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Barzan R, Bozkurt B, Nejad MM, Süß ST, Surdin T, Böke H, Spoida K, Azimi Z, Grömmke M, Eickelbeck D, Mark MD, Rohr L, Siveke I, Cheng S, Herlitze S, Jancke D. Gain control of sensory input across polysynaptic circuitries in mouse visual cortex by a single G protein-coupled receptor type (5-HT 2A). Nat Commun 2024; 15:8078. [PMID: 39277631 PMCID: PMC11401874 DOI: 10.1038/s41467-024-51861-1] [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] [Received: 12/01/2022] [Accepted: 08/16/2024] [Indexed: 09/17/2024] Open
Abstract
Response gain is a crucial means by which modulatory systems control the impact of sensory input. In the visual cortex, the serotonergic 5-HT2A receptor is key in such modulation. However, due to its expression across different cell types and lack of methods that allow for specific activation, the underlying network mechanisms remain unsolved. Here we optogenetically activate endogenous G protein-coupled receptor (GPCR) signaling of a single receptor subtype in distinct mouse neocortical subpopulations in vivo. We show that photoactivation of the 5-HT2A receptor pathway in pyramidal neurons enhances firing of both excitatory neurons and interneurons, whereas 5-HT2A photoactivation in parvalbumin interneurons produces bidirectional effects. Combined photoactivation in both cell types and cortical network modelling demonstrates a conductance-driven polysynaptic mechanism that controls the gain of visual input without affecting ongoing baseline levels. Our study opens avenues to explore GPCRs neuromodulation and its impact on sensory-driven activity and ongoing neuronal dynamics.
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Affiliation(s)
- Ruxandra Barzan
- Optical Imaging Group, Institut für Neuroinformatik, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
- MEDICE Arzneimittel Pütter GmbH & Co. KG, Iserlohn, Germany
| | - Beyza Bozkurt
- Optical Imaging Group, Institut für Neuroinformatik, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Mohammadreza M Nejad
- Computational Neuroscience, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
| | - Sandra T Süß
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Tatjana Surdin
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Hanna Böke
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Katharina Spoida
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Zohre Azimi
- Optical Imaging Group, Institut für Neuroinformatik, Ruhr University Bochum, Bochum, Germany
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Michelle Grömmke
- Behavioral Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Dennis Eickelbeck
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Melanie D Mark
- Behavioral Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Lennard Rohr
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Ida Siveke
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Sen Cheng
- Computational Neuroscience, Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
| | - Stefan Herlitze
- Department of Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany
| | - Dirk Jancke
- Optical Imaging Group, Institut für Neuroinformatik, Ruhr University Bochum, Bochum, Germany.
- International Graduate School of Neuroscience, Ruhr University Bochum, Bochum, Germany.
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2
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Perez Velazquez JL, Mateos DM, Guevara R, Wennberg R. Unifying biophysical consciousness theories with MaxCon: maximizing configurations of brain connectivity. Front Syst Neurosci 2024; 18:1426986. [PMID: 39135560 PMCID: PMC11317472 DOI: 10.3389/fnsys.2024.1426986] [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: 05/02/2024] [Accepted: 07/09/2024] [Indexed: 08/15/2024] Open
Abstract
There is such a vast proliferation of scientific theories of consciousness that it is worrying some scholars. There are even competitions to test different theories, and the results are inconclusive. Consciousness research, far from converging toward a unifying framework, is becoming more discordant than ever, especially with respect to theoretical elements that do not have a clear neurobiological basis. Rather than dueling theories, an integration across theories is needed to facilitate a comprehensive view on consciousness and on how normal nervous system dynamics can develop into pathological states. In dealing with what is considered an extremely complex matter, we try to adopt a perspective from which the subject appears in relative simplicity. Grounded in experimental and theoretical observations, we advance an encompassing biophysical theory, MaxCon, which incorporates aspects of several of the main existing neuroscientific consciousness theories, finding convergence points in an attempt to simplify and to understand how cellular collective activity is organized to fulfill the dynamic requirements of the diverse theories our proposal comprises. Moreover, a computable index indicating consciousness level is presented. Derived from the level of description of the interactions among cell networks, our proposal highlights the association of consciousness with maximization of the number of configurations of neural network connections -constrained by neuroanatomy, biophysics and the environment- that is common to all consciousness theories.
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Affiliation(s)
- Jose Luis Perez Velazquez
- The Ronin Institute, Montclair, NJ, United States
- Institute for Globally Distributed Open Research and Education, Gothenburg, Sweden
| | - Diego Martin Mateos
- Institute for Globally Distributed Open Research and Education, Gothenburg, Sweden
- Achucarro Basque Centre for Neuroscience, Leioa, Spain
| | - Ramon Guevara
- Department of Physics and Astronomy, Department of Developmental Psychology and Socialization, University of Padua, Padova, Italy
| | - Richard Wennberg
- University Health Network, University of Toronto, Toronto, ON, Canada
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3
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Karvat G, Landau AN. A Role for Bottom-Up Alpha Oscillations in Temporal Integration. J Cogn Neurosci 2024; 36:632-639. [PMID: 37713671 DOI: 10.1162/jocn_a_02056] [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: 09/17/2023]
Abstract
Neural oscillations in the 8-12 Hz alpha band are thought to represent top-down inhibitory control and to influence temporal resolution: Individuals with faster peak frequencies segregate stimuli appearing closer in time. Recently, this theory has been challenged. Here, we investigate a special case in which alpha does not correlate with temporal resolution: when stimuli are presented amidst strong visual drive. Based on findings regarding alpha rhythmogenesis and wave spatial propagation, we suggest that stimulus-induced, bottom-up alpha oscillations play a role in temporal integration. We propose a theoretical model, informed by visual persistence, lateral inhibition, and network refractory periods, and simulate physiologically plausible scenarios of the interaction between bottom-up alpha and the temporal segregation. Our simulations reveal that different features of oscillations, including frequency, phase, and power, can influence temporal perception and provide a theoretically informed starting point for future empirical studies.
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4
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Lukemire J, Pagnoni G, Guo Y. Sparse Bayesian modeling of hierarchical independent component analysis: Reliable estimation of individual differences in brain networks. Biometrics 2023; 79:3599-3611. [PMID: 37036246 PMCID: PMC11149774 DOI: 10.1111/biom.13867] [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: 02/08/2022] [Accepted: 03/27/2023] [Indexed: 04/11/2023]
Abstract
Independent component analysis (ICA) is one of the leading approaches for studying brain functional networks. There is increasing interest in neuroscience studies to investigate individual differences in brain networks and their association with demographic characteristics and clinical outcomes. In this work, we develop a sparse Bayesian group hierarchical ICA model that offers significant improvements over existing ICA techniques for identifying covariate effects on the brain network. Specifically, we model the population-level ICA source signals for brain networks using a Dirichlet process mixture. To reliably capture individual differences on brain networks, we propose sparse estimation of the covariate effects in the hierarchical ICA model via a horseshoe prior. Through extensive simulation studies, we show that our approach performs considerably better in detecting covariate effects in comparison with the leading group ICA methods. We then perform an ICA decomposition of a between-subject meditation study. Our method is able to identify significant effects related to meditative practice in brain regions that are consistent with previous research into the default mode network, whereas other group ICA approaches find few to no effects.
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Affiliation(s)
- Joshua Lukemire
- Department of Biostatistics and Bioinformatics, Emory University, Georgia, USA
| | - Giuseppe Pagnoni
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Ying Guo
- Department of Biostatistics and Bioinformatics, Emory University, Georgia, USA
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5
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Klimenko AV, Pertsov SS. Physiological Support of Goal-Directed Activity in Human. Bull Exp Biol Med 2023; 176:1-8. [PMID: 38085394 DOI: 10.1007/s10517-023-05956-2] [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: 03/02/2023] [Indexed: 12/19/2023]
Abstract
The effectiveness of goal-directed human behavior and the processes underlying organization of such activity are the subjects of various biomedical studies. Here we review both classical and modern evidence on the fundamental principles of goal-directed human activity. Facts are presented about the basic mechanisms that ensure the effectiveness of goal-directed behavior and determine its physiological cost.
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Affiliation(s)
- A V Klimenko
- P. K. Anokhin Research Institute of Normal Physiology, Moscow, Russia.
| | - S S Pertsov
- P. K. Anokhin Research Institute of Normal Physiology, Moscow, Russia
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6
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Maldonado PE, Concha-Miranda M, Schwalm M. Autogenous cerebral processes: an invitation to look at the brain from inside out. Front Neural Circuits 2023; 17:1253609. [PMID: 37941893 PMCID: PMC10629273 DOI: 10.3389/fncir.2023.1253609] [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: 07/05/2023] [Accepted: 09/26/2023] [Indexed: 11/10/2023] Open
Abstract
While external stimulation can reliably trigger neuronal activity, cerebral processes can operate independently from the environment. In this study, we conceptualize autogenous cerebral processes (ACPs) as intrinsic operations of the brain that exist on multiple scales and can influence or shape stimulus responses, behavior, homeostasis, and the physiological state of an organism. We further propose that the field should consider exploring to what extent perception, arousal, behavior, or movement, as well as other cognitive functions previously investigated mainly regarding their stimulus-response dynamics, are ACP-driven.
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Affiliation(s)
- Pedro E. Maldonado
- Departamento de Neurociencia, Facultad de Medicina, Universidad de Chile, Santiago, Chile
- Biomedical Neuroscience Institute (BNI), Faculty of Medicine, University of Chile, Santiago, Chile
- National Center for Artificial Intelligence (CENIA), Santiago, Chile
| | - Miguel Concha-Miranda
- Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Miriam Schwalm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
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7
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Beresniewicz J, Riemer F, Kazimierczak K, Ersland L, Craven AR, Hugdahl K, Grüner R. Similarities and differences between intermittent and continuous resting-state fMRI. Front Hum Neurosci 2023; 17:1238888. [PMID: 37600552 PMCID: PMC10435290 DOI: 10.3389/fnhum.2023.1238888] [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: 06/12/2023] [Accepted: 07/12/2023] [Indexed: 08/22/2023] Open
Abstract
Introduction Functional Magnetic Resonance Imaging (fMRI) block-design experiments typically include active ON-blocks with presentation of cognitive tasks which are contrasted with OFF- blocks with no tasks presented. OFF-blocks in between ON-blocks can however, also be seen as a proxy for intermittent periods of resting, inducing temporary resting-states. We still do not know if brain activity during such intermittent periods reflects the same kind of resting-state activity as that obtained during a continuous period, as is typically the case in studies of the classic Default Mode Network (DMN). The purpose of the current study was therefore to investigate both similarities and differences in brain activity between intermittent and continuous resting conditions. Methods There were 47 healthy participants in the 3T fMRI experiment. Data for the intermittent resting-state condition were acquired from resting-periods in between active task-processing periods in a standard ON-OFF block design, with three different cognitive tasks presented during ON-blocks. Data for the continuous resting-state condition were acquired during a 5 min resting period after the task-design had been presented. Results and discussion The results showed that activity was overall similar in the two conditions, but with some differences. These differences were within the DMN network, and for the interaction of DMN with other brain networks. DMN maps showed weak overlap between conditions in the medial prefrontal cortex (MPFC), and in particular for the intermittent compared to the continuous resting-state condition. Moreover, DMN showed strong connectivity with the salience network (SN) in the intermittent resting-state condition, particularly in the anterior insula and the supramarginal gyrus. The observed differences may reflect a "carry-over" effect from task-processing to the next resting-state period, not present in the continuous resting-state condition, causing interference from the ON-blocks. Further research is needed to fully understand the extent of differences between intermittent and continuous resting-state conditions.
