1
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Yokoo S, Higo T, Gerard-Mercier F, Oguchi M, Sakagami M, Bito H, Sakamoto M, Ichinohe N, Tanaka K. Projection-specific and reversible functional blockage in the association cortex of macaque monkeys. Neurosci Res 2025:S0168-0102(25)00086-0. [PMID: 40381890 DOI: 10.1016/j.neures.2025.05.004] [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: 02/26/2025] [Revised: 05/08/2025] [Accepted: 05/14/2025] [Indexed: 05/20/2025]
Abstract
The functional manipulation techniques based on optogenetics have been widely and effectively utilized in the rodent brain. However, the applications of these techniques to the macaque cerebral cortex, particularly those to the prefrontal cortex, have been limited due to the extensive size and complex functional organization of each prefrontal area. In this study, we developed projection-specific and reversible functional blockade methods applicable to areas of the macaque prefrontal cortex, based on chemogenetic techniques. In chemogenetics, once a pair of viral vectors has been injected into the regions of projection source and destination, the projection-specific functional blockage can be initiated through the oral, intravenous, or intramuscular administration of an appropriate pharmaceutical agent. Two methods were developed using two different effector proteins, an inhibitory DREADD, hM4Di, and tetanus toxin, given the substantial discrepancy in the on-off time course of functional blockade between the two. The Cre-DIO system was combined with hM4Di, and the Tet-On system with tetanus toxin. The effectiveness of these methods was evaluated by developing an electrophysiological assay using photic stimulation and field potential recordings.
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Affiliation(s)
- Seiichirou Yokoo
- Cognitive Brain Mapping Laboratory, RIKEN Center for Brain Science
| | - Takayasu Higo
- Cognitive Brain Mapping Laboratory, RIKEN Center for Brain Science,; Department of Neuroscience, Graduate School of Medicine, Kyoto University
| | | | | | | | - Haruhiko Bito
- Graduate School of Medicine, The University of Tokyo
| | - Masayuki Sakamoto
- Graduate School of Medicine, The University of Tokyo,; Graduate School of Biostudies, Kyoto University
| | - Noritake Ichinohe
- Department of Ultrastructural Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry
| | - Keiji Tanaka
- Cognitive Brain Mapping Laboratory, RIKEN Center for Brain Science,.
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2
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Banaie Boroujeni K, Helfrich RF, Fiebelkorn IC, Bentley N, Lin JJ, Knight RT, Kastner S. Fast Attentional Information Routing via High-Frequency Bursts in the Human Brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.09.11.612548. [PMID: 39314423 PMCID: PMC11419049 DOI: 10.1101/2024.09.11.612548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Brain-wide communication supporting flexible behavior requires coordination between sensory and associative regions but how brain networks route sensory information at fast timescales to guide action remains unclear. Using spiking neural networks and human intracranial electrophysiology during spatial attention tasks, where participants detected targets at cued locations, we show that high-frequency activity bursts (HFAb) serve as information-carrying events, facilitating fast, long-range communications. HFAbs were evoked by sensory cues and targets, dynamically linked to low-frequency rhythms. Notably, both HFAb responses following cues and their decoupling from slow rhythms predicted performance accuracy. HFAbs were synchronized at the network-level, identifying distinct cue- and target-activated subnetworks. These subnetworks exhibited a temporal lead-lag organization following target onset, with cue-sactivated subnetworks preceding target-activated subnetworks when the cue provided relevant target information. Computational modeling indicated that HFAbs reflect transitions to coherent population spiking and are coordinated across networks through distinct mechanisms. Together, these findings establish HFAbs as neural mechanisms for fast, large-scale communication supporting attentional performance.
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3
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Katz LN, Bohlen MO, Yu G, Mejias-Aponte C, Sommer MA, Krauzlis RJ. Optogenetic Manipulation of Covert Attention in the Nonhuman Primate. J Cogn Neurosci 2025; 37:266-285. [PMID: 39509098 PMCID: PMC12022921 DOI: 10.1162/jocn_a_02274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2024]
Abstract
Optogenetics affords new opportunities to interrogate neuronal circuits that control behavior. In primates, the usefulness of optogenetics in studying cognitive functions remains a challenge. The technique has been successfully wielded, but behavioral effects have been demonstrated primarily for sensorimotor processes. Here, we tested whether brief optogenetic suppression of primate superior colliculus can change performance in a covert attention task, in addition to previously reported optogenetic effects on saccadic eye movements. We used an attention task that required the monkey to detect and report a stimulus change at a cued location via joystick release, while ignoring changes at an uncued location. When the cued location was positioned in the response fields of transduced neurons in the superior colliculus, transient light delivery coincident with the stimulus change disrupted the monkey's detection performance, significantly lowering hit rates. When the cued location was elsewhere, hit rates were unaltered, indicating that the effect was spatially specific and not a motor deficit. Hit rates for trials with only one stimulus were also unaltered, indicating that the effect depended on selection among distractors rather than a low-level visual impairment. Psychophysical analysis revealed that optogenetic suppression increased perceptual threshold, but only for locations matching the transduced site. These data show that optogenetic manipulations can cause brief and spatially specific deficits in covert attention, independent of sensorimotor functions. This dissociation of effect, and the temporal precision provided by the technique, demonstrates the utility of optogenetics in interrogating neuronal circuits that mediate cognitive functions in the primate.
