Memory in Schizophrenia: A Cross-data-set Examination. J Cogn Neurosci 2021; 33:1880-1908. [PMID: 34375420 DOI: 10.1162/jocn_a_01726] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Working memory (WM) impairment in schizophrenia substantially impacts functional outcome. Although the dorsolateral pFC has been implicated in such impairment, a more comprehensive examination of brain networks comprising pFC is warranted. The present research used a whole-brain, multi-experiment analysis to delineate task-related networks comprising pFC. Activity was examined in schizophrenia patients across a variety of cognitive demands. METHODS One hundred schizophrenia patients and 102 healthy controls completed one of four fMRI tasks: a Sternberg verbal WM task, a visuospatial WM task, a Stroop set-switching task, and a thought generation task (TGT). Task-related networks were identified using multi-experiment constrained PCA for fMRI. Effects of task conditions and group differences were examined using mixed-model ANOVA on the task-related time series. Correlations between task performance and network engagement were also performed. RESULTS Four spatially and temporally distinct networks with pFC activation emerged and were postulated to subserve (1) internal attention, (2) auditory-motor attention, (3) motor responses, and (4) task energizing. The "energizing" network-engaged during WM encoding and diminished in patients-exhibited consistent trend relationships with WM capacity across different data sets. The dorsolateral-prefrontal-cortex-dominated "internal attention" network exhibited some evidence of hypoactivity in patients, but was not correlated with WM performance. CONCLUSIONS Multi-experiment analysis allowed delineation of task-related, pFC-anchored networks across different cognitive constructs. Given the results with respect to the early-responding "energizing" network, WM deficits in schizophrenia may arise from disruption in the "energization" process described by Donald Stuss' model of pFC functions.
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Affiliation(s)
| | - Todd S Woodward
- University of British Columbia, Vancouver, Canada.,BC Mental Health and Substance Use Services Research Institute, Vancouver, Canada
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36
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Jiménez-Balado J, Eich TS. GABAergic dysfunction, neural network hyperactivity and memory impairments in human aging and Alzheimer's disease. Semin Cell Dev Biol 2021; 116:146-159. [PMID: 33573856 PMCID: PMC8292162 DOI: 10.1016/j.semcdb.2021.01.005] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 01/25/2021] [Accepted: 01/30/2021] [Indexed: 02/07/2023]
Abstract
In this review, we focus on the potential role of the γ-aminobutyric acidergic (GABAergic) system in age-related episodic memory impairments in humans, with a particular focus on Alzheimer's disease (AD). Well-established animal models have shown that GABA plays a central role in regulating and synchronizing neuronal signaling in the hippocampus, a brain area critical for episodic memory that undergoes early and significant morphologic and functional changes in the course of AD. Neuroimaging research in humans has documented hyperactivity in the hippocampus and losses of resting state functional connectivity in the Default Mode Network, a network that itself prominently includes the hippocampus-presaging episodic memory decline in individuals at-risk for AD. Apolipoprotein ε4, the highest genetic risk factor for AD, is associated with GABAergic dysfunction in animal models, and episodic memory impairments in humans. In combination, these findings suggest that GABA may be the linchpin in a complex system of factors that eventually leads to the principal clinical hallmark of AD: episodic memory loss. Here, we will review the current state of literature supporting this hypothesis. First, we will focus on the molecular and cellular basis of the GABAergic system and its role in memory and cognition. Next, we report the evidence of GABA dysregulations in AD and normal aging, both in animal models and human studies. Finally, we outline a model of GABAergic dysfunction based on the results of functional neuroimaging studies in humans, which have shown hippocampal hyperactivity to episodic memory tasks concurrent with and even preceding AD diagnosis, along with factors that may modulate this association.
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Affiliation(s)
- Joan Jiménez-Balado
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Teal S Eich
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA.
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37
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Investigating neurophysiological markers of impaired cognition in schizophrenia. Schizophr Res 2021; 233:34-43. [PMID: 34225025 DOI: 10.1016/j.schres.2021.06.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 04/21/2021] [Accepted: 06/21/2021] [Indexed: 01/22/2023]
Abstract
Cognitive impairment is highly prevalent in schizophrenia and treatment options are severely limited. A greater understanding of the pathophysiology of impaired cognition would have broad implications, including for the development of effective treatments. In the current study we used a multimodal approach to identify neurophysiological markers of cognitive impairment in schizophrenia. Fifty-seven participants (30 schizophrenia, 27 controls) underwent neurobiological assessment (electroencephalography [EEG] and Transcranial Magnetic Stimulation combined with EEG [TMS-EEG]) and assessment of cognitive functioning using an n-back task and the MATRICS Consensus Cognitive Battery. Neurobiological outcome measures included oscillatory power during a 2-back task, TMS-related oscillations and TMS-evoked potentials (TEPs). Cognitive outcome measures were d prime and accurate reaction time on the 2-back and MATRICS domain scores. Compared to healthy controls, participants with schizophrenia showed significantly reduced theta oscillations in response to TMS, and trend level decreases in task-related theta and cortical reactivity (i.e. reduced N100 and N40 TEPs). Participants with schizophrenia also showed significantly impaired cognitive performance across all measures. Correlational analysis identified significant associations between cortical reactivity and TMS-related oscillations in both groups; and trend level associations between task-related oscillations and impaired cognition in schizophrenia. The current study provides experimental support for possible neurophysiological markers of cognitive impairment in schizophrenia. The potential implications of these findings, including for treatment development, are discussed.