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Affiliation(s)
- Justyna Beresniewicz
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Katarzyna Kazimierczak
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Lars Ersland
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Alexander R. Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Kenneth Hugdahl
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Renate Grüner
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Physics and Technology, University of Bergen, Bergen, Norway
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8
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Croce P, Tecchio F, Tamburro G, Fiedler P, Comani S, Zappasodi F. Brain electrical microstate features as biomarkers of a stable motor output. J Neural Eng 2022; 19. [PMID: 36195069 DOI: 10.1088/1741-2552/ac975b] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 10/04/2022] [Indexed: 01/27/2023]
Abstract
Objective.The aim of the present study was to elucidate the brain dynamics underlying the maintenance of a constant force level exerted during a visually guided isometric contraction task by optimizing a predictive multivariate model based on global and spectral brain dynamics features.Approach.Electroencephalography (EEG) was acquired in 18 subjects who were asked to press a bulb and maintain a constant force level, indicated by a bar on a screen. For intervals of 500 ms, we calculated an index of force stability as well as indices of brain dynamics: microstate metrics (duration, occurrence, global explained variance, directional predominance) and EEG spectral amplitudes in the theta, low alpha, high alpha and beta bands. We optimized a multivariate regression model (partial least square (PLS)) where the microstate features and the spectral amplitudes were the input variables and the indexes of force stability were the output variables. The issues related to the collinearity among the input variables and to the generalizability of the model were addressed using PLS in a nested cross-validation approach.Main results.The optimized PLS regression model reached a good generalizability and succeeded to show the predictive value of microstates and spectral features in inferring the stability of the exerted force. Longer duration and higher occurrence of microstates, associated with visual and executive control networks, corresponded to better contraction performances, in agreement with the role played by the visual system and executive control network for visuo-motor integration.Significance.A combination of microstate metrics and brain rhythm amplitudes could be considered as biomarkers of a stable visually guided motor output not only at a group level, but also at an individual level. Our results may play an important role for a better understanding of the motor control in single trials or in real-time applications as well as in the study of motor control.
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Affiliation(s)
- Pierpaolo Croce
- Department of Neuroscience, Imaging and Clinical Sciences, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy.,Behavioral Imaging and Neural Dynamics Center, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy
| | - Franca Tecchio
- Laboratory of Electrophysiology for Translational NeuroScience (LET'S), ISTC-CNR, Rome, Italy.,Fondazione Policlinico Gemelli IRCCS, Rome, Italy
| | - Gabriella Tamburro
- Department of Neuroscience, Imaging and Clinical Sciences, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy.,Behavioral Imaging and Neural Dynamics Center, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy
| | - Patrique Fiedler
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, 98693 Ilmenau, Germany
| | - Silvia Comani
- Department of Neuroscience, Imaging and Clinical Sciences, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy.,Behavioral Imaging and Neural Dynamics Center, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy
| | - Filippo Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy.,Behavioral Imaging and Neural Dynamics Center, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies, University 'Gabriele d'Annunzio' of Chieti-Pescara, Chieti, Italy
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9
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Spontaneous activity patterns in human motor cortex replay evoked activity patterns for hand movements. Sci Rep 2022; 12:16867. [PMID: 36207360 PMCID: PMC9546868 DOI: 10.1038/s41598-022-20866-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 09/20/2022] [Indexed: 11/08/2022] Open
Abstract
Spontaneous brain activity, measured with resting state fMRI (R-fMRI), is correlated among regions that are co-activated by behavioral tasks. It is unclear, however, whether spatial patterns of spontaneous activity within a cortical region correspond to spatial patterns of activity evoked by specific stimuli, actions, or mental states. The current study investigated the hypothesis that spontaneous activity in motor cortex represents motor patterns commonly occurring in daily life. To test this hypothesis 15 healthy participants were scanned while performing four different hand movements. Three movements (Grip, Extend, Pinch) were ecological involving grip and grasp hand movements; one control movement involving the rotation of the wrist was not ecological and infrequent (Shake). They were also scanned at rest before and after the execution of the motor tasks (resting-state scans). Using the task data, we identified movement-specific patterns in the primary motor cortex. These task-defined patterns were compared to resting-state patterns in the same motor region. We also performed a control analysis within the primary visual cortex. We found that spontaneous activity patterns in the primary motor cortex were more like task patterns for ecological than control movements. In contrast, there was no difference between ecological and control hand movements in the primary visual area. These findings provide evidence that spontaneous activity in human motor cortex forms fine-scale, patterned representations associated with behaviors that frequently occur in daily life.
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10
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Capouskova K, Kringelbach ML, Deco G. Modes of cognition: Evidence from metastable brain dynamics. Neuroimage 2022; 260:119489. [PMID: 35882268 DOI: 10.1016/j.neuroimage.2022.119489] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/12/2022] [Accepted: 07/15/2022] [Indexed: 01/31/2023] Open
Abstract
Managing cognitive load depends on adequate resource allocation by the human brain through the engagement of metastable substates, which are large-scale functional networks that change over time. We employed a novel analysis method, deep autoencoder dynamical analysis (DADA), with 100 healthy adults selected from the Human Connectome Project (HCP) data set in rest and six cognitive tasks. The deep autoencoder of DADA described seven recurrent stochastic metastable substates from the functional connectome of BOLD phase coherence matrices. These substates were significantly differentiated in terms of their probability of appearance, time duration, and spatial attributes. We found that during different cognitive tasks, there was a higher probability of having more connected substates dominated by a high degree of connectivity in the thalamus. In addition, compared with those during tasks, resting brain dynamics have a lower level of predictability, indicating a more uniform distribution of metastability between substates, quantified by higher entropy. These novel findings provide empirical evidence for the philosophically motivated cognitive theory, suggesting on-line and off-line as two fundamentally distinct modes of cognition. On-line cognition refers to task-dependent engagement with the sensory input, while off-line cognition is a slower, environmentally detached mode engaged with decision and planning. Overall, the DADA framework provides a bridge between neuroscience and cognitive theory that can be further explored in the future.
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Affiliation(s)
- Katerina Capouskova
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Ramon Trias Fargas 25-27, Barcelona 08005, Spain.
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Ramon Trias Fargas 25-27, Barcelona 08005, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
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11
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Goetz SM, Howell B, Wang B, Li Z, Sommer MA, Peterchev AV, Grill WM. Isolating two sources of variability of subcortical stimulation to quantify fluctuations of corticospinal tract excitability. Clin Neurophysiol 2022; 138:134-142. [PMID: 35397278 PMCID: PMC9271909 DOI: 10.1016/j.clinph.2022.02.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/17/2022] [Accepted: 02/01/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Investigate the variability previously found with cortical stimulation and handheld transcranial magnetic stimulation (TMS) coils, criticized for its high potential of coil position fluctuations, bypassing the cortex using deep brain electrical stimulation (DBS) of the corticospinal tract with fixed electrodes where both latent variations of the coil position of TMS are eliminated and cortical excitation fluctuations should be absent. METHODS Ten input-output curves were recorded from five anesthetized cats with implanted DBS electrodes targeting the corticospinal tract. Goodness of fit of regressions with a conventional single variability source as well as a dual variability source model was quantified using a Schwarz Bayesian Information approach to avoid overfitting. RESULTS Motor evoked potentials (MEPs) through DBS of the corticospinal tract revealed short-term fluctuations in excitability of the targeted neuron pathway reflecting endogenous input-side variability at similar magnitude as TMS despite bypassing cortical networks. CONCLUSION Input-side variability, i.e., variability resulting in changing MEP amplitudes as if the stimulation strength was modulated, also emerges in electrical stimulation at a similar degree and is not primarily a result of varying stimulation, such as minor coil movements in TMS. More importantly, this variability component is present, although the cortex is bypassed. Thus, it may be of spinal origin, which can include cortical input from spinal projections. Further, the nonlinearity of the compound variability entails complex heteroscedastic non-Gaussian distributions and typically does not allow simple linear averages in statistical analysis of MEPs. As the average is dominated by outliers, it risks bias. With appropriate regression, the net effects of excitatory and inhibitory inputs to the targeted neuron pathways become noninvasively observable and quantifiable. SIGNIFICANCE The neural responses evoked by artificial stimulation in the cerebral cortex are variable. For example, MEPs in response to repeated presentations of the same stimulus can vary from no response to saturation across trials. Several sources of such variability have been suggested, and most of them may be technical in nature, but localization is missing.
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Affiliation(s)
- Stefan M Goetz
- Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, UK; Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC 27710, USA; Department of Neurosurgery, Duke University, Durham, NC 27710, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA.
| | - Bryan Howell
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Boshuo Wang
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC 27710, USA
| | - Zhongxi Li
- Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA
| | - Marc A Sommer
- Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Angel V Peterchev
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC 27710, USA; Department of Neurosurgery, Duke University, Durham, NC 27710, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Warren M Grill
- Department of Neurosurgery, Duke University, Durham, NC 27710, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Department of Neurobiology, Duke University, Durham, NC 27710, USA
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12
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Connolly P. Instability and Uncertainty Are Critical for Psychotherapy: How the Therapeutic Alliance Opens Us Up. Front Psychol 2022; 12:784295. [PMID: 35069367 PMCID: PMC8777103 DOI: 10.3389/fpsyg.2021.784295] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 12/06/2021] [Indexed: 01/04/2023] Open
Abstract
Tschacher and Haken have recently applied a systems-based approach to modeling psychotherapy process in terms of potentially beneficial tendencies toward deterministic as well as chaotic forms of change in the client's behavioral, cognitive and affective experience during the course of therapy. A chaotic change process refers to a greater exploration of the states that a client can be in, and it may have a potential positive role to play in their development. A distinction is made between on the one hand, specific instances of instability which are due to techniques employed by the therapist, and on the other, a more general instability which is due to the therapeutic relationship, and a key, necessary result of a successful therapeutic alliance. Drawing on Friston's systems-based model of free energy minimization and predictive coding, it is proposed here that the increase in the instability of a client's functioning due to therapy can be conceptualized as a reduction in the precisions (certainty) with which the client's prior beliefs about themselves and their world, are held. It is shown how a good therapeutic alliance (characterized by successful interpersonal synchrony of the sort described by Friston and Frith) results in the emergence of a new hierarchical level in the client's generative model of themselves and their relationship with the world. The emergence of this new level of functioning permits the reduction of the precisions of the client's priors, which allows the client to 'open up': to experience thoughts, emotions and experiences they did not have before. It is proposed that this process is a necessary precursor to change due to psychotherapy. A good consilience can be found between this approach to understanding the role of the therapeutic alliance, and the role of epistemic trust in psychotherapy as described by Fonagy and Allison. It is suggested that beneficial forms of instability in clients are an underappreciated influence on psychotherapy process, and thoughts about the implications, as well as situations in which instability may not be beneficial (or potentially harmful) for therapy, are considered.
