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Yao R, Song M, Shi L, Pei Y, Li H, Tan S, Wang B. Microstate D as a Biomarker in Schizophrenia: Insights from Brain State Transitions. Brain Sci 2024; 14:985. [PMID: 39451999 PMCID: PMC11505886 DOI: 10.3390/brainsci14100985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Revised: 09/23/2024] [Accepted: 09/26/2024] [Indexed: 10/26/2024] Open
Abstract
Objectives. There is a significant correlation between EEG microstate and the neurophysiological basis of mental illness, brain state, and cognitive function. Given that the unclear relationship between network dynamics and different microstates, this paper utilized microstate, brain network, and control theories to understand the microstate characteristics of short-term memory task, aiming to mechanistically explain the most influential microstates and brain regions driving the abnormal changes in brain state transitions in patients with schizophrenia. Methods. We identified each microstate and analyzed the microstate abnormalities in schizophrenia patients during short-term memory tasks. Subsequently, the network dynamics underlying the primary microstates were studied to reveal the relationships between network dynamics and microstates. Finally, using control theory, we confirmed that the abnormal changes in brain state transitions in schizophrenia patients are driven by specific microstates and brain regions. Results. The frontal-occipital lobes activity of microstate D decreased significantly, but the left frontal lobe of microstate B increased significantly in schizophrenia, when the brain was moving toward the easy-to-reach states. However, the frontal-occipital lobes activity of microstate D decreased significantly in schizophrenia, when the brain was moving toward the hard-to-reach states. Microstate D showed that the right-frontal activity had a higher priority than the left-frontal, but microstate B showed that the left-frontal priority decreased significantly in schizophrenia, when changes occur in the synchronization state of the brain. Conclusions. In conclusion, microstate D may be a biomarker candidate of brain abnormal activity during the states transitions in schizophrenia, and microstate B may represent a compensatory mechanism that maintains brain function and exchanges information with other brain regions. Microstate and brain network provide complementary perspectives on the neurodynamics, offering potential insights into brain function in health and disease.
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Affiliation(s)
- Rong Yao
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Meirong Song
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Langhua Shi
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Yan Pei
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Haifang Li
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
| | - Shuping Tan
- Psychiatry Research Center, Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China;
| | - Bin Wang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China; (R.Y.); (M.S.); (L.S.); (Y.P.); (H.L.)
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Fernández-Linsenbarth I, Mijancos-Martínez G, Bachiller A, Núñez P, Rodríguez-González V, Beño-Ruiz-de-la-Sierra RM, Roig-Herrero A, Arjona-Valladares A, Poza J, Mañanas MÁ, Molina V. Relation between task-related activity modulation and cortical inhibitory function in schizophrenia and healthy controls: a TMS-EEG study. Eur Arch Psychiatry Clin Neurosci 2024; 274:837-847. [PMID: 38243018 PMCID: PMC11127880 DOI: 10.1007/s00406-023-01745-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 12/11/2023] [Indexed: 01/21/2024]
Abstract
Schizophrenia has been associated with a reduced task-related modulation of cortical activity assessed through electroencephalography (EEG). However, to the best of our knowledge, no study so far has assessed the underpinnings of this decreased EEG modulation in schizophrenia. A possible substrate of these findings could be a decreased inhibitory function, a replicated finding in the field. In this pilot study, our aim was to explore the association between EEG modulation during a cognitive task and the inhibitory system function in vivo in a sample including healthy controls and patients with schizophrenia. We hypothesized that the replicated decreased task-related activity modulation during a cognitive task in schizophrenia would be related to a hypofunction of the inhibitory system. For this purpose, 27 healthy controls and 22 patients with schizophrenia (including 13 first episodes) performed a 3-condition auditory oddball task from which the spectral entropy modulation was calculated. In addition, cortical reactivity-as an index of the inhibitory function-was assessed by the administration of 75 monophasic transcranial magnetic stimulation single pulses over the left dorsolateral prefrontal cortex. Our results replicated the task-related cortical activity modulation deficit in schizophrenia patients. Moreover, schizophrenia patients showed higher cortical reactivity following transcranial magnetic stimulation single pulses over the left dorsolateral prefrontal cortex compared to healthy controls. Cortical reactivity was inversely associated with EEG modulation, supporting the idea that a hypofunction of the inhibitory system could hamper the task-related modulation of EEG activity.
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Affiliation(s)
- Inés Fernández-Linsenbarth
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005, Valladolid, Spain
| | - Gema Mijancos-Martínez
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Polytechnic University of Catalonia, Barcelona, Spain
- Institute of Research Sant Joan de Déu, Barcelona, Spain
| | - Alejandro Bachiller
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Polytechnic University of Catalonia, Barcelona, Spain
- Institute of Research Sant Joan de Déu, Barcelona, Spain
| | - Pablo Núñez
- Coma Science Group, CIGA-Consciousness, University of Liège, Liège, Belgium
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Biomaterials and Nanomedicine (BICER-BBN), CIBER of Bioengineering, Madrid, Spain
| | - Víctor Rodríguez-González
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Biomaterials and Nanomedicine (BICER-BBN), CIBER of Bioengineering, Madrid, Spain
| | | | - Alejandro Roig-Herrero
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005, Valladolid, Spain
- Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain
| | - Antonio Arjona-Valladares
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005, Valladolid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Biomaterials and Nanomedicine (BICER-BBN), CIBER of Bioengineering, Madrid, Spain
- Instituto de Investigación en Matemáticas (IMUCA), University of Valladolid, Valladolid, Spain
| | - Miguel Ángel Mañanas
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Polytechnic University of Catalonia, Barcelona, Spain
- Institute of Research Sant Joan de Déu, Barcelona, Spain
- Biomaterials and Nanomedicine (BICER-BBN), CIBER of Bioengineering, Madrid, Spain
| | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005, Valladolid, Spain.
- Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain.
- Neurosciences Institute of Castilla y Léon (INCYL), University of Salamanca, Salamanca, Spain.
