1
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Cone JJ, Mitchell AO, Parker RK, Maunsell JHR. Stimulus-dependent differences in cortical versus subcortical contributions to visual detection in mice. Curr Biol 2024; 34:1940-1952.e5. [PMID: 38640924 PMCID: PMC11080572 DOI: 10.1016/j.cub.2024.03.061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 02/08/2024] [Accepted: 03/27/2024] [Indexed: 04/21/2024]
Abstract
The primary visual cortex (V1) and the superior colliculus (SC) both occupy stations early in the processing of visual information. They have long been thought to perform distinct functions, with the V1 supporting the perception of visual features and the SC regulating orienting to visual inputs. However, growing evidence suggests that the SC supports the perception of many of the same visual features traditionally associated with the V1. To distinguish V1 and SC contributions to visual processing, it is critical to determine whether both areas causally contribute to the detection of specific visual stimuli. Here, mice reported changes in visual contrast or luminance near their perceptual threshold while white noise patterns of optogenetic stimulation were delivered to V1 or SC inhibitory neurons. We then performed a reverse correlation analysis on the optogenetic stimuli to estimate a neuronal-behavioral kernel (NBK), a moment-to-moment estimate of the impact of V1 or SC inhibition on stimulus detection. We show that the earliest moments of stimulus-evoked activity in the SC are critical for the detection of both luminance and contrast changes. Strikingly, there was a robust stimulus-aligned modulation in the V1 contrast-detection NBK but no sign of a comparable modulation for luminance detection. The data suggest that behavioral detection of visual contrast depends on both V1 and SC spiking, whereas mice preferentially use SC activity to detect changes in luminance. Electrophysiological recordings showed that neurons in both the SC and V1 responded strongly to both visual stimulus types, while the reverse correlation analysis reveals when these neuronal signals actually contribute to visually guided behaviors.
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Affiliation(s)
- Jackson J Cone
- Department of Neurobiology and Neuroscience Institute, University of Chicago, 5812 S. Ellis Ave. MC 0912, Suite P-400, Chicago, IL 60637, USA.
| | - Autumn O Mitchell
- Department of Neurobiology and Neuroscience Institute, University of Chicago, 5812 S. Ellis Ave. MC 0912, Suite P-400, Chicago, IL 60637, USA
| | - Rachel K Parker
- Department of Neurobiology and Neuroscience Institute, University of Chicago, 5812 S. Ellis Ave. MC 0912, Suite P-400, Chicago, IL 60637, USA
| | - John H R Maunsell
- Department of Neurobiology and Neuroscience Institute, University of Chicago, 5812 S. Ellis Ave. MC 0912, Suite P-400, Chicago, IL 60637, USA
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2
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Russell LE, Fişek M, Yang Z, Tan LP, Packer AM, Dalgleish HWP, Chettih SN, Harvey CD, Häusser M. The influence of cortical activity on perception depends on behavioral state and sensory context. Nat Commun 2024; 15:2456. [PMID: 38503769 PMCID: PMC10951313 DOI: 10.1038/s41467-024-46484-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 02/28/2024] [Indexed: 03/21/2024] Open
Abstract
The mechanistic link between neural circuit activity and behavior remains unclear. While manipulating cortical activity can bias certain behaviors and elicit artificial percepts, some tasks can still be solved when cortex is silenced or removed. Here, mice were trained to perform a visual detection task during which we selectively targeted groups of visually responsive and co-tuned neurons in L2/3 of primary visual cortex (V1) for two-photon photostimulation. The influence of photostimulation was conditional on two key factors: the behavioral state of the animal and the contrast of the visual stimulus. The detection of low-contrast stimuli was enhanced by photostimulation, while the detection of high-contrast stimuli was suppressed, but crucially, only when mice were highly engaged in the task. When mice were less engaged, our manipulations of cortical activity had no effect on behavior. The behavioral changes were linked to specific changes in neuronal activity. The responses of non-photostimulated neurons in the local network were also conditional on two factors: their functional similarity to the photostimulated neurons and the contrast of the visual stimulus. Functionally similar neurons were increasingly suppressed by photostimulation with increasing visual stimulus contrast, correlating with the change in behavior. Our results show that the influence of cortical activity on perception is not fixed, but dynamically and contextually modulated by behavioral state, ongoing activity and the routing of information through specific circuits.
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Affiliation(s)
- Lloyd E Russell
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Mehmet Fişek
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Zidan Yang
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Lynn Pei Tan
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Adam M Packer
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Henry W P Dalgleish
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | | | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK.
