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Lemoine É, Neves Briard J, Rioux B, Gharbi O, Podbielski R, Nauche B, Toffa D, Keezer M, Lesage F, Nguyen DK, Bou Assi E. Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review. Comput Struct Biotechnol J 2024; 24:66-86. [PMID: 38204455 PMCID: PMC10776381 DOI: 10.1016/j.csbj.2023.12.006] [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: 09/26/2023] [Revised: 12/05/2023] [Accepted: 12/05/2023] [Indexed: 01/12/2024] Open
Abstract
Background Computational analysis of routine electroencephalogram (rEEG) could improve the accuracy of epilepsy diagnosis. We aim to systematically assess the diagnostic performances of computed biomarkers for epilepsy in individuals undergoing rEEG. Methods We searched MEDLINE, EMBASE, EBM reviews, IEEE Explore and the grey literature for studies published between January 1961 and December 2022. We included studies reporting a computational method to diagnose epilepsy based on rEEG without relying on the identification of interictal epileptiform discharges or seizures. Diagnosis of epilepsy as per a treating physician was the reference standard. We assessed the risk of bias using an adapted QUADAS-2 tool. Results We screened 10 166 studies, and 37 were included. The sample size ranged from 8 to 192 (mean=54). The computed biomarkers were based on linear (43%), non-linear (27%), connectivity (38%), and convolutional neural networks (10%) models. The risk of bias was high or unclear in all studies, more commonly from spectrum effect and data leakage. Diagnostic accuracy ranged between 64% and 100%. We observed high methodological heterogeneity, preventing pooling of accuracy measures. Conclusion The current literature provides insufficient evidence to reliably assess the diagnostic yield of computational analysis of rEEG. Significance We provide guidelines regarding patient selection, reference standard, algorithms, and performance validation.
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Affiliation(s)
- Émile Lemoine
- Department of Neurosciences, University of Montreal, Canada
- Institute of biomedical engineering, Polytechnique Montreal, Canada
- University of Montreal Hospital Center’s Research Center, Canada
| | - Joel Neves Briard
- Department of Neurosciences, University of Montreal, Canada
- University of Montreal Hospital Center’s Research Center, Canada
| | - Bastien Rioux
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Oumayma Gharbi
- Department of Neurosciences, University of Montreal, Canada
- University of Montreal Hospital Center’s Research Center, Canada
| | | | - Bénédicte Nauche
- University of Montreal Hospital Center’s Research Center, Canada
| | - Denahin Toffa
- Department of Neurosciences, University of Montreal, Canada
- University of Montreal Hospital Center’s Research Center, Canada
| | - Mark Keezer
- Department of Neurosciences, University of Montreal, Canada
- School of Public Health, University of Montreal, Canada
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, the Netherlands
| | - Frédéric Lesage
- Institute of biomedical engineering, Polytechnique Montreal, Canada
| | - Dang K. Nguyen
- Department of Neurosciences, University of Montreal, Canada
- University of Montreal Hospital Center’s Research Center, Canada
| | - Elie Bou Assi
- Department of Neurosciences, University of Montreal, Canada
- University of Montreal Hospital Center’s Research Center, Canada
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2
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Euler MJ, Vehar JV, Guevara JE, Geiger AR, Deboeck PR, Lohse KR. Associations between the resting EEG aperiodic slope and broad domains of cognitive ability. Psychophysiology 2024; 61:e14543. [PMID: 38415824 DOI: 10.1111/psyp.14543] [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: 05/15/2023] [Revised: 01/30/2024] [Accepted: 02/02/2024] [Indexed: 02/29/2024]
Abstract
Recent studies suggest that the EEG aperiodic exponent (often represented as a slope in log-log space) is sensitive to individual differences in momentary cognitive skills such as selective attention and information processing speed. However, findings are mixed, and most of the studies have focused on just a narrow range of cognitive domains. This study used an archival dataset to help clarify associations between resting aperiodic features and broad domains of cognitive ability, which vary in their demands on momentary processing. Undergraduates (N = 166) of age 18-52 years completed a resting EEG session as well as a standardized, individually administered assessment of cognitive ability that included measures of processing speed, working memory, and higher-order visuospatial and verbal skills. A subsample (n = 110) also completed a computerized reaction time task with three difficulty levels. Data reduction analyses revealed strong correlations between the aperiodic offset and slope across electrodes, and a single component accounted for ~60% of variance in slopes across the scalp, in both eyes-closed and eyes-open conditions. Structural equation models did not support relations between the slope and specific domains tapping momentary processes. However, secondary analyses indicated that the eyes-open slope was related to higher overall performance, as represented by a single general ability factor. A latent reaction time variable was significantly inversely related to both eyes-closed and eyes-open resting exponents, such that faster reaction times were associated with steeper slopes. These findings support and help clarify the relation of the resting EEG exponent to individual differences in cognitive skills.
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Affiliation(s)
- Matthew J Euler
- Department of Psychology, University of Utah, Salt Lake City, Utah, USA
| | - Julia V Vehar
- Department of Psychology, University of Utah, Salt Lake City, Utah, USA
| | - Jasmin E Guevara
- Department of Psychology, University of Utah, Salt Lake City, Utah, USA
| | - Allie R Geiger
- Department of Psychology, University of Utah, Salt Lake City, Utah, USA
| | - Pascal R Deboeck
- Department of Psychology, University of Utah, Salt Lake City, Utah, USA
| | - Keith R Lohse
- Physical Therapy and Neurology, Washington University School of Medicine in Saint Louis, Saint Louis, Missouri, USA
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3
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Mana L, Schwartz-Pallejà M, Vila-Vidal M, Deco G. Overview on cognitive impairment in psychotic disorders: From impaired microcircuits to dysconnectivity. Schizophr Res 2024; 269:132-143. [PMID: 38788432 DOI: 10.1016/j.schres.2024.05.008] [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: 01/15/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
Schizophrenia's cognitive deficits, often overshadowed by positive symptoms, significantly contribute to the disorder's morbidity. Increasing attention highlights these deficits as reflections of neural circuit dysfunction across various cortical regions. Numerous connectivity alterations linked to cognitive symptoms in psychotic disorders have been reported, both at the macroscopic and microscopic level, emphasizing the potential role of plasticity and microcircuits impairment during development and later stages. However, the heterogeneous clinical presentation of cognitive impairment and diverse connectivity findings pose challenges in summarizing them into a cohesive picture. This review aims to synthesize major cognitive alterations, recent insights into network structural and functional connectivity changes and proposed mechanisms and microcircuit alterations underpinning these symptoms, particularly focusing on neurodevelopmental impairment, E/I balance, and sleep disturbances. Finally, we will also comment on some of the most recent and promising therapeutic approaches that aim to target these mechanisms to address cognitive symptoms. Through this comprehensive exploration, we strive to provide an updated and nuanced overview of the multiscale connectivity impairment underlying cognitive impairment in psychotic disorders.
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Affiliation(s)
- L Mana
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain.
| | - M Schwartz-Pallejà
- 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 Experimental and Health Science, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Eurecat, Technology Center of Catalonia, Multimedia Technologies, Barcelona, Spain.
| | - M Vila-Vidal
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Computational Biology and Complex Systems Group, Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain.
| | - G 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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4
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Nagy B, Kojouharova P, Protzner AB, Gaál ZA. Investigating the Effect of Contextual Cueing with Face Stimuli on Electrophysiological Measures in Younger and Older Adults. J Cogn Neurosci 2024; 36:776-799. [PMID: 38437174 DOI: 10.1162/jocn_a_02135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Extracting repeated patterns from our surroundings plays a crucial role in contextualizing information, making predictions, and guiding our behavior implicitly. Previous research showed that contextual cueing enhances visual search performance in younger adults. In this study, we investigated whether contextual cueing could also improve older adults' performance and whether age-related differences in the neural processes underlying implicit contextual learning could be detected. Twenty-four younger and 25 older participants performed a visual search task with contextual cueing. Contextual information was generated using repeated face configurations alongside random new configurations. We measured RT difference between new and repeated configurations; ERPs to uncover the neural processes underlying contextual cueing for early (N2pc), intermediate (P3b), and late (r-LRP) processes; and multiscale entropy and spectral power density analyses to examine neural dynamics. Both younger and older adults showed similar contextual cueing benefits in their visual search efficiency at the behavioral level. In addition, they showed similar patterns regarding contextual information processing: Repeated face configurations evoked decreased finer timescale entropy (1-20 msec) and higher frequency band power (13-30 Hz) compared with new configurations. However, we detected age-related differences in ERPs: Younger, but not older adults, had larger N2pc and P3b components for repeated compared with new configurations. These results suggest that contextual cueing remains intact with aging. Although attention- and target-evaluation-related ERPs differed between the age groups, the neural dynamics of contextual learning were preserved with aging, as both age groups increasingly utilized more globally grouped representations for repeated face configurations during the learning process.
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Affiliation(s)
- Boglárka Nagy
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
- Department of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary
| | - Petia Kojouharova
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
| | - Andrea B Protzner
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Zsófia Anna Gaál
- Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
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5
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Khanjanianpak M, Azimi-Tafreshi N, Valizadeh A. Emergence of complex oscillatory dynamics in the neuronal networks with long activity time of inhibitory synapses. iScience 2024; 27:109401. [PMID: 38532887 PMCID: PMC10963234 DOI: 10.1016/j.isci.2024.109401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 12/30/2023] [Accepted: 02/28/2024] [Indexed: 03/28/2024] Open
Abstract
The brain displays complex dynamics, including collective oscillations, and extensive research has been conducted to understand their generation. However, our understanding of how biological constraints influence these oscillations is incomplete. This study investigates the essential properties of neuronal networks needed to generate oscillations resembling those in the brain. A simple discrete-time model of interconnected excitable elements is developed, capable of closely resembling the complex oscillations observed in biological neural networks. In the model, synaptic connections remain active for a duration exceeding individual neuron activity. We show that the inhibitory synapses must exhibit longer activity than excitatory synapses to produce a diverse range of the dynamical states, including biologically plausible oscillations. Upon meeting this condition, the transition between different dynamical states can be controlled by external stochastic input to the neurons. The study provides a comprehensive explanation for the emergence of distinct dynamical states in neural networks based on specific parameters.
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Affiliation(s)
- Mozhgan Khanjanianpak
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
| | - Nahid Azimi-Tafreshi
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
| | - Alireza Valizadeh
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
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6
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Kulkarni N, Lega BC. Episodic boundaries affect neural features of representational drift in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.20.553078. [PMID: 37662212 PMCID: PMC10473664 DOI: 10.1101/2023.08.20.553078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
A core feature of episodic memory is representational drift, the gradual change in aggregate oscillatory features that supports temporal association of memory items. However, models of drift overlook the role of episodic boundaries, which indicate a shift from prior to current context states. Our study focuses on the impact of task boundaries on representational drift in the parietal and temporal lobes in 99 subjects during a free recall task. Using intracranial EEG recordings, we show boundary representations reset gamma band drift in the medial parietal lobe, selectively enhancing the recall of early list (primacy) items. Conversely, the lateral temporal cortex shows increased drift for recalled items but lacked sensitivity to task boundaries. Our results suggest regional sensitivity to varied contextual features: the lateral temporal cortex uses drift to differentiate items, while the medial parietal lobe uses drift-resets to associate items with the current context. We propose drift represents relational information tailored to a region's sensitivity to unique contextual elements. Our findings offer a mechanism to integrate models of temporal association by drift with event segmentation by episodic boundaries.
