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Jäger AP, Bailey A, Huntenburg JM, Tardif CL, Villringer A, Gauthier CJ, Nikulin V, Bazin P, Steele CJ. Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training. Hum Brain Mapp 2024; 45:e26539. [PMID: 38124341 PMCID: PMC10915743 DOI: 10.1002/hbm.26539] [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: 05/10/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023] Open
Abstract
Decreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity.
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Affiliation(s)
- Anna‐Thekla P. Jäger
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Center for Stroke Research Berlin (CSB)Charité—Universitätsmedizin BerlinBerlinGermany
- Brain Language LabFreie Universität BerlinBerlinGermany
| | - Alexander Bailey
- Temerty Faculty of MedicineUniversity of TorontoTorontoOntarioCanada
| | - Julia M. Huntenburg
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Max Planck Institute for Biological CyberneticsTuebingenGermany
| | - Christine L. Tardif
- Department of Biomedical EngineeringMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMontrealQuébecCanada
| | - Arno Villringer
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Center for Stroke Research Berlin (CSB)Charité—Universitätsmedizin BerlinBerlinGermany
- Clinic for Cognitive NeurologyLeipzigGermany
- Leipzig University Medical Centre, IFB Adiposity DiseasesLeipzigGermany
- Collaborative Research Centre 1052‐A5University of LeipzigLeipzigGermany
| | - Claudine J. Gauthier
- Department of Physics/School of HealthConcordia UniversityMontrealQuébecCanada
- Montreal Heart InstituteMontrealQuébecCanada
| | - Vadim Nikulin
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Pierre‐Louis Bazin
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Faculty of Social and Behavioral SciencesUniversity of AmsterdamAmsterdamNetherlands
| | - Christopher J. Steele
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Department of Psychology/School of HealthConcordia UniversityMontrealQuébecCanada
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2
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Aberizk K, Sefik E, Addington J, Anticevic A, Bearden CE, Cadenhead KS, Cannon TD, Cornblatt BA, Keshavan M, Mathalon DH, Perkins DO, Stone WS, Tsuang MT, Woods SW, Walker EF. Hippocampal Connectivity with the Default Mode Network is Linked to Hippocampal Volume in the Clinical High Risk for Psychosis Syndrome and Healthy Individuals. Clin Psychol Sci 2023; 11:801-818. [PMID: 37981950 PMCID: PMC10656030 DOI: 10.1177/21677026221138819] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
Reduced hippocampal volume (HV) is an established brain morphological feature of psychiatric conditions. HV is associated with brain connectivity in humans and non-human animals and altered connectivity is associated with risk for psychiatric illness. Associations between HV and connectivity remain poorly characterized in humans, and especially in phases of psychiatric illness that precede disease onset. This study examined associations between HV and hippocampal functional connectivity (FC) during rest in 141 healthy controls and 248 individuals at-risk for psychosis. Significant inverse associations between HV and hippocampal FC with the inferior parietal lobe (IPL) and thalamus were observed. Select associations between hippocampal FC and HV were moderated by diagnostic group. Significant moderation results shifted from implicating the IPL to the temporal pole after excluding participants on antipsychotic medication. Considered together, this work implicates hippocampal FC with the temporoparietal junction, within a specialized subsystem of the default mode network, as sensitive to HV.
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Affiliation(s)
- Katrina Aberizk
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Esra Sefik
- Department of Psychology, Emory University, Atlanta, GA, USA
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Alan Anticevic
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Carrie E. Bearden
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California, Los Angeles, CA, USA
| | | | | | | | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School, Harvard University, Cambridge, MA, USA
| | - Daniel H. Mathalon
- Department of Psychiatry, University of California, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Diana O. Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Harvard University, Cambridge, MA, USA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Scott W. Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
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3
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Gao W, Biswal B, Yang J, Li S, Wang Y, Chen S, Yuan J. Temporal dynamic patterns of the ventromedial prefrontal cortex underlie the association between rumination and depression. Cereb Cortex 2023; 33:969-982. [PMID: 35462398 DOI: 10.1093/cercor/bhac115] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 11/14/2022] Open
Abstract
As a major contributor to the development of depression, rumination has proven linked with aberrant default-mode network (DMN) activity. However, it remains unclear how the spontaneous spatial and temporal activity of DMN underlie the association between rumination and depression. To illustrate this issue, behavioral measures and resting-state functional magnetic resonance images were connected in 2 independent samples (NSample1 = 100, NSample2 = 95). Fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) were used to assess spatial characteristic patterns, while voxel-wise functional concordance (across time windows) (VC) and Hurst exponent (HE) were used to assess temporal dynamic patterns of brain activity. Results from both samples consistently show that temporal dynamics but not spatial patterns of DMN are associated with rumination. Specifically, rumination is positively correlated with HE and VC (but not fALFF and ReHo) values, reflecting more consistent and regular temporal dynamic patterns in DMN. Moreover, subregion analyses indicate that temporal dynamics of the ventromedial prefrontal cortex (VMPFC) reliably predict rumination scores. Furthermore, mediation analyses show that HE and VC of VMPFC mediate the association between rumination and depression. These findings shed light on neural mechanisms of individual differences in rumination and corresponding risk for depression.
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Affiliation(s)
- Wei Gao
- Institute of Brain and Psychological Science, Sichuan Normal University, Chengdu, Sichuan, China.,Faculty of Psychology, Southwest University, Chongqing, China
| | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Jiemin Yang
- Institute of Brain and Psychological Science, Sichuan Normal University, Chengdu, Sichuan, China
| | - Songlin Li
- School of Educational Science, Sichuan Normal University, Chengdu, Sichuan, China
| | - YanQing Wang
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Shengdong Chen
- School of Psychology, Qufu Normal University, Qufu, Shandong, China
| | - JiaJin Yuan
- Institute of Brain and Psychological Science, Sichuan Normal University, Chengdu, Sichuan, China
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4
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Long Z, Li J, Liao H, Deng L, Du Y, Fan J, Li X, Miao J, Qiu S, Long C, Jing B. A Multi-Modal and Multi-Atlas Integrated Framework for Identification of Mild Cognitive Impairment. Brain Sci 2022; 12:751. [PMID: 35741636 PMCID: PMC9221217 DOI: 10.3390/brainsci12060751] [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: 04/09/2022] [Revised: 05/29/2022] [Accepted: 06/03/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Multi-modal neuroimaging with appropriate atlas is vital for effectively differentiating mild cognitive impairment (MCI) from healthy controls (HC). METHODS The resting-state functional magnetic resonance imaging (rs-fMRI) and structural MRI (sMRI) of 69 MCI patients and 61 HC subjects were collected. Then, the gray matter volumes obtained from the sMRI and Hurst exponent (HE) values calculated from rs-fMRI data in the Automated Anatomical Labeling (AAL-90), Brainnetome (BN-246), Harvard-Oxford (HOA-112) and AAL3-170 atlases were extracted, respectively. Next, these characteristics were selected with a minimal redundancy maximal relevance algorithm and a sequential feature collection method in single or multi-modalities, and only the optimal features were retained after this procedure. Lastly, the retained characteristics were served as the input features for the support vector machine (SVM)-based method to classify MCI patients, and the performance was estimated with a leave-one-out cross-validation (LOOCV). RESULTS Our proposed method obtained the best 92.00% accuracy, 94.92% specificity and 89.39% sensitivity with the sMRI in AAL-90 and the fMRI in HOA-112 atlas, which was much better than using the single-modal or single-atlas features. CONCLUSION The results demonstrated that the multi-modal and multi-atlas integrated method could effectively recognize MCI patients, which could be extended into various neurological and neuropsychiatric diseases.
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Affiliation(s)
- Zhuqing Long
- Medical Apparatus and Equipment Deployment, Hunan Children’s Hospital, Changsha 410007, China; (Z.L.); (J.L.); (H.L.); (Y.D.); (S.Q.)
- School of Biomedical Engineering, Capital Medical University, Beijing 100069, China
| | - Jie Li
- Medical Apparatus and Equipment Deployment, Hunan Children’s Hospital, Changsha 410007, China; (Z.L.); (J.L.); (H.L.); (Y.D.); (S.Q.)
| | - Haitao Liao
- Medical Apparatus and Equipment Deployment, Hunan Children’s Hospital, Changsha 410007, China; (Z.L.); (J.L.); (H.L.); (Y.D.); (S.Q.)
| | - Li Deng
- Department of Data Assessment and Examination, Hunan Children’s Hospital, Changsha 410007, China;
| | - Yukeng Du
- Medical Apparatus and Equipment Deployment, Hunan Children’s Hospital, Changsha 410007, China; (Z.L.); (J.L.); (H.L.); (Y.D.); (S.Q.)
| | - Jianghua Fan
- Department of Pediatric Emergency Center, Emergency Generally Department I, Hunan Children’s Hospital, Changsha 410007, China;
| | - Xiaofeng Li
- Hunan Guangxiu Hospital, Hunan Normal University, Changsha 410006, China;
| | - Jichang Miao
- Department of Medical Devices, Nanfang Hospital, Guangzhou 510515, China;
| | - Shuang Qiu
- Medical Apparatus and Equipment Deployment, Hunan Children’s Hospital, Changsha 410007, China; (Z.L.); (J.L.); (H.L.); (Y.D.); (S.Q.)
| | - Chaojie Long
- Medical Apparatus and Equipment Deployment, Hunan Children’s Hospital, Changsha 410007, China; (Z.L.); (J.L.); (H.L.); (Y.D.); (S.Q.)
| | - Bin Jing
- School of Biomedical Engineering, Capital Medical University, Beijing 100069, China
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5
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Deng S, Franklin CG, O'Boyle M, Zhang W, Heyl BL, Jerabek PA, Lu H, Fox PT. Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults. Neuroimage 2022; 250:118923. [PMID: 35066157 PMCID: PMC9201851 DOI: 10.1016/j.neuroimage.2022.118923] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 01/07/2022] [Accepted: 01/11/2022] [Indexed: 12/18/2022] Open
Abstract
Voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF), fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity (ReHo). Although these BOLD-derived variables can detect between-group (e.g. disease vs control) spatial pattern differences, physiological interpretations are not well established. The primary objective of this study was to quantify spatial correspondences between BOLD VBP variables and PET measurements of cerebral metabolic rate and hemodynamics, being well-validated physiological standards. To this end, quantitative, whole-brain PET images of metabolic rate of glucose (MRGlu; 18FDG) and oxygen (MRO2; 15OO), blood flow (BF; H215O) and blood volume (BV; C15O) were obtained in 16 healthy controls. In the same subjects, BOLD time-courses were obtained for computation of ALFF, fALFF and ReHo images. PET variables were compared pair-wise with BOLD variables. In group-averaged, across-region analyses, ALFF corresponded significantly only with BV (R = 0.64; p < 0.0001). fALFF corresponded most strongly with MRGlu (R = 0.79; p < 0.0001), but also significantly (p < 0.0001) with MRO2 (R = 0.68), BF (R = 0.68) and BV (R=0.68). ReHo performed similarly to fALFF, with significant strong correspondence (p < 0.0001) with MRGlu (R = 0.78), MRO2 (R = 0.54), and, but less strongly with BF (R = 0.50) and BV (R=0.50). Mutual information analyses further clarified these physiological interpretations. When conditioned by BV, ALFF retained no significant MRGlu, MRO2 or BF information. When conditioned by MRGlu, fALFF and ReHo retained no significant MRO2, BF or BV information. Of concern, however, the strength of PET-BOLD correspondences varied markedly by brain region, which calls for future investigation on physiological interpretations at a regional and per-subject basis.