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Díez Á, Gomez-Pilar J, Poza J, Beño-Ruiz-de-la-Sierra R, Fernández-Linsenbarth I, Recio-Barbero M, Núñez P, Holgado-Madera P, Molina V. Functional network properties in schizophrenia and bipolar disorder assessed with high-density electroencephalography. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110902. [PMID: 38036032 DOI: 10.1016/j.pnpbp.2023.110902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/10/2023] [Accepted: 11/24/2023] [Indexed: 12/02/2023]
Abstract
BACKGROUND The study of the cortical functional network properties in schizophrenia (SZ) may benefit from the use of graph theory parameters applied to high-density electroencephalography (EEG). Connectivity Strength (CS) assesses global synchrony of the network, and Shannon Graph Complexity (SGC) summarizes the network distribution of link weights and allows distinguishing between primary and secondary pathways. Their joint use may help in understanding the underpinnings of the functional network hyperactivation and task-related hypomodulation previously described in psychoses. METHODS We used 64-sensor EEG recordings during a P300 oddball task in 128 SZ patients (96 chronic, CR, and 32 first episodes, FE), as well as 46 bipolar disorder (BD) patients, and 92 healthy controls (HC). Pre-stimulus and modulation (task-response minus pre-stimulus windows values) of CS and SGC were assessed in the theta band (4-8 Hz) and the broadband (4-70 Hz). RESULTS Compared to HC, SZ patients (CR and FE) showed significantly higher pre-stimulus CS values in the broadband, and both SZ and BD patients showed lower theta-band CS modulation. SGC modulation values, both theta-band and broadband, were also abnormally reduced in CR patients. Statistically significant relationships were found in the theta band between SGC modulation and both CS pre-stimulus and modulation values in patients. CS altered measures in patients were additionally related to their cognitive outcome and negative symptoms. A primary role of antipsychotics in these results was ruled out. CONCLUSIONS Our results linking SGC and CS alterations in psychotic patients supported a hyperactive and hypomodulatory network mainly involving connections in secondary pathways.
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Affiliation(s)
- Álvaro Díez
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain
| | | | | | | | - Pablo Núñez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain.; Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
| | | | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain.; Psychiatry Service, Clinical University Hospital of Valladolid, Valladolid, Spain..
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Beño-Ruiz-de-la-Sierra RM, Fernández-Linsenbarth I, Roig-Herrero A, Díez-Revuelta Á. Electroencephalography for the Study of the Auditory P300 Evoked Potential and Derived Measurements. Methods Mol Biol 2023; 2687:93-106. [PMID: 37464165 DOI: 10.1007/978-1-0716-3307-6_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Electroencephalography (EEG) is a widely used tool in neuropsychiatry research. The most used measurements in EEG are the amplitude and latency of the cortical electrophysiological activity in response to stimulus, known as evoked potentials. Besides potentials, time/frequency analysis is also used to obtain information on global fluctuations of the recordings, which evoked potentials do not provide. Time/frequency analysis results in different values known as derived measures. In this work, a brief introduction to evoked potentials and time/frequency analyses in schizophrenia is given, focusing on P300, noise power, and spectral entropy. Finally, a detailed description is given on how to obtain EEG recordings, evoked potentials, and derived measures.
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Affiliation(s)
| | | | | | - Álvaro Díez-Revuelta
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
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Gallucci J, Tan T, Schifani C, Dickie EW, Voineskos AN, Hawco C. Greater individual variability in functional brain activity during working memory performance in Schizophrenia Spectrum Disorders (SSD). Schizophr Res 2022; 248:21-31. [PMID: 35908378 DOI: 10.1016/j.schres.2022.07.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 06/14/2022] [Accepted: 07/17/2022] [Indexed: 10/16/2022]
Abstract
Heterogeneity has been a persistent challenge in understanding Schizophrenia Spectrum Disorders (SSD). Traditional case-control comparisons often show variable results, and may not map well onto individuals. To better understand heterogeneity and group differences in SSD compared to typically developing controls (TDC), we examined variability in functional brain activity during a working memory (WM) task with known deficits in SSD. Neuroimaging and behavioural data were extracted from two datasets collectively providing 34 TDC and 56 individuals with SSD (n = 90). Functional activity in response to an N-Back WM task (3-Back vs 1-Back) was examined between and within groups. Individual variability was calculated via the correlational distance of fMRI activity maps between participants; mean correlational distance from one participant to all others was defined as a 'variability score'. Greater individual variability in functional activity was found in SSD compared to TDC (p = 0.00090). At the group level, a case-control comparison suggested SSD had reduced activity in task positive and task negative networks. However, when SSD were divided into high and low variability subgroups, the low variability groups showed no differences relative to TDC while the high variability group showed little activity at the group level. Our results imply prior case-control differences may be driven by a subgroup of SSD who do not show specific impairments but instead show more 'idiosyncratic' activity patterns. In SSD but not TDC, variability was also related to cognitive performance and age. This novel approach focusing on individual variability has important implications for understanding the neurobiology of SSD.
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Affiliation(s)
- Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Thomas Tan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Christin Schifani
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
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Roig-Herrero A, Planchuelo-Gómez Á, Hernández-García M, de Luis-García R, Fernández-Linsenbarth I, Beño-Ruiz-de-la-Sierra RM, Molina V. Default mode network components and its relationship with anomalous self-experiences in schizophrenia: A rs-fMRI exploratory study. Psychiatry Res Neuroimaging 2022; 324:111495. [PMID: 35635932 DOI: 10.1016/j.pscychresns.2022.111495] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 04/28/2022] [Accepted: 05/22/2022] [Indexed: 01/24/2023]
Abstract
Anomalous self-experiences (ASEs) in schizophrenia have been under research for the last 20 years. However, no neuroimage studies have provided insight of the possible biological underpinning of ASEs. In this novel approach, the connectivity within the default mode network, calculated through a ROI-based analysis of functional magnetic resonance imaging data, was correlated to the ASEs scores assessed by the Inventory of Psychotic-Like Anomalous Self-Experiences (IPASE) in a sample of 22 schizophrenia patients. The Pearson's correlation coefficients between IPASE scores and intrahemispheric connectivity of the parahippocampal gyrus with the isthmus cingulate cortex in both hemispheres, and right parahippocampal gyrus with the right rostral anterior cingulate cortex were positive and significant suggesting a relation between hyperactive functional connectivity and anomalous self-experiences intensity. Prior literature reported these areas to have a role in self-processing and consciousness as well as being anatomically connected. Further research with larger sample size and comparison with controls are needed to confirm the relationship of this connectivity with anomalous self-experiences.