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Affiliation(s)
- Patrick Connolly
- Counselling and Psychology Department, Hong Kong Shue Yan University, North Point, Hong Kong SAR, China
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13
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Winters JJ. The Temporally-Integrated Causality Landscape: Reconciling Neuroscientific Theories With the Phenomenology of Consciousness. Front Hum Neurosci 2021; 15:768459. [PMID: 34803643 PMCID: PMC8599361 DOI: 10.3389/fnhum.2021.768459] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/11/2021] [Indexed: 11/30/2022] Open
Abstract
In recent years, there has been a proliferation of neuroscientific theories of consciousness. These include theories which explicitly point to EM fields, notably Operational Architectonics and, more recently, the General Resonance Theory. In phenomenological terms, human consciousness is a unified composition of contents. These contents are specific and meaningful, and they exist from a subjective point of view. Human conscious experience is temporally continuous, limited in content, and coherent. Based upon those phenomenal observations, pre-existing theories of consciousness, and a large body of experimental evidence, I derived the Temporally-Integrated Causality Landscape (TICL). In brief, the TICL proposes that the neural correlate of consciousness is a structure of temporally integrated causality occurring over a large portion of the thalamocortical system. This structure is composed of a large, integrated set of neuronal elements (the System), which contains some subsystems, defined as having a higher level of temporally-integrated causality than the System as a whole. Each Subsystem exists from the point of view of the System, in the form of meaningful content. In this article, I review the TICL and consider the importance of EM forces as a mechanism of neural causality. I compare the fundamentals of TICL to those of several other neuroscientific theories. Using five major characteristics of phenomenal consciousness as a standard, I compare the basic tenets of Integrated Information Theory, Global Neuronal Workspace, General Resonance Theory, Operational Architectonics, and the Temporo-spatial Theory of Consciousness with the framework of the TICL. While the literature concerned with these theories tends to focus on different lines of evidence, there are fundamental areas of agreement. This means that, in time, it may be possible for many of them to converge upon the truth. In this analysis, I conclude that a primary distinction which divides these theories is the feature of spatial and temporal nesting. Interestingly, this distinction does not separate along the fault line between theories explicitly concerned with EM fields and those which are not. I believe that reconciliation is possible, at least in principle, among those theories that recognize the following: just as the contents of consciousness are distinctions within consciousness, the neural correlates of conscious content should be distinguishable from but fall within the spatial and temporal boundaries of the full neural correlates of consciousness.
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Affiliation(s)
- Jesse J Winters
- Department of Psychiatry and Behavioral Sciences, Texas A&M University, College Station, United States
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14
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Schwartz R, Rozier C, Seidel Malkinson T, Lehongre K, Adam C, Lambrecq V, Navarro V, Naccache L, Axelrod V. Comparing stimulus-evoked and spontaneous response of the face-selective multi-units in the human posterior fusiform gyrus. Neurosci Conscious 2021; 2021:niab033. [PMID: 34667640 PMCID: PMC8520048 DOI: 10.1093/nc/niab033] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 08/03/2021] [Accepted: 09/02/2021] [Indexed: 11/23/2022] Open
Abstract
The stimulus-evoked neural response is a widely explored phenomenon. Conscious awareness is associated in many cases with the corresponding selective stimulus-evoked response. For example, conscious awareness of a face stimulus is associated with or accompanied by stimulus-evoked activity in the fusiform face area (FFA). In addition to the stimulus-evoked response, spontaneous (i.e. task-unrelated) activity in the brain is also abundant. Notably, spontaneous activity is considered unconscious. For example, spontaneous activity in the FFA is not associated with conscious awareness of a face. The question is: what is the difference at the neural level between stimulus-evoked activity in a case that this activity is associated with conscious awareness of some content (e.g. activity in the FFA in response to fully visible face stimuli) and spontaneous activity in that same region of the brain? To answer this question, in the present study, we had a rare opportunity to record two face-selective multi-units in the vicinity of the FFA in a human patient. We compared multi-unit face-selective task-evoked activity with spontaneous prestimulus and a resting-state activity. We found that when activity was examined over relatively long temporal windows (e.g. 100–200 ms), face-selective stimulus-evoked firing in the recorded multi-units was much higher than the spontaneous activity. In contrast, when activity was examined over relatively short windows, we found many cases of high firing rates within the spontaneous activity that were comparable to stimulus-evoked activity. Our results thus indicate that the sustained activity is what might differentiate between stimulus-evoked activity that is associated with conscious awareness and spontaneous activity.
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Affiliation(s)
- Rina Schwartz
- The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan 52900, Israel
| | - Camille Rozier
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, Paris 75013, France
| | - Tal Seidel Malkinson
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, Paris 75013, France
| | - Katia Lehongre
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, Paris 75013, France
| | - Claude Adam
- Neurology Department, AP-HP, GH Pitie-Salpêtrière-Charles Foix, Epilepsy Unit, 47-83 boulevard de l'Hôpital, Paris 75013, France
| | - Virginie Lambrecq
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, Paris 75013, France
| | - Vincent Navarro
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, Paris 75013, France
| | - Lionel Naccache
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, Paris 75013, France
| | - Vadim Axelrod
- The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan 52900, Israel
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15
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Pezzulo G, Zorzi M, Corbetta M. The secret life of predictive brains: what's spontaneous activity for? Trends Cogn Sci 2021; 25:730-743. [PMID: 34144895 PMCID: PMC8363551 DOI: 10.1016/j.tics.2021.05.007] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 05/14/2021] [Accepted: 05/19/2021] [Indexed: 01/23/2023]
Abstract
Brains at rest generate dynamical activity that is highly structured in space and time. We suggest that spontaneous activity, as in rest or dreaming, underlies top-down dynamics of generative models. During active tasks, generative models provide top-down predictive signals for perception, cognition, and action. When the brain is at rest and stimuli are weak or absent, top-down dynamics optimize the generative models for future interactions by maximizing the entropy of explanations and minimizing model complexity. Spontaneous fluctuations of correlated activity within and across brain regions may reflect transitions between 'generic priors' of the generative model: low dimensional latent variables and connectivity patterns of the most common perceptual, motor, cognitive, and interoceptive states. Even at rest, brains are proactive and predictive.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Roma, Italy.
| | - Marco Zorzi
- Department of General Psychology and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; IRCCS San Camillo Hospital, Venice, Italy
| | - Maurizio Corbetta
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Venetian Institute of Molecular Medicine (VIMM), Fondazione Biomedica, Padova, Italy
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16
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Wainio-Theberge S, Wolff A, Northoff G. Dynamic relationships between spontaneous and evoked electrophysiological activity. Commun Biol 2021; 4:741. [PMID: 34131279 PMCID: PMC8206204 DOI: 10.1038/s42003-021-02240-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 05/14/2021] [Indexed: 02/06/2023] Open
Abstract
Spontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.
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Affiliation(s)
- Soren Wainio-Theberge
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada.,Integrated Program in Neuroscience, McGill University, Montréal, QC, Canada
| | - Annemarie Wolff
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada. .,Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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17
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Alderson TH, Bokde ALW, Kelso JAS, Maguire L, Coyle D. Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms. Hum Brain Mapp 2020; 41:3212-3234. [PMID: 32301561 PMCID: PMC7375112 DOI: 10.1002/hbm.25009] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 01/20/2020] [Accepted: 03/31/2020] [Indexed: 12/24/2022] Open
Abstract
Despite resting state networks being associated with a variety of cognitive abilities, it remains unclear how these local areas act in concert to express particular cognitive operations. Theoretical and empirical accounts indicate that large-scale resting state networks reconcile dual tendencies towards integration and segregation by operating in a metastable regime of their coordination dynamics. Metastability may confer important behavioural qualities by binding distributed local areas into large-scale neurocognitive networks. We tested this hypothesis by analysing fMRI data in a large cohort of healthy individuals (N = 566) and comparing the metastability of the brain's large-scale resting network architecture at rest and during the performance of several tasks. Metastability was estimated using a well-defined collective variable capturing the level of 'phase-locking' between large-scale networks over time. Task-based reasoning was principally characterised by high metastability in cognitive control networks and low metastability in sensory processing areas. Although metastability between resting state networks increased during task performance, cognitive ability was more closely linked to spontaneous activity. High metastability in the intrinsic connectivity of cognitive control networks was linked to novel problem solving or fluid intelligence, but was less important in tasks relying on previous experience or crystallised intelligence. Crucially, subjects with resting architectures similar or 'pre-configured' to a task-general arrangement demonstrated superior cognitive performance. Taken together, our findings support a key linkage between the spontaneous metastability of large-scale networks in the cerebral cortex and cognition.
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Affiliation(s)
- Thomas H. Alderson
- Intelligent Systems Research CentreUlster UniversityAntrimUnited Kingdom
- Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana‐ChampaignUrbanaIllinoisUnited States
| | - Arun L. W. Bokde
- Trinity College Institute of Neuroscience and Cognitive Systems Group, Discipline of Psychiatry, School of MedicineTrinity College DublinDublinIreland
| | - J. A. Scott Kelso
- Intelligent Systems Research CentreUlster UniversityAntrimUnited Kingdom
- Center for Complex Systems and Brain SciencesFlorida Atlantic UniversityBoca RatonFloridaUnited States
| | - Liam Maguire
- Intelligent Systems Research CentreUlster UniversityAntrimUnited Kingdom
| | - Damien Coyle
- Intelligent Systems Research CentreUlster UniversityAntrimUnited Kingdom
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18
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Temporal Signatures of Criticality in Human Cortical Excitability as Probed by Early Somatosensory Responses. J Neurosci 2020; 40:6572-6583. [PMID: 32719161 DOI: 10.1523/jneurosci.0241-20.2020] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 05/05/2020] [Accepted: 06/19/2020] [Indexed: 11/21/2022] Open
Abstract
Brain responses vary considerably from moment to moment, even to identical sensory stimuli. This has been attributed to changes in instantaneous neuronal states determining the system's excitability. Yet the spatiotemporal organization of these dynamics remains poorly understood. Here we test whether variability in stimulus-evoked activity can be interpreted within the framework of criticality, which postulates dynamics of neural systems to be tuned toward the phase transition between stability and instability as is reflected in scale-free fluctuations in spontaneous neural activity. Using a novel noninvasive approach in 33 male human participants, we tracked instantaneous cortical excitability by inferring the magnitude of excitatory postsynaptic currents from the N20 component of the somatosensory evoked potential. Fluctuations of cortical excitability demonstrated long-range temporal dependencies decaying according to a power law across trials, a hallmark of systems at critical states. As these dynamics covaried with changes in prestimulus oscillatory activity in the alpha band (8-13 Hz), we establish a mechanistic link between ongoing and evoked activity through cortical excitability and argue that the co-emergence of common temporal power laws may indeed originate from neural networks poised close to a critical state. In contrast, no signatures of criticality were found in subcortical or peripheral nerve activity. Thus, criticality may represent a parsimonious organizing principle of variability in stimulus-related brain processes on a cortical level, possibly reflecting a delicate equilibrium between robustness and flexibility of neural responses to external stimuli.SIGNIFICANCE STATEMENT Variability of neural responses in primary sensory areas is puzzling, as it is detrimental to the exact mapping between stimulus features and neural activity. However, such variability can be beneficial for information processing in neural networks if it is of a specific nature, namely, if dynamics are poised at a so-called critical state characterized by a scale-free spatiotemporal structure. Here, we demonstrate the existence of a link between signatures of criticality in ongoing and evoked activity through cortical excitability, which fills the long-standing gap between two major directions of research on neural variability: the impact of instantaneous brain states on stimulus processing on the one hand and the scale-free organization of spatiotemporal network dynamics of spontaneous activity on the other.
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19
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Azimi Z, Barzan R, Spoida K, Surdin T, Wollenweber P, Mark MD, Herlitze S, Jancke D. Separable gain control of ongoing and evoked activity in the visual cortex by serotonergic input. eLife 2020; 9:e53552. [PMID: 32252889 PMCID: PMC7138610 DOI: 10.7554/elife.53552] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 03/04/2020] [Indexed: 01/25/2023] Open
Abstract
Controlling gain of cortical activity is essential to modulate weights between internal ongoing communication and external sensory drive. Here, we show that serotonergic input has separable suppressive effects on the gain of ongoing and evoked visual activity. We combined optogenetic stimulation of the dorsal raphe nucleus (DRN) with wide-field calcium imaging, extracellular recordings, and iontophoresis of serotonin (5-HT) receptor antagonists in the mouse visual cortex. 5-HT1A receptors promote divisive suppression of spontaneous activity, while 5-HT2A receptors act divisively on visual response gain and largely account for normalization of population responses over a range of visual contrasts in awake and anesthetized states. Thus, 5-HT input provides balanced but distinct suppressive effects on ongoing and evoked activity components across neuronal populations. Imbalanced 5-HT1A/2A activation, either through receptor-specific drug intake, genetically predisposed irregular 5-HT receptor density, or change in sensory bombardment may enhance internal broadcasts and reduce sensory drive and vice versa.
