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Peelman K, Haider B. Environmental context sculpts spatial and temporal visual processing in thalamus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605345. [PMID: 39091887 PMCID: PMC11291113 DOI: 10.1101/2024.07.26.605345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Behavioral state modulates neural activity throughout the visual system; this is largely due to changes in arousal that alter internal brain state. However, behaviors are constrained by the external environmental context, so it remains unclear if this context itself dictates the regime of visual processing, apart from ongoing changes in arousal. Here, we addressed this question in awake head-fixed mice while they passively viewed visual stimuli in two different environmental contexts: either a cylindrical tube, or a circular running wheel. We targeted high-density silicon probe recordings to the dorsal lateral geniculate nucleus (dLGN) and simultaneously measured several electrophysiological and behavioral correlates of arousal changes, and thus controlled for them across contexts. We found surprising differences in spatial and temporal processing in dLGN across contexts, even in identical states of alertness and stillness. The wheel context (versus tube) showed elevated baseline activity, faster visual responses, and smaller but less selective spatial receptive fields. Further, arousal caused similar changes to visual responsiveness across all conditions, but the environmental context mainly changed the overall set-point for this relationship. Together, our results reveal an unexpected influence of the physical environmental context on fundamental aspects of visual processing in the early visual system.
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Affiliation(s)
- Kayla Peelman
- Dept of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Dept of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
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2
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Spyropoulos G, Schneider M, van Kempen J, Gieselmann MA, Thiele A, Vinck M. Distinct feedforward and feedback pathways for cell-type specific attention effects. Neuron 2024; 112:2423-2434.e7. [PMID: 38759641 DOI: 10.1016/j.neuron.2024.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 02/12/2024] [Accepted: 04/17/2024] [Indexed: 05/19/2024]
Abstract
Selective attention is thought to depend on enhanced firing activity in extrastriate areas. Theories suggest that this enhancement depends on selective inter-areal communication via gamma (30-80 Hz) phase-locking. To test this, we simultaneously recorded from different cell types and cortical layers of macaque V1 and V4. We find that while V1-V4 gamma phase-locking between local field potentials increases with attention, the V1 gamma rhythm does not engage V4 excitatory-neurons, but only fast-spiking interneurons in L4 of V4. By contrast, attention enhances V4 spike-rates in both excitatory and inhibitory cells, most strongly in L2/3. The rate increase in L2/3 of V4 precedes V1 in time. These findings suggest enhanced signal transmission with attention does not depend on inter-areal gamma phase-locking and show that the endogenous gamma rhythm has cell-type- and layer-specific effects on downstream target areas. Similar findings were made in the mouse visual system, based on opto-tagging of identified interneurons.
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Affiliation(s)
- Georgios Spyropoulos
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Marius Schneider
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands
| | - Jochem van Kempen
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | | | - Alexander Thiele
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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3
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Johnsen KA, Cruzado NA, Menard ZC, Willats AA, Charles AS, Markowitz JE, Rozell CJ. Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.27.525963. [PMID: 39026717 PMCID: PMC11257437 DOI: 10.1101/2023.01.27.525963] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Systems neuroscience has experienced an explosion of new tools for reading and writing neural activity, enabling exciting new experiments such as all-optical or closed-loop control that effect powerful causal interventions. At the same time, improved computational models are capable of reproducing behavior and neural activity with increasing fidelity. Unfortunately, these advances have drastically increased the complexity of integrating different lines of research, resulting in the missed opportunities and untapped potential of suboptimal experiments. Experiment simulation can help bridge this gap, allowing model and experiment to better inform each other by providing a low-cost testbed for experiment design, model validation, and methods engineering. Specifically, this can be achieved by incorporating the simulation of the experimental interface into our models, but no existing tool integrates optogenetics, two-photon calcium imaging, electrode recording, and flexible closed-loop processing with neural population simulations. To address this need, we have developed Cleo: the Closed-Loop, Electrophysiology, and Optophysiology experiment simulation testbed. Cleo is a Python package enabling injection of recording and stimulation devices as well as closed-loop control with realistic latency into a Brian spiking neural network model. It is the only publicly available tool currently supporting two-photon and multi-opsin/wavelength optogenetics. To facilitate adoption and extension by the community, Cleo is open-source, modular, tested, and documented, and can export results to various data formats. Here we describe the design and features of Cleo, validate output of individual components and integrated experiments, and demonstrate its utility for advancing optogenetic techniques in prospective experiments using previously published systems neuroscience models.
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Affiliation(s)
- Kyle A. Johnsen
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | | | - Zachary C. Menard
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Adam A. Willats
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Adam S. Charles
- Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Jeffrey E. Markowitz
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
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4
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Wang B, Li M, Haihambo N, Qiu Z, Sun M, Guo M, Zhao X, Han C. Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB). J Affect Disord 2024; 355:254-264. [PMID: 38561155 DOI: 10.1016/j.jad.2024.03.145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 03/24/2024] [Accepted: 03/25/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear. METHODS In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB). RESULTS We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone. CONCLUSIONS Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.
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Affiliation(s)
- Bin Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, 100191 Beijing, China
| | - Meijia Li
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Naem Haihambo
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Zihan Qiu
- Avenues the World School Shenzhen Campus, Shenzhen 518000, China
| | - Meirong Sun
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Mingrou Guo
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong
| | - Xixi Zhao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, 100191 Beijing, China.
| | - Chuanliang Han
- School of Biomedical Sciences and Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong.
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5
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Quintana D, Bounds H, Veit J, Adesnik H. Balanced bidirectional optogenetics reveals the causal impact of cortical temporal dynamics in sensory perception. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.30.596706. [PMID: 38853943 PMCID: PMC11160799 DOI: 10.1101/2024.05.30.596706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Whether the fast temporal dynamics of neural activity in brain circuits causally drive perception and cognition remains one of most longstanding unresolved questions in neuroscience 1-6 . While some theories posit a 'timing code' in which dynamics on the millisecond timescale is central to brain function, others instead argue that mean firing rates over more extended periods (a 'rate code') carry most of the relevant information. Existing tools, such as optogenetics, can be used to alter temporal structure of neural dynamics 7 , but they invariably change mean firing rates, leaving the interpretation of such experiments ambiguous. Here we developed and validated a new approach based on balanced, bidirectional optogenetics that can alter temporal structure of neural dynamics while mitigating effects on mean activity. Using this new approach, we found that selectively altering cortical temporal dynamics substantially reduced performance in a sensory perceptual task. These results demonstrate that endogenous temporal dynamics in the cortex are causally required for perception and behavior. More generally, this new bidirectional optogenetic approach should be broadly useful for disentangling the causal impact of different timescales of neural dynamics on behavior.
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Lemercier CE, Krieger P, Manahan-Vaughan D. Dynamic modulation of mouse thalamocortical visual activity by salient sounds. iScience 2024; 27:109364. [PMID: 38523779 PMCID: PMC10959669 DOI: 10.1016/j.isci.2024.109364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 12/11/2023] [Accepted: 02/26/2024] [Indexed: 03/26/2024] Open
Abstract
Visual responses of the primary visual cortex (V1) are altered by sound. Sound-driven behavioral arousal suggests that, in addition to direct inputs from the primary auditory cortex (A1), multiple other sources may shape V1 responses to sound. Here, we show in anesthetized mice that sound (white noise, ≥70dB) drives a biphasic modulation of V1 visually driven gamma-band activity, comprising fast-transient inhibitory and slow, prolonged excitatory (A1-independent) arousal-driven components. An analogous yet quicker modulation of the visual response also occurred earlier in the visual pathway, at the level of the dorsolateral geniculate nucleus (dLGN), where sound transiently inhibited the early phasic visual response and subsequently induced a prolonged increase in tonic spiking activity and gamma rhythmicity. Our results demonstrate that sound-driven modulations of visual activity are not exclusive to V1 and suggest that thalamocortical inputs from the dLGN to V1 contribute to shaping V1 visual response to sound.
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Affiliation(s)
- Clément E. Lemercier
- Department of Neurophysiology, Medical Faculty, Ruhr-University Bochum, 44801 Bochum, Germany
| | - Patrik Krieger
- Department of Neurophysiology, Medical Faculty, Ruhr-University Bochum, 44801 Bochum, Germany
| | - Denise Manahan-Vaughan
- Department of Neurophysiology, Medical Faculty, Ruhr-University Bochum, 44801 Bochum, Germany
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7
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Meneghetti N, Vannini E, Mazzoni A. Rodents' visual gamma as a biomarker of pathological neural conditions. J Physiol 2024; 602:1017-1048. [PMID: 38372352 DOI: 10.1113/jp283858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 01/23/2024] [Indexed: 02/20/2024] Open
Abstract
Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.
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Affiliation(s)
- Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), Pisa, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
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8
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Hayden DJ, Finnie PSB, Thomazeau A, Li AY, Cooke SF, Bear MF. Electrophysiological Signatures of Visual Recognition Memory across All Layers of Mouse V1. J Neurosci 2023; 43:7307-7321. [PMID: 37714707 PMCID: PMC10621768 DOI: 10.1523/jneurosci.0090-23.2023] [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: 01/16/2023] [Revised: 08/31/2023] [Accepted: 09/05/2023] [Indexed: 09/17/2023] Open
Abstract
In mouse primary visual cortex (V1), familiar stimuli evoke significantly altered responses when compared with novel stimuli. This stimulus-selective response plasticity (SRP) was described originally as an increase in the magnitude of visual evoked potentials (VEPs) elicited in layer 4 (L4) by familiar phase-reversing grating stimuli. SRP is dependent on NMDA receptors (NMDARs) and has been hypothesized to reflect potentiation of thalamocortical (TC) synapses in L4. However, recent evidence indicates that the synaptic modifications that manifest as SRP do not occur on L4 principal cells. To shed light on where and how SRP is induced and expressed in male and female mice, the present study had three related aims: (1) to confirm that NMDAR are required specifically in glutamatergic principal neurons of V1, (2) to investigate the consequences of deleting NMDAR specifically in L6, and (3) to use translaminar electrophysiological recordings to characterize SRP expression in different layers of V1. We find that knock-out (KO) of NMDAR in L6 principal neurons disrupts SRP. Current-source density (CSD) analysis of the VEP depth profile shows augmentation of short latency current sinks in layers 3, 4, and 6 in response to phase reversals of familiar stimuli. Multiunit recordings demonstrate that increased peak firing occurs in response to phase reversals of familiar stimuli across all layers, but that activity between phase reversals is suppressed. Together, these data reveal important aspects of the underlying phenomenology of SRP and generate new hypotheses for the expression of experience-dependent plasticity in V1.SIGNIFICANCE STATEMENT Repeated exposure to stimuli that portend neither reward nor punishment leads to behavioral habituation, enabling organisms to dedicate attention to novel or otherwise significant features of the environment. The neural basis of this process, which is so often dysregulated in neurologic and psychiatric disorders, remains poorly understood. Learning and memory of stimulus familiarity can be studied in mouse visual cortex by measuring electrophysiological responses to simple phase-reversing grating stimuli. The current study advances knowledge of this process by documenting changes in visual evoked potentials (VEPs), neuronal spiking activity, and oscillations in the local field potentials (LFPs) across all layers of mouse visual cortex. In addition, we identify a key contribution of a specific population of neurons in layer 6 (L6) of visual cortex.