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Affiliation(s)
| | | | | | | | | | | | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain; Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain
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Gregorich M, Melograna F, Sunqvist M, Michiels S, Van Steen K, Heinze G. Individual-specific networks for prediction modelling – A scoping review of methods. BMC Med Res Methodol 2022; 22:62. [PMID: 35249534 PMCID: PMC8898441 DOI: 10.1186/s12874-022-01544-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 02/11/2022] [Indexed: 11/10/2022] Open
Abstract
Background Recent advances in biotechnology enable the acquisition of high-dimensional data on individuals, posing challenges for prediction models which traditionally use covariates such as clinical patient characteristics. Alternative forms of covariate representations for the features derived from these modern data modalities should be considered that can utilize their intrinsic interconnection. The connectivity information between these features can be represented as an individual-specific network defined by a set of nodes and edges, the strength of which can vary from individual to individual. Global or local graph-theoretical features describing the network may constitute potential prognostic biomarkers instead of or in addition to traditional covariates and may replace the often unsuccessful search for individual biomarkers in a high-dimensional predictor space. Methods We conducted a scoping review to identify, collate and critically appraise the state-of-art in the use of individual-specific networks for prediction modelling in medicine and applied health research, published during 2000–2020 in the electronic databases PubMed, Scopus and Embase. Results Our scoping review revealed the main application areas namely neurology and pathopsychology, followed by cancer research, cardiology and pathology (N = 148). Network construction was mainly based on Pearson correlation coefficients of repeated measurements, but also alternative approaches (e.g. partial correlation, visibility graphs) were found. For covariates measured only once per individual, network construction was mostly based on quantifying an individual’s contribution to the overall group-level structure. Despite the multitude of identified methodological approaches for individual-specific network inference, the number of studies that were intended to enable the prediction of clinical outcomes for future individuals was quite limited, and most of the models served as proof of concept that network characteristics can in principle be useful for prediction. Conclusion The current body of research clearly demonstrates the value of individual-specific network analysis for prediction modelling, but it has not yet been considered as a general tool outside the current areas of application. More methodological research is still needed on well-founded strategies for network inference, especially on adequate network sparsification and outcome-guided graph-theoretical feature extraction and selection, and on how networks can be exploited efficiently for prediction modelling. Supplementary Information The online version contains supplementary material available at 10.1186/s12874-022-01544-6.
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Yao R, Xue J, Li H, Wang Q, Deng H, Tan S. Dynamics and synchronization control in schizophrenia for EEG signals. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103118] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Fernández-Linsenbarth I, Planchuelo-Gómez Á, Beño-Ruiz-de-la-Sierra RM, Díez A, Arjona A, Pérez A, Rodríguez-Lorenzana A, Del Valle P, de Luis-García R, Mascialino G, Holgado-Madera P, Segarra-Echevarría R, Gomez-Pilar J, Núñez P, Bote-Boneaechea B, Zambrana-Gómez A, Roig-Herrero A, Molina V. Search for schizophrenia and bipolar biotypes using functional network properties. Brain Behav 2021; 11:e2415. [PMID: 34758203 PMCID: PMC8671779 DOI: 10.1002/brb3.2415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 09/17/2021] [Accepted: 10/20/2021] [Indexed: 11/15/2022] Open
Abstract
INTRODUCTION Recent studies support the identification of valid subtypes within schizophrenia and bipolar disorder using cluster analysis. Our aim was to identify meaningful biotypes of psychosis based on network properties of the electroencephalogram. We hypothesized that these parameters would be more altered in a subgroup of patients also characterized by more severe deficits in other clinical, cognitive, and biological measurements. METHODS A clustering analysis was performed using the electroencephalogram-based network parameters derived from graph-theory obtained during a P300 task of 137 schizophrenia (of them, 35 first episodes) and 46 bipolar patients. Both prestimulus and modulation of the electroencephalogram were included in the analysis. Demographic, clinical, cognitive, structural cerebral data, and the modulation of the spectral entropy of the electroencephalogram were compared between clusters. Data from 158 healthy controls were included for further comparisons. RESULTS We identified two clusters of patients. One cluster presented higher prestimulus connectivity strength, clustering coefficient, path-length, and lower small-world index compared to controls. The modulation of clustering coefficient and path-length parameters was smaller in the former cluster, which also showed an altered structural connectivity network and a widespread cortical thinning. The other cluster of patients did not show significant differences with controls in the functional network properties. No significant differences were found between patients´ clusters in first episodes and bipolar proportions, symptoms scores, cognitive performance, or spectral entropy modulation. CONCLUSION These data support the existence of a subgroup within psychosis with altered global properties of functional and structural connectivity.