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4
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Das A, Sheffield AG, Nandy AS, Jadi MP. Brain-state mediated modulation of inter-laminar dependencies in visual cortex. Nat Commun 2024; 15:5105. [PMID: 38877026 PMCID: PMC11178935 DOI: 10.1038/s41467-024-49144-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 05/23/2024] [Indexed: 06/16/2024] Open
Abstract
Spatial attention is critical for recognizing behaviorally relevant objects in a cluttered environment. How the deployment of spatial attention aids the hierarchical computations of object recognition remains unclear. We investigated this in the laminar cortical network of visual area V4, an area strongly modulated by attention. We found that deployment of attention strengthened unique dependencies in neural activity across cortical layers. On the other hand, shared dependencies were reduced within the excitatory population of a layer. Surprisingly, attention strengthened unique dependencies within a laminar population. Crucially, these modulation patterns were also observed during successful behavioral outcomes that are thought to be mediated by internal brain state fluctuations. Successful behavioral outcomes were also associated with phases of reduced neural excitability, suggesting a mechanism for enhanced information transfer during optimal states. Our results suggest common computation goals of optimal sensory states that are attained by either task demands or internal fluctuations.
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Affiliation(s)
- Anirban Das
- Department of Psychiatry, Yale University, New Haven, CT, 06511, USA
- Department of Neuroscience, Yale University, New Haven, CT, 06511, USA
- Design and Patterning AI Group, Intel Corp., Hillsboro, Oregon, 97124, USA
| | - Alec G Sheffield
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, 06511, USA
| | - Anirvan S Nandy
- Department of Neuroscience, Yale University, New Haven, CT, 06511, USA
- Department of Psychology, Yale University, New Haven, CT, 06511, USA
- Kavli Institute for Neuroscience, Yale University, New Haven, CT, 06511, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06511, USA
| | - Monika P Jadi
- Department of Psychiatry, Yale University, New Haven, CT, 06511, USA.
- Department of Neuroscience, Yale University, New Haven, CT, 06511, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, 06511, USA.
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5
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Mendoza-Halliday D, Xu H, Azevedo FAC, Desimone R. Dissociable neuronal substrates of visual feature attention and working memory. Neuron 2024; 112:850-863.e6. [PMID: 38228138 PMCID: PMC10939754 DOI: 10.1016/j.neuron.2023.12.007] [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: 05/12/2023] [Revised: 10/10/2023] [Accepted: 12/12/2023] [Indexed: 01/18/2024]
Abstract
Attention and working memory (WM) are distinct cognitive functions, yet given their close interactions, it is often assumed that they share the same neuronal mechanisms. We show that in macaques performing a WM-guided feature attention task, the activity of most neurons in areas middle temporal (MT), medial superior temporal (MST), lateral intraparietal (LIP), and posterior lateral prefrontal cortex (LPFC-p) displays attentional modulation or WM coding and not both. One area thought to play a role in both functions is LPFC-p. To test this, we optogenetically inactivated LPFC-p bilaterally during different task periods. Attention period inactivation reduced attentional modulation in LPFC-p, MST, and LIP neurons and impaired task performance. In contrast, WM period inactivation did not affect attentional modulation or performance and minimally affected WM coding. Our results suggest that feature attention and WM have dissociable neuronal substrates and that LPFC-p plays a critical role in feature attention, but not in WM.
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Affiliation(s)
- Diego Mendoza-Halliday
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Haoran Xu
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Frederico A C Azevedo
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert Desimone
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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6
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Parajuli A, Gutnisky D, Tandon N, Dragoi V. Endogenous fluctuations in cortical state selectively enhance different modes of sensory processing in human temporal lobe. Nat Commun 2023; 14:5591. [PMID: 37696880 PMCID: PMC10495466 DOI: 10.1038/s41467-023-41406-3] [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: 09/22/2022] [Accepted: 08/31/2023] [Indexed: 09/13/2023] Open
Abstract
The degree of synchronized fluctuations in neocortical network activity can vary widely during alertness. One influential idea that has emerged over the past few decades is that perceptual decisions are more accurate when the state of population activity is desynchronized. This suggests that optimal task performance may occur during a particular cortical state - the desynchronized state. Here we show that, contrary to this view, cortical state can both facilitate and suppress perceptual performance in a task-dependent manner. We performed electrical recordings from surface-implanted grid electrodes in the temporal lobe while human subjects completed two perceptual tasks. We found that when local population activity is in a synchronized state, network and perceptual performance are enhanced in a detection task and impaired in a discrimination task, but these modulatory effects are reversed when population activity is desynchronized. These findings indicate that the brain has adapted to take advantage of endogenous fluctuations in the state of neural populations in temporal cortex to selectively enhance different modes of sensory processing during perception in a state-dependent manner.
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Affiliation(s)
- Arun Parajuli
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas at Houston, Houston, TX, USA
| | - Diego Gutnisky
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas at Houston, Houston, TX, USA
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Nitin Tandon
- Vivian L. Smith Department of Neurosurgery, University of Texas Medical School, Houston, TX, USA
| | - Valentin Dragoi
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas at Houston, Houston, TX, USA.
