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Ventura B, Çatal Y, Wolman A, Buccellato A, Cooper AC, Northoff G. Intrinsic neural timescales exhibit different lengths in distinct meditation techniques. Neuroimage 2024; 297:120745. [PMID: 39069224 DOI: 10.1016/j.neuroimage.2024.120745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 07/12/2024] [Accepted: 07/18/2024] [Indexed: 07/30/2024] Open
Abstract
Meditation encompasses a range of practices employing diverse induction techniques, each characterized by a distinct attentional focus. In Mantra meditation, for instance, practitioners direct their attention narrowly to a given sentence that is recursively repeated, while other forms of meditation such as Shoonya meditation are induced by a wider attentional focus. Here we aimed to identify the neural underpinnings and correlates associated with this spectrum of distinct attentional foci. To accomplish this, we used EEG data to estimate the brain's intrinsic neural timescales (INTs), that is, its temporal windows of activity, by calculating the Autocorrelation Window (ACW) of the EEG signal. The autocorrelation function measures the similarity of a timeseries with a time-lagged version of itself by correlating the signal with itself on different time lags, consequently providing an estimation of INTs length. Therefore, through using the ACW metric, our objective was to explore whether there is a correspondence between the length of the brain's temporal windows of activity and the width of the attentional scope during various meditation techniques. This was performed on three groups of highly proficient practitioners belonging to different meditation traditions, as well as a meditation-naïve control group. Our results indicated that practices with a wider attentional focus, like Shoonya meditation, exhibit longer ACW durations compared to practices requiring a narrower attentional focus, such as Mantra meditation or body-scanning Vipassana meditation. Together, we demonstrated that distinct meditation techniques with varying widths of attentional foci exhibit unique durations in their brain's INTs. This may suggest that the width of the attentional scope during meditation relates and corresponds to the width of the brain's temporal windows in its neural activity. SIGNIFICANCE STATEMENT: Our research uncovered the neural mechanisms that underpin the attentional foci in various meditation techniques. We revealed that distinct meditation induction techniques, featured by their range of attentional widths, are characterized by varying lengths of intrinsic neural timescales (INTs) within the brain, as measured by the Autocorrelation Window function. This finding may bridge the gap between the width of attentional windows (subjective) and the width of the temporal windows in the brain's neural activity (objective) during different meditation techniques, offering a new understanding of how cognitive and neural processes are related to each other. This work holds significant implications, especially in the context of the increasing use of meditation in mental health and well-being interventions. By elucidating the distinct neural foundations of different meditation techniques, our research aims to pave the way for developing more tailored and effective meditation-based treatments.
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Affiliation(s)
- Bianca Ventura
- School of Psychology, University of Ottawa, 136 Jean-Jacques Lussier, Ottawa K1N 6N5, ON, Canada.
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa K1Z 7K4, ON, Canada.
| | - Angelika Wolman
- School of Psychology, University of Ottawa, 136 Jean-Jacques Lussier, Ottawa K1N 6N5, ON, Canada.
| | - Andrea Buccellato
- Padova Neuroscience Center, University of Padova, Via Orus 2/B, Padova 35129, Italy; Department of General Psychology, University of Padova, Via Venezia, 8, 35131 Padova, Italy.
| | - Austin Clinton Cooper
- Integrated Program of Neuroscience, Room 302, Irving Ludmer Building, 1033 Pine Avenue W., McGill University, Montreal, QC H3A 1A1, Canada.
| | - Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa K1Z 7K4, ON, Canada.
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Murai SA, Mano T, Sanes JN, Watanabe T. Atypical intrinsic neural timescale in the left angular gyrus in Alzheimer's disease. Brain Commun 2024; 6:fcae199. [PMID: 38993284 PMCID: PMC11227993 DOI: 10.1093/braincomms/fcae199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 04/18/2024] [Accepted: 06/07/2024] [Indexed: 07/13/2024] Open
Abstract
Alzheimer's disease is characterized by cognitive impairment and progressive brain atrophy. Recent human neuroimaging studies reported atypical anatomical and functional changes in some regions in the default mode network in patients with Alzheimer's disease, but which brain area of the default mode network is the key region whose atrophy disturbs the entire network activity and consequently contributes to the symptoms of the disease remains unidentified. Here, in this case-control study, we aimed to identify crucial neural regions that mediated the phenotype of Alzheimer's disease, and as such, we examined the intrinsic neural timescales-a functional metric to evaluate the capacity to integrate diverse neural information-and grey matter volume of the regions in the default mode network using resting-state functional MRI images and structural MRI data obtained from individuals with Alzheimer's disease and cognitively typical people. After confirming the atypically short neural timescale of the entire default mode network in Alzheimer's disease and its link with the symptoms of the disease, we found that the shortened neural timescale of the default mode network was associated with the aberrantly short neural timescale of the left angular gyrus. Moreover, we revealed that the shortened neural timescale of the angular gyrus was correlated with the atypically reduced grey matter volume of this parietal region. Furthermore, we identified an association between the neural structure, brain function and symptoms and proposed a model in which the reduced grey matter volume of the left angular gyrus shortened the intrinsic neural time of the region, which then destabilized the entire neural timescale of the default mode network and resultantly contributed to cognitive decline in Alzheimer's disease. These findings highlight the key role of the left angular gyrus in the anatomical and functional aetiology of Alzheimer's disease.
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Affiliation(s)
- Shota A Murai
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study, Bunkyo City, Tokyo 113-0033, Japan
| | - Tatsuo Mano
- Department of Degenerative Neurological Diseases, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan
| | - Jerome N Sanes
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Carney Institute for Brain Science, Brown University, Providence, RI 02912, USA
- Center for Neurorestoration and Neurotechnology, Veterans Affairs Providence Healthcare System, Providence, RI 02908, USA
| | - Takamitsu Watanabe
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study, Bunkyo City, Tokyo 113-0033, Japan
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Geenjaar E, Kim D, Calhoun V. Providing context: Extracting non-linear and dynamic temporal motifs from brain activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.27.600937. [PMID: 38979316 PMCID: PMC11230350 DOI: 10.1101/2024.06.27.600937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Approaches studying the dynamics of resting-state functional magnetic resonance imaging (rs-fMRI) activity often focus on time-resolved functional connectivity (tr-FC). While many approaches have been proposed, these typically focus on linear approaches like computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. This has the advantage of allowing our model to capture differences at multiple temporal scales. For the timestep-specific scale, which has higher temporal precision, we find significant differences between schizophrenia patients and control subjects in their temporal step distance through our model's latent space. We also find that window-specific embeddings, or as we refer to them, context embeddings, more accurately separate windows from schizophrenia patients and control subjects than the standard tr-FC approach. Moreover, we find that for individuals with schizophrenia, our model's context embedding space is significantly correlated with both age and symptom severity. Interestingly, patients appear to spend more time in three clusters, one closer to controls which shows increased visual-sensorimotor, cerebellar-subcortical, and reduced cerebellar-sensorimotor functional network connectivity (FNC), an intermediate station showing increased subcortical-sensorimotor FNC, and one that shows decreased visual-sensorimotor, decreased subcortical-sensorimotor, and increased visual-subcortical domains. We verify that our model captures features that are complementary to - but not the same as - standard tr-FC features. Our model can thus help broaden the neuroimaging toolset in analyzing fMRI dynamics and shows potential as an approach for finding psychiatric links that are more sensitive to individual and group characteristics.
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Affiliation(s)
- Eloy Geenjaar
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, 30303, USA
| | - Donghyun Kim
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, 30303, USA
| | - Vince Calhoun
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, 30303, USA
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4
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Zhang A, Wengler K, Zhu X, Horga G, Goldberg TE, Lee S. Altered Hierarchical Gradients of Intrinsic Neural Timescales in Mild Cognitive Impairment and Alzheimer's Disease. J Neurosci 2024; 44:e2024232024. [PMID: 38658167 PMCID: PMC11209657 DOI: 10.1523/jneurosci.2024-23.2024] [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: 10/19/2023] [Revised: 03/08/2024] [Accepted: 04/12/2024] [Indexed: 04/26/2024] Open
Abstract
Alzheimer's disease (AD) is a devastating neurodegenerative disease that affects millions of seniors in the United States. Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to study neurophysiology in AD and its prodromal condition, mild cognitive impairment (MCI). The intrinsic neural timescale (INT), which can be estimated through the magnitude of the autocorrelation of neural signals from rs-fMRI, is thought to quantify the duration that neural information is stored in a local circuit. Such heterogeneity of the timescales forms a basis of the brain functional hierarchy and captures an aspect of circuit dynamics relevant to excitation/inhibition balance, which is broadly relevant for cognitive functions. Given that, we applied rs-fMRI to test whether distinct changes of INT at different hierarchies are present in people with MCI, those progressing to AD (called Converter), and AD patients of both sexes. Linear mixed-effect model was implemented to detect altered hierarchical gradients across populations followed by pairwise comparisons to identify regional differences. High similarities between AD and Converter were observed. Specifically, the inferior temporal, caudate, and pallidum areas exhibit significant alterations in both AD and Converter. Distinct INT-related pathological changes in MCI and AD were found. For AD/Converter, neural information is stored for a longer time in lower hierarchical areas, while higher levels of hierarchy seem to be preferentially impaired in MCI leading to a less pronounced hierarchical gradient. These results inform that the INT holds great potential as an additional measure for AD prediction, even a stable biomarker for clinical diagnosis.
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Affiliation(s)
- Aiying Zhang
- New York State Psychiatric Institute, New York, New York 10032
- Department of Psychiatry, Columbia University, New York, New York 10032
| | - Kenneth Wengler
- New York State Psychiatric Institute, New York, New York 10032
- Department of Psychiatry, Columbia University, New York, New York 10032
| | - Xi Zhu
- New York State Psychiatric Institute, New York, New York 10032
- Department of Psychiatry, Columbia University, New York, New York 10032
| | - Guillermo Horga
- New York State Psychiatric Institute, New York, New York 10032
- Department of Psychiatry, Columbia University, New York, New York 10032
| | - Terry E Goldberg
- New York State Psychiatric Institute, New York, New York 10032
- Department of Psychiatry, Columbia University, New York, New York 10032
- Department of Anesthesiology, Columbia University Irving Medical Center, New York, New York 10032
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York 10032
| | - Seonjoo Lee
- New York State Psychiatric Institute, New York, New York 10032
- Department of Psychiatry, Columbia University, New York, New York 10032
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York 10032
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Bryant AG, Aquino K, Parkes L, Fornito A, Fulcher BD. Extracting interpretable signatures of whole-brain dynamics through systematic comparison. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.573372. [PMID: 38915560 PMCID: PMC11195072 DOI: 10.1101/2024.01.10.573372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures. While simple statistical representations of fMRI dynamics performed surprisingly well (e.g., properties within a single brain region), combining intra-regional properties with inter-regional coupling generally improved performance, underscoring the distributed, multifaceted changes to fMRI dynamics in neuropsychiatric disorders. The comprehensive, data-driven method introduced here enables systematic identification and interpretation of quantitative dynamical signatures of multivariate time-series data, with applicability beyond neuroimaging to diverse scientific problems involving complex time-varying systems.
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Affiliation(s)
- Annie G. Bryant
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
| | - Kevin Aquino
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
- Brain Key Incorporated, San Francisco, CA, USA
| | - Linden Parkes
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
- Turner Institute for Brain & Mental Health, Monash University, VIC, Australia
| | - Alex Fornito
- Turner Institute for Brain & Mental Health, Monash University, VIC, Australia
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
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Zhang M, Niu X, Tao Q, Sun J, Dang J, Wang W, Han S, Zhang Y, Cheng J. Altered intrinsic neural timescales and neurotransmitter activity in males with tobacco use disorder. J Psychiatr Res 2024; 175:446-454. [PMID: 38797041 DOI: 10.1016/j.jpsychires.2024.05.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/07/2024] [Accepted: 05/08/2024] [Indexed: 05/29/2024]
Abstract
Previous researches of tobacco use disorder (TUD) has overlooked the hierarchy of cortical functions and single modality design separated the relationship between macroscopic neuroimaging aberrance and microscopic molecular basis. At present, intrinsic timescale gradient of TUD and its molecular features are not fully understood. Our study recruited 146 male subjects, including 44 heavy smokers, 50 light smokers and 52 non-smokers, then obtained their rs-fMRI data and clinical scales related to smoking. Intrinsic neural timescale (INT) method was performed to describe how long neural information was stored in a brain region by calculating the autocorrelation function (ACF) of each voxel to examine the difference in the ability of information integration among the three groups. Then, correlation analyses were conducted to explore the relationship between INT abnormalities and clinical scales of smokers. Finally, cross-modal JuSpace toolbox was used to investigate the association between INT aberrance and the expression of specific receptor/transporters. Compared to healthy controls, TUD subjects displayed decreased INT in control network (CN), default mode network (DMN), sensorimotor areas and visual cortex, and such trend of decreasing INT was more pronounced in heavy smokers. Moreover, various neurotransmitters (including dopaminergic, acetylcholine and μ-opioid receptors) were involved in the molecular mechanism of timescale decreasing and differed in heavy and light smokers. These findings supplied novel insights into the brain functional aberrance in TUD from an intrinsic neural dynamic perspective and confirm INT was a potential neurobiological marker. And also established the connection between macroscopic imaging aberrance and microscopic molecular changes in TUD.
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Affiliation(s)
- Mengzhe Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Qiuying Tao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Jieping Sun
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, China.
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Hirsch F, Bumanglag Â, Zhang Y, Wohlschlaeger A. Diverging functional connectivity timescales: Capturing distinct aspects of cognitive performance in early psychosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.07.24306932. [PMID: 38766002 PMCID: PMC11100938 DOI: 10.1101/2024.05.07.24306932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Background Psychosis spectrum disorders (PSDs) are marked by cognitive impairments, the neurobiological correlates of which remain poorly understood. Here, we investigate the entropy of time-varying functional connectivity (TVFC) patterns from resting-state fMRI (rfMRI) as potential biomarker for cognitive performance in PSDs. By combining our results with multimodal reference data, we hope to generate new insights into the mechanisms underlying cognitive dysfunction in PSDs. We hypothesized that low-entropy TVFC patterns (LEN) would be more behaviorally informative than high-entropy TVFC patterns (HEN), especially for tasks that require extensive integration across diverse cognitive subdomains. Methods rfMRI and behavioral data from 97 patients in the early phases of psychosis and 53 controls were analyzed. Positron-Emission Tomography (PET) and magnetoencephalography (MEG) data were taken from a public repository (Hansen et al., 2022). Multivariate analyses were conducted to examine relationships between TVFC patterns at multiple spatial scales and cognitive performance in patients. Results Compared to HEN, LEN explained significantly more cognitive variance on average in PSD patients, driven by superior encoding of information on psychometrically more integrated tasks. HEN better captured information in specific subdomains of executive functioning. Nodal HEN-LEN transitions were spatially aligned with neurobiological gradients reflecting monoaminergic transporter densities and MEG beta power. Exploratory analyses revealed a close statistical relationship between LEN and positive PSD symptoms. Conclusion Our entropy-based analysis of TVFC patterns dissociates distinct aspects of cognition in PSDs. By linking topographies of neurotransmission and oscillatory dynamics with cognitive performance, it enhances our understanding of the mechanisms underlying cognitive deficits in PSDs. CRediT Authorship Contribution Statement Fabian Hirsch: Conceptualization, Methodology, Software, Formal analysis, Writing - Original Draft, Writing - Review & Editing, Visualization; Ângelo Bumanglag: Methodology, Software, Formal analysis, Writing - Review & Editing; Yifei Zhang: Methodology, Software, Formal analysis, Writing - Review & Editing; Afra Wohlschlaeger: Methodology, Writing - Review & Editing, Supervision, Project administration.
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Wolman A, Çatal Y, Klar P, Steffener J, Northoff G. Repertoire of timescales in uni - and transmodal regions mediate working memory capacity. Neuroimage 2024; 291:120602. [PMID: 38579900 DOI: 10.1016/j.neuroimage.2024.120602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 04/01/2024] [Accepted: 04/02/2024] [Indexed: 04/07/2024] Open
Abstract
Working memory (WM) describes the dynamic process of maintenance and manipulation of information over a certain time delay. Neuronally, WM recruits a distributed network of cortical regions like the visual and dorsolateral prefrontal cortex as well as the subcortical hippocampus. How the input dynamics and subsequent neural dynamics impact WM remains unclear though. To answer this question, we combined the analysis of behavioral WM capacity with measuring neural dynamics through task-related power spectrum changes, e.g., median frequency (MF) in functional magnetic resonance imaging (fMRI). We show that the processing of the input dynamics, e.g., the task structure's specific timescale, leads to changes in the unimodal visual cortex's corresponding timescale which also relates to working memory capacity. While the more transmodal hippocampus relates to working memory capacity through its balance across multiple timescales or frequencies. In conclusion, we here show the relevance of both input dynamics and different neural timescales for WM capacity in uni - and transmodal regions like visual cortex and hippocampus for the subject's WM performance.
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Affiliation(s)
- Angelika Wolman
- School of Psychology, University of Ottawa, 136 Jean-Jacques Lussier, Ottawa, ON K1N 6N5, Canada; Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre, University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada.
| | - Yasir Çatal
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre, University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Philipp Klar
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Jason Steffener
- Interdisciplinary School of Health Science, University of Ottawa, 200 Lees Ave, Ottawa, ON K1N 6N5, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre, University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
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Harding JN, Wolpe N, Brugger SP, Navarro V, Teufel C, Fletcher PC. A new predictive coding model for a more comprehensive account of delusions. Lancet Psychiatry 2024; 11:295-302. [PMID: 38242143 DOI: 10.1016/s2215-0366(23)00411-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/01/2023] [Accepted: 11/30/2023] [Indexed: 01/21/2024]
Abstract
Attempts to understand psychosis-the experience of profoundly altered perceptions and beliefs-raise questions about how the brain models the world. Standard predictive coding approaches suggest that it does so by minimising mismatches between incoming sensory evidence and predictions. By adjusting predictions, we converge iteratively on a best guess of the nature of the reality. Recent arguments have shown that a modified version of this framework-hybrid predictive coding-provides a better model of how healthy agents make inferences about external reality. We suggest that this more comprehensive model gives us a richer understanding of psychosis compared with standard predictive coding accounts. In this Personal View, we briefly describe the hybrid predictive coding model and show how it offers a more comprehensive account of the phenomenology of delusions, thereby providing a potentially powerful new framework for computational psychiatric approaches to psychosis. We also make suggestions for future work that could be important in formalising this novel perspective.
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Affiliation(s)
- Jessica Niamh Harding
- School of Clinical Medicine, University of Cambridge, Cambridge, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - Noham Wolpe
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Department of Physical Therapy, The Stanley Steyer School of Health Professions, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Stefan Peter Brugger
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK; Centre for Academic Mental Health, Bristol Medical school, University of Bristol, Bristol, UK
| | - Victor Navarro
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Christoph Teufel
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Paul Charles Fletcher
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK; Wellcome Trust MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
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Zheng R, Bu C, Chen Y, Wei Y, Zhou B, Jiang Y, Zhu C, Wang K, Wang C, Li S, Han S, Zhang Y, Cheng J. Decreased intrinsic neural timescale in treatment-naïve adolescent depression. J Affect Disord 2024; 348:389-397. [PMID: 38160888 DOI: 10.1016/j.jad.2023.12.048] [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: 07/23/2023] [Revised: 11/25/2023] [Accepted: 12/23/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is mainly characterized by its core dysfunction in higher-order brain cortices involved in emotional and cognitive processes, whose neurobiological basis remains unclear. In this study, we applied a relatively new developed resting-state functional magnetic resonance imaging (rs-fMRI) method of intrinsic neural timescale (INT), which reflects how long neural information is stored in a local brain area and reflects an ability of information integration, to investigate the local intrinsic neural dynamics using univariate and multivariate analyses in adolescent depression. METHOD Based on the rs-fMRI data of sixty-six treatment-naïve adolescents with MDD and fifty-two well-matched healthy controls (HCs), we calculated an INT by assessing the magnitude of autocorrelation of the resting-state brain activity, and then compared the difference of INT between the two groups. Correlation between abnormal INT and clinical features was performed. We also utilized multivariate pattern analysis to determine whether INT could differentiate MDD patients from HCs at the individual level. RESULT Compared with HCs, patients with MDD showed shorter INT widely distributed in cortical and partial subcortical regions. Interestingly, the decreased INT in the left hippocampus was related to disease severity of MDD. Furthermore, INT can distinguish MDD patients from HCs with the most discriminative regions located in the dorsolateral prefrontal cortex, angular, middle occipital gyrus, and cerebellar posterior lobe. CONCLUSION Our research aids in advancing understanding the brain abnormalities of treatment-naïve adolescents with MDD from the perspective of the local neural dynamics, highlighting the significant role of INT in understanding neurophysiological mechanisms. This study shows that the altered intrinsic timescales of local neural signals widely distributed in higher-order brain cortices regions may be the neurodynamic basis of cognitive and emotional disturbances in MDD patients, and provides preliminary support for the suggestion that these could be used to aid the identification of MDD patients in clinical practice.
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Affiliation(s)
- Ruiping Zheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Chunxiao Bu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Chendi Zhu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Henan University of Chinese Medicine, PR China
| | - Kefan Wang
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Shuying Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China.
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Mukherjee A, Halassa MM. The Associative Thalamus: A Switchboard for Cortical Operations and a Promising Target for Schizophrenia. Neuroscientist 2024; 30:132-147. [PMID: 38279699 PMCID: PMC10822032 DOI: 10.1177/10738584221112861] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2024]
Abstract
Schizophrenia is a brain disorder that profoundly perturbs cognitive processing. Despite the success in treating many of its symptoms, the field lacks effective methods to measure and address its impact on reasoning, inference, and decision making. Prefrontal cortical abnormalities have been well documented in schizophrenia, but additional dysfunction in the interactions between the prefrontal cortex and thalamus have recently been described. This dysfunction may be interpreted in light of parallel advances in neural circuit research based on nonhuman animals, which show critical thalamic roles in maintaining and switching prefrontal activity patterns in various cognitive tasks. Here, we review this basic literature and connect it to emerging innovations in clinical research. We highlight the value of focusing on associative thalamic structures not only to better understand the very nature of cognitive processing but also to leverage these circuits for diagnostic and therapeutic development in schizophrenia. We suggest that the time is right for building close bridges between basic thalamic research and its clinical translation, particularly in the domain of cognition and schizophrenia.
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Affiliation(s)
- Arghya Mukherjee
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael M Halassa
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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12
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Lurie DJ, Pappas I, D'Esposito M. Cortical timescales and the modular organization of structural and functional brain networks. Hum Brain Mapp 2024; 45:e26587. [PMID: 38339903 PMCID: PMC10823764 DOI: 10.1002/hbm.26587] [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: 05/25/2023] [Revised: 12/01/2023] [Accepted: 12/21/2023] [Indexed: 02/12/2024] Open
Abstract
Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the "timescale" over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.
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Affiliation(s)
- Daniel J. Lurie
- Department of PsychologyUniversity of CaliforniaBerkeleyCaliforniaUSA
- Department of Biomedical Informatics University of Pittsburgh School of Medicine PittsburghPennsylvaniaUSA
| | - Ioannis Pappas
- Department of Neurology, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Mark D'Esposito
- Department of Psychology and Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
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13
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Ibanez A, Northoff G. Intrinsic timescales and predictive allostatic interoception in brain health and disease. Neurosci Biobehav Rev 2024; 157:105510. [PMID: 38104789 PMCID: PMC11184903 DOI: 10.1016/j.neubiorev.2023.105510] [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: 09/07/2023] [Revised: 11/29/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023]
Abstract
The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.
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Affiliation(s)
- Agustin Ibanez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, USA; Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Trinity College Dublin, Dublin, Ireland.
| | - Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China; Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, People's Republic of China; Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada.
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14
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Yang J, Shen L, Long Q, Li W, Zhang W, Chen Q, Han B. Electrical stimulation induced self-related auditory hallucinations correlate with oscillatory power change in the default mode network. Cereb Cortex 2024; 34:bhad473. [PMID: 38061695 DOI: 10.1093/cercor/bhad473] [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: 08/25/2023] [Revised: 11/17/2023] [Accepted: 11/18/2023] [Indexed: 01/19/2024] Open
Abstract
Self-related information is crucial in our daily lives, which has led to the proposal that there is a specific brain mechanism for processing it. Neuroimaging studies have consistently demonstrated that the default mode network (DMN) is strongly associated with the representation and processing of self-related information. However, the precise relationship between DMN activity and self-related information, particularly in terms of neural oscillations, remains largely unknown. We electrically stimulated the superior temporal and fusiform areas, using stereo-electroencephalography to investigate neural oscillations associated with elicited self-related auditory hallucinations. Twenty-two instances of auditory hallucinations were recorded and categorized into self-related and other-related conditions. Comparing oscillatory power changes within the DMN between self-related and other-related auditory hallucinations, we discovered that self-related hallucinations are associated with significantly stronger positive power changes in both alpha and gamma bands compared to other-related hallucinations. To ensure the validity of our findings, we conducted controlled analyses for factors of familiarity and clarity, which revealed that the observed effects within the DMN remain independent of these factors. These results underscore the significance of the functional role of the DMN during the processing of self-related auditory hallucinations and shed light on the relationship between self-related perception and neural oscillatory activity.
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Affiliation(s)
- Jing Yang
- Center for Studies of Psychological Application, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
- School of Psychology, South China Normal University, No. 55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
| | - Lu Shen
- Center for Studies of Psychological Application, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
- School of Psychology, South China Normal University, No. 55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
| | - Qiting Long
- School of Psychology, South China Normal University, No. 55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
| | - Wenjie Li
- School of Psychology, South China Normal University, No. 55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
| | - Wei Zhang
- Department of Neurology, Beijing Tsinghua Changgung Hospital, Litang Road No. 168, Changping District, 102218, Beijing, China
- Epilepsy Center, Shanghai Neuromedical Center, Gulang Road No. 378, Putuo District, 200331, Shanghai, China
| | - Qi Chen
- Center for Studies of Psychological Application, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
- School of Psychology, South China Normal University, No. 55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
| | - Biao Han
- Center for Studies of Psychological Application, South China Normal University, No.55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
- School of Psychology, South China Normal University, No. 55, West of Zhongshan Avenue, Tianhe District, 510631, Guangzhou, China
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15
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Mihali A, Broeker M, Ragalmuto FDM, Horga G. Introspective inference counteracts perceptual distortion. Nat Commun 2023; 14:7826. [PMID: 38030601 PMCID: PMC10687029 DOI: 10.1038/s41467-023-42813-2] [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: 09/29/2022] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Introspective agents can recognize the extent to which their internal perceptual experiences deviate from the actual states of the external world. This ability, also known as insight, is critically required for reality testing and is impaired in psychosis, yet little is known about its cognitive underpinnings. We develop a Bayesian modeling framework and a psychophysics paradigm to quantitatively characterize this type of insight while people experience a motion after-effect illusion. People can incorporate knowledge about the illusion into their decisions when judging the actual direction of a motion stimulus, compensating for the illusion (and often overcompensating). Furthermore, confidence, reaction-time, and pupil-dilation data all show signatures consistent with inferential adjustments in the Bayesian insight model. Our results suggest that people can question the veracity of what they see by making insightful inferences that incorporate introspective knowledge about internal distortions.
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Affiliation(s)
- Andra Mihali
- New York State Psychiatric Institute, New York, NY, USA.
- Columbia University, Department of Psychiatry, New York, NY, USA.
| | - Marianne Broeker
- New York State Psychiatric Institute, New York, NY, USA
- Columbia University, Department of Psychiatry, New York, NY, USA
- Columbia University, Teachers College, New York, NY, USA
- University of Oxford, Department of Experimental Psychology, Oxford, UK
| | - Florian D M Ragalmuto
- New York State Psychiatric Institute, New York, NY, USA
- Columbia University, Department of Psychiatry, New York, NY, USA
- Vrije Universiteit, Faculty of Behavioral and Movement Science, Amsterdam, the Netherlands
- Berliner FortbildungsAkademie, Berlin, DE, Germany
| | - Guillermo Horga
- New York State Psychiatric Institute, New York, NY, USA.
- Columbia University, Department of Psychiatry, New York, NY, USA.
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16
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Klar P, Çatal Y, Fogel S, Jocham G, Langner R, Owen AM, Northoff G. Auditory inputs modulate intrinsic neuronal timescales during sleep. Commun Biol 2023; 6:1180. [PMID: 37985812 PMCID: PMC10661171 DOI: 10.1038/s42003-023-05566-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/09/2023] [Indexed: 11/22/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies have demonstrated that intrinsic neuronal timescales (INT) undergo modulation by external stimulation during consciousness. It remains unclear if INT keep the ability for significant stimulus-induced modulation during primary unconscious states, such as sleep. This fMRI analysis addresses this question via a dataset that comprises an awake resting-state plus rest and stimulus states during sleep. We analyzed INT measured via temporal autocorrelation supported by median frequency (MF) in the frequency-domain. Our results were replicated using a biophysical model. There were two main findings: (1) INT prolonged while MF decreased from the awake resting-state to the N2 resting-state, and (2) INT shortened while MF increased during the auditory stimulus in sleep. The biophysical model supported these results by demonstrating prolonged INT in slowed neuronal populations that simulate the sleep resting-state compared to an awake state. Conversely, under sine wave input simulating the stimulus state during sleep, the model's regions yielded shortened INT that returned to the awake resting-state level. Our results highlight that INT preserve reactivity to stimuli in states of unconsciousness like sleep, enhancing our understanding of unconscious brain dynamics and their reactivity to stimuli.
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Affiliation(s)
- Philipp Klar
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany.
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Room 6435, Ottawa, ON, K1Z 7K4, Canada
| | - Stuart Fogel
- Sleep Unit, University of Ottawa Institute of Mental Health Research at The Royal, K1Z 7K4, Ottawa, ON, Canada
| | - Gerhard Jocham
- Faculty of Mathematics and Natural Sciences, Institute of Experimental Psychology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Adrian M Owen
- Departments of Physiology and Pharmacology and Psychology, Western University, London, ON, N6A 5B7, Canada
| | - Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa, Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, 145 Carling Avenue, Room 6435, Ottawa, ON, K1Z 7K4, Canada
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Tianmu Road 305, Hangzhou, Zhejiang Province, 310013, China
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17
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Zhang A, Wengler K, Zhu X, Horga G, Goldberg TE, Lee S. Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.26.559549. [PMID: 37808862 PMCID: PMC10557723 DOI: 10.1101/2023.09.26.559549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Alzheimer's disease (AD) is a devastating neurodegenerative disease that affects millions of older adults in the US and worldwide. Resting-state functional magnetic resonance imaging (rs-fMRI) has become a widely used neuroimaging tool to study neurophysiology in AD and its prodromal condition, mild cognitive impairment (MCI). The intrinsic neural timescale (INT), which can be estimated through the magnitude of the autocorrelation of intrinsic neural signals using rs-fMRI, is thought to quantify the duration that neural information is stored in a local cortical circuit. The heterogeneity of the timescales is considered to be a basis of the functional hierarchy in the brain. In addition, INT captures an aspect of circuit dynamics relevant to excitation/inhibition (E/I) balance, which is thought to be broadly relevant for cognitive functions. Here we examined its relevance to AD. We used rs-fMRI data of 904 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The subjects were divided into 4 groups based on their baseline and end-visit clinical status, which were cognitively normal (CN), stable MCI, Converter, and AD groups. Linear mixed effect model and pairwise comparison were implemented to investigate the large-scale hierarchical organization and local differences. We observed high similarities between AD and Converter groups. Specifically, among the eight identified ROIs with distinct INT alterations in AD, three ROIs (inferior temporal, caudate, pallidum areas) exhibit stable and significant alteration in AD converter. In addition, distinct INT related pathological changes in stable MCI and AD/Converter were found. For AD and Converter groups, neural information is stored for a longer time in lower hierarchical order areas, while higher levels of hierarchy seem to be preferentially impaired in stable MCI leading to a less pronounced hierarchical gradient effect. These results inform that the INT holds great potential as an additional measure for AD prediction, a stable biomarker for clinical diagnosis and an important therapeutic target in AD.
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18
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Lurie DJ, Pappas I, D'Esposito M. Cortical timescales and the modular organization of structural and functional brain networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.12.548751. [PMID: 37502887 PMCID: PMC10370009 DOI: 10.1101/2023.07.12.548751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the "timescale" over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.
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Affiliation(s)
- Daniel J Lurie
- Department of Psychology, University of California, Berkeley
| | - Ioannis Pappas
- Department of Neurology, Keck School of Medicine, University of Southern California
| | - Mark D'Esposito
- Department of Psychology and Helen Wills Neuroscience Institute, University of California, Berkeley
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19
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Northoff G, Klar P, Bein M, Safron A. As without, so within: how the brain's temporo-spatial alignment to the environment shapes consciousness. Interface Focus 2023; 13:20220076. [PMID: 37065263 PMCID: PMC10102730 DOI: 10.1098/rsfs.2022.0076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/02/2023] [Indexed: 04/18/2023] Open
Abstract
Consciousness is constituted by a structure that includes contents as foreground and the environment as background. This structural relation between the experiential foreground and background presupposes a relationship between the brain and the environment, often neglected in theories of consciousness. The temporo-spatial theory of consciousness addresses the brain-environment relation by a concept labelled 'temporo-spatial alignment'. Briefly, temporo-spatial alignment refers to the brain's neuronal activity's interaction with and adaption to interoceptive bodily and exteroceptive environmental stimuli, including their symmetry as key for consciousness. Combining theory and empirical data, this article attempts to demonstrate the yet unclear neuro-phenomenal mechanisms of temporo-spatial alignment. First, we suggest three neuronal layers of the brain's temporo-spatial alignment to the environment. These neuronal layers span across a continuum from longer to shorter timescales. (i) The background layer comprises longer and more powerful timescales mediating topographic-dynamic similarities between different subjects' brains. (ii) The intermediate layer includes a mixture of medium-scaled timescales allowing for stochastic matching between environmental inputs and neuronal activity through the brain's intrinsic neuronal timescales and temporal receptive windows. (iii) The foreground layer comprises shorter and less powerful timescales for neuronal entrainment of stimuli temporal onset through neuronal phase shifting and resetting. Second, we elaborate on how the three neuronal layers of temporo-spatial alignment correspond to their respective phenomenal layers of consciousness. (i) The inter-subjectively shared contextual background of consciousness. (ii) An intermediate layer that mediates the relationship between different contents of consciousness. (iii) A foreground layer that includes specific fast-changing contents of consciousness. Overall, temporo-spatial alignment may provide a mechanism whose different neuronal layers modulate corresponding phenomenal layers of consciousness. Temporo-spatial alignment can provide a bridging principle for linking physical-energetic (free energy), dynamic (symmetry), neuronal (three layers of distinct time-space scales) and phenomenal (form featured by background-intermediate-foreground) mechanisms of consciousness.
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Affiliation(s)
- Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, TheRoyal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada K1Z 7K4
- Mental Health Centre, Zhejiang University School of Medicine, Hangzhou 310053, People's Republic of China
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310053, People's Republic of China
| | - Philipp Klar
- Medical Faculty, C. & O. Vogt-Institute for Brain Research, Heinrich Heine University of Düsseldorf, 40225 Düsseldorf, Germany
| | - Magnus Bein
- Department of Biology and Department of Psychiatry, McGill University, Quebec, Canada H3A 0G4
| | - Adam Safron
- Center for Psychedelic and Consciousness Research, Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA
- Institute for Advanced Consciousness Studies, Santa Monica, CA 90403, USA
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20
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Lechner S, Northoff G. Prolonged Intrinsic Neural Timescales Dissociate from Phase Coherence in Schizophrenia. Brain Sci 2023; 13:brainsci13040695. [PMID: 37190660 DOI: 10.3390/brainsci13040695] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 04/17/2023] [Accepted: 04/17/2023] [Indexed: 05/17/2023] Open
Abstract
Input processing in the brain is mediated by phase synchronization and intrinsic neural timescales, both of which have been implicated in schizophrenia. Their relationship remains unclear, though. Recruiting a schizophrenia EEG sample from the B-SNIP consortium dataset (n = 134, 70 schizophrenia patients, 64 controls), we investigate phase synchronization, as measured by intertrial phase coherence (ITPC), and intrinsic neural timescales, as measured by the autocorrelation window (ACW) during both the rest and oddball-task states. The main goal of our paper was to investigate whether reported shifts from shorter to longer timescales are related to decreased ITPC. Our findings show (i) decreases in both theta and alpha ITPC in response to both standard and deviant tones; and (iii) a negative correlation of ITPC and ACW in healthy subjects while such correlation is no longer present in SCZ participants. Together, we demonstrate evidence of abnormally long intrinsic neural timescales (ACW) in resting-state EEG of schizophrenia as well as their dissociation from phase synchronization (ITPC). Our data suggest that, during input processing, the resting state's abnormally long intrinsic neural timescales tilt the balance of temporal segregation and integration towards the latter. That results in temporal imprecision with decreased phase synchronization in response to inputs. Our findings provide further evidence for a basic temporal disturbance in schizophrenia on the different timescales (longer ACW and shorter ITPC), which, in the future, might be able to explain common symptoms related to the temporal experience in schizophrenia, for example temporal fragmentation.
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Affiliation(s)
- Stephan Lechner
- The Royal's Institute of Mental Health Research, Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
- Research Group Neuroinformatics, Faculty of Computer Science, University of Vienna, 1010 Vienna, Austria
- Vienna Doctoral School Cognition, Behavior and Neuroscience, University of Vienna, 1030 Vienna, Austria
| | - Georg Northoff
- The Royal's Institute of Mental Health Research, Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
- Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, Roger Guindon Hall 451 Smyth Road, Ottawa, ON K1H 8M5, Canada
- Mental Health Centre, School of Medicine, Zhejiang University, Hangzhou 310013, China
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310013, China
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21
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Uscătescu LC, Kronbichler M, Said-Yürekli S, Kronbichler L, Calhoun V, Corbera S, Bell M, Pelphrey K, Pearlson G, Assaf M. Intrinsic neural timescales in autism spectrum disorder and schizophrenia. A replication and direct comparison study. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:18. [PMID: 36997542 PMCID: PMC10063601 DOI: 10.1038/s41537-023-00344-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 03/06/2023] [Indexed: 04/03/2023]
Abstract
Intrinsic neural timescales (INT) reflect the duration for which brain areas store information. A posterior-anterior hierarchy of increasingly longer INT has been revealed in both typically developed individuals (TD), as well as persons diagnosed with autism spectrum disorder (ASD) and schizophrenia (SZ), though INT are, overall, shorter in both patient groups. In the present study, we aimed to replicate previously reported group differences by comparing INT of TD to ASD and SZ. We partially replicated the previously reported result, showing reduced INT in the left lateral occipital gyrus and the right post-central gyrus in SZ compared to TD. We also directly compared the INT of the two patient groups and found that these same two areas show significantly reduced INT in SZ compared to ASD. Previously reported correlations between INT and symptom severity were not replicated in the current project. Our findings serve to circumscribe the brain areas that can potentially play a determinant role in observed sensory peculiarities in ASD and SZ.
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Affiliation(s)
| | - Martin Kronbichler
- Centre for Cognitive Neuroscience & Department of Psychology, Paris-Lodron University of Salzburg, Salzburg, Austria
- Neuroscience Institute, Christian-Doppler Medical University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Sarah Said-Yürekli
- Centre for Cognitive Neuroscience & Department of Psychology, Paris-Lodron University of Salzburg, Salzburg, Austria
- Neuroscience Institute, Christian-Doppler Medical University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Lisa Kronbichler
- Centre for Cognitive Neuroscience & Department of Psychology, Paris-Lodron University of Salzburg, Salzburg, Austria
- Neuroscience Institute, Christian-Doppler Medical University Hospital, Paracelsus Medical University, Salzburg, Austria
- Department of Psychiatry, Psychotherapy & Psychosomatics, Christian-Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Silvia Corbera
- Central Connecticut State University, Department of Psychological Science, New Britain, CT, USA
| | - Morris Bell
- Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA
| | - Kevin Pelphrey
- University of Virginia, Department of Neurology, Charlottesville, VA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
- Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA
| | - Michal Assaf
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
- Yale University, School of Medicine, Department of Psychiatry, New Haven, CT, USA
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22
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Fleming LM, Lemonde AC, Benrimoh D, Gold JM, Taylor JR, Malla A, Joober R, Iyer SN, Lepage M, Shah J, Corlett PR. Using dimensionality-reduction techniques to understand the organization of psychotic symptoms in persistent psychotic illness and first episode psychosis. Sci Rep 2023; 13:4841. [PMID: 36964175 PMCID: PMC10039017 DOI: 10.1038/s41598-023-31909-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 03/17/2023] [Indexed: 03/26/2023] Open
Abstract
Psychotic disorders are highly heterogeneous. Understanding relationships between symptoms will be relevant to their underlying pathophysiology. We apply dimensionality-reduction methods across two unique samples to characterize the patterns of symptom organization. We analyzed publicly-available data from 153 participants diagnosed with schizophrenia or schizoaffective disorder (fBIRN Data Repository and the Consortium for Neuropsychiatric Phenomics), as well as 636 first-episode psychosis (FEP) participants from the Prevention and Early Intervention Program for Psychosis (PEPP-Montreal). In all participants, the Scale for the Assessment of Positive Symptoms (SAPS) and Scale for the Assessment of Negative Symptoms (SANS) were collected. Multidimensional scaling (MDS) combined with cluster analysis was applied to SAPS and SANS scores across these two groups of participants. MDS revealed relationships between items of SAPS and SANS. Our application of cluster analysis to these results identified: 1 cluster of disorganization symptoms, 2 clusters of hallucinations/delusions, and 2 SANS clusters (asocial and apathy, speech and affect). Those reality distortion items which were furthest from auditory hallucinations had very weak to no relationship with hallucination severity. Despite being at an earlier stage of illness, symptoms in FEP presentations were similarly organized. While hallucinations and delusions commonly co-occur, we found that their specific themes and content sometimes travel together and sometimes do not. This has important implications, not only for treatment, but also for research-particularly efforts to understand the neurocomputational and pathophysiological mechanism underlying delusions and hallucinations.
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Affiliation(s)
- Leah M Fleming
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Department, Yale University, New Haven, CT, USA
| | | | - David Benrimoh
- Department of Psychiatry, McGill University Montreal, Qubec, Canada
| | - James M Gold
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jane R Taylor
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - Ashok Malla
- Department of Psychiatry, McGill University Montreal, Qubec, Canada
- The Prevention and Early Intervention Program for Psychosis (PEPP-Montreal), Douglas Mental Health University Institute, Qubec, Canada
| | - Ridha Joober
- Department of Psychiatry, McGill University Montreal, Qubec, Canada
- The Prevention and Early Intervention Program for Psychosis (PEPP-Montreal), Douglas Mental Health University Institute, Qubec, Canada
| | - Srividya N Iyer
- Department of Psychiatry, McGill University Montreal, Qubec, Canada
- The Prevention and Early Intervention Program for Psychosis (PEPP-Montreal), Douglas Mental Health University Institute, Qubec, Canada
| | - Martin Lepage
- Department of Psychiatry, McGill University Montreal, Qubec, Canada
- The Prevention and Early Intervention Program for Psychosis (PEPP-Montreal), Douglas Mental Health University Institute, Qubec, Canada
| | - Jai Shah
- Department of Psychiatry, McGill University Montreal, Qubec, Canada
- The Prevention and Early Intervention Program for Psychosis (PEPP-Montreal), Douglas Mental Health University Institute, Qubec, Canada
| | - Philip R Corlett
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychology, Yale University, New Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
- Connecticut Mental Health Center, 34 Park St, New Haven, CT, 06519, USA.
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23
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Hudson M, Santavirta S, Putkinen V, Seppälä K, Sun L, Karjalainen T, Karlsson HK, Hirvonen J, Nummenmaa L. Neural responses to biological motion distinguish autistic and schizotypal traits. Soc Cogn Affect Neurosci 2023; 18:nsad011. [PMID: 36847146 PMCID: PMC10032360 DOI: 10.1093/scan/nsad011] [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: 09/15/2022] [Revised: 01/26/2023] [Accepted: 02/24/2023] [Indexed: 03/01/2023] Open
Abstract
Difficulties in social interactions characterize both autism and schizophrenia and are correlated in the neurotypical population. It is unknown whether this represents a shared etiology or superficial phenotypic overlap. Both conditions exhibit atypical neural activity in response to the perception of social stimuli and decreased neural synchronization between individuals. This study investigated if neural activity and neural synchronization associated with biological motion perception are differentially associated with autistic and schizotypal traits in the neurotypical population. Participants viewed naturalistic social interactions while hemodynamic brain activity was measured with fMRI, which was modeled against a continuous measure of the extent of biological motion. General linear model analysis revealed that biological motion perception was associated with neural activity across the action observation network. However, intersubject phase synchronization analysis revealed neural activity to be synchronized between individuals in occipital and parietal areas but desynchronized in temporal and frontal regions. Autistic traits were associated with decreased neural activity (precuneus and middle cingulate gyrus), and schizotypal traits were associated with decreased neural synchronization (middle and inferior frontal gyri). Biological motion perception elicits divergent patterns of neural activity and synchronization, which dissociate autistic and schizotypal traits in the general population, suggesting that they originate from different neural mechanisms.
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Affiliation(s)
- Matthew Hudson
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Turku University Hospital, Turku 20520, Finland
- School of Psychology, University of Plymouth, Plymouth PL4 8AA, UK
- Brain Research & Imaging Centre, Faculty of Health, University of Plymouth, Research Way, Plymouth PL6 8BU, UK
| | - Severi Santavirta
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Turku University Hospital, Turku 20520, Finland
| | - Vesa Putkinen
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Turku University Hospital, Turku 20520, Finland
| | - Kerttu Seppälä
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Turku University Hospital, Turku 20520, Finland
- Department of Medical Physics, Turku University Hospital, Turku 20520, Finland
| | - Lihua Sun
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Turku University Hospital, Turku 20520, Finland
- Department of Nuclear Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Tomi Karjalainen
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Turku University Hospital, Turku 20520, Finland
| | - Henry K Karlsson
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Turku University Hospital, Turku 20520, Finland
| | - Jussi Hirvonen
- Department of Radiology, University of Turku and Turku University Hospital, Turku 20520, Finland
- Medical Imaging Centre, Department of Radiology, Tampere University and Tampere University Hospital, Tampere 33100, Finland
| | - Lauri Nummenmaa
- Turku PET Centre, University of Turku, Turku 20520, Finland
- Department of Psychology, University of Turku, Turku 20520, Finland
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24
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Xie K, Royer J, Lariviere S, Rodriguez-Cruces R, de Wael RV, Park BY, Auer H, Tavakol S, DeKraker J, Abdallah C, Caciagli L, Bassett DS, Bernasconi A, Bernasconi N, Frauscher B, Concha L, Bernhardt BC. Atypical intrinsic neural timescales in temporal lobe epilepsy. Epilepsia 2023; 64:998-1011. [PMID: 36764677 DOI: 10.1111/epi.17541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/06/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) is the most common pharmacoresistant epilepsy in adults. Here we profiled local neural function in TLE in vivo, building on prior evidence that has identified widespread structural alterations. Using resting-state functional magnetic resonance imaging (rs-fMRI), we mapped the whole-brain intrinsic neural timescales (INT), which reflect temporal hierarchies of neural processing. Parallel analysis of structural and diffusion MRI data examined associations with TLE-related structural compromise. Finally, we evaluated the clinical utility of INT. METHODS We studied 46 patients with TLE and 44 healthy controls from two independent sites, and mapped INT changes in patients relative to controls across hippocampal, subcortical, and neocortical regions. We examined region-specific associations to structural alterations and explored the effects of age and epilepsy duration. Supervised machine learning assessed the utility of INT for identifying patients with TLE vs controls and left- vs right-sided seizure onset. RESULTS Relative to controls, TLE showed marked INT reductions across multiple regions bilaterally, indexing faster changing resting activity, with strongest effects in the ipsilateral medial and lateral temporal regions, and bilateral sensorimotor cortices as well as thalamus and hippocampus. Findings were similar, albeit with reduced effect sizes, when correcting for structural alterations. INT reductions in TLE increased with advancing disease duration, yet findings differed from the aging effects seen in controls. INT-derived classifiers discriminated patients vs controls (balanced accuracy, 5-fold: 76% ± 2.65%; cross-site, 72%-83%) and lateralized the focus in TLE (balanced accuracy, 5-fold: 96% ± 2.10%; cross-site, 95%-97%), with high accuracy and cross-site generalizability. Findings were consistent across both acquisition sites and robust when controlling for motion and several methodological confounds. SIGNIFICANCE Our findings demonstrate atypical macroscale function in TLE in a topography that extends beyond mesiotemporal epicenters. INT measurements can assist in TLE diagnosis, seizure focus lateralization, and monitoring of disease progression, which emphasizes promising clinical utility.
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Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Sara Lariviere
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Department of Data Science, Inha University, Incheon, Republic of Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Lorenzo Caciagli
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dani S Bassett
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Santa Fe Institute, Santa Fe, New Mexico, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Luis Concha
- Brain Connectivity Laboratory, Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Juriquilla, Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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25
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Cushnie AK, Bullock DN, Manea AM, Tang W, Zimmermann J, Heilbronner SR. The use of chemogenetic actuator ligands in nonhuman primate DREADDs-fMRI. CURRENT RESEARCH IN NEUROBIOLOGY 2022; 4:100072. [PMID: 36691404 PMCID: PMC9860110 DOI: 10.1016/j.crneur.2022.100072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 12/01/2022] [Accepted: 12/26/2022] [Indexed: 12/31/2022] Open
Abstract
Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are engineered receptors that allow for genetically targeted, reversible manipulation of cellular activity via systemic drug administration. DREADD induced manipulations are initiated via the binding of an actuator ligand. Therefore, the use of DREADDs is contingent on the availability of actuator ligands. Actuator ligands low-dose clozapine (CLZ) and deschloroclozapine (DCZ) are highly selective for DREADDs, and, upon binding, induce physiological and behavioral changes in rodents and nonhuman primates (NHPs). Despite this reported specificity, both CLZ and DCZ have partial affinity for a variety of endogenous receptors and can induce dose-specific changes even in naïve animals. As such, this study aimed to examine the effects of CLZ and DCZ on resting-state functional connectivity (rs-FC) and intrinsic neural timescales (INTs) in naïve NHPs. In doing so, we evaluated whether CLZ and DCZ - in the absence of DREADDs - are inert by examining these ligands' effects on the intrinsic functional properties of the brain. Low-dose DCZ did not induce consistent changes in rs-FC or INTs prior to the expression of DREADDs; however, a high dose resulted in subject-specific changes in rs-FC and INTs. In contrast, CLZ administration induced consistent changes in rs-FC and INTs prior to DREADD expression in our subjects. Our results caution against the use of CLZ by explicitly demonstrating the impact of off-target effects that can confound experimental results. Altogether, these data endorse the use of low dose DCZ for future DREADD-based experiments.
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Affiliation(s)
- Adriana K. Cushnie
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Daniel N. Bullock
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Ana M.G. Manea
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Wei Tang
- Department of Computer Science, Program in Neuroscience, Indiana University Bloomington, Bloomington, IN, 47408, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Sarah R. Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, 55455, USA
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26
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Northoff G. Spatiotemporal Psychopathology - A Novel Approach to Brain and Symptoms. Noro Psikiyatr Ars 2022; 59:S3-S9. [PMID: 36578984 PMCID: PMC9767129 DOI: 10.29399/npa.28146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 03/13/2022] [Indexed: 12/31/2022] Open
Abstract
How can we characterize psychopathological symptoms and connect them to the brain? Current psychopathological symptoms only focus on either the symptoms themselves or predominantly on the brain. This leaves open their intimate connection. A novel approach, Spatiotemporal Psychopathology, proposes that the brain inner spatiotemporal organisation of its neural activity provides the spatiotemporal organization of the psychopathological symptoms. Specifically, the brains' neuronal topography and dynamic is manifest in a more or less analogous spatiotemporal organisation on the mental level, i.e., mental topography and dynamic. This is strongly supported by various examples including major depressive disorder, bipolar disorder, schizophrenia, and autism. We therefore conclude that Spatiotemporal Psychopathology provides a promising approach to intimately connect brain and symptoms.
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Affiliation(s)
- Georg Northoff
- University of Ottawa, Institute of Mental Health Research, Ontario, Canada,Correspondence Address: Georg Northoff, 1145 Carling Avenue, Ottawa, K1L 8K9 Ontario, Canada • E-mail:
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27
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Niedernhuber M, Raimondo F, Sitt JD, Bekinschtein TA. Sensory Target Detection at Local and Global Timescales Reveals a Hierarchy of Supramodal Dynamics in the Human Cortex. J Neurosci 2022; 42:8729-8741. [PMID: 36223999 PMCID: PMC9671580 DOI: 10.1523/jneurosci.0658-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 06/24/2022] [Accepted: 07/20/2022] [Indexed: 11/21/2022] Open
Abstract
To ensure survival in a dynamic environment, the human neocortex monitors input streams from different sensory organs for important sensory events. Which principles govern whether different senses share common or modality-specific brain networks for sensory target detection? We examined whether complex targets evoke sustained supramodal activity while simple targets rely on modality-specific networks with short-lived supramodal contributions. In a series of hierarchical multisensory target detection studies (n = 77, of either sex) using EEG, we applied a temporal cross-decoding approach to dissociate supramodal and modality-specific cortical dynamics elicited by rule-based global and feature-based local sensory deviations within and between the visual, somatosensory, and auditory modality. Our data show that each sense implements a cortical hierarchy orchestrating supramodal target detection responses, which operate at local and global timescales in successive processing stages. Across different sensory modalities, simple feature-based sensory deviations presented in temporal vicinity to a monotonous input stream triggered a mismatch negativity-like local signal which decayed quickly and early, whereas complex rule-based targets tracked across time evoked a P3b-like global neural response which generalized across a late time window. Converging results from temporal cross-modality decoding analyses across different datasets, we reveal that global neural responses are sustained in a supramodal higher-order network, whereas local neural responses canonically thought to rely on modality-specific regions evolve into short-lived supramodal activity. Together, our findings demonstrate that cortical organization largely follows a gradient in which short-lived modality-specific as well as supramodal processes dominate local responses, whereas higher-order processes encode temporally extended abstract supramodal information fed forward from modality-specific cortices.SIGNIFICANCE STATEMENT Each sense supports a cortical hierarchy of processes tracking deviant sensory events at multiple timescales. Conflicting evidence produced a lively debate around which of these processes are supramodal. Here, we manipulated the temporal complexity of auditory, tactile, and visual targets to determine whether cortical local and global ERP responses to sensory targets share cortical dynamics between the senses. Using temporal cross-decoding, we found that temporally complex targets elicit a supramodal sustained response. Conversely, local responses to temporally confined targets typically considered modality-specific rely on early short-lived supramodal activation. Our finding provides evidence for a supramodal gradient supporting sensory target detection in the cortex, with implications for multiple fields in which these responses are studied (e.g., predictive coding, consciousness, and attention).
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Affiliation(s)
- Maria Niedernhuber
- Cambridge Consciousness and Cognition Lab, Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom
- Body, Self, and Plasticity Lab, Department of Psychology, University of Zurich, Zurich, 8050, Switzerland
| | - Federico Raimondo
- Brain and Spine Institute, Pitiè Salpêtrière Hospital, Paris, 75013, France
- National Institute of Health and Medical Research, Paris, 75013, France
- Institute of Neuroscience and Medicine, Brain & Behaviour, Research Centre Jülich, Jülich, 52425, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany
| | - Jacobo D. Sitt
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, APHP, Hôpital de la Pitié Salpêtrière, Paris, 75013, France
| | - Tristan A. Bekinschtein
- Cambridge Consciousness and Cognition Lab, Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom
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28
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Niznikiewicz MA, Brady RO, Whitfield-Gabrieli S, Keshavan MS, Zhang T, Li H, Pasternak O, Shenton ME, Wang J, Stone WS. Dynamic intervention-based biomarkers may reduce heterogeneity and motivate targeted interventions in clinical high risk for psychosis. Schizophr Res 2022; 246:60-62. [PMID: 35709648 DOI: 10.1016/j.schres.2022.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 03/26/2022] [Accepted: 05/06/2022] [Indexed: 10/18/2022]
Affiliation(s)
- M A Niznikiewicz
- Department of Psychiatry, VA Boston Healthcare System, Brockton Division, Brockton, MA, USA; Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - R O Brady
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | | | - M S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - T Zhang
- Shanghai Key Laboratory of Psychotic Disorders, SHARP Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - H Li
- Department of Psychology, Florida A&M University, Tallahassee, FL, USA
| | - O Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M E Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Wang
- Shanghai Key Laboratory of Psychotic Disorders, SHARP Program, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - W S Stone
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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29
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Rethinking delusions: A selective review of delusion research through a computational lens. Schizophr Res 2022; 245:23-41. [PMID: 33676820 PMCID: PMC8413395 DOI: 10.1016/j.schres.2021.01.023] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 01/27/2021] [Accepted: 01/29/2021] [Indexed: 02/06/2023]
Abstract
Delusions are rigid beliefs held with high certainty despite contradictory evidence. Notwithstanding decades of research, we still have a limited understanding of the computational and neurobiological alterations giving rise to delusions. In this review, we highlight a selection of recent work in computational psychiatry aimed at developing quantitative models of inference and its alterations, with the goal of providing an explanatory account for the form of delusional beliefs in psychosis. First, we assess and evaluate the experimental paradigms most often used to study inferential alterations in delusions. Based on our review of the literature and theoretical considerations, we contend that classic draws-to-decision paradigms are not well-suited to isolate inferential processes, further arguing that the commonly cited 'jumping-to-conclusion' bias may reflect neither delusion-specific nor inferential alterations. Second, we discuss several enhancements to standard paradigms that show promise in more effectively isolating inferential processes and delusion-related alterations therein. We further draw on our recent work to build an argument for a specific failure mode for delusions consisting of prior overweighting in high-level causal inferences about partially observable hidden states. Finally, we assess plausible neurobiological implementations for this candidate failure mode of delusional beliefs and outline promising future directions in this area.
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30
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Manea AMG, Zilverstand A, Ugurbil K, Heilbronner SR, Zimmermann J. Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain. eLife 2022; 11:e75540. [PMID: 35234612 PMCID: PMC8923667 DOI: 10.7554/elife.75540] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 02/28/2022] [Indexed: 11/13/2022] Open
Abstract
Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultrahigh field functional magnetic resonance imaging (fMRI) performed at 10.5 T to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we extended existing electrophysiological hierarchies to whole-brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Further, with these results in hand, we were able to show that one facet of the high-dimensional functional connectivity (FC) topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match FC gradient topographies across the whole brain. We conclude that intrinsic timescales are a unifying organizational principle of neural processing across the whole brain.
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Affiliation(s)
- Ana MG Manea
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences , University of MinnesotaMinneapolisUnited States
- Medical Discovery Team on Addiction, University of MinnesotaMinneapolisUnited States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
- Center for Neuroengineering, University of MinnesotaMinneapolisUnited States
- Department of Radiology, University of MinnesotaMinneapolisUnited States
| | - Sarah R Heilbronner
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Medical Discovery Team on Addiction, University of MinnesotaMinneapolisUnited States
- Center for Neuroengineering, University of MinnesotaMinneapolisUnited States
| | - Jan Zimmermann
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
- Medical Discovery Team on Addiction, University of MinnesotaMinneapolisUnited States
- Center for Neuroengineering, University of MinnesotaMinneapolisUnited States
- Department of Biomedical Engineering, University of MinnesotaMinneapolisUnited States
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31
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Han S, Zheng R, Li S, Zhou B, Jiang Y, Wang C, Wei Y, Pang J, Li H, Zhang Y, Chen Y, Cheng J. Integrative Functional, Molecular, and Transcriptomic Analyses of Altered Intrinsic Timescale Gradient in Depression. Front Neurosci 2022; 16:826609. [PMID: 35250462 PMCID: PMC8891525 DOI: 10.3389/fnins.2022.826609] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/10/2022] [Indexed: 12/13/2022] Open
Abstract
The pathophysiology and pharmacology of depression are hypothesized to be related to the imbalance of excitation–inhibition that gives rise to hierarchical dynamics (or intrinsic timescale gradient), further supporting a hierarchy of cortical functions. On this assumption, intrinsic timescale gradient is theoretically altered in depression. However, it remains unknown. We investigated altered intrinsic timescale gradient recently developed to measure hierarchical brain dynamics gradient and its underlying molecular architecture and brain-wide gene expression in depression. We first presented replicable intrinsic timescale gradient in two independent Chinese Han datasets and then investigated altered intrinsic timescale gradient and its possible underlying molecular and transcriptional bases in patients with depression. As a result, patients with depression showed stage-specifically shorter timescales compared with healthy controls according to illness duration. The shorter timescales were spatially correlated with monoamine receptor/transporter densities, suggesting the underlying molecular basis of timescale aberrance and providing clues to treatment. In addition, we identified that timescale aberrance-related genes ontologically enriched for synapse-related and neurotransmitter (receptor) terms, elaborating the underlying transcriptional basis of timescale aberrance. These findings revealed atypical timescale gradient in depression and built a link between neuroimaging, transcriptome, and neurotransmitter information, facilitating an integrative understanding of depression.
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Affiliation(s)
- Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- *Correspondence: Shaoqiang Han,
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shuying Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jianyue Pang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hengfen Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Yuan Chen,
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Jingliang Cheng,
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32
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Li S, Wang XJ. Hierarchical timescales in the neocortex: Mathematical mechanism and biological insights. Proc Natl Acad Sci U S A 2022; 119:e2110274119. [PMID: 35110401 PMCID: PMC8832993 DOI: 10.1073/pnas.2110274119] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 12/07/2021] [Indexed: 11/18/2022] Open
Abstract
A cardinal feature of the neocortex is the progressive increase of the spatial receptive fields along the cortical hierarchy. Recently, theoretical and experimental findings have shown that the temporal response windows also gradually enlarge, so that early sensory neural circuits operate on short timescales whereas higher-association areas are capable of integrating information over a long period of time. While an increased receptive field is accounted for by spatial summation of inputs from neurons in an upstream area, the emergence of timescale hierarchy cannot be readily explained, especially given the dense interareal cortical connectivity known in the modern connectome. To uncover the required neurobiological properties, we carried out a rigorous analysis of an anatomically based large-scale cortex model of macaque monkeys. Using a perturbation method, we show that the segregation of disparate timescales is defined in terms of the localization of eigenvectors of the connectivity matrix, which depends on three circuit properties: 1) a macroscopic gradient of synaptic excitation, 2) distinct electrophysiological properties between excitatory and inhibitory neuronal populations, and 3) a detailed balance between long-range excitatory inputs and local inhibitory inputs for each area-to-area pathway. Our work thus provides a quantitative understanding of the mechanism underlying the emergence of timescale hierarchy in large-scale primate cortical networks.
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Affiliation(s)
- Songting Li
- School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai 200240, China;
- Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
- Ministry of Education Key Laboratory of Scientific and Engineering Computing, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY 10003
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33
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Çatal Y, Gomez-Pilar J, Northoff G. Intrinsic dynamics and topography of sensory input systems. Cereb Cortex 2022; 32:4592-4604. [PMID: 35094077 PMCID: PMC9614113 DOI: 10.1093/cercor/bhab504] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/07/2021] [Accepted: 12/08/2021] [Indexed: 02/01/2023] Open
Abstract
The brain is continuously bombarded by external stimuli, which are processed in different input systems. The intrinsic features of these sensory input systems remain yet unclear. Investigating topography and dynamics of input systems is the goal of our study in order to better understand the intrinsic features that shape their neural processing. Using a functional magnetic resonance imaging dataset, we measured neural topography and dynamics of the input systems during rest and task states. Neural dynamics were probed by scale-free activity, measured with the power-law exponent (PLE), as well as by order/disorder as measured with sample entropy (SampEn). Our main findings during both rest and task states are: 1) differences in neural dynamics (PLE, SampEn) between regions within each of the three sensory input systems 2) differences in topography and dynamics among the three input systems; 3) PLE and SampEn correlate and, as demonstrated in simulation, show non-linear relationship in the critical range of PLE; 4) scale-free activity during rest mediates the transition of SampEn from rest to task as probed in a mediation model. We conclude that the sensory input systems are characterized by their intrinsic topographic and dynamic organization which, through scale-free activity, modulates their input processing.
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Affiliation(s)
- Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, Ontario K1Z 7K4, Canada
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Valladolid 47011, Spain,Centro de Investigación Biomédica en Red—Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid 28029, Spain
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34
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Adams RA, Pinotsis D, Tsirlis K, Unruh L, Mahajan A, Horas AM, Convertino L, Summerfelt A, Sampath H, Du XM, Kochunov P, Ji JL, Repovs G, Murray JD, Friston KJ, Hong LE, Anticevic A. Computational Modeling of Electroencephalography and Functional Magnetic Resonance Imaging Paradigms Indicates a Consistent Loss of Pyramidal Cell Synaptic Gain in Schizophrenia. Biol Psychiatry 2022; 91:202-215. [PMID: 34598786 PMCID: PMC8654393 DOI: 10.1016/j.biopsych.2021.07.024] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/29/2021] [Accepted: 07/29/2021] [Indexed: 12/23/2022]
Abstract
BACKGROUND Diminished synaptic gain-the sensitivity of postsynaptic responses to neural inputs-may be a fundamental synaptic pathology in schizophrenia. Evidence for this is indirect, however. Furthermore, it is unclear whether pyramidal cells or interneurons (or both) are affected, or how these deficits relate to symptoms. METHODS People with schizophrenia diagnoses (PScz) (n = 108), their relatives (n = 57), and control subjects (n = 107) underwent 3 electroencephalography (EEG) paradigms-resting, mismatch negativity, and 40-Hz auditory steady-state response-and resting functional magnetic resonance imaging. Dynamic causal modeling was used to quantify synaptic connectivity in cortical microcircuits. RESULTS Classic group differences in EEG features between PScz and control subjects were replicated, including increased theta and other spectral changes (resting EEG), reduced mismatch negativity, and reduced 40-Hz power. Across all 4 paradigms, characteristic PScz data features were all best explained by models with greater self-inhibition (decreased synaptic gain) in pyramidal cells. Furthermore, disinhibition in auditory areas predicted abnormal auditory perception (and positive symptoms) in PScz in 3 paradigms. CONCLUSIONS First, characteristic EEG changes in PScz in 3 classic paradigms are all attributable to the same underlying parameter change: greater self-inhibition in pyramidal cells. Second, psychotic symptoms in PScz relate to disinhibition in neural circuits. These findings are more commensurate with the hypothesis that in PScz, a primary loss of synaptic gain on pyramidal cells is then compensated by interneuron downregulation (rather than the converse). They further suggest that psychotic symptoms relate to this secondary downregulation.
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Affiliation(s)
- Rick A Adams
- Centre for Medical Image Computing and Artificial Intelligence, University College London, London, United Kingdom; Institute of Cognitive Neuroscience, University College London, London, United Kingdom; Max Planck-UCL Centre for Computational Psychiatry and Ageing Research, London, United Kingdom; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.
| | - Dimitris Pinotsis
- Centre for Mathematical Neuroscience and Psychology and Department of Psychology, City University of London, London, United Kingdom; Picower Institute for Learning & Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Konstantinos Tsirlis
- Centre for Medical Image Computing and Artificial Intelligence, University College London, London, United Kingdom
| | - Leonhardt Unruh
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Aashna Mahajan
- Centre for Medical Image Computing and Artificial Intelligence, University College London, London, United Kingdom
| | - Ana Montero Horas
- Centre for Medical Image Computing and Artificial Intelligence, University College London, London, United Kingdom
| | - Laura Convertino
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Ann Summerfelt
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
| | - Hemalatha Sampath
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
| | - Xiaoming Michael Du
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jie Lisa Ji
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Grega Repovs
- Department of Psychology, University of Ljubljana, Ljubljana, Slovenia
| | - John D Murray
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
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35
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Wolff A, Berberian N, Golesorkhi M, Gomez-Pilar J, Zilio F, Northoff G. Intrinsic neural timescales: temporal integration and segregation. Trends Cogn Sci 2022; 26:159-173. [PMID: 34991988 DOI: 10.1016/j.tics.2021.11.007] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 11/19/2021] [Accepted: 11/23/2021] [Indexed: 12/11/2022]
Abstract
We are continuously bombarded by external inputs of various timescales from the environment. How does the brain process this multitude of timescales? Recent resting state studies show a hierarchy of intrinsic neural timescales (INT) with a shorter duration in unimodal regions (e.g., visual cortex and auditory cortex) and a longer duration in transmodal regions (e.g., default mode network). This unimodal-transmodal hierarchy is present across acquisition modalities [electroencephalogram (EEG)/magnetoencephalogram (MEG) and fMRI] and can be found in different species and during a variety of different task states. Together, this suggests that the hierarchy of INT is central to the temporal integration (combining successive stimuli) and segregation (separating successive stimuli) of external inputs from the environment, leading to temporal segmentation and prediction in perception and cognition.