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Affiliation(s)
- Dustin J Hayden
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Peter S B Finnie
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Aurore Thomazeau
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Alyssa Y Li
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Biochemistry Program, Wellesley College, Wellesley, Massachusetts 02481
| | - Samuel F Cooke
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Mark F Bear
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
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Wang J, Azimi H, Zhao Y, Kaeser M, Vaca Sánchez P, Vazquez-Guardado A, Rogers JA, Harvey M, Rainer G. Optogenetic activation of visual thalamus generates artificial visual percepts. eLife 2023; 12:e90431. [PMID: 37791662 PMCID: PMC10593406 DOI: 10.7554/elife.90431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/03/2023] [Indexed: 10/05/2023] Open
Abstract
The lateral geniculate nucleus (LGN), a retinotopic relay center where visual inputs from the retina are processed and relayed to the visual cortex, has been proposed as a potential target for artificial vision. At present, it is unknown whether optogenetic LGN stimulation is sufficient to elicit behaviorally relevant percepts, and the properties of LGN neural responses relevant for artificial vision have not been thoroughly characterized. Here, we demonstrate that tree shrews pretrained on a visual detection task can detect optogenetic LGN activation using an AAV2-CamKIIα-ChR2 construct and readily generalize from visual to optogenetic detection. Simultaneous recordings of LGN spiking activity and primary visual cortex (V1) local field potentials (LFPs) during optogenetic LGN stimulation show that LGN neurons reliably follow optogenetic stimulation at frequencies up to 60 Hz and uncovered a striking phase locking between the V1 LFP and the evoked spiking activity in LGN. These phase relationships were maintained over a broad range of LGN stimulation frequencies, up to 80 Hz, with spike field coherence values favoring higher frequencies, indicating the ability to relay temporally precise information to V1 using light activation of the LGN. Finally, V1 LFP responses showed sensitivity values to LGN optogenetic activation that were similar to the animal's behavioral performance. Taken together, our findings confirm the LGN as a potential target for visual prosthetics in a highly visual mammal closely related to primates.
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Affiliation(s)
- Jing Wang
- Department of Medicine, University of FribourgFribourgSwitzerland
- Department of Neurobiology, School of Basic Medical Sciences, Nanjing Medical UniversityNanjingChina
| | - Hamid Azimi
- Department of Medicine, University of FribourgFribourgSwitzerland
| | - Yilei Zhao
- Department of Medicine, University of FribourgFribourgSwitzerland
| | - Melanie Kaeser
- Department of Medicine, University of FribourgFribourgSwitzerland
| | | | | | - John A Rogers
- Querrey Simpson Institute for Bioelectronics, Northwestern UniversityEvanstonUnited States
| | - Michael Harvey
- Department of Medicine, University of FribourgFribourgSwitzerland
| | - Gregor Rainer
- Department of Medicine, University of FribourgFribourgSwitzerland
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Perrenoud Q, Cardin JA. Beyond rhythm - a framework for understanding the frequency spectrum of neural activity. Front Syst Neurosci 2023; 17:1217170. [PMID: 37719024 PMCID: PMC10500127 DOI: 10.3389/fnsys.2023.1217170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 08/14/2023] [Indexed: 09/19/2023] Open
Abstract
Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we use a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: (1) the distribution of neural events in time and (2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity.
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Affiliation(s)
- Quentin Perrenoud
- Department of Neuroscience, Yale School of Medicine, Kavli Institute for Neuroscience, Wu Tsai Institute, New Haven, CT, United States
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11
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Rimehaug AE, Stasik AJ, Hagen E, Billeh YN, Siegle JH, Dai K, Olsen SR, Koch C, Einevoll GT, Arkhipov A. Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortex. eLife 2023; 12:e87169. [PMID: 37486105 PMCID: PMC10393295 DOI: 10.7554/elife.87169] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 07/10/2023] [Indexed: 07/25/2023] Open
Abstract
Local field potential (LFP) recordings reflect the dynamics of the current source density (CSD) in brain tissue. The synaptic, cellular, and circuit contributions to current sinks and sources are ill-understood. We investigated these in mouse primary visual cortex using public Neuropixels recordings and a detailed circuit model based on simulating the Hodgkin-Huxley dynamics of >50,000 neurons belonging to 17 cell types. The model simultaneously captured spiking and CSD responses and demonstrated a two-way dissociation: firing rates are altered with minor effects on the CSD pattern by adjusting synaptic weights, and CSD is altered with minor effects on firing rates by adjusting synaptic placement on the dendrites. We describe how thalamocortical inputs and recurrent connections sculpt specific sinks and sources early in the visual response, whereas cortical feedback crucially alters them in later stages. These results establish quantitative links between macroscopic brain measurements (LFP/CSD) and microscopic biophysics-based understanding of neuron dynamics and show that CSD analysis provides powerful constraints for modeling beyond those from considering spikes.
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Affiliation(s)
| | | | - Espen Hagen
- Department of Physics, University of OsloOsloNorway
- Department of Data Science, Norwegian University of Life SciencesÅsNorway
| | | | - Josh H Siegle
- MindScope Program, Allen InstituteSeattleUnited States
| | - Kael Dai
- MindScope Program, Allen InstituteSeattleUnited States
| | - Shawn R Olsen
- MindScope Program, Allen InstituteSeattleUnited States
| | - Christof Koch
- MindScope Program, Allen InstituteSeattleUnited States
| | - Gaute T Einevoll
- Department of Physics, University of OsloOsloNorway
- Department of Physics, Norwegian University of Life SciencesÅsNorway
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12
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Neuenschwander S, Rosso G, Branco N, Freitag F, Tehovnik EJ, Schmidt KE, Baron J. On the Functional Role of Gamma Synchronization in the Retinogeniculate System of the Cat. J Neurosci 2023; 43:5204-5220. [PMID: 37328291 PMCID: PMC10342227 DOI: 10.1523/jneurosci.1550-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 02/06/2023] [Accepted: 03/09/2023] [Indexed: 06/18/2023] Open
Abstract
Fast gamma oscillations, generated within the retina, and transmitted to the cortex via the lateral geniculate nucleus (LGN), are thought to carry information about stimulus size and continuity. This hypothesis relies mainly on studies conducted under anesthesia and the extent to which it holds under more naturalistic conditions remains unclear. Using multielectrode recordings of spiking activity in the retina and the LGN of both male and female cats, we show that visually driven gamma oscillations are absent for awake states and are highly dependent on halothane (or isoflurane). Under ketamine, responses were nonoscillatory, as in the awake condition. Response entrainment to the monitor refresh was commonly observed up to 120 Hz and was superseded by the gamma oscillatory responses induced by halothane. Given that retinal gamma oscillations are contingent on halothane anesthesia and absent in the awake cat, such oscillations should be considered artifactual, thus playing no functional role in vision.SIGNIFICANCE STATEMENT Gamma rhythms have been proposed to be a robust encoding mechanism critical for visual processing. In the retinogeniculate system of the cat, many studies have shown gamma oscillations associated with responses to static stimuli. Here, we extend these observations to dynamic stimuli. An unexpected finding was that retinal gamma responses strongly depend on halothane concentration levels and are absent in the awake cat. These results weaken the notion that gamma in the retina is relevant for vision. Notably, retinal gamma shares many of the properties of cortical gamma. In this respect, oscillations induced by halothane in the retina may serve as a valuable preparation, although artificial, for studying oscillatory dynamics.
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Affiliation(s)
- Sergio Neuenschwander
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Giovanne Rosso
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Natalia Branco
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Fabio Freitag
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Edward J Tehovnik
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Kerstin E Schmidt
- Brain Institute, Federal University of Rio Grande do Norte, 59076-550, Natal, Brazil
| | - Jerome Baron
- Department of Physiology and Biophysics, Institute of Biological Sciences, Federal University of Minas Gerais, 31270-901, Belo Horizonte, Brazil
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13
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Bygrave AM, Sengupta A, Jackert EP, Ahmed M, Adenuga B, Nelson E, Goldschmidt HL, Johnson RC, Zhong H, Yeh FL, Sheng M, Huganir RL. Btbd11 supports cell-type-specific synaptic function. Cell Rep 2023; 42:112591. [PMID: 37261953 PMCID: PMC10592477 DOI: 10.1016/j.celrep.2023.112591] [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: 11/23/2022] [Revised: 04/21/2023] [Accepted: 05/16/2023] [Indexed: 06/03/2023] Open
Abstract
Synapses in the brain exhibit cell-type-specific differences in basal synaptic transmission and plasticity. Here, we evaluated cell-type-specific specializations in the composition of glutamatergic synapses, identifying Btbd11 as an inhibitory interneuron-specific, synapse-enriched protein. Btbd11 is highly conserved across species and binds to core postsynaptic proteins, including Psd-95. Intriguingly, we show that Btbd11 can undergo liquid-liquid phase separation when expressed with Psd-95, supporting the idea that the glutamatergic postsynaptic density in synapses in inhibitory interneurons exists in a phase-separated state. Knockout of Btbd11 decreased glutamatergic signaling onto parvalbumin-positive interneurons. Further, both in vitro and in vivo, Btbd11 knockout disrupts network activity. At the behavioral level, Btbd11 knockout from interneurons alters exploratory behavior, measures of anxiety, and sensitizes mice to pharmacologically induced hyperactivity following NMDA receptor antagonist challenge. Our findings identify a cell-type-specific mechanism that supports glutamatergic synapse function in inhibitory interneurons-with implications for circuit function and animal behavior.
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Affiliation(s)
- Alexei M Bygrave
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
| | - Ayesha Sengupta
- National Institute on Drug Abuse, Bayview Boulevard, Baltimore, MD 21224, USA
| | - Ella P Jackert
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Mehroz Ahmed
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Beloved Adenuga
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Erik Nelson
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Hana L Goldschmidt
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Richard C Johnson
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Haining Zhong
- Vollum Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | - Felix L Yeh
- Department of Neuroscience, Genentech, Inc, South San Francisco, CA 94080, USA
| | - Morgan Sheng
- Department of Neuroscience, Genentech, Inc, South San Francisco, CA 94080, USA
| | - Richard L Huganir
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21205, USA.
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14
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Klaver LMF, Brinkhof LP, Sikkens T, Casado-Román L, Williams AG, van Mourik-Donga L, Mejías JF, Pennartz CMA, Bosman CA. Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness. Cereb Cortex 2023; 33:7564-7581. [PMID: 36935096 PMCID: PMC10267643 DOI: 10.1093/cercor/bhad061] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 02/11/2023] [Accepted: 02/14/2023] [Indexed: 03/21/2023] Open
Abstract
Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.
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Affiliation(s)
- Lianne M F Klaver
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lotte P Brinkhof
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Tom Sikkens
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lorena Casado-Román
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Alex G Williams
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Laura van Mourik-Donga
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Jorge F Mejías
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Conrado A Bosman
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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15
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Perrenoud Q, Cardin JA. Beyond rhythm - A framework for understanding the frequency spectrum of neural activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.12.540559. [PMID: 37215044 PMCID: PMC10197620 DOI: 10.1101/2023.05.12.540559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we propose a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: 1) the distribution of neural events in time and 2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity.