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
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7
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Afraz A. Behavioral optogenetics in nonhuman primates; a psychological perspective. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 5:100101. [PMID: 38020813 PMCID: PMC10663131 DOI: 10.1016/j.crneur.2023.100101] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 06/02/2023] [Accepted: 06/22/2023] [Indexed: 12/01/2023] Open
Abstract
Optogenetics has been a promising and developing technology in systems neuroscience throughout the past decade. It has been difficult though to reliably establish the potential behavioral effects of optogenetic perturbation of the neural activity in nonhuman primates. This poses a challenge on the future of optogenetics in humans as the concepts and technology need to be developed in nonhuman primates first. Here, I briefly summarize the viable approaches taken to improve nonhuman primate behavioral optogenetics, then focus on one approach: improvements in the measurement of behavior. I bring examples from visual behavior and show how the choice of method of measurement might conceal large behavioral effects. I will then discuss the "cortical perturbation detection" task in detail as an example of a sensitive task that can record the behavioral effects of optogenetic cortical stimulation with high fidelity. Finally, encouraged by the rich scientific landscape ahead of behavioral optogenetics, I invite technology developers to improve the chronically implantable devices designed for simultaneous neural recording and optogenetic intervention in nonhuman primates.
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Affiliation(s)
- Arash Afraz
- Laboratory of Neuropsychology, National Institute of Mental Health, National Institute of Health, Bethesda, Maryland, USA
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8
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Mendoza-Halliday D, Xu H, Azevedo FAC, Desimone R. Dissociable neuronal substrates of visual feature attention and working memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.01.530719. [PMID: 36909606 PMCID: PMC10002769 DOI: 10.1101/2023.03.01.530719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Attention and working memory (WM) are distinct cognitive functions, yet given their close interactions, it has been proposed that they share the same neuronal mechanisms. Here we show that in macaques performing a WM-guided feature attention task, the activity of most neurons in areas middle temporal (MT), medial superior temporal (MST), lateral intraparietal (LIP), and posterior lateral prefrontal cortex (LPFC-p) displays either WM coding or attentional modulation, but not both. One area thought to play a role in both functions is LPFC-p. To test this, we optogenetically inactivated LPFC-p bilaterally during the attention or WM periods of the task. Attention period inactivation reduced attentional modulation in LPFC-p, MST, and LIP neurons, and impaired task performance. WM period inactivation did not affect attentional modulation nor performance, and minimally reduced WM coding. Our results suggest that feature attention and WM have dissociable neuronal substrates, and that LPFC-p plays a critical role in attention but not WM.
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9
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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: 30] [Impact Index Per Article: 15.0] [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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10
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Kim TH, Schnitzer MJ. Fluorescence imaging of large-scale neural ensemble dynamics. Cell 2022; 185:9-41. [PMID: 34995519 PMCID: PMC8849612 DOI: 10.1016/j.cell.2021.12.007] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/14/2022]
Abstract
Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca2+ imaging studies of neural activity can track brain area interactions and distributed information processing at cellular resolution. Across smaller spatial scales, high-speed voltage imaging reveals the distinctive spiking patterns and coding properties of targeted neuron types. Collectively, these innovations will propel studies of brain function and dovetail with ongoing neuroscience initiatives to identify new neuron types and develop widely applicable, non-human primate models. The optical toolkit's growing sophistication also suggests that "brain observatory" facilities would be useful open resources for future brain-imaging studies.
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Affiliation(s)
- Tony Hyun Kim
- James Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| | - Mark J Schnitzer
- James Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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11
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Westerberg JA, Sigworth EA, Schall JD, Maier A. Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers. Proc Natl Acad Sci U S A 2021; 118:e2103702118. [PMID: 34893538 PMCID: PMC8685673 DOI: 10.1073/pnas.2103702118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2021] [Indexed: 11/18/2022] Open
Abstract
Visual search is a workhorse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed a search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified "feature columns" which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4's superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.
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Affiliation(s)
- Jacob A Westerberg
- Department of Psychology, Vanderbilt Brain Institute, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN 37240;
| | | | - Jeffrey D Schall
- Centre for Vision Research, Vision: Science to Applications Program, Department of Biology and Department of Psychology, York University, Toronto, ON M3J 1P3, Canada
| | - Alexander Maier
- Department of Psychology, Vanderbilt Brain Institute, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN 37240
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12
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Scott JT, Bourne JA. Modelling behaviors relevant to brain disorders in the nonhuman primate: Are we there yet? Prog Neurobiol 2021; 208:102183. [PMID: 34728308 DOI: 10.1016/j.pneurobio.2021.102183] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/27/2021] [Accepted: 10/27/2021] [Indexed: 12/30/2022]
Abstract
Recent years have seen a profound resurgence of activity with nonhuman primates (NHPs) to model human brain disorders. From marmosets to macaques, the study of NHP species offers a unique window into the function of primate-specific neural circuits that are impossible to examine in other models. Examining how these circuits manifest into the complex behaviors of primates, such as advanced cognitive and social functions, has provided enormous insights to date into the mechanisms underlying symptoms of numerous neurological and neuropsychiatric illnesses. With the recent optimization of modern techniques to manipulate and measure neural activity in vivo, such as optogenetics and calcium imaging, NHP research is more well-equipped than ever to probe the neural mechanisms underlying pathological behavior. However, methods for behavioral experimentation and analysis in NHPs have noticeably failed to keep pace with these advances. As behavior ultimately lies at the junction between preclinical findings and its translation to clinical outcomes for brain disorders, approaches to improve the integrity, reproducibility, and translatability of behavioral experiments in NHPs requires critical evaluation. In this review, we provide a unifying account of existing brain disorder models using NHPs, and provide insights into the present and emerging contributions of behavioral studies to the field.