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Affiliation(s)
| | | | | | - Alvaro Díez
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | - Antonio Arjona
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | - Adela Pérez
- Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain
| | | | - Pilar Del Valle
- Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain
| | | | - Guido Mascialino
- School of Psychology, Universidad de Las Américas, Quito, Ecuador
| | | | | | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
| | - Pablo Núñez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
| | | | | | | | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain.,Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain
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Northoff G, Gomez-Pilar J. Overcoming Rest-Task Divide-Abnormal Temporospatial Dynamics and Its Cognition in Schizophrenia. Schizophr Bull 2021; 47:751-765. [PMID: 33305324 PMCID: PMC8661394 DOI: 10.1093/schbul/sbaa178] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Schizophrenia is a complex psychiatric disorder exhibiting alterations in spontaneous and task-related cerebral activity whose relation (termed "state dependence") remains unclear. For unraveling their relationship, we review recent electroencephalographic (and a few functional magnetic resonance imaging) studies in schizophrenia that assess and compare both rest/prestimulus and task states, ie, rest/prestimulus-task modulation. Results report reduced neural differentiation of task-related activity from rest/prestimulus activity across different regions, neural measures, cognitive domains, and imaging modalities. Together, the findings show reduced rest/prestimulus-task modulation, which is mediated by abnormal temporospatial dynamics of the spontaneous activity. Abnormal temporospatial dynamics, in turn, may lead to abnormal prediction, ie, predictive coding, which mediates cognitive changes and psychopathological symptoms, including confusion of internally and externally oriented cognition. In conclusion, reduced rest/prestimulus-task modulation in schizophrenia provides novel insight into the neuronal mechanisms that connect task-related changes to cognitive abnormalities and psychopathological symptoms.
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Affiliation(s)
- Georg Northoff
- Mental Health Center/7th Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, Royal Ottawa Healthcare Group, University of Ottawa, Ottawa ON, Canada
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Valladolid, Spain
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Fernández-Linsenbarth I, Planchuelo-Gómez Á, Díez Á, Arjona-Valladares A, de Luis R, Martín-Santiago Ó, Benito-Sánchez JA, Pérez-Laureano Á, González-Parra D, Montes-Gonzalo C, Melero-Lerma R, Morante SF, Sanz-Fuentenebro J, Gómez-Pilar J, Núñez-Novo P, Molina V. Neurobiological underpinnings of cognitive subtypes in psychoses: A cross-diagnostic cluster analysis. Schizophr Res 2021; 229:102-111. [PMID: 33221149 DOI: 10.1016/j.schres.2020.11.013] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 10/01/2020] [Accepted: 11/12/2020] [Indexed: 02/02/2023]
Abstract
Schizophrenia and bipolar disorder include patients with different characteristics, which may hamper the definition of biomarkers. One of the dimensions with greater heterogeneity among these patients is cognition. Recent studies support the identification of different patients' subgroups along the cognitive domain using cluster analysis. Our aim was to validate clusters defined on the basis of patients' cognitive status and to assess its relation with demographic, clinical and biological measurements. We hypothesized that subgroups characterized by different cognitive profiles would show differences in an array of biological data. Cognitive data from 198 patients (127 with chronic schizophrenia, 42 first episodes of schizophrenia and 29 bipolar patients) were analyzed by a K-means cluster approach and were compared on several clinical and biological variables. We also included 155 healthy controls for further comparisons. A two-cluster solution was selected, including a severely impaired group and a moderately impaired group. The severely impaired group was associated with higher illness duration and symptoms scores, lower thalamus and hippocampus volume, lower frontal connectivity and basal hypersynchrony in comparison to controls and the moderately impaired group. Moreover, both patients' groups showed lower cortical thickness and smaller functional connectivity modulation than healthy controls. This study supports the existence of different cognitive subgroups within the psychoses with different neurobiological underpinnings.
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Affiliation(s)
| | | | - Álvaro Díez
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | | | - Rodrigo de Luis
- Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain
| | | | | | | | | | | | | | | | | | - Javier Gómez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Pablo Núñez-Novo
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain; Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain; Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain.
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Dynamic Changes of Brain Networks during Working Memory Tasks in Schizophrenia. Neuroscience 2020; 453:187-205. [PMID: 33249224 DOI: 10.1016/j.neuroscience.2020.11.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 11/03/2020] [Accepted: 11/04/2020] [Indexed: 12/20/2022]
Abstract
Electroencephalograph (EEG) signals and graph theory measures have been widely used to characterize the brain functional networks of healthy individuals and patients by calculating the correlations between different electrodes over an entire time series. Although EEG signals have a high temporal resolution and can provide relatively stable results, the process of constructing and analyzing brain functional networks is inevitably complicated by high time complexity. Our goal in this research was to distinguish the brain function networks of schizophrenia patients from those of healthy participants during working memory tasks. Consequently, we utilized a method involving microstates, which are each characterized by a unique topography of electric potentials over an entire channel array, to reduce the dimension of the EEG signals during working memory tasks and then compared and analyzed the brain functional networks using the microstates time series (MTS) and original time series (OTS) of the schizophrenia patients and healthy individuals. We found that the right frontal and parietal-occipital regions neurons of the schizophrenia patients were less active than those of the healthy participants during working memory tasks. Notably, compared with OTS, the time needed to construct the brain functional networks was significantly reduced by using MTS. In conclusion, our results show that, like OTS, MTS can well distinguish the brain functional network of schizophrenia patients from those of healthy individuals during working memory tasks while greatly decreasing time complexity. MTS can thus provide a method for characterizing the original time series for the construction and analysis of EEG brain functional networks.
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Molina V, Lubeiro A, de Luis Garcia R, Gomez-Pilar J, Martín-Santiago O, Iglesias-Tejedor M, Holgado-Madera P, Segarra-Echeverría R, Recio-Barbero M, Núñez P, Haidar MK, Fernández-Sevillano J, Sanz-Fuentenebro J. Deficits of entropy modulation of the EEG: A biomarker for altered function in schizophrenia and bipolar disorder? J Psychiatry Neurosci 2020; 45:322-333. [PMID: 32100521 PMCID: PMC7850148 DOI: 10.1503/jpn.190032] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The synchronized activity of distributed neural assemblies — reflected in the electroencephalogram (EEG) — underpins mental function. In schizophrenia, modulation deficits of EEG spectral content during a P300 task have been replicated. The effects of treatment, chronicity and specificity in these deficits and their possible relationship with anatomic connectivity remain to be explored. METHODS We assessed spectral entropy modulation of the EEG during a P300 task in 79 patients with schizophrenia (of those, 31 werein their first episode), 29 patients with bipolar disorder and 48 healthy controls. Spectral entropy values summarize EEG characteristics by quantifying the irregularity of spectral content. In a subsample, we calculated the network architecture of structural connectivity using diffusion tensor imaging and graph-theory parameters. RESULTS We found significant spectral entropy modulation deficits with task performance in patients with chronic or first-episode schizophrenia and in patients with bipolar disorder, without significant pre-stimulus spectral entropy differences. The deficits were unrelated to treatment doses, and spectral entropy modulation did not differ between patients taking or not taking antipsychotics, lithium, benzodiazepines or antidepressants. Structural connectivity values were unrelated to spectral entropy modulation. In patients with schizophrenia, spectral entropy modulation was inversely related to negative symptoms and directly related to verbal memory. LIMITATIONS All patients were taking medication. Patients with bipolar disorder were euthymic and chronic. The cross-sectional nature of this study prevented a more thorough analysis of state versus trait criteria for spectral entropy changes. CONCLUSION Spectral entropy modulation with task performance is decreased in patients with schizophrenia and bipolar disorder. This deficit was not an effect of psychopharmacological treatment or structural connectivity and might reflect a deficit in the synchronization of the neural assemblies that underlie cognitive activity.