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3
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Bolaños F, Orlandi JG, Aoki R, Jagadeesh AV, Gardner JL, Benucci A. Efficient coding of natural images in the mouse visual cortex. Nat Commun 2024; 15:2466. [PMID: 38503746 PMCID: PMC10951403 DOI: 10.1038/s41467-024-45919-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 02/06/2024] [Indexed: 03/21/2024] Open
Abstract
How the activity of neurons gives rise to natural vision remains a matter of intense investigation. The mid-level visual areas along the ventral stream are selective to a common class of natural images-textures-but a circuit-level understanding of this selectivity and its link to perception remains unclear. We addressed these questions in mice, first showing that they can perceptually discriminate between textures and statistically simpler spectrally matched stimuli, and between texture types. Then, at the neural level, we found that the secondary visual area (LM) exhibited a higher degree of selectivity for textures compared to the primary visual area (V1). Furthermore, textures were represented in distinct neural activity subspaces whose relative distances were found to correlate with the statistical similarity of the images and the mice's ability to discriminate between them. Notably, these dependencies were more pronounced in LM, where the texture-related subspaces were smaller than in V1, resulting in superior stimulus decoding capabilities. Together, our results demonstrate texture vision in mice, finding a linking framework between stimulus statistics, neural representations, and perceptual sensitivity-a distinct hallmark of efficient coding computations.
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Affiliation(s)
- Federico Bolaños
- University of British Columbia, Neuroimaging and NeuroComputation Centre, Vancouver, BC, V6T, Canada
| | - Javier G Orlandi
- University of Calgary, Department of Physics and Astronomy, Calgary, AB, T2N 1N4, Canada.
| | - Ryo Aoki
- RIKEN Center for Brain Science, Laboratory for Neural Circuits and Behavior, Wakoshi, Japan
| | | | - Justin L Gardner
- Stanford University, Wu Tsai Neurosciences Institute, Stanford, CA, USA
| | - Andrea Benucci
- RIKEN Center for Brain Science, Laboratory for Neural Circuits and Behavior, Wakoshi, Japan.
- Queen Mary, University of London, School of Biological and Behavioral Science, London, E1 4NS, UK.
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4
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Cazemier JL, Haak R, Tran TKL, Hsu ATY, Husic M, Peri BD, Kirchberger L, Self MW, Roelfsema P, Heimel JA. Involvement of superior colliculus in complex figure detection of mice. eLife 2024; 13:e83708. [PMID: 38270590 PMCID: PMC10810606 DOI: 10.7554/elife.83708] [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: 09/28/2022] [Accepted: 01/08/2024] [Indexed: 01/26/2024] Open
Abstract
Object detection is an essential function of the visual system. Although the visual cortex plays an important role in object detection, the superior colliculus can support detection when the visual cortex is ablated or silenced. Moreover, it has been shown that superficial layers of mouse SC (sSC) encode visual features of complex objects, and that this code is not inherited from the primary visual cortex. This suggests that mouse sSC may provide a significant contribution to complex object vision. Here, we use optogenetics to show that mouse sSC is involved in figure detection based on differences in figure contrast, orientation, and phase. Additionally, our neural recordings show that in mouse sSC, image elements that belong to a figure elicit stronger activity than those same elements when they are part of the background. The discriminability of this neural code is higher for correct trials than for incorrect trials. Our results provide new insight into the behavioral relevance of the visual processing that takes place in sSC.