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Affiliation(s)
- Jack T Scott
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia
| | - James A Bourne
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
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13
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Davis ZW, Benigno GB, Fletterman C, Desbordes T, Steward C, Sejnowski TJ, H Reynolds J, Muller L. Spontaneous traveling waves naturally emerge from horizontal fiber time delays and travel through locally asynchronous-irregular states. Nat Commun 2021; 12:6057. [PMID: 34663796 PMCID: PMC8523565 DOI: 10.1038/s41467-021-26175-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 09/17/2021] [Indexed: 11/25/2022] Open
Abstract
Studies of sensory-evoked neuronal responses often focus on mean spike rates, with fluctuations treated as internally-generated noise. However, fluctuations of spontaneous activity, often organized as traveling waves, shape stimulus-evoked responses and perceptual sensitivity. The mechanisms underlying these waves are unknown. Further, it is unclear whether waves are consistent with the low rate and weakly correlated “asynchronous-irregular” dynamics observed in cortical recordings. Here, we describe a large-scale computational model with topographically-organized connectivity and conduction delays relevant to biological scales. We find that spontaneous traveling waves are a general property of these networks. The traveling waves that occur in the model are sparse, with only a small fraction of neurons participating in any individual wave. Consequently, they do not induce measurable spike correlations and remain consistent with locally asynchronous irregular states. Further, by modulating local network state, they can shape responses to incoming inputs as observed in vivo. Spontaneous traveling cortical waves shape neural responses. Using a large-scale computational model, the authors show that transmission delays shape locally asynchronous spiking dynamics into traveling waves without inducing correlations and boost responses to external input, as observed in vivo.
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Affiliation(s)
- Zachary W Davis
- The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Gabriel B Benigno
- Department of Applied Mathematics, Western University, London, ON, Canada.,Brain and Mind Institute, Western University, London, ON, Canada
| | | | - Theo Desbordes
- The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | | | - John H Reynolds
- The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Lyle Muller
- Department of Applied Mathematics, Western University, London, ON, Canada. .,Brain and Mind Institute, Western University, London, ON, Canada.
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14
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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: 1.0] [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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15
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Waschke L, Kloosterman NA, Obleser J, Garrett DD. Behavior needs neural variability. Neuron 2021; 109:751-766. [PMID: 33596406 DOI: 10.1016/j.neuron.2021.01.023] [Citation(s) in RCA: 146] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 11/16/2020] [Accepted: 01/22/2021] [Indexed: 01/26/2023]
Abstract
Human and non-human animal behavior is highly malleable and adapts successfully to internal and external demands. Such behavioral success stands in striking contrast to the apparent instability in neural activity (i.e., variability) from which it arises. Here, we summon the considerable evidence across scales, species, and imaging modalities that neural variability represents a key, undervalued dimension for understanding brain-behavior relationships at inter- and intra-individual levels. We believe that only by incorporating a specific focus on variability will the neural foundation of behavior be comprehensively understood.
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Affiliation(s)
- Leonhard Waschke
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Max Planck Institute for Human Development, 14195 Berlin, Germany; Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany.
| | - Niels A Kloosterman
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Max Planck Institute for Human Development, 14195 Berlin, Germany; Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
| | - Jonas Obleser
- Department of Psychology, University of Lübeck, 23562 Lübeck, Germany; Center of Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Douglas D Garrett
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Max Planck Institute for Human Development, 14195 Berlin, Germany; Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
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16
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Tremblay S, Acker L, Afraz A, Albaugh DL, Amita H, Andrei AR, Angelucci A, Aschner A, Balan PF, Basso MA, Benvenuti G, Bohlen MO, Caiola MJ, Calcedo R, Cavanaugh J, Chen Y, Chen S, Chernov MM, Clark AM, Dai J, Debes SR, Deisseroth K, Desimone R, Dragoi V, Egger SW, Eldridge MAG, El-Nahal HG, Fabbrini F, Federer F, Fetsch CR, Fortuna MG, Friedman RM, Fujii N, Gail A, Galvan A, Ghosh S, Gieselmann MA, Gulli RA, Hikosaka O, Hosseini EA, Hu X, Hüer J, Inoue KI, Janz R, Jazayeri M, Jiang R, Ju N, Kar K, Klein C, Kohn A, Komatsu M, Maeda K, Martinez-Trujillo JC, Matsumoto M, Maunsell JHR, Mendoza-Halliday D, Monosov IE, Muers RS, Nurminen L, Ortiz-Rios M, O'Shea DJ, Palfi S, Petkov CI, Pojoga S, Rajalingham R, Ramakrishnan C, Remington ED, Revsine C, Roe AW, Sabes PN, Saunders RC, Scherberger H, Schmid MC, Schultz W, Seidemann E, Senova YS, Shadlen MN, Sheinberg DL, Siu C, Smith Y, Solomon SS, Sommer MA, Spudich JL, Stauffer WR, Takada M, Tang S, Thiele A, Treue S, Vanduffel W, Vogels R, Whitmire MP, Wichmann T, Wurtz RH, Xu H, Yazdan-Shahmorad A, Shenoy KV, DiCarlo JJ, Platt ML. An Open Resource for Non-human Primate Optogenetics. Neuron 2020; 108:1075-1090.e6. [PMID: 33080229 PMCID: PMC7962465 DOI: 10.1016/j.neuron.2020.09.027] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/28/2020] [Accepted: 09/21/2020] [Indexed: 12/26/2022]
Abstract
Optogenetics has revolutionized neuroscience in small laboratory animals, but its effect on animal models more closely related to humans, such as non-human primates (NHPs), has been mixed. To make evidence-based decisions in primate optogenetics, the scientific community would benefit from a centralized database listing all attempts, successful and unsuccessful, of using optogenetics in the primate brain. We contacted members of the community to ask for their contributions to an open science initiative. As of this writing, 45 laboratories around the world contributed more than 1,000 injection experiments, including precise details regarding their methods and outcomes. Of those entries, more than half had not been published. The resource is free for everyone to consult and contribute to on the Open Science Framework website. Here we review some of the insights from this initial release of the database and discuss methodological considerations to improve the success of optogenetic experiments in NHPs.