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Affiliation(s)
- Annemarie Wolff
- Mind, Brain Imaging, and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Nareg Berberian
- Mind, Brain Imaging, and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Mehrshad Golesorkhi
- Mind, Brain Imaging, and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - 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 Nanomedicia, (CIBER-BBN), Madrid, Spain
| | - Federico Zilio
- Department of Philosophy, Sociology, Education, and Applied Psychology, University of Padova, Padua, Italy
| | - Georg Northoff
- Mind, Brain Imaging, and Neuroethics Research Unit, Institute of Mental Health Research, The Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China; Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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36
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Wang K, Zhang X, Song C, Ma K, Bai M, Zheng R, Wei Y, Chen J, Cheng J, Zhang Y, Han S. Decreased Intrinsic Neural Timescales in Mesial Temporal Lobe Epilepsy. Front Hum Neurosci 2021; 15:772365. [PMID: 34955790 PMCID: PMC8693765 DOI: 10.3389/fnhum.2021.772365] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/16/2021] [Indexed: 01/02/2023] Open
Abstract
It is well established that epilepsy is characterized by the destruction of the information capacity of brain network and the interference with information processing in regions outside the epileptogenic focus. However, the potential mechanism remains poorly understood. In the current study, we applied a recently proposed approach on the basis of resting-state fMRI data to measure altered local neural dynamics in mesial temporal lobe epilepsy (mTLE), which represents how long neural information is stored in a local brain area and reflect an ability of information integration. Using resting-state-fMRI data recorded from 36 subjects with mTLE and 36 healthy controls, we calculated the intrinsic neural timescales (INT) of neural signals by summing the positive magnitude of the autocorrelation of the resting-state brain activity. Compared to healthy controls, the INT values were significantly lower in patients in the right orbitofrontal cortices, right insula, and right posterior lobe of cerebellum. Whereas, we observed no statistically significant changes between patients with long- and short-term epilepsy duration or between left-mTLE and right-mTLE. Our study provides distinct insight into the brain abnormalities of mTLE from the perspective of the dynamics of the brain activity, highlighting the significant role of intrinsic timescale in understanding neurophysiological mechanisms. And we postulate that altered intrinsic timescales of neural signals in specific cortical brain areas may be the neurodynamic basis of cognitive impairment and emotional comorbidities in mTLE patients.
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Affiliation(s)
- Kefan Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
| | - Xiaonan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Chengru Song
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Keran Ma
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Man Bai
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingli Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
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37
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Reduced intrinsic neural timescales in schizophrenia along posterior parietal and occipital areas. NPJ SCHIZOPHRENIA 2021; 7:55. [PMID: 34811376 PMCID: PMC8608811 DOI: 10.1038/s41537-021-00184-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 11/03/2021] [Indexed: 11/09/2022]
Abstract
We computed intrinsic neural timescales (INT) based on resting-state functional magnetic resonance imaging (rsfMRI) data of healthy controls (HC) and patients with schizophrenia spectrum disorder (SZ) from three independently collected samples. Five clusters showed decreased INT in SZ compared to HC in all three samples: right occipital fusiform gyrus (rOFG), left superior occipital gyrus (lSOG), right superior occipital gyrus (rSOG), left lateral occipital cortex (lLOC) and right postcentral gyrus (rPG). In other words, it appears that sensory information in visual and posterior parietal areas is stored for reduced lengths of time in SZ compared to HC. Finally, we found that symptom severity appears to modulate INT of these areas in SZ.
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38
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Overbeek G, Gawne TJ, Reid MA, Kraguljac NV, Lahti AC. A multimodal neuroimaging study investigating resting-state connectivity, glutamate and GABA at 7 T in first-episode psychosis. J Psychiatry Neurosci 2021; 46:E702-E710. [PMID: 34933941 PMCID: PMC8695527 DOI: 10.1503/jpn.210107] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 10/05/2021] [Accepted: 10/18/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The major excitatory and inhibitory neurometabolites in the brain, glutamate and γ-aminobutyric acid (GABA), respectively, are related to the functional MRI signal. Disruption of resting-state functional MRI signals has been reported in psychosis spectrum disorders, but few studies have investigated the role of these metabolites in this context. METHODS We included 19 patients with first-episode psychosis and 21 healthy controls in this combined magnetic resonance spectroscopy (MRS) and resting-state functional connectivity study. All imaging was performed on a Siemens Magnetom 7 T MRI scanner. Both the MRS voxel and the seed for functional connectivity analysis were located in the dorsal anterior cingulate cortex (ACC). We used multiple regressions to test for an interaction between ACC brain connectivity, diagnosis and neurometabolites. RESULTS ACC brain connectivity was altered in first-episode psychosis. The relationship between ACC glutamate and ACC functional connectivity differed between patients with first-episode psychosis and healthy controls in the precuneus, retrosplenial cortex, supramarginal gyrus and angular gyrus. As well, the relationship between ACC GABA and ACC functional connectivity differed between groups in the caudate, putamen and supramarginal gyrus. LIMITATIONS We used a small sample size. As well, although they were not chronically medicated, all participants were medicated during the study. CONCLUSION We demonstrated a link between the major excitatory and inhibitory brain metabolites and resting-state functional connectivity in healthy participants, as well as an alteration in this relationship in patients with first-episode psychosis. Combining data from different imaging modalities may help our mechanistic understanding of the relationship between major neurometabolites and brain network dynamics, and shed light on the pathophysiology of first-episode psychosis.
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Affiliation(s)
- Gregory Overbeek
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Timothy J Gawne
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Meredith A Reid
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Nina V Kraguljac
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Adrienne C Lahti
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
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Liu DY, Ju X, Gao Y, Han JF, Li Z, Hu XW, Tan ZL, Northoff G, Song XM. From Molecular to Behavior: Higher Order Occipital Cortex in Major Depressive Disorder. Cereb Cortex 2021; 32:2129-2139. [PMID: 34613359 DOI: 10.1093/cercor/bhab343] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 08/24/2021] [Accepted: 08/25/2021] [Indexed: 11/14/2022] Open
Abstract
Medial prefrontal cortex (MPFC) and other regions like the occipital cortex (OC) exhibit abnormal neural activity in major depressive disorder (MDD). Their relationship to specific biochemical, psychophysical, and psychopathological changes remains unclear, though. For that purpose, we focus on a particular subregion in OC, namely middle temporal (MT) visual area that is known to mediate the perception of visual motion. Using high-field 7 T magnetic resonance imaging (MRI), including resting state functional MRI and proton magnetic resonance spectroscopy, the amplitude of low-frequency fluctuations (ALFF) of the blood oxygen level-dependent signal in MT, MT-seeded functional connectivity (FC), and gamma-aminobutyric acid (GABA) in MT were investigated. Applying the vision motion psychophysical task, the motion suppression index of subjects was also examined. We demonstrate significantly elevated neural variability (as measured by ALFF) in MT together with decreases in both MT GABA and motion suppression in our MDD sample. Unlike in healthy subjects, MT neural variability no longer modulates the relationship of MT GABA and motion suppression in MDD. MT also exhibits reduction in global inter-regional FC to MPFC in MDD. Finally, elevated MT ALFF relates to specifically retardation in behavior as measured by the Hamilton subscore. Together, MT provides a strong candidate for biomarker in MDD.
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Affiliation(s)
- Dong-Yu Liu
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China.,Key Laboratory of Biomedical Engineering of Ministry of Education, Qiushi Academy for Advanced Studies, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Xuan Ju
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China
| | - Yuan Gao
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China
| | - Jin-Fang Han
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China
| | - Zhe Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China.,Key Laboratory of Biomedical Engineering of Ministry of Education, Qiushi Academy for Advanced Studies, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Xi-Wen Hu
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China
| | - Zhong-Lin Tan
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China
| | - Georg Northoff
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China.,University of Ottawa Institute of Mental Health Research, University of Ottawa; Ottawa, ON, K1Z 7K4, Canada
| | - Xue Mei Song
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310013, China.,Key Laboratory of Biomedical Engineering of Ministry of Education, Qiushi Academy for Advanced Studies, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
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Golesorkhi M, Gomez-Pilar J, Zilio F, Berberian N, Wolff A, Yagoub MCE, Northoff G. The brain and its time: intrinsic neural timescales are key for input processing. Commun Biol 2021; 4:970. [PMID: 34400800 PMCID: PMC8368044 DOI: 10.1038/s42003-021-02483-6] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 07/19/2021] [Indexed: 02/07/2023] Open
Abstract
We process and integrate multiple timescales into one meaningful whole. Recent evidence suggests that the brain displays a complex multiscale temporal organization. Different regions exhibit different timescales as described by the concept of intrinsic neural timescales (INT); however, their function and neural mechanisms remains unclear. We review recent literature on INT and propose that they are key for input processing. Specifically, they are shared across different species, i.e., input sharing. This suggests a role of INT in encoding inputs through matching the inputs' stochastics with the ongoing temporal statistics of the brain's neural activity, i.e., input encoding. Following simulation and empirical data, we point out input integration versus segregation and input sampling as key temporal mechanisms of input processing. This deeply grounds the brain within its environmental and evolutionary context. It carries major implications in understanding mental features and psychiatric disorders, as well as going beyond the brain in integrating timescales into artificial intelligence.
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Affiliation(s)
- Mehrshad Golesorkhi
- grid.28046.380000 0001 2182 2255School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada ,grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Javier Gomez-Pilar
- grid.5239.d0000 0001 2286 5329Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ,grid.413448.e0000 0000 9314 1427Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Madrid, Spain
| | - Federico Zilio
- grid.5608.b0000 0004 1757 3470Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy
| | - Nareg Berberian
- grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Annemarie Wolff
- grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada
| | - Mustapha C. E. Yagoub
- grid.28046.380000 0001 2182 2255School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Canada
| | - Georg Northoff
- grid.28046.380000 0001 2182 2255Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada ,grid.410595.c0000 0001 2230 9154Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China ,grid.13402.340000 0004 1759 700XMental Health Centre, Zhejiang University School of Medicine, Hangzhou, Zhejiang China
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Wiring of higher-order cortical areas: Spatiotemporal development of cortical hierarchy. Semin Cell Dev Biol 2021; 118:35-49. [PMID: 34034988 DOI: 10.1016/j.semcdb.2021.05.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/27/2021] [Accepted: 05/08/2021] [Indexed: 01/04/2023]
Abstract
A hierarchical development of cortical areas was suggested over a century ago, but the diversity and complexity of cortical hierarchy properties have so far prevented a formal demonstration. The aim of this review is to clarify the similarities and differences in the developmental processes underlying cortical development of primary and higher-order areas. We start by recapitulating the historical and recent advances underlying the biological principle of cortical hierarchy in adults. We then revisit the arguments for a hierarchical maturation of cortical areas, and further integrate the principles of cortical areas specification during embryonic and postnatal development. We highlight how the dramatic expansion in cortical size might have contributed to the increased number of association areas sustaining cognitive complexification in evolution. Finally, we summarize the recent observations of an alteration of cortical hierarchy in neuropsychiatric disorders and discuss their potential developmental origins.
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