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Affiliation(s)
- J Leonie Cazemier
- Department of Circuits, Structure & Function, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - Robin Haak
- Department of Circuits, Structure & Function, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - TK Loan Tran
- Department of Circuits, Structure & Function, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - Ann TY Hsu
- Department of Circuits, Structure & Function, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - Medina Husic
- Department of Circuits, Structure & Function, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - Brandon D Peri
- Department of Circuits, Structure & Function, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - Lisa Kirchberger
- Department of Vision and Cognition, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - Matthew W Self
- Department of Vision and Cognition, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
| | - Pieter Roelfsema
- Department of Vision and Cognition, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
- Department of Integrative Neurophysiology, VU UniversityAmsterdamNetherlands
- Department of Psychiatry, Academic Medical CentreAmsterdamNetherlands
- Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la VisionParisFrance
| | - J Alexander Heimel
- Department of Circuits, Structure & Function, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW)AmsterdamNetherlands
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5
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Tang Y, Gervais C, Moffitt R, Nareddula S, Zimmermann M, Nadew YY, Quinn CJ, Saldarriaga V, Edens P, Chubykin AA. Visual experience induces 4-8 Hz synchrony between V1 and higher-order visual areas. Cell Rep 2023; 42:113482. [PMID: 37999977 PMCID: PMC10790627 DOI: 10.1016/j.celrep.2023.113482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 09/20/2023] [Accepted: 11/07/2023] [Indexed: 11/26/2023] Open
Abstract
Visual perceptual experience induces persistent 4-8 Hz oscillations in the mouse primary visual cortex (V1), encoding visual familiarity. Recent studies suggest that higher-order visual areas (HVAs) are functionally specialized and segregated into information streams processing distinct visual features. However, whether visual memories are processed and stored within the distinct streams is not understood. We report here that V1 and lateromedial (LM), but not V1 and anterolateral, become more phase synchronized in 4-8 Hz after the entrainment of visual stimulus that maximally induces responses in LM. Directed information analysis reveals changes in the top-down functional connectivity between V1 and HVAs. Optogenetic inactivation of LM reduces post-stimulus oscillation peaks in V1 and impairs visual discrimination behavior. Our results demonstrate that 4-8 Hz familiarity-evoked oscillations are specific for the distinct visual features and are present in the corresponding HVAs, where they may be used for the inter-areal communication with V1 during memory-related behaviors.
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Affiliation(s)
- Yu Tang
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Catherine Gervais
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Rylann Moffitt
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Sanghamitra Nareddula
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Michael Zimmermann
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Yididiya Y Nadew
- Department of Computer Sciences, Iowa State University, Ames, IA 50011, USA
| | | | - Violeta Saldarriaga
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Paige Edens
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Alexander A Chubykin
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA.
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6
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O'Rawe JF, Zhou Z, Li AJ, LaFosse PK, Goldbach HC, Histed MH. Excitation creates a distributed pattern of cortical suppression due to varied recurrent input. Neuron 2023; 111:4086-4101.e5. [PMID: 37865083 PMCID: PMC10872553 DOI: 10.1016/j.neuron.2023.09.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 05/14/2023] [Accepted: 09/08/2023] [Indexed: 10/23/2023]
Abstract
Dense local, recurrent connections are a major feature of cortical circuits, yet how they affect neurons' responses has been unclear, with some studies reporting weak recurrent effects, some reporting amplification, and others indicating local suppression. Here, we show that optogenetic input to mouse V1 excitatory neurons generates salt-and-pepper patterns of both excitation and suppression. Responses in individual neurons are not strongly predicted by that neuron's direct input. A balanced-state network model reconciles a set of diverse observations: the observed dynamics, suppressed responses, decoupling of input and output, and long tail of excited responses. The model shows recurrent excitatory-excitatory connections are strong and also variable across neurons. Together, these results demonstrate that excitatory recurrent connections can have major effects on cortical computations by shaping and changing neurons' responses to input.
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Affiliation(s)
- Jonathan F O'Rawe
- National Institute of Mental Health Intramural Program, NIH, Bethesda, MD, USA
| | - Zhishang Zhou
- National Institute of Mental Health Intramural Program, NIH, Bethesda, MD, USA
| | - Anna J Li
- National Institute of Mental Health Intramural Program, NIH, Bethesda, MD, USA
| | - Paul K LaFosse
- National Institute of Mental Health Intramural Program, NIH, Bethesda, MD, USA; NIH-University of Maryland Graduate Partnerships Program, Bethesda, MD, USA; Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, USA
| | - Hannah C Goldbach
- National Institute of Mental Health Intramural Program, NIH, Bethesda, MD, USA
| | - Mark H Histed
- National Institute of Mental Health Intramural Program, NIH, Bethesda, MD, USA.
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7
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LaFosse PK, Zhou Z, Scott VM, Deng Y, Histed MH. Single cell optogenetics reveals attenuation-by-suppression in visual cortical neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.13.557650. [PMID: 37745464 PMCID: PMC10515908 DOI: 10.1101/2023.09.13.557650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The relationship between neurons' input and spiking output is central to brain computation. Studies in vitro and in anesthetized animals suggest nonlinearities emerge in cells' input-output (activation) functions as network activity increases, yet how neurons transform inputs in vivo has been unclear. Here, we characterize cortical principal neurons' activation functions in awake mice using two-photon optogenetics and imaging. We find responses to fixed optogenetic input are nearly unchanged as neurons are excited, reflecting a linear response regime above neurons' resting point. In contrast, responses are dramatically attenuated by suppression. This attenuation is a powerful means to filter inputs arriving to suppressed cells, privileging other inputs arriving to excited neurons. These data have two major implications: first, neural activation functions in vivo accord with the activation functions used in recent machine learning systems, and second, neurons' IO functions can enhance sensory processing by attenuating some inputs while leaving others unchanged.