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38
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Umbricht D, Abt M, Tamburri P, Chatham C, Holiga Š, Frank MJ, Collins AG, Walling DP, Mofsen R, Gruener D, Gertsik L, Sevigny J, Keswani S, Dukart J. Proof-of-Mechanism Study of the Phosphodiesterase 10 Inhibitor RG7203 in Patients With Schizophrenia and Negative Symptoms. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 1:70-77. [PMID: 36324430 PMCID: PMC9616307 DOI: 10.1016/j.bpsgos.2021.03.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/16/2021] [Accepted: 03/05/2021] [Indexed: 12/27/2022] Open
Abstract
Background Reduced activation of dopamine D1 receptor signaling may be implicated in reward functioning as a potential driver of negative symptoms in schizophrenia. Phosphodiesterase 10A (PDE10A), an enzyme that is highly expressed in the striatum, modulates both dopamine D2- and D1-dependent signaling. Methods We assessed whether augmentation of D1 signaling by the PDE10 inhibitor RG7203 enhances imaging and behavioral markers of reward functions in patients with schizophrenia and negative symptoms. In a 3-period, double-blind, crossover study, we investigated the effects of RG7203 (5 mg and 15 mg doses) and placebo as adjunctive treatment to stable background antipsychotic treatment in patients with chronic schizophrenia with moderate levels of negative symptoms. Effects on reward functioning and reward-based effortful behavior were evaluated using the monetary incentive delay task during functional magnetic resonance imaging and the effort-cost-benefit and working memory reinforcement learning tasks. Results Patients (N = 33; 30 male, mean age ± SD 36.6 ± 7.0 years; Positive and Negative Syndrome Scale negative symptom factor score 23.0 ± 3.5 at screening) were assessed at three study centers in the United States; 24 patients completed the study. RG7203 at 5 mg significantly increased reward expectation–related activity in the monetary incentive delay task, but in the context of significantly decreased overall activity across all task conditions. Conclusions In contrast to our expectations, RG7203 significantly worsened reward-based effortful behavior and indices of reward learning. The results do not support the utility of RG7203 as adjunctive treatment for negative symptoms in patients with schizophrenia.
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Affiliation(s)
- Daniel Umbricht
- Roche Pharma and Early Development, Basel, Switzerland
- Address correspondence to Daniel Umbricht, M.D.
| | - Markus Abt
- Roche Pharma and Early Development, Basel, Switzerland
| | | | | | - Štefan Holiga
- Roche Pharma and Early Development, Basel, Switzerland
| | - Michael J. Frank
- Department of Cognitive, Linguistic & Psychological Sciences, Carney Institute for Brain Science, Brown University, Providence, Rhode Island
| | - Anne G.E. Collins
- Department of Psychology and Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California
| | - David P. Walling
- Collaborative Neuroscience Network, LLC, Garden Grove, California
| | - Rick Mofsen
- Translational Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Daniel Gruener
- Evolution Research Group, LLC, New Providence, New Jersey
| | - Lev Gertsik
- California Clinical Trials Medical Group, Glendale, California
| | | | | | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Medical Faculty, Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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Jahangir M, Zhou JS, Lang B, Wang XP. GABAergic System Dysfunction and Challenges in Schizophrenia Research. Front Cell Dev Biol 2021; 9:663854. [PMID: 34055795 PMCID: PMC8160111 DOI: 10.3389/fcell.2021.663854] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 04/06/2021] [Indexed: 12/13/2022] Open
Abstract
Despite strenuous studies since the last century, the precise cause and pathology of schizophrenia are still largely unclear and arguably controversial. Although many hypotheses have been proposed to explain the etiology of schizophrenia, the definitive genes or core pathological mechanism remains absent. Among these hypotheses, however, GABAergic dysfunction stands out as a common feature consistently reported in schizophrenia, albeit a satisfactory mechanism that could be exploited for therapeutic purpose has not been developed yet. This review is focusing on the progress made to date in the field in terms of understanding the mechanisms involving dysfunctional GABAergic system and loops identified in schizophrenia research.