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Affiliation(s)
- Sébastien Tremblay
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Leah Acker
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Arash Afraz
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel L Albaugh
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Hidetoshi Amita
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ariana R Andrei
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Alessandra Angelucci
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Amir Aschner
- Dominik P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Puiu F Balan
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium
| | - Michele A Basso
- Departments of Psychiatry and Biobehavioral Sciences and Neurobiology, UCLA, Los Angeles, CA 90095, USA
| | - Giacomo Benvenuti
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Martin O Bohlen
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Michael J Caiola
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Roberto Calcedo
- Gene Therapy Program, Department of Medicine, University of Pennsylvania, Philadelphia, PA 19014, USA
| | - James Cavanaugh
- Laboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD 20982, USA
| | - Yuzhi Chen
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Spencer Chen
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Mykyta M Chernov
- Division of Neuroscience, Oregon National Primate Resource Center, Oregon Health and Science University, Beaverton, OR 97006, USA
| | - Andrew M Clark
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Ji Dai
- CAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen 518055, China
| | - Samantha R Debes
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Karl Deisseroth
- Neuroscience Program, Departments of Bioengineering, Psychiatry, and Behavioral Science, Wu Tsai Neurosciences Institute, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Robert Desimone
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Valentin Dragoi
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Seth W Egger
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mark A G Eldridge
- Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892, USA
| | - Hala G El-Nahal
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Francesco Fabbrini
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium
| | - Frederick Federer
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Christopher R Fetsch
- The Solomon H. Snyder Department of Neuroscience & Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Michal G Fortuna
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Robert M Friedman
- Division of Neuroscience, Oregon National Primate Resource Center, Oregon Health and Science University, Beaverton, OR 97006, USA
| | - Naotaka Fujii
- Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | - Alexander Gail
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Faculty for Biology and Psychology, University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Adriana Galvan
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Supriya Ghosh
- Department of Neurobiology and Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL 60637, USA
| | - Marc Alwin Gieselmann
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Roberto A Gulli
- Zuckerman Institute, Columbia University, New York, NY 10027, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - Okihide Hikosaka
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Eghbal A Hosseini
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Xing Hu
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Janina Hüer
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany
| | - Ken-Ichi Inoue
- Systems Neuroscience Section, Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan
| | - Roger Janz
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Mehrdad Jazayeri
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Rundong Jiang
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Niansheng Ju
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Kohitij Kar
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Carsten Klein
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Adam Kohn
- Dominik P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Misako Komatsu
- Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | - Kazutaka Maeda
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio C Martinez-Trujillo
- Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada; Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Masayuki Matsumoto
- Division of Biomedical Science, Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki 305-8575, Japan; Transborder Medical Research Center, University of Tsukuba, Tsukuba, Ibaraki 305-8577, Japan
| | - John H R Maunsell
- Department of Neurobiology and Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL 60637, USA
| | - Diego Mendoza-Halliday
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ilya E Monosov
- Department of Neuroscience, Biomedical Engineering, Electrical Engineering, Neurosurgery and Pain Center, Washington University, St. Louis, MO 63110, USA
| | - Ross S Muers
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Lauri Nurminen
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Michael Ortiz-Rios
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany; Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Daniel J O'Shea
- Department of Electrical Engineering, Wu Tsai Neurosciences Institute, and Bio-X Institute, and Neuroscience Graduate Program, Stanford University, Stanford, CA 94305, USA
| | - Stéphane Palfi
- Department of Neurosurgery, Assistance Publique-Hopitaux de Paris (APHP), U955 INSERM IMRB eq.15, University of Paris 12 UPEC, Faculté de Médecine, Créteil 94010, France
| | - Christopher I Petkov
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Sorin Pojoga
- Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas-Houston, Houston, TX 77030, USA
| | - Rishi Rajalingham
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Charu Ramakrishnan
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Evan D Remington
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Cambria Revsine
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA; Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20814, USA
| | - Anna W Roe
- Division of Neuroscience, Oregon National Primate Resource Center, Oregon Health and Science University, Beaverton, OR 97006, USA; Interdisciplinary Institute of Neuroscience and Technology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310029, China; Key Laboratory of Biomedical Engineering of the Ministry of Education, Zhejiang University, Hangzhou 310029, China
| | - Philip N Sabes
- Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Richard C Saunders
- Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892, USA
| | - Hansjörg Scherberger
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Faculty for Biology and Psychology, University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Michael C Schmid
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK; Department of Neurosciences and Movement Sciences, Faculty of Science and Medicine, University of Fribourg, 1700 Fribourg, Switzerland