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Affiliation(s)
- Zohre Azimi
- Optical Imaging Group, Institut für Neuroinformatik, Ruhr University BochumBochumGermany
- International Graduate School of Neuroscience (IGSN), Ruhr University BochumBochumGermany
| | - Ruxandra Barzan
- Optical Imaging Group, Institut für Neuroinformatik, Ruhr University BochumBochumGermany
- International Graduate School of Neuroscience (IGSN), Ruhr University BochumBochumGermany
| | - Katharina Spoida
- Department of General Zoology and Neurobiology, Ruhr University BochumBochumGermany
| | - Tatjana Surdin
- Department of General Zoology and Neurobiology, Ruhr University BochumBochumGermany
| | - Patric Wollenweber
- Department of General Zoology and Neurobiology, Ruhr University BochumBochumGermany
| | - Melanie D Mark
- Department of General Zoology and Neurobiology, Ruhr University BochumBochumGermany
| | - Stefan Herlitze
- Department of General Zoology and Neurobiology, Ruhr University BochumBochumGermany
| | - Dirk Jancke
- Optical Imaging Group, Institut für Neuroinformatik, Ruhr University BochumBochumGermany
- International Graduate School of Neuroscience (IGSN), Ruhr University BochumBochumGermany
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20
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On the emergence of cognition: from catalytic closure to neuroglial closure. J Biol Phys 2020; 46:95-119. [PMID: 32130568 DOI: 10.1007/s10867-020-09543-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 02/12/2020] [Indexed: 10/24/2022] Open
Abstract
In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called "life"-due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions-it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.
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21
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Sadaghiani S, Wirsich J. Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches. Netw Neurosci 2020; 4:1-29. [PMID: 32043042 PMCID: PMC7006873 DOI: 10.1162/netn_a_00114] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 11/11/2019] [Indexed: 12/17/2022] Open
Abstract
The discovery of a stable, whole-brain functional connectivity organization that is largely independent of external events has drastically extended our view of human brain function. However, this discovery has been primarily based on functional magnetic resonance imaging (fMRI). The role of this whole-brain organization in fast oscillation-based connectivity as measured, for example, by electroencephalography (EEG) and magnetoencephalography (MEG) is only beginning to emerge. Here, we review studies of intrinsic connectivity and its whole-brain organization in EEG, MEG, and intracranial electrophysiology with a particular focus on direct comparisons to connectome studies in fMRI. Synthesizing this literature, we conclude that irrespective of temporal scale over four orders of magnitude, intrinsic neurophysiological connectivity shows spatial similarity to the connectivity organization commonly observed in fMRI. A shared structural connectivity basis and cross-frequency coupling are possible mechanisms contributing to this similarity. Acknowledging that a stable whole-brain organization governs long-range coupling across all timescales of neural processing motivates researchers to take "baseline" intrinsic connectivity into account when investigating brain-behavior associations, and further encourages more widespread exploration of functional connectomics approaches beyond fMRI by using EEG and MEG modalities.
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Affiliation(s)
- Sepideh Sadaghiani
- Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jonathan Wirsich
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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22
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Mathematics and the Brain: A Category Theoretical Approach to Go Beyond the Neural Correlates of Consciousness. ENTROPY 2019. [PMCID: PMC7514579 DOI: 10.3390/e21121234] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Consciousness is a central issue in neuroscience, however, we still lack a formal framework that can address the nature of the relationship between consciousness and its physical substrates. In this review, we provide a novel mathematical framework of category theory (CT), in which we can define and study the sameness between different domains of phenomena such as consciousness and its neural substrates. CT was designed and developed to deal with the relationships between various domains of phenomena. We introduce three concepts of CT which include (i) category; (ii) inclusion functor and expansion functor; and, most importantly, (iii) natural transformation between the functors. Each of these mathematical concepts is related to specific features in the neural correlates of consciousness (NCC). In this novel framework, we will examine two of the major theories of consciousness, integrated information theory (IIT) of consciousness and temporospatial theory of consciousness (TTC). We conclude that CT, especially the application of the notion of natural transformation, highlights that we need to go beyond NCC and unravels questions that need to be addressed by any future neuroscientific theory of consciousness.
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23
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Shaw SB, Dhindsa K, Reilly JP, Becker S. Capturing the Forest but Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics. Neural Comput 2019; 31:2177-2211. [DOI: 10.1162/neco_a_01229] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
The brain is known to be active even when not performing any overt cognitive tasks, and often it engages in involuntary mind wandering. This resting state has been extensively characterized in terms of fMRI-derived brain networks. However, an alternate method has recently gained popularity: EEG microstate analysis. Proponents of microstates postulate that the brain discontinuously switches between four quasi-stable states defined by specific EEG scalp topologies at peaks in the global field potential (GFP). These microstates are thought to be “atoms of thought,” involved with visual, auditory, salience, and attention processing. However, this method makes some major assumptions by excluding EEG data outside the GFP peaks and then clustering the EEG scalp topologies at the GFP peaks, assuming that only one microstate is active at any given time. This study explores the evidence surrounding these assumptions by studying the temporal dynamics of microstates and its clustering space using tools from dynamical systems analysis, fractal, and chaos theory to highlight the shortcomings in microstate analysis. The results show evidence of complex and chaotic EEG dynamics outside the GFP peaks, which is being missed by microstate analysis. Furthermore, the winner-takes-all approach of only one microstate being active at a time is found to be inadequate since the dynamic EEG scalp topology does not always resemble that of the assigned microstate, and there is competition among the different microstate classes. Finally, clustering space analysis shows that the four microstates do not cluster into four distinct and separable clusters. Taken collectively, these results show that the discontinuous description of EEG microstates is inadequate when looking at nonstationary short-scale EEG dynamics.
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Affiliation(s)
- Saurabh Bhaskar Shaw
- Neuroscience Graduate Program, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Kiret Dhindsa
- Research and High Performance Computing, McMaster University, Hamilton, ON L8S 4L8, Canada, and Vector Institute for Artificial Intelligence, Toronto, ON M5G 1M1, Canada
| | - James P. Reilly
- Vector Institute for Artificial Intelligence, Toronto, ON M5G 1M1, Canada, and Department of Electrical and Computer Engineering and McMaster School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Suzanna Becker
- Department of Psychology Neuroscience and Behaviour, McMaster University, Hamilton, ON L8S 4L8, Canada, and Vector Institute for Artificial Intelligence, Toronto, ON M5G 1M1, Canada
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24
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Perez Velazquez JL, Mateos DM, Guevara Erra R. On a Simple General Principle of Brain Organization. Front Neurosci 2019; 13:1106. [PMID: 31680839 PMCID: PMC6804438 DOI: 10.3389/fnins.2019.01106] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 10/01/2019] [Indexed: 12/27/2022] Open
Abstract
A possible framework to characterize nervous system dynamics and its organization in conscious and unconscious states is introduced, derived from a high level perspective on the coordinated activity of brain cell ensembles. Some questions are best addressable in a global framework and here we build on past observations about the structure of configurations of brain networks in conscious and unconscious states and about neurophysiological results. Aiming to bind some results together into some sort of coherence with a central theme, the scenario that emerges underscores the crucial importance of the creation and dissipation of energy gradients in brain cellular ensembles resulting in maximization of the configurations in the functional connectivity among those networks that favor conscious awareness and healthy conditions. These considerations are then applied to indicate approaches that can be used to improve neuropathological syndromes.
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Affiliation(s)
| | - Diego M. Mateos
- Instituto de Matemática Aplicada del Litoral–CONICET–UNL, CCT CONICET, Santa Fe, Argentina
- Facultad de Ciencia y Tecnología, Universidad Autónoma de Entre Ríos, Entre Ríos, Argentina
| | - Ramon Guevara Erra
- Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Sorbonne Paris Cité, Paris, France
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25
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Parker DB, Razlighi QR. Task-evoked Negative BOLD Response and Functional Connectivity in the Default Mode Network are Representative of Two Overlapping but Separate Neurophysiological Processes. Sci Rep 2019; 9:14473. [PMID: 31597927 PMCID: PMC6785640 DOI: 10.1038/s41598-019-50483-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 08/30/2019] [Indexed: 01/21/2023] Open
Abstract
The topography of the default mode network (DMN) can be obtained with one of two different functional magnetic resonance imaging (fMRI) methods: either from the spontaneous but organized synchrony of the low-frequency fluctuations in resting-state fMRI (rs-fMRI), known as "functional connectivity", or from the consistent and robust deactivations in task-based fMRI (tb-fMRI), here referred to as the "negative BOLD response" (NBR). These two methods are fundamentally different, but their results are often used interchangeably to describe the brain's resting-state, baseline, or intrinsic activity. While the DMN was initially defined by consistent task-based decreases in blood flow in a set of specific brain regions using PET imaging, recently nearly all studies on the DMN employ functional connectivity in rs-fMRI. In this study, we first show the high level of spatial overlap between NBR and functional connectivity of the DMN extracted from the same tb-fMRI scan; then, we demonstrate that the NBR in putative DMN regions can be significantly altered without causing any change in their overlapping functional connectivity. Furthermore, we present evidence that in the DMN, the NBR is more closely related to task performance than the functional connectivity. We conclude that the NBR and functional connectivity of the DMN reflect two separate but overlapping neurophysiological processes, and thus should be differentiated in studies investigating brain-behavior relationships in both healthy and diseased populations. Our findings further raise the possibility that the macro-scale networks of the human brain might internally exhibit a hierarchical functional architecture.
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Affiliation(s)
- David B Parker
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Qolamreza R Razlighi
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA.
- Department of Neurology, College of Physicians and Surgeons, Columbia University Medial Center, New York, NY, 10032, USA.
- Taub Institute for research on Alzheimer's disease and the aging brain, Columbia University Medical Center, New York, NY, 10032, USA.
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26
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Goetz SM, Alavi SMM, Deng ZD, Peterchev AV. Statistical Model of Motor-Evoked Potentials. IEEE Trans Neural Syst Rehabil Eng 2019; 27:1539-1545. [PMID: 31283508 DOI: 10.1109/tnsre.2019.2926543] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Motor-evoked potentials (MEPs) are widely used for biomarkers and dose individualization in transcranial stimulation. The large variability of MEPs requires sophisticated methods of analysis to extract information fast and correctly. Development and testing of such methods relies on the availability for realistic models of MEP generation, which are presently lacking. This paper presents a statistical model that can simulate long sequences of individualized MEP amplitude data with properties matching experimental observations. The MEP model includes three sources of trial-to-trial variability: excitability fluctuations, variability in the neural and muscular pathways, and physiological and measurement noise. It also generates virtual human subject data from statistics of population variability. All parameters are extracted as statistical distributions from experimental data from the literature. The model exhibits previously described features, such as stimulus-intensity-dependent MEP amplitude distributions, including bimodal ones. The model can generate long sequences of test data for individual subjects with specified parameters or for subjects from a virtual population. The presented MEP model is the most detailed to date and can be used for the development and implementation of dosing and biomarker estimation algorithms for transcranial stimulation.