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Affiliation(s)
- Quentin Perrenoud
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT, USA
| | - Jessica A. Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT, USA
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16
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Fernandez-Ruiz A, Sirota A, Lopes-Dos-Santos V, Dupret D. Over and above frequency: Gamma oscillations as units of neural circuit operations. Neuron 2023; 111:936-953. [PMID: 37023717 PMCID: PMC7614431 DOI: 10.1016/j.neuron.2023.02.026] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 11/30/2022] [Accepted: 02/16/2023] [Indexed: 04/08/2023]
Abstract
Gamma oscillations (∼30-150 Hz) are widespread correlates of neural circuit functions. These network activity patterns have been described across multiple animal species, brain structures, and behaviors, and are usually identified based on their spectral peak frequency. Yet, despite intensive investigation, whether gamma oscillations implement causal mechanisms of specific brain functions or represent a general dynamic mode of neural circuit operation remains unclear. In this perspective, we review recent advances in the study of gamma oscillations toward a deeper understanding of their cellular mechanisms, neural pathways, and functional roles. We discuss that a given gamma rhythm does not per se implement any specific cognitive function but rather constitutes an activity motif reporting the cellular substrates, communication channels, and computational operations underlying information processing in its generating brain circuit. Accordingly, we propose shifting the attention from a frequency-based to a circuit-level definition of gamma oscillations.
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Affiliation(s)
| | - Anton Sirota
- Bernstein Center for Computational Neuroscience, Faculty of Medicine, Ludwig-Maximilians Universität München, Planegg-Martinsried, Germany.
| | - Vítor Lopes-Dos-Santos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - David Dupret
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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17
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Shin D, Peelman K, Lien AD, Del Rosario J, Haider B. Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system. Neuron 2023; 111:1076-1085.e8. [PMID: 37023711 PMCID: PMC10112544 DOI: 10.1016/j.neuron.2023.03.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 12/16/2022] [Accepted: 03/06/2023] [Indexed: 04/08/2023]
Abstract
Oscillations of neural activity permeate sensory systems. In the visual system, broadband gamma oscillations (30-80 Hz) are thought to act as a communication mechanism underlying perception. However, these oscillations show widely varying frequency and phase, providing constraints for coordinating spike timing across areas. Here, we examined Allen Brain Observatory data and performed causal experiments to show that narrowband gamma (NBG) oscillations (50-70 Hz) propagate and synchronize throughout the awake mouse visual system. Lateral geniculate nucleus (LGN) neurons fired precisely relative to NBG phase in primary visual cortex (V1) and multiple higher visual areas (HVAs). NBG neurons across areas showed a higher likelihood of functional connectivity and stronger visual responses; remarkably, NBG neurons in LGN, preferring bright (ON) versus dark (OFF), fired at distinct NBG phases aligned across the cortical hierarchy. NBG oscillations may thus serve to coordinate spike timing across brain areas and facilitate communication of distinct visual features during perception.
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Affiliation(s)
- Donghoon Shin
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA; Electrical and Computer Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA; Bioengineering, UCSF - UC Berkeley Joint PhD Program, San Francisco, CA, USA
| | - Kayla Peelman
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Anthony D Lien
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Joseph Del Rosario
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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18
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Murphy E. ROSE: A Neurocomputational Architecture for Syntax. ARXIV 2023:arXiv:2303.08877v1. [PMID: 36994166 PMCID: PMC10055479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
A comprehensive model of natural language processing in the brain must accommodate four components: representations, operations, structures and encoding. It further requires a principled account of how these different components mechanistically, and causally, relate to each another. While previous models have isolated regions of interest for structure-building and lexical access, and have utilized specific neural recording measures to expose possible signatures of syntax, many gaps remain with respect to bridging distinct scales of analysis that map onto these four components. By expanding existing accounts of how neural oscillations can index various linguistic processes, this article proposes a neurocomputational architecture for syntax, termed the ROSE model (Representation, Operation, Structure, Encoding). Under ROSE, the basic data structures of syntax are atomic features, types of mental representations (R), and are coded at the single-unit and ensemble level. Elementary computations (O) that transform these units into manipulable objects accessible to subsequent structure-building levels are coded via high frequency broadband γ activity. Low frequency synchronization and cross-frequency coupling code for recursive categorial inferences (S). Distinct forms of low frequency coupling and phase-amplitude coupling (δ-θ coupling via pSTS-IFG; θ-γ coupling via IFG to conceptual hubs in lateral and ventral temporal cortex) then encode these structures onto distinct workspaces (E). Causally connecting R to O is spike-phase/LFP coupling; connecting O to S is phase-amplitude coupling; connecting S to E is a system of frontotemporal traveling oscillations; connecting E back to lower levels is low-frequency phase resetting of spike-LFP coupling. This compositional neural code has important implications for algorithmic accounts, since it makes concrete predictions for the appropriate level of study for psycholinguistic parsing models. ROSE is reliant on neurophysiologically plausible mechanisms, is supported at all four levels by a range of recent empirical research, and provides an anatomically precise and falsifiable grounding for the basic property of natural language syntax: hierarchical, recursive structure-building.
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Affiliation(s)
- Elliot Murphy
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, UTHealth, Houston, TX, USA
- Texas Institute for Restorative Neurotechnologies, UTHealth, Houston, TX, USA
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19
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Zhang Q, Cramer SR, Turner KL, Neuberger T, Drew PJ, Zhang N. High-frequency neuronal signal better explains multi-phase BOLD response. Neuroimage 2023; 268:119887. [PMID: 36681134 PMCID: PMC9962576 DOI: 10.1016/j.neuroimage.2023.119887] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 01/20/2023] Open
Abstract
Visual stimulation-evoked blood-oxygen-level dependent (BOLD) responses can exhibit more complex temporal dynamics than a simple monophasic response. For instance, BOLD responses sometimes include a phase of positive response followed by a phase of post-stimulus undershoot. Whether the BOLD response during these phases reflects the underlying neuronal signal fluctuations or is contributed by non-neuronal physiological factors remains elusive. When presenting blocks of sustained (i.e. DC) light ON-OFF stimulations to unanesthetized rats, we observed that the response following a decrease in illumination (i.e. OFF stimulation-evoked BOLD response) in the visual cortices displayed reproducible multiple phases, including an initial positive BOLD response, followed by an undershoot and then an overshoot before the next ON trial. This multi-phase BOLD response did not result from the entrainment of the periodic stimulation structure. When we measured the neural correlates of these responses, we found that the high-frequency band from the LFP power (300 - 3000 Hz, multi-unit activity (MUA)), but not the power in the gamma band (30 - 100 Hz) exhibited the same multiphasic dynamics as the BOLD signal. This study suggests that the post-stimulus phases of the BOLD response can be better explained by the high-frequency neuronal signal.
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Affiliation(s)
- Qingqing Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA
| | - Samuel R Cramer
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA
| | - Kevin L Turner
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA
| | - Thomas Neuberger
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA
| | - Patrick J Drew
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA; Departments of Engineering Science and Mechanics, Neurosurgery, and Biology, The Pennsylvania State University, University Park, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA.
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20
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Veit J, Handy G, Mossing DP, Doiron B, Adesnik H. Cortical VIP neurons locally control the gain but globally control the coherence of gamma band rhythms. Neuron 2023; 111:405-417.e5. [PMID: 36384143 PMCID: PMC9898108 DOI: 10.1016/j.neuron.2022.10.036] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 09/12/2022] [Accepted: 10/28/2022] [Indexed: 11/17/2022]
Abstract
Gamma band synchronization can facilitate local and long-range neural communication. In the primary visual cortex, visual stimulus properties within a specific location determine local synchronization strength, while the match of stimulus properties between distant locations controls long-range synchronization. The neural basis for the differential control of local and global gamma band synchronization is unknown. Combining electrophysiology, optogenetics, and computational modeling, we found that VIP disinhibitory interneurons in mouse cortex linearly scale gamma power locally without changing its stimulus tuning. Conversely, they suppress long-range synchronization when two regions process non-matched stimuli, tuning gamma coherence globally. Modeling shows that like-to-like connectivity across space and specific VIP→SST inhibition capture these opposing effects. VIP neurons thus differentially impact local and global properties of gamma rhythms depending on visual stimulus statistics. They may thereby construct gamma-band filters for spatially extended but continuous image features, such as contours, facilitating the downstream generation of coherent visual percepts.
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Affiliation(s)
- Julia Veit
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.
| | - Gregory Handy
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA; Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA
| | - Daniel P Mossing
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; Biophysics Graduate Program, University of California, Berkeley, Berkeley, CA, USA
| | - Brent Doiron
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA; Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA
| | - Hillel Adesnik
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
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21
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Hayden DJ, Finnie PSB, Thomazeau A, Li AY, Cooke SF, Bear MF. Electrophysiological signatures of visual recognition memory across all layers of mouse V1. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.524429. [PMID: 36747661 PMCID: PMC9900851 DOI: 10.1101/2023.01.25.524429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
In mouse primary visual cortex (V1), familiar stimuli evoke significantly altered responses when compared to novel stimuli. This stimulus-selective response plasticity (SRP) was described originally as an increase in the magnitude of visual evoked potentials (VEPs) elicited in layer (L) 4 by familiar phase-reversing grating stimuli. SRP is dependent on NMDA receptors (NMDAR) and has been hypothesized to reflect potentiation of thalamocortical synapses in L4. However, recent evidence indicates that the synaptic modifications that manifest as SRP do not occur on L4 principal cells. To shed light on where and how SRP is induced and expressed, the present study had three related aims: (1) to confirm that NMDAR are required specifically in glutamatergic principal neurons of V1, (2) to investigate the consequences of deleting NMDAR specifically in L6, and (3) to use translaminar electrophysiological recordings to characterize SRP expression in different layers of V1. We find that knockout of NMDAR in L6 principal neurons disrupts SRP. Current-source density analysis of the VEP depth profile shows augmentation of short latency current sinks in layers 3, 4 and 6 in response to phase reversals of familiar stimuli. Multiunit recordings demonstrate that increased peak firing occurs to in response to phase reversals of familiar stimuli across all layers, but that activity between phase reversals is suppressed. Together, these data reveal important aspects of the underlying phenomenology of SRP and generate new hypotheses for the expression of experience-dependent plasticity in V1. Significance Statement Repeated exposure to stimuli that portend neither reward nor punishment leads to behavioral habituation, enabling organisms to dedicate attention to novel or otherwise significant features of the environment. The neural basis of this process, which is so often dysregulated in neurological and psychiatric disorders, remains poorly understood. Learning and memory of stimulus familiarity can be studied in mouse visual cortex by measuring electrophysiological responses to simple phase-reversing grating stimuli. The current study advances knowledge of this process by documenting changes in visual evoked potentials, neuronal spiking activity, and oscillations in the local field potentials across all layers of mouse visual cortex. In addition, we identify a key contribution of a specific population of neurons in layer 6 of visual cortex.
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22
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Wilson MN, Thunemann M, Liu X, Lu Y, Puppo F, Adams JW, Kim JH, Ramezani M, Pizzo DP, Djurovic S, Andreassen OA, Mansour AA, Gage FH, Muotri AR, Devor A, Kuzum D. Multimodal monitoring of human cortical organoids implanted in mice reveal functional connection with visual cortex. Nat Commun 2022; 13:7945. [PMID: 36572698 PMCID: PMC9792589 DOI: 10.1038/s41467-022-35536-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 12/09/2022] [Indexed: 12/27/2022] Open
Abstract
Human cortical organoids, three-dimensional neuronal cultures, are emerging as powerful tools to study brain development and dysfunction. However, whether organoids can functionally connect to a sensory network in vivo has yet to be demonstrated. Here, we combine transparent microelectrode arrays and two-photon imaging for longitudinal, multimodal monitoring of human cortical organoids transplanted into the retrosplenial cortex of adult mice. Two-photon imaging shows vascularization of the transplanted organoid. Visual stimuli evoke electrophysiological responses in the organoid, matching the responses from the surrounding cortex. Increases in multi-unit activity (MUA) and gamma power and phase locking of stimulus-evoked MUA with slow oscillations indicate functional integration between the organoid and the host brain. Immunostaining confirms the presence of human-mouse synapses. Implantation of transparent microelectrodes with organoids serves as a versatile in vivo platform for comprehensive evaluation of the development, maturation, and functional integration of human neuronal networks within the mouse brain.
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Affiliation(s)
- Madison N Wilson
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Martin Thunemann
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Xin Liu
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Yichen Lu
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Francesca Puppo
- Department of Pediatrics, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Jason W Adams
- Department of Pediatrics, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
| | - Jeong-Hoon Kim
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Mehrdad Ramezani
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Donald P Pizzo
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT Center, Oslo, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
- K. G. Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Center, Oslo, Norway
- K. G. Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Abed AlFatah Mansour
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Medical Neurobiology, The Hebrew University of Jerusalem, Ein Kerem-Jerusalem, Israel
| | - Fred H Gage
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Alysson R Muotri
- Department of Pediatrics, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, School of Medicine, La Jolla, CA, USA
- Center for Academic Research and Training in Anthropogeny, University of California San Diego, La Jolla, CA, USA
- Archealization Center, University of California San Diego, La Jolla, CA, USA
- Kavli Institute for Brain and Mind, University of California San Diego, La Jolla, CA, USA
| | - Anna Devor
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA.
| | - Duygu Kuzum
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.
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23
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Zhang S, Morrison J, Wang W, Greene E. Recognition of letters displayed as successive contour fragments. AIMS Neurosci 2022; 9:491-515. [PMID: 36660071 PMCID: PMC9826752 DOI: 10.3934/neuroscience.2022028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 12/01/2022] [Accepted: 12/04/2022] [Indexed: 12/14/2022] Open
Abstract
Shapes can be displayed as parts but perceived as a whole through feedforward and feedback mechanisms in the visual system, though the exact spatiotemporal relationships for this process are still unclear. Our experiments examined the integration of letter fragments that were displayed as a rapid sequence. We examined the effects of timing and masking on integration, hypothesizing that increasing the timing interval between frames would impair recognition by disrupting contour linkage. We further used different mask types, a full-field pattern mask and a smaller strip mask, to examine the effects of global vs local masking on integration. We found that varying mask types and contrast produced a greater decline in recognition than was found when persistence or mask density was manipulated. The study supports prior work on letter recognition and provides greater insight into the spatiotemporal factors that contribute to the identification of shapes.
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Affiliation(s)
- Sherry Zhang
- Department of Psychology, University of Southern California, Los Angeles, CA 90007, United States of America,* Correspondence:
| | - Jack Morrison
- Neuropsychology Foundation, Sun Valley, CA 91353, United States of America
| | - Wei Wang
- Departments of Medicine and Neurology, Brigham and Women's Hospital. Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, United States of America
| | - Ernest Greene
- Department of Psychology, University of Southern California, Los Angeles, CA 90007, United States of America
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24
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Rodrigues FR, Papanikolaou A, Holeniewska J, Phillips KG, Saleem AB, Solomon SG. Altered low-frequency brain rhythms precede changes in gamma power during tauopathy. iScience 2022; 25:105232. [PMID: 36274955 PMCID: PMC9579020 DOI: 10.1016/j.isci.2022.105232] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 08/22/2022] [Accepted: 09/25/2022] [Indexed: 11/12/2022] Open
Abstract
Neurodegenerative disorders are associated with widespread disruption to brain activity and brain rhythms. Some disorders are linked to dysfunction of the membrane-associated protein Tau. Here, we ask how brain rhythms are affected in rTg4510 mouse model of tauopathy, at an early stage of tauopathy (5 months), and at a more advanced stage (8 months). We measured brain rhythms in primary visual cortex in presence or absence of visual stimulation, while monitoring pupil diameter and locomotion to establish behavioral state. At 5 months, we found increased low-frequency rhythms during resting state in tauopathic animals, associated with periods of abnormally increased neural synchronization. At 8 months, this increase in low-frequency rhythms was accompanied by a reduction of power in the gamma range. Our results therefore show that slower rhythms are impaired earlier than gamma rhythms in this model of tauopathy, and suggest that electrophysiological measurements can track the progression of tauopathic neurodegeneration.
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Affiliation(s)
- Fabio R. Rodrigues
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, UK
| | - Amalia Papanikolaou
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, UK
| | - Joanna Holeniewska
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, UK
| | | | - Aman B. Saleem
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, UK
| | - Samuel G. Solomon
- UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, UK
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25
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Meneghetti N, Cerri C, Vannini E, Tantillo E, Tottene A, Pietrobon D, Caleo M, Mazzoni A. Synaptic alterations in visual cortex reshape contrast-dependent gamma oscillations and inhibition-excitation ratio in a genetic mouse model of migraine. J Headache Pain 2022; 23:125. [PMID: 36175826 PMCID: PMC9523950 DOI: 10.1186/s10194-022-01495-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 08/09/2022] [Indexed: 11/21/2022] Open
Abstract
Background Migraine affects a significant fraction of the world population, yet its etiology is not completely understood. In vitro results highlighted thalamocortical and intra-cortical glutamatergic synaptic gain-of-function associated with a monogenic form of migraine (familial-hemiplegic-migraine-type-1: FHM1). However, how these alterations reverberate on cortical activity remains unclear. As altered responsivity to visual stimuli and abnormal processing of visual sensory information are common hallmarks of migraine, herein we investigated the effects of FHM1-driven synaptic alterations in the visual cortex of awake mice. Methods We recorded extracellular field potentials from the primary visual cortex (V1) of head-fixed awake FHM1 knock-in (n = 12) and wild type (n = 12) mice in response to square-wave gratings with different visual contrasts. Additionally, we reproduced in silico the obtained experimental results with a novel spiking neurons network model of mouse V1, by implementing in the model both the synaptic alterations characterizing the FHM1 genetic mouse model adopted. Results FHM1 mice displayed similar amplitude but slower temporal evolution of visual evoked potentials. Visual contrast stimuli induced a lower increase of multi-unit activity in FHM1 mice, while the amount of information content about contrast level remained, however, similar to WT. Spectral analysis of the local field potentials revealed an increase in the β/low γ range of WT mice following the abrupt reversal of contrast gratings. Such frequency range transitioned to the high γ range in FHM1 mice. Despite this change in the encoding channel, these oscillations preserved the amount of information conveyed about visual contrast. The computational model showed how these network effects may arise from a combination of changes in thalamocortical and intra-cortical synaptic transmission, with the former inducing a lower cortical activity and the latter inducing the higher frequencies ɣ oscillations. Conclusions Contrast-driven ɣ modulation in V1 activity occurs at a much higher frequency in FHM1. This is likely to play a role in the altered processing of visual information. Computational studies suggest that this shift is specifically due to enhanced cortical excitatory transmission. Our network model can help to shed light on the relationship between cellular and network levels of migraine neural alterations. Graphical Abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s10194-022-01495-9.
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Affiliation(s)
- Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, 56025, Pisa, Italy.,Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, 56025, Pisa, Italy
| | - Chiara Cerri
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Fondazione Umberto Veronesi, 20122, Milan, Italy.,Department of Pharmacy, University of Pisa, 56126, Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Fondazione Umberto Veronesi, 20122, Milan, Italy
| | - Elena Tantillo
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Fondazione Pisana per la Scienza Onlus (FPS), 56017, Pisa, Italy.,Scuola Normale Superiore, 56100, Pisa, Italy
| | - Angelita Tottene
- Department of Biomedical Sciences, University of Padova, 35131, Padova, Italy
| | - Daniela Pietrobon
- Department of Biomedical Sciences, University of Padova, 35131, Padova, Italy.,Padova Neuroscience Center, University of Padova, 35131, Padova, Italy.,CNR Institute of Neuroscience, 35131, Padova, Italy
| | - Matteo Caleo
- Neuroscience Institute, National Research Council (CNR), 56124, Pisa, Italy.,Department of Biomedical Sciences, University of Padova, 35131, Padova, Italy.,Padova Neuroscience Center, University of Padova, 35131, Padova, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, 56025, Pisa, Italy. .,Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, 56025, Pisa, Italy.
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26
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Wagatsuma N, Nobukawa S, Fukai T. A microcircuit model involving parvalbumin, somatostatin, and vasoactive intestinal polypeptide inhibitory interneurons for the modulation of neuronal oscillation during visual processing. Cereb Cortex 2022; 33:4459-4477. [PMID: 36130096 PMCID: PMC10110453 DOI: 10.1093/cercor/bhac355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 08/06/2022] [Accepted: 08/08/2022] [Indexed: 11/12/2022] Open
Abstract
Various subtypes of inhibitory interneurons contact one another to organize cortical networks. Most cortical inhibitory interneurons express 1 of 3 genes: parvalbumin (PV), somatostatin (SOM), or vasoactive intestinal polypeptide (VIP). This diversity of inhibition allows the flexible regulation of neuronal responses within and between cortical areas. However, the exact roles of these interneuron subtypes and of excitatory pyramidal (Pyr) neurons in regulating neuronal network activity and establishing perception (via interactions between feedforward sensory and feedback attentional signals) remain largely unknown. To explore the regulatory roles of distinct neuronal types in cortical computation, we developed a computational microcircuit model with biologically plausible visual cortex layers 2/3 that combined Pyr neurons and the 3 inhibitory interneuron subtypes to generate network activity. In simulations with our model, inhibitory signals from PV and SOM neurons preferentially induced neuronal firing at gamma (30-80 Hz) and beta (20-30 Hz) frequencies, respectively, in agreement with observed physiological results. Furthermore, our model indicated that rapid inhibition from VIP to SOM subtypes underlies marked attentional modulation for low-gamma frequency (30-50 Hz) in Pyr neuron responses. Our results suggest the distinct but cooperative roles of inhibitory interneuron subtypes in the establishment of visual perception.
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Affiliation(s)
- Nobuhiko Wagatsuma
- Faculty of Science, Toho University, 2-2-1 Miyama, Funabashi, Chiba 274-8510, Japan
| | - Sou Nobukawa
- Department of Computer Science, Chiba Institute of Technology, 2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan.,Department of Preventive Intervention for Psychiatric Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawa-Higashi, Kodaira, Tokyo 187-8502, Japan
| | - Tomoki Fukai
- Neural Coding and Brain Computing Unit, Okinawa Institute of Science and Technology Graduate University, 1919-1 Tancha, Onna-son, Kunigami-gun, Okinawa 904-0495, Japan
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27
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Hou B, Chen K, Jia A, Liu S, Bao X, Liao B, Zhao YL, Guo D, Xia Y, Yao D. Visually induced γ band rhythm in spatial summation beyond the receptive field in mouse primary visual cortex. Cereb Cortex 2022; 33:4350-4359. [PMID: 36124829 DOI: 10.1093/cercor/bhac347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/12/2022] Open
Abstract
Recent studies in many kinds of mammals have established the existence of multiple γ rhythms in the cerebral cortex subserving different functions. In the primary visual cortex (V1), visually induced γ rhythms are dependent on stimulus features. However, experimental findings of γ power induced by varying the size of the drifting grating are inconsistent. Here, we reinvestigated the spatial summation properties of visually induced spike and γ rhythm activities in mouse V1. Our results show that drifting sinusoidal grating stimuli mainly induce 2 γ band rhythms, including a low-frequency band (25-45 Hz) and a high-frequency band (55-75 Hz). Unlike previous findings, we discovered that visually induced γ power could also exhibit extrareceptive field (ERF) modulatory properties. The modulation by ERF stimulation could be either suppressive, countersuppressive, or nonsuppressive, mostly similar to the local spike activity. Moreover, further analysis of the neuron group exhibiting surround suppression in both spike and γ activity revealed that the strength of the surround suppression and the receptive field size showed moderate correlations between measurements by spike and γ rhythm activity. Our findings improve the understanding of the characteristics and neural mechanisms of induced γ rhythms in visual spatial summation.
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Affiliation(s)
- BoJun Hou
- Sichuan Provincial People's Hospital, Medical School, University of Electronic Science and Technology of China, Xiyuan road 2006, Chengdu 611731, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Ke Chen
- Sichuan Provincial People's Hospital, Medical School, University of Electronic Science and Technology of China, Xiyuan road 2006, Chengdu 611731, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Ang Jia
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Shanshan Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xiaojing Bao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Baitao Liao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yi Lei Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Daqing Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yang Xia
- Sichuan Provincial People's Hospital, Medical School, University of Electronic Science and Technology of China, Xiyuan road 2006, Chengdu 611731, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Dezhong Yao
- Sichuan Provincial People's Hospital, Medical School, University of Electronic Science and Technology of China, Xiyuan road 2006, Chengdu 611731, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Xiyuan road 2006, Chengdu 611731, China
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28
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Panarese A, Vissani M, Meneghetti N, Vannini E, Cracchiolo M, Micera S, Caleo M, Mazzoni A, Restani L. Disruption of layer-specific visual processing in a model of focal neocortical epilepsy. Cereb Cortex 2022; 33:4173-4187. [PMID: 36089833 DOI: 10.1093/cercor/bhac335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 07/25/2022] [Accepted: 07/26/2022] [Indexed: 11/12/2022] Open
Abstract
The epileptic brain is the result of a sequence of events transforming normal neuronal populations into hyperexcitable networks supporting recurrent seizure generation. These modifications are known to induce fundamental alterations of circuit function and, ultimately, of behavior. However, how hyperexcitability affects information processing in cortical sensory circuits is not yet fully understood. Here, we investigated interlaminar alterations in sensory processing of the visual cortex in a mouse model of focal epilepsy. We found three main circuit dynamics alterations in epileptic mice: (i) a spreading of visual contrast-driven gamma modulation across layers, (ii) an increase in firing rate that is layer-unspecific for excitatory units and localized in infragranular layers for inhibitory neurons, and (iii) a strong and contrast-dependent locking of firing units to network activity. Altogether, our data show that epileptic circuits display a functional disruption of layer-specific organization of visual sensory processing, which could account for visual dysfunction observed in epileptic subjects. Understanding these mechanisms paves the way to circuital therapeutic interventions for epilepsy.
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Affiliation(s)
- Alessandro Panarese
- The Biorobotics Institute, Scuola Superiore Sant'Anna, viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.,Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà, 56127 Pisa, Italy
| | - Matteo Vissani
- The Biorobotics Institute, Scuola Superiore Sant'Anna, viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.,Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà, 56127 Pisa, Italy
| | - Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.,Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà, 56127 Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), via G. Moruzzi 1, 56124 Pisa, Italy
| | - Marina Cracchiolo
- The Biorobotics Institute, Scuola Superiore Sant'Anna, viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.,Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà, 56127 Pisa, Italy
| | - Silvestro Micera
- The Biorobotics Institute, Scuola Superiore Sant'Anna, viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.,Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà, 56127 Pisa, Italy.,Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, 1202 Geneva, Switzerland
| | - Matteo Caleo
- Neuroscience Institute, National Research Council (CNR), via G. Moruzzi 1, 56124 Pisa, Italy.,Department of Biomedical Sciences, University of Padua, via G. Colombo 3, 35121 Padua, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.,Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà, 56127 Pisa, Italy
| | - Laura Restani
- Neuroscience Institute, National Research Council (CNR), via G. Moruzzi 1, 56124 Pisa, Italy
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29
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Visual evoked feedforward-feedback traveling waves organize neural activity across the cortical hierarchy in mice. Nat Commun 2022; 13:4754. [PMID: 35963850 PMCID: PMC9376099 DOI: 10.1038/s41467-022-32378-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 07/27/2022] [Indexed: 12/26/2022] Open
Abstract
Sensory processing is distributed among many brain regions that interact via feedforward and feedback signaling. Neuronal oscillations have been shown to mediate intercortical feedforward and feedback interactions. Yet, the macroscopic structure of the multitude of such oscillations remains unclear. Here, we show that simple visual stimuli reliably evoke two traveling waves with spatial wavelengths that cover much of the cerebral hemisphere in awake mice. 30-50 Hz feedforward waves arise in primary visual cortex (V1) and propagate rostrally, while 3-6 Hz feedback waves originate in the association cortex and flow caudally. The phase of the feedback wave modulates the amplitude of the feedforward wave and synchronizes firing between V1 and parietal cortex. Altogether, these results provide direct experimental evidence that visual evoked traveling waves percolate through the cerebral cortex and coordinate neuronal activity across broadly distributed networks mediating visual processing.
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30
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Uran C, Peter A, Lazar A, Barnes W, Klon-Lipok J, Shapcott KA, Roese R, Fries P, Singer W, Vinck M. Predictive coding of natural images by V1 firing rates and rhythmic synchronization. Neuron 2022; 110:1240-1257.e8. [PMID: 35120628 PMCID: PMC8992798 DOI: 10.1016/j.neuron.2022.01.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 11/22/2021] [Accepted: 01/04/2022] [Indexed: 01/12/2023]
Abstract
Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that sensory responses result from comparisons between bottom-up inputs and contextual predictions, a process in which rates and synchronization may play distinct roles. We recorded from awake macaque V1 and developed a technique to quantify stimulus predictability for natural images based on self-supervised, generative neural networks. We find that neuronal firing rates were mainly modulated by the contextual predictability of higher-order image features, which correlated strongly with human perceptual similarity judgments. By contrast, V1 gamma (γ)-synchronization increased monotonically with the contextual predictability of low-level image features and emerged exclusively for larger stimuli. Consequently, γ-synchronization was induced by natural images that are highly compressible and low-dimensional. Natural stimuli with low predictability induced prominent, late-onset beta (β)-synchronization, likely reflecting cortical feedback. Our findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.
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Affiliation(s)
- Cem Uran
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 AJ Nijmegen, the Netherlands.
| | - Alina Peter
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Andreea Lazar
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - William Barnes
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany
| | - Johanna Klon-Lipok
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany
| | - Katharine A Shapcott
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Frankfurt Institute for Advanced Studies, 60438 Frankfurt, Germany
| | - Rasmus Roese
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Donders Institute for Brain, Cognition and Behaviour, Department of Biophysics, Radboud University Nijmegen, 6525 AJ Nijmegen, the Netherlands
| | - Wolf Singer
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany; Frankfurt Institute for Advanced Studies, 60438 Frankfurt, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 AJ Nijmegen, the Netherlands.
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31
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Li X, Li Z, Yang W, Wu Z, Wang J. Bidirectionally Regulating Gamma Oscillations in Wilson-Cowan Model by Self-Feedback Loops: A Computational Study. Front Syst Neurosci 2022; 16:723237. [PMID: 35264933 PMCID: PMC8900601 DOI: 10.3389/fnsys.2022.723237] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 01/06/2022] [Indexed: 11/13/2022] Open
Abstract
The Wilson-Cowan model can emulate gamma oscillations, and thus is extensively used to research the generation of gamma oscillations closely related to cognitive functions. Previous studies have revealed that excitatory and inhibitory inputs to the model can modulate its gamma oscillations. Inhibitory and excitatory self-feedback loops are important structural features of the model, however, its functional role in the regulation of gamma oscillations in the model is still unclear. In the present study, bifurcation analysis and spectrum analysis are employed to elucidate the regulating mechanism of gamma oscillations underlined by the inhibitory and excitatory self-feedback loops, especially how the two self-feedback loops cooperate to generate the gamma oscillations and regulate the oscillation frequency. The present results reveal that, on one hand, the inhibitory self-feedback loop is not conducive to the generation of gamma oscillations, and increased inhibitory self-feedback strength facilitates the enhancement of the oscillation frequency. On the other hand, the excitatory self-feedback loop promotes the generation of gamma oscillations, and increased excitatory self-feedback strength leads to the decrease of oscillation frequency. Finally, theoretical analysis is conducted to provide explain on how the two self-feedback loops play a crucial role in the generation and regulation of neural oscillations in the model. To sum up, Inhibitory and excitatory self-feedback loops play a complementary role in generating and regulating the gamma oscillation in Wilson-Cowan model, and cooperate to bidirectionally regulate the gamma-oscillation frequency in a more flexible manner. These results might provide testable hypotheses for future experimental research.
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Affiliation(s)
- XiuPing Li
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - ZhengHong Li
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - WanMei Yang
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Zhen Wu
- Department of Psychology, Tianjin University of Technology and Education, Tianjin, China
| | - JunSong Wang
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
- College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China
- *Correspondence: JunSong Wang,
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32
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Barzegaran E, Plomp G. Four concurrent feedforward and feedback networks with different roles in the visual cortical hierarchy. PLoS Biol 2022; 20:e3001534. [PMID: 35143472 PMCID: PMC8865670 DOI: 10.1371/journal.pbio.3001534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 02/23/2022] [Accepted: 01/10/2022] [Indexed: 11/18/2022] Open
Abstract
Visual stimuli evoke fast-evolving activity patterns that are distributed across multiple cortical areas. These areas are hierarchically structured, as indicated by their anatomical projections, but how large-scale feedforward and feedback streams are functionally organized in this system remains an important missing clue to understanding cortical processing. By analyzing visual evoked responses in laminar recordings from 6 cortical areas in awake mice, we uncovered a dominant feedforward network with scale-free interactions in the time domain. In addition, we established the simultaneous presence of a gamma band feedforward and 2 low frequency feedback networks, each with a distinct laminar functional connectivity profile, frequency spectrum, temporal dynamics, and functional hierarchy. We could identify distinct roles for each of these 4 processing streams, by leveraging stimulus contrast effects, analyzing receptive field (RF) convergency along functional interactions, and determining relationships to spiking activity. Our results support a dynamic dual counterstream view of hierarchical processing and provide new insight into how separate functional streams can simultaneously and dynamically support visual processes. Visual stimuli evoke fast-evolving activity patterns that are distributed across multiple cortical areas, but how large-scale feedforward and feedback streams are functionally organized in this system remains unclear. Visual evoked responses in laminar recordings from six cortical areas in awake mice reveal how layers and rhythms dynamically orchestrate functional streams in vision.
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Affiliation(s)
- Elham Barzegaran
- Perceptual Networks Group, Department of Psychology, University of Fribourg, Fribourg, Switzerland
- * E-mail: (EB); (GP)
| | - Gijs Plomp
- Perceptual Networks Group, Department of Psychology, University of Fribourg, Fribourg, Switzerland
- * E-mail: (EB); (GP)
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33
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Gamma rhythms in the visual cortex: functions and mechanisms. Cogn Neurodyn 2021; 16:745-756. [PMID: 35847544 PMCID: PMC9279528 DOI: 10.1007/s11571-021-09767-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/09/2021] [Accepted: 12/05/2021] [Indexed: 01/18/2023] Open
Abstract
Gamma-band activity, peaking around 30–100 Hz in the local field potential's power spectrum, has been found and intensively studied in many brain regions. Although gamma is thought to play a critical role in processing neural information in the brain, its cognitive functions and neural mechanisms remain unclear or debatable. Experimental studies showed that gamma rhythms are stochastic in time and vary with visual stimuli. Recent studies further showed that multiple rhythms coexist in V1 with distinct origins in different species. While all these experimental facts are a challenge for understanding the functions of gamma in the visual cortex, there are many signs of progress in computational studies. This review summarizes and discusses studies on gamma in the visual cortex from multiple perspectives and concludes that gamma rhythms are still a mystery. Combining experimental and computational studies seems the best way forward in the future.
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34
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Schneider M, Broggini AC, Dann B, Tzanou A, Uran C, Sheshadri S, Scherberger H, Vinck M. A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power. Neuron 2021; 109:4050-4067.e12. [PMID: 34637706 PMCID: PMC8691951 DOI: 10.1016/j.neuron.2021.09.037] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 07/14/2021] [Accepted: 09/17/2021] [Indexed: 11/21/2022]
Abstract
Inter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communication and naturally emerges because spiking activity in a sending area causes post-synaptic potentials both in the same and in other areas. Consequently, coherence depends in a lawful manner on power and phase-locking in the sender and connectivity. Changes in oscillatory power explained prominent changes in fronto-parietal and LGN-V1 coherence across behavioral conditions. Optogenetic experiments and excitatory-inhibitory network simulations identified afferent synaptic inputs rather than spiking entrainment as the principal determinant of coherence. These findings suggest that unique spectral profiles of different brain areas automatically give rise to large-scale coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.
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Affiliation(s)
- Marius Schneider
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
| | - Ana Clara Broggini
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | | | - Athanasia Tzanou
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Cem Uran
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Swathi Sheshadri
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Hansjörg Scherberger
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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35
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Chrobok L, Belle MDC, Myung J. From Fast Oscillations to Circadian Rhythms: Coupling at Multiscale Frequency Bands in the Rodent Subcortical Visual System. Front Physiol 2021; 12:738229. [PMID: 34899375 PMCID: PMC8662821 DOI: 10.3389/fphys.2021.738229] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
The subcortical visual system (SVS) is a unique collection of brain structures localised in the thalamus, hypothalamus and midbrain. The SVS receives ambient light inputs from retinal ganglion cells and integrates this signal with internal homeostatic demands to influence physiology. During this processing, a multitude of oscillatory frequency bands coalesces, with some originating from the retinas, while others are intrinsically generated in the SVS. Collectively, these rhythms are further modulated by the day and night cycle. The multiplexing of these diverse frequency bands (from circadian to infra-slow and gamma oscillations) makes the SVS an interesting system to study coupling at multiscale frequencies. We review the functional organisation of the SVS, and the various frequencies generated and processed by its neurons. We propose a perspective on how these different frequency bands couple with one another to synchronise the activity of the SVS to control physiology and behaviour.
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Affiliation(s)
- Lukasz Chrobok
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Mino D C Belle
- Institute of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Jihwan Myung
- Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, Taipei Medical University-Shuang Ho Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan
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36
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Han C, Wang T, Yang Y, Wu Y, Li Y, Dai W, Zhang Y, Wang B, Yang G, Cao Z, Kang J, Wang G, Li L, Yu H, Yeh CI, Xing D. Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex. PLoS Biol 2021; 19:e3001466. [PMID: 34932558 PMCID: PMC8691622 DOI: 10.1371/journal.pbio.3001466] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 11/03/2021] [Indexed: 12/26/2022] Open
Abstract
Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial frequency (SF) signals and had different neural origins. The low gamma (LG; 25 to 40 Hz) rhythm was generated at the V1 superficial layer and preferred a higher SF compared with spike activity, whereas both the medium gamma (MG; 40 to 65 Hz), generated at the cortical level, and the high gamma HG; (65 to 85 Hz), originated precortically, preferred lower SF information. Furthermore, compared with the rates of spike activity, the powers of the 3 gammas had better performance in discriminating the edge and surface of simple objects. These findings suggest that gamma rhythms reflect the neural dynamics of neural circuitries that process different SF information in the visual system, which may be crucial for multiplexing SF information and synchronizing different features of an object.
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Affiliation(s)
- Chuanliang Han
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yi Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yang Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Weifeng Dai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yange Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Bin Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Guanzhong Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ziqi Cao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jian Kang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Gang Wang
- Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Liang Li
- Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Hongbo Yu
- Vision Research Laboratory, Center for Brain Science Research and School of Life Sciences, Fudan University, Shanghai, China
| | - Chun-I Yeh
- Department of Psychology, National Taiwan University, Taipei, Taiwan, China
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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37
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Kat R, van den Berg B, Perenboom MJ, Schenke M, van den Maagdenberg AM, Bruining H, Tolner EA, Kas MJ. EEG-based visual deviance detection in freely behaving mice. Neuroimage 2021; 245:118757. [PMID: 34838751 DOI: 10.1016/j.neuroimage.2021.118757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/09/2021] [Accepted: 11/23/2021] [Indexed: 11/18/2022] Open
Abstract
The mouse is widely used as an experimental model to study visual processing. To probe how the visual system detects changes in the environment, functional paradigms in freely behaving mice are strongly needed. We developed and validated the first EEG-based method to investigate visual deviance detection in freely behaving mice. Mice with EEG implants were exposed to a visual deviant detection paradigm that involved changes in light intensity as standard and deviant stimuli. By subtracting the standard from the deviant evoked waveform, deviant detection was evident as bi-phasic negativity (starting around 70 ms) in the difference waveform. Additionally, deviance-associated evoked (beta/gamma) and induced (gamma) oscillatory responses were found. We showed that the results were stimulus-independent by applying a "flip-flop" design and the results showed good repeatability in an independent measurement. Together, we put forward a validated, easy-to-use paradigm to measure visual deviance processing in freely behaving mice.
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Affiliation(s)
- Renate Kat
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Nijenborgh 7, 9747 AG, Groningen, the Netherlands.
| | - Berry van den Berg
- Faculty of Behavioral and Social Sciences, Cognitive Neuroscience, Department of Experimental Psychology, University of Groningen, Grote Kruisstraat 2/1, 9712 TS, Groningen, the Netherlands.
| | - Matthijs Jl Perenboom
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands.
| | - Maarten Schenke
- Department of Human Genetics, Leiden University Medical Center, Einthovenweg 20, 2300 RC, Leiden, the Netherlands
| | - Arn Mjm van den Maagdenberg
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands; Department of Human Genetics, Leiden University Medical Center, Einthovenweg 20, 2300 RC, Leiden, the Netherlands.
| | - Hilgo Bruining
- Department of Child and Adolescent Psychiatry, Amsterdam University Medical Center, University of Amsterdam, Postbus 7057, 1007 MB, Amsterdam, the Netherlands.
| | - Else A Tolner
- Department of Neurology, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, the Netherlands; Department of Human Genetics, Leiden University Medical Center, Einthovenweg 20, 2300 RC, Leiden, the Netherlands.
| | - Martien Jh Kas
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Nijenborgh 7, 9747 AG, Groningen, the Netherlands.
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38
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Chrobok L, Pradel K, Janik ME, Sanetra AM, Bubka M, Myung J, Ridla Rahim A, Klich JD, Jeczmien-Lazur JS, Palus-Chramiec K, Lewandowski MH. Intrinsic circadian timekeeping properties of the thalamic lateral geniculate nucleus. J Neurosci Res 2021; 99:3306-3324. [PMID: 34758124 DOI: 10.1002/jnr.24973] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/07/2021] [Accepted: 09/17/2021] [Indexed: 01/08/2023]
Abstract
Circadian rhythmicity in mammals is sustained by the central brain clock-the suprachiasmatic nucleus of the hypothalamus (SCN), entrained to the ambient light-dark conditions through a dense retinal input. However, recent discoveries of autonomous clock gene expression cast doubt on the supremacy of the SCN and suggest circadian timekeeping mechanisms devolve to local brain clocks. Here, we use a combination of molecular, electrophysiological, and optogenetic tools to evaluate intrinsic clock properties of the main retinorecipient thalamic center-the lateral geniculate nucleus (LGN) in male rats and mice. We identify the dorsolateral geniculate nucleus as a slave oscillator, which exhibits core clock gene expression exclusively in vivo. Additionally, we provide compelling evidence for intrinsic clock gene expression accompanied by circadian variation in neuronal activity in the intergeniculate leaflet and ventrolateral geniculate nucleus (VLG). Finally, our optogenetic experiments propose the VLG as a light-entrainable oscillator, whose phase may be advanced by retinal input at the beginning of the projected night. Altogether, this study for the first time demonstrates autonomous timekeeping mechanisms shaping circadian physiology of the LGN.
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Affiliation(s)
- Lukasz Chrobok
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Kamil Pradel
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Marcelina Elzbieta Janik
- Department of Glycoconjugate Biochemistry, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Anna Magdalena Sanetra
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Monika Bubka
- Department of Glycoconjugate Biochemistry, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Jihwan Myung
- Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, Taipei Medical University-Shuang Ho Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan
| | - Amalia Ridla Rahim
- Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Centre, Taipei Medical University-Shuang Ho Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan
| | - Jasmin Daniela Klich
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Jagoda Stanislawa Jeczmien-Lazur
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Katarzyna Palus-Chramiec
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
| | - Marian Henryk Lewandowski
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, Poland
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39
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Narrow and Broad γ Bands Process Complementary Visual Information in Mouse Primary Visual Cortex. eNeuro 2021; 8:ENEURO.0106-21.2021. [PMID: 34663617 PMCID: PMC8570688 DOI: 10.1523/eneuro.0106-21.2021] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 06/03/2021] [Accepted: 06/22/2021] [Indexed: 11/21/2022] Open
Abstract
γ Band plays a key role in the encoding of visual features in the primary visual cortex (V1). In rodents V1 two ranges within the γ band are sensitive to contrast: a broad γ band (BB) increasing with contrast, and a narrow γ band (NB), peaking at ∼60 Hz, decreasing with contrast. The functional roles of the two bands and the neural circuits originating them are not completely clear yet. Here, we show, combining experimental and simulated data, that in mice V1 (1) BB carries information about high contrast and NB about low contrast; (2) BB modulation depends on excitatory-inhibitory interplay in the cortex, while NB modulation is because of entrainment to the thalamic drive. In awake mice presented with alternating gratings, NB power progressively decreased from low to intermediate levels of contrast where it reached a plateau. Conversely, BB power was constant across low levels of contrast, but it progressively increased from intermediate to high levels of contrast. Furthermore, BB response was stronger immediately after contrast reversal, while the opposite held for NB. These complementary modulations were reproduced by a recurrent excitatory-inhibitory leaky integrate-and-fire network provided that the thalamic inputs were composed of a sustained and a periodic component having complementary sensitivity ranges. These results show that in rodents the thalamic-driven NB plays a specific key role in encoding visual contrast. Moreover, we propose a simple and effective network model of response to visual stimuli in rodents that might help in investigating network dysfunctions of pathologic visual information processing.
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40
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Speed A, Haider B. Probing mechanisms of visual spatial attention in mice. Trends Neurosci 2021; 44:822-836. [PMID: 34446296 PMCID: PMC8484049 DOI: 10.1016/j.tins.2021.07.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/05/2021] [Accepted: 07/30/2021] [Indexed: 11/25/2022]
Abstract
The role of spatial attention for visual perception has been thoroughly studied in primates, but less so in mice. Several behavioral tasks in mice reveal spatial attentional effects, with similarities to observations in primates. Pairing these tasks with large-scale, cell-type-specific techniques could enable deeper access to underlying mechanisms, and help define the utility and limitations of resolving attentional effects on visual perception and neural activity in mice. In this Review, we evaluate behavioral and neural evidence for visual spatial attention in mice; assess how specializations of the mouse visual system and behavioral repertoire impact interpretation of spatial attentional effects; and outline how several measurement and manipulation techniques in mice could precisely test and refine models of attentional modulation across scales.
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Affiliation(s)
- Anderson Speed
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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41
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Hayden DJ, Montgomery DP, Cooke SF, Bear MF. Visual Recognition Is Heralded by Shifts in Local Field Potential Oscillations and Inhibitory Networks in Primary Visual Cortex. J Neurosci 2021; 41:6257-6272. [PMID: 34103358 PMCID: PMC8287992 DOI: 10.1523/jneurosci.0391-21.2021] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/18/2021] [Accepted: 05/19/2021] [Indexed: 11/22/2022] Open
Abstract
Learning to recognize and filter familiar, irrelevant sensory stimuli eases the computational burden on the cerebral cortex. Inhibition is a candidate mechanism in this filtration process, and oscillations in the cortical local field potential (LFP) serve as markers of the engagement of different inhibitory neurons. We show here that LFP oscillatory activity in visual cortex is profoundly altered as male and female mice learn to recognize an oriented grating stimulus-low-frequency (∼15 Hz peak) power sharply increases, whereas high-frequency (∼65 Hz peak) power decreases. These changes report recognition of the familiar pattern as they disappear when the stimulus is rotated to a novel orientation. Two-photon imaging of neuronal activity reveals that parvalbumin-expressing inhibitory neurons disengage with familiar stimuli and reactivate to novelty, whereas somatostatin-expressing inhibitory neurons show opposing activity patterns. We propose a model in which the balance of two interacting interneuron circuits shifts as novel stimuli become familiar.SIGNIFICANCE STATEMENT Habituation, familiarity, and novelty detection are fundamental cognitive processes that enable organisms to adaptively filter meaningless stimuli and focus attention on potentially important elements of their environment. We have shown that this process can be studied fruitfully in the mouse primary visual cortex by using simple grating stimuli for which novelty and familiarity are defined by orientation and by measuring stimulus-evoked and continuous local field potentials. Altered event-related and spontaneous potentials, and deficient habituation, are well-documented features of several neurodevelopmental psychiatric disorders. The paradigm described here will be valuable to interrogate the origins of these signals and the meaning of their disruption more deeply.
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Affiliation(s)
- Dustin J Hayden
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Daniel P Montgomery
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Samuel F Cooke
- Medical Research Council Centre for Neurodevelopmental Disorders, Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London SE5 9RT, England
| | - Mark F Bear
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
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42
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Del Rosario J, Speed A, Arrowood H, Motz C, Pardue M, Haider B. Diminished Cortical Excitation and Elevated Inhibition During Perceptual Impairments in a Mouse Model of Autism. Cereb Cortex 2021; 31:3462-3474. [PMID: 33677512 PMCID: PMC8525192 DOI: 10.1093/cercor/bhab025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 01/14/2021] [Accepted: 01/21/2021] [Indexed: 01/02/2023] Open
Abstract
Sensory impairments are a core feature of autism spectrum disorder (ASD). These impairments affect visual perception and have been hypothesized to arise from imbalances in cortical excitatory and inhibitory activity. There is conflicting evidence for this hypothesis from several recent studies of transgenic mouse models of ASD; crucially, none have measured activity from identified excitatory and inhibitory neurons during simultaneous impairments of sensory perception. Here, we directly recorded putative excitatory and inhibitory population spiking in primary visual cortex (V1) while simultaneously measuring visual perceptual behavior in CNTNAP2-/- knockout (KO) mice. We observed quantitative impairments in the speed, accuracy, and contrast sensitivity of visual perception in KO mice. During these perceptual impairments, stimuli evoked more firing of inhibitory neurons and less firing of excitatory neurons, with reduced neural sensitivity to contrast. In addition, pervasive 3-10 Hz oscillations in superficial cortical layers 2/3 (L2/3) of KO mice degraded predictions of behavioral performance from neural activity. Our findings show that perceptual deficits relevant to ASD may be associated with elevated cortical inhibitory activity along with diminished and aberrant excitatory population activity in L2/3, a major source of feedforward projections to higher cortical regions.
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Affiliation(s)
- Joseph Del Rosario
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA 30332, USA
| | - Anderson Speed
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA 30332, USA
| | - Hayley Arrowood
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA 30332, USA
| | - Cara Motz
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA 30332, USA
- Atlanta VA Center for Visual and Neurocognitive Rehabilitation, Decatur, GA 30033, USA
| | - Machelle Pardue
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA 30332, USA
- Atlanta VA Center for Visual and Neurocognitive Rehabilitation, Decatur, GA 30033, USA
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA 30332, USA
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43
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Lantz CL, Quinlan EM. High-Frequency Visual Stimulation Primes Gamma Oscillations for Visually Evoked Phase Reset and Enhances Spatial Acuity. Cereb Cortex Commun 2021; 2:tgab016. [PMID: 33997786 PMCID: PMC8110461 DOI: 10.1093/texcom/tgab016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 02/24/2021] [Accepted: 02/24/2021] [Indexed: 11/12/2022] Open
Abstract
The temporal frequency of sensory stimulation is a decisive factor in the plasticity of perceptual detection thresholds. However, surprisingly little is known about how distinct temporal parameters of sensory input differentially recruit activity of neuronal circuits in sensory cortices. Here we demonstrate that brief repetitive visual stimulation induces long-term plasticity of visual responses revealed 24 h after stimulation and that the location and generalization of visual response plasticity is determined by the temporal frequency of the visual stimulation. Brief repetitive low-frequency stimulation (2 Hz) is sufficient to induce a visual response potentiation that is expressed exclusively in visual cortex layer 4 and in response to a familiar stimulus. In contrast, brief, repetitive high-frequency stimulation (HFS, 20 Hz) is sufficient to induce a visual response potentiation that is expressed in all cortical layers and transfers to novel stimuli. HFS induces a long-term suppression of the activity of fast-spiking interneurons and primes ongoing gamma oscillatory rhythms for phase reset by subsequent visual stimulation. This novel form of generalized visual response enhancement induced by HFS is paralleled by an increase in visual acuity, measured as improved performance in a visual detection task.
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Affiliation(s)
- Crystal L Lantz
- Department of Biology, University of Maryland, College Park, MD 20742, USA
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44
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Hoseini MS, Higashikubo B, Cho FS, Chang AH, Clemente-Perez A, Lew I, Ciesielska A, Stryker MP, Paz JT. Gamma rhythms and visual information in mouse V1 specifically modulated by somatostatin + neurons in reticular thalamus. eLife 2021; 10:e61437. [PMID: 33843585 PMCID: PMC8064751 DOI: 10.7554/elife.61437] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 04/11/2021] [Indexed: 01/15/2023] Open
Abstract
Visual perception in natural environments depends on the ability to focus on salient stimuli while ignoring distractions. This kind of selective visual attention is associated with gamma activity in the visual cortex. While the nucleus reticularis thalami (nRT) has been implicated in selective attention, its role in modulating gamma activity in the visual cortex remains unknown. Here, we show that somatostatin- (SST) but not parvalbumin-expressing (PV) neurons in the visual sector of the nRT preferentially project to the dorsal lateral geniculate nucleus (dLGN), and modulate visual information transmission and gamma activity in primary visual cortex (V1). These findings pinpoint the SST neurons in nRT as powerful modulators of the visual information encoding accuracy in V1 and represent a novel circuit through which the nRT can influence representation of visual information.
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Affiliation(s)
- Mahmood S Hoseini
- University of California, San Francisco, Department of PhysiologySan FranciscoUnited States
| | - Bryan Higashikubo
- Gladstone Institute of Neurological DiseaseSan FranciscoUnited States
| | - Frances S Cho
- Gladstone Institute of Neurological DiseaseSan FranciscoUnited States
- University of California, San Francisco, Neurosciences Graduate ProgramSan FranciscoUnited States
- University of California, San Francisco, Department of NeurologySan FranciscoUnited States
- Kavli Institute for Fundamental Neuroscience, University of California San FranciscoSan FranciscoUnited States
| | - Andrew H Chang
- Gladstone Institute of Neurological DiseaseSan FranciscoUnited States
- University of California, San Francisco, Department of NeurologySan FranciscoUnited States
| | - Alexandra Clemente-Perez
- Gladstone Institute of Neurological DiseaseSan FranciscoUnited States
- University of California, San Francisco, Neurosciences Graduate ProgramSan FranciscoUnited States
- University of California, San Francisco, Department of NeurologySan FranciscoUnited States
- Kavli Institute for Fundamental Neuroscience, University of California San FranciscoSan FranciscoUnited States
| | - Irene Lew
- Gladstone Institute of Neurological DiseaseSan FranciscoUnited States
- University of California, San Francisco, Department of NeurologySan FranciscoUnited States
| | - Agnieszka Ciesielska
- Gladstone Institute of Neurological DiseaseSan FranciscoUnited States
- University of California, San Francisco, Department of NeurologySan FranciscoUnited States
| | - Michael P Stryker
- University of California, San Francisco, Department of PhysiologySan FranciscoUnited States
- University of California, San Francisco, Neurosciences Graduate ProgramSan FranciscoUnited States
- Kavli Institute for Fundamental Neuroscience, University of California San FranciscoSan FranciscoUnited States
| | - Jeanne T Paz
- Gladstone Institute of Neurological DiseaseSan FranciscoUnited States
- University of California, San Francisco, Neurosciences Graduate ProgramSan FranciscoUnited States
- University of California, San Francisco, Department of NeurologySan FranciscoUnited States
- Kavli Institute for Fundamental Neuroscience, University of California San FranciscoSan FranciscoUnited States
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45
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The Prediction of Acute Postoperative Pain Based on Neural Oscillations Measured before the Surgery. Neural Plast 2021; 2021:5543974. [PMID: 33897775 PMCID: PMC8052183 DOI: 10.1155/2021/5543974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 03/05/2021] [Accepted: 03/16/2021] [Indexed: 11/17/2022] Open
Abstract
Even with an improved understanding of pain mechanisms and advances in perioperative pain management, inadequately controlled postoperative pain remains. Predicting acute postoperative pain based on presurgery physiological measures could provide valuable insights into individualized, effective analgesic strategies, thus helping improve the analgesic efficacy. Considering the strong correlation between pain perception and neural oscillations, we hypothesize that acute postoperative pain could be predicted by neural oscillations measured shortly before the surgery. Here, we explored the relationship between neural oscillations 2 hours before the thoracoscopic surgery and the subjective intensity of acute postoperative pain. The spectral power density of resting-state beta and gamma band oscillations at the frontocentral region was significantly different between patients with different levels of acute postoperative pain (i.e., low pain vs. moderate/high pain). A positive correlation was also observed between the spectral power density of resting-state beta and gamma band oscillations and subjective reports of postoperative pain. Then, we predicted the level of acute postoperative pain based on features of neural oscillations using machine learning techniques, which achieved a prediction accuracy of 92.54% and a correlation coefficient between the real pain intensities and the predicted pain intensities of 0.84. Altogether, the prediction of acute postoperative pain based on neural oscillations measured before the surgery is feasible and could meet the clinical needs in the future for better control of postoperative pain and other unwanted negative effects. The study was registered on the Clinical Trial Registry (https://clinicaltrials.gov/ct2/show/NCT03761576?term=NCT03761576&draw=2&rank=1) with the registration number NCT03761576.
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Wason TD. A model integrating multiple processes of synchronization and coherence for information instantiation within a cortical area. Biosystems 2021; 205:104403. [PMID: 33746019 DOI: 10.1016/j.biosystems.2021.104403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 03/05/2021] [Indexed: 12/14/2022]
Abstract
What is the form of dynamic, e.g., sensory, information in the mammalian cortex? Information in the cortex is modeled as a coherence map of a mixed chimera state of synchronous, phasic, and disordered minicolumns. The theoretical model is built on neurophysiological evidence. Complex spatiotemporal information is instantiated through a system of interacting biological processes that generate a synchronized cortical area, a coherent aperture. Minicolumn elements are grouped in macrocolumns in an array analogous to a phased-array radar, modeled as an aperture, a "hole through which radiant energy flows." Coherence maps in a cortical area transform inputs from multiple sources into outputs to multiple targets, while reducing complexity and entropy. Coherent apertures can assume extremely large numbers of different information states as coherence maps, which can be communicated among apertures with corresponding very large bandwidths. The coherent aperture model incorporates considerable reported research, integrating five conceptually and mathematically independent processes: 1) a damped Kuramoto network model, 2) a pumped area field potential, 3) the gating of nearly coincident spikes, 4) the coherence of activity across cortical lamina, and 5) complex information formed through functions in macrocolumns. Biological processes and their interactions are described in equations and a functional circuit such that the mathematical pieces can be assembled the same way the neurophysiological ones are. The model can be conceptually convolved over the specifics of local cortical areas within and across species. A coherent aperture becomes a node in a graph of cortical areas with a corresponding distribution of information.
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Affiliation(s)
- Thomas D Wason
- North Carolina State University, Department of Biological Sciences, Meitzen Laboratory, Campus Box 7617, 128 David Clark Labs, Raleigh, NC 27695-7617, USA.
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VerMaas JR, Lew BJ, Trevarrow MP, Wilson TW, Kurz MJ. Children with Cerebral Palsy Have Altered Occipital Cortical Oscillations during a Visuospatial Attention Task. Cereb Cortex 2021; 31:3353-3362. [PMID: 33611348 DOI: 10.1093/cercor/bhab016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/28/2020] [Accepted: 01/08/2021] [Indexed: 11/13/2022] Open
Abstract
Dynamically allocating neural resources to salient features or objects within our visual space is fundamental to making rapid and accurate decisions. Impairments in such visuospatial abilities have been consistently documented in the clinical literature on individuals with cerebral palsy (CP), although the underlying neural mechanisms are poorly understood. In this study, we used magnetoencephalography (MEG) and oscillatory analysis methods to examine visuospatial processing in children with CP and demographically matched typically developing (TD) children. Our results indicated robust oscillations in the theta (4-8 Hz), alpha (8-14 Hz), and gamma (64-80 Hz) frequency bands in the occipital cortex of both groups during visuospatial processing. Importantly, the group with CP exhibited weaker cortical oscillations in the theta and gamma frequency bands, as well as slower response times and worse accuracy during task performance compared to the TD children. Furthermore, we found that weaker theta and gamma oscillations were related to greater visuospatial performance deficits across both groups. We propose that the weaker occipital oscillations seen in children with CP may reflect poor bottom-up processing of incoming visual information, which subsequently affects the higher-order visual computations essential for accurate visual perception and integration for decision-making.
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Affiliation(s)
- Jacy R VerMaas
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA.,Department of Physical Therapy, Munroe-Meyer Institute, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Brandon J Lew
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA
| | - Michael P Trevarrow
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA
| | - Max J Kurz
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA
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Han C, Wang T, Wu Y, Li Y, Yang Y, Li L, Wang Y, Xing D. The Generation and Modulation of Distinct Gamma Oscillations with Local, Horizontal, and Feedback Connections in the Primary Visual Cortex: A Model Study on Large-Scale Networks. Neural Plast 2021; 2021:8874516. [PMID: 33531893 PMCID: PMC7834828 DOI: 10.1155/2021/8874516] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 10/25/2020] [Accepted: 11/12/2020] [Indexed: 11/23/2022] Open
Abstract
Gamma oscillation (GAMMA) in the local field potential (LFP) is a synchronized activity commonly found in many brain regions, and it has been thought as a functional signature of network connectivity in the brain, which plays important roles in information processing. Studies have shown that the response property of GAMMA is related to neural interaction through local recurrent connections (RC), feed-forward (FF), and feedback (FB) connections. However, the relationship between GAMMA and long-range horizontal connections (HC) in the brain remains unclear. Here, we aimed to understand this question in a large-scale network model for the primary visual cortex (V1). We created a computational model composed of multiple excitatory and inhibitory units with biologically plausible connectivity patterns for RC, FF, FB, and HC in V1; then, we quantitated GAMMA in network models at different strength levels of HC and other connection types. Surprisingly, we found that HC and FB, the two types of large-scale connections, play very different roles in generating and modulating GAMMA. While both FB and HC modulate a fast gamma oscillation (around 50-60 Hz) generated by FF and RC, HC generates a new GAMMA oscillating around 30 Hz, whose power and peak frequency can also be modulated by FB. Furthermore, response properties of the two GAMMAs in a network with both HC and FB are different in a way that is highly consistent with a recent experimental finding for distinct GAMMAs in macaque V1. The results suggest that distinct GAMMAs are signatures for neural connections in different spatial scales and they might be related to different functions for information integration. Our study, for the first time, pinpoints the underlying circuits for distinct GAMMAs in a mechanistic model for macaque V1, which might provide a new framework to study multiple gamma oscillations in other cortical regions.
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Affiliation(s)
- Chuanliang Han
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yang Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yi Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Liang Li
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Yizheng Wang
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
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Orlowska-Feuer P, Allen AE, Brown TM, Szkudlarek HJ, Lucas RJ, Storchi R. Infra-slow modulation of fast beta/gamma oscillations in the mouse visual system. J Physiol 2021; 599:1631-1650. [PMID: 33428215 DOI: 10.1113/jp280030] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 01/05/2021] [Indexed: 12/28/2022] Open
Abstract
KEY POINTS Neurophysiological activity in the subcortical visual system fluctuates in both infra-slow and fast oscillatory ranges, but the level of co-occurrence and potential functional interaction of these rhythms is unknown. Analysing dark-adapted spontaneous activity in the mouse subcortical visual system, we find that these two types of oscillation interact uniquely through a population of neurons expressing both rhythms. Genetic ablation of rod/cone signalling potentiates infra-slow and abolishes fast beta/gamma oscillations while genetic ablation of melanopsin substantially diminishes the interaction between these two rhythms. Our results indicate that in an intact visual system the phase of infra-slow modulates fast beta/gamma oscillations. Thus one possible impact of infra-slow oscillations in vision is to guide visual processing by interacting with fast narrowband oscillations. ABSTRACT Infra-slow (<0.02 Hz) and fast beta/gamma (20-100 Hz) oscillations in neurophysiological activity have been widely found in the subcortical visual system. While it is well established that fast beta/gamma oscillations are involved in visual processing, the role (if any) of infra-slow oscillations is currently unknown. One possibility is that infra-slow oscillations exert influence by modulating the amplitude of fast oscillations, yet the extent to which these different oscillations arise independently and interact remains unknown. We addressed these questions by recording in vivo spontaneous activity from the subcortical visual system of visually intact mice, and animals whose retinal network was disrupted by advanced rod/cone degeneration (rd/rd cl) or melanopsin loss (Opn4-/- ). We found many neurons expressing only one type of oscillation, and indeed fast oscillations were absent in rd/rd cl. Conversely, neurons co-expressing the two oscillations were also common, and were encountered more often than expected by chance in visually intact but not Opn4-/- mice. Finally, where they co-occurred we found that beta/gamma amplitude was modulated by the infra-slow rhythm. Our data thus reveal that: (1) infra-slow and beta-gamma oscillations are separable phenomena; and (2) that they actively co-occur in a subset of neurones in which the phase of infra-slow oscillations defines beta-gamma oscillations amplitude. These findings suggest that infra-slow oscillations could influence vision by modulating beta-gamma oscillations, and raise the possibility that disruptions in these oscillatory behaviours contribute to vision dysfunction in retinal dystrophy.
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Affiliation(s)
- Patrycja Orlowska-Feuer
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, 30-387, Poland
| | - Annette Elisabeth Allen
- Division of Neuroscience and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - Timothy Matthew Brown
- Centre for Biological Timing, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - Hanna Jowita Szkudlarek
- Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Krakow, 30-387, Poland
| | - Robert James Lucas
- Centre for Biological Timing, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - Riccardo Storchi
- Division of Neuroscience and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
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Huang P, Xiang X, Chen X, Li H. Somatostatin Neurons Govern Theta Oscillations Induced by Salient Visual Signals. Cell Rep 2020; 33:108415. [PMID: 33238116 DOI: 10.1016/j.celrep.2020.108415] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 09/14/2020] [Accepted: 10/29/2020] [Indexed: 01/21/2023] Open
Abstract
Salient visual stimuli enhance theta oscillations and spike-phase locking in the theta band in the primary visual cortex (V1) of mice; however, the detailed mechanisms remain unknown. GABAergic neurons play a vital role in regulating these oscillations. Here, we use optogenetic recordings to tag cell-type-specific neurons in V1 of head-fixed mice and demonstrate that salient visual stimuli facilitate somatostatin (SOM)-expressing neuron responses and firing with theta band oscillations but suppress activities of parvalbumin (PV)-expressing neurons. Furthermore, inactivation of SOM neurons attenuates the enhancement of theta oscillations induced by salient visual stimuli and rhythmic activation of SOM neurons enhances theta oscillations. These results reveal a potential cortical theta oscillation mechanism governed by SOM neurons.
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Affiliation(s)
- Pengcheng Huang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xinkuan Xiang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Xinfeng Chen
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Haohong Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
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