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Affiliation(s)
- Shengwen Deng
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Crystal G Franklin
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
| | - Michael O'Boyle
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
| | - Wei Zhang
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
| | - Betty L Heyl
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
| | - Paul A Jerabek
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; South Texas Veterans Health Care System, San Antonio, TX, USA.
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6
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Campbell OL, Weber AM. Monofractal analysis of functional magnetic resonance imaging: An introductory review. Hum Brain Mapp 2022; 43:2693-2706. [PMID: 35266236 PMCID: PMC9057087 DOI: 10.1002/hbm.25801] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 01/24/2022] [Accepted: 01/26/2022] [Indexed: 11/11/2022] Open
Abstract
The following review will aid readers in providing an overview of scale-free dynamics and monofractal analysis, as well as its applications and potential in functional magnetic resonance imaging (fMRI) neuroscience and clinical research. Like natural phenomena such as the growth of a tree or crashing ocean waves, the brain expresses scale-invariant, or fractal, patterns in neural signals that can be measured. While neural phenomena may represent both monofractal and multifractal processes and can be quantified with many different interrelated parameters, this review will focus on monofractal analysis using the Hurst exponent (H). Monofractal analysis of fMRI data is an advanced analysis technique that measures the complexity of brain signaling by quantifying its degree of scale-invariance. As such, the H value of the blood oxygenation level-dependent (BOLD) signal specifies how the degree of correlation in the signal may mediate brain functions. This review presents a brief overview of the theory of fMRI monofractal analysis followed by notable findings in the field. Through highlighting the advantages and challenges of the technique, the article provides insight into how to best conduct fMRI fractal analysis and properly interpret the findings with physiological relevance. Furthermore, we identify the future directions necessary for its progression towards impactful functional neuroscience discoveries and widespread clinical use. Ultimately, this presenting review aims to build a foundation of knowledge among readers to facilitate greater understanding, discussion, and use of this unique yet powerful imaging analysis technique.
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Affiliation(s)
- Olivia Lauren Campbell
- School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexander Mark Weber
- School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Neurology, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Neuroscience, University of British Columbia, Vancouver, British Columbia, Canada.,BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
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7
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Campbell O, Vanderwal T, Weber AM. Fractal-Based Analysis of fMRI BOLD Signal During Naturalistic Viewing Conditions. Front Physiol 2022; 12:809943. [PMID: 35087421 PMCID: PMC8787275 DOI: 10.3389/fphys.2021.809943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 12/14/2021] [Indexed: 01/04/2023] Open
Abstract
Background: Temporal fractals are characterized by prominent scale-invariance and self-similarity across time scales. Monofractal analysis quantifies this scaling behavior in a single parameter, the Hurst exponent (H). Higher H reflects greater correlation in the signal structure, which is taken as being more fractal. Previous fMRI studies have observed lower H during conventional tasks relative to resting state conditions, and shown that H is negatively correlated with task difficulty and novelty. To date, no study has investigated the fractal dynamics of BOLD signal during naturalistic conditions. Methods: We performed fractal analysis on Human Connectome Project 7T fMRI data (n = 72, 41 females, mean age 29.46 ± 3.76 years) to compare H across movie-watching and rest. Results: In contrast to previous work using conventional tasks, we found higher H values for movie relative to rest (mean difference = 0.014; p = 5.279 × 10-7; 95% CI [0.009, 0.019]). H was significantly higher in movie than rest in the visual, somatomotor and dorsal attention networks, but was significantly lower during movie in the frontoparietal and default networks. We found no cross-condition differences in test-retest reliability of H. Finally, we found that H of movie-derived stimulus properties (e.g., luminance changes) were fractal whereas H of head motion estimates were non-fractal. Conclusions: Overall, our findings suggest that movie-watching induces fractal signal dynamics. In line with recent work characterizing connectivity-based brain state dynamics during movie-watching, we speculate that these fractal dynamics reflect the configuring and reconfiguring of brain states that occurs during naturalistic processing, and are markedly different than dynamics observed during conventional tasks.
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Affiliation(s)
- Olivia Campbell
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Tamara Vanderwal
- British Columbia (BC) Children's Hospital Research Institute, UBC, Vancouver, BC, Canada.,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Alexander Mark Weber
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.,British Columbia (BC) Children's Hospital Research Institute, UBC, Vancouver, BC, Canada.,Division of Neurology, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada.,Department of Neuroscience, University of British Columbia, Vancouver, BC, Canada
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8
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Orso B, Arnaldi D, Peira E, Famá F, Giorgetti L, Girtler N, Brugnolo A, Mattioli P, Biassoni E, Donniaquio A, Massa F, Bauckneht M, Miceli A, Morbelli S, Nobili F, Pardini M. The Role of Monoaminergic Tones and Brain Metabolism in Cognition in De Novo Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:1945-1955. [PMID: 35811536 DOI: 10.3233/jpd-223308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
BACKGROUND Cognitive impairment is frequent in Parkinson's disease (PD) and several neurotransmitter changes have been reported since the time of diagnosis, although seldom investigated altogether in the same patient cohort. OBJECTIVE Our aim was to evaluate the association between neurotransmitter impairment, brain metabolism, and cognition in a cohort of de novo, drug-naïve PD patients. METHODS We retrospectively selected 95 consecutive drug-naïve PD patients (mean age 71.89±7.53) undergoing at the time of diagnosis a brain [18F]FDG-PET as a marker of brain glucose metabolism and proxy measure of neurodegeneration, [123I]FP-CIT-SPECT as a marker and dopaminergic deafferentation in the striatum and frontal cortex, as well as a marker of serotonergic deafferentation in the thalamus, and quantitative electroencephalography (qEEG) as an indirect measure of cholinergic deafferentation. Patients also underwent a complete neuropsychological battery. RESULTS Positive correlations were observed between (i) executive functions and left cerebellar cortex metabolism, (ii) prefrontal dopaminergic tone and working memory (r = 0.304, p = 0.003), (iii) qEEG slowing in the posterior leads and both memory (r = 0.299, p = 0.004) and visuo-spatial functions (r = 0.357, p < 0.001). CONCLUSIONS In subjects with PD, the impact of regional metabolism and diffuse projection systems degeneration differs across cognitive domains. These findings suggest possible tailored approaches to the treatment of cognitive deficits in PD.
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Affiliation(s)
- Beatrice Orso
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Dario Arnaldi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | - Enrico Peira
- Istituto nazionale di Fisica Nucleare (IN FN), Genoa section, Genoa, Italy
| | - Francesco Famá
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | | | - Nicola Girtler
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | - Andrea Brugnolo
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | - Pietro Mattioli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Erica Biassoni
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Andrea Donniaquio
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Federico Massa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Matteo Bauckneht
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
- Department of Health Science (DISSAL), University of Genoa, Genoa, Italy
| | - Alberto Miceli
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
- Department of Health Science (DISSAL), University of Genoa, Genoa, Italy
| | - Silvia Morbelli
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
- Department of Health Science (DISSAL), University of Genoa, Genoa, Italy
| | - Flavio Nobili
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
| | - Matteo Pardini
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico S. Martino, Genoa, Italy
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9
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Effect of education on functional network edge efficiency in Alzheimer's disease. Sci Rep 2021; 11:17255. [PMID: 34446742 PMCID: PMC8390462 DOI: 10.1038/s41598-021-96361-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 07/29/2021] [Indexed: 11/24/2022] Open
Abstract
We investigated the effect of education on the edge efficiency in resting state functional networks (RSFNs) in amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease dementia (ADD). We collected the data of 57 early aMCI, 141 late aMCI, 173 mild ADD, and 39 moderate-to-severe ADD patients. We used years of education as a proxy for cognitive reserve. We measured edge efficiency for each edge in RSFNs, and performed simple slope analyses to discover their associations with education level among the four groups. In the late aMCI, a sub-network that had hub nodes in the right middle frontal gyrus and the right posterior cingulate gyrus, showed a positive association between RSFN edge efficiency and education (threshold = 2.5, p = 0.0478). There was no negative effect of education on the RSFN edge efficiency. In the early aMCI, mild ADD, and moderate-to-severe ADD, there were no sub-networks showing positive or negative correlation between education and RSFN edge efficiency. There was a positive effect of higher education on RSFN edge efficiency in the late aMCI, but not in the early aMCI or ADD. This indicates that in late aMCI, those who have higher education level have greater ability to resist collapsed functional network.
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10
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Incidence of the "Adrenaline Rush" and Vasovagal Response with Local Anesthetic Injection. PLASTIC AND RECONSTRUCTIVE SURGERY-GLOBAL OPEN 2021; 9:e3659. [PMID: 34178562 PMCID: PMC8225362 DOI: 10.1097/gox.0000000000003659] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 05/05/2021] [Indexed: 11/26/2022]
Abstract
Background Many patients feel an "adrenaline rush" or a vasovagal reaction when injected with lidocaine and epinephrine during wide awake surgery. The incidence of these reactions is not well documented in the literature. Methods In total, 387 patients were prospectively injected with lidocaine and epinephrine for minor procedures without sedation between July 1, 2019 and November 1, 2020. A concentration of epinephrine with 1:100,000 in 2% lidocaine was injected, with most patients getting less than 20 mL of volume. Results Eight (2.2%) of the patients had adrenaline rush symptoms, which included nervousness, anxiety, tremors, shaky feelings, flushing, diaphoresis, light-headedness, tingling, and "heart racing." Seven patients (1.8%) experienced vasovagal responses, which included nausea, a feeling of being unwell, faint, or lightheaded, or had circumoral pallor. Conclusions Patients run a low risk of feeling an adrenaline rush or vasovagal reaction when injected with lidocaine and epinephrine. Routinely advising patients that the adrenaline rush can happen, and that this is not an allergic reaction can be helpful to allay fear of the unknown and to prevent false allergy beliefs. Injecting patients lying down may decrease the incidence of vasovagal reactions by increasing cerebral blood flow with the advantage of gravity.
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11
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Pharmaco-fUS: Quantification of pharmacologically-induced dynamic changes in brain perfusion and connectivity by functional ultrasound imaging in awake mice. Neuroimage 2020; 222:117231. [DOI: 10.1016/j.neuroimage.2020.117231] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 07/24/2020] [Accepted: 07/31/2020] [Indexed: 11/20/2022] Open
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12
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Dhamala E, Jamison KW, Sabuncu MR, Kuceyeski A. Sex classification using long-range temporal dependence of resting-state functional MRI time series. Hum Brain Mapp 2020; 41:3567-3579. [PMID: 32627300 PMCID: PMC7416025 DOI: 10.1002/hbm.25030] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 04/27/2020] [Indexed: 12/13/2022] Open
Abstract
A thorough understanding of sex differences that exist in the brains of healthy individuals is crucial for the study of neurological illnesses that exhibit phenotypic differences between males and females. Here we evaluate sex differences in regional temporal dependence of resting-state brain activity in 195 adult male-female pairs strictly matched for total grey matter volume from the Human Connectome Project. We find that males have more persistent temporal dependence in regions within temporal, parietal, and occipital cortices. Machine learning algorithms trained on regional temporal dependence measures achieve sex classification accuracies up to 81%. Regions with the strongest feature importance in the sex classification task included cerebellum, amygdala, and frontal and occipital cortices. Secondarily, we show that even after strict matching of total gray matter volume, significant volumetric sex differences persist; males have larger absolute cerebella, hippocampi, parahippocampi, thalami, caudates, and amygdalae while females have larger absolute cingulates, precunei, and frontal and parietal cortices. Sex classification based on regional volume achieves accuracies up to 85%, highlighting the importance of strict volume-matching when studying brain-based sex differences. Differential patterns in regional temporal dependence between the sexes identifies a potential neurobiological substrate or environmental effect underlying sex differences in functional brain activation patterns.