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Affiliation(s)
- Vicente Molina
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Alba Lubeiro
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Rodrigo de Luis Garcia
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Javier Gomez-Pilar
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Oscar Martín-Santiago
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - María Iglesias-Tejedor
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Pedro Holgado-Madera
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Rafael Segarra-Echeverría
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - María Recio-Barbero
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Pablo Núñez
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Mahmoud Karim Haidar
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Jessica Fernández-Sevillano
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
| | - Javier Sanz-Fuentenebro
- From the Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain (Molina, Lubeiro); the Psychiatry Service, Clinical Hospital of Valladolid, Valladolid, Spain (Molina, Martín-Santiago); the Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain (Molina); the Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain (de Luis Garcia); the Biomedical Engineering Group, University of Valladolid, Valladolid, Spain (Gomez-Pilar, Núñez); the Neurophysiology Service, Clinical Hospital of Valladolid, Valladolid, Spain (Iglesias-Tejedor); the Psychiatry Service, Doce de Octubre University Hospital, Madrid, Spain (Holgado-Madera, Sanz-Fuentenebro); the Psychiatry Service, Cruces Hospital, Bilbao, Spain (Segarra-Echeverría, Recio-Barbero); and the Psychiatry Service, Santiago Apostol Hospital, Vitoria, Spain (Haidar, Fernández-Sevillano)
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Hernández-García M, Martín-Gómez C, Gómez-García M, Gomez-Pilar J, Núñez-Novo P, Arjona-Valladares A, Alejos-Herrera MV, Lozano-López MT, Gamonal Limcaoco S, Molina-Novoa C, Molina V. Abnormal self-experiences related to a hypersynchronic brain state in schizophrenia. Schizophr Res 2020; 222:538-540. [PMID: 32507377 DOI: 10.1016/j.schres.2020.03.056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 03/25/2020] [Accepted: 03/27/2020] [Indexed: 10/24/2022]
Affiliation(s)
- Marta Hernández-García
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Carmen Martín-Gómez
- Psychiatry Service, Hospital Universitario de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Spain
| | - Marta Gómez-García
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Pablo Núñez-Novo
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Antonio Arjona-Valladares
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain; Instituto de Investigación Biomédica de Salamanca (IBSAL), Spain
| | - María Victoria Alejos-Herrera
- Neurophysiology Service, Hospital Universitario de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Spain
| | - Maria Teresa Lozano-López
- Psychiatry Service, Hospital Universitario de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Spain
| | - Sinta Gamonal Limcaoco
- Psychiatry Service, Hospital Universitario de Salamanca, Instituto de Investigación Biomédica de Salamanca (IBSAL), Spain
| | | | - Vicente Molina
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain; Neurosciences Institute of Castilla y León (INCYL), School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain.
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Adams RA, Bush D, Zheng F, Meyer SS, Kaplan R, Orfanos S, Marques TR, Howes OD, Burgess N. Impaired theta phase coupling underlies frontotemporal dysconnectivity in schizophrenia. Brain 2020; 143:1261-1277. [PMID: 32236540 PMCID: PMC7174039 DOI: 10.1093/brain/awaa035] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 11/21/2019] [Accepted: 12/16/2019] [Indexed: 12/17/2022] Open
Abstract
Frontotemporal dysconnectivity is a key pathology in schizophrenia. The specific nature of this dysconnectivity is unknown, but animal models imply dysfunctional theta phase coupling between hippocampus and medial prefrontal cortex (mPFC). We tested this hypothesis by examining neural dynamics in 18 participants with a schizophrenia diagnosis, both medicated and unmedicated; and 26 age, sex and IQ matched control subjects. All participants completed two tasks known to elicit hippocampal-prefrontal theta coupling: a spatial memory task (during magnetoencephalography) and a memory integration task. In addition, an overlapping group of 33 schizophrenia and 29 control subjects underwent PET to measure the availability of GABAARs expressing the α5 subunit (concentrated on hippocampal somatostatin interneurons). We demonstrate-in the spatial memory task, during memory recall-that theta power increases in left medial temporal lobe (mTL) are impaired in schizophrenia, as is theta phase coupling between mPFC and mTL. Importantly, the latter cannot be explained by theta power changes, head movement, antipsychotics, cannabis use, or IQ, and is not found in other frequency bands. Moreover, mPFC-mTL theta coupling correlated strongly with performance in controls, but not in subjects with schizophrenia, who were mildly impaired at the spatial memory task and no better than chance on the memory integration task. Finally, mTL regions showing reduced phase coupling in schizophrenia magnetoencephalography participants overlapped substantially with areas of diminished α5-GABAAR availability in the wider schizophrenia PET sample. These results indicate that mPFC-mTL dysconnectivity in schizophrenia is due to a loss of theta phase coupling, and imply α5-GABAARs (and the cells that express them) have a role in this process.