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Affiliation(s)
- Muhammad Jahangir
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jian-Song Zhou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Bing Lang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- School of Medicine, Medical Sciences and Nutrition, Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Xiao-Ping Wang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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Sambataro F, Cattarinussi G, Lawrence A, Biaggi A, Fusté M, Hazelgrove K, Mehta MA, Pawlby S, Conroy S, Seneviratne G, Craig MC, Pariante CM, Miele M, Dazzan P. Altered dynamics of the prefrontal networks are associated with the risk for postpartum psychosis: a functional magnetic resonance imaging study. Transl Psychiatry 2021; 11:238. [PMID: 33976106 PMCID: PMC8113224 DOI: 10.1038/s41398-021-01351-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 02/15/2021] [Accepted: 03/02/2021] [Indexed: 11/23/2022] Open
Abstract
Postpartum psychosis (PP) is a severe mental disorder that affects women in the first few weeks after delivery. To date there are no biomarkers that distinguish which women at risk (AR) develop a significant psychiatric relapse postpartum. While altered brain connectivity may contribute to the risk for psychoses unrelated to the puerperium, this remains unexplored in PP. We followed up 32 AR and 27 healthy (HC) women from pregnancy to 8-week postpartum. At this point, we classified women as AR-unwell (n = 15) if they had developed a psychiatric relapse meeting DSM-IV diagnostic criteria, or impacting on daily functioning and requiring treatment, or AR-well (n = 17) if they remained asymptomatic. Women also underwent an fMRI scan at rest and during an emotional-processing task, to study within- and between-networks functional connectivity. Women AR, and specifically those in the AR-well group, showed increased resting connectivity within an executive network compared to HC. During the execution of the emotional task, women AR also showed decreased connectivity in the executive network, and altered emotional load-dependent connectivity between executive, salience, and default-mode networks. AR-unwell women particularly showed increased salience network-dependent modulation of the default-mode and executive network relative to AR-well, who showed greater executive network-dependent modulation of the salience network. Our finding that the executive network and its interplay with other brain networks implicated in goal-directed behavior are intrinsically altered suggest that they could be considered neural phenotypes for postpartum psychosis and help advance our understanding of the pathophysiology of this disorder.
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Affiliation(s)
- Fabio Sambataro
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy.
| | - Giulia Cattarinussi
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Andrew Lawrence
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Alessandra Biaggi
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Montserrat Fusté
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Katie Hazelgrove
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Mitul A Mehta
- National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Susan Pawlby
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Susan Conroy
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Gertrude Seneviratne
- South London and Maudsley NHS Foundation Trust Channi Kumar Mother and Baby Unit, Bethlem Royal Hospital, London, UK
| | - Michael C Craig
- National Female Hormone Clinic, Maudsley Hospital, SLaM NHS Foundation Trust, and Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, De Crespigny Park, London, UK
| | - Carmine M Pariante
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Maddalena Miele
- Perinatal Mental Health Service, St Mary's Hospital, Imperial College London and Central North West London NHS Foundation Trust, London, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
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41
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He X, Li X, Fu J, Xu J, Liu H, Zhang P, Li W, Yu C, Ye Z, Qin W. The morphometry of left cuneus mediating the genetic regulation on working memory. Hum Brain Mapp 2021; 42:3470-3480. [PMID: 33939221 PMCID: PMC8249898 DOI: 10.1002/hbm.25446] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/06/2021] [Indexed: 02/06/2023] Open
Abstract
Working memory is a basic human cognitive function. However, the genetic signatures and their biological pathway remain poorly understood. In the present study, we tried to clarify this issue by exploring the potential associations and pathways among genetic variants, brain morphometry and working memory performance. We first carried out association analyses between 2‐back accuracy and 212 image‐derived phenotypes from 1141 Human Connectome Project (HCP) subjects using a linear mixed model (LMM). We found a significantly positive correlation between the left cuneus volume and 2‐back accuracy (T = 3.615, p = 3.150e−4, Cohen's d = 0.226, corrected using family‐wise error [FWE] method). Based on the LMM‐based genome‐wide association study (GWAS) on the HCP dataset and UK Biobank 33 k GWAS summary statistics, we identified eight independent single nucleotide polymorphisms (SNPs) that were reliably associated with left cuneus volume in both UKB and HCP dataset. Within the eight SNPs, we found a negative correlation between the rs76119478 polymorphism and 2‐back accuracy accuracy (T = −2.045, p = .041, Cohen's d = −0.129). Finally, an LMM‐based mediation analysis elucidated a significant effect of left cuneus volume in mediating rs76119478 polymorphism on the 2‐back accuracy (indirect effect = −0.007, 95% BCa CI = [−0.045, −0.003]). These results were also replicated in a subgroup of Caucasians in the HCP population. Further fine mapping demonstrated that rs76119478 maps on intergene CTD‐2315A10.2 adjacent to protein‐encoding gene DAAM1, and is significantly associated with L3HYPDH mRNA expression. Our study suggested this new variant rs76119478 may regulate the working memory through exerting influence on the left cuneus volume.