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Affiliation(s)
- Elvisha Dhamala
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
- Brain and Mind Research InstituteWeill Cornell MedicineNew YorkNew YorkUSA
| | - Keith W. Jamison
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Mert R. Sabuncu
- School of Electrical and Computer EngineeringCornell UniversityIthacaNew YorkUSA
- Meinig School of Biomedical EngineeringCornell UniversityIthacaNew YorkUSA
| | - Amy Kuceyeski
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
- Brain and Mind Research InstituteWeill Cornell MedicineNew YorkNew YorkUSA
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13
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Anatomical and neurochemical bases of theory of mind in de novo Parkinson's Disease. Cortex 2020; 130:401-412. [DOI: 10.1016/j.cortex.2020.06.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 06/15/2020] [Accepted: 06/29/2020] [Indexed: 11/19/2022]
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14
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Zimmern V. Why Brain Criticality Is Clinically Relevant: A Scoping Review. Front Neural Circuits 2020; 14:54. [PMID: 32982698 PMCID: PMC7479292 DOI: 10.3389/fncir.2020.00054] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 07/23/2020] [Indexed: 12/13/2022] Open
Abstract
The past 25 years have seen a strong increase in the number of publications related to criticality in different areas of neuroscience. The potential of criticality to explain various brain properties, including optimal information processing, has made it an increasingly exciting area of investigation for neuroscientists. Recent reviews on this topic, sometimes termed brain criticality, make brief mention of clinical applications of these findings to several neurological disorders such as epilepsy, neurodegenerative disease, and neonatal hypoxia. Other clinicallyrelevant domains - including anesthesia, sleep medicine, developmental-behavioral pediatrics, and psychiatry - are seldom discussed in review papers of brain criticality. Thorough assessments of these application areas and their relevance for clinicians have also yet to be published. In this scoping review, studies of brain criticality involving human data of all ages are evaluated for their current and future clinical relevance. To make the results of these studies understandable to a more clinical audience, a review of the key concepts behind criticality (e.g., phase transitions, long-range temporal correlation, self-organized criticality, power laws, branching processes) precedes the discussion of human clinical studies. Open questions and forthcoming areas of investigation are also considered.
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Affiliation(s)
- Vincent Zimmern
- Division of Child Neurology, The University of Texas Southwestern Medical Center, Dallas, TX, United States
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15
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Neufang S, Akhrif A. Regional Hurst Exponent Reflects Impulsivity-Related Alterations in Fronto-Hippocampal Pathways Within the Waiting Impulsivity Network. Front Physiol 2020; 11:827. [PMID: 32765298 PMCID: PMC7381286 DOI: 10.3389/fphys.2020.00827] [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: 03/14/2020] [Accepted: 06/22/2020] [Indexed: 12/01/2022] Open
Abstract
In general, the Hurst exponent. is used as a measure of long-term memory of time series. In previous neuroimaging studies, H has been introduced as one important parameter to define resting-state networks, reflecting upon global scale-free properties emerging from a network. H has been examined in the waiting impulsivity (WI) network in an earlier study. We found that alterations of H in the anterior cingulate cortex (HACC) and the nucleus accumbens (HNAcc) were lower in high impulsive (highIMP) compared to low impulsive (lowIMP) participants. Following up on those findings, we addressed the relation between altered fractality in HACC and HNAcc and brain activation and neural network connectivity. To do so, brain activation maps were calculated, and network connectivity was determined using the Dynamic Causal Modeling (DCM) approach. Finally, 1–H scores were determined to quantify the alterations of H. This way, the focus of the analyses was placed on the potential effects of alterations of H on neural network activation and connectivity. Correlation analyses between the alterations of HACC/HNAcc and activation maps and DCM estimates were performed. We found that the alterations of H predominantly correlated with fronto-hippocampal pathways and correlations were significant only in highIMP subjects. For example, alterations of HACC was associated with a decrease in neural activation in the right HC in combination with increased ACC-hippocampal connectivity. Alteration inHNAcc, in return, was related to an increase in bilateral prefrontal activation in combination with increased fronto-hippocampal connectivity. The findings, that the WI network was related to H alteration in highIMP subjects indicated that impulse control was not reduced per se but lacked consistency. Additionally, H has been used to describe long-term memory processes before, e.g., in capital markets, energy future prices, and human memory. Thus, current findings supported the relation of H toward memory processing even when further prominent cognitive functions were involved.
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Affiliation(s)
- Susanne Neufang
- Department of Psychiatry and Psychotherapy, Medical Faculty Heinrich-Heine University, Düsseldorf, Germany.,Comparative Psychology, Institute of Experimental Psychology, Heinrich-Heine University, Düsseldorf, Germany
| | - Atae Akhrif
- Comparative Psychology, Institute of Experimental Psychology, Heinrich-Heine University, Düsseldorf, Germany.,Center of Mental Health, Department of Child and Adolescent Psychiatry, University of Würzburg, Würzburg, Germany
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16
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Trakoshis S, Martínez-Cañada P, Rocchi F, Canella C, You W, Chakrabarti B, Ruigrok ANV, Bullmore ET, Suckling J, Markicevic M, Zerbi V, Baron-Cohen S, Gozzi A, Lai MC, Panzeri S, Lombardo MV. Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women. eLife 2020; 9:e55684. [PMID: 32746967 PMCID: PMC7402681 DOI: 10.7554/elife.55684] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Accepted: 06/29/2020] [Indexed: 12/22/2022] Open
Abstract
Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.
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Affiliation(s)
- Stavros Trakoshis
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
- Department of Psychology, University of CyprusNicosiaCyprus
| | - Pablo Martínez-Cañada
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
- Optical Approaches to Brain Function Laboratory, Department of Neuroscience and Brain Technologies, Istituto Italiano di TecnologiaGenovaItaly
| | - Federico Rocchi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Carola Canella
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Wonsang You
- Artificial Intelligence and Image Processing Laboratory, Department of Information and Communications Engineering, Sun Moon UniversityAsanRepublic of Korea
| | - Bhismadev Chakrabarti
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of ReadingReadingUnited Kingdom
| | - Amber NV Ruigrok
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Edward T Bullmore
- Cambridgeshire and Peterborough National Health Service Foundation TrustCambridgeUnited Kingdom
- Brain Mapping Unit, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Marija Markicevic
- Neural Control of Movement Lab, D-HEST, ETH ZurichZurichSwitzerland
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, D-HEST, ETH ZurichZurichSwitzerland
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
| | | | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
- Cambridgeshire and Peterborough National Health Service Foundation TrustCambridgeUnited Kingdom
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Meng-Chuan Lai
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
- The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health, Azrieli Adult Neurodevelopmental Centre, and Campbell Family Mental Health Research Institute, Centre for Addiction and Mental HealthTorontoCanada
- Department of Psychiatry and Autism Research Unit, The Hospital for Sick ChildrenTorontoCanada
- Department of Psychiatry, Faculty of Medicine, University of TorontoTorontoCanada
- Department of Psychiatry, National Taiwan University Hospital and College of MedicineTaipeiTaiwan
| | - Stefano Panzeri
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di TecnologiaRoveretoItaly
- Autism Research Centre, Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
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17
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You do not have to act to be impulsive: Brain resting-state activity predicts performance and impulsivity on the Balloon Analogue Risk Task. Behav Brain Res 2020; 379:112395. [DOI: 10.1016/j.bbr.2019.112395] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 10/19/2019] [Accepted: 11/27/2019] [Indexed: 01/08/2023]
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18
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Vingerhoets C, Bakker G, Schrantee A, van der Pluijm M, Bloemen OJN, Reneman L, Caan M, Booij J, van Amelsvoort TAMJ. Influence of muscarinic M 1 receptor antagonism on brain choline levels and functional connectivity in medication-free subjects with psychosis: A placebo controlled, cross-over study. Psychiatry Res Neuroimaging 2019; 290:5-13. [PMID: 31252222 DOI: 10.1016/j.pscychresns.2019.06.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 06/21/2019] [Accepted: 06/22/2019] [Indexed: 01/18/2023]
Abstract
An increasing number of studies implicate the muscarinic cholinergic system in cognitive dysfunction associated with psychosis. This study examined the effect of muscarinic M1 receptor modulation on anterior cingulate cortex (ACC) and striatal choline concentrations and the relation with cognitive performance, as well as functional connectivity of cognitive networks. Thirty medication-free subjects with a psychosis spectrum disorder and 30 gender, age and IQ-matched healthy control subjects underwent 1H-proton magnetic resonance spectroscopy (1H-MRS) twice, once after placebo and once after a single dose of biperiden (M1 receptor antagonist, 4 mg). A subset of 19 psychotic subjects and 28 controls underwent resting-state functional magnetic resonance imaging (rs-fMRI) as well. No significant differences were found in ACC and striatal choline levels, nor in functional connectivity, between the two groups after placebo. Moreover, M1 antagonism did not significantly affect choline levels or functional connectivity. No correlations were found between choline levels and cognition as well as psychotic symptoms. Our findings do not support an association between the cholinergic system and cognition and psychotic symptoms. However, the lack of group differences in choline concentrations and functional connectivity, both after biperiden and placebo, may indicate that there were no severe cholinergic abnormalities present in our sample.