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Affiliation(s)
- Rick A Adams
- Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London, WC1N 3AZ, UK.,Division of Psychiatry, University College London, 149 Tottenham Court Road, London, W1T 7NF, UK.,Max Planck-UCL Centre for Computational Psychiatry and Ageing Research, 10-12 Russell Square, London, WC1B 5EH, UK.,Centre for Medical Image Computing, Department of Computer Science, University College London, Malet Place, London, WC1E 7JE, UK.,Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK
| | - Daniel Bush
- Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London, WC1N 3AZ, UK.,Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Fanfan Zheng
- Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London, WC1N 3AZ, UK.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190 Beijing, China
| | - Sofie S Meyer
- Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London, WC1N 3AZ, UK.,Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Raphael Kaplan
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK.,Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Stelios Orfanos
- South West London and St George's Mental Health NHS Trust, Springfield University Hospital, 61 Glenburnie Rd, London SW17 7DJ, UK.,Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, De Crespigny Park, Denmark Hill, London SE5 8AF, UK
| | - Tiago Reis Marques
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK.,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, SE5 8AF, UK
| | - Oliver D Howes
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK.,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, SE5 8AF, UK
| | - Neil Burgess
- Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London, WC1N 3AZ, UK.,Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, WC1N 3BG, UK.,Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
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Planchuelo-Gómez Á, Lubeiro A, Núñez-Novo P, Gomez-Pilar J, de Luis-García R, Del Valle P, Martín-Santiago Ó, Pérez-Escudero A, Molina V. Identificacion of MRI-based psychosis subtypes: Replication and refinement. Prog Neuropsychopharmacol Biol Psychiatry 2020; 100:109907. [PMID: 32113850 DOI: 10.1016/j.pnpbp.2020.109907] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 02/19/2020] [Accepted: 02/25/2020] [Indexed: 11/29/2022]
Abstract
The identification of the cerebral substrates of psychoses such as schizophrenia and bipolar disorder is likely hampered by its biological heterogeneity, which may contribute to the low replication of results in the field. In this study we aimed to replicate in a completely new sample and supplement the results of a previous study with additional data on this topic. In the aforementioned study we identified a schizophrenia cluster characterized by high mean cortical curvature and low cortical thickness, subcortical hypometabolism and progressive negative symptoms. Here, we have used magnetic resonance images from 61 schizophrenia and 28 bipolar patients, as well as 51 healthy controls and a cluster analysis to search for possible subgroups primarily characterized by cerebral structural data. Diffusion tensor imaging (fractional anisotropy, FA), cognition, clinical data and electroencephalographic (EEG) modulation during a P300 task were used to validate the possible clusters. Two clusters of patients were identified. The first cluster (29 schizophrenia and 18 bipolar patients) showed decreased cortical thickness and area values, as well as lower subcortical volumes and higher cortical curvature in some regions, as compared to the second cluster. This first cluster also showed decreased FA in frontal lobe connections and worse cognitive performance. Although this cluster also showed longer illness duration, there were first episode patients in both clusters and treatment doses and types were not different between clusters. Both clusters of patients showed decreased EEG task-related modulation. In conclusion, our data give additional support to a distinct biologically based cluster encompassing schizophrenia and bipolar disorder patients with cortical and subcortical alterations, hampered cortical connectivity and lower cognitive performance.
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Affiliation(s)
- Álvaro Planchuelo-Gómez
- Imaging Processing Laboratory, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Alba Lubeiro
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain
| | - Pablo Núñez-Novo
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Av. Monforte de Lemos, 3-5, 28029 Madrid, Spain
| | - Rodrigo de Luis-García
- Imaging Processing Laboratory, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Pilar Del Valle
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain; Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Óscar Martín-Santiago
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain; Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Adela Pérez-Escudero
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain; Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain; Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain; Neurosciences Institute of Castilla y León (INCYL), Pintor Fernando Gallego, 1, 37007, University of Salamanca, Spain.
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Wang H, Sun Y, Lan F, Liu Y. Altered brain network topology related to working memory in internet addiction. J Behav Addict 2020; 9:325-338. [PMID: 32644933 PMCID: PMC8939409 DOI: 10.1556/2006.2020.00020] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 03/28/2020] [Accepted: 04/15/2020] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND AND AIMS The working memory (WM) ability of internet addicts and the topology underlying the WM processing in internet addiction (IA) are poorly understood. In this study, we employed a graph theoretical framework to characterize the topological properties of the IA brain network in the source cortical space during WM task. METHODS A sample of 24 subjects with IA and 23 matched healthy controls (HCs) performed visual 2-back task. Exact Low Resolution Electromagnetic Tomography was adopted to project the pre-processed EEG signals into source space. Subsequently, Lagged phase synchronization was calculated between all pairs of Brodmann areas, the graph theoretical approaches were then employed to estimate the brain topological properties of all participants during the WM task. RESULTS We found better WM behavioral performance in IA subjects compared with the HCs. Moreover, compared to the HC group, more integrated and hierarchical brain network was revealed in the IA subjects in alpha band. And altered regional centrality was mainly resided in frontal and limbic lobes. In addition, significant relationships between the IA severity and the significant altered graph indices were found. CONCLUSIONS In conclusion, these findings provide evidence to support the notion that altered topological configuration may underline changed WM function observed in IA.