| | - Wolfram Schultz
- Department of Physiology, Development of Neuroscience, University of Cambridge, Cambridge CB3 0LT, UK
| | - Eyal Seidemann
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Yann-Suhan Senova
- Department of Neurosurgery, Assistance Publique-Hopitaux de Paris (APHP), U955 INSERM IMRB eq.15, University of Paris 12 UPEC, Faculté de Médecine, Créteil 94010, France
| | - Michael N Shadlen
- Department of Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, The Kavli Institute for Brain Science & Howard Hughes Medical Institute, Columbia University, NY 10027, USA
| | - David L Sheinberg
- Department of Neuroscience and Carney Institute for Brain Science, Brown University, Providence, RI 02912, USA
| | - Caitlin Siu
- Department of Ophthalmology, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
| | - Yoland Smith
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Selina S Solomon
- Dominik P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Marc A Sommer
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - John L Spudich
- Department of Biochemistry and Molecular Biology, McGovern Medical School, The University of Texas-Houston, Houston, TX 77030, USA
| | - William R Stauffer
- Systems Neuroscience Institute, Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Masahiko Takada
- Systems Neuroscience Section, Primate Research Institute, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Shiming Tang
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Alexander Thiele
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE2 4HH, UK
| | - Stefan Treue
- German Primate Center - Leibniz Institute for Primate Research, 37077 Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Faculty for Biology and Psychology, University of Göttingen, Göttingen, Germany; Leibniz Science Campus Primate Cognition, Göttingen, Germany
| | - Wim Vanduffel
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium; MGH Martinos Center, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02144, USA
| | - Rufin Vogels
- Laboratory of Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium
| | - Matthew P Whitmire
- Departments of Psychology and Neuroscience, Center for Perceptual Systems, University of Texas, Austin, TX 78712, USA
| | - Thomas Wichmann
- Yerkes National Primate Research Center, Morris K. Udall Center of Excellence for Parkinson's Disease, Department of Neurology, Emory University, GA 30329, USA
| | - Robert H Wurtz
- Laboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD 20982, USA
| | - Haoran Xu
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Azadeh Yazdan-Shahmorad
- Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA; Departments of Bioengineering and Electrical and Computer Engineering, Washington National Primate Research Center, University of Washington, Seattle, WA 98105, USA
| | - Krishna V Shenoy
- Departments of Electrical Engineering, Bioengineering, and Neurobiology, Wu Tsai Neurosciences Institute and Bio-X Institute, Neuroscience Graduate Program, and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - James J DiCarlo
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Michael L Platt
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Marketing, Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
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Gaillard C, Ben Hamed S. The neural bases of spatial attention and perceptual rhythms. Eur J Neurosci 2020; 55:3209-3223. [PMID: 33185294 DOI: 10.1111/ejn.15044] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 11/04/2020] [Accepted: 11/05/2020] [Indexed: 12/24/2022]
Abstract
Attentional processes allow the brain to overcome its processing capacities limitations by enhancing relevant visual information and suppressing irrelevant information. Thus attention plays a critical role, shaping our perception of the world. Several models have been proposed to describe the neuronal bases of attention and its mechanistic underlyings. Recent electrophysiological evidence show that attentional processes rely on oscillatory brain activities that correlate with rhythmic changes in cognitive performance. In the present review, we first take a historical perspective on how attention is viewed, from the initial spotlight theory of attention to the recent dynamic view of attention selection and we review their supporting psychophysical evidence. Based on recent prefrontal electrophysiological evidence, we refine the most recent models of attention sampling by proposing a rhythmic and continuous model of attentional sampling. In particular, we show that attention involves a continuous exploration of space, shifting within and across visual hemifield at specific alpha and theta rhythms, independently of the current attentional load. In addition, we show that this prefrontal attentional spotlight implements conjointly selection and suppression mechanisms, and is captured by salient incoming items. Last, we argue that this attention spotlight implements a highly flexible alternation of attentional exploration and exploitation epochs, depending on ongoing task contingencies. In a last part, we review the local and network oscillatory mechanisms that correlate with rhythmic attentional sampling, describing multiple rhythmic generators and complex network interactions.
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Affiliation(s)
- Corentin Gaillard
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, Université de Lyon - CNRS, Bron, France
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, Université de Lyon - CNRS, Bron, France
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18
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Gong X, Mendoza-Halliday D, Ting JT, Kaiser T, Sun X, Bastos AM, Wimmer RD, Guo B, Chen Q, Zhou Y, Pruner M, Wu CWH, Park D, Deisseroth K, Barak B, Boyden ES, Miller EK, Halassa MM, Fu Z, Bi G, Desimone R, Feng G. An Ultra-Sensitive Step-Function Opsin for Minimally Invasive Optogenetic Stimulation in Mice and Macaques. Neuron 2020; 107:38-51.e8. [PMID: 32353253 PMCID: PMC7351618 DOI: 10.1016/j.neuron.2020.03.032] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 02/26/2020] [Accepted: 03/27/2020] [Indexed: 01/27/2023]
Abstract
Optogenetics is among the most widely employed techniques to manipulate neuronal activity. However, a major drawback is the need for invasive implantation of optical fibers. To develop a minimally invasive optogenetic method that overcomes this challenge, we engineered a new step-function opsin with ultra-high light sensitivity (SOUL). We show that SOUL can activate neurons located in deep mouse brain regions via transcranial optical stimulation and elicit behavioral changes in SOUL knock-in mice. Moreover, SOUL can be used to modulate neuronal spiking and induce oscillations reversibly in macaque cortex via optical stimulation from outside the dura. By enabling external light delivery, our new opsin offers a minimally invasive tool for manipulating neuronal activity in rodent and primate models with fewer limitations on the depth and size of target brain regions and may further facilitate the development of minimally invasive optogenetic tools for the treatment of neurological disorders.