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27
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Li Q, Liu G, Yuan G, Wang G, Wu Z, Zhao X. DC Shifts-fMRI: A Supplement to Event-Related fMRI. Front Comput Neurosci 2019; 13:37. [PMID: 31244636 PMCID: PMC6581730 DOI: 10.3389/fncom.2019.00037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Accepted: 05/21/2019] [Indexed: 11/13/2022] Open
Abstract
Event-related fMRI have been widely used in locating brain regions which respond to specific tasks. However, activities of brain regions which modulate or indirectly participate in the response to a specific task are not event-related. Event-related fMRI can't locate these regulatory regions, detrimental to the integrity of the result that event-related fMRI revealed. Direct-current EEG shifts (DC shifts) have been found linked to the inner brain activity, a fusion DC shifts-fMRI method may have the ability to reveal a more complete response of the brain. In this study, we used DC shifts-fMRI to verify that even when responding to a very simple task, (1) The response of the brain is more complicated than event-related fMRI generally revealed and (2) DC shifts-fMRI have the ability of revealing brain regions whose responses are not in event-related way. We used a classical and simple paradigm which is often used in auditory cortex tonotopic mapping. Data were recorded from 50 subjects (25 male, 25 female) who were presented with randomly presented pure tone sequences with six different frequencies (200, 400, 800, 1,600, 3,200, 6,400 Hz). Our traditional fMRI results are consistent with previous findings that the activations are concentrated on the auditory cortex. Our DC shifts-fMRI results showed that the cingulate-caudate-thalamus network which underpins sustained attention is positively activated while the dorsal attention network and the right middle frontal gyrus which underpin attention orientation are negatively activated. The regional-specific correlations between DC shifts and brain networks indicate the complexity of the response of the brain even to a simple task and that the DC shifts can effectively reflect these non-event-related inner brain activities.
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Affiliation(s)
- Qiang Li
- Education Science College, Guizhou Normal College, Guiyang, China
| | - Guangyuan Liu
- College of Electronic and Information Engineering, Southwest University, Chongqing, China.,Chongqing Collaborative Innovation Center for Brain Science, Southwest University, Chongqing, China
| | - Guangjie Yuan
- College of Electronic and Information Engineering, Southwest University, Chongqing, China
| | - Gaoyuan Wang
- College of Music, Southwest University, Chongqing, China
| | - Zonghui Wu
- Southwest University Hospital, Southwest University, Chongqing, China
| | - Xingcong Zhao
- College of Electronic and Information Engineering, Southwest University, Chongqing, China
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28
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Large-scale intrinsic connectivity is consistent across varying task demands. PLoS One 2019; 14:e0213861. [PMID: 30970031 PMCID: PMC6457563 DOI: 10.1371/journal.pone.0213861] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 03/02/2019] [Indexed: 01/02/2023] Open
Abstract
Measuring whole-brain functional connectivity patterns based on task-free (‘resting-state’) spontaneous fluctuations in the functional MRI (fMRI) signal is a standard approach to probing habitual brain states, independent of task-specific context. This view is supported by spatial correspondence between task- and rest-derived connectivity networks. Yet, it remains unclear whether intrinsic connectivity observed in a resting-state acquisition is persistent during task. Here, we sought to determine how changes in ongoing brain activation, elicited by task performance, impact the integrity of whole-brain functional connectivity patterns (commonly termed ‘resting state networks’). We employed a ‘steady-states’ paradigm, in which participants continuously executed a specific task (without baseline periods). Participants underwent separate task-based (visual, motor and visuomotor) or task-free (resting) steady-state scans, each performed over a 5-minute period. This unique design allowed us to apply a set of traditional resting-state analyses to various task-states. In addition, a classical fMRI block-design was employed to identify individualized brain activation patterns for each task, allowing us to characterize how differing activation patterns across the steady-states impact whole-brain intrinsic connectivity patterns. By examining correlations across segregated brain regions (nodes) and the whole brain (using independent component analysis) using standard resting-state functional connectivity (FC) analysis, we show that the whole-brain network architecture characteristic of the resting-state is comparable across different steady-task states, despite striking inter-task changes in brain activation (signal amplitude). Changes in functional connectivity were detected locally, within the active networks. But to identify these local changes, the contributions of different FC networks to the global intrinsic connectivity pattern had to be isolated. Together, we show that intrinsic connectivity underlying the canonical resting-state networks is relatively stable even when participants are engaged in different tasks and is not limited to the resting-state.
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29
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Boon LI, Geraedts VJ, Hillebrand A, Tannemaat MR, Contarino MF, Stam CJ, Berendse HW. A systematic review of MEG-based studies in Parkinson's disease: The motor system and beyond. Hum Brain Mapp 2019; 40:2827-2848. [PMID: 30843285 PMCID: PMC6594068 DOI: 10.1002/hbm.24562] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 01/27/2019] [Accepted: 02/13/2019] [Indexed: 01/29/2023] Open
Abstract
Parkinson's disease (PD) is accompanied by functional changes throughout the brain, including changes in the electromagnetic activity recorded with magnetoencephalography (MEG). An integrated overview of these changes, its relationship with clinical symptoms, and the influence of treatment is currently missing. Therefore, we systematically reviewed the MEG studies that have examined oscillatory activity and functional connectivity in the PD‐affected brain. The available articles could be separated into motor network‐focused and whole‐brain focused studies. Motor network studies revealed PD‐related changes in beta band (13–30 Hz) neurophysiological activity within and between several of its components, although it remains elusive to what extent these changes underlie clinical motor symptoms. In whole‐brain studies PD‐related oscillatory slowing and decrease in functional connectivity correlated with cognitive decline and less strongly with other markers of disease progression. Both approaches offer a different perspective on PD‐specific disease mechanisms and could therefore complement each other. Combining the merits of both approaches will improve the setup and interpretation of future studies, which is essential for a better understanding of the disease process itself and the pathophysiological mechanisms underlying specific PD symptoms, as well as for the potential to use MEG in clinical care.
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Affiliation(s)
- Lennard I Boon
- Amsterdam UMC, location VUmc, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Victor J Geraedts
- Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Arjan Hillebrand
- Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Martijn R Tannemaat
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Maria Fiorella Contarino
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.,Department of Neurology, Haga Teaching Hospital, The Hague, The Netherlands
| | - Cornelis J Stam
- Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Henk W Berendse
- Amsterdam UMC, location VUmc, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
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30
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Barik K, Daimi SN, Jones R, Bhattacharya J, Saha G. A machine learning approach to predict perceptual decisions: an insight into face pareidolia. Brain Inform 2019; 6:2. [PMID: 30721365 PMCID: PMC6363645 DOI: 10.1186/s40708-019-0094-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2018] [Accepted: 01/17/2019] [Indexed: 11/21/2022] Open
Abstract
The perception of an external stimulus not only depends upon the characteristics of the stimulus but is also influenced by the ongoing brain activity prior to its presentation. In this work, we directly tested whether spontaneous electrical brain activities in prestimulus period could predict perceptual outcome in face pareidolia (visualizing face in noise images) on a trial-by-trial basis. Participants were presented with only noise images but with the prior information that some faces would be hidden in these images, while their electrical brain activities were recorded; participants reported their perceptual decision, face or no-face, on each trial. Using differential hemispheric asymmetry features based on large-scale neural oscillations in a machine learning classifier, we demonstrated that prestimulus brain activities could achieve a classification accuracy, discriminating face from no-face perception, of 75% across trials. The time–frequency features representing hemispheric asymmetry yielded the best classification performance, and prestimulus alpha oscillations were found to be mostly involved in predicting perceptual decision. These findings suggest a mechanism of how prior expectations in the prestimulus period may affect post-stimulus decision making.
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Affiliation(s)
- Kasturi Barik
- Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur, India.
| | - Syed Naser Daimi
- Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur, India
| | - Rhiannon Jones
- Department of Psychology, University of Winchester, Winchester, UK
| | | | - Goutam Saha
- Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur, India
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31
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Affiliation(s)
- Til O Bergmann
- Department of Neurology and Stroke, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,Deutsches Resilienz Zentrum, University Medical Center Mainz, Mainz, Germany
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32
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Castellazzi G, Bruno SD, Toosy AT, Casiraghi L, Palesi F, Savini G, D'Angelo E, Wheeler-Kingshott CAMG. Prominent Changes in Cerebro-Cerebellar Functional Connectivity During Continuous Cognitive Processing. Front Cell Neurosci 2018; 12:331. [PMID: 30327590 PMCID: PMC6174227 DOI: 10.3389/fncel.2018.00331] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 09/10/2018] [Indexed: 01/07/2023] Open
Abstract
While task-dependent responses of specific brain areas during cognitive tasks are well established, much less is known about the changes occurring in resting state networks (RSNs) in relation to continuous cognitive processing. In particular, the functional involvement of cerebro-cerebellar loops connecting the posterior cerebellum to associative cortices, remains unclear. In this study, 22 healthy volunteers underwent a multi-session functional magnetic resonance imaging (fMRI) protocol composed of four consecutive 8-min resting state fMRI (rs-fMRI) scans. After a first control scan, participants listened to a narrated story for the entire duration of the second rs-fMRI scan; two further rs-fMRI scans followed the end of story listening. The story plot was purposely designed to stimulate specific cognitive processes that are known to involve the cerebro-cerebellar loops. Almost all of the identified 15 RSNs showed changes in functional connectivity (FC) during and for several minutes after the story. The FC changes mainly occurred in the frontal and prefrontal cortices and in the posterior cerebellum, especially in Crus I-II and lobule VI. The FC changes occurred in cerebellar clusters belonging to different RSNs, including the cerebellar network (CBLN), sensory networks (lateral visual network, LVN; medial visual network, MVN) and cognitive networks (default mode network, DMN; executive control network, ECN; right and left ventral attention networks, RVAN and LVAN; salience network, SN; language network, LN; and working memory network, WMN). Interestingly, a k-means analysis of FC changes revealed clustering of FCN, ECN, and WMN, which are all involved in working memory functions, CBLN, DMN, and SN, which play a key-role in attention switching, and RSNs involved in visual imagery. These results show that the cerebellum is deeply entrained in well-structured network clusters, which reflect multiple aspects of cognitive processing, during and beyond the conclusion of auditory stimulation.
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Affiliation(s)
- Gloria Castellazzi
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, Institute of Neurology, University College London, London, United Kingdom.,Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.,Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Stefania D Bruno
- Blackheath Brain Injury Rehabilitation Centre, London, United Kingdom
| | - Ahmed T Toosy
- NMR Research Unit, Department of Brain Repair and Rehabilitation, Queen Square MS Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Letizia Casiraghi
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Fulvia Palesi
- Brain MRI 3T Center, Neuroradiology Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Giovanni Savini
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Physics, University of Milan, Milan, Italy
| | - Egidio D'Angelo
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Claudia Angela Michela Gandini Wheeler-Kingshott
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, Institute of Neurology, University College London, London, United Kingdom.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Brain MRI 3T Center, IRCCS Mondino Foundation, Pavia, Italy
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33
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Wollman I, Morillon B. Organizational principles of multidimensional predictions in human auditory attention. Sci Rep 2018; 8:13466. [PMID: 30194376 PMCID: PMC6128843 DOI: 10.1038/s41598-018-31878-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 08/17/2018] [Indexed: 11/09/2022] Open
Abstract
Anticipating the future rests upon our ability to exploit contextual cues and to formulate valid internal models or predictions. It is currently unknown how multiple predictions combine to bias perceptual information processing, and in particular whether this is determined by physiological constraints, behavioral relevance (task demands), or past knowledge (perceptual expertise). In a series of behavioral auditory experiments involving musical experts and non-musicians, we investigated the respective and combined contribution of temporal and spectral predictions in multiple detection tasks. We show that temporal and spectral predictions alone systematically increase perceptual sensitivity, independently of task demands or expertise. When combined, however, spectral predictions benefit more to non-musicians and dominate over temporal ones, and the extent of the spectrotemporal synergistic interaction depends on task demands. This suggests that the hierarchy of dominance primarily reflects the tonotopic organization of the auditory system and that expertise or attention only have a secondary modulatory influence.
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Affiliation(s)
- Indiana Wollman
- Montreal Neurological Institute, McGill University, Montreal, Canada
- CIRMMT, Schulich School of Music, McGill University, Montreal, Canada
| | - Benjamin Morillon
- Montreal Neurological Institute, McGill University, Montreal, Canada.
- Aix Marseille Univ, Inserm, INS, Inst Neurosci Syst, Marseille, France.
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34
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Jie B, Liu M, Shen D. Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease. Med Image Anal 2018; 47:81-94. [PMID: 29702414 PMCID: PMC5986611 DOI: 10.1016/j.media.2018.03.013] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 01/06/2018] [Accepted: 03/26/2018] [Indexed: 12/30/2022]
Abstract
Functional connectivity networks (FCNs) using resting-state functional magnetic resonance imaging (rs-fMRI) have been applied to the analysis and diagnosis of brain disease, such as Alzheimer's disease (AD) and its prodrome, i.e., mild cognitive impairment (MCI). Different from conventional studies focusing on static descriptions on functional connectivity (FC) between brain regions in rs-fMRI, recent studies have resorted to dynamic connectivity networks (DCNs) to characterize the dynamic changes of FC, since dynamic changes of FC may indicate changes in macroscopic neural activity patterns in cognitive and behavioral aspects. However, most of the existing studies only investigate the temporal properties of DCNs (e.g., temporal variability of FC between specific brain regions), ignoring the important spatial properties of the network (e.g., spatial variability of FC associated with a specific brain region). Also, emerging evidence on FCNs has suggested that, besides temporal variability, there is significant spatial variability of activity foci over time. Hence, integrating both temporal and spatial properties of DCNs can intuitively promote the performance of connectivity-network-based learning methods. In this paper, we first define a new measure to characterize the spatial variability of DCNs, and then propose a novel learning framework to integrate both temporal and spatial variabilities of DCNs for automatic brain disease diagnosis. Specifically, we first construct DCNs from the rs-fMRI time series at successive non-overlapping time windows. Then, we characterize the spatial variability of a specific brain region by computing the correlation of functional sequences (i.e., the changing profile of FC between a pair of brain regions within all time windows) associated with this region. Furthermore, we extract both temporal variabilities and spatial variabilities from DCNs as features, and integrate them for classification by using manifold regularized multi-task feature learning and multi-kernel learning techniques. Results on 149 subjects with baseline rs-fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) suggest that our method can not only improve the classification performance in comparison with state-of-the-art methods, but also provide insights into the spatio-temporal interaction patterns of brain activity and their changes in brain disorders.
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Affiliation(s)
- Biao Jie
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA; Department of Computer Science and Technology, Anhui Normal University, Anhui 241003, China.
| | - Mingxia Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA.
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA; Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
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35
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Borchardt V, Surova G, van der Meer J, Bola M, Frommer J, Leutritz AL, Sweeney‐Reed CM, Buchheim A, Strauß B, Nolte T, Olbrich S, Walter M. Exposure to attachment narratives dynamically modulates cortical arousal during the resting state in the listener. Brain Behav 2018; 8:e01007. [PMID: 29877060 PMCID: PMC6043700 DOI: 10.1002/brb3.1007] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 04/14/2018] [Accepted: 04/20/2018] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Affective stimulation entails changes in brain network patterns at rest, but it is unknown whether exogenous emotional stimulation has a prolonged effect on the temporal dynamics of endogenous cortical arousal. We therefore investigated differences in cortical arousal in the listener following stimulation with different attachment-related narratives. METHODS Resting-state EEG was recorded from sixteen healthy subjects for ten minutes each with eyes closed: first at baseline and then after passively listening to three affective narratives from strangers about their early childhood experiences (prototypical for insecure-dismissing, insecure-preoccupied, and secure attachment). Using the VIGALL 2.1 algorithm, low or high vigilance stages in consecutive EEG segments were classified, and their dynamic profile was analyzed. Questionnaires assessed the listeners' emotional response to the content of the narrative. RESULTS As a general effect of preceding affective stimulation, vigilance following the stimulation was significantly elevated compared to baseline rest, and carryover effects in dynamic vigilance profiles were observed. A difference between narrative conditions was revealed for the insecure-dismissing condition, in which the decrease in duration of high vigilance stages was fastest compared to the other two conditions. The behavioral data supported the observation that especially the insecure narratives induced a tendency in the listener to affectively disengage from the narrative content. DISCUSSION This study revealed carryover effects in endogenous cortical arousal evoked by preceding affective stimulation and provides evidence for attachment-specific dynamic alterations of brain states and individual differences in emotional reactivity.
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Affiliation(s)
- Viola Borchardt
- Clinical Affective Neuroimaging LaboratoryMagdeburgGermany
- Department of Behavioral NeurologyLeibniz Institute for NeurobiologyMagdeburgGermany
| | - Galina Surova
- Clinical Affective Neuroimaging LaboratoryMagdeburgGermany
- Clinic for Psychiatry and PsychotherapyUniversity of LeipzigLeipzigGermany
| | | | - Michał Bola
- Laboratory of Brain ImagingNeurobiology CenterNencki Institute of Experimental Biology of Polish Academy of SciencesWarsawPoland
| | - Jörg Frommer
- Clinic for Psychosomatic Medicine and PsychotherapyUniversity Clinic MagdeburgMagdeburgGermany
| | - Anna Linda Leutritz
- Clinical Affective Neuroimaging LaboratoryMagdeburgGermany
- Clinic for Psychiatry and PsychotherapyOtto von Guericke University MagdeburgMagdeburgGermany
| | - Catherine M. Sweeney‐Reed
- Neurocybernetics and RehabilitationDepartment of Neurology and Stereotactic NeurosurgeryOtto von Guericke UniversityMagdeburgGermany
| | - Anna Buchheim
- Institute of PsychologyUniversity of InnsbruckInnsbruckAustria
| | - Bernhard Strauß
- Institute of Psychosocial Medicine and PsychotherapyUniversity Hospital JenaJenaGermany
| | - Tobias Nolte
- Anna Freud National Centre for Children And FamiliesLondonUK
- Wellcome Trust Centre for NeuroimagingUniversity College of LondonLondonUK
| | - Sebastian Olbrich
- Clinic for Psychiatry and PsychotherapyUniversity of LeipzigLeipzigGermany
- Clinic for Psychiatry, Psychotherapy and PsychosomaticUniversity Clinic ZurichZurichSwitzerland
| | - Martin Walter
- Clinical Affective Neuroimaging LaboratoryMagdeburgGermany
- Department of Behavioral NeurologyLeibniz Institute for NeurobiologyMagdeburgGermany
- Clinic for Psychiatry and PsychotherapyEberhard‐Karls UniversityTuebingenGermany
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36
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Abstract
Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.
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Affiliation(s)
- Bin He
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA;
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Emery Brown
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Zhongming Liu
- Weldon School of Biomedical Engineering, School of Electrical and Computer Engineering, and Purdue Institute of Integrative Neuroscience, Purdue University, West Lafayette, Indiana 47906, USA
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37
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Cordani L, Tagliazucchi E, Vetter C, Hassemer C, Roenneberg T, Stehle JH, Kell CA. Endogenous modulation of human visual cortex activity improves perception at twilight. Nat Commun 2018; 9:1274. [PMID: 29636448 PMCID: PMC5893589 DOI: 10.1038/s41467-018-03660-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Accepted: 03/01/2018] [Indexed: 11/09/2022] Open
Abstract
Perception, particularly in the visual domain, is drastically influenced by rhythmic changes in ambient lighting conditions. Anticipation of daylight changes by the circadian system is critical for survival. However, the neural bases of time-of-day-dependent modulation in human perception are not yet understood. We used fMRI to study brain dynamics during resting-state and close-to-threshold visual perception repeatedly at six times of the day. Here we report that resting-state signal variance drops endogenously at times coinciding with dawn and dusk, notably in sensory cortices only. In parallel, perception-related signal variance in visual cortices decreases and correlates negatively with detection performance, identifying an anticipatory mechanism that compensates for the deteriorated visual signal quality at dawn and dusk. Generally, our findings imply that decreases in spontaneous neural activity improve close-to-threshold perception.
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Affiliation(s)
- Lorenzo Cordani
- Cognitive Neuroscience Group, Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany.,Department of Neurology, Goethe University, 60528, Frankfurt am Main, Germany
| | - Enzo Tagliazucchi
- Cognitive Neuroscience Group, Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany.,Brain and Spine Institute, Hôpital Pitié Salpêtrière, 75013, Paris, France.,Departamento de Física, Instituto de Física de Buenos Aires-CONICET, Buenos Aires, 1428, Argentina
| | - Céline Vetter
- Department of Integrative Physiology, University of Colorado, Boulder, CO, 80310, USA.,Institute of Medical Psychology, Ludwig Maximilian University, 80336, Munich, Germany
| | - Christian Hassemer
- Cognitive Neuroscience Group, Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany.,Institute of Anatomy III, Goethe University, 60590, Frankfurt am Main, Germany
| | - Till Roenneberg
- Institute of Medical Psychology, Ludwig Maximilian University, 80336, Munich, Germany
| | - Jörg H Stehle
- Institute of Anatomy III, Goethe University, 60590, Frankfurt am Main, Germany
| | - Christian A Kell
- Cognitive Neuroscience Group, Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany. .,Department of Neurology, Goethe University, 60528, Frankfurt am Main, Germany.
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38
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Brodski-Guerniero A, Naumer MJ, Moliadze V, Chan J, Althen H, Ferreira-Santos F, Lizier JT, Schlitt S, Kitzerow J, Schütz M, Langer A, Kaiser J, Freitag CM, Wibral M. Predictable information in neural signals during resting state is reduced in autism spectrum disorder. Hum Brain Mapp 2018; 39:3227-3240. [PMID: 29617056 DOI: 10.1002/hbm.24072] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 03/20/2018] [Accepted: 03/25/2018] [Indexed: 11/12/2022] Open
Abstract
The neurophysiological underpinnings of the nonsocial symptoms of autism spectrum disorder (ASD) which include sensory and perceptual atypicalities remain poorly understood. Well-known accounts of less dominant top-down influences and more dominant bottom-up processes compete to explain these characteristics. These accounts have been recently embedded in the popular framework of predictive coding theory. To differentiate between competing accounts, we studied altered information dynamics in ASD by quantifying predictable information in neural signals. Predictable information in neural signals measures the amount of stored information that is used for the next time step of a neural process. Thus, predictable information limits the (prior) information which might be available for other brain areas, for example, to build predictions for upcoming sensory information. We studied predictable information in neural signals based on resting-state magnetoencephalography (MEG) recordings of 19 ASD patients and 19 neurotypical controls aged between 14 and 27 years. Using whole-brain beamformer source analysis, we found reduced predictable information in ASD patients across the whole brain, but in particular in posterior regions of the default mode network. In these regions, epoch-by-epoch predictable information was positively correlated with source power in the alpha and beta frequency range as well as autocorrelation decay time. Predictable information in precuneus and cerebellum was negatively associated with nonsocial symptom severity, indicating a relevance of the analysis of predictable information for clinical research in ASD. Our findings are compatible with the assumption that use or precision of prior knowledge is reduced in ASD patients.