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Affiliation(s)
- Xiaoxi He
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xi Li
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Peng Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Wei Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.,National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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42
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Chen C, Wang Z, Chen C, Xue G, Lu S, Liu H, Dong Q, Zhang M. CPNE3 moderates the association between anxiety and working memory. Sci Rep 2021; 11:6891. [PMID: 33767297 PMCID: PMC7994849 DOI: 10.1038/s41598-021-86263-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 03/08/2021] [Indexed: 11/09/2022] Open
Abstract
Mutual influences between anxiety and working memory (WM) have been extensively studied, and their curvilinear relationship resembles the classic Yerkes-Dodson law of arousal and performance. Given the genetic bases of both anxiety and WM, it is likely that the individual differences in the Yerkes-Dodson law of anxiety and WM may have genetic correlates. The current genome wide association study (GWAS) enrolled 1115 healthy subjects to search for genes that are potential moderators of the association between anxiety and WM. Results showed that CPNE3 rs10102229 had the strongest effect, p = 3.38E−6 at SNP level and p = 2.68E−06 at gene level. Anxiety and WM had a significant negative correlation (i.e., more anxious individuals performed worse on the WM tasks) for the TT genotype of rs10102229 (resulting in lower expression of CPNE3), whereas the correlation was positive (i.e., more anxious individuals performed better on the WM tasks) for the CC carriers. The same pattern of results was found at the gene level using gene score analysis. These effects were replicated in an independent sample (N = 330). The current study is the first to report a gene that moderates the relation between anxiety and WM and potentially provides a genetic explanation for the classic Yerkes-Dodson law.
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Affiliation(s)
- Chunhui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China. .,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
| | - Ziyi Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Chuansheng Chen
- Department of Psychological Science, University of California, Irvine, CA, USA
| | - Gui Xue
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Shuzhen Lu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Hejun Liu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingxia Zhang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.
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43
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Liu Y, Bi T, Zhang B, Kuang Q, Li H, Zong K, Zhao J, Ning Y, She S, Zheng Y. Face and object visual working memory deficits in first-episode schizophrenia correlate with multiple neurocognitive performances. Gen Psychiatr 2021; 34:e100338. [PMID: 33728399 PMCID: PMC7896562 DOI: 10.1136/gpsych-2020-100338] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 11/19/2020] [Accepted: 12/15/2020] [Indexed: 12/17/2022] Open
Abstract
Background Working memory (WM) deficit is considered a core feature and cognitive biomarker in patients with schizophrenia. Several studies have reported prominent object WM deficits in patients with schizophrenia, suggesting that visual WM in these patients extends to non-spatial domains. However, whether non-spatial WM is similarly affected remains unclear. Aim This study primarily aimed to identify the processing of visual object WM in patients with first-episode schizophrenia. Methods The study included 36 patients with first-episode schizophrenia and 35 healthy controls. Visual object WM capacity, including face and house WM capacity, was assessed by means of delayed matching-to-sample visual WM tasks, in which participants must distribute memory so that they can discriminate a target sample. We specifically examined their anhedonia experience by the Temporal Experience of Pleasure Scale and the Snaith-Hamilton Pleasure Scale. Cognitive performance was measured by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Results Both face and house WM capacity was significantly impaired in patients with schizophrenia. For both tasks, the performance of all the subjects was worse under the high-load condition than under the low-load condition. We found that WM capacity was highly positively correlated with the performance on RBANS total scores (r=−0.528, p=0.005), RBANS delayed memory scores (r=−0.470, p=0.013), RBANS attention scores (r=−0.584, p=0.001), RBANS language scores (r=−0.448, p=0.019), Trail-Making Test: Part A raw scores (r=0.465, p=0.015) and simple IQ total scores (r=−0.538, p=0.005), and correlated with scores of the vocabulary test (r=−0.490, p=0.011) and scores of the Block Diagram Test (r=−0.426, p=0.027) in schizophrenia. No significant correlations were observed between WM capacity and Positive and Negative Syndrome Scale symptoms. Conclusions Our research found that visual object WM capacity is dramatically impaired in patients with schizophrenia and is strongly correlated with other measures of cognition, suggesting a mechanism that is critical in explaining a portion of the broad cognitive deficits observed in schizophrenia.