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Affiliation(s)
- Claudia Vingerhoets
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam University medical center, location Academic Medical Center, Amsterdam, the Netherlands.
| | - Geor Bakker
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam University medical center, location Academic Medical Center, Amsterdam, the Netherlands; Development and Experimental Medicine, Sosei-Heptaris, Cambridge, United Kingdom
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University medical center, location Academic Medical Center, Amsterdam, the Netherlands; Spinoza Centre for Neuroimaging, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, the Netherlands
| | - Marieke van der Pluijm
- Department of Radiology and Nuclear Medicine, Amsterdam University medical center, location Academic Medical Center, Amsterdam, the Netherlands
| | - Oswald J N Bloemen
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands; GGZ Centraal, Center for Mental Health Care Innova, Amersfoort, the Netherlands
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam University medical center, location Academic Medical Center, Amsterdam, the Netherlands
| | - Matthan Caan
- Department of Radiology and Nuclear Medicine, Amsterdam University medical center, location Academic Medical Center, Amsterdam, the Netherlands; Department of Biomedical Engineering, Amsterdam University Medical Center, location AMC, Amsterdam, the Netherlands
| | - Jan Booij
- Department of Radiology and Nuclear Medicine, Amsterdam University medical center, location Academic Medical Center, Amsterdam, the Netherlands
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19
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Gao W, Chen S, Biswal B, Lei X, Yuan J. Temporal dynamics of spontaneous default-mode network activity mediate the association between reappraisal and depression. Soc Cogn Affect Neurosci 2019; 13:1235-1247. [PMID: 30339260 PMCID: PMC6277739 DOI: 10.1093/scan/nsy092] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 10/12/2018] [Indexed: 12/24/2022] Open
Abstract
Cognitive reappraisal is associated with major depressive disorder (MDD), while spontaneous activity patterns of the default mode network (DMN) is implicated in reappraisal and MDD. However, neural mechanisms subserving the close association of spontaneous reappraisal and depression are unclear. Spontaneous reappraisal, depression and resting-state functional magnetic resonance imaging (rsfMRI) were measured from 105 healthy subjects. We assessed the temporal complexity (Hurst exponent), Regional Homogeneity (ReHo) and fractional Amplitude of Low Frequency Fluctuation (fALFF) profiles of DMN, a network involved in both reappraisal and depression. Mediation effects of these standard measures on the relationship between reappraisal and depression, and the contributions of each DMN subregion, were assessed. Results indicated that Hurst exponent (H) of DMN, whether extracted by independent component analysis (ICA) or region of interest (ROI), was significantly associated with reappraisal scores. An individual with a higher reappraisal score has a lower Hurst value of DMN. Mediation analyses suggest that H of DMN partially mediates the association between reappraisal and the degree of depression, and this mediation effect arises from the contribution of medial prefrontal cortex. Neither ReHo nor fALFF showed a similar correlation or mediation effect. These findings suggest that temporal dynamics of DMN play an important role in emotion regulation and its association with depression. H of DMN may serve as a neural marker mediating the association between reappraisal and depression.
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Affiliation(s)
- Wei Gao
- The Laboratory for Affect Cognition and Regulation (ACRLAB), Key Laboratory of Cognition and Personality of Ministry of Education (SWU), Faculty of Psychology, Southwest University, Chongqing, China
| | - ShengDong Chen
- The Laboratory for Affect Cognition and Regulation (ACRLAB), Key Laboratory of Cognition and Personality of Ministry of Education (SWU), Faculty of Psychology, Southwest University, Chongqing, China
| | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Xu Lei
- Sleep and Neuroimaging Center, Faculty of Psychology, Southwest University, Chongqing, China
| | - JiaJin Yuan
- The Laboratory for Affect Cognition and Regulation (ACRLAB), Key Laboratory of Cognition and Personality of Ministry of Education (SWU), Faculty of Psychology, Southwest University, Chongqing, China
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20
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Jia H, Li Y, Yu D. Attenuation of long-range temporal correlations of neuronal oscillations in young children with autism spectrum disorder. NEUROIMAGE-CLINICAL 2018; 20:424-432. [PMID: 30128281 PMCID: PMC6095951 DOI: 10.1016/j.nicl.2018.08.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 07/12/2018] [Accepted: 08/08/2018] [Indexed: 11/26/2022]
Abstract
Although autism spectrum disorder (ASD) was previously found to be associated with aberrant brain structure, neuronal amplitudes and spatial neuronal interactions, surprisingly little is known about the temporal dynamics of neuronal oscillations in this disease. Here, the hemoglobin concentration signals (i.e., oxy-Hb and deoxy-Hb) of young children with ASD and typically developing (TD) children were recorded via functional near infrared spectroscopy (fNIRS) when they were watching a cartoon. The long-range temporal correlations (LRTCs) of hemoglobin concentration signals were quantified using detrended fluctuation analysis (DFA). Compared with TD group, the DFA exponents of young children with ASD were significantly smaller over left temporal region for oxy-Hb signal, and over bilateral temporo-occipital regions for deoxy-Hb signals, indicating a shift-to-randomness of brain oscillations in the children with ASD. Testing the relationship between age and DFA exponents revealed that this association could be modulated by autism. The correlation coefficients between age and DFA exponents were significantly more positive in TD group, compared to those in ASD group over several brain regions. Furthermore, the DFA exponents of oxy-Hb in left temporal region were negatively correlated with autistic symptom severity. These results suggest that the decreased DFA exponent of hemoglobin concentration signals may be one of the pathologic changes in ASD, and studying the temporal structure of brain activity via fNIRS technique may provide physiological indicators for autism. The LRTCs of fNIRS signals are attenuated in young children with ASD. Opposite relationships between age and LRTCs of fNIRS signals are revealed in young children with ASD and TD. The LRTCs of oxy-Hb in left temporal region are negatively correlated with autistic symptom severity.
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Affiliation(s)
- Huibin Jia
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, Jiangsu, China
| | - Yanwei Li
- College of Preschool Education, Nanjing Xiaozhuang University, Nanjing, Jiangsu, China
| | - Dongchuan Yu
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, Jiangsu, China.
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21
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Muthukumaraswamy SD, Liley DT. 1/f electrophysiological spectra in resting and drug-induced states can be explained by the dynamics of multiple oscillatory relaxation processes. Neuroimage 2018; 179:582-595. [PMID: 29959047 DOI: 10.1016/j.neuroimage.2018.06.068] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 06/20/2018] [Accepted: 06/25/2018] [Indexed: 02/01/2023] Open
Abstract
Neurophysiological recordings are dominated by arhythmical activity whose spectra can be characterised by power-law functions, and on this basis are often referred to as reflecting scale-free brain dynamics (1/fβ). Relatively little is known regarding the neural generators and temporal dynamics of this arhythmical behaviour compared to rhythmical behaviour. Here we used Irregularly Resampled AutoSpectral Analysis (IRASA) to quantify β, in both the high (5-100 Hz, βhf) and low frequency bands (0.1-2.5 Hz, βlf) in MEG/EEG/ECoG recordings and to separate arhythmical from rhythmical modes of activity, such as, alpha rhythms. In MEG/EEG/ECoG data, we demonstrate that oscillatory alpha power dynamically correlates over time with βhf and similarly, participants with higher rhythmical alpha power have higher βhf. In a series of pharmaco-MEG investigations using the GABA reuptake inhibitor tiagabine, the glutamatergic AMPA receptor antagonist perampanel, the NMDA receptor antagonist ketamine and the mixed partial serotonergic agonist LSD, a variety of effects on both βhf and βlf were observed. Additionally, strong modulations of βhf were seen in monkey ECoG data during general anaesthesia using propofol and ketamine. We develop and test a unifying model which can explain, the 1/f nature of electrophysiological spectra, their dynamic interaction with oscillatory rhythms as well as the sensitivity of 1/f activity to drug interventions by considering electrophysiological spectra as being generated by a collection of stochastically perturbed damped oscillators having a distribution of relaxation rates.
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Affiliation(s)
- Suresh D Muthukumaraswamy
- School of Pharmacy and Centre for Brain Research, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.
| | - David Tj Liley
- Centre for Human Psychopharmacology, School of Health Sciences, Swinburne University of Technology, Melbourne, Australia
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22
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Li X, Li Q, Wang X, Li D, Li S. Differential Age-Related Changes in Structural Covariance Networks of Human Anterior and Posterior Hippocampus. Front Physiol 2018; 9:518. [PMID: 29867561 PMCID: PMC5954440 DOI: 10.3389/fphys.2018.00518] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 04/20/2018] [Indexed: 11/13/2022] Open
Abstract
The hippocampus plays an important role in memory function relying on information interaction between distributed brain areas. The hippocampus can be divided into the anterior and posterior sections with different structure and function along its long axis. The aim of this study is to investigate the effects of normal aging on the structural covariance of the anterior hippocampus (aHPC) and the posterior hippocampus (pHPC). In this study, 240 healthy subjects aged 18-89 years were selected and subdivided into young (18-23 years), middle-aged (30-58 years), and older (61-89 years) groups. The aHPC and pHPC was divided based on the location of uncal apex in the MNI space. Then, the structural covariance networks were constructed by examining their covariance in gray matter volumes with other brain regions. Finally, the influence of age on the structural covariance of these hippocampal sections was explored. We found that the aHPC and pHPC had different structural covariance patterns, but both of them were associated with the medial temporal lobe and insula. Moreover, both increased and decreased covariances were found with the aHPC but only increased covariance was found with the pHPC with age (p < 0.05, family-wise error corrected). These decreased connections occurred within the default mode network, while the increased connectivity mainly occurred in other memory systems that differ from the hippocampus. This study reveals different age-related influence on the structural networks of the aHPC and pHPC, providing an essential insight into the mechanisms of the hippocampus in normal aging.
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Affiliation(s)
- Xinwei Li
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China
| | - Qiongling Li
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China
| | - Xuetong Wang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China
| | - Deyu Li
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China
| | - Shuyu Li
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China
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23
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Long Z, Jing B, Guo R, Li B, Cui F, Wang T, Chen H. A Brainnetome Atlas Based Mild Cognitive Impairment Identification Using Hurst Exponent. Front Aging Neurosci 2018; 10:103. [PMID: 29692721 PMCID: PMC5902491 DOI: 10.3389/fnagi.2018.00103] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 03/27/2018] [Indexed: 11/15/2022] Open
Abstract
Mild cognitive impairment (MCI), which generally represents the transition state between normal aging and the early changes related to Alzheimer’s disease (AD), has drawn increasing attention from neuroscientists due that efficient AD treatments need early initiation ahead of irreversible brain tissue damage. Thus effective MCI identification methods are desperately needed, which may be of great importance for the clinical intervention of AD. In this article, the range scaled analysis, which could effectively detect the temporal complexity of a time series, was utilized to calculate the Hurst exponent (HE) of functional magnetic resonance imaging (fMRI) data at a voxel level from 64 MCI patients and 60 healthy controls (HCs). Then the average HE values of each region of interest (ROI) in brainnetome atlas were extracted and compared between MCI and HC. At last, the abnormal average HE values were adopted as the classification features for a proposed support vector machine (SVM) based identification algorithm, and the classification performance was estimated with leave-one-out cross-validation (LOOCV). Our results indicated 83.1% accuracy, 82.8% sensitivity and 83.3% specificity, and an area under curve of 0.88, suggesting that the HE index could serve as an effective feature for the MCI identification. Furthermore, the abnormal HE brain regions in MCI were predominately involved in left middle frontal gyrus, right hippocampus, bilateral parahippocampal gyrus, bilateral amygdala, left cingulate gyrus, left insular gyrus, left fusiform gyrus, left superior parietal gyrus, left orbital gyrus and left basal ganglia.