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Affiliation(s)
- Xin Gong
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, Anhui 230026, China; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Diego Mendoza-Halliday
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jonathan T Ting
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Human Cell Types, Allen Institute for Brain Science, Seattle, WA 98109, USA; Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Tobias Kaiser
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Xuyun Sun
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - André M Bastos
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ralf D Wimmer
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Baolin Guo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Qian Chen
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yang Zhou
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Maxwell Pruner
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Carolyn W-H Wu
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Demian Park
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Boaz Barak
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Edward S Boyden
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Michael M Halassa
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Zhanyan Fu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Guoqiang Bi
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, Anhui 230026, China; Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Robert Desimone
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Guoping Feng
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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19
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De A, El-Shamayleh Y, Horwitz GD. Fast and reversible neural inactivation in macaque cortex by optogenetic stimulation of GABAergic neurons. eLife 2020; 9:52658. [PMID: 32452766 PMCID: PMC7329331 DOI: 10.7554/elife.52658] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 05/24/2020] [Indexed: 12/21/2022] Open
Abstract
Optogenetic techniques for neural inactivation are valuable for linking neural activity to behavior but they have serious limitations in macaques. To achieve powerful and temporally precise neural inactivation, we used an adeno-associated viral (AAV) vector carrying the channelrhodopsin-2 gene under the control of a Dlx5/6 enhancer, which restricts expression to GABAergic neurons. We tested this approach in the primary visual cortex, an area where neural inactivation leads to interpretable behavioral deficits. Optical stimulation modulated spiking activity and reduced visual sensitivity profoundly in the region of space represented by the stimulated neurons. Rebound firing, which can have unwanted effects on neural circuits following inactivation, was not observed, and the efficacy of the optogenetic manipulation on behavior was maintained across >1000 trials. We conclude that this inhibitory cell-type-specific optogenetic approach is a powerful and spatiotemporally precise neural inactivation tool with broad utility for probing the functional contributions of cortical activity in macaques.
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Affiliation(s)
- Abhishek De
- Graduate Program in Neuroscience, University of Washington, Seattle, United States.,Department of Physiology and Biophysics, Washington National Primate Research Center, University of Washington, Seattle, United States
| | - Yasmine El-Shamayleh
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, United States
| | - Gregory D Horwitz
- Department of Physiology and Biophysics, Washington National Primate Research Center, University of Washington, Seattle, United States
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20
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Abstract
Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.
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Affiliation(s)
- David A McCormick
- Institute of Neuroscience, University of Oregon, Eugene, Oregon 97403, USA;
| | - Dennis B Nestvogel
- Institute of Neuroscience, University of Oregon, Eugene, Oregon 97403, USA;
| | - Biyu J He
- Departments of Neurology, Neuroscience and Physiology, and Radiology, Neuroscience Institute, New York University School of Medicine, New York, NY 10016, USA
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21
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Alpha Synchrony and the Neurofeedback Control of Spatial Attention. Neuron 2020; 105:577-587.e5. [DOI: 10.1016/j.neuron.2019.11.001] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 08/16/2019] [Accepted: 10/31/2019] [Indexed: 12/12/2022]
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22
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Speed A, Del Rosario J, Mikail N, Haider B. Spatial attention enhances network, cellular and subthreshold responses in mouse visual cortex. Nat Commun 2020; 11:505. [PMID: 31980628 PMCID: PMC6981183 DOI: 10.1038/s41467-020-14355-4] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 01/02/2020] [Indexed: 12/28/2022] Open
Abstract
Internal brain states strongly modulate sensory processing during behaviour. Studies of visual processing in primates show that attention to space selectively improves behavioural and neural responses to stimuli at the attended locations. Here we develop a visual spatial task for mice that elicits behavioural improvements consistent with the effects of spatial attention, and simultaneously measure network, cellular, and subthreshold activity in primary visual cortex. During trial-by-trial behavioural improvements, local field potential (LFP) responses to stimuli detected inside the receptive field (RF) strengthen. Moreover, detection inside the RF selectively enhances excitatory and inhibitory neuron responses to task-irrelevant stimuli and suppresses noise correlations and low frequency LFP fluctuations. Whole-cell patch-clamp recordings reveal that detection inside the RF increases synaptic activity that depolarizes membrane potential responses at the behaviorally relevant location. Our study establishes that mice display fundamental signatures of visual spatial attention spanning behavioral, network, cellular, and synaptic levels, providing new insight into rapid cognitive enhancement of sensory signals in visual cortex. Extensive research in primates shows that attention to space improves behavioural performance as well as neural responses to stimuli in that location. Here, the authors establish a visual spatial attention task in mice and report on attentional modulation of behaviour, as well as neural correlates from subthreshold responses in single cells to spikes and LFP at network level.
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Affiliation(s)
- Anderson Speed
- Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | | | - Navid Mikail
- Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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23
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Abstract
Monkeys are a premier model organism for neuroscience research. Activity in the central nervous systems of monkeys can be recorded and manipulated while they perform complex perceptual, motor, or cognitive tasks. Conventional techniques for manipulating neural activity in monkeys are too coarse to address many of the outstanding questions in primate neuroscience, but optogenetics holds the promise to overcome this hurdle. In this article, we review the progress that has been made in primate optogenetics over the past 5 years. We emphasize the use of gene regulatory sequences in viral vectors to target specific neuronal types, and we present data on vectors that we engineered to target parvalbumin-expressing neurons. We conclude with a discussion of the utility of optogenetics for treating sensorimotor hearing loss and Parkinson's disease, areas of translational neuroscience in which monkeys provide unique leverage for basic science and medicine.