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Affiliation(s)
- Yi Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Taiyong Bi
- Centre for Mental Health Research in School of Management, Zunyi Medical University, Zunyi, Guizhou, China
| | - Bei Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.,Department of Psychology, General and Experimental Psychology, LMU Munich, Germany
| | - Qijie Kuang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Haijing Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Kunlun Zong
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jingping Zhao
- Mental Health Institute of the Second Xiangya Hospital, Central South University; Chinese National Clinical Research Center on Mental Disorders; Chinese National Technology Institute on Mental Disorders; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China
| | - Yuping Ning
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Shenglin She
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yingjun Zheng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
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44
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Liu R, Wang Y, Chen X, Zhang Z, Xiao L, Zhou Y. Anhedonia correlates with functional connectivity of the nucleus accumbens subregions in patients with major depressive disorder. Neuroimage Clin 2021; 30:102599. [PMID: 33662708 PMCID: PMC7930634 DOI: 10.1016/j.nicl.2021.102599] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 02/10/2021] [Accepted: 02/11/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND The nucleus accumbens (NAc) is an important region in reward circuit that has been linked with anhedonia, which is a characteristic symptom of major depressive disorder (MDD). However, the relationship between the functional connectivity of the NAc subregions and anhedonia in MDD patients remains unclear. METHODS We acquired resting-state functional magnetic resonance imaging (fMRI) scans from fifty-one subjects (23 MDD patients and 28 healthy controls). We assessed subjects' trait anhedonia with the Temporal Experience of Pleasure Scale (TEPS). Seed-based resting-state functional connectivity (rsFC) was conducted for each of the NAc subregions (bilateral core-like and shell-like subdivisions) separately to identify regions whose rsFCs with the NAc subregions were altered in the MDD patients and regions whose rsFCs with the NAc subregions showed different correlates with anhedonia between the MDD patients and the healthy controls. RESULTS Compared with the health controls, the MDD patients showed decreased rsFCs of the right NAc core-like subdivision with the left mid-anterior orbital prefrontal cortex and the right inferior parietal lobe as well as decreased rsFC of the left NAc core-like subdivision with the right middle frontal gyrus. Moreover, the severity of anhedonia by the group interaction was significant for the rsFC of the right NAc shell-like subdivision with the subgenual/pregenual anterior cingulate cortex and the rsFC of the right NAc core-like subdivision with the precuneus. CONCLUSIONS We found that the neural correlates of anhedonia indicated by the rsFCs of the NAc subregions were modulated by depression. The modulation effect was regionally-dependent. These findings enrich our understanding of the neural basis of anhedonia in MDD.
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Affiliation(s)
- Rui Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Yun Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Xiongying Chen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Zhifang Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Le Xiao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Yuan Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China; CAS Key Laboratory of Behavioral Science, Institute of Psychology & Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
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45
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Kumar V, Nichenmetla S, Chhabra H, Sreeraj VS, Rao NP, Kesavan M, Varambally S, Venkatasubramanian G, Gangadhar BN. Prefrontal cortex activation during working memory task in schizophrenia: A fNIRS study. Asian J Psychiatr 2021; 56:102507. [PMID: 33388563 DOI: 10.1016/j.ajp.2020.102507] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 12/01/2020] [Accepted: 12/08/2020] [Indexed: 11/19/2022]
Abstract
Neurocognitive cognitive deficits including working memory (WM) impairment is a key component of schizophrenia (SCZ). Though a prefrontal cortex (PFC) abnormality is recognised to contribute to WM impairment, the exact nature of its neurobiological basis in SCZ is not well established. Functional near infra-red spectroscopy (fNIRS) is an emerging low-cost neuroimaging tool to study neuro-hemodynamics. In this background, we examined the hemodynamic activity during a WM task in schizophrenia using fNIRS. fNIRS was acquired during computerised N-back (zero-, one- & two-back) task in 15 SCZ patients and compared with 22 healthy controls. Performance in N-back test were calculated using signal detection theory alongside the mean reaction times. Concentration and latencies of oxy-, deoxy-, and totalhaemoglobin, and oxygen saturation were computed from 8*8 optodes positioned over bilateral PFC. SCZ performed poorly as measured by most of the WM parameters (p < 0.05). Lesser deoxyhemoglobin concentration (two > zero, at right BA10, p = 0.006) was noted in the right frontopolar cortex in SCZ surviving multiple-comparison correction. In addition, olanzapine equivalent doses correlated negatively with right frontopolar cortex activation (two > zero back, BA10, ρ = 0.70, p = 0.004) and better performance in two back (false alarm rate, ρ = 0.61, p = 0.015). A delayed but compensatory hyperactivation of right frontopolar cortex noted in SCZ may underlie the WM deficit in SCZ. Future studies are recommended to replicate the role of right frontopolar cortex in WM using larger samples and systematically explore the effect of antipsychotics on them.