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Affiliation(s)
- Paul K LaFosse
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
- NIH-University of Maryland Graduate Partnerships Program, Bethesda, MD USA 20892
- Neuroscience and Cognitive Science Program, University of Maryland College Park, College Park, MD USA 20742
| | - Zhishang Zhou
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
| | - Victoria M Scott
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
| | - Yanting Deng
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
| | - Mark H Histed
- Intramural Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA 20892
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8
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Cone JJ, Mitchell AO, Parker RK, Maunsell JHR. Temporal weighting of cortical and subcortical spikes reveals stimulus dependent differences in their contributions to behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.23.554473. [PMID: 37662213 PMCID: PMC10473714 DOI: 10.1101/2023.08.23.554473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The primary visual cortex (V1) and the superior colliculus (SC) both occupy stations early in the processing of visual information. They have long been thought to perform distinct functions, with V1 supporting perception of visual features and the SC regulating orienting to visual inputs. However, growing evidence suggests that the SC supports perception of many of the same visual features traditionally associated with V1. To distinguish V1 and SC contributions to visual processing, it is critical to determine whether both areas causally contribute to perception of specific visual stimuli. Here, mice reported changes in visual contrast or luminance near perceptual threshold while we presented white noise patterns of optogenetic stimulation to V1 or SC inhibitory neurons. We then performed a reverse correlation analysis on the optogenetic stimuli to estimate a neuronal-behavioral kernel (NBK), a moment-to-moment estimate of the impact of V1 or SC inhibition on stimulus detection. We show that the earliest moments of stimulus-evoked activity in SC are critical for detection of both luminance or contrast changes. Strikingly, there was a robust stimulus-aligned modulation in the V1 contrast-detection NBK, but no sign of a comparable modulation for luminance detection. The data suggest that perception of visual contrast depends on both V1 and SC spiking, whereas mice preferentially use SC activity to detect changes in luminance. Electrophysiological recordings showed that neurons in both SC and V1 responded strongly to both visual stimulus types, while the reverse correlation analysis reveals when these neuronal signals actually contribute to visually-guided behaviors.
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9
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Akitake B, Douglas HM, LaFosse PK, Beiran M, Deveau CE, O'Rawe J, Li AJ, Ryan LN, Duffy SP, Zhou Z, Deng Y, Rajan K, Histed MH. Amplified cortical neural responses as animals learn to use novel activity patterns. Curr Biol 2023; 33:2163-2174.e4. [PMID: 37148876 DOI: 10.1016/j.cub.2023.04.032] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 02/09/2023] [Accepted: 04/14/2023] [Indexed: 05/08/2023]
Abstract
Cerebral cortex supports representations of the world in patterns of neural activity, used by the brain to make decisions and guide behavior. Past work has found diverse, or limited, changes in the primary sensory cortex in response to learning, suggesting that the key computations might occur in downstream regions. Alternatively, sensory cortical changes may be central to learning. We studied cortical learning by using controlled inputs we insert: we trained mice to recognize entirely novel, non-sensory patterns of cortical activity in the primary visual cortex (V1) created by optogenetic stimulation. As animals learned to use these novel patterns, we found that their detection abilities improved by an order of magnitude or more. The behavioral change was accompanied by large increases in V1 neural responses to fixed optogenetic input. Neural response amplification to novel optogenetic inputs had little effect on existing visual sensory responses. A recurrent cortical model shows that this amplification can be achieved by a small mean shift in recurrent network synaptic strength. Amplification would seem to be desirable to improve decision-making in a detection task; therefore, these results suggest that adult recurrent cortical plasticity plays a significant role in improving behavioral performance during learning.
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Affiliation(s)
- Bradley Akitake
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Hannah M Douglas
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Paul K LaFosse
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Manuel Beiran
- Nash Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Ciana E Deveau
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jonathan O'Rawe
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Anna J Li
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lauren N Ryan
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Samuel P Duffy
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Zhishang Zhou
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yanting Deng
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kanaka Rajan
- Nash Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mark H Histed
- Unit on Neural Computation and Behavior, National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD 20892, USA.