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Affiliation(s)
- Hongxia Wang
- School of Psychology, Liaoning Normal University, Da Lian, 116029, China,Department of Psychology, Renmin University of China, Beijing, 100872, China
| | - Yan Sun
- School of Psychology, Liaoning Normal University, Da Lian, 116029, China,Corresponding author’s e-mail:
| | - Fan Lan
- School of Psychology, Liaoning Normal University, Da Lian, 116029, China
| | - Yan Liu
- School of Psychology, Liaoning Normal University, Da Lian, 116029, China
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18
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Cea-Cañas B, Gomez-Pilar J, Núñez P, Rodríguez-Vázquez E, de Uribe N, Díez Á, Pérez-Escudero A, Molina V. Connectivity strength of the EEG functional network in schizophrenia and bipolar disorder. Prog Neuropsychopharmacol Biol Psychiatry 2020; 98:109801. [PMID: 31682892 DOI: 10.1016/j.pnpbp.2019.109801] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 09/16/2019] [Accepted: 10/29/2019] [Indexed: 01/22/2023]
Abstract
The application of graph theory measures in the study of functional brain networks allows for the description of their general properties and their alterations in mental illness. Among these measures, connectivity strength (CS) estimates the degree of functional connectivity of the whole network. Previous studies in schizophrenia patients have reported higher baseline CS values and modulation deficits in EEG spectral properties during cognitive activity. The specificity of these alterations and their relationships with pharmacological treatments remain unknown. Therefore, in the present study, we assessed functional CS on EEG-based brain networks in 79 schizophrenia and 29 bipolar patients in addition to 63 healthy controls. The subjects performed a P300 task during the EEG recordings from which the pre-stimulus and the task-related modulation CS values were computed in the global and theta bands. These values were compared between the groups and between the patients who had and had not received different treatments. The global band pre-stimulus CS was significantly higher in the schizophrenia group compared with the bipolar and control groups. Theta band CS modulation was decreased in schizophrenia and bipolar patients. Treatment with antipsychotics, lithium, benzodiazepines, and anticonvulsants did not significantly alter these CS values. The first-episode and chronic schizophrenia patients did not show significant differences in CS values. Higher global band pre-stimulus CS values were associated with worse general cognition in schizophrenia patients. These data support increased connectivity in the whole-brain network that is specific to schizophrenia and suggest a general hyper-synchronized basal state that might hamper cognition in this syndrome.
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Affiliation(s)
- Benjamín Cea-Cañas
- Clinical Neurophysiology Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Pablo Núñez
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Eva Rodríguez-Vázquez
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Nieves de Uribe
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Álvaro Díez
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain
| | - Adela Pérez-Escudero
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain
| | - Vicente Molina
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, 47003 Valladolid, Spain; Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain; Neurosciences Institute of Castilla y León (INCYL), School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, 47005 Valladolid, Spain.
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19
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Predicting response to electroconvulsive therapy combined with antipsychotics in schizophrenia using multi-parametric magnetic resonance imaging. Schizophr Res 2020; 216:262-271. [PMID: 31826827 DOI: 10.1016/j.schres.2019.11.046] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 09/04/2019] [Accepted: 11/25/2019] [Indexed: 12/23/2022]
Abstract
Electroconvulsive therapy (ECT) has been shown to be effective in schizophrenia, particularly when rapid symptom reduction is needed or in cases of resistance to drug treatment. However, there are no markers available to predict response to ECT. Here, we examine whether multi-parametric magnetic resonance imaging (MRI)-based radiomic features can predict response to ECT for individual patients. A total of 57 treatment-resistant schizophrenia patients, or schizophrenia patients with an acute episode or suicide attempts were randomly divided into primary (42 patients) and test (15 patients) cohorts. We collected T1-weighted structural MRI and diffusion MRI for 57 patients before receiving ECT and extracted 600 radiomic features for feature selection and prediction. To predict a continuous improvement in symptoms (ΔPANSS), the prediction process was performed with a support vector regression model based on a leave-one-out cross-validation framework in primary cohort and was tested in test cohort. The multi-parametric MRI-based radiomic model, including four structural MRI feature from left inferior frontal gyrus, right insula, left middle temporal gyrus and right superior temporal gyrus respectively and six diffusion MRI features from tracts connecting frontal or temporal gyrus possessed a low root mean square error of 15.183 in primary cohort and 14.980 in test cohort. The Pearson's correlation coefficients between predicted and actual values were 0.671 and 0.777 respectively. These results demonstrate that multi-parametric MRI-based radiomic features may predict response to ECT for individual patients. Such features could serve as prognostic neuroimaging biomarkers that provide a critical step toward individualized treatment response prediction in schizophrenia.
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20
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Alvarez-Astorga A, Sotelo E, Lubeiro A, de Luis R, Gomez-Pilar J, Becoechea B, Molina V. Social cognition in psychosis: Predictors and effects of META-cognitive training. Prog Neuropsychopharmacol Biol Psychiatry 2019; 94:109672. [PMID: 31228639 DOI: 10.1016/j.pnpbp.2019.109672] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 06/07/2019] [Accepted: 06/17/2019] [Indexed: 11/25/2022]
Abstract
Social cognition deficits are found in schizophrenia and bipolar disorder, but its neural underpinnings are poorly understood. Given the complexity of psychological functions underlying this kind of cognition, we hypothesized that alterations in global structural connectivity could contribute to those deficits. To test this hypothesis, we studied a group of schizophrenia and bipolar patients with connectomics based on diffusion magnetic resonance imaging and assessments of general and social cognition. The latter was assessed using the Mayer, Salovey and Caruso Emotional Intelligence Test (MSCEIT) for emotional intelligence and the Spanish Group for Schizophrenia Treatment Optimization (Grupo Español para la OPtimización del Tratamiento de la Esquizofrenia, GEOPTE) test for behavioral aspects of social cognition. Graph theory applied to fractional anisotropy for the connections among cortical regions was used to obtain the small-world (SW) index of the structural connectivity network. In addition, we assessed the possibility of predicting the response of social cognition deficits to Meta-cognitive Training based on their possible underpinnings in a subgroup of patients. Patients showed lower scores in emotional intelligence and behavioral social cognition. MSCEIT scores were associated with SW index and working memory, and GEOPTE scores were related to verbal memory. Improvement in social cognition after Meta-cognitive Training was associated with lower scores of the social cognition in the baseline, according to the GEOPTE scale. Our findings support structural connectivity as one of the factors underlying emotional intelligence in schizophrenia, and the use of Meta-cognitive Training to improve social cognition in patients with larger deficits.
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Affiliation(s)
| | - Eva Sotelo
- Psychiatry Service, Clinical University Hospital of Valladolid, Valladolid, Spain
| | - Alba Lubeiro
- Psychiatry Department, School of Medicine, University of Valladolid, Spain
| | - Rodrigo de Luis
- Imaging Processing Laboratory, University of Valladolid, Valladolid, Spain
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
| | - Begoña Becoechea
- Psychiatry Service, Clinical University Hospital of Valladolid, Valladolid, Spain
| | - Vicente Molina
- Psychiatry Service, Clinical University Hospital of Valladolid, Valladolid, Spain; Psychiatry Department, School of Medicine, University of Valladolid, Spain.
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21
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Gomez-Pilar J, Poza J, Gómez C, Northoff G, Lubeiro A, Cea-Cañas BB, Molina V, Hornero R. Altered predictive capability of the brain network EEG model in schizophrenia during cognition. Schizophr Res 2018; 201:120-129. [PMID: 29764760 DOI: 10.1016/j.schres.2018.04.043] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 04/10/2018] [Accepted: 04/29/2018] [Indexed: 12/21/2022]
Abstract
The study of the mechanisms involved in cognition is of paramount importance for the understanding of the neurobiological substrates in psychiatric disorders. Hence, this research is aimed at exploring the brain network dynamics during a cognitive task. Specifically, we analyze the predictive capability of the pre-stimulus theta activity to ascertain the functional brain dynamics during cognition in both healthy and schizophrenia subjects. Firstly, EEG recordings were acquired during a three-tone oddball task from fifty-one healthy subjects and thirty-five schizophrenia patients. Secondly, phase-based coupling measures were used to generate the time-varying functional network for each subject. Finally, pre-stimulus network connections were iteratively modified according to different models of network reorganization. This adjustment was applied by minimizing the prediction error through recurrent iterations, following the predictive coding approach. Both controls and schizophrenia patients follow a reinforcement of the secondary neural pathways (i.e., pathways between cortical brain regions weakly connected during pre-stimulus) for most of the subjects, though the ratio of controls that exhibited this behavior was statistically significant higher than for patients. These findings suggest that schizophrenia is associated with an impaired ability to modify brain network configuration during cognition. Furthermore, we provide direct evidence that the changes in phase-based brain network parameters from pre-stimulus to cognitive response in the theta band are closely related to the performance in important cognitive domains. Our findings not only contribute to the understanding of healthy brain dynamics, but also shed light on the altered predictive neuronal substrates in schizophrenia.
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Affiliation(s)
- Javier Gomez-Pilar
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain.
| | - Jesús Poza
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain; INCYL, Instituto de Neurociencias de Castilla y León, University of Salamanca, Salamanca, Spain
| | - Carlos Gómez
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
| | - Alba Lubeiro
- Psychiatry Department, University Hospital of Valladolid, Valladolid, Spain
| | | | - Vicente Molina
- INCYL, Instituto de Neurociencias de Castilla y León, University of Salamanca, Salamanca, Spain; Psychiatry Department, University Hospital of Valladolid, Valladolid, Spain
| | - Roberto Hornero
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain; INCYL, Instituto de Neurociencias de Castilla y León, University of Salamanca, Salamanca, Spain
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22
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Gomez-Pilar J, de Luis-García R, Lubeiro A, de la Red H, Poza J, Núñez P, Hornero R, Molina V. Relations between structural and EEG-based graph metrics in healthy controls and schizophrenia patients. Hum Brain Mapp 2018; 39:3152-3165. [PMID: 29611297 DOI: 10.1002/hbm.24066] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 03/06/2018] [Accepted: 03/19/2018] [Indexed: 12/27/2022] Open
Abstract
Our aim was to assess structural and functional networks in schizophrenia patients; and the possible prediction of the latter based on the former. The possible dependence of functional network properties on structural alterations has not been analyzed in schizophrenia. We applied averaged path-length (PL), clustering coefficient, and density (D) measurements to data from diffusion magnetic resonance and electroencephalography in 39 schizophrenia patients and 79 controls. Functional data were collected for the global and theta frequency bands during an odd-ball task, prior to stimulus delivery and at the corresponding processing window. Connectivity matrices were constructed from tractography and registered cortical segmentations (structural) and phase-locking values (functional). Both groups showed a significant electroencephalographic task-related modulation (change between prestimulus and response windows) in the global and theta bands. Patients showed larger structural PL and prestimulus density in the global and theta bands, and lower PL task-related modulation in the theta band. Structural network values predicted prestimulus global band values in controls and global band task-related modulation in patients. Abnormal functional values found in patients (prestimulus density in the global and theta bands and task-related modulation in the theta band) were not predicted by structural data in this group. Structural and functional network abnormalities respectively predicted cognitive performance and positive symptoms in patients. Taken together, the alterations in the structural and functional theta networks in the patients and the lack of significant relations between these alterations, suggest that these types of network abnormalities exist in different groups of schizophrenia patients.
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Affiliation(s)
- Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Rodrigo de Luis-García
- Imaging Processing Laboratory, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Alba Lubeiro
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, Valladolid, 47005, Spain
| | - Henar de la Red
- Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, Valladolid, 47003, Spain
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.,Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, Valladolid, 47003, Spain.,Neurosciences Institute of Castilla y León (INCYL), Pintor Fernando Gallego, 1, 37007 University of Salamanca, 37007, Salamanca, Spain.,IMUVA, Mathematics Research Institute, University of Valladolid, Valladolid, Spain
| | - Pablo Núñez
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
| | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.,Neurosciences Institute of Castilla y León (INCYL), Pintor Fernando Gallego, 1, 37007 University of Salamanca, 37007, Salamanca, Spain.,IMUVA, Mathematics Research Institute, University of Valladolid, Valladolid, Spain
| | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Av. Ramón y Cajal, 7, Valladolid, 47005, Spain.,Psychiatry Service, Clinical Hospital of Valladolid, Ramón y Cajal, 3, Valladolid, 47003, Spain.,Neurosciences Institute of Castilla y León (INCYL), Pintor Fernando Gallego, 1, 37007 University of Salamanca, 37007, Salamanca, Spain
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