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Affiliation(s)
- Vijay Kumar
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India.
| | - Sonika Nichenmetla
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
| | - Harleen Chhabra
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
| | - Vanteemar S Sreeraj
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
| | - Naren P Rao
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
| | - Muralidharan Kesavan
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
| | - Shivarama Varambally
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
| | - Ganesan Venkatasubramanian
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
| | - Bangalore N Gangadhar
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of mental health and neurosciences (NIMHANS), Bengaluru, India
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Curic S, Andreou C, Nolte G, Steinmann S, Thiebes S, Polomac N, Haaf M, Rauh J, Leicht G, Mulert C. Ketamine Alters Functional Gamma and Theta Resting-State Connectivity in Healthy Humans: Implications for Schizophrenia Treatment Targeting the Glutamate System. Front Psychiatry 2021; 12:671007. [PMID: 34177660 PMCID: PMC8222814 DOI: 10.3389/fpsyt.2021.671007] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 05/07/2021] [Indexed: 01/08/2023] Open
Abstract
Disturbed functional connectivity is assumed to cause neurocognitive deficits in patients suffering from schizophrenia. A Glutamate N-methyl-D-aspartate receptor (NMDAR) dysfunction has been suggested as a possible mechanism underlying altered connectivity in schizophrenia, especially in the gamma- and theta-frequency range. The present study aimed to investigate the effects of the NMDAR-antagonist ketamine on resting-state power, functional connectivity, and schizophrenia-like psychopathological changes in healthy volunteers. In a placebo-controlled crossover design, 25 healthy subjects were recorded using resting-state 64-channel-electroencephalography (EEG) (eyes closed). The imaginary coherence-based Multivariate Interaction Measure (MIM) was used to measure gamma and theta connectivity across 80 cortical regions. The network-based statistic was applied to identify involved networks under ketamine. Psychopathology was assessed with the Positive and Negative Syndrome Scale (PANSS) and the 5-Dimensional Altered States of Consciousness Rating Scale (5D-ASC). Ketamine caused an increase in all PANSS (p < 0.001) as well as 5D-ASC scores (p < 0.01). Significant increases in resting-state gamma and theta power were observed under ketamine compared to placebo (p < 0.05). The source-space analysis revealed two distinct networks with an increased mean functional gamma- or theta-band connectivity during the ketamine session. The gamma-network consisted of midline regions, the cuneus, the precuneus, and the bilateral posterior cingulate cortices, while the theta-band network involved the Heschl gyrus, midline regions, the insula, and the middle cingulate cortex. The current source density (CSD) within the gamma-band correlated negatively with the PANSS negative symptom score, and the activity within the gamma-band network correlated negatively with the subjective changed meaning of percepts subscale of the 5D-ASC. These results are in line with resting-state patterns seen in people who have schizophrenia and argue for a crucial role of the glutamate system in mediating dysfunctional gamma- and theta-band-connectivity in schizophrenia. Resting-state networks could serve as biomarkers for the response to glutamatergic drugs or drug development efforts within the glutamate system.
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Affiliation(s)
- Stjepan Curic
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Sex Research, Sexual Medicine and Forensic Psychiatry, Center of Psychosocial Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christina Andreou
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Translational Psychiatry Unit, Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Guido Nolte
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Saskia Steinmann
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stephanie Thiebes
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Nenad Polomac
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Moritz Haaf
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonas Rauh
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gregor Leicht
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christoph Mulert
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Centre for Psychiatry and Psychotherapy, Justus Liebig University, Giessen, Germany
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47
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Olaithe M, Ree M, McArdle N, Donaldson S, Pushpanathan M, Eastwood PR, Bucks RS. Cognitive Dysfunction in Insomnia Phenotypes: Further Evidence for Different Disorders. Front Psychiatry 2021; 12:688672. [PMID: 34349682 PMCID: PMC8326515 DOI: 10.3389/fpsyt.2021.688672] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 06/22/2021] [Indexed: 11/13/2022] Open
Abstract
Study Objectives: To determine cognitive profiles in individuals with short sleep duration insomnia (SSDI) and normal sleep duration insomnia (NSDI; also, paradoxical insomnia), compared to healthy sleepers. Method: Polysomnographic (PSG) and neuropsychological data were analysed from 902 community-based Raine Study participants aged 22 ± 0.6 years of whom 124 met criteria for insomnia (53 with NSDI and 71 with or SSDI) and 246 were classified as healthy with normal sleep (i.e., without insomnia or other sleep disorders). Measurements of self- report (attention and memory) and laboratory-assessed (attention, episodic memory, working memory, learning, and psychomotor function) cognition and mood, and PSG-based sleep stages (% total sleep time; %TST) were compared between these 3 groups. Results: In comparison to the healthy sleeper group, both insomnia groups had poorer self-reported attention, memory, mood, and sleep, and poorer laboratory-assessed attention (inconsistency). The NSDI group had less consistent working memory reaction time than healthy-sleepers or those with SSDI. The SSDI group had more inconsistency in executive function (shifting), and showed greater %TST in stage N1 and N3, and less REM sleep than either healthy-sleepers or those with NSDI. Conclusions: Individuals with NSDI demonstrated greater working memory inconsistency, despite no laboratory assessed sleep problems, implicating early signs of pathophysiology other than disturbed sleep. Those with SSDI demonstrated different sleep architecture, poorer attention (inconsistency), and greater executive function (inconsistency) compared to healthy-sleepers and those with NSDI, implicating sleep disturbance in the disease process of this phenotype.
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Affiliation(s)
- Michelle Olaithe
- School of Psychological Science, University of Western Australia, Perth, WA, Australia
| | - Melissa Ree
- School of Psychological Science, University of Western Australia, Perth, WA, Australia.,Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia
| | - Nigel McArdle
- Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia.,Department of Pulmonary Physiology and Sleep Medicine, West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Nedlands, WA, Australia
| | - Sara Donaldson
- School of Psychological Science, University of Western Australia, Perth, WA, Australia
| | - Maria Pushpanathan
- School of Psychological Science, University of Western Australia, Perth, WA, Australia
| | - Peter R Eastwood
- Centre for Sleep Science, School of Human Sciences, University of Western Australia, Perth, WA, Australia.,Department of Pulmonary Physiology and Sleep Medicine, West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital, Nedlands, WA, Australia.,College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Bedford Park, SA, Australia
| | - Romola S Bucks
- School of Psychological Science, University of Western Australia, Perth, WA, Australia.,School of Population and Global Health, University of Western Australia, Perth, WA, Australia
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48
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Zink CF, Barker PB, Sawa A, Weinberger DR, Wang M, Quillian H, Ulrich WS, Chen Q, Jaffe AE, Kleinman JE, Hyde TM, Prettyman GE, Giegerich M, Carta K, van Ginkel M, Bigos KL. Association of Missense Mutation in FOLH1 With Decreased NAAG Levels and Impaired Working Memory Circuitry and Cognition. Am J Psychiatry 2020; 177:1129-1139. [PMID: 33256444 DOI: 10.1176/appi.ajp.2020.19111152] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Altering the metabotropic glutamate receptor 3 (mGluR3) by pharmacology or genetics is associated with differences in learning and memory in animals and humans. GRM3 (the gene coding for mGluR3) is also genome-wide associated with risk for schizophrenia. The neurotransmitter N-acetyl-aspartyl-glutamate (NAAG) is the selective endogenous agonist of mGluR3, and increasing NAAG may improve cognition. Glutamate carboxypeptidase II (GCPII), coded by the gene folate hydrolase 1 (FOLH1), regulates the amount of NAAG in the synapse. The goal of this study was to determine the relationship between FOLH1, NAAG levels, measures of human cognition, and neural activity associated with cognition. METHODS The effects of genetic variation in FOLH1 on mRNA expression in human brain and NAAG levels using 7-T magnetic resonance spectroscopy (MRS) were measured. NAAG levels and FOLH1 genetic variation were correlated with measures of cognition in subjects with psychosis and unaffected subjects. Additionally, FOLH1 genetic variation was correlated with neural activity during working memory, as measured by functional MRI (fMRI). RESULTS A missense mutation in FOLH1 (rs202676 G allele) was associated with increased FOLH1 mRNA in the dorsolateral prefrontal cortex of brains from unaffected subjects and schizophrenia patients. This FOLH1 variant was associated with decreased NAAG levels in unaffected subjects and patients with psychosis. NAAG levels were positively correlated with visual memory performance. Carriers of the FOLH1 variant associated with lower NAAG levels had lower IQ scores. Carriers of this FOLH1 variant had less efficient cortical activity during working memory. CONCLUSIONS These data show that higher NAAG levels are associated with better cognition, suggesting that increasing NAAG levels through FOLH1/GCPII inhibition may improve cognition. Additionally, NAAG levels measured by MRS and cortical efficiency during working memory measured by fMRI have the potential to be neuroimaging biomarkers for future clinical trials.
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Affiliation(s)
- Caroline F Zink
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Peter B Barker
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Akira Sawa
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Daniel R Weinberger
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Min Wang
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Henry Quillian
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - William S Ulrich
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Qiang Chen
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Andrew E Jaffe
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Joel E Kleinman
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Thomas M Hyde
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Greer E Prettyman
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Mellissa Giegerich
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Kayla Carta
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Marcus van Ginkel
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
| | - Kristin L Bigos
- Baltimore Research and Education Foundation, Baltimore (Zink); Lieber Institute for Brain Development, Baltimore (Zink, Weinberger, Quillian, Ulrich, Chen, Jaffe, Kleinman, Hyde, Prettyman, Giegerich, Carta, van Ginkel, Bigos); Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore (Zink, Sawa, Weinberger, Jaffe, Kleinman, Hyde, Bigos); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine, Baltimore (Barker, Wang); Department of Oncology, Johns Hopkins School of Medicine, Baltimore (Barker); Kennedy Krieger Institute, Baltimore (Barker); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Sawa, Jaffe); Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger); McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Sawa, Weinberger, Jaffe); Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore (Sawa); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Weinberger, Hyde); Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Center for Computational Biology, Johns Hopkins University, Baltimore (Jaffe); Department of Neuroscience, University of Pennsylvania, Philadelphia (Prettyman); Eating Disorders Center for Treatment and Research, University of California San Diego (Giegerich); Department of Medicine, Division of Clinical Pharmacology, Johns Hopkins School of Medicine, Baltimore (Carta, van Ginkel, Bigos); and Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore (Bigos)
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Coffman BA, Murphy TK, Haas G, Olson C, Cho R, Ghuman AS, Salisbury DF. Lateralized evoked responses in parietal cortex demonstrate visual short-term memory deficits in first-episode schizophrenia. J Psychiatr Res 2020; 130:292-299. [PMID: 32866678 PMCID: PMC7554220 DOI: 10.1016/j.jpsychires.2020.07.036] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 07/25/2020] [Accepted: 07/25/2020] [Indexed: 11/19/2022]
Abstract
Working memory dysfunction may be central to neurocognitive deficits in schizophrenia. Maintenance of visual information in working memory, or visual short-term memory (vSTM), is linked to general cognitive dysfunction and predicts functional outcome. Lateralized change-detection tasks afford investigation of the contralateral delay activity (CDA), a useful tool for investigating vSTM dysfunction. Previous work suggests "hyperfocusing" of attention in schizophrenia, such that CDA is increased when a single item is maintained in vSTM but reduced for multiple items. If observed early in the disease, vSTM dysfunction may be a key feature of schizophrenia or target for intervention. We investigated CDA during lateralized vSTM of one versus three items using sensor-level electroencephalography and source-level magnetoencephalography in 26 individuals at their first episode of schizophrenia-spectrum psychosis (FESz) and 26 matched healthy controls. FESz were unable to modulate CDA with increased memory load - high-load CDA was reduced and low-load CDA was increased compared to controls. Further, sources of CDA in posterior parietal cortex were reduced in FESz and indices of working memory were correlated with neurocognitive deficits and symptom severity. These results support working memory maintenance dysfunction as a central and early component to the disorder. Targeted intervention focusing on vSTM deficits may be warranted to alleviate downstream effects of this disability.
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Affiliation(s)
- Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital of UPMC, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Tim K Murphy
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital of UPMC, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Gretchen Haas
- Western Psychiatric Hospital of UPMC, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Carl Olson
- Center for Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Raymond Cho
- Western Psychiatric Hospital of UPMC, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; Michael E. DeBakey Houston VA Medical Center, Houston, TX, USA
| | - Avniel Singh Ghuman
- Laboratory of Cognitive Neurodynamics, Department of Neurosurgery, Presbyterian Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital of UPMC, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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50
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Zhang X, Liu W, Guo F, Li C, Wang X, Wang H, Yin H, Zhu Y. Disrupted structural covariance network in first episode schizophrenia patients: Evidence from a large sample MRI-based morphometric study. Schizophr Res 2020; 224:24-32. [PMID: 33203611 DOI: 10.1016/j.schres.2020.11.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 09/30/2020] [Accepted: 11/02/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Recent progress in neuroscience research has provided evidence that schizophrenia is a disease that involves dysconnectivity of brain networks. Widespread gray matter loss was commonly observed but how these gray matter abnormalities are characterized at the large-scale network-level in schizophrenia, especially patients with first-episode (FE-SCZ) remains unclear. METHODS In this study, gray matter structural network aberrations were investigated by applying structural covariance network analysis to 193 first episode schizophrenia patients and 178 age and gender-matched healthy controls (HCs). The mean gray matter volume in seed regions relating to eight specific networks (visual, auditory, sensorimotor, speech, semantic, default-mode, executive control, and salience) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain gray matter volume and each seed region for FE-SCZ and HCs. RESULTS The auditory network was less extended in FE-SCZ compared with HCs, with a significant decrease in the structural association between the Hesch's gyrus and the middle frontal gyrus and the superior frontal gyrus. Hyperconnectivity was observed in executive control network with a significant increase in the structural association between the dorsal lateral prefrontal cortex and the superior frontal gyrus and supplementary motor area. CONCLUSION Our research shows that seed based structural covariance analysis can well characterize multiple large-scale networks, the observed changes might underly the hallucinations and cognitive impairments observed in FE-SCZ. Given that these patients were experiencing their first episode of schizophrenia, our findings suggest that such structural network deficits are present at an early stage in this disorder.
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Affiliation(s)
- Xiao Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Wenming Liu
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Xingrui Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
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