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24
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Waschke L, Tune S, Obleser J. Local cortical desynchronization and pupil-linked arousal differentially shape brain states for optimal sensory performance. eLife 2019; 8:e51501. [PMID: 31820732 PMCID: PMC6946578 DOI: 10.7554/elife.51501] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 12/08/2019] [Indexed: 12/20/2022] Open
Abstract
Instantaneous brain states have consequences for our sensation, perception, and behaviour. Fluctuations in arousal and neural desynchronization likely pose perceptually relevant states. However, their relationship and their relative impact on perception is unclear. We here show that, at the single-trial level in humans, local desynchronization in sensory cortex (expressed as time-series entropy) versus pupil-linked arousal differentially impact perceptual processing. While we recorded electroencephalography (EEG) and pupillometry data, stimuli of a demanding auditory discrimination task were presented into states of high or low desynchronization of auditory cortex via a real-time closed-loop setup. Desynchronization and arousal distinctly influenced stimulus-evoked activity and shaped behaviour displaying an inverted u-shaped relationship: States of intermediate desynchronization elicited minimal response bias and fastest responses, while states of intermediate arousal gave rise to highest response sensitivity. Our results speak to a model in which independent states of local desynchronization and global arousal jointly optimise sensory processing and performance.
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Affiliation(s)
| | - Sarah Tune
- Department of PsychologyUniversity of LübeckLübeckGermany
| | - Jonas Obleser
- Department of PsychologyUniversity of LübeckLübeckGermany
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25
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Alishbayli A, Tichelaar JG, Gorska U, Cohen MX, Englitz B. The asynchronous state's relation to large-scale potentials in cortex. J Neurophysiol 2019; 122:2206-2219. [PMID: 31642401 PMCID: PMC6966315 DOI: 10.1152/jn.00013.2019] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 08/08/2019] [Accepted: 08/08/2019] [Indexed: 11/22/2022] Open
Abstract
Understanding the relation between large-scale potentials (M/EEG) and their underlying neural activity can improve the precision of research and clinical diagnosis. Recent insights into cortical dynamics highlighted a state of strongly reduced spike count correlations, termed the asynchronous state (AS). The AS has received considerable attention from experimenters and theorists alike, regarding its implications for cortical dynamics and coding of information. However, how reconcilable are these vanishing correlations in the AS with large-scale potentials such as M/EEG observed in most experiments? Typically the latter are assumed to be based on underlying correlations in activity, in particular between subthreshold potentials. We survey the occurrence of the AS across brain states, regions, and layers and argue for a reconciliation of this seeming disparity: large-scale potentials are either observed, first, at transitions between cortical activity states, which entail transient changes in population firing rate, as well as during the AS, and, second, on the basis of sufficiently large, asynchronous populations that only need to exhibit weak correlations in activity. Cells with no or little spiking activity can contribute to large-scale potentials via their subthreshold currents, while they do not contribute to the estimation of spiking correlations, defining the AS. Furthermore, third, the AS occurs only within particular cortical regions and layers associated with the currently selected modality, allowing for correlations at other times and between other areas and layers.
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Affiliation(s)
- A. Alishbayli
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Tactile Perception and Learning Laboratory, International School for Advanced Studies, Trieste, Italy
| | - J. G. Tichelaar
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - U. Gorska
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Psychophysiology Laboratory, Institute of Psychology, Jagiellonian University, Krakow, Poland
- Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland
| | - M. X. Cohen
- Department of Neuroinformatics, Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - B. Englitz
- Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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26
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Nandy A, Nassi JJ, Jadi MP, Reynolds J. Optogenetically induced low-frequency correlations impair perception. eLife 2019; 8:35123. [PMID: 30794156 PMCID: PMC6391072 DOI: 10.7554/elife.35123] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Accepted: 02/06/2019] [Indexed: 11/13/2022] Open
Abstract
Deployment of covert attention to a spatial location can cause large decreases in low-frequency correlated variability among neurons in macaque area V4 whose receptive-fields lie at the attended location. It has been estimated that this reduction accounts for a substantial fraction of the attention-mediated improvement in sensory processing. These estimates depend on assumptions about how population signals are decoded and the conclusion that correlated variability impairs perception, is purely hypothetical. Here we test this proposal directly by optogenetically inducing low-frequency fluctuations, to see if this interferes with performance in an attention-demanding task. We find that low-frequency optical stimulation of neurons in V4 elevates correlations among pairs of neurons and impairs the animal’s ability to make fine sensory discriminations. Stimulation at higher frequencies does not impair performance, despite comparable modulation of neuronal responses. These results support the hypothesis that attention-dependent reductions in correlated variability contribute to improved perception of attended stimuli.
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Affiliation(s)
- Anirvan Nandy
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, United States.,Department of Neuroscience, Yale University, New Haven, United States
| | - Jonathan J Nassi
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, United States
| | - Monika P Jadi
- Department of Neuroscience, Yale University, New Haven, United States.,Department of Psychiatry, Yale University, New Haven, United States
| | - John Reynolds
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, United States
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