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10
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Shin D, Peelman K, Lien AD, Del Rosario J, Haider B. Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system. Neuron 2023; 111:1076-1085.e8. [PMID: 37023711 PMCID: PMC10112544 DOI: 10.1016/j.neuron.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 12/16/2022] [Accepted: 03/06/2023] [Indexed: 04/08/2023]
Abstract
Oscillations of neural activity permeate sensory systems. In the visual system, broadband gamma oscillations (30-80 Hz) are thought to act as a communication mechanism underlying perception. However, these oscillations show widely varying frequency and phase, providing constraints for coordinating spike timing across areas. Here, we examined Allen Brain Observatory data and performed causal experiments to show that narrowband gamma (NBG) oscillations (50-70 Hz) propagate and synchronize throughout the awake mouse visual system. Lateral geniculate nucleus (LGN) neurons fired precisely relative to NBG phase in primary visual cortex (V1) and multiple higher visual areas (HVAs). NBG neurons across areas showed a higher likelihood of functional connectivity and stronger visual responses; remarkably, NBG neurons in LGN, preferring bright (ON) versus dark (OFF), fired at distinct NBG phases aligned across the cortical hierarchy. NBG oscillations may thus serve to coordinate spike timing across brain areas and facilitate communication of distinct visual features during perception.
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Affiliation(s)
- Donghoon Shin
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA; Electrical and Computer Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA; Bioengineering, UCSF - UC Berkeley Joint PhD Program, San Francisco, CA, USA
| | - Kayla Peelman
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Anthony D Lien
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Joseph Del Rosario
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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11
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Basal Forebrain Chemogenetic Inhibition Converts the Attentional Control Mode of Goal-Trackers to That of Sign-Trackers. eNeuro 2022; 9:ENEURO.0418-22.2022. [PMID: 36635246 PMCID: PMC9794377 DOI: 10.1523/eneuro.0418-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/06/2022] [Accepted: 11/29/2022] [Indexed: 12/14/2022] Open
Abstract
Sign tracking versus goal tracking in rats indicate vulnerability and resistance, respectively, to Pavlovian cue-evoked addictive drug taking and relapse. Here, we tested hypotheses predicting that the opponent cognitive-behavioral styles indexed by sign tracking versus goal tracking include variations in attentional performance which differentially depend on basal forebrain projection systems. Pavlovian Conditioned Approach (PCA) testing was used to identify male and female sign-trackers (STs) and goal-trackers (GTs), as well as rats with an intermediate phenotype (INTs). Upon reaching asymptotic performance in an operant task requiring the detection of visual signals (hits) as well as the reporting of signal absence for 40 min per session, GTs scored more hits than STs, and hit rates across all phenotypes correlated with PCA scores. STs missed relatively more signals than GTs specifically during the last 15 min of a session. Chemogenetic inhibition of the basal forebrain decreased hit rates in GTs but was without effect in STs. Moreover, the decrease in hits in GTs manifested solely during the last 15 min of a session. Transfection efficacy in the horizontal limb of the diagonal band (HDB), but not substantia innominate (SI) or nucleus basalis of Meynert (nbM), predicted the behavioral efficacy of chemogenetic inhibition in GTs. Furthermore, the total subregional transfection space, not transfection of just cholinergic neurons, correlated with performance effects. These results indicate that the cognitive-behavioral phenotype indexed by goal tracking, but not sign tracking, depends on activation of the basal forebrain-frontal cortical projection system and associated biases toward top-down or model-based performance.
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12
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Javadzadeh M, Hofer SB. Dynamic causal communication channels between neocortical areas. Neuron 2022; 110:2470-2483.e7. [PMID: 35690063 PMCID: PMC9616801 DOI: 10.1016/j.neuron.2022.05.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 03/26/2022] [Accepted: 05/12/2022] [Indexed: 11/08/2022]
Abstract
Processing of sensory information depends on the interactions between hierarchically connected neocortical regions, but it remains unclear how the activity in one area causally influences the activity dynamics in another and how rapidly such interactions change with time. Here, we show that the communication between the primary visual cortex (V1) and high-order visual area LM is context-dependent and surprisingly dynamic over time. By momentarily silencing one area while recording activity in the other, we find that both areas reliably affected changing subpopulations of target neurons within one hundred milliseconds while mice observed a visual stimulus. The influence of LM feedback on V1 responses became even more dynamic when the visual stimuli predicted a reward, causing fast changes in the geometry of V1 population activity and affecting stimulus coding in a context-dependent manner. Therefore, the functional interactions between cortical areas are not static but unfold through rapidly shifting communication subspaces whose dynamics depend on context when processing sensory information. Optogenetic perturbations reveal the causal structure of long-range cortical influences How visual areas influence each other changes dynamