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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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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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Ni S, Harris B, Gong P. Distributed and dynamical communication: a mechanism for flexible cortico-cortical interactions and its functional roles in visual attention. Commun Biol 2024; 7:550. [PMID: 38719883 PMCID: PMC11078951 DOI: 10.1038/s42003-024-06228-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 04/22/2024] [Indexed: 05/12/2024] Open
Abstract
Perceptual and cognitive processing relies on flexible communication among cortical areas; however, the underlying neural mechanism remains unclear. Here we report a mechanism based on the realistic spatiotemporal dynamics of propagating wave patterns in neural population activity. Using a biophysically plausible, multiarea spiking neural circuit model, we demonstrate that these wave patterns, characterized by their rich and complex dynamics, can account for a wide variety of empirically observed neural processes. The coordinated interactions of these wave patterns give rise to distributed and dynamic communication (DDC) that enables flexible and rapid routing of neural activity across cortical areas. We elucidate how DDC unifies the previously proposed oscillation synchronization-based and subspace-based views of interareal communication, offering experimentally testable predictions that we validate through the analysis of Allen Institute Neuropixels data. Furthermore, we demonstrate that DDC can be effectively modulated during attention tasks through the interplay of neuromodulators and cortical feedback loops. This modulation process explains many neural effects of attention, underscoring the fundamental functional role of DDC in cognition.
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Affiliation(s)
- Shencong Ni
- School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Brendan Harris
- School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Pulin Gong
- School of Physics, University of Sydney, Sydney, NSW, Australia.
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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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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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Parto-Dezfouli M, Vezoli J, Bosman CA, Fries P. Enhanced behavioral performance through interareal gamma and beta synchronization. Cell Rep 2023; 42:113249. [PMID: 37837620 PMCID: PMC10679823 DOI: 10.1016/j.celrep.2023.113249] [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: 03/02/2023] [Revised: 07/18/2023] [Accepted: 09/26/2023] [Indexed: 10/16/2023] Open
Abstract
Cognitive functioning requires coordination between brain areas. Between visual areas, feedforward gamma synchronization improves behavioral performance. Here, we investigate whether similar principles hold across brain regions and frequency bands, using simultaneous electrocorticographic recordings from 15 areas of two macaque monkeys during performance of a selective attention task. Short behavioral reaction times (RTs), suggesting efficient interareal communication, occurred when occipital areas V1, V2, V4, and DP showed gamma synchronization, and fronto-central areas S1, 5, F1, F2, and F4 showed beta synchronization. For both area clusters and corresponding frequency bands, deviations from the typically observed phase relations increased RTs. Across clusters and frequency bands, good phase relations occurred in a correlated manner specifically when they processed the behaviorally relevant stimulus. Furthermore, the fronto-central cluster exerted a beta-band influence onto the occipital cluster whose strength predicted short RTs. These results suggest that local gamma and beta synchronization and their inter-regional coordination jointly improve behavioral performance.
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Affiliation(s)
- Mohsen Parto-Dezfouli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Julien Vezoli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Conrado Arturo Bosman
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands; Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1090 GE Amsterdam, the Netherlands
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands.
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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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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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