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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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52
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Zilio F, Lavazza A. Consciousness in a Rotor? Science and Ethics of Potentially Conscious Human Cerebral Organoids. AJOB Neurosci 2023; 14:178-196. [PMID: 36794285 DOI: 10.1080/21507740.2023.2173329] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Human cerebral organoids are three-dimensional biological cultures grown in the laboratory to mimic as closely as possible the cellular composition, structure, and function of the corresponding organ, the brain. For now, cerebral organoids lack blood vessels and other characteristics of the human brain, but are also capable of having coordinated electrical activity. They have been usefully employed for the study of several diseases and the development of the nervous system in unprecedented ways. Research on human cerebral organoids is proceeding at a very fast pace and their complexity is bound to improve. This raises the question of whether cerebral organoids will also be able to develop the unique feature of the human brain, consciousness. If this is the case, some ethical issues would arise. In this article, we discuss the necessary neural correlates and constraints for the emergence of consciousness according to some of the most debated neuroscientific theories. Based on this, we consider what the moral status of a potentially conscious brain organoid might be, in light of ethical and ontological arguments. We conclude by proposing a precautionary principle and some leads for further investigation. In particular, we consider the outcomes of some very recent experiments as entities of a potential new kind.
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Manea AMG, Zilverstand A, Hayden B, Zimmermann J. Neural timescales reflect behavioral demands in freely moving rhesus macaques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.27.534470. [PMID: 37034608 PMCID: PMC10081241 DOI: 10.1101/2023.03.27.534470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/22/2023]
Abstract
Previous work has demonstrated remarkably reproducible and consistent hierarchies of neural timescales across cortical areas at rest. The question arises how such stable hierarchies give rise to adaptive behavior that requires flexible adjustment of temporal coding and integration demands. Potentially, this previously found lack of variability in the hierarchical organization of neural timescales could be a reflection of the structure of the laboratory contexts in which they were measured. Indeed, computational work demonstrates the existence of multiple temporal hierarchies within the same anatomical network when the input structure is altered. We posit that unconstrained behavioral environments where relatively little temporal demands are imposed from the experimenter are an ideal test bed to address the question of whether the hierarchical organization and the magnitude of neural timescales reflect ongoing behavioral demands. To tackle this question, we measured timescales of local field potential activity while rhesus macaques were foraging freely in a large open space. We find a hierarchy of neural timescales that is unique to this foraging environment. Importantly, although the magnitude of neural timescales generally expanded with task engagement, the brain areas' relative position in the hierarchy was stable across the recording sessions. Notably, the magnitude of neural timescales monotonically expanded with task engagement across a relatively long temporal scale spanning the duration of the recording session. Over shorter temporal scales, the magnitude of neural timescales changed dynamically around foraging events. Moreover, the change in the magnitude of neural timescales contained functionally relevant information, differentiating between seemingly similar events in terms of motor demands and associated reward. That is, the patterns of change were associated with the cognitive and behavioral meaning of these events. Finally, we demonstrated that brain areas were differentially affected by these behavioral demands - i.e., the expansion of neural timescales was not the same across all areas. Together, these results demonstrate that the observed hierarchy of neural timescales is context-dependent and that changes in the magnitude of neural timescales are closely related to overall task engagement and behavioral demands.
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Affiliation(s)
- Ana M G Manea
- Department of Neuroscience, University of Minnesota, Minneapolis MN
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis MN
| | - Anna Zilverstand
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis MN
| | - Benjamin Hayden
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis MN
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis MN
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Esmailpour H, Raman R, Vogels R. Inferior temporal cortex leads prefrontal cortex in response to a violation of a learned sequence. Cereb Cortex 2023; 33:3124-3141. [PMID: 35780398 DOI: 10.1093/cercor/bhac265] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/09/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
Primates learn statistical regularities that are embedded in visual sequences, a form of statistical learning. Single-unit recordings in macaques showed that inferior temporal (IT) neurons are sensitive to statistical regularities in visual sequences. Here, we asked whether ventrolateral prefrontal cortex (VLPFC), which is connected to IT, is also sensitive to the transition probabilities in visual sequences and whether the statistical learning signal in IT originates in VLPFC. We recorded simultaneously multiunit activity (MUA) and local field potentials (LFPs) in IT and VLPFC after monkeys were exposed to triplets of images with a fixed presentation order. In both areas, the MUA was stronger to images that violated the learned sequence (deviants) compared to the same images presented in the learned triplets. The high-gamma and beta LFP power showed an enhanced and suppressed response, respectively, to the deviants in both areas. The enhanced response was present also for the image following the deviant, suggesting a sensitivity for temporal adjacent dependencies in IT and VLPFC. The increased response to the deviant occurred later in VLPFC than in IT, suggesting that the deviant response in IT was not inherited from VLPFC. These data support predictive coding theories that propose a feedforward flow of prediction errors.
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Affiliation(s)
- Hamideh Esmailpour
- Laboratorium voor Neuro-en Psychofysiologie, Department of Neurosciences, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
- Leuven Brain Institute, KU Leuven, ON V Herestraat 49, 3000 Leuven, Belgium
| | - Rajani Raman
- Laboratorium voor Neuro-en Psychofysiologie, Department of Neurosciences, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
- Leuven Brain Institute, KU Leuven, ON V Herestraat 49, 3000 Leuven, Belgium
| | - Rufin Vogels
- Laboratorium voor Neuro-en Psychofysiologie, Department of Neurosciences, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
- Leuven Brain Institute, KU Leuven, ON V Herestraat 49, 3000 Leuven, Belgium
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Northoff G, Scalabrini A, Fogel S. Topographic-dynamic reorganisation model of dreams (TRoD) - A spatiotemporal approach. Neurosci Biobehav Rev 2023; 148:105117. [PMID: 36870584 DOI: 10.1016/j.neubiorev.2023.105117] [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: 10/09/2022] [Revised: 12/13/2022] [Accepted: 02/28/2023] [Indexed: 03/06/2023]
Abstract
Dreams are one of the most bizarre and least understood states of consciousness. Bridging the gap between brain and phenomenology of (un)conscious experience, we propose the Topographic-dynamic Re-organization model of Dreams (TRoD). Topographically, dreams are characterized by a shift towards increased activity and connectivity in the default-mode network (DMN) while they are reduced in the central executive network, including the dorsolateral prefrontal cortex (except in lucid dreaming). This topographic re-organization is accompanied by dynamic changes; a shift towards slower frequencies and longer timescales. This puts dreams dynamically in an intermediate position between awake state and NREM 2/SWS sleep. TRoD proposes that the shift towards DMN and slower frequencies leads to an abnormal spatiotemporal framing of input processing including both internally- and externally-generated inputs (from body and environment). In dreams, a shift away from temporal segregation to temporal integration of inputs results in the often bizarre and highly self-centric mental contents as well as hallucinatory-like states. We conclude that topography and temporal dynamics are core features of the TroD, which may provide the connection of neural and mental activity, e.g., brain and experience during dreams as their "common currency".
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Affiliation(s)
- Georg Northoff
- Faculty of Medicine, Centre for Neural Dynamics, The Royal's Institute of Mental Health Research, Brain and Mind Research Institute, University of Ottawa, Ottawa, ON, Canada; Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China.
| | - Andrea Scalabrini
- Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy.
| | - Stuart Fogel
- Sleep and Neuroscience, The Royal's Institute of Mental Health Research, Brain and Mind Research Institute and Faculty of Social Sciences, University of Ottawa, Ottawa, ON, Canada.
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Kent L, Nelson B, Northoff G. Can disorders of subjective time inform the differential diagnosis of psychiatric disorders? A transdiagnostic taxonomy of time. Early Interv Psychiatry 2023; 17:231-243. [PMID: 36935204 DOI: 10.1111/eip.13333] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 02/09/2022] [Accepted: 05/29/2022] [Indexed: 12/01/2022]
Abstract
AIM Time is a core aspect of psychopathology with potential for clinical use and early intervention. Temporal experience, perception, judgement and processing are distorted in various psychiatric disorders such as mood (depression and mania), anxiety, autistic, impulse-control, dissociative and attention-deficit/hyperactivity disorders. Can these disorders of time be used as early diagnostic or predictive markers? To answer this question, we develop a Transdiagnostic Taxonomy of (disordered) Time (TTT) that maps on to the symptomatological, phenomenal, perceptual and functional descriptions of each underlying disorder in a 2 × 2 × 2 state space. Temporal distortions may precede functional decline, and so assist efforts at early detection and intervention in at-risk groups. METHOD Firstly, this article integrates a psychological model of how time is processed with a subjective or phenomenological model of how time is experienced or perceived. Secondly, the integrated combined model of time is then used to heuristically map major psychiatric disorders on to the basic elements of temporal flow and integration. RESULTS The TTT systematically describes the basic temporal nature of eight diagnostic categories of psychiatric illness. It differentiates between diagnoses primarily associated with distorted "macro-level" phenomenal temporal experiences (i.e. anxiety, dissociation/PTSD, depression, and mania) from those primarily related to distorted 'micro-level' temporal processing (i.e. psychotic, impulse-control, autistic and attention-deficit/hyperactivity disorders). CONCLUSIONS The TTT allows differential diagnostic classification of various psychiatric disorders in terms of a possible underlying time disorder, making it useful for future diagnostic and predictive purposes using novel techniques of temporal processing, time perception, passage of time, and time perspective.
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Affiliation(s)
- Lachlan Kent
- Royal Melbourne Institute of Technology, Melbourne, Victoria, Australia
| | - Barnaby Nelson
- Centre for Youth Mental Health, The University of Melbourne, Victoria, Australia
| | - Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Zhejiang, Hangzhou, People's Republic of China
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, People's Republic of China
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Intrinsic neural timescales mediate the cognitive bias of self - temporal integration as key mechanism. Neuroimage 2023; 268:119896. [PMID: 36693598 DOI: 10.1016/j.neuroimage.2023.119896] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 01/10/2023] [Accepted: 01/20/2023] [Indexed: 01/22/2023] Open
Abstract
Our perceptions and decisions are not always objectively correct as they are featured by a bias related to our self. What are the behavioral, neural, and computational mechanisms of such cognitive bias? Addressing this yet unresolved question, we here investigate whether the cognitive bias is related to temporal integration and segregation as mediated by the brain's Intrinsic neural timescales (INT). Using Signal Detection Theory (SDT), we operationalize the cognitive bias by the Criterion C as distinguished from the sensitivity index d'. This was probed in a self-task based on morphed self- and other faces. Behavioral data demonstrate clear cognitive bias, i.e., Criterion C. That was related to the EEG-based INT as measured by the autocorrelation window (ACW) in especially the transmodal regions dorsolateral prefrontal cortex (dlPFC) and default-mode network (DMN) as distinct from unimodal visual cortex. Finally, simulation of the same paradigm in a large-scale network model shows high degrees of temporal integration of temporally distinct inputs in CMS/DMN and dlPFC while temporal segregation predominates in visual cortex. Together, we demonstrate a key role of INT-based temporal integration in CMS/DMN and dlPFC including its relation to the brain's uni-transmodal topographical organization in mediating the cognitive bias of our self.
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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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Shafiei G, Fulcher BD, Voytek B, Satterthwaite TD, Baillet S, Misic B. Neurophysiological signatures of cortical micro-architecture. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.23.525101. [PMID: 36747831 PMCID: PMC9900796 DOI: 10.1101/2023.01.23.525101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Systematic spatial variation in micro-architecture is observed across the cortex. These micro-architectural gradients are reflected in neural activity, which can be captured by neurophysiological time-series. How spontaneous neurophysiological dynamics are organized across the cortex and how they arise from heterogeneous cortical micro-architecture remains unknown. Here we extensively profile regional neurophysiological dynamics across the human brain by estimating over 6 800 timeseries features from the resting state magnetoencephalography (MEG) signal. We then map regional time-series profiles to a comprehensive multi-modal, multi-scale atlas of cortical micro-architecture, including microstructure, metabolism, neurotransmitter receptors, cell types and laminar differentiation. We find that the dominant axis of neurophysiological dynamics reflects characteristics of power spectrum density and linear correlation structure of the signal, emphasizing the importance of conventional features of electromagnetic dynamics while identifying additional informative features that have traditionally received less attention. Moreover, spatial variation in neurophysiological dynamics is colocalized with multiple micro-architectural features, including genomic gradients, intracortical myelin, neurotransmitter receptors and transporters, and oxygen and glucose metabolism. Collectively, this work opens new avenues for studying the anatomical basis of neural activity.
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Affiliation(s)
- Golia Shafiei
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, NSW 2006, Australia
| | - Bradley Voytek
- Department of Cognitive Science, Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, USA
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
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Kringelbach ML, Perl YS, Tagliazucchi E, Deco G. Toward naturalistic neuroscience: Mechanisms underlying the flattening of brain hierarchy in movie-watching compared to rest and task. SCIENCE ADVANCES 2023; 9:eade6049. [PMID: 36638163 PMCID: PMC9839335 DOI: 10.1126/sciadv.ade6049] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 12/13/2022] [Indexed: 06/04/2023]
Abstract
Identifying the functional specialization of the brain has moved from using cognitive tasks and resting state to using ecological relevant, naturalistic movies. We leveraged a large-scale neuroimaging dataset to directly investigate the hierarchical reorganization of functional brain activity when watching naturalistic films compared to performing seven cognitive tasks and resting. A thermodynamics-inspired whole-brain model paradigm revealed the generative underlying mechanisms for changing the balance in causal interactions between brain regions in different conditions. Paradoxically, the hierarchy is flatter for movie-watching, and the level of nonreversibility is significantly smaller in comparison to both rest and tasks, where the latter in turn have the highest levels of hierarchy and nonreversibility. The underlying mechanisms were revealed by the model-based generative effective connectivity (GEC). Naturalistic films could therefore provide a fast and convenient way to measure important changes in GEC (integrating functional and anatomical connectivity) found in, for example, neuropsychiatric disorders. Overall, this study demonstrates the benefits of moving toward a more naturalistic neuroscience.
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Affiliation(s)
- Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Yonatan Sanz Perl
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain
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Buccellato A, Zang D, Zilio F, Gomez-Pilar J, Wang Z, Qi Z, Zheng R, Xu Z, Wu X, Bisiacchi P, Felice AD, Mao Y, Northoff G. Disrupted relationship between intrinsic neural timescales and alpha peak frequency during unconscious states - A high-density EEG study. Neuroimage 2023; 265:119802. [PMID: 36503159 DOI: 10.1016/j.neuroimage.2022.119802] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/22/2022] [Accepted: 12/07/2022] [Indexed: 12/13/2022] Open
Abstract
Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.
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Affiliation(s)
- Andrea Buccellato
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy.
| | - Di Zang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, Valladolid 47011, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain
| | - Zhe Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Ruizhe Zheng
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Zeyu Xu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Xuehai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Patrizia Bisiacchi
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy
| | - Alessandra Del Felice
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China.
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Ontario K1Z7K4, Canada; Mental Health Center, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang Province, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310013, Zhejiang Province, China.
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62
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Klar P, Çatal Y, Langner R, Huang Z, Northoff G. Scale-free dynamics of core-periphery topography. Hum Brain Mapp 2022; 44:1997-2017. [PMID: 36579661 PMCID: PMC9980897 DOI: 10.1002/hbm.26187] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 11/15/2022] [Accepted: 12/11/2022] [Indexed: 12/30/2022] Open
Abstract
The human brain's cerebral cortex exhibits a topographic division into higher-order transmodal core and lower-order unimodal periphery regions. While timescales between the core and periphery region diverge, features of their power spectra, especially scale-free dynamics during resting-state and their mdulation in task states, remain unclear. To answer this question, we investigated the ~1/f-like pink noise manifestation of scale-free dynamics in the core-periphery topography during rest and task states applying infra-slow inter-trial intervals up to 1 min falling inside the BOLD's infra-slow frequency band. The results demonstrate (1) higher resting-state power-law exponent (PLE) in the core compared to the periphery region; (2) significant PLE increases in task across the core and periphery regions; and (3) task-related PLE increases likely followed the task's atypically low event rates, namely the task's periodicity (inter-trial interval = 52-60 s; 0.016-0.019 Hz). A computational model and a replication dataset that used similar infra-slow inter-trial intervals provide further support for our main findings. Altogether, the results show that scale-free dynamics differentiate core and periphery regions in the resting-state and mediate task-related effects.
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Affiliation(s)
- Philipp Klar
- Medical Faculty, C. & O. Vogt‐Institute for Brain ResearchHeinrich Heine University of DüsseldorfDüsseldorfGermany
| | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of MedicineUniversity of OttawaOttawaOntarioCanada
| | - Robert Langner
- Institute of Systems NeuroscienceHeinrich Heine University DusseldorfDusseldorfGermany,Institute of Neuroscience and MedicineBrain & Behaviour (INM‐7), Research Centre JülichJülichGermany
| | - Zirui Huang
- Department of AnesthesiologyUniversity of Michigan Medical SchoolAnn ArborMichiganUSA,Center for Consciousness ScienceUniversity of Michigan Medical SchoolAnn ArborMichiganUSA
| | - Georg Northoff
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of MedicineUniversity of OttawaOttawaOntarioCanada,Centre for Cognition and Brain DisordersHangzhou Normal UniversityHangzhouZhejiangChina
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63
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Parkes L, Kim JZ, Stiso J, Calkins ME, Cieslak M, Gur RE, Gur RC, Moore TM, Ouellet M, Roalf DR, Shinohara RT, Wolf DH, Satterthwaite TD, Bassett DS. Asymmetric signaling across the hierarchy of cytoarchitecture within the human connectome. SCIENCE ADVANCES 2022; 8:eadd2185. [PMID: 36516263 PMCID: PMC9750154 DOI: 10.1126/sciadv.add2185] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 11/10/2022] [Indexed: 05/30/2023]
Abstract
Cortical variations in cytoarchitecture form a sensory-fugal axis that shapes regional profiles of extrinsic connectivity and is thought to guide signal propagation and integration across the cortical hierarchy. While neuroimaging work has shown that this axis constrains local properties of the human connectome, it remains unclear whether it also shapes the asymmetric signaling that arises from higher-order topology. Here, we used network control theory to examine the amount of energy required to propagate dynamics across the sensory-fugal axis. Our results revealed an asymmetry in this energy, indicating that bottom-up transitions were easier to complete compared to top-down. Supporting analyses demonstrated that asymmetries were underpinned by a connectome topology that is wired to support efficient bottom-up signaling. Lastly, we found that asymmetries correlated with differences in communicability and intrinsic neuronal time scales and lessened throughout youth. Our results show that cortical variation in cytoarchitecture may guide the formation of macroscopic connectome topology.
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Affiliation(s)
- Linden Parkes
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jason Z. Kim
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jennifer Stiso
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Monica E. Calkins
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Matthew Cieslak
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Radiology, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Radiology, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Tyler M. Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mathieu Ouellet
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R. Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Russell T. Shinohara
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel H. Wolf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dani S. Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
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64
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Zhang J, Northoff G. Beyond noise to function: reframing the global brain activity and its dynamic topography. Commun Biol 2022; 5:1350. [PMID: 36481785 PMCID: PMC9732046 DOI: 10.1038/s42003-022-04297-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 11/24/2022] [Indexed: 12/13/2022] Open
Abstract
How global and local activity interact with each other is a common question in complex systems like climate and economy. Analogously, the brain too displays 'global' activity that interacts with local-regional activity and modulates behavior. The brain's global activity, investigated as global signal in fMRI, so far, has mainly been conceived as non-neuronal noise. We here review the findings from healthy and clinical populations to demonstrate the neural basis and functions of global signal to brain and behavior. We show that global signal (i) is closely coupled with physiological signals and modulates the arousal level; and (ii) organizes an elaborated dynamic topography and coordinates the different forms of cognition. We also postulate a Dual-Layer Model including both background and surface layers. Together, the latest evidence strongly suggests the need to go beyond the view of global signal as noise by embracing a dual-layer model with background and surface layer.
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Affiliation(s)
- Jianfeng Zhang
- grid.263488.30000 0001 0472 9649Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China ,grid.263488.30000 0001 0472 9649School of Psychology, Shenzhen University, Shenzhen, China
| | - Georg Northoff
- grid.13402.340000 0004 1759 700XMental Health Center, Zhejiang University School of Medicine, Hangzhou, China ,grid.28046.380000 0001 2182 2255Institute of Mental Health Research, University of Ottawa, Ottawa, Canada ,grid.410595.c0000 0001 2230 9154Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
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65
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Adolfi F, Wareham T, van Rooij I. A Computational Complexity Perspective on Segmentation as a Cognitive Subcomputation. Top Cogn Sci 2022; 15:255-273. [PMID: 36453947 DOI: 10.1111/tops.12629] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 10/06/2022] [Accepted: 10/07/2022] [Indexed: 12/05/2022]
Abstract
Computational feasibility is a widespread concern that guides the framing and modeling of natural and artificial intelligence. The specification of cognitive system capacities is often shaped by unexamined intuitive assumptions about the search space and complexity of a subcomputation. However, a mistaken intuition might make such initial conceptualizations misleading for what empirical questions appear relevant later on. We undertake here computational-level modeling and complexity analyses of segmentation - a widely hypothesized subcomputation that plays a requisite role in explanations of capacities across domains, such as speech recognition, music cognition, active sensing, event memory, action parsing, and statistical learning - as a case study to show how crucial it is to formally assess these assumptions. We mathematically prove two sets of results regarding computational hardness and search space size that may run counter to intuition, and position their implications with respect to existing views on the subcapacity.
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Affiliation(s)
- Federico Adolfi
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max‐Planck Society
- School of Psychological Science University of Bristol
| | - Todd Wareham
- Department of Computer Science Memorial University of Newfoundland
| | - Iris van Rooij
- Donders Institute for Brain, Cognition, and Behaviour Radboud University
- School of Artificial Intelligence Radboud University
- Department of Linguistics, Cognitive Science, and Semiotics & Interacting Minds Centre Aarhus University
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66
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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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67
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Hsu C, Liu T, Lee D, Yeh D, Chen Y, Liang W, Juan C. Amplitude modulating frequency overrides carrier frequency in tACS-induced phosphene percept. Hum Brain Mapp 2022; 44:914-926. [PMID: 36250439 PMCID: PMC9875935 DOI: 10.1002/hbm.26111] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 09/24/2022] [Accepted: 10/03/2022] [Indexed: 01/28/2023] Open
Abstract
The amplitude modulated (AM) neural oscillation is an essential feature of neural dynamics to coordinate distant brain areas. The AM transcranial alternating current stimulation (tACS) has recently been adopted to examine various cognitive functions, but its neural mechanism remains unclear. The current study utilized the phosphene phenomenon to investigate whether, in an AM-tACS, the AM frequency could modulate or even override the carrier frequency in phosphene percept. We measured the phosphene threshold and the perceived flash rate/pattern from 12 human subjects (four females, aged from 20-44 years old) under tACS that paired carrier waves (10, 14, 18, 22 Hz) with different envelope conditions (0, 2, 4 Hz) over the mid-occipital and left facial areas. We also examined the phosphene source by adopting a high-density stimulation montage. Our results revealed that (1) phosphene threshold was higher for AM-tACS than sinusoidal tACS and demonstrated different carrier frequency functions in two stimulation montages. (2) AM-tACS slowed down the phosphene flashing and abolished the relation between the carrier frequency and flash percept in sinusoidal tACS. This effect was independent of the intensity change of the stimulation. (3) Left facial stimulation elicited phosphene in the upper-left visual field, while occipital stimulation elicited equally distributed phosphene. (4) The near-eye electrodermal activity (EDA) measured under the threshold-level occipital tACS was greater than the lowest power sufficient to elicit retinal phosphene. Our results show that AM frequency may override the carrier frequency and determine the perceived flashing frequency of AM-tACS-induced phosphene.
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Affiliation(s)
- Che‐Yi Hsu
- Institute of Cognitive Neuroscience, College of Health Sciences and TechnologyNational Central UniversityTaoyuanTaiwan
| | - Tzu‐Ling Liu
- Institute of Cognitive Neuroscience, College of Health Sciences and TechnologyNational Central UniversityTaoyuanTaiwan,Cognitive Intelligence and Precision Healthcare Research CenterNational Central UniversityTaoyuanTaiwan
| | - Dong‐Han Lee
- Institute of Cognitive Neuroscience, College of Health Sciences and TechnologyNational Central UniversityTaoyuanTaiwan,Cognitive Intelligence and Precision Healthcare Research CenterNational Central UniversityTaoyuanTaiwan
| | - Ding‐Ruey Yeh
- Institute of Cognitive Neuroscience, College of Health Sciences and TechnologyNational Central UniversityTaoyuanTaiwan
| | - Yan‐Hsun Chen
- Institute of Cognitive Neuroscience, College of Health Sciences and TechnologyNational Central UniversityTaoyuanTaiwan,Cognitive Intelligence and Precision Healthcare Research CenterNational Central UniversityTaoyuanTaiwan
| | - Wei‐Kuang Liang
- Institute of Cognitive Neuroscience, College of Health Sciences and TechnologyNational Central UniversityTaoyuanTaiwan,Cognitive Intelligence and Precision Healthcare Research CenterNational Central UniversityTaoyuanTaiwan
| | - Chi‐Hung Juan
- Institute of Cognitive Neuroscience, College of Health Sciences and TechnologyNational Central UniversityTaoyuanTaiwan,Cognitive Intelligence and Precision Healthcare Research CenterNational Central UniversityTaoyuanTaiwan,Department of PsychologyKaohsiung Medical UniversityKaohsiungTaiwan
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68
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Cooper AC, Ventura B, Northoff G. Beyond the veil of duality-topographic reorganization model of meditation. Neurosci Conscious 2022; 2022:niac013. [PMID: 36237370 PMCID: PMC9552929 DOI: 10.1093/nc/niac013] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 08/08/2022] [Accepted: 09/01/2022] [Indexed: 11/14/2022] Open
Abstract
Meditation can exert a profound impact on our mental life, with proficient practitioners often reporting an experience free of boundaries between a separate self and the environment, suggesting an explicit experience of "nondual awareness." What are the neural correlates of such experiences and how do they relate to the idea of nondual awareness itself? In order to unravel the effects that meditation has on the brain's spatial topography, we review functional magnetic resonance imaging brain findings from studies specific to an array of meditation types and meditator experience levels. We also review findings from studies that directly probe the interaction between meditation and the experience of the self. The main results are (i) decreased posterior default mode network (DMN) activity, (ii) increased central executive network (CEN) activity, (iii) decreased connectivity within posterior DMN as well as between posterior and anterior DMN, (iv) increased connectivity within the anterior DMN and CEN, and (v) significantly impacted connectivity between the DMN and CEN (likely a nonlinear phenomenon). Together, these suggest a profound organizational shift of the brain's spatial topography in advanced meditators-we therefore propose a topographic reorganization model of meditation (TRoM). One core component of the TRoM is that the topographic reorganization of DMN and CEN is related to a decrease in the mental-self-processing along with a synchronization with the more nondual layers of self-processing, notably interoceptive and exteroceptive-self-processing. This reorganization of the functionality of both brain and self-processing can result in the explicit experience of nondual awareness. In conclusion, this review provides insight into the profound neural effects of advanced meditation and proposes a result-driven unifying model (TRoM) aimed at identifying the inextricably tied objective (neural) and subjective (experiential) effects of meditation.
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Affiliation(s)
- Austin Clinton Cooper
- Integrated Program of Neuroscience, Room 302, Irving Ludmer Building, 1033 Pine Avenue W., McGill University, Montreal, QC H3A 1A1, Canada
| | - Bianca Ventura
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
- Mental Health Center, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou 310058, China
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69
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Zhang H, Zhao R, Hu X, Guan S, Margulies DS, Meng C, Biswal BB. Cortical connectivity gradients and local timescales during cognitive states are modulated by cognitive loads. Brain Struct Funct 2022; 227:2701-2712. [PMID: 36098843 DOI: 10.1007/s00429-022-02564-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 08/29/2022] [Indexed: 11/02/2022]
Abstract
Although resting-state fMRI studies support that human brain is topographically organized regarding localized and distributed processes, it is still unclear about the task-modulated cortical hierarchy in terms of distributed functional connectivity and localized timescales. To address, current study investigated the effect of cognitive load on cortical connectivity gradients and local timescales in the healthy brain using resting state fMRI as well as 1- and 2-back working memory task fMRI. The results demonstrated that (1) increased cognitive load was associated with lower principal gradient in transmodal cortices, higher principal gradient in primary cortices, decreased decay rate and reduced timescale variability; (2) global properties including gradient variability, timescale decay rate, timescale variability and network topology were all modulated by cognitive load, with timescale variability related to behavioral performance; and (3) at 2-back state, the timescale variability was indirectly and negatively linked with global network integration, which was mediated by gradient variability. In conclusion, current study provides novel evidence for load-modulated cortical connectivity gradients and local timescales during cognitive states, which could contribute to better understanding about cognitive load theory and brain disorders with cognitive dysfunction.
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Affiliation(s)
- Heming Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, Chengdu, 611731, China
| | - Rong Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, Chengdu, 611731, China
| | - Xin Hu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, Chengdu, 611731, China
| | - Sihai Guan
- Key Laboratory of Electronic and Information Engineering (Southwest Minzu University), State Ethnic Affairs Commission. College of Electronic and Information, Southwest Minzu University, Chengdu, 610225, China
| | - Daniel S Margulies
- Max Planck Research Group for Neuroanatomy & Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
| | - Chun Meng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, Chengdu, 611731, China.
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, Chengdu, 611731, China. .,Department of Biomedical Engineering, New Jersey Institute of Technology, University Height, 607 Fenster Hall, Newark, NJ, 07102, USA.
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70
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Djebbara Z, Jensen OB, Parada FJ, Gramann K. Neuroscience and architecture: Modulating behavior through sensorimotor responses to the built environment. Neurosci Biobehav Rev 2022; 138:104715. [PMID: 35654280 DOI: 10.1016/j.neubiorev.2022.104715] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 11/18/2022]
Abstract
As we move through the world, natural and built environments implicitly guide behavior by appealing to certain sensory and motor dynamics. This process can be motivated by automatic attention to environmental features that resonate with specific sensorimotor responses. This review aims at providing a psychobiological framework describing how environmental features can lead to automated sensorimotor responses through defined neurophysiological mechanisms underlying attention. Through the use of automated processes in subsets of cortical structures, the goal of this framework is to describe on a neuronal level the functional link between the designed environment and sensorimotor responses. By distinguishing between environmental features and sensorimotor responses we elaborate on how automatic behavior employs the environment for sensorimotor adaptation. This is realized through a thalamo-cortical network integrating environmental features with motor aspects of behavior. We highlight the underlying transthalamic transmission from an Enactive and predictive perspective and review recent studies that effectively modulated behavior by systematically manipulating environmental features. We end by suggesting a promising combination of neuroimaging and computational analysis for future studies.
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Affiliation(s)
- Zakaria Djebbara
- Department of Architecture, Design, Media, and Technology, Aalborg University, Aalborg, Denmark; Biopsychology and Neuroergonomics, Technical University Berlin, Berlin, Germany.
| | - Ole B Jensen
- Department of Architecture, Design, Media, and Technology, Aalborg University, Aalborg, Denmark
| | - Francisco J Parada
- Centro de Estudios en Neurociencia Humana y Neuropsicología, Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
| | - Klaus Gramann
- Biopsychology and Neuroergonomics, Technical University Berlin, Berlin, Germany
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71
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Smith D, Wolff A, Wolman A, Ignaszewski J, Northoff G. Temporal continuity of self: Long autocorrelation windows mediate self-specificity. Neuroimage 2022; 257:119305. [PMID: 35568347 DOI: 10.1016/j.neuroimage.2022.119305] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 04/13/2022] [Accepted: 05/10/2022] [Indexed: 11/27/2022] Open
Abstract
The self is characterized by an intrinsic temporal component consisting in continuity across time. On the neural level, this temporal continuity manifests in the brain's intrinsic neural timescales (INT) that can be measured by the autocorrelation window (ACW). Recent EEG studies reveal a relationship between resting state ACW and self-consciousness. However, it remains unclear whether ACW exhibits different degrees of task-related changes during self-specific compared to non-self-specific activities. To this end, participants in our study initially recorded an eight-minute autobiographical narrative. Following a resting-state session, participants were presented with their own narrative and the narrative of a stranger while undergoing concurrent EEG recording. Behaviorally, subjects evaluated both of the narratives and indicated their perceptions of positivity or negativity on a moment-to-moment basis by positioning a cursor relative to the center of the computer screen. Our results indicate: (a) greater spatial extension and velocity in the behavioral cursor movement during the self narrative assessment compared to the non-self narrative assessment; and (b) longer neural ACWs in response to the self- compared to the non-self narrative and rest. These findings demonstrate the importance of longer temporal windows in neural activity measured by ACWs for self-specificity. More broadly, the results highlight the relevance of temporal continuity for the self on the neural level. Such temporal continuity may, correspondingly, also manifest on the psychological level as a "common currency" between brain and self.
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Affiliation(s)
- David Smith
- Carleton University, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada; Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada.
| | - Annemarie Wolff
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Angelika Wolman
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Julia Ignaszewski
- Carleton University, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada; Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Unit, Institute of Mental Health Research, Royal Ottawa Mental Health Centre and University of Ottawa, 1145 Carling Avenue, 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, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Tianmu Road 305, Hangzhou 310013, China.
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72
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Hsu TY, Zhou JF, Yeh SL, Northoff G, Lane TJ. Intrinsic neural activity predisposes susceptibility to a body illusion. Cereb Cortex Commun 2022; 3:tgac012. [PMID: 35382092 PMCID: PMC8976633 DOI: 10.1093/texcom/tgac012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 02/21/2022] [Accepted: 03/01/2022] [Indexed: 11/13/2022] Open
Abstract
Susceptibility to the rubber hand illusion (RHI) varies. To date, however, there is no consensus explanation of this variability. Previous studies, focused on the role of multisensory integration, have searched for neural correlates of the illusion. But those studies have failed to identify a sufficient set of functionally specific neural correlates. Because some evidence suggests that frontal α power is one means of tracking neural instantiations of self, we hypothesized that the higher the frontal α power during the eyes-closed resting state, the more stable the self. As a corollary, we infer that the more stable the self, the less susceptible are participants to a blurring of boundaries—to feeling that the rubber hand belongs to them. Indeed, we found that frontal α amplitude oscillations negatively correlate with susceptibility. Moreover, since lower frequencies often modulate higher frequencies, we explored the possibility that this might be the case for the RHI. Indeed, some evidence suggests that high frontal α power observed in low-RHI participants is modulated by δ frequency oscillations. We conclude that while neural correlates of multisensory integration might be necessary for the RHI, sufficient explanation involves variable intrinsic neural activity that modulates how the brain responds to incompatible sensory stimuli.
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Affiliation(s)
- Tzu-Yu Hsu
- Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Centre, TMU Shuang Ho Hospital, New Taipei City, Taiwan
| | - Ji-Fan Zhou
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hang Zhou, China
| | - Su-Ling Yeh
- Department of Psychology, National Taiwan University, Taipei, Taiwan
- Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, Taiwan
- Neurobiology and Cognitive Neuroscience Center, National Taiwan University, Taipei, Taiwan
- Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, Taipei, Taiwan
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
| | - Timothy Joseph Lane
- Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Centre, TMU Shuang Ho Hospital, New Taipei City, Taiwan
- Institute of European and American Studies, Academia Sinica, Taipei, Taiwan
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73
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Golesorkhi M, Gomez-Pilar J, Çatal Y, Tumati S, Yagoub MCE, Stamatakis EA, Northoff G. From temporal to spatial topography: hierarchy of neural dynamics in higher- and lower-order networks shapes their complexity. Cereb Cortex 2022; 32:5637-5653. [PMID: 35188968 PMCID: PMC9753094 DOI: 10.1093/cercor/bhac042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 01/25/2023] Open
Abstract
The brain shows a topographical hierarchy along the lines of lower- and higher-order networks. The exact temporal dynamics characterization of this lower-higher-order topography at rest and its impact on task states remains unclear, though. Using 2 functional magnetic resonance imaging data sets, we investigate lower- and higher-order networks in terms of the signal compressibility, operationalized by Lempel-Ziv complexity (LZC). As we assume that this degree of complexity is related to the slow-fast frequency balance, we also compute the median frequency (MF), an estimation of frequency distribution. We demonstrate (i) topographical differences at rest between higher- and lower-order networks, showing lower LZC and MF in the former; (ii) task-related and task-specific changes in LZC and MF in both lower- and higher-order networks; (iii) hierarchical relationship between LZC and MF, as MF at rest correlates with LZC rest-task change along the lines of lower- and higher-order networks; and (iv) causal and nonlinear relation between LZC at rest and LZC during task, with MF at rest acting as mediator. Together, results show that the topographical hierarchy of lower- and higher-order networks converges with their temporal hierarchy, with these neural dynamics at rest shaping their range of complexity during task states in a nonlinear way.
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Affiliation(s)
| | | | - Yasir Çatal
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa ON K1Z 7K4, Canada
| | - Shankar Tumati
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa ON K1Z 7K4, Canada
| | - Mustapha C E Yagoub
- School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa ON K1Z 7K4, Canada
| | - Emanuel A Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge CB1 0SP, United Kingdom
| | - Georg Northoff
- Corresponding author: Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Canada.
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74
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From Shorter to Longer Timescales: Converging Integrated Information Theory (IIT) with the Temporo-Spatial Theory of Consciousness (TTC). ENTROPY 2022; 24:e24020270. [PMID: 35205564 PMCID: PMC8871397 DOI: 10.3390/e24020270] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/19/2022] [Accepted: 02/10/2022] [Indexed: 02/01/2023]
Abstract
Time is a key element of consciousness as it includes multiple timescales from shorter to longer ones. This is reflected in our experience of various short-term phenomenal contents at discrete points in time as part of an ongoing, more continuous, and long-term ‘stream of consciousness.’ Can Integrated Information Theory (IIT) account for this multitude of timescales of consciousness? According to the theory, the relevant spatiotemporal scale for consciousness is the one in which the system reaches the maximum cause-effect power; IIT currently predicts that experience occurs on the order of short timescales, namely, between 100 and 300 ms (theta and alpha frequency range). This can well account for the integration of single inputs into a particular phenomenal content. However, such short timescales leave open the temporal relation of specific phenomenal contents to others during the course of the ongoing time, that is, the stream of consciousness. For that purpose, we converge the IIT with the Temporo-spatial Theory of Consciousness (TTC), which, assuming a multitude of different timescales, can take into view the temporal integration of specific phenomenal contents with other phenomenal contents over time. On the neuronal side, this is detailed by considering those neuronal mechanisms driving the non-additive interaction of pre-stimulus activity with the input resulting in stimulus-related activity. Due to their non-additive interaction, the single input is not only integrated with others in the short-term timescales of 100–300 ms (alpha and theta frequencies) (as predicted by IIT) but, at the same time, also virtually expanded in its temporal (and spatial) features; this is related to the longer timescales (delta and slower frequencies) that are carried over from pre-stimulus to stimulus-related activity. Such a non-additive pre-stimulus-input interaction amounts to temporo-spatial expansion as a key mechanism of TTC for the constitution of phenomenal contents including their embedding or nesting within the ongoing temporal dynamic, i.e., the stream of consciousness. In conclusion, we propose converging the short-term integration of inputs postulated in IIT (100–300 ms as in the alpha and theta frequency range) with the longer timescales (in delta and slower frequencies) of temporo-spatial expansion in TTC.
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75
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Northoff G, Zilio F. Temporo-spatial Theory of Consciousness (TTC) - Bridging the gap of neuronal activity and phenomenal states. Behav Brain Res 2022; 424:113788. [PMID: 35149122 DOI: 10.1016/j.bbr.2022.113788] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 02/04/2022] [Accepted: 02/04/2022] [Indexed: 01/22/2023]
Abstract
Consciousness and its neural mechanisms remain a mystery. Current neuroscientific theories focus predominantly on the external input/stimulus and the associated stimulus-related activity during conscious contents. Despite all progress, we encounter two gaps: (i) a gap between spontaneous and stimulus-related activity; (ii) a gap between neuronal and phenomenal features. A novel, different, and unique approach, Temporo-spatial theory of consciousness (TTC) aims to bridge both gaps. The TTC focuses on the brain's spontaneous activity and how its spatial topography and temporal dynamic shape stimulus-related activity and resurface in the corresponding spatial and temporal features of consciousness, i.e., 'common currency'. The TTC introduces four temporo-spatial mechanisms: expansion, globalization, alignment, and nestedness. These are associated with distinct dimensions of consciousness including phenomenal content, access, form/structure, and level/state, respectively. Following up on the first introduction of the TTC in 2017, we review updates, further develop these temporo-spatial mechanisms, and postulate specific neurophenomenal hypotheses. We conclude that the TTC offers a viable approach for (i) linking spontaneous and stimulus-related activity in conscious states; (ii) determining specific neuronal and neurophenomenal mechanisms for the distinct dimensions of consciousness; (iii) an integrative and unifying framework of different neuroscientific theories of consciousness; and (iv) offers novel empirically grounded conceptual assumptions about the biological and ontological nature of consciousness and its relation to the brain.
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Affiliation(s)
- 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.
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua, Padua, Italy.
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76
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Whyte CJ, Hohwy J, Smith R. An active inference model of conscious access: How cognitive action selection reconciles the results of report and no-report paradigms. CURRENT RESEARCH IN NEUROBIOLOGY 2022; 3:100036. [PMID: 36304590 PMCID: PMC9593308 DOI: 10.1016/j.crneur.2022.100036] [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: 01/11/2022] [Revised: 03/08/2022] [Accepted: 03/18/2022] [Indexed: 10/31/2022] Open
Abstract
Cognitive theories of consciousness, such as global workspace theory and higher-order theories, posit that frontoparietal circuits play a crucial role in conscious access. However, recent studies using no-report paradigms have posed a challenge to cognitive theories by demonstrating conscious accessibility in the apparent absence of prefrontal cortex (PFC) activation. To address this challenge, this paper presents a computational model of conscious access, based upon active inference, that treats working memory gating as a cognitive action. We simulate a visual masking task and show that late P3b-like event-related potentials (ERPs), and increased PFC activity, are induced by the working memory demands of self-report generation. When reporting demands are removed, these late ERPs vanish and PFC activity is reduced. These results therefore reproduce, and potentially explain, results from no-report paradigms. However, even without reporting demands, our model shows that simulated PFC activity on visible stimulus trials still crosses the threshold for reportability - maintaining the link between PFC and conscious access. Therefore, our simulations show that evidence provided by no-report paradigms does not necessarily contradict cognitive theories of consciousness.
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Affiliation(s)
- Christopher J. Whyte
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Corresponding author. MRC Cognition and Brain Sciences Unit, 15 Chaucer Rd, Cambridge, CB2 7EF, UK.
| | - Jakob Hohwy
- Centre for Consciousness & Contemplative Studies, Monash University, Melbourne, Australia
| | - Ryan Smith
- Laureate Institute for Brain Research, Tulsa, OK, USA
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