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Affiliation(s)
| | - Marcus J Naumer
- Institute of Medical Psychology, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany
| | - Vera Moliadze
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany.,Department of Medical Psychology and Medical Sociology, Schleswig-Holstein University Hospital (UKSH), Christian-Albrechts-University, Kiel, Germany
| | - Jason Chan
- Institute of Medical Psychology, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany.,Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany.,School of Applied Psychology, University College Cork, Cork, Ireland
| | - Heike Althen
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Fernando Ferreira-Santos
- Laboratory of Neuropsychophysiology, Faculty of Psychology and Education Sciences, University of Porto, Porto, Portugal
| | - Joseph T Lizier
- Complex Systems Research Group and Centre for Complex Systems, Faculty of Engineering & IT, The University of Sydney, New South Wales, 2006, Australia
| | - Sabine Schlitt
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Janina Kitzerow
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Magdalena Schütz
- Institute of Medical Psychology, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany.,Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Anne Langer
- Institute of Medical Psychology, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany.,Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Jochen Kaiser
- Institute of Medical Psychology, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Michael Wibral
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
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39
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Bolt T, Anderson ML, Uddin LQ. Beyond the evoked/intrinsic neural process dichotomy. Netw Neurosci 2018; 2:1-22. [PMID: 29911670 PMCID: PMC5989985 DOI: 10.1162/netn_a_00028] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2017] [Accepted: 09/28/2017] [Indexed: 01/20/2023] Open
Abstract
Contemporary functional neuroimaging research has increasingly focused on characterization of intrinsic or "spontaneous" brain activity. Analysis of intrinsic activity is often contrasted with analysis of task-evoked activity that has traditionally been the focus of cognitive neuroscience. But does this evoked/intrinsic dichotomy adequately characterize human brain function? Based on empirical data demonstrating a close functional interdependence between intrinsic and task-evoked activity, we argue that the dichotomy between intrinsic and task-evoked activity as unobserved contributions to brain activity is artificial. We present an alternative picture of brain function in which the brain's spatiotemporal dynamics do not consist of separable intrinsic and task-evoked components, but reflect the enaction of a system of mutual constraints to move the brain into and out of task-appropriate functional configurations. According to this alternative picture, cognitive neuroscientists are tasked with describing both the temporal trajectory of brain activity patterns across time, and the modulation of this trajectory by task states, without separating this process into intrinsic and task-evoked components. We argue that this alternative picture of brain function is best captured in a novel explanatory framework called enabling constraint. Overall, these insights call for a reconceptualization of functional brain activity, and should drive future methodological and empirical efforts.
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Affiliation(s)
- Taylor Bolt
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Michael L. Anderson
- Department of Philosophy and Brain and Mind Institute, Western University, London, ON, Canada
- Institute for Advanced Computer Studies, Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA
| | - Lucina Q. Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, USA
- Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA
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40
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Honey CJ, Newman EL, Schapiro AC. Switching between internal and external modes: A multiscale learning principle. Netw Neurosci 2017; 1:339-356. [PMID: 30090870 PMCID: PMC6063714 DOI: 10.1162/netn_a_00024] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Accepted: 08/18/2017] [Indexed: 01/21/2023] Open
Abstract
Brains construct internal models that support perception, prediction, and action in the external world. Individual circuits within a brain also learn internal models of the local world of input they receive, in order to facilitate efficient and robust representation. How are these internal models learned? We propose that learning is facilitated by continual switching between internally biased and externally biased modes of processing. We review computational evidence that this mode-switching can produce an error signal to drive learning. We then consider empirical evidence for the instantiation of mode-switching in diverse neural systems, ranging from subsecond fluctuations in the hippocampus to wake-sleep alternations across the whole brain. We hypothesize that these internal/external switching processes, which occur at multiple scales, can drive learning at each scale. This framework predicts that (a) slower mode-switching should be associated with learning of more temporally extended input features and (b) disruption of switching should impair the integration of new information with prior information.
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Affiliation(s)
- Christopher J. Honey
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Ehren L. Newman
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Anna C. Schapiro
- Department of Psychiatry, Beth Israel Deaconess Medical Center / Harvard Medical School, Boston, MA, USA
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41
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Yousefi B, Shin J, Schumacher EH, Keilholz SD. Quasi-periodic patterns of intrinsic brain activity in individuals and their relationship to global signal. Neuroimage 2017; 167:297-308. [PMID: 29175200 DOI: 10.1016/j.neuroimage.2017.11.043] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Revised: 11/17/2017] [Accepted: 11/20/2017] [Indexed: 12/14/2022] Open
Abstract
Quasiperiodic patterns (QPPs) as reported by Majeed et al., 2011 are prominent features of the brain's intrinsic activity that involve important large-scale networks (default mode, DMN; task positive, TPN) and are likely to be major contributors to widely used measures of functional connectivity. We examined the variability of these patterns in 470 individuals from the Human Connectome Project resting state functional MRI dataset. The QPPs from individuals can be coarsely categorized into two types: one where strong anti-correlation between the DMN and TPN is present, and another where most areas are strongly correlated. QPP type could be predicted by an individual's global signal, with lower global signal corresponding to QPPs with strong anti-correlation. After regression of global signal, all QPPs showed strong anti-correlation between DMN and TPN. QPP occurrence and type was similar between a subgroup of individuals with extremely low motion and the rest of the sample, which shows that motion is not a major contributor to the QPPs. After regression of estimates of slow respiratory and cardiac induced signal fluctuations, more QPPs showed strong anti-correlation between DMN and TPN, an indication that while physiological noise influences the QPP type, it is not the primary source of the QPP itself. QPPs were more similar for the same subjects scanned on different days than for different subjects. These results provide the first assessment of the variability in individual QPPs and their relationship to physiological parameters.
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Affiliation(s)
- Behnaz Yousefi
- Biomedical Engineering, Emory University/Georgia Institute of Technology, 1760 Haygood Dr, HSRB W200, Atlanta, GA 30322, United States.
| | - Jaemin Shin
- Center for Advanced Brain Imaging, Georgia Institute of Technology, 831 Marietta St NW, Atlanta, GA 30318, United States.
| | - Eric H Schumacher
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, JS Coon Bldg R224, Atlanta, GA 30332, United States.
| | - Shella D Keilholz
- Biomedical Engineering, Emory University/Georgia Institute of Technology, 1760 Haygood Dr, HSRB W200, Atlanta, GA 30322, United States.
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Alpha Oscillations Reduce Temporal Long-Range Dependence in Spontaneous Human Brain Activity. J Neurosci 2017; 38:755-764. [PMID: 29167403 DOI: 10.1523/jneurosci.0831-17.2017] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 10/18/2017] [Accepted: 11/12/2017] [Indexed: 01/26/2023] Open
Abstract
Ongoing neural dynamics comprise both frequency-specific oscillations and broadband-features, such as long-range dependence (LRD). Despite both being behaviorally relevant, little is known about their potential interactions. In humans, 8-12 Hz α oscillations constitute the strongest deviation from 1/f power-law scaling, the signature of LRD. We postulated that α oscillations, believed to exert active inhibitory gating, downmodulate the temporal width of LRD in slower ongoing brain activity. In two independent "resting-state" datasets (electroencephalography surface recordings and magnetoencephalography source reconstructions), both across space and dynamically over time, power of α activity covaried with the power slope <5 Hz (i.e., greater α activity shortened LRD). Causality of α activity dynamics was implied by its temporal precedence over changes of slope. A model where power-law fluctuations of the α envelope inhibit baseline activity closely replicated our results. Thus, α oscillations may provide an active control mechanism to adaptively regulate LRD of brain activity at slow temporal scales, thereby shaping internal states and cognitive processes.SIGNIFICANCE STATEMENT The two prominent features of ongoing brain activity are oscillations and temporal long-range dependence. Both shape behavioral performance, but little is known about their interaction. Here, we demonstrate such an interaction in EEG and MEG recordings of task-free human brain activity. Specifically, we show that spontaneous dynamics in alpha activity explain ensuing variations of dependence in the low and ultra-low-frequency range. In modeling, two features of alpha oscillations are critical to account for the observed effects on long-range dependence, scale-free properties of alpha oscillations themselves, and a modulation of baseline levels, presumably inhibitory. Both these properties have been observed empirically, and our study hence establishes alpha oscillations as a regulatory mechanism governing long-range dependence or "memory" in slow ongoing brain activity.
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43
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Meehan TP, Bressler SL, Tang W, Astafiev SV, Sylvester CM, Shulman GL, Corbetta M. Top-down cortical interactions in visuospatial attention. Brain Struct Funct 2017; 222:3127-3145. [PMID: 28321551 PMCID: PMC5607080 DOI: 10.1007/s00429-017-1390-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 02/23/2017] [Indexed: 01/08/2023]
Abstract
The voluntary allocation of visuospatial attention depends upon top-down influences from the frontal eye field (FEF) and intraparietal sulcus (IPS)-the core regions of the dorsal attention network (DAN)-to visual occipital cortex (VOC), and has been further associated with within-DAN influences, particularly from the FEF to IPS. However, the degree to which these influences manifest at rest and are then modulated during anticipatory visuospatial attention tasks remains poorly understood. Here, we measured both undirected and directed functional connectivity (UFC, DFC) between the FEF, IPS, and VOC at rest and during an anticipatory visuospatial attention task, using a slow event-related design. Whereas the comparison between rest and task indicated FC modulations that persisted throughout the task duration, the large number of task trials we collected further enabled us to measure shorter timescale modulations of FC across the trial. Relative to rest, task engagement induced enhancement of both top-down influences from the DAN to VOC, as well as bidirectional influences between the FEF and IPS. These results suggest that task performance induces enhanced interaction within the DAN and a greater top-down influence on VOC. While resting FC generally showed right hemisphere dominance, task-related enhancement favored the left hemisphere, effectively balancing a resting hemispheric asymmetry, particularly within the DAN. On a shorter (within-trial) timescale, VOC-to-DAN and bidirectional FEF-IPS influences were transiently elevated during the anticipatory period of the trial, evincing phasic modulations related to changing attentional demands. In contrast to these task-specific effects, resting and task-related influence patterns were highly correlated, suggesting a predisposing role for resting organization, which requires minimal tonic and phasic modulations for control of visuospatial attention.
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Affiliation(s)
- Timothy P Meehan
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Steven L Bressler
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
- Department of Psychology, Florida Atlantic University, Boca Raton, FL, 33431, USA.
| | - Wei Tang
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA
| | - Serguei V Astafiev
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Maurizio Corbetta
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Neurobiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
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44
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Northoff G. Personal Identity and Cortical Midline Structure (CMS): Do Temporal Features of CMS Neural Activity Transform Into “Self-Continuity”? PSYCHOLOGICAL INQUIRY 2017. [DOI: 10.1080/1047840x.2017.1337396] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Georg Northoff
- Mental Health Centre, Zhejiang University School of Medicine, Hangzhou, China
- Institute of Mental Health Research, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
- Centre for Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- College for Humanities and Medicine, Taipei Medical University, Taipei, Taiwan
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45
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Prestimulus Theta Oscillations and Connectivity Modulate Pain Perception. J Neurosci 2017; 36:5026-33. [PMID: 27147655 DOI: 10.1523/jneurosci.3325-15.2016] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2015] [Accepted: 03/18/2016] [Indexed: 11/21/2022] Open
Abstract
UNLABELLED The perception of pain is strongly influenced by cognitive processes, such as expectations toward the efficacy of pain medication. It is reasonable to assume that such processes, among other sources of fluctuation, are reflected in ongoing brain activity, which in turn influences perceptual processing. To identify specific prestimulus EEG activity, and connectivity patterns related to subsequent pain perception in humans, we contrasted painful with nonpainful sensations delivered at the individual threshold level determined by the psychophysical QUEST estimation method (Watson and Pelli, 1983). The 64-channel EEG was recorded using active electrodes during a constant stimulation procedure. The power contrast between trials sorted by rating revealed a signal decrease of 8% before stimulus onset in theta-band (4-7 Hz) at T7/FT7 as well as increased theta-power by 6% at T8/FT8. Gamma-band power was increased (12%, 28-32 Hz) at frontocentral sites (all p < 0.05). Changes in theta-band power are covarying with subsequent pain perception, as well as lowered frontolateral theta-band connectivity for painful percepts. A decrease in frontoparietal connectivity for painful sensations was also identified in the gamma-band (28-32 Hz). A single-trial logistic regression revealed significant information content in the EEG signal at temporal electrode T7 in theta-band (p < 0.01) and frontal electrode F1 in gamma-band (all p < 0.02). The observed patterns suggest top-down modulation of the theta-band effects by a frontocentral network node. These findings contribute to the understanding of ongoing subjective pain sensitivity, potentially relevant to both clinical diagnostics and pain management. SIGNIFICANCE STATEMENT The perceived intensity of a constant stimulus is known to vary considerably across multiple presentations. Here, we used state-of-the-art psychophysical methods in an EEG experiment to identify the specific neuronal activity before stimulus onset that reflects the subsequent perception of pain. We found specific oscillatory activity at the bilateral insular cortices as well as connectivity patterns that reflect and correlate with subsequent ratings. These results further the understanding of pain perception and are potentially relevant for the decoding of ongoing pain sensitivity and pain management.
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46
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Mullinger KJ, Cherukara MT, Buxton RB, Francis ST, Mayhew SD. Post-stimulus fMRI and EEG responses: Evidence for a neuronal origin hypothesised to be inhibitory. Neuroimage 2017; 157:388-399. [PMID: 28610902 DOI: 10.1016/j.neuroimage.2017.06.020] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 06/05/2017] [Accepted: 06/09/2017] [Indexed: 12/26/2022] Open
Abstract
Post-stimulus undershoots, negative responses following cessation of stimulation, are widely observed in functional magnetic resonance (fMRI) blood oxygenation level dependent (BOLD) data. However, the debate surrounding whether the origin of this response phase is neuronal or vascular, and whether it provides functionally relevant information, that is additional to what is contained in the primary response, means that undershoots are widely overlooked. We simultaneously recorded electroencephalography (EEG), BOLD and cerebral blood-flow (CBF) [obtained from arterial spin labelled (ASL) fMRI] fMRI responses to hemifield checkerboard stimulation to test the potential neural origin of the fMRI post-stimulus undershoot. The post-stimulus BOLD and CBF signal amplitudes in both contralateral and ipsilateral visual cortex depended on the post-stimulus power of the occipital 8-13Hz (alpha) EEG neuronal activity, such that trials with highest EEG power showed largest fMRI undershoots in contralateral visual cortex. This correlation in post-stimulus EEG-fMRI responses was not predicted by the primary response amplitude. In the contralateral visual cortex we observed a decrease in both cerebral rate of oxygen metabolism (CMRO2) and CBF during the post-stimulus phase. In addition, the coupling ratio (n) between CMRO2 and CBF was significantly lower during the positive contralateral primary response phase compared with the post-stimulus phase and we propose that this reflects an altered balance of excitatory and inhibitory neuronal activity. Together our data provide strong evidence that the post-stimulus phase of the BOLD response has a neural origin which reflects, at least partially, an uncoupling of the neuronal responses driving the primary and post-stimulus responses, explaining the uncoupling of the signals measured in the two response phases. We suggest our results are consistent with inhibitory processes driving the post-stimulus EEG and fMRI responses. We therefore propose that new methods are required to model the post-stimulus and primary responses independently, enabling separate investigation of response phases in cognitive function and neurological disease.
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Affiliation(s)
- K J Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK; Birmingham University Imaging Centre, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK.
| | - M T Cherukara
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - R B Buxton
- Department of Radiology, Center for Functional MRI, University of California, San Diego, La Jolla, CA, USA
| | - S T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - S D Mayhew
- Birmingham University Imaging Centre, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
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47
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Bockhorst T, Homberg U. Interaction of compass sensing and object-motion detection in the locust central complex. J Neurophysiol 2017; 118:496-506. [PMID: 28404828 DOI: 10.1152/jn.00927.2016] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 02/21/2017] [Accepted: 03/11/2017] [Indexed: 01/08/2023] Open
Abstract
Goal-directed behavior is often complicated by unpredictable events, such as the appearance of a predator during directed locomotion. This situation requires adaptive responses like evasive maneuvers followed by subsequent reorientation and course correction. Here we study the possible neural underpinnings of such a situation in an insect, the desert locust. As in other insects, its sense of spatial orientation strongly relies on the central complex, a group of midline brain neuropils. The central complex houses sky compass cells that signal the polarization plane of skylight and thus indicate the animal's steering direction relative to the sun. Most of these cells additionally respond to small moving objects that drive fast sensory-motor circuits for escape. Here we investigate how the presentation of a moving object influences activity of the neurons during compass signaling. Cells responded in one of two ways: in some neurons, responses to the moving object were simply added to the compass response that had adapted during continuous stimulation by stationary polarized light. By contrast, other neurons disadapted, i.e., regained their full compass response to polarized light, when a moving object was presented. We propose that the latter case could help to prepare for reorientation of the animal after escape. A neuronal network based on central-complex architecture can explain both responses by slight changes in the dynamics and amplitudes of adaptation to polarized light in CL columnar input neurons of the system.NEW & NOTEWORTHY Neurons of the central complex in several insects signal compass directions through sensitivity to the sky polarization pattern. In locusts, these neurons also respond to moving objects. We show here that during polarized-light presentation, responses to moving objects override their compass signaling or restore adapted inhibitory as well as excitatory compass responses. A network model is presented to explain the variations of these responses that likely serve to redirect flight or walking following evasive maneuvers.
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Affiliation(s)
- Tobias Bockhorst
- Animal Physiology, Department of Biology, Philipps University, Marburg, Germany
| | - Uwe Homberg
- Animal Physiology, Department of Biology, Philipps University, Marburg, Germany
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48
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Michels L, O'Gorman R, Kucian K. Functional hyperconnectivity vanishes in children with developmental dyscalculia after numerical intervention. Dev Cogn Neurosci 2017; 30:291-303. [PMID: 28442224 PMCID: PMC6969091 DOI: 10.1016/j.dcn.2017.03.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 02/23/2017] [Accepted: 03/16/2017] [Indexed: 01/25/2023] Open
Abstract
Developmental dyscalculia (DD) is a developmental learning disability associated with deficits in processing numerical and mathematical information. Although behavioural training can reduce these deficits, it is unclear which neuronal resources show a functional reorganization due to training. We examined typically developing (TD) children (N = 16, mean age: 9.5 years) and age-, gender-, and handedness-matched children with DD (N = 15, mean age: 9.5 years) during the performance of a numerical order task with fMRI and functional connectivity before and after 5-weeks of number line training. Using the intraparietal sulcus (IPS) as seed region, DD showed hyperconnectivity in parietal, frontal, visual, and temporal regions before the training controlling for age and IQ. Hyperconnectivity disappeared after training, whereas math abilities improved. Multivariate classification analysis of task-related fMRI data corroborated the connectivity results as the same group of TD could be discriminated from DD before but not after number line training (86.4 vs. 38.9%, respectively). Our results indicate that abnormally high functional connectivity in DD can be normalized on the neuronal level by intensive number line training. As functional connectivity in DD was indistinguishable to TD’s connectivity after training, we conclude that training lead to a re-organization of inter-regional task engagement.
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Affiliation(s)
- Lars Michels
- Clinic of Neuroradiology, University Hospital Zurich, Switzerland; Center for MR-Research, University Children's Hospital Zurich, Zurich, Switzerland; Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland.
| | - Ruth O'Gorman
- Center for MR-Research, University Children's Hospital Zurich, Zurich, Switzerland; Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Karin Kucian
- Center for MR-Research, University Children's Hospital Zurich, Zurich, Switzerland; Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland; Center for Neuroscience Zurich, University and ETH Zurich, Zurich, Switzerland
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49
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Peng KY, Mathews PM, Levy E, Wilson DA. Apolipoprotein E4 causes early olfactory network abnormalities and short-term olfactory memory impairments. Neuroscience 2016; 343:364-371. [PMID: 28003161 DOI: 10.1016/j.neuroscience.2016.12.004] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Revised: 11/30/2016] [Accepted: 12/02/2016] [Indexed: 02/08/2023]
Abstract
While apolipoprotein (Apo) E4 is linked to increased incidence of Alzheimer's disease (AD), there is growing evidence that it plays a role in functional brain irregularities that are independent of AD pathology. However, ApoE4-driven functional differences within olfactory processing regions have yet to be examined. Utilizing knock-in mice humanized to ApoE4 versus the more common ApoE3, we examined a simple olfactory perceptual memory that relies on the transfer of information from the olfactory bulb (OB) to the piriform cortex (PCX), the primary cortical region involved in higher order olfaction. In addition, we have recorded in vivo resting and odor-evoked local field potentials (LPF) from both brain regions and measured corresponding odor response magnitudes in anesthetized young (6-month-old) and middle-aged (12-month-old) ApoE mice. Young ApoE4 compared to ApoE3 mice exhibited a behavioral olfactory deficit coinciding with hyperactive odor-evoked response magnitudes within the OB that were not observed in older ApoE4 mice. Meanwhile, middle-aged ApoE4 compared to ApoE3 mice exhibited heightened response magnitudes in the PCX without a corresponding olfactory deficit, suggesting a shift with aging in ApoE4-driven effects from OB to PCX. Interestingly, the increased ApoE4-specific response in the PCX at middle-age was primarily due to a dampening of baseline spontaneous activity rather than an increase in evoked response power. Our findings indicate that early ApoE4-driven olfactory memory impairments and OB network abnormalities may be a precursor to later network dysfunction in the PCX, a region that not only is targeted early in AD, but may be selectively vulnerable to ApoE4 genotype.
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Affiliation(s)
- Katherine Y Peng
- Department of Neuroscience & Physiology, New York University Langone Medical Center, 560 1st Avenue, 10016 New York, NY, USA; Department of Biochemistry & Molecular Pharmacology, New York University Langone Medical Center, 560 1st Avenue, 10016 New York, NY, USA.
| | - Paul M Mathews
- Department of Psychiatry, New York University Langone Medical Center, 560 1st Avenue, 10016 New York, NY, USA; Center for Dementia Research, Nathan S. Kline Institute, 140 Old Orangeburg Road, Orangeburg, 10962 New York, USA.
| | - Efrat Levy
- Department of Biochemistry & Molecular Pharmacology, New York University Langone Medical Center, 560 1st Avenue, 10016 New York, NY, USA; Department of Psychiatry, New York University Langone Medical Center, 560 1st Avenue, 10016 New York, NY, USA; Center for Dementia Research, Nathan S. Kline Institute, 140 Old Orangeburg Road, Orangeburg, 10962 New York, USA.
| | - Donald A Wilson
- Department of Neuroscience & Physiology, New York University Langone Medical Center, 560 1st Avenue, 10016 New York, NY, USA; Department of Child & Adolescent Psychiatry, New York University Langone Medical Center, 560 1st Avenue, 10016 New York, NY, USA; Emotional Brain Institute, Nathan S. Kline Institute, 140 Old Orangeburg Road, Orangeburg, 10962 New York, USA.
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Iordan AD, Reuter-Lorenz PA. Age-related Change and the Predictive Value of the 'Resting State': A Commentary on Campbell and Schacter (2016). LANGUAGE, COGNITION AND NEUROSCIENCE 2016; 32:674-677. [PMID: 37275748 PMCID: PMC10237480 DOI: 10.1080/23273798.2016.1242759] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Accepted: 09/21/2016] [Indexed: 06/07/2023]
Abstract
This is a commentary on Campbell and Schacter (2016), 'Aging and the Resting State: Is Cognition Obsolete?'
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