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Affiliation(s)
- Zhuqing Long
- Medical Apparatus and Equipment Deployment, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Bin Jing
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Ru Guo
- Department of Tuberculosis, Beijing Chest Hospital Capital Medical University, Beijing, China
| | - Bo Li
- Department of Traditional Chinese Medicine, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Feiyi Cui
- Medical Apparatus and Equipment Deployment, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Tingting Wang
- Medical Apparatus and Equipment Deployment, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Hongwen Chen
- Medical Apparatus and Equipment Deployment, Nanfang Hospital, Southern Medical University, Guangzhou, China
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Liu X, Lin X, Zheng M, Hu Y, Wang Y, Wang L, Du X, Dong G. Internet Search Alters Intra- and Inter-regional Synchronization in the Temporal Gyrus. Front Psychol 2018; 9:260. [PMID: 29559939 PMCID: PMC5845706 DOI: 10.3389/fpsyg.2018.00260] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 02/16/2018] [Indexed: 12/19/2022] Open
Abstract
Internet search changed the way we store and recall information and possibly altered our brain functions. Previous studies suggested that Internet search facilitates the information-acquisition process. However, this process may cause individuals to lose the ability to store and recollect specific contents. Despite the numerous behavioral studies conducted in this field, little is known about the neural mechanisms underlying Internet searches. The present study explores potential brain activity changes induced by Internet search. The whole paradigm includes three phases, namely, pre-resting state fMRI (rs-fMRI) scan, 6-day Internet search training, and post rs-fMRI scan. We detected the functional integrations induced by Internet search training by comparing post- with pre-scan. Regional homogeneity (ReHo) and functional connectivity (FC) were used to detect intra- and interregional synchronized activity in 42 university students. Compared with pre-scan, post-scan showed decreased ReHo in the temporal gyrus, the middle frontal gyrus, and the postcentral gyrus. Further seed-based FC analysis showed that the temporal gyrus exhibited decreased FC in the parahippocampal cortex and the temporal gyrus after training. Based on the features of current task and functions exhibited by these brain regions, results indicate that short-term Internet search training changed the brain regional activities involved in memory retrieval. In general, this study provides evidence that supports the idea that Internet search can affect our brain functions.
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Affiliation(s)
- Xiaoyue Liu
- Department of Psychology, Zhejiang Normal University, Jinhua, China
| | - Xiao Lin
- Center for Life Sciences, Peking University, Beijing, China
| | - Ming Zheng
- Department of Psychology, Zhejiang Normal University, Jinhua, China
| | - Yanbo Hu
- Department of Psychology, London Metropolitan University, London, United Kingdom
| | - Yifan Wang
- Department of Psychology, Zhejiang Normal University, Jinhua, China
| | - Lingxiao Wang
- Department of Psychology, Zhejiang Normal University, Jinhua, China
| | - Xiaoxia Du
- Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Guangheng Dong
- Department of Psychology, Zhejiang Normal University, Jinhua, China.,Institute of Psychological and Brain Sciences, Zhejiang Normal University, Jinhua, China
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Dong J, Jing B, Ma X, Liu H, Mo X, Li H. Hurst Exponent Analysis of Resting-State fMRI Signal Complexity across the Adult Lifespan. Front Neurosci 2018; 12:34. [PMID: 29456489 PMCID: PMC5801317 DOI: 10.3389/fnins.2018.00034] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 01/15/2018] [Indexed: 01/16/2023] Open
Abstract
Exploring functional information among various brain regions across time enables understanding of healthy aging process and holds great promise for age-related brain disease diagnosis. This paper proposed a method to explore fractal complexity of the resting-state functional magnetic resonance imaging (rs-fMRI) signal in the human brain across the adult lifespan using Hurst exponent (HE). We took advantage of the examined rs-fMRI data from 116 adults 19 to 85 years of age (44.3 ± 19.4 years, 49 females) from NKI/Rockland sample. Region-wise and voxel-wise analyses were performed to investigate the effects of age, gender, and their interaction on complexity. In region-wise analysis, we found that the healthy aging is accompanied by a loss of complexity in frontal and parietal lobe and increased complexity in insula, limbic, and temporal lobe. Meanwhile, differences in HE between genders were found to be significant in parietal lobe (p = 0.04, corrected). However, there was no interaction between gender and age. In voxel-wise analysis, the significant complexity decrease with aging was found in frontal and parietal lobe, and complexity increase was found in insula, limbic lobe, occipital lobe, and temporal lobe with aging. Meanwhile, differences in HE between genders were found to be significant in frontal, parietal, and limbic lobe. Furthermore, we found age and sex interaction in right parahippocampal gyrus (p = 0.04, corrected). Our findings reveal HE variations of the rs-fMRI signal across the human adult lifespan and show that HE may serve as a new parameter to assess healthy aging process.
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Affiliation(s)
- Jianxin Dong
- School of Biomedical Engineering, Capital Medical University, Beijing, China
- Yanjing Medical College, Capital Medical University, Beijing, China
| | - Bin Jing
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Xiangyu Ma
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Han Liu
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Xiao Mo
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Haiyun Li
- School of Biomedical Engineering, Capital Medical University, Beijing, China
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26
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Yousaf T, Dervenoulas G, Politis M. Advances in MRI Methodology. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2018; 141:31-76. [DOI: 10.1016/bs.irn.2018.08.008] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Identifying current and remitted major depressive disorder with the Hurst exponent: a comparative study on two automated anatomical labeling atlases. Oncotarget 2017; 8:90452-90464. [PMID: 29163844 PMCID: PMC5685765 DOI: 10.18632/oncotarget.19860] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2017] [Accepted: 07/17/2017] [Indexed: 11/25/2022] Open
Abstract
Major depressive disorder (MDD) is a leading world-wide psychiatric disorder with high recurrence rate, therefore, it is desirable to identify current MDD (cMDD) and remitted MDD (rMDD) for their appropriate therapeutic interventions. In the study, 19 cMDD, 19 rMDD and 19 well-matched healthy controls (HC) were enrolled and scanned with the resting-state functional magnetic resonance imaging (rs-fMRI). The Hurst exponent (HE) of rs-fMRI in AAL-90 and AAL-1024 atlases were calculated and compared between groups. Then, a radial basis function (RBF) based support vector machine was proposed to identify every pair of the cMDD, rMDD and HC groups using the abnormal HE features, and a leave-one-out cross-validation was used to evaluate the classification performance. Applying the proposed method with AAL-1024 and AAL-90 atlas respectively, 87% and 84% subjects were correctly identified between cMDD and HC, 84% and 71% between rMDD and HC, and 89% and 74% between cMDD and rMDD. Our results indicated that the HE was an effective feature to distinguish cMDD and rMDD from HC, and the recognition performances with AAL-1024 parcellation were better than that with the conventional AAL-90 parcellation.
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28
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Gu S, Yang M, Medaglia JD, Gur RC, Gur RE, Satterthwaite TD, Bassett DS. Functional hypergraph uncovers novel covariant structures over neurodevelopment. Hum Brain Mapp 2017; 38:3823-3835. [PMID: 28493536 PMCID: PMC6323637 DOI: 10.1002/hbm.23631] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 04/02/2017] [Accepted: 04/20/2017] [Indexed: 02/01/2023] Open
Abstract
Brain development during adolescence is marked by substantial changes in brain structure and function, leading to a stable network topology in adulthood. However, most prior work has examined the data through the lens of brain areas connected to one another in large-scale functional networks. Here, we apply a recently developed hypergraph approach that treats network connections (edges) rather than brain regions as the unit of interest, allowing us to describe functional network topology from a fundamentally different perspective. Capitalizing on a sample of 780 youth imaged as part of the Philadelphia Neurodevelopmental Cohort, this hypergraph representation of resting-state functional MRI data reveals three distinct classes of subnetworks (hyperedges): clusters, bridges, and stars, which respectively represent homogeneously connected, bipartite, and focal architectures. Cluster hyperedges show a strong resemblance to previously-described functional modules of the brain including somatomotor, visual, default mode, and salience systems. In contrast, star hyperedges represent highly localized subnetworks centered on a small set of regions, and are distributed across the entire cortex. Finally, bridge hyperedges link clusters and stars in a core-periphery organization. Notably, developmental changes within hyperedges are ordered in a similar core-periphery fashion, with the greatest developmental effects occurring in networked hyperedges within the functional core. Taken together, these results reveal a novel decomposition of the network organization of human brain, and further provide a new perspective on the role of local structures that emerge across neurodevelopment. Hum Brain Mapp 38:3823-3835, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Shi Gu
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of Electrical and Systems EngineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Muzhi Yang
- Applied Mathematics and Computational Science Graduate GroupUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | | | - Ruben C. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Raquel E. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | | | - Danielle S. Bassett
- Department of Electrical and Systems EngineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvania
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29
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Telesford QK, Ashourvan A, Wymbs NF, Grafton ST, Vettel JM, Bassett DS. Cohesive network reconfiguration accompanies extended training. Hum Brain Mapp 2017. [PMID: 28646563 PMCID: PMC5554863 DOI: 10.1002/hbm.23699] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Human behavior is supported by flexible neurophysiological processes that enable the fine‐scale manipulation of information across distributed neural circuits. Yet, approaches for understanding the dynamics of these circuit interactions have been limited. One promising avenue for quantifying and describing these dynamics lies in multilayer network models. Here, networks are composed of nodes (which represent brain regions) and time‐dependent edges (which represent statistical similarities in activity time series). We use this approach to examine functional connectivity measured by non‐invasive neuroimaging techniques. These multilayer network models facilitate the examination of changes in the pattern of statistical interactions between large‐scale brain regions that might facilitate behavior. In this study, we define and exercise two novel measures of network reconfiguration, and demonstrate their utility in neuroimaging data acquired as healthy adult human subjects learn a new motor skill. In particular, we identify putative functional modules in multilayer networks and characterize the degree to which nodes switch between modules. Next, we define cohesive switches, in which a set of nodes moves between modules together as a group, and we define disjoint switches, in which a single node moves between modules independently from other nodes. Together, these two concepts offer complementary yet distinct insights into the changes in functional connectivity that accompany motor learning. More generally, our work offers statistical tools that other researchers can use to better understand the reconfiguration patterns of functional connectivity over time. Hum Brain Mapp 38:4744–4759, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Qawi K Telesford
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, 19104.,Human Research and Engineering Directorate, U.S. Army Research Laboratory, Aberdeen, Maryland, 21001
| | - Arian Ashourvan
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, 19104.,Human Research and Engineering Directorate, U.S. Army Research Laboratory, Aberdeen, Maryland, 21001
| | - Nicholas F Wymbs
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21218
| | - Scott T Grafton
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, California, 93106
| | - Jean M Vettel
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, 19104.,Human Research and Engineering Directorate, U.S. Army Research Laboratory, Aberdeen, Maryland, 21001.,Department of Psychological and Brain Sciences, University of California, Santa Barbara, California, 93106
| | - Danielle S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, 19104.,Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, 19104
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30
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Zhang Z, Telesford QK, Giusti C, Lim KO, Bassett DS. Choosing Wavelet Methods, Filters, and Lengths for Functional Brain Network Construction. PLoS One 2016; 11:e0157243. [PMID: 27355202 PMCID: PMC4927172 DOI: 10.1371/journal.pone.0157243] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Accepted: 05/26/2016] [Indexed: 11/19/2022] Open
Abstract
Wavelet methods are widely used to decompose fMRI, EEG, or MEG signals into time series representing neurophysiological activity in fixed frequency bands. Using these time series, one can estimate frequency-band specific functional connectivity between sensors or regions of interest, and thereby construct functional brain networks that can be examined from a graph theoretic perspective. Despite their common use, however, practical guidelines for the choice of wavelet method, filter, and length have remained largely undelineated. Here, we explicitly explore the effects of wavelet method (MODWT vs. DWT), wavelet filter (Daubechies Extremal Phase, Daubechies Least Asymmetric, and Coiflet families), and wavelet length (2 to 24)—each essential parameters in wavelet-based methods—on the estimated values of graph metrics and in their sensitivity to alterations in psychiatric disease. We observe that the MODWT method produces less variable estimates than the DWT method. We also observe that the length of the wavelet filter chosen has a greater impact on the estimated values of graph metrics than the type of wavelet chosen. Furthermore, wavelet length impacts the sensitivity of the method to detect differences between health and disease and tunes classification accuracy. Collectively, our results suggest that the choice of wavelet method and length significantly alters the reliability and sensitivity of these methods in estimating values of metrics drawn from graph theory. They furthermore demonstrate the importance of reporting the choices utilized in neuroimaging studies and support the utility of exploring wavelet parameters to maximize classification accuracy in the development of biomarkers of psychiatric disease and neurological disorders.