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7
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Jiao L, Kang H, Geng Y, Liu X, Wang M, Shu K. The role of the nucleus basalis of Meynert in neuromodulation therapy: a systematic review from the perspective of neural network oscillations. Front Aging Neurosci 2024; 16:1376764. [PMID: 38650866 PMCID: PMC11033491 DOI: 10.3389/fnagi.2024.1376764] [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: 01/26/2024] [Accepted: 03/28/2024] [Indexed: 04/25/2024] Open
Abstract
As a crucial component of the cerebral cholinergic system and the Papez circuit in the basal forebrain, dysfunction of the nucleus basalis of Meynert (NBM) is associated with various neurodegenerative disorders. However, no drugs, including existing cholinesterase inhibitors, have been shown to reverse this dysfunction. Due to advancements in neuromodulation technology, researchers are exploring the use of deep brain stimulation (DBS) therapy targeting the NBM (NBM-DBS) to treat mental and neurological disorders as well as the related mechanisms. Herein, we provided an update on the research progress on cognition-related neural network oscillations and complex anatomical and projective relationships between the NBM and other cognitive structures and circuits. Furthermore, we reviewed previous animal studies of NBM lesions, NBM-DBS models, and clinical case studies to summarize the important functions of the NBM in neuromodulation. In addition to elucidating the mechanism of the NBM neural network, future research should focus on to other types of neurons in the NBM, despite the fact that cholinergic neurons are still the key target for cell type-specific activation by DBS.
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Affiliation(s)
- Liwu Jiao
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huicong Kang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yumei Geng
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuyang Liu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Mengying Wang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Kai Shu
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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8
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Shavikloo M, Esmaeili A, Valizadeh A, Madadi Asl M. Synchronization of delayed coupled neurons with multiple synaptic connections. Cogn Neurodyn 2024; 18:631-643. [PMID: 38699603 PMCID: PMC11061096 DOI: 10.1007/s11571-023-10013-9] [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: 04/17/2023] [Revised: 08/16/2023] [Accepted: 09/16/2023] [Indexed: 05/05/2024] Open
Abstract
Synchronization is a key feature of the brain dynamics and is necessary for information transmission across brain regions and in higher brain functions like cognition, learning and memory. Experimental findings demonstrated that in cortical microcircuits there are multiple synapses between pairs of connected neurons. Synchronization of neurons in the presence of multiple synaptic connections may be relevant for optimal learning and memory, however, its effect on the dynamics of the neurons is not adequately studied. Here, we address the question that how changes in the strength of the synaptic connections and transmission delays between neurons impact synchronization in a two-neuron system with multiple synapses. To this end, we analytically and computationally investigated synchronization dynamics by considering both phase oscillator model and conductance-based Hodgkin-Huxley (HH) model. Our results show that symmetry/asymmetry of feedforward and feedback connections crucially determines stability of the phase locking of the system based on the strength of connections and delays. In both models, the two-neuron system with multiple synapses achieves in-phase synchrony in the presence of small and large delays, whereas an anti-phase synchronization state is favored for median delays. Our findings can expand the understanding of the functional role of multisynaptic contacts in neuronal synchronization and may shed light on the dynamical consequences of pathological multisynaptic connectivity in a number of brain disorders.
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Affiliation(s)
- Masoumeh Shavikloo
- Department of Physics, Faculty of Science, Urmia University, Urmia, Iran
| | - Asghar Esmaeili
- Department of Physics, Faculty of Science, Urmia University, Urmia, Iran
| | - Alireza Valizadeh
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
| | - Mojtaba Madadi Asl
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
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9
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Riascos AP. Dissimilarity between synchronization processes on networks. Phys Rev E 2024; 109:044301. [PMID: 38755919 DOI: 10.1103/physreve.109.044301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 03/12/2024] [Indexed: 05/18/2024]
Abstract
In this study, we present a general framework for comparing two dynamical processes that describe the synchronization of oscillators coupled through networks of the same size. We introduce a measure of dissimilarity defined in terms of a metric on a hypertorus, allowing us to compare the phases of coupled oscillators. In the first part, this formalism is implemented to examine systems of networked identical phase oscillators that evolve with the Kuramoto model. In particular, we analyze the effect of the weight of an edge in the synchronization of two oscillators, the introduction of new sets of edges in interacting cycles, the effect of bias in the couplings, and the addition of a link in a ring. We also compare the synchronization of nonisomorphic graphs with four nodes. Finally, we explore the dissimilarities generated when we contrast the Kuramoto model with its linear approximation for different random initial phases in deterministic and random networks. The approach introduced provides a general tool for comparing synchronization processes on networks, allowing us to understand the dynamics of a complex system as a consequence of the coupling structure and the processes that can occur in it.
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10
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Riddle J, Schooler JW. Hierarchical consciousness: the Nested Observer Windows model. Neurosci Conscious 2024; 2024:niae010. [PMID: 38504828 PMCID: PMC10949963 DOI: 10.1093/nc/niae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/31/2024] [Accepted: 02/26/2024] [Indexed: 03/21/2024] Open
Abstract
Foremost in our experience is the intuition that we possess a unified conscious experience. However, many observations run counter to this intuition: we experience paralyzing indecision when faced with two appealing behavioral choices, we simultaneously hold contradictory beliefs, and the content of our thought is often characterized by an internal debate. Here, we propose the Nested Observer Windows (NOW) Model, a framework for hierarchical consciousness wherein information processed across many spatiotemporal scales of the brain feeds into subjective experience. The model likens the mind to a hierarchy of nested mosaic tiles-where an image is composed of mosaic tiles, and each of these tiles is itself an image composed of mosaic tiles. Unitary consciousness exists at the apex of this nested hierarchy where perceptual constructs become fully integrated and complex behaviors are initiated via abstract commands. We define an observer window as a spatially and temporally constrained system within which information is integrated, e.g. in functional brain regions and neurons. Three principles from the signal analysis of electrical activity describe the nested hierarchy and generate testable predictions. First, nested observer windows disseminate information across spatiotemporal scales with cross-frequency coupling. Second, observer windows are characterized by a high degree of internal synchrony (with zero phase lag). Third, observer windows at the same spatiotemporal level share information with each other through coherence (with non-zero phase lag). The theoretical framework of the NOW Model accounts for a wide range of subjective experiences and a novel approach for integrating prominent theories of consciousness.
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Affiliation(s)
- Justin Riddle
- Department of Psychology, Florida State University, 1107 W Call St, Tallahassee, FL 32304, USA
| | - Jonathan W Schooler
- Department of Psychological & Brain Sciences, University of California, Santa Barbara, Psychological & Brain Sciences, Santa Barbara, CA 93106, USA
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Sack AT, Paneva J, Küthe T, Dijkstra E, Zwienenberg L, Arns M, Schuhmann T. Target Engagement and Brain State Dependence of Transcranial Magnetic Stimulation: Implications for Clinical Practice. Biol Psychiatry 2024; 95:536-544. [PMID: 37739330 DOI: 10.1016/j.biopsych.2023.09.011] [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: 04/19/2023] [Revised: 08/31/2023] [Accepted: 09/12/2023] [Indexed: 09/24/2023]
Abstract
Transcranial magnetic stimulation (TMS) is capable of noninvasively inducing lasting neuroplastic changes when applied repetitively across multiple treatment sessions. In recent years, repetitive TMS has developed into an established evidence-based treatment for various neuropsychiatric disorders such as depression. Despite significant advancements in our understanding of the mechanisms of action of TMS, there is still much to learn about how these mechanisms relate to the clinical effects observed in patients. If there is one thing about TMS that we know for sure, it is that TMS effects are state dependent. In this review, we describe how the effects of TMS on brain networks depend on various factors, including cognitive brain state, oscillatory brain state, and recent brain state history. These states play a crucial role in determining the effects of TMS at the moment of stimulation and are therefore directly linked to what is referred to as target engagement in TMS therapy. There is no control over target engagement without considering the different brain state dependencies of our TMS intervention. Clinical TMS protocols are largely ignoring this fundamental principle, which may explain the large variability and often still limited efficacy of TMS treatments. We propose that after almost 30 years of research on state dependency of TMS, it is time to change standard clinical practice by taking advantage of this fundamental principle. Rather than ignoring TMS state dependency, we can use it to our clinical advantage to improve the effectiveness of TMS treatments.
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Affiliation(s)
- Alexander T Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Brain + Nerve Center, Maastricht University Medical Center, Maastricht, the Netherlands.
| | - Jasmina Paneva
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Tara Küthe
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Eva Dijkstra
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Heart and Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands; Neurowave, Amsterdam, the Netherlands
| | - Lauren Zwienenberg
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Heart and Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands; Synaeda Psycho Medisch Centrum, Leeuwarden, the Netherlands
| | - Martijn Arns
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Brain + Nerve Center, Maastricht University Medical Center, Maastricht, the Netherlands; Heart and Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands
| | - Teresa Schuhmann
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Zemliak V, Mayer J, Nieters P, Pipa G. Spike synchrony as a measure of Gestalt structure. Sci Rep 2024; 14:5910. [PMID: 38467630 PMCID: PMC10928224 DOI: 10.1038/s41598-024-54755-w] [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: 12/08/2023] [Accepted: 02/16/2024] [Indexed: 03/13/2024] Open
Abstract
The function of spike synchrony is debatable: some researchers view it as a mechanism for binding perceptual features, others - as a byproduct of brain activity. We argue for an alternative computational role: synchrony can estimate the prior probability of incoming stimuli. In V1, this can be achieved by comparing input with previously acquired visual experience, which is encoded in plastic horizontal intracortical connections. V1 connectivity structure can encode the acquired visual experience in the form of its aggregate statistics. Since the aggregate statistics of natural images tend to follow the Gestalt principles, we can assume that V1 is more often exposed to Gestalt-like stimuli, and this is manifested in its connectivity structure. At the same time, the connectivity structure has an impact on spike synchrony in V1. We used a spiking model with V1-like connectivity to demonstrate that spike synchrony reflects the Gestalt structure of the stimulus. We conducted simulation experiments with three Gestalt laws: proximity, similarity, and continuity, and found substantial differences in firing synchrony for stimuli with varying degrees of Gestalt-likeness. This allows us to conclude that spike synchrony indeed reflects the Gestalt structure of the stimulus, which can be interpreted as a mechanism for prior probability estimation.
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Affiliation(s)
- Viktoria Zemliak
- Institute of Cognitive Science, University of Osnabrück, 49074, Osnabrück, Germany.
| | - Julius Mayer
- Institute of Cognitive Science, University of Osnabrück, 49074, Osnabrück, Germany
| | - Pascal Nieters
- Institute of Cognitive Science, University of Osnabrück, 49074, Osnabrück, Germany
| | - Gordon Pipa
- Institute of Cognitive Science, University of Osnabrück, 49074, Osnabrück, Germany
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13
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Mazzi C, Mele S, Bagattini C, Sanchez-Lopez J, Savazzi S. Coherent activity within and between hemispheres: cortico-cortical connectivity revealed by rTMS of the right posterior parietal cortex. Front Hum Neurosci 2024; 18:1362742. [PMID: 38516308 PMCID: PMC10954802 DOI: 10.3389/fnhum.2024.1362742] [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: 12/28/2023] [Accepted: 02/23/2024] [Indexed: 03/23/2024] Open
Abstract
Introduction Low frequency (1 Hz) repetitive transcranial stimulation (rTMS) applied over right posterior parietal cortex (rPPC) has been shown to reduce cortical excitability both of the stimulated area and of the interconnected contralateral homologous areas. In the present study, we investigated the whole pattern of intra- and inter-hemispheric cortico-cortical connectivity changes induced by rTMS over rPPC. Methods To do so, 14 healthy participants underwent resting state EEG recording before and after 30 min of rTMS at 1 Hz or sham stimulation over the rPPC (electrode position P6). Real stimulation was applied at 90% of motor threshold. Coherence values were computed on the electrodes nearby the stimulated site (i.e., P4, P8, and CP6) considering all possible inter- and intra-hemispheric combinations for the following frequency bands: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12Hz), low beta (12-20 Hz), high beta (20-30 Hz), and gamma (30-50 Hz). Results and discussion Results revealed a significant increase in coherence in delta, theta, alpha and beta frequency bands between rPPC and the contralateral homologous sites. Moreover, an increase in coherence in theta, alpha, beta and gamma frequency bands was found between rPPC and right frontal sites, reflecting the activation of the fronto-parietal network within the right hemisphere. Summarizing, subthreshold rTMS over rPPC revealed cortico-cortical inter- and intra-hemispheric connectivity as measured by the increase in coherence among these areas. Moreover, the present results further confirm previous evidence indicating that the increase of coherence values is related to intra- and inter-hemispheric inhibitory effects of rTMS. These results can have implications for devising evidence-based rehabilitation protocols after stroke.
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Affiliation(s)
- Chiara Mazzi
- Perception and Awareness (PandA) Laboratory, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Sonia Mele
- Perception and Awareness (PandA) Laboratory, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Chiara Bagattini
- Perception and Awareness (PandA) Laboratory, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Section of Neurosurgery, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Javier Sanchez-Lopez
- Escuela Nacional de Estudios Superiores Unidad Juriquilla, Universidad Nacional Autonoma de Mexico, Santiago de Querétaro, Mexico
| | - Silvia Savazzi
- Perception and Awareness (PandA) Laboratory, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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14
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Schantell M, Taylor BK, Mansouri A, Arif Y, Coutant AT, Rice DL, Wang YP, Calhoun VD, Stephen JM, Wilson TW. Theta oscillatory dynamics serving cognitive control index psychosocial distress in youth. Neurobiol Stress 2024; 29:100599. [PMID: 38213830 PMCID: PMC10776433 DOI: 10.1016/j.ynstr.2023.100599] [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: 06/28/2023] [Revised: 11/09/2023] [Accepted: 12/10/2023] [Indexed: 01/13/2024] Open
Abstract
Background Psychosocial distress among youth is a major public health issue characterized by disruptions in cognitive control processing. Using the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, we quantified multidimensional neural oscillatory markers of psychosocial distress serving cognitive control in youth. Methods The sample consisted of 39 peri-adolescent participants who completed the NIH Toolbox Emotion Battery (NIHTB-EB) and the Eriksen flanker task during magnetoencephalography (MEG). A psychosocial distress index was computed with exploratory factor analysis using assessments from the NIHTB-EB. MEG data were analyzed in the time-frequency domain and peak voxels from oscillatory maps depicting the neural cognitive interference effect were extracted for voxel time series analyses to identify spontaneous and oscillatory aberrations in dynamics serving cognitive control as a function of psychosocial distress. Further, we quantified the relationship between psychosocial distress and dynamic functional connectivity between regions supporting cognitive control. Results The continuous psychosocial distress index was strongly associated with validated measures of pediatric psychopathology. Theta-band neural cognitive interference was identified in the left dorsolateral prefrontal cortex (dlPFC) and middle cingulate cortex (MCC). Time series analyses of these regions indicated that greater psychosocial distress was associated with elevated spontaneous activity in both the dlPFC and MCC and blunted theta oscillations in the MCC. Finally, we found that stronger phase coherence between the dlPFC and MCC was associated with greater psychosocial distress. Conclusions Greater psychosocial distress was marked by alterations in spontaneous and oscillatory theta activity serving cognitive control, along with hyperconnectivity between the dlPFC and MCC.
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Affiliation(s)
- Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Brittany K. Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Amirsalar Mansouri
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yasra Arif
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Anna T. Coutant
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Danielle L. Rice
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging & Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | | | - Tony W. Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
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15
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Öztel T, Balcı F. Metric error monitoring as a component of metacognitive processing. Eur J Neurosci 2024; 59:807-821. [PMID: 37941152 DOI: 10.1111/ejn.16182] [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: 03/31/2023] [Revised: 09/12/2023] [Accepted: 10/16/2023] [Indexed: 11/10/2023]
Abstract
Metacognitive processing constitutes one of the contemporary target domains in consciousness research. Error monitoring (the ability to correctly report one's own errors without feedback) is considered one of the functional outcomes of metacognitive processing. Error monitoring is traditionally investigated as part of categorical decisions where choice accuracy is a binary construct (choice is either correct or incorrect). However, recent studies revealed that this ability is characterized by metric features (i.e., direction and magnitude) in temporal, spatial, and numerical domains. Here, we discuss methodological approaches to investigating metric error monitoring in both humans and non-human animals and review their findings. The potential neural substrates of metric error monitoring measures are also discussed. This new scope of metacognitive processing can help improve our current understanding of conscious processing from a new perspective. Thus, by summarizing and discussing the perspectives, findings, and common applications in the metric error monitoring literature, this paper aims to provide a guideline for future research.
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Affiliation(s)
- Tutku Öztel
- Psychology Department, Koç University, Istanbul, Turkey
| | - Fuat Balcı
- Psychology Department, Koç University, Istanbul, Turkey
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
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16
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Douchamps V, di Volo M, Torcini A, Battaglia D, Goutagny R. Gamma oscillatory complexity conveys behavioral information in hippocampal networks. Nat Commun 2024; 15:1849. [PMID: 38418832 PMCID: PMC10902292 DOI: 10.1038/s41467-024-46012-5] [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: 10/13/2023] [Accepted: 02/09/2024] [Indexed: 03/02/2024] Open
Abstract
The hippocampus and entorhinal cortex exhibit rich oscillatory patterns critical for cognitive functions. In the hippocampal region CA1, specific gamma-frequency oscillations, timed at different phases of the ongoing theta rhythm, are hypothesized to facilitate the integration of information from varied sources and contribute to distinct cognitive processes. Here, we show that gamma elements -a multidimensional characterization of transient gamma oscillatory episodes- occur at any frequency or phase relative to the ongoing theta rhythm across all CA1 layers in male mice. Despite their low power and stochastic-like nature, individual gamma elements still carry behavior-related information and computational modeling suggests that they reflect neuronal firing. Our findings challenge the idea of rigid gamma sub-bands, showing that behavior shapes ensembles of irregular gamma elements that evolve with learning and depend on hippocampal layers. Widespread gamma diversity, beyond randomness, may thus reflect complexity, likely functional but invisible to classic average-based analyses.
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Affiliation(s)
- Vincent Douchamps
- Université de Strasbourg, Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA), CNRS, UMR 7364, Strasbourg, France
| | - Matteo di Volo
- Université Claude Bernard Lyon 1, Institut National de la Santé et de la Recherche Médicale, Stem Cell and Brain Research Institute, U1208, Bron, France
- CY Cergy Paris Université, Laboratoire de Physique Théorique et Modélisation (LPTM), CNRS, UMR 8089, 95302, Cergy-Pontoise, France
| | - Alessandro Torcini
- CY Cergy Paris Université, Laboratoire de Physique Théorique et Modélisation (LPTM), CNRS, UMR 8089, 95302, Cergy-Pontoise, France
- CNR - Consiglio Nazionale delle Ricerche, Istituto dei Sistemi Complessi, via Madonna del Piano 10, 50019, Sesto Fiorentino, Italy
| | - Demian Battaglia
- Université de Strasbourg, Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA), CNRS, UMR 7364, Strasbourg, France.
- Aix-Marseille Université, Institut de Neurosciences des Systèmes (INS), INSERM, UMR 1106, Marseille, France.
- University of Strasbourg Institute for Advanced Studies (USIAS), Strasbourg, France.
| | - Romain Goutagny
- Université de Strasbourg, Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA), CNRS, UMR 7364, Strasbourg, France.
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17
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Das P, He M, Purdon PL. A dynamic generative model can extract interpretable oscillatory components from multichannel neurophysiological recordings. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.26.550594. [PMID: 37546851 PMCID: PMC10402019 DOI: 10.1101/2023.07.26.550594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Modern neurophysiological recordings are performed using multichannel sensor arrays that are able to record activity in an increasingly high number of channels numbering in the 100's to 1000's. Often, underlying lower-dimensional patterns of activity are responsible for the observed dynamics, but these representations are difficult to reliably identify using existing methods that attempt to summarize multivariate relationships in a post-hoc manner from univariate analyses, or using current blind source separation methods. While such methods can reveal appealing patterns of activity, determining the number of components to include, assessing their statistical significance, and interpreting them requires extensive manual intervention and subjective judgement in practice. These difficulties with component selection and interpretation occur in large part because these methods lack a generative model for the underlying spatio-temporal dynamics. Here we describe a novel component analysis method anchored by a generative model where each source is described by a bio-physically inspired state space representation. The parameters governing this representation readily capture the oscillatory temporal dynamics of the components, so we refer to it as Oscillation Component Analysis (OCA). These parameters - the oscillatory properties, the component mixing weights at the sensors, and the number of oscillations - all are inferred in a data-driven fashion within a Bayesian framework employing an instance of the expectation maximization algorithm. We analyze high-dimensional electroencephalography and magnetoencephalography recordings from human studies to illustrate the potential utility of this method for neuroscience data.
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Affiliation(s)
- Proloy Das
- Department of Anesthesia, Perioperative and Pain Medicine, Stanford University, Stanford, CA-94301
| | - Mingjian He
- Department of Anesthesia, Perioperative and Pain Medicine, Stanford University, Stanford, CA-94301
| | - Patrick L. Purdon
- Department of Anesthesia, Perioperative and Pain Medicine, Stanford University, Stanford, CA-94301
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18
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Du M, Behera AK, Vaikuntanathan S. Active oscillatory associative memory. J Chem Phys 2024; 160:055103. [PMID: 38341712 DOI: 10.1063/5.0171983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 01/07/2024] [Indexed: 02/13/2024] Open
Abstract
Traditionally, physical models of associative memory assume conditions of equilibrium. Here, we consider a prototypical oscillator model of associative memory and study how active noise sources that drive the system out of equilibrium, as well as nonlinearities in the interactions between the oscillators, affect the associative memory properties of the system. Our simulations show that pattern retrieval under active noise is more robust to the number of learned patterns and noise intensity than under passive noise. To understand this phenomenon, we analytically derive an effective energy correction due to the temporal correlations of active noise in the limit of short correlation decay time. We find that active noise deepens the energy wells corresponding to the patterns by strengthening the oscillator couplings, where the more nonlinear interactions are preferentially enhanced. Using replica theory, we demonstrate qualitative agreement between this effective picture and the retrieval simulations. Our work suggests that the nonlinearity in the oscillator couplings can improve memory under nonequilibrium conditions.