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Affiliation(s)
- Zitong Zhang
- Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Qawi K. Telesford
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Chad Giusti
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Warren Center for Network and Data Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Kelvin O. Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55455, United States of America
| | - Danielle S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- * E-mail:
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31
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Tromp D, Dufour A, Lithfous S, Pebayle T, Després O. Episodic memory in normal aging and Alzheimer disease: Insights from imaging and behavioral studies. Ageing Res Rev 2015; 24:232-62. [PMID: 26318058 DOI: 10.1016/j.arr.2015.08.006] [Citation(s) in RCA: 201] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2015] [Accepted: 08/20/2015] [Indexed: 12/30/2022]
Abstract
Age-related cognitive changes often include difficulties in retrieving memories, particularly those that rely on personal experiences within their temporal and spatial contexts (i.e., episodic memories). This decline may vary depending on the studied phase (i.e., encoding, storage or retrieval), according to inter-individual differences, and whether we are talking about normal or pathological (e.g., Alzheimer disease; AD) aging. Such cognitive changes are associated with different structural and functional alterations in the human neural network that underpins episodic memory. The prefrontal cortex is the first structure to be affected by age, followed by the medial temporal lobe (MTL), the parietal cortex and the cerebellum. In AD, however, the modifications occur mainly in the MTL (hippocampus and adjacent structures) before spreading to the neocortex. In this review, we will present results that attempt to characterize normal and pathological cognitive aging at multiple levels by integrating structural, behavioral, inter-individual and neuroimaging measures of episodic memory.
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Affiliation(s)
- D Tromp
- Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA - UMR 7364 - CNRS/UDS) - 21 rue Becquerel, 67087 Strasbourg, France.
| | - A Dufour
- Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA - UMR 7364 - CNRS/UDS) - 21 rue Becquerel, 67087 Strasbourg, France; Centre d'Investigations Neurocognitives et Neurophysiologiques (CI2N - UMS 3489 - CNRS/UDS) - 21 rue Becquerel, 67087 Strasbourg, France
| | - S Lithfous
- Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA - UMR 7364 - CNRS/UDS) - 21 rue Becquerel, 67087 Strasbourg, France
| | - T Pebayle
- Centre d'Investigations Neurocognitives et Neurophysiologiques (CI2N - UMS 3489 - CNRS/UDS) - 21 rue Becquerel, 67087 Strasbourg, France
| | - O Després
- Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA - UMR 7364 - CNRS/UDS) - 21 rue Becquerel, 67087 Strasbourg, France.
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Scopolamine effects on functional brain connectivity: a pharmacological model of Alzheimer's disease. Sci Rep 2015; 5:9748. [PMID: 26130273 PMCID: PMC4486953 DOI: 10.1038/srep09748] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2014] [Accepted: 03/10/2015] [Indexed: 11/17/2022] Open
Abstract
Scopolamine administration may be considered as a psychopharmacological model of Alzheimer’s disease (AD). Here, we studied a group of healthy elderly under scopolamine to test whether it elicits similar changes in brain connectivity as those observed in AD, thereby verifying a possible model of AD impairment. We did it by testing healthy elderly subjects in two experimental conditions: glycopyrrolate (placebo) and scopolamine administration. We then analyzed magnetoencephalographic (MEG) data corresponding to both conditions in resting-state with eyes closed. This analysis was performed in source space by combining a nonlinear frequency band-specific measure of functional connectivity (phase locking value, PLV) with network analysis methods. Under scopolamine, functional connectivity between several brain areas was significantly reduced as compared to placebo, in most frequency bands analyzed. Besides, regarding the two complex network indices studied (clustering and shortest path length), clustering significantly decreased in the alpha band while shortest path length significantly increased also in alpha band both after scopolamine administration. Overall our findings indicate that both PLV and graph analysis are suitable tools to measure brain connectivity changes induced by scopolamine, which causes alterations in brain connectivity apparently similar to those reported in AD.
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Gentili C, Vanello N, Cristea I, David D, Ricciardi E, Pietrini P. Proneness to social anxiety modulates neural complexity in the absence of exposure: A resting state fMRI study using Hurst exponent. Psychiatry Res 2015; 232:135-44. [PMID: 25882042 DOI: 10.1016/j.pscychresns.2015.03.005] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2014] [Revised: 02/07/2015] [Accepted: 03/13/2015] [Indexed: 01/07/2023]
Abstract
To test the hypothesis that brain activity is modulated by trait social anxiety, we measured the Hurst Exponent (HE), an index of complexity in time series, in healthy individuals at rest in the absence of any social trigger. Functional magnetic resonance imaging (fMRI) time series were recorded in 36 subjects at rest. All volunteers were healthy without any psychiatric, medical or neurological disorder. Subjects completed the Liebowitz Social Anxiety Scale (LSAS) and the Brief Fear of Negative Evaluation (BFNE) to assess social anxiety and thoughts in social contexts. We also obtained the fractional Amplitude of Low Frequency Fluctuations (fALFF) of the BOLD signal as an independent control measure for HE data. BFNE scores correlated positively with HE in the posterior cingulate/precuneus, while LSAS scores correlated positively with HE in the precuneus, in the inferior parietal sulci and in the parahippocamus. Results from fALFF were highly consistent with those obtained using LSAS and BFNE to predict HE. Overall our data indicate that spontaneous brain activity is influenced by the degree of social anxiety, on a continuum and in the absence of social stimuli. These findings suggest that social anxiety is a trait characteristic that shapes brain activity and predisposes to different reactions in social contexts.
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Affiliation(s)
- Claudio Gentili
- Clinical Psychology Branch, Department of Neuroscience, Pisa University Hospital, Via Roma. 67, Pisa, Italy; Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Via Paradisa 10, Pisa, Italy.
| | - Nicola Vanello
- Department of Information Engineering, University of Pisa, Via Diotisalvi 10, Pisa, Italy
| | - Ioana Cristea
- Clinical Psychology Branch, Department of Neuroscience, Pisa University Hospital, Via Roma. 67, Pisa, Italy; Department of Clinical Psychology and Psychotherapy, University Babes-Bolyai, Republicii str. 37, Cluj-Napoca, Romania
| | - Daniel David
- Department of Clinical Psychology and Psychotherapy, University Babes-Bolyai, Republicii str. 37, Cluj-Napoca, Romania; Department of Oncological Sciences, Mount Sinai School of Medicine, 1428 Madison Ave New York, NY, USA
| | - Emiliano Ricciardi
- Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Via Paradisa 10, Pisa, Italy
| | - Pietro Pietrini
- Clinical Psychology Branch, Department of Neuroscience, Pisa University Hospital, Via Roma. 67, Pisa, Italy; Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Via Paradisa 10, Pisa, Italy
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Association of resting-state network dysfunction with their dynamics of inter-network interactions in depression. J Affect Disord 2015; 174:527-34. [PMID: 25556670 DOI: 10.1016/j.jad.2014.12.020] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2014] [Revised: 10/25/2014] [Accepted: 12/04/2014] [Indexed: 01/24/2023]
Abstract
BACKGROUND Network-level brain analysis on resting state has demonstrated that depression is not only associated with intra-network dysfunction, but relates to the disturbed interplay between the networks. However, the underlying associations between the intra-network dysfunction and the disturbed inter-network interactions remain unexplored. This study was aimed to explore the association of resting-state networks dysfunction with their dynamics of inter-network interactions in depression. METHODS Resting-state functional magnetic resonance imaging (fMRI) data were collected from 20 depressed patients and 20 matched healthy controls. We evaluated the Hurst exponents of the time series from resting-state networks, and employed multivariate pattern analysis to capture depression-associated networks with increased or decreased Hurst values. Granger causalities between these networks were explored to undertake an intensive study of the dynamic inter-network interactions. RESULTS The default mode network (DMN) exhibited decreased Hurst value, indicative of more irregular oscillation within the DMN implicated in depressive symptoms. The ventromedial prefrontal network (vmPFN) and salience network (SN) with increased Hurst values, as compensatory mechanisms, continually enhanced the interactions to the DMN for trying hard to impel the DMN to function synchronously. On the other side, the DMN exerted frequently enhanced causality on the left fronto-parietal network with elevated Hurst exponent, accompanied by imbalance between the fronto-parietal network and DMN circuits in depression. LIMITATIONS This study suffers from small sample size and is confined to large-scale networks. CONCLUSIONS Our preliminary findings mainly revealed the DMN-related dynamic interactions with the vmPFN, SN and the fronto-parietal network in depression, which might offer useful information for discovering the neuropathological mechanisms underlying the depressive symptoms.
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Shah D, Blockx I, Guns PJ, De Deyn PP, Van Dam D, Jonckers E, Delgado Y Palacios R, Verhoye M, Van der Linden A. Acute modulation of the cholinergic system in the mouse brain detected by pharmacological resting-state functional MRI. Neuroimage 2015; 109:151-9. [PMID: 25583611 DOI: 10.1016/j.neuroimage.2015.01.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 12/22/2014] [Accepted: 01/05/2015] [Indexed: 01/13/2023] Open
Abstract
INTRODUCTION The cholinergic system is involved in learning and memory and is affected in neurodegenerative disorders such as Alzheimer's disease. The possibility of non-invasively detecting alterations of neurotransmitter systems in the mouse brain would greatly improve early diagnosis and treatment strategies. The hypothesis of this study is that acute modulation of the cholinergic system might be reflected as altered functional connectivity (FC) and can be measured using pharmacological resting-state functional MRI (rsfMRI). MATERIAL AND METHODS Pharmacological rsfMRI was performed on a 9.4T MRI scanner (Bruker BioSpec, Germany) using a gradient echo EPI sequence. All mice were sedated with medetomidine. C57BL/6 mice (N = 15/group) were injected with either saline, the cholinergic antagonist scopolamine, or methyl-scopolamine, after which rsfMRI was acquired. For an additional group (N = 8), rsfMRI scans of the same mouse were acquired first at baseline, then after the administration of scopolamine and finally after the additional injection of the cholinergic agonist milameline. Contextual memory was evaluated with the same setup as the pharmacological rsfMRI using the passive avoidance behavior test. RESULTS Scopolamine induced a dose-dependent decrease of FC between brain regions involved in memory. Scopolamine-induced FC deficits could be recovered completely by milameline for FC between the hippocampus-thalamus, cingulate-retrosplenial, and visual-retrosplenial cortex. FC between the cingulate-rhinal, cingulate-visual and visual-rhinal cortex could not be completely recovered by milameline. This is consistent with the behavioral outcome, where milameline only partially recovered scopolamine-induced contextual memory deficits. Methyl-scopolamine administered at the same dose as scopolamine did not affect FC in the brain. CONCLUSION The results of the current study are important for future studies in mouse models of neurodegenerative disorders, where pharmacological rsfMRI may possibly be used as a non-invasive read-out tool to detect alterations of neurotransmitter systems induced by pathology or treatment.
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Affiliation(s)
- Disha Shah
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium.
| | - Ines Blockx
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Pieter-Jan Guns
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Peter Paul De Deyn
- Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium; Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Lindendreef 1, 2020 Antwerp, Belgium; Department of Neurology and Alzheimer Research Center, University of Groningen and University Medical Center Groningen (UMCG), Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Debby Van Dam
- Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | - Elisabeth Jonckers
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | | | - Marleen Verhoye
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
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Ni H, Huang X, Ning X, Huo C, Liu T, Ben D. Multifractal analysis of resting state fMRI series in default mode network: age and gender effects. CHINESE SCIENCE BULLETIN-CHINESE 2014. [DOI: 10.1007/s11434-014-0355-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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de Macêdo Medeiros A, Izídio GS, Sousa DS, Macedo PT, Silva AF, Shiramizu VKM, Cabral A, Ribeiro AM, Silva RH. Estrogen levels modify scopolamine-induced amnesia in gonadally intact rats. Prog Neuropsychopharmacol Biol Psychiatry 2014; 53:99-108. [PMID: 24657885 DOI: 10.1016/j.pnpbp.2014.03.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Revised: 02/24/2014] [Accepted: 03/10/2014] [Indexed: 12/23/2022]
Abstract
Previous studies suggested that estrogen plays a role in cognitive function by modulating the cholinergic transmission. However, most of the studies dealing with this subject have been conducted using ovariectomized rats. In the present study we evaluated the effects of physiological and supra-physiological variation of estrogen levels on scopolamine-induced amnesia in gonadally intact female rats. We used the plus-maze discriminative avoidance task (PMDAT) in order to evaluate anxiety levels and motor activity concomitantly to the memory performance. In experiment 1, female Wistar rats in each estrous cycle phase received scopolamine (1 mg/kg) or saline i.p. 20 min before the training session in the PMDAT. In experiment 2, rats in diestrus received estradiol valerate (1 mg/kg) or sesame oil i.m., and scopolamine (1 mg/kg) or saline i.p., 45 min and 20 min before the training, respectively. In experiment 3, rats in diestrus received scopolamine (1 mg/kg) or saline i.p. 20 min before the training, and estradiol valerate (1 mg/kg) or sesame oil i.m. immediately after the training session. In all experiments, a test session was performed 24 h later. The main results showed that: (1) scopolamine impaired retrieval and induced anxiolytic and hyperlocomotor effects in all experiments; (2) this cholinergic antagonist impaired acquisition only in animals in diestrus; (3) acute administration of estradiol valerate prevented the learning impairment induced by scopolamine and (4) interfered with memory consolidation process. The results suggest that endogenous variations in estrogen levels across the estrous cycle modulate some aspects of memory mediated by the cholinergic system. Indeed, specifically in diestrus, a stage with low estrogen levels, the impairment produced by scopolamine on the acquisition was counteracted by exogenous administration of the hormone, whereas the posttraining treatment potentiated the negative effects of scopolamine during the consolidation phase of memory.
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Affiliation(s)
| | - Geison Souza Izídio
- Behavioral Genetics Laboratory, Universidade Federal de Santa Catarina, Florianópolis, Brazil
| | - Diego Silveira Sousa
- Memory Studies Laboratory, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | | | | | | | - Alicia Cabral
- Memory Studies Laboratory, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | | | - Regina Helena Silva
- Memory Studies Laboratory, Universidade Federal do Rio Grande do Norte, Natal, Brazil.
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The integrity of the cholinergic system determines memory performance in healthy elderly. Neuroimage 2014; 100:481-8. [PMID: 24952230 DOI: 10.1016/j.neuroimage.2014.06.031] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2014] [Revised: 05/13/2014] [Accepted: 06/11/2014] [Indexed: 02/06/2023] Open
Abstract
The cholinergic system plays a central role in episodic memory-related processes in health and disease. Cerebral acetylcholinesterase (AChE) activity, a measure of the integrity of the cholinergic system, can be assessed in vivo using positron emission tomography (PET) and [(11)C]N-methyl-4-piperidyl acetate (MP4A). A close relationship between the kinetic constant k3 of MP4A and mnestic functions has been demonstrated for patients suffering from amnestic mild cognitive impairment and Alzheimer's disease. Under the hypothesis that AChE activity and memory are intimately linked in older age, we obtained MP4A-PET and structural magnetic resonance images as well as neuropsychological data from fourteen healthy older adults. Multiple regression analysis revealed that AChE activity in areas previously implicated in mnestic functions predicted episodic memory performance irrespective of cortical atrophy. Data suggest that in older adults the integrity of the cholinergic system underlies inter-individual variability in memory function.
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Sanchez-Alavez M, Robledo P, Wills DN, Havstad J, Ehlers CL. Cholinergic modulation of event-related oscillations (ERO). Brain Res 2014; 1559:11-25. [PMID: 24594019 DOI: 10.1016/j.brainres.2014.02.043] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Revised: 02/12/2014] [Accepted: 02/24/2014] [Indexed: 12/24/2022]
Abstract
The cholinergic system in the brain modulates patterns of activity involved in general arousal, attention processing, memory and consciousness. In the present study we determined the effects of selective cholinergic lesions of the medial septum area (MS) or nucleus basalis magnocellularis (NBM) on amplitude and phase characteristics of event related oscillations (EROs). A time-frequency based representation was used to determine ERO energy, phase synchronization across trials, recorded within a structure (phase lock index, PLI), and phase synchronization across trials, recorded between brain structures (phase difference lock index, PDLI), in the frontal cortex (Fctx), dorsal hippocampus (DHPC) and central amygdala (Amyg). Lesions in MS produced: (1) decreases in ERO energy in delta, theta, alpha, beta and gamma frequencies in Amyg, (2) reductions in gamma ERO energy and PLI in Fctx, (3) decreases in PDLI between the Fctx-Amyg in the theta, alpha, beta and gamma frequencies, and (4) decreases in PDLI between the DHPC-Amyg and Fctx-DHPC in the theta frequency bands. Lesions in NBM resulted in: (1) increased ERO energy in delta and theta frequency bands in Fctx, (2) reduced gamma ERO energy in Fctx and Amyg, (3) reductions in PLI in the theta, beta and gamma frequency ranges in Fctx, (4) reductions in gamma PLI in DHPC and (5) reduced beta PLI in Amyg. These studies suggest that the MS cholinergic system can alter phase synchronization between brain areas whereas the NBM cholinergic system modifies phase synchronization/phase resetting within a brain area.
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Affiliation(s)
- Manuel Sanchez-Alavez
- Department of Molecular and Cellular Neuroscience, The Scripps Research Institute, 10550 North Torrey Pines Road, SP30-1501, La Jolla, CA 92037, USA
| | - Patricia Robledo
- Laboratory of Neuropharmacology, Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Plaça de la Mercè, 10-12, 08002 Barcelona, Spain
| | - Derek N Wills
- Department of Molecular and Cellular Neuroscience, The Scripps Research Institute, 10550 North Torrey Pines Road, SP30-1501, La Jolla, CA 92037, USA
| | - James Havstad
- Laboratory of Neuropharmacology, Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Plaça de la Mercè, 10-12, 08002 Barcelona, Spain
| | - Cindy L Ehlers
- Department of Molecular and Cellular Neuroscience, The Scripps Research Institute, 10550 North Torrey Pines Road, SP30-1501, La Jolla, CA 92037, USA.
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Wei M, Qin J, Yan R, Li H, Yao Z, Lu Q. Identifying major depressive disorder using Hurst exponent of resting-state brain networks. Psychiatry Res 2013; 214:306-12. [PMID: 24113289 DOI: 10.1016/j.pscychresns.2013.09.008] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2013] [Revised: 08/30/2013] [Accepted: 09/12/2013] [Indexed: 02/07/2023]
Abstract
Resting-state functional magnetic resonance imaging (fMRI) studies of major depressive disorder (MDD) have revealed abnormalities of functional connectivity within or among the resting-state networks. They provide valuable insight into the pathological mechanisms of depression. However, few reports were involved in the "long-term memory" of fMRI signals. This study was to investigate the "long-term memory" of resting-state networks by calculating their Hurst exponents for identifying depressed patients from healthy controls. Resting-state networks were extracted from fMRI data of 20 MDD and 20 matched healthy control subjects. The Hurst exponent of each network was estimated by Range Scale analysis for further discriminant analysis. 95% of depressed patients and 85% of healthy controls were correctly classified by Support Vector Machine with an accuracy of 90%. The right fronto-parietal and default mode network constructed a deficit network (lower memory and more irregularity in MDD), while the left fronto-parietal, ventromedial prefrontal and salience network belonged to an excess network (longer memory in MDD), suggesting these dysfunctional networks may be related to a portion of the complex of emotional and cognitive disturbances. The abnormal "long-term memory" of resting-state networks associated with depression may provide a new possibility towards the exploration of the pathophysiological mechanisms of MDD.
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Affiliation(s)
- Maobin Wei
- Research Center of Learning Science, Southeast University, 2 sipailou, Nanjing 210096, China
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Weber AM, Soreni N, Noseworthy MD. A preliminary study on the effects of acute ethanol ingestion on default mode network and temporal fractal properties of the brain. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2013; 27:291-301. [DOI: 10.1007/s10334-013-0420-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2013] [Revised: 10/30/2013] [Accepted: 11/05/2013] [Indexed: 10/26/2022]
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Hagan CC, Graham JME, Widmer B, Holt RJ, Ooi C, van Nieuwenhuizen AO, Fonagy P, Reynolds S, Target M, Kelvin R, Wilkinson PO, Bullmore ET, Lennox BR, Sahakian BJ, Goodyer I, Suckling J. Magnetic resonance imaging of a randomized controlled trial investigating predictors of recovery following psychological treatment in adolescents with moderate to severe unipolar depression: study protocol for Magnetic Resonance-Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT). BMC Psychiatry 2013; 13:247. [PMID: 24094274 PMCID: PMC3851239 DOI: 10.1186/1471-244x-13-247] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 10/02/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making. METHODS/DESIGN Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550). DISCUSSION MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response. TRIAL REGISTRATION Adjunctive study to IMPACT trial (Current Controlled Trials: ISRCTN83033550).