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Affiliation(s)
- Matthew Du
- Department of Chemistry, University of Chicago, Chicago, Illinois 60637, USA
- The James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA
| | - Agnish Kumar Behera
- Department of Chemistry, University of Chicago, Chicago, Illinois 60637, USA
| | - Suriyanarayanan Vaikuntanathan
- Department of Chemistry, University of Chicago, Chicago, Illinois 60637, USA
- The James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA
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19
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Zoefel B, Kösem A. Neural tracking of continuous acoustics: properties, speech-specificity and open questions. Eur J Neurosci 2024; 59:394-414. [PMID: 38151889 DOI: 10.1111/ejn.16221] [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: 06/27/2023] [Revised: 11/17/2023] [Accepted: 11/22/2023] [Indexed: 12/29/2023]
Abstract
Human speech is a particularly relevant acoustic stimulus for our species, due to its role of information transmission during communication. Speech is inherently a dynamic signal, and a recent line of research focused on neural activity following the temporal structure of speech. We review findings that characterise neural dynamics in the processing of continuous acoustics and that allow us to compare these dynamics with temporal aspects in human speech. We highlight properties and constraints that both neural and speech dynamics have, suggesting that auditory neural systems are optimised to process human speech. We then discuss the speech-specificity of neural dynamics and their potential mechanistic origins and summarise open questions in the field.
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Affiliation(s)
- Benedikt Zoefel
- Centre de Recherche Cerveau et Cognition (CerCo), CNRS UMR 5549, Toulouse, France
- Université de Toulouse III Paul Sabatier, Toulouse, France
| | - Anne Kösem
- Lyon Neuroscience Research Center (CRNL), INSERM U1028, Bron, France
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20
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Chen D, Axmacher N, Wang L. Grid codes underlie multiple cognitive maps in the human brain. Prog Neurobiol 2024; 233:102569. [PMID: 38232782 DOI: 10.1016/j.pneurobio.2024.102569] [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: 11/06/2023] [Revised: 01/07/2024] [Accepted: 01/10/2024] [Indexed: 01/19/2024]
Abstract
Grid cells fire at multiple positions that organize the vertices of equilateral triangles tiling a 2D space and are well studied in rodents. The last decade witnessed rapid progress in two other research lines on grid codes-empirical studies on distributed human grid-like representations in physical and multiple non-physical spaces, and cognitive computational models addressing the function of grid cells based on principles of efficient and predictive coding. Here, we review the progress in these fields and integrate these lines into a systematic organization. We also discuss the coordinate mechanisms of grid codes in the human entorhinal cortex and medial prefrontal cortex and their role in neurological and psychiatric diseases.
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Affiliation(s)
- Dong Chen
- CAS Key Laboratory of Mental Health, Institute of Psychology, 100101, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, 100101, Beijing, China
| | - Nikolai Axmacher
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, 44801, Bochum, Germany
| | - Liang Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, 100101, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, 100101, Beijing, China.
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21
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Hoffman SJ, Dotson NM, Lima V, Gray CM. The Primate Cortical LFP Exhibits Multiple Spectral and Temporal Gradients and Widespread Task-Dependence During Visual Short-Term Memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577843. [PMID: 38352585 PMCID: PMC10862751 DOI: 10.1101/2024.01.29.577843] [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: 02/22/2024]
Abstract
Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3-80 Hz that differ between the two monkeys. The LFP power in each band, as well as the Sample Entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in layer 3 pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.
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Affiliation(s)
- Steven J Hoffman
- Department of Cell Biology and Neuroscience, Montana State University, Bozeman, MT 59717, USA
- Current address: Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Nicholas M Dotson
- Department of Cell Biology and Neuroscience, Montana State University, Bozeman, MT 59717, USA
- Current address: Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Vinicius Lima
- Aix Marseille Université, INSERM, Systems Neuroscience Institute, Marseille, France
| | - Charles M Gray
- Department of Cell Biology and Neuroscience, Montana State University, Bozeman, MT 59717, USA
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22
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Shipp S. Computational components of visual predictive coding circuitry. Front Neural Circuits 2024; 17:1254009. [PMID: 38259953 PMCID: PMC10800426 DOI: 10.3389/fncir.2023.1254009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 12/13/2023] [Indexed: 01/24/2024] Open
Abstract
If a full visual percept can be said to be a 'hypothesis', so too can a neural 'prediction' - although the latter addresses one particular component of image content (such as 3-dimensional organisation, the interplay between lighting and surface colour, the future trajectory of moving objects, and so on). And, because processing is hierarchical, predictions generated at one level are conveyed in a backward direction to a lower level, seeking to predict, in fact, the neural activity at that prior stage of processing, and learning from errors signalled in the opposite direction. This is the essence of 'predictive coding', at once an algorithm for information processing and a theoretical basis for the nature of operations performed by the cerebral cortex. Neural models for the implementation of predictive coding invoke specific functional classes of neuron for generating, transmitting and receiving predictions, and for producing reciprocal error signals. Also a third general class, 'precision' neurons, tasked with regulating the magnitude of error signals contingent upon the confidence placed upon the prediction, i.e., the reliability and behavioural utility of the sensory data that it predicts. So, what is the ultimate source of a 'prediction'? The answer is multifactorial: knowledge of the current environmental context and the immediate past, allied to memory and lifetime experience of the way of the world, doubtless fine-tuned by evolutionary history too. There are, in consequence, numerous potential avenues for experimenters seeking to manipulate subjects' expectation, and examine the neural signals elicited by surprising, and less surprising visual stimuli. This review focuses upon the predictive physiology of mouse and monkey visual cortex, summarising and commenting on evidence to date, and placing it in the context of the broader field. It is concluded that predictive coding has a firm grounding in basic neuroscience and that, unsurprisingly, there remains much to learn.
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Affiliation(s)
- Stewart Shipp
- Institute of Ophthalmology, University College London, London, United Kingdom
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23
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Keil J, Kiiski H, Doherty L, Hernandez-Urbina V, Vassiliou C, Dean C, Müschenich M, Bahmani H. Artificial sharp-wave-ripples to support memory and counter neurodegeneration. Brain Res 2024; 1822:148646. [PMID: 37871674 DOI: 10.1016/j.brainres.2023.148646] [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: 07/21/2023] [Revised: 10/11/2023] [Accepted: 10/20/2023] [Indexed: 10/25/2023]
Abstract
Information processed in our sensory neocortical areas is transported to the hippocampus during memory encoding, and between hippocampus and neocortex during memory consolidation, and retrieval. Short bursts of high-frequency oscillations, so called sharp-wave-ripples, have been proposed as a potential mechanism for this information transfer: They can synchronize neural activity to support the formation of local neural networks to store information, and between distant cortical sites to act as a bridge to transfer information between sensory cortical areas and hippocampus. In neurodegenerative diseases like Alzheimer's Disease, different neuropathological processes impair normal neural functioning and neural synchronization as well as sharp-wave-ripples, which impairs consolidation and retrieval of information, and compromises memory. Here, we formulate a new hypothesis, that artificially inducing sharp-wave-ripples with noninvasive high-frequency visual stimulation could potentially support memory functioning, as well as target the neuropathological processes underlying neurodegenerative diseases. We also outline key challenges for empirical tests of the hypothesis.
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Affiliation(s)
- Julian Keil
- Department of Psychology, Christian-Albrechts-University Kiel, Germany; Ababax Health GmbH, Berlin, Germany; Department of Cognitive Science, University of Potsdam, Germany.
| | - Hanni Kiiski
- Ababax Health GmbH, Berlin, Germany; Department of Cognitive Science, University of Potsdam, Germany
| | | | | | - Chrystalleni Vassiliou
- German Center for Neurodegenerative Diseases, Charité University of Medicine, Berlin, Germany
| | - Camin Dean
- German Center for Neurodegenerative Diseases, Charité University of Medicine, Berlin, Germany
| | | | - Hamed Bahmani
- Ababax Health GmbH, Berlin, Germany; Bernstein Center for Computational Neuroscience, Tuebingen, Germany
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24
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Clusella P, Montbrió E. Exact low-dimensional description for fast neural oscillations with low firing rates. Phys Rev E 2024; 109:014229. [PMID: 38366470 DOI: 10.1103/physreve.109.014229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 12/18/2023] [Indexed: 02/18/2024]
Abstract
Recently, low-dimensional models of neuronal activity have been exactly derived for large networks of deterministic, quadratic integrate-and-fire (QIF) neurons. Such firing rate models (FRM) describe the emergence of fast collective oscillations (>30 Hz) via the frequency locking of a subset of neurons to the global oscillation frequency. However, the suitability of such models to describe realistic neuronal states is seriously challenged by the fact that during episodes of fast collective oscillations, neuronal discharges are often very irregular and have low firing rates compared to the global oscillation frequency. Here we extend the theory to derive exact FRM for QIF neurons to include noise and show that networks of stochastic neurons displaying irregular discharges at low firing rates during episodes of fast oscillations are governed by exactly the same evolution equations as deterministic networks. Our results reconcile two traditionally confronted views on neuronal synchronization and upgrade the applicability of exact FRM to describe a broad range of biologically realistic neuronal states.
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Affiliation(s)
- Pau Clusella
- Departament de Matemàtiques, Universitat Politècnica de Catalunya, 08242 Manresa, Spain
| | - Ernest Montbrió
- Neuronal Dynamics Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain
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25
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Gillespie B, Panthi S, Sundram S, Hill RA. The impact of maternal immune activation on GABAergic interneuron development: A systematic review of rodent studies and their translational implications. Neurosci Biobehav Rev 2024; 156:105488. [PMID: 38042358 DOI: 10.1016/j.neubiorev.2023.105488] [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: 08/11/2023] [Revised: 11/09/2023] [Accepted: 11/27/2023] [Indexed: 12/04/2023]
Abstract
Mothers exposed to infections during pregnancy disproportionally birth children who develop autism and schizophrenia, disorders associated with altered GABAergic function. The maternal immune activation (MIA) model recapitulates this risk factor, with many studies also reporting disruptions to GABAergic interneuron expression, protein, cellular density and function. However, it is unclear if there are species, sex, age, region, or GABAergic subtype specific vulnerabilities to MIA. Furthermore, to fully comprehend the impact of MIA on the GABAergic system a synthesised account of molecular, cellular, electrophysiological and behavioural findings was required. To this end we conducted a systematic review of GABAergic interneuron changes in the MIA model, focusing on the prefrontal cortex and hippocampus. We reviewed 102 articles that revealed robust changes in a number of GABAergic markers that present as gestationally-specific, region-specific and sometimes sex-specific. Disruptions to GABAergic markers coincided with distinct behavioural phenotypes, including memory, sensorimotor gating, anxiety, and sociability. Findings suggest the MIA model is a valid tool for testing novel therapeutics designed to recover GABAergic function and associated behaviour.
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Affiliation(s)
- Brendan Gillespie
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC 3168, Australia
| | - Sandesh Panthi
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC 3168, Australia
| | - Suresh Sundram
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC 3168, Australia
| | - Rachel A Hill
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC 3168, Australia.
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26
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Hofman MA. The Fractal Geometry of the Human Brain: An Evolutionary Perspective. ADVANCES IN NEUROBIOLOGY 2024; 36:241-258. [PMID: 38468036 DOI: 10.1007/978-3-031-47606-8_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
The evolution of the brain in mammals is characterized by changes in size, architecture, and internal organization. Consequently, the geometry of the brain, and especially the size and shape of the cerebral cortex, has changed notably during evolution. Comparative studies of the cerebral cortex suggest that there are general architectural principles governing its growth and evolutionary development. In this chapter, some of the design principles and operational modes that underlie the fractal geometry and information processing capacity of the cerebral cortex in primates, including humans, will be explored. It is shown that the development of the cortex coordinates folding with connectivity in a way that produces smaller and faster brains.
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Affiliation(s)
- Michel A Hofman
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
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27
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Doherty JL, Cunningham AC, Chawner SJRA, Moss HM, Dima DC, Linden DEJ, Owen MJ, van den Bree MBM, Singh KD. Atypical cortical networks in children at high-genetic risk of psychiatric and neurodevelopmental disorders. Neuropsychopharmacology 2024; 49:368-376. [PMID: 37402765 PMCID: PMC7615386 DOI: 10.1038/s41386-023-01628-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 05/04/2023] [Accepted: 06/01/2023] [Indexed: 07/06/2023]
Abstract
Although many genetic risk factors for psychiatric and neurodevelopmental disorders have been identified, the neurobiological route from genetic risk to neuropsychiatric outcome remains unclear. 22q11.2 deletion syndrome (22q11.2DS) is a copy number variant (CNV) syndrome associated with high rates of neurodevelopmental and psychiatric disorders including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and schizophrenia. Alterations in neural integration and cortical connectivity have been linked to the spectrum of neuropsychiatric disorders seen in 22q11.2DS and may be a mechanism by which the CNV acts to increase risk. In this study, magnetoencephalography (MEG) was used to investigate electrophysiological markers of local and global network function in 34 children with 22q11.2DS and 25 controls aged 10-17 years old. Resting-state oscillatory activity and functional connectivity across six frequency bands were compared between groups. Regression analyses were used to explore the relationships between these measures, neurodevelopmental symptoms and IQ. Children with 22q11.2DS had altered network activity and connectivity in high and low frequency bands, reflecting modified local and long-range cortical circuitry. Alpha and theta band connectivity were negatively associated with ASD symptoms while frontal high frequency (gamma band) activity was positively associated with ASD symptoms. Alpha band activity was positively associated with cognitive ability. These findings suggest that haploinsufficiency at the 22q11.2 locus impacts short and long-range cortical circuits, which could be a mechanism underlying neurodevelopmental and psychiatric vulnerability in this high-risk group.
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Affiliation(s)
- Joanne L Doherty
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
- Cardiff University's Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK.
| | - Adam C Cunningham
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Samuel J R A Chawner
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Hayley M Moss
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Diana C Dima
- Cardiff University's Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - David E J Linden
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
- Cardiff University's Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Marianne B M van den Bree
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Krish D Singh
- Cardiff University's Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
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Yang X, Ying C, Zhu L, Wenjing W. The neural oscillations in delta- and theta-bands contribute to divided attention in audiovisual integration. Perception 2024; 53:44-60. [PMID: 37899595 DOI: 10.1177/03010066231208539] [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] [Indexed: 10/31/2023]
Abstract
One of key mechanisms implicated in multisensory processing is neural oscillations in distinct frequency band. Many studies explored the modulation of attention by recording the electroencephalography signals when subjects attended one modality, and ignored the other modality input. However, when attention is directed toward one modality, it may be not always possible to shut out completely inputs from a different modality. Since many situations require division of attention between audition and vision, it is imperative to investigate the neural mechanisms underlying processing of concurrent auditory and visual sensory streams. In the present study, we designed a task of audiovisual semantic discrimination, in which the subjects were asked to share attention to both auditory and visual stimuli. We explored the contribution of neural oscillations in lower-frequency to the modulation of divided attention on audiovisual integration. Our results implied that theta-band activity contributes to the early modulation of divided attention, and delta-band activity contributes to the late modulation of divided attention to audiovisual integration. Moreover, the fronto-central delta- and theta-bands activity is likely a marker of divided attention in audiovisual integration, and the neural oscillation on delta- and theta-bands is conducive to allocating attention resources to dual-tasking involving task-coordinating abilities.
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Affiliation(s)
- Xi Yang
- Northeast Electric Power University, P. R. China
| | - Chen Ying
- Northeast Electric Power University, P. R. China
| | - Lan Zhu
- Northeast Electric Power University, P. R. China
| | - Wang Wenjing
- Northeast Electric Power University, P. R. China
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29
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Baruzzi V, Lodi M, Sorrentino F, Storace M. Bridging functional and anatomical neural connectivity through cluster synchronization. Sci Rep 2023; 13:22430. [PMID: 38104227 PMCID: PMC10725511 DOI: 10.1038/s41598-023-49746-2] [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: 06/01/2023] [Accepted: 12/11/2023] [Indexed: 12/19/2023] Open
Abstract
The dynamics of the brain results from the complex interplay of several neural populations and is affected by both the individual dynamics of these areas and their connection structure. Hence, a fundamental challenge is to derive models of the brain that reproduce both structural and functional features measured experimentally. Our work combines neuroimaging data, such as dMRI, which provides information on the structure of the anatomical connectomes, and fMRI, which detects patterns of approximate synchronous activity between brain areas. We employ cluster synchronization as a tool to integrate the imaging data of a subject into a coherent model, which reconciles structural and dynamic information. By using data-driven and model-based approaches, we refine the structural connectivity matrix in agreement with experimentally observed clusters of brain areas that display coherent activity. The proposed approach leverages the assumption of homogeneous brain areas; we show the robustness of this approach when heterogeneity between the brain areas is introduced in the form of noise, parameter mismatches, and connection delays. As a proof of concept, we apply this approach to MRI data of a healthy adult at resting state.
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Affiliation(s)
| | - Matteo Lodi
- DITEN, University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy
| | - Francesco Sorrentino
- Mechanical Engineering Department, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Marco Storace
- DITEN, University of Genoa, Via Opera Pia 11a, 16145, Genova, Italy.
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Ardelean ER, Bârzan H, Ichim AM, Mureşan RC, Moca VV. Sharp detection of oscillation packets in rich time-frequency representations of neural signals. Front Hum Neurosci 2023; 17:1112415. [PMID: 38144896 PMCID: PMC10748759 DOI: 10.3389/fnhum.2023.1112415] [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: 11/30/2022] [Accepted: 11/13/2023] [Indexed: 12/26/2023] Open
Abstract
Brain oscillations most often occur in bursts, called oscillation packets, which span a finite extent in time and frequency. Recent studies have shown that these packets portray a much more dynamic picture of synchronization and transient communication between sites than previously thought. To understand their nature and statistical properties, techniques are needed to objectively detect oscillation packets and to quantify their temporal and frequency extent, as well as their magnitude. There are various methods to detect bursts of oscillations. The simplest ones divide the signal into band limited sub-components, quantifying the strength of the resulting components. These methods cannot by themselves cope with broadband transients that look like genuine oscillations when restricted to a narrow band. The most successful detection methods rely on time-frequency representations, which can readily show broadband transients and harmonics. However, the performance of such methods is conditioned by the ability of the representation to localize packets simultaneously in time and frequency, and by the capabilities of packet detection techniques, whose current state of the art is limited to extraction of bounding boxes. Here, we focus on the second problem, introducing two detection methods that use concepts derived from clustering and topographic prominence. These methods are able to delineate the packets' precise contour in the time-frequency plane. We validate the new approaches using both synthetic and real data recorded in humans and animals and rely on a super-resolution time-frequency representation, namely the superlets, as input to the detection algorithms. In addition, we define robust tests for benchmarking and compare the new methods to previous techniques. Results indicate that the two methods we introduce shine in low signal-to-noise ratio conditions, where they only miss a fraction of packets undetected by previous methods. Finally, algorithms that delineate precisely the border of spectral features and their subcomponents offer far more valuable information than simple rectangular bounding boxes (time and frequency span) and can provide a solid foundation to investigate neural oscillations' dynamics.
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Affiliation(s)
- Eugen-Richard Ardelean
- Experimental and Theoretical Neuroscience Laboratory, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- Computer Science Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
| | - Harald Bârzan
- Experimental and Theoretical Neuroscience Laboratory, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
| | - Ana-Maria Ichim
- Experimental and Theoretical Neuroscience Laboratory, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
| | - Raul Cristian Mureşan
- Experimental and Theoretical Neuroscience Laboratory, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
- STAR-UBB Institute, Babeş-Bolyai University, Cluj-Napoca, Romania
| | - Vasile Vlad Moca
- Experimental and Theoretical Neuroscience Laboratory, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
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31
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Ouyang G, Wang S, Liu M, Zhang M, Zhou C. Multilevel and multifaceted brain response features in spiking, ERP and ERD: experimental observation and simultaneous generation in a neuronal network model with excitation-inhibition balance. Cogn Neurodyn 2023; 17:1417-1431. [PMID: 37969943 PMCID: PMC10640466 DOI: 10.1007/s11571-022-09889-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 08/26/2022] [Accepted: 09/14/2022] [Indexed: 11/25/2022] Open
Abstract
Brain as a dynamic system responds to stimulations with specific patterns affected by its inherent ongoing dynamics. The patterns are manifested across different levels of organization-from spiking activity of neurons to collective oscillations in local field potential (LFP) and electroencephalogram (EEG). The multilevel and multifaceted response activities show patterns seemingly distinct and non-comparable from each other, but they should be coherently related because they are generated from the same underlying neural dynamic system. A coherent understanding of the interrelationships between different levels/aspects of activity features is important for understanding the complex brain functions. Here, based on analysis of data from human EEG, monkey LFP and neuronal spiking, we demonstrated that the brain response activities from different levels of neural system are highly coherent: the external stimulus simultaneously generated event-related potentials, event-related desynchronization, and variation in neuronal spiking activities that precisely match with each other in the temporal unfolding. Based on a biologically plausible but generic network of conductance-based integrate-and-fire excitatory and inhibitory neurons with dense connections, we showed that the multiple key features can be simultaneously produced at critical dynamical regimes supported by excitation-inhibition (E-I) balance. The elucidation of the inherent coherency of various neural response activities and demonstration of a simple dynamical neural circuit system having the ability to simultaneously produce multiple features suggest the plausibility of understanding high-level brain function and cognition from elementary and generic neuronal dynamics. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09889-w.
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Affiliation(s)
- Guang Ouyang
- Faculty of Education, The University of Hong Kong, Pok Fu Lam, Hong Kong China
| | - Shengjun Wang
- Department of Physics, Shaanxi Normal University, Xi’an, 710119 China
| | - Mianxin Liu
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong China
| | - Mingsha Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875 China
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong China
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32
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Yin Q, Johnson EL, Ofen N. Neurophysiological mechanisms of cognition in the developing brain: Insights from intracranial EEG studies. Dev Cogn Neurosci 2023; 64:101312. [PMID: 37837918 PMCID: PMC10589793 DOI: 10.1016/j.dcn.2023.101312] [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: 07/04/2023] [Revised: 09/26/2023] [Accepted: 10/08/2023] [Indexed: 10/16/2023] Open
Abstract
The quest to understand how the development of the brain supports the development of complex cognitive functions is fueled by advances in cognitive neuroscience methods. Intracranial EEG (iEEG) recorded directly from the developing human brain provides unprecedented spatial and temporal resolution for mapping the neurophysiological mechanisms supporting cognitive development. In this paper, we focus on episodic memory, the ability to remember detailed information about past experiences, which improves from childhood into adulthood. We review memory effects based on broadband spectral power and emphasize the importance of isolating narrowband oscillations from broadband activity to determine mechanisms of neural coordination within and between brain regions. We then review evidence of developmental variability in neural oscillations and present emerging evidence linking the development of neural oscillations to the development of memory. We conclude by proposing that the development of oscillations increases the precision of neural coordination and may be an essential factor underlying memory development. More broadly, we demonstrate how recording neural activity directly from the developing brain holds immense potential to advance our understanding of cognitive development.
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Affiliation(s)
- Qin Yin
- Department of Psychology, Wayne State University, Detroit, MI, USA; Life-span Cognitive Neuroscience Program, Institute of Gerontology and Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI, USA
| | - Elizabeth L Johnson
- Departments of Medical Social Sciences and Pediatrics, Northwestern University, Chicago, IL, USA; Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Noa Ofen
- Department of Psychology, Wayne State University, Detroit, MI, USA; Life-span Cognitive Neuroscience Program, Institute of Gerontology and Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI, USA.
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33
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Hao S, Xin Q, Xiaomin Z, Jiali P, Xiaoqin W, Rong Y, Cenlin Z. Group membership modulates the hold-up problem: an event-related potentials and oscillations study. Soc Cogn Affect Neurosci 2023; 18:nsad071. [PMID: 37990077 PMCID: PMC10689188 DOI: 10.1093/scan/nsad071] [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: 02/20/2023] [Revised: 10/12/2023] [Accepted: 11/20/2023] [Indexed: 11/23/2023] Open
Abstract
This paper investigates the neural mechanism that underlies the effect of group identity on hold-up problems. The behavioral results indicated that the investment rate among members of the in-group was significantly higher than that of the out-group. In comparison to the NoChat treatment, the Chat treatment resulted in significantly lower offers for both in-group and out-group members. The event-related potentials (ERP) results demonstrated the presence of a distinct N2 component in the frontal midline of the brain when investment decisions were made for both in-group and out-group members. During the offer decision-making stage, the P3 peak amplitude was significantly larger when interacting with in-group members compared to the out-group members. The event-related potentials oscillations (ERO) results indicated that when investment decisions were made for in-group members in the NoChat treatment, the beta band (18-28 Hz, 250-350 ms) power was more pronounced than when decisions were made for out-group members. In the NoChat treatment, offer decisions for in-group members yielded a more pronounced difference in beta band (15-20 Hz, 200-300 ms) power when compared to out-group members. Evidence from this study suggests that group identity can reduce the hold-up problem and corroborates the neural basis of group identity.
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Affiliation(s)
- Su Hao
- School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China
- Key Laboratory of Energy Security and Low-carbon Development, Southwest Petroleum University, Chengdu 610500, China
| | - Qing Xin
- School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China
| | - Zhang Xiaomin
- School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China
| | - Pan Jiali
- School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China
| | - Wang Xiaoqin
- School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China
| | - Yu Rong
- School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China
| | - Zhang Cenlin
- School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China
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Mazancieux A, Mauconduit F, Amadon A, Willem de Gee J, Donner TH, Meyniel F. Brainstem fMRI signaling of surprise across different types of deviant stimuli. Cell Rep 2023; 42:113405. [PMID: 37950868 PMCID: PMC10698303 DOI: 10.1016/j.celrep.2023.113405] [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: 07/21/2022] [Revised: 08/10/2023] [Accepted: 10/24/2023] [Indexed: 11/13/2023] Open
Abstract
Detection of deviant stimuli is crucial to orient and adapt our behavior. Previous work shows that deviant stimuli elicit phasic activation of the locus coeruleus (LC), which releases noradrenaline and controls central arousal. However, it is unclear whether the detection of behaviorally relevant deviant stimuli selectively triggers LC responses or other neuromodulatory systems (dopamine, serotonin, and acetylcholine). We combine human functional MRI (fMRI) recordings optimized for brainstem imaging with pupillometry to perform a mapping of deviant-related responses in subcortical structures. Participants have to detect deviant items in a "local-global" paradigm that distinguishes between deviance based on the stimulus probability and the sequence structure. fMRI responses to deviant stimuli are distributed in many cortical areas. Both types of deviance elicit responses in the pupil, LC, and other neuromodulatory systems. Our results reveal that the detection of task-relevant deviant items recruits the same multiple subcortical systems across computationally different types of deviance.
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Affiliation(s)
- Audrey Mazancieux
- Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, Commissariat à l'Energie Atomique et aux énergies alternatives, Centre national de la recherche scientifique, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France.
| | - Franck Mauconduit
- NeuroSpin, CEA, CNRS, BAOBAB, Université Paris-Saclay, Gif-Sur-Yvette, France
| | - Alexis Amadon
- NeuroSpin, CEA, CNRS, BAOBAB, Université Paris-Saclay, Gif-Sur-Yvette, France
| | - Jan Willem de Gee
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Tobias H Donner
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Florent Meyniel
- Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale, Commissariat à l'Energie Atomique et aux énergies alternatives, Centre national de la recherche scientifique, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France; Institut de neuromodulation, GHU Paris, psychiatrie et neurosciences, centre hospitalier Sainte-Anne, pôle hospitalo-universitaire 15, Université Paris Cité, Paris, France.
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35
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Herrera B, Sajad A, Errington SP, Schall JD, Riera JJ. Cortical origin of theta error signals. Cereb Cortex 2023; 33:11300-11319. [PMID: 37804250 PMCID: PMC10690871 DOI: 10.1093/cercor/bhad367] [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: 06/23/2023] [Revised: 09/13/2023] [Accepted: 09/14/2023] [Indexed: 10/09/2023] Open
Abstract
A multi-scale approach elucidated the origin of the error-related-negativity (ERN), with its associated theta-rhythm, and the post-error-positivity (Pe) in macaque supplementary eye field (SEF). Using biophysical modeling, synaptic inputs to a subpopulation of layer-3 (L3) and layer-5 (L5) pyramidal cells (PCs) were optimized to reproduce error-related spiking modulation and inter-spike intervals. The intrinsic dynamics of dendrites in L5 but not L3 error PCs generate theta rhythmicity with random phases. Saccades synchronized the phases of the theta-rhythm, which was magnified on errors. Contributions from error PCs to the laminar current source density (CSD) observed in SEF were negligible and could not explain the observed association between error-related spiking modulation in L3 PCs and scalp-EEG. CSD from recorded laminar field potentials in SEF was comprised of multipolar components, with monopoles indicating strong electro-diffusion, dendritic/axonal electrotonic current leakage outside SEF, or violations of the model assumptions. Our results also demonstrate the involvement of secondary cortical regions, in addition to SEF, particularly for the later Pe component. The dipolar component from the observed CSD paralleled the ERN dynamics, while the quadrupolar component paralleled the Pe. These results provide the most advanced explanation to date of the cellular mechanisms generating the ERN.
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Affiliation(s)
- Beatriz Herrera
- Department of Biomedical Engineering, Florida International University, Miami, FL 33174, United States
| | - Amirsaman Sajad
- Department of Psychology, Vanderbilt Vision Research Center, Center for Integrative & Cognitive Neuroscience, Vanderbilt University, Nashville, TN 37203, United States
| | - Steven P Errington
- Department of Psychology, Vanderbilt Vision Research Center, Center for Integrative & Cognitive Neuroscience, Vanderbilt University, Nashville, TN 37203, United States
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Jeffrey D Schall
- Centre for Vision Research, Vision: Science to Applications Program, Departments of Biology and Psychology, York University, Toronto, ON M3J 1P3, Canada
| | - Jorge J Riera
- Department of Biomedical Engineering, Florida International University, Miami, FL 33174, United States
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Cha O, Blake R. Procedure for extracting temporal structure embedded within psychophysical data. Behav Res Methods 2023:10.3758/s13428-023-02282-3. [PMID: 37993671 DOI: 10.3758/s13428-023-02282-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/28/2023] [Indexed: 11/24/2023]
Abstract
The idea that mental events unfold over time with an intrinsically paced regularity has a long history within experimental psychology, and it has gained traction from the actual measurement of brain rhythms evident in EEG signals recorded from the human brain and from direct recordings of action potentials and local field potentials within the nervous systems of nonhumans. The weak link in this idea, however, is the challenge of extracting signatures of this temporal structure from behavioral measures. Because there is nothing in the seamless stream of conscious awareness that belies rhythmic modulations in sensitivity or mental acuity, one must deploy inferential strategies for extracting evidence for the existence of temporal regularities in neural activity. We have devised a parametric procedure for analysis of temporal structure embedded in behaviorally measured data comprising durations. We confirm that this procedure, dubbed PATS, achieves comparable results to those obtained using spectral analysis, and that it outperforms conventional spectral analysis when analyzing human response time data containing just a few hundred data points per condition. PATS offers an efficient, sensitive means for bridging the gap between oscillations identified neurophysiologically and estimates of rhythmicity embedded within durations measured behaviorally.
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Affiliation(s)
- Oakyoon Cha
- Department of Psychology, Vanderbilt University, Nashville, TN, 37240, USA.
- Department of Psychology, Sungshin Women's University, Seoul, 02844, Republic of Korea.
| | - Randolph Blake
- Department of Psychology, Vanderbilt University, Nashville, TN, 37240, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, 37240, USA
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37
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Lu Z, Wang J, Wang F, Wu Z. Application of graph frequency attention convolutional neural networks in depression treatment response. Front Psychiatry 2023; 14:1244208. [PMID: 38045613 PMCID: PMC10690947 DOI: 10.3389/fpsyt.2023.1244208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 10/06/2023] [Indexed: 12/05/2023] Open
Abstract
Depression, a prevalent global mental health disorder, necessitates precise treatment response prediction for the improvement of personalized care and patient prognosis. The Graph Convolutional Neural Networks (GCNs) have emerged as a promising technique for handling intricate signals and classification tasks owing to their end-to-end neural architecture and nonlinear processing capabilities. In this context, this article proposes a model named the Graph Frequency Attention Convolutional Neural Network (GFACNN). Primarily, the model transforms the EEG signals into graphs to depict the connections between electrodes and brain regions, while integrating a frequency attention module to accentuate brain rhythm information. The proposed approach delves into the application of graph neural networks in the classification of EEG data, aiming to evaluate the response to antidepressant treatment and discern between treatment-resistant and treatment-responsive cases. Experimental results obtained from an EEG dataset at Peking University People's Hospital demonstrate the notable performance of GFACNN in distinguishing treatment responses among depression patients, surpassing deep learning methodologies including CapsuleNet and GoogLeNet. This highlights the efficacy of graph neural networks in leveraging the connections within EEG signal data. Overall, GFACNN exhibits potential for the classification of depression EEG signals, thereby potentially aiding clinical diagnosis and treatment.
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Affiliation(s)
| | | | - Fengqin Wang
- College of Physics and Electronics Science, Hubei Normal University, Huangshi, China
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38
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Hou J, Wang C, Jia L, Ma H. Long-term exposure to high altitude reduces alpha and beta bands event-related desynchronization in a Go/NoGo task. Sci Rep 2023; 13:19719. [PMID: 37957177 PMCID: PMC10643632 DOI: 10.1038/s41598-023-45807-8] [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: 04/02/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
More than 80 million people worldwide permanently live at high altitudes, and living in such a hypoxic environment can impair cognitive functions. However, it is largely unknown how long-term exposure to high altitude affects neural oscillations underlying these cognitive functions. The present study employed a Go/NoGo task to investigate the effects of long-term exposure to high altitude on neural oscillations during cognitive control. We compared event-related spectral perturbations between the low-altitude and high-altitude groups, and the results revealed increased theta event-related synchronization (ERS) and decreased alpha and beta event-related desynchronizations (ERDs) during the NoGo condition compared to the Go condition. Importantly, the high-altitude group showed reduced alpha and beta ERDs compared to the low-altitude group, while the theta ERS was not affected by altitude. We suggest that long-term exposure to high altitude has an impact on top-down inhibitory control and movement preparation and execution in the Go/NoGo task.
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Affiliation(s)
- Jianmin Hou
- School of Psychology, Zhejiang Normal University, Jinhua, 321004, China
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Cheng Wang
- School of Psychology, Zhejiang Normal University, Jinhua, 321004, China
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Lei Jia
- School of Psychology, Zhejiang Normal University, Jinhua, 321004, China
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Hailin Ma
- Plateau Brain Science Research Center, Tibet University, Lhasa, 850000, China.
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Xiao Y, Zhou J, Zhou R, Liu Y, Lü J, Huang L. Fronto-parietal theta high-definition transcranial alternating current stimulation may modulate working memory under postural control conditions in young healthy adults. Front Hum Neurosci 2023; 17:1265600. [PMID: 38021229 PMCID: PMC10666918 DOI: 10.3389/fnhum.2023.1265600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Objects This study aimed to investigate the immediate effects of fronto-parietal θ HD-tACS on a dual task of working memory-postural control. Methods In this within-subject cross-over pilot study, we assessed the effects of 20 min of 6 Hz-tACS targeting both the left dorsolateral prefrontal cortex (lDLPFC) and posterior parietal cortex (PPC) in 20 healthy adults (age: 21.6 ± 1.3 years). During each session, single- and dual-task behavioral tests (working memory single-task, static tandem standing, and a dual-task of working memory-postural control) and closed-eye resting-state EEG were assessed before and immediately after stimulation. Results Within the tACS group, we found a 5.3% significant decrease in working memory response time under the dual-task following tACS (t = -3.157, p = 0.005, Cohen's d = 0.742); phase synchronization analysis revealed a significant increase in the phase locking value (PLV) of θ band between F3 and P3 after tACS (p = 0.010, Cohen's d = 0.637). Correlation analyses revealed a significant correlation between increased rs-EEG θ power in the F3 and P3 channels and faster reaction time (r = -0.515, p = 0.02; r = -0.483, p = 0.031, respectively) in the dual-task working memory task after tACS. However, no differences were observed on either upright postural control performance or rs-EEG results (p-values <0.05). Conclusion Fronto-parietal θ HD-tACS has the potential of being a neuromodulatory tool for improving working memory performance in dual-task situations, but its effect on the modulation of concurrently performed postural control tasks requires further investigation.
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Affiliation(s)
- Yanwen Xiao
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
- Department of Rehabilitation Medicine, Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Shanwei, Guangdong, China
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Harvard Medical School, Boston, MA, United States
| | - Rong Zhou
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
| | - Yu Liu
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
| | - Jiaojiao Lü
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
| | - Lingyan Huang
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
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Morris PG, Herbison AE. Mechanism of Arcuate Kisspeptin Neuron Synchronization in Acute Brain Slices From Female Mice. Endocrinology 2023; 164:bqad167. [PMID: 37936337 PMCID: PMC10652333 DOI: 10.1210/endocr/bqad167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 10/27/2023] [Accepted: 11/01/2023] [Indexed: 11/09/2023]
Abstract
The mechanism by which arcuate kisspeptin (ARNKISS) neurons co-expressing glutamate, neurokinin B, and dynorphin intermittently synchronize their activity to drive pulsatile hormone secretion remains unclear in females. In order to study spontaneous synchronization within the ARNKISS neuron network, acute brain slices were prepared from adult female Kiss1-GCaMP6 mice. Analysis of both spontaneous synchronizations and those driven by high frequency stimulation of individual ARNKISS neurons revealed that the network exhibits semi-random emergent excitation dependent upon glutamate signaling through AMPA receptors. No role for NMDA receptors was identified. In contrast to male mice, ongoing tachykinin receptor tone within the slice operated to promote spontaneous synchronizations in females. As previously observed in males, we found that ongoing dynorphin transmission in the slice did not contribute to synchronization events. These observations indicate that a very similar AMPA receptor-dependent mechanism underlies ARNKISS neuron synchronizations in the female mouse supporting the "glutamate two-transition" model for kisspeptin neuron synchronization. However, a potentially important sex difference appears to exist with a more prominent facilitatory role for tachykinin transmission in the female.
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Affiliation(s)
- Paul G Morris
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK
| | - Allan E Herbison
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK
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41
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Phillips RS, Baertsch NA. Interdependence of cellular and network properties in respiratory rhythmogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.30.564834. [PMID: 37961254 PMCID: PMC10634953 DOI: 10.1101/2023.10.30.564834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
How breathing is generated by the preBötzinger Complex (preBötC) remains divided between two ideological frameworks, and the persistent sodium current (INaP) lies at the heart of this debate. Although INaP is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or "pacemaker" activity. In contrast, burstlet theory considers INaP dispensable because rhythm emerges from "pre-inspiratory" spiking activity driven by feed-forward network interactions. Using computational modeling, we discover that changes in spike shape can dissociate INaP from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and pre-inspiratory spiking without altering the role of INaP. Our results support a unifying hypothesis where INaP and excitatory network interactions, but not intrinsic bursting or pre-inspiratory spiking, are critical interdependent features of preBötC rhythmogenesis.
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Affiliation(s)
- Ryan S Phillips
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle WA, USA
| | - Nathan A Baertsch
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle WA, USA
- Pulmonary, Critical Care and Sleep Medicine, Department of Pediatrics, University of Washington, Seattle WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle WA, USA
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Zhao S, Zhou J, Zhang Y, Wang DH. γ And β Band Oscillation in Working Memory Given Sequential or Concurrent Multiple Items: A Spiking Network Model. eNeuro 2023; 10:ENEURO.0373-22.2023. [PMID: 37903618 PMCID: PMC10630927 DOI: 10.1523/eneuro.0373-22.2023] [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: 09/09/2022] [Revised: 10/10/2023] [Accepted: 10/22/2023] [Indexed: 11/01/2023] Open
Abstract
Working memory (WM) can maintain sequential and concurrent information, and the load enhances the γ band oscillation during the delay period. To provide a unified account for these phenomena in working memory, we investigated a continuous network model consisting of pyramidal cells, high-threshold fast-spiking interneurons (FS), and low-threshold nonfast-spiking interneurons (nFS) for working memory of sequential and concurrent directional cues. Our model exhibits the γ (30-100 Hz) and β (10-30 Hz) band oscillation during the retention of both concurrent cues and sequential cues. We found that the β oscillation results from the interaction between pyramidal cells and nFS, whereas the γ oscillation emerges from the interaction between pyramidal cells and FS because of the strong excitation elicited by cue presentation, shedding light on the mechanism underlying the enhancement of γ power in many cognitive executions.
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Affiliation(s)
- Shukuo Zhao
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Jinpu Zhou
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Yongwen Zhang
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Da-Hui Wang
- School of Systems Science, Beijing Normal University, Beijing 100875, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
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Kenefati G, Rockholt MM, Ok D, McCartin M, Zhang Q, Sun G, Maslinski J, Wang A, Chen B, Voigt EP, Chen ZS, Wang J, Doan LV. Changes in alpha, theta, and gamma oscillations in distinct cortical areas are associated with altered acute pain responses in chronic low back pain patients. Front Neurosci 2023; 17:1278183. [PMID: 37901433 PMCID: PMC10611481 DOI: 10.3389/fnins.2023.1278183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Introduction Chronic pain negatively impacts a range of sensory and affective behaviors. Previous studies have shown that the presence of chronic pain not only causes hypersensitivity at the site of injury but may also be associated with pain-aversive experiences at anatomically unrelated sites. While animal studies have indicated that the cingulate and prefrontal cortices are involved in this generalized hyperalgesia, the mechanisms distinguishing increased sensitivity at the site of injury from a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs are not well known. Methods We compared measured pain responses to peripheral mechanical stimuli applied to a site of chronic pain and at a pain-free site in participants suffering from chronic lower back pain (n = 15) versus pain-free control participants (n = 15) by analyzing behavioral and electroencephalographic (EEG) data. Results As expected, participants with chronic pain endorsed enhanced pain with mechanical stimuli in both back and hand. We further analyzed electroencephalographic (EEG) recordings during these evoked pain episodes. Brain oscillations in theta and alpha bands in the medial orbitofrontal cortex (mOFC) were associated with localized hypersensitivity, while increased gamma oscillations in the anterior cingulate cortex (ACC) and increased theta oscillations in the dorsolateral prefrontal cortex (dlPFC) were associated with generalized hyperalgesia. Discussion These findings indicate that chronic pain may disrupt multiple cortical circuits to impact nociceptive processing.
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Affiliation(s)
- George Kenefati
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
| | - Mika M. Rockholt
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
| | - Deborah Ok
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
| | - Michael McCartin
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
| | - Qiaosheng Zhang
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
| | - Guanghao Sun
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
| | - Julia Maslinski
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
| | - Aaron Wang
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
| | - Baldwin Chen
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
| | - Erich P. Voigt
- Department of Otolaryngology-Head and Neck Surgery, New York University Grossman School of Medicine, New York, NY, United States
| | - Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neuroscience and Physiology, Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY, United States
| | - Jing Wang
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neuroscience and Physiology, Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Lisa V. Doan
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Interdisciplinary Pain Research Program, New York University Grossman School of Medicine, New York, NY, United States
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Lu X, Wang Y, Liu Z, Gou Y, Jaeger D, St-Pierre F. Widefield imaging of rapid pan-cortical voltage dynamics with an indicator evolved for one-photon microscopy. Nat Commun 2023; 14:6423. [PMID: 37828037 PMCID: PMC10570354 DOI: 10.1038/s41467-023-41975-3] [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: 08/23/2022] [Accepted: 09/20/2023] [Indexed: 10/14/2023] Open
Abstract
Widefield imaging with genetically encoded voltage indicators (GEVIs) is a promising approach for understanding the role of large cortical networks in the neural coding of behavior. However, the limited performance of current GEVIs restricts their deployment for single-trial imaging of rapid neuronal voltage dynamics. Here, we developed a high-throughput platform to screen for GEVIs that combine fast kinetics with high brightness, sensitivity, and photostability under widefield one-photon illumination. Rounds of directed evolution produced JEDI-1P, a green-emitting fluorescent indicator with enhanced performance across all metrics. Next, we optimized a neonatal intracerebroventricular delivery method to achieve cost-effective and wide-spread JEDI-1P expression in mice. We also developed an approach to correct optical measurements from hemodynamic and motion artifacts effectively. Finally, we achieved stable brain-wide voltage imaging and successfully tracked gamma-frequency whisker and visual stimulations in awake mice in single trials, opening the door to investigating the role of high-frequency signals in brain computations.
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Affiliation(s)
- Xiaoyu Lu
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, 77005, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Yunmiao Wang
- Neuroscience Graduate Program, Emory University, Atlanta, GA, 30322, USA
- Biology Department, Emory University, Atlanta, GA, 30322, USA
| | - Zhuohe Liu
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yueyang Gou
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Dieter Jaeger
- Biology Department, Emory University, Atlanta, GA, 30322, USA.
| | - François St-Pierre
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, 77005, USA.
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, 77030, USA.
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Flores-Sandoval AA, Davila-Pérez P, Buss SS, Donohoe K, O'Connor M, Shafi MM, Pascual-Leone A, Benwell CSY, Fried PJ. Spectral power ratio as a measure of EEG changes in mild cognitive impairment due to Alzheimer's disease: a case-control study. Neurobiol Aging 2023; 130:50-60. [PMID: 37459658 PMCID: PMC10614059 DOI: 10.1016/j.neurobiolaging.2023.05.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/12/2023] [Accepted: 05/17/2023] [Indexed: 08/13/2023]
Abstract
Adopting preventive strategies in individuals with subclinical Alzheimer's disease (AD) has the potential to delay dementia onset and reduce healthcare costs. Thus, it is extremely important to identify inexpensive, scalable, sensitive, and specific markers to track disease progression. The electroencephalography spectral power ratio (SPR: the fast to slow spectral power ratio), a measure of the shift in power distribution from higher to lower frequencies, holds potential for aiding clinical practice. The SPR is altered in patients with AD, correlates with cognitive functions, and can be easily implemented in clinical settings. However, whether the SPR is sensitive to pathophysiological changes in the prodromal stage of AD is unclear. We explored the SPR of individuals diagnosed with amyloid-positive amnestic mild cognitive impairment (Aβ+aMCI) and its association with both cognitive function and amyloid load. The SPR was lower in Aβ+aMCI than in the cognitively unimpaired individuals and correlated with executive function scores but not with amyloid load. Hypothesis-generating analyses suggested that aMCI participants with a lower SPR had an increased probability of a positive amyloid positron emission tomography. Future research may explore the potential of this measure to classify aMCI individuals according to their AD biomarker status.
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Affiliation(s)
- Aimee A Flores-Sandoval
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, 10117 Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Paula Davila-Pérez
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Department of Clinical Neurophysiology, Hospital Universitario Rey Juan Carlos, Móstoles, Spain; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Stephanie S Buss
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Kevin Donohoe
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Margaret O'Connor
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, MA, USA; Hinda and Arthur Marcus Institute for Aging Research, and Deanna and Sidney Wolk Center for Memory Health, Hebrew Senior Life, Boston, MA, USA
| | - Christopher S Y Benwell
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Division of Psychology, School of Humanities, Social Sciences and Law, University of Dundee, Dundee, UK
| | - Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.
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Williams N, Ojanperä A, Siebenhühner F, Toselli B, Palva S, Arnulfo G, Kaski S, Palva JM. The influence of inter-regional delays in generating large-scale brain networks of phase synchronization. Neuroimage 2023; 279:120318. [PMID: 37572765 DOI: 10.1016/j.neuroimage.2023.120318] [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: 03/15/2023] [Revised: 07/14/2023] [Accepted: 08/10/2023] [Indexed: 08/14/2023] Open
Abstract
Large-scale networks of phase synchronization are considered to regulate the communication between brain regions fundamental to cognitive function, but the mapping to their structural substrates, i.e., the structure-function relationship, remains poorly understood. Biophysical Network Models (BNMs) have demonstrated the influences of local oscillatory activity and inter-regional anatomical connections in generating alpha-band (8-12 Hz) networks of phase synchronization observed with Electroencephalography (EEG) and Magnetoencephalography (MEG). Yet, the influence of inter-regional conduction delays remains unknown. In this study, we compared a BNM with standard "distance-dependent delays", which assumes constant conduction velocity, to BNMs with delays specified by two alternative methods accounting for spatially varying conduction velocities, "isochronous delays" and "mixed delays". We followed the Approximate Bayesian Computation (ABC) workflow, i) specifying neurophysiologically informed prior distributions of BNM parameters, ii) verifying the suitability of the prior distributions with Prior Predictive Checks, iii) fitting each of the three BNMs to alpha-band MEG resting-state data (N = 75) with Bayesian optimization for Likelihood-Free Inference (BOLFI), and iv) choosing between the fitted BNMs with ABC model comparison on a separate MEG dataset (N = 30). Prior Predictive Checks revealed the range of dynamics generated by each of the BNMs to encompass those seen in the MEG data, suggesting the suitability of the prior distributions. Fitting the models to MEG data yielded reliable posterior distributions of the parameters of each of the BNMs. Finally, model comparison revealed the BNM with "distance-dependent delays", as the most probable to describe the generation of alpha-band networks of phase synchronization seen in MEG. These findings suggest that distance-dependent delays might contribute to the neocortical architecture of human alpha-band networks of phase synchronization. Hence, our study illuminates the role of inter-regional delays in generating the large-scale networks of phase synchronization that might subserve the communication between regions vital to cognition.
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Affiliation(s)
- N Williams
- Helsinki Institute of Information Technology, Department of Computer Science, Aalto University, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University, Finland.
| | - A Ojanperä
- Department of Computer Science, Aalto University, Finland
| | - F Siebenhühner
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Finland; BioMag laboratory, HUS Medical Imaging Center, Helsinki, Finland
| | - B Toselli
- Department of Informatics, Bioengineering, Robotics & Systems Engineering, University of Genoa, Italy
| | - S Palva
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Finland; Centre for Cognitive Neuroimaging, School of Neuroscience & Psychology, University of Glasgow, United Kingdom
| | - G Arnulfo
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Finland; Department of Informatics, Bioengineering, Robotics & Systems Engineering, University of Genoa, Italy
| | - S Kaski
- Helsinki Institute of Information Technology, Department of Computer Science, Aalto University, Finland; Department of Computer Science, Aalto University, Finland; Department of Computer Science, University of Manchester, United Kingdom
| | - J M Palva
- Department of Neuroscience and Biomedical Engineering, Aalto University, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Finland; Centre for Cognitive Neuroimaging, School of Neuroscience & Psychology, University of Glasgow, United Kingdom
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Jia Y, Gu H, Li Y. Influence of inhibitory autapses on synchronization of inhibitory network gamma oscillations. Cogn Neurodyn 2023; 17:1131-1152. [PMID: 37786650 PMCID: PMC10542088 DOI: 10.1007/s11571-022-09856-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 06/22/2022] [Accepted: 07/12/2022] [Indexed: 11/30/2022] Open
Abstract
A recent experimental study showed that inhibitory autapses favor firing synchronization of parvalbumin interneurons in the neocortex during gamma oscillations. In the present paper, to provide a comprehensive and deep understanding to the experimental observation, the influence of inhibitory autapses on synchronization of interneuronal network gamma oscillations is theoretically investigated. Weak, middle, and strong synchronizations of a globally inhibitory coupled network composed of Wang-Buzsáki model without autapses appear at the bottom-left, middle, and top-right of the parameter plane with the conductance (gsyn) and the decay constant (τsyn) of inhibitory synapses taken as the x-axis and y-axis, respectively. After introducing inhibitory autapses, the border between the strong and middle synchronizations in the (gsyn, τsyn) plane moves to the top-right with increasing the conductance (gaut) and the decay constant (τaut) of autapses, due to that interspike interval of the single neuron becomes longer, leading to that larger τsyn is needed to ensure the strong synchronization. Then, the synchronization degree of middle and strong synchronizations around the border in the (gsyn, τsyn) plane decreases, while of strong synchronization in the remaining region remains unchanged. The synchronization degree of weak synchronization increases with increasing τaut and gaut, due to that the inhibitory autaptic current becomes strong and long to facilitate synchronization. The enhancement of weak synchronization modulated by inhibitory autapses is also simulated in the random, small-world, and scale-free networks, which may provide explanations to the experimental observation. These results present complex dynamics of synchronization modulated by inhibitory autapses, which needs future experimental demonstrations.
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Affiliation(s)
- Yanbing Jia
- School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, 471000 China
| | - Huaguang Gu
- School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai, 200092 China
| | - Yuye Li
- College of Mathematics and Computer Science, Chifeng University, Chifeng, 024000 China
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Theriault JE, Shaffer C, Dienel GA, Sander CY, Hooker JM, Dickerson BC, Barrett LF, Quigley KS. A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments. Neurosci Biobehav Rev 2023; 153:105373. [PMID: 37634556 PMCID: PMC10591873 DOI: 10.1016/j.neubiorev.2023.105373] [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: 04/24/2023] [Revised: 07/28/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.
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Affiliation(s)
- Jordan E Theriault
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - Clare Shaffer
- Northeastern University, Department of Psychology, Boston, MA, USA
| | - Gerald A Dienel
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Department of Cell Biology and Physiology, University of New Mexico, Albuquerque, NM, USA
| | - Christin Y Sander
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Jacob M Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Bradford C Dickerson
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Lisa Feldman Barrett
- Northeastern University, Department of Psychology, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Karen S Quigley
- Northeastern University, Department of Psychology, Boston, MA, USA; VA Bedford Healthcare System, Bedford, MA, USA
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Shafiei G, Fulcher BD, Voytek B, Satterthwaite TD, Baillet S, Misic B. Neurophysiological signatures of cortical micro-architecture. Nat Commun 2023; 14:6000. [PMID: 37752115 PMCID: PMC10522715 DOI: 10.1038/s41467-023-41689-6] [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] [Received: 01/24/2023] [Accepted: 09/11/2023] [Indexed: 09/28/2023] Open
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 6800 time-series 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 co-localized with multiple micro-architectural features, including gene expression 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, Camperdown, 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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Perellón-Alfonso R, Oblak A, Kuclar M, Škrlj B, Pileckyte I, Škodlar B, Pregelj P, Abellaneda-Pérez K, Bartrés-Faz D, Repovš G, Bon J. Dense attention network identifies EEG abnormalities during working memory performance of patients with schizophrenia. Front Psychiatry 2023; 14:1205119. [PMID: 37817830 PMCID: PMC10560761 DOI: 10.3389/fpsyt.2023.1205119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 09/04/2023] [Indexed: 10/12/2023] Open
Abstract
Introduction Patients with schizophrenia typically exhibit deficits in working memory (WM) associated with abnormalities in brain activity. Alterations in the encoding, maintenance and retrieval phases of sequential WM tasks are well established. However, due to the heterogeneity of symptoms and complexity of its neurophysiological underpinnings, differential diagnosis remains a challenge. We conducted an electroencephalographic (EEG) study during a visual WM task in fifteen schizophrenia patients and fifteen healthy controls. We hypothesized that EEG abnormalities during the task could be identified, and patients successfully classified by an interpretable machine learning algorithm. Methods We tested a custom dense attention network (DAN) machine learning model to discriminate patients from control subjects and compared its performance with simpler and more commonly used machine learning models. Additionally, we analyzed behavioral performance, event-related EEG potentials, and time-frequency representations of the evoked responses to further characterize abnormalities in patients during WM. Results The DAN model was significantly accurate in discriminating patients from healthy controls, ACC = 0.69, SD = 0.05. There were no significant differences between groups, conditions, or their interaction in behavioral performance or event-related potentials. However, patients showed significantly lower alpha suppression in the task preparation, memory encoding, maintenance, and retrieval phases F(1,28) = 5.93, p = 0.022, η2 = 0.149. Further analysis revealed that the two highest peaks in the attention value vector of the DAN model overlapped in time with the preparation and memory retrieval phases, as well as with two of the four significant time-frequency ROIs. Discussion These results highlight the potential utility of interpretable machine learning algorithms as an aid in diagnosis of schizophrenia and other psychiatric disorders presenting oscillatory abnormalities.
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Affiliation(s)
- Ruben Perellón-Alfonso
- Faculty of Medicine and Health Sciences, and Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Aleš Oblak
- University Psychiatric Clinic Ljubljana, Ljubljana, Slovenia
| | - Matija Kuclar
- Department of Psychiatry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Blaž Škrlj
- Jožef Stefan Institute, Ljubljana, Slovenia
| | - Indre Pileckyte
- Center for Brain and Cognition, Pompeu Fabra University, Barcelona, Spain
| | - Borut Škodlar
- University Psychiatric Clinic Ljubljana, Ljubljana, Slovenia
- Department of Psychiatry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Peter Pregelj
- University Psychiatric Clinic Ljubljana, Ljubljana, Slovenia
- Department of Psychiatry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Kilian Abellaneda-Pérez
- Faculty of Medicine and Health Sciences, and Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Institut Guttmann, Institut Universitari de Neurorehabilitació Adscrit a la UAB, Barcelona, Spain
| | - David Bartrés-Faz
- Faculty of Medicine and Health Sciences, and Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Grega Repovš
- Department of Psychology, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia
| | - Jurij Bon
- University Psychiatric Clinic Ljubljana, Ljubljana, Slovenia
- Department of Psychiatry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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