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Affiliation(s)
- Cindy C Hagan
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
| | - Julia ME Graham
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
| | - Barry Widmer
- Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge CB2 8AH, UK
| | - Rosemary J Holt
- Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge CB2 8AH, UK
| | - Cinly Ooi
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
| | - Adrienne O van Nieuwenhuizen
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
| | - Peter Fonagy
- Psychoanalysis Unit, Research Department of Clinical, Educational and Health Psychology, University College London, Gower Street, London WC1E 6BT, UK
| | - Shirley Reynolds
- Department of Psychological Sciences, Norwich Medical School, University of East Anglia, Norwich NR4 7QH, UK
| | - Mary Target
- Psychoanalysis Unit, Research Department of Clinical, Educational and Health Psychology, University College London, Gower Street, London WC1E 6BT, UK
| | - Raphael Kelvin
- Brookside Family Consultation Clinic, 18d Trumpington Road, Cambridge CB2 8AH, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Paul O Wilkinson
- Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge CB2 8AH, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
- MRC/Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- GlaxoSmithKline, Clinical Unit Cambridge, Cambridge, UK
| | - Belinda R Lennox
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Barbara J Sahakian
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
- MRC/Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
| | - Ian Goodyer
- Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, Cambridge CB2 8AH, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
- MRC/Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Robinson Way, Cambridge CB2 0SZ, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
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Extraversion is encoded by scale-free dynamics of default mode network. Neuroimage 2013; 74:52-7. [PMID: 23454049 DOI: 10.1016/j.neuroimage.2013.02.020] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2012] [Revised: 02/06/2013] [Accepted: 02/11/2013] [Indexed: 11/21/2022] Open
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Optimizing complexity measures for FMRI data: algorithm, artifact, and sensitivity. PLoS One 2013; 8:e63448. [PMID: 23700424 PMCID: PMC3660309 DOI: 10.1371/journal.pone.0063448] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2012] [Accepted: 04/02/2013] [Indexed: 01/17/2023] Open
Abstract
INTRODUCTION Complexity in the brain has been well-documented at both neuronal and hemodynamic scales, with increasing evidence supporting its use in sensitively differentiating between mental states and disorders. However, application of complexity measures to fMRI time-series, which are short, sparse, and have low signal/noise, requires careful modality-specific optimization. METHODS HERE WE USE BOTH SIMULATED AND REAL DATA TO ADDRESS TWO FUNDAMENTAL ISSUES: choice of algorithm and degree/type of signal processing. Methods were evaluated with regard to resilience to acquisition artifacts common to fMRI as well as detection sensitivity. Detection sensitivity was quantified in terms of grey-white matter contrast and overlap with activation. We additionally investigated the variation of complexity with activation and emotional content, optimal task length, and the degree to which results scaled with scanner using the same paradigm with two 3T magnets made by different manufacturers. Methods for evaluating complexity were: power spectrum, structure function, wavelet decomposition, second derivative, rescaled range, Higuchi's estimate of fractal dimension, aggregated variance, and detrended fluctuation analysis. To permit direct comparison across methods, all results were normalized to Hurst exponents. RESULTS Power-spectrum, Higuchi's fractal dimension, and generalized Hurst exponent based estimates were most successful by all criteria; the poorest-performing measures were wavelet, detrended fluctuation analysis, aggregated variance, and rescaled range. CONCLUSIONS Functional MRI data have artifacts that interact with complexity calculations in nontrivially distinct ways compared to other physiological data (such as EKG, EEG) for which these measures are typically used. Our results clearly demonstrate that decisions regarding choice of algorithm, signal processing, time-series length, and scanner have a significant impact on the reliability and sensitivity of complexity estimates.
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Mikkelsen KB, Lund TE. Sampling rate dependence of correlation at long time lags in BOLD fMRI measurements on humans and gel phantoms. Front Physiol 2013; 4:106. [PMID: 23730289 PMCID: PMC3657634 DOI: 10.3389/fphys.2013.00106] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2013] [Accepted: 04/25/2013] [Indexed: 11/29/2022] Open
Abstract
The aim of this study is to investigate the effects of sampling rate on Hurst exponents derived from Blood Oxygenation Level Dependent functional Magnetic Resonance Imaging (BOLD fMRI) resting state time series. fMRI measurements were performed on 2 human subjects and a selection of gel phantoms. From these, Hurst exponents were calculated. It was found that low sampling rates induced non-trivial exponents at sharp material transitions, and that Hurst exponents of human measurements had a strong TR-dependence. The findings are compared to theoretical considerations regarding the fractional Gaussian noise model and resampling, and it is found that the implications are problematic. This result should have a direct influence on the way future studies of low-frequency variation in BOLD fMRI data are conducted, especially if the fractional Gaussian noise model is considered. We recommend either using a different model (examples of such are referenced in the conclusion), or standardizing experimental procedures along an optimal sampling rate.
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Affiliation(s)
- Kaare B Mikkelsen
- Department of Physics and Astronomy, Science and Technology, Aarhus University Aarhus, Denmark ; Center of Functionally Integrative Neuroscience, Aarhus University Hospital Aarhus, Denmark
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Zhang M, Ye Y, Cong J, Pu D, Liu J, Hu G, Wu J. Regulation of STAT3 by miR-106a is linked to cognitive impairment in ovariectomized mice. Brain Res 2013; 1503:43-52. [PMID: 23399684 DOI: 10.1016/j.brainres.2013.01.052] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2012] [Revised: 01/28/2013] [Accepted: 01/31/2013] [Indexed: 10/27/2022]
Abstract
MicroRNAs are abundantly expressed in the brain and play an important role in disorders of the brain, including cognitive impairment and Alzheimer's disease (AD). A growing body of evidence suggests that the janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway plays a key role in the pathogenesis of AD. However, it is unclear whether miRNAs are involved in this process. Therefore, we characterized the expression and role of miR-106a and JAK/STAT signaling in an ovariectomized (OVX) mouse model of cognitive impairment. Cognitive impairment, as indicated by escape latency and time spent in the platform quadrant in the Morris water maze test, was significantly reduced at 12 weeks post-OVX, compared to age-matched controls. Quantitative real-time PCR and Western blotting demonstrated that miR-106a was upregulated, and STAT3 and phospho-STAT3 were downregulated in the hippocampus at 12 weeks post-OVX, compared with age matched controls and the 6 and 8 weeks post-OVX groups. Transfection of human neuroblastoma SH-SY5Y cells with a miR-106a mimic reduced the expression of STAT3 mRNA, compared to control cells transfected with a scrambled mimic. STAT3 and phospho-STAT3 protein expression was upregulated or downregulated by a miR-106a inhibitor or miR-106a mimic, respectively, indicating that miR-106a negatively regulates STAT3. Luciferase reporter gene assays confirmed that miR-106a directly targets the 3' untranslated region (UTR) of STAT3. This study suggests that miR-106a negatively regulates STAT3 activation, and also that miR-106a may provide a marker of onset or potential therapeutic target for cognitive disturbances.
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Affiliation(s)
- Min Zhang
- State Key Laboratory of Reproductive Medicine, Department of Obstetrics and Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing 210029, China
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Giessing C, Thiel CM. Pro-cognitive drug effects modulate functional brain network organization. Front Behav Neurosci 2012; 6:53. [PMID: 22973209 PMCID: PMC3428580 DOI: 10.3389/fnbeh.2012.00053] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2012] [Accepted: 07/25/2012] [Indexed: 12/14/2022] Open
Abstract
Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with functional magnetic resonance imaging (fMRI). Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e., the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the "global workspace" theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs might be related to higher network integration.
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Affiliation(s)
- Carsten Giessing
- Biological Psychology Lab, Institute of Psychology, University of OldenburgOldenburg, Germany
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Pharmacologic magnetic resonance imaging (phMRI): imaging drug action in the brain. Neuroimage 2012; 62:1072-85. [PMID: 22495143 DOI: 10.1016/j.neuroimage.2012.03.075] [Citation(s) in RCA: 85] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2012] [Accepted: 03/23/2012] [Indexed: 02/01/2023] Open
Abstract
The technique of functional magnetic resonance (fMRI), using various cognitive, motor and sensory stimuli has led to a revolution in the ability to map brain function. Drugs can also be used as stimuli to elicit an hemodynamic change. Stimulation with a pharmaceutical has a number of very different consequences compared to user controllable stimuli, most importantly in the time course of stimulus and response that is not, in general, controllable by the experimenter. Therefore, this type of experiment has been termed pharmacologic MRI (phMRI). The use of a drug stimulus leads to a number of interesting possibilities compared to conventional fMRI. Using receptor specific ligands one can characterize brain circuitry specific to neurotransmitter systems. The possibility exists to measure parameters reflecting neurotransmitter release and binding associated with the pharmacokinetics and/or the pharmacodynamics of drugs. There is also the ability to measure up- and down-regulation of receptors in specific disease states. phMRI can be characterized as a molecular imaging technique using the natural hemodynamic transduction related to neuro-receptor stimulus. This provides a coupling mechanism with very high sensitivity that can rival positron emission tomography (PET) in some circumstances. The large numbers of molecules available, that do not require a radio-label, means that phMRI becomes a very useful tool for performing drug discovery. Data and arguments will be presented to show that phMRI can provide information on neuro-receptor signaling and function that complements the static picture generated by PET studies of receptor numbers and occupancies.
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Warsi MA, Molloy W, Noseworthy MD. Correlating brain blood oxygenation level dependent (BOLD) fractal dimension mapping with magnetic resonance spectroscopy (MRS) in Alzheimer's disease. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2012; 25:335-44. [PMID: 22446877 DOI: 10.1007/s10334-012-0312-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2011] [Revised: 02/15/2012] [Accepted: 03/02/2012] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To correlate temporal fractal structure of resting state blood oxygen level dependent (rsBOLD) functional magnetic resonance imaging (fMRI) with in vivo proton magnetic resonance spectroscopy ((1)H-MRS), in Alzheimer's disease (AD) and healthy age-matched normal controls (NC). MATERIALS AND METHODS High temporal resolution (4 Hz) rsBOLD signal and single voxel (left putamen) magnetic resonance spectroscopy data was acquired in 33 AD patients and 13 NC. The rsBOLD data was analyzed using two types of fractal dimension (FD) analysis based on relative dispersion and frequency power spectrum. Comparisons in FD were performed between AD and NC, and FD measures were correlated with (1)H-MRS findings. RESULTS Temporal fractal analysis of rsBOLD, was able to differentiate AD from NC subjects (P = 0.03). Low FD correlated with markers of AD severity including decreased concentrations of N-acetyl aspartate (R = 0.44, P = 0.015) and increased myoinositol (mI) (R = -0.45, P = 0.012). CONCLUSION Based on these results we suggest fractal analysis of rsBOLD could provide an early marker of AD.
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Affiliation(s)
- Mohammed A Warsi
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada
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Ehlers CL, Wills DN, Havstad J. Ethanol reduces the phase locking of neural activity in human and rodent brain. Brain Res 2012; 1450:67-79. [PMID: 22410292 DOI: 10.1016/j.brainres.2012.02.039] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2011] [Revised: 02/10/2012] [Accepted: 02/14/2012] [Indexed: 11/29/2022]
Abstract
How the neuromolecular actions of ethanol translate to its observed intoxicating effects remains poorly understood. Synchrony of phase (phase locking) of event-related oscillations (EROs) within and between different brain areas has been suggested to reflect communication exchange between neural networks and as such may be a sensitive and translational measure of ethanol's effects. Using a similar auditory event-related potential paradigm in both rats and humans we investigated the phase variability of EROs collected from 38 young men who had participated in an ethanol/placebo challenge protocol, and 46 adult male rats given intraperitoneal injections of ethanol/saline. Phase locking was significantly higher in the delta frequencies in humans than in rats. Phase locking was also higher for the rare (target) tone than the frequent (non-target) tone in both species. Significant reductions in phase locking to the rare (target) tone in the delta, theta, alpha, beta and gamma frequencies, within and between brain sites, was found at 1h following ethanol as compared to placebo/saline administration in both rats and humans. Reductions in phase locking in the alpha frequencies in the parietal cortex were found to be correlated with blood ethanol concentrations. These findings are consistent with the hypothesis that ethanol's intoxicating actions in the brain include reducing synchrony within and between neuronal networks, perhaps by increasing the level of noise in key neuromolecular interactions.
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Affiliation(s)
- Cindy L Ehlers
- Department of Molecular and Integrative Neuroscience, The Scripps Research Institute,10550 North Torrey Pines Road, La Jolla, CA 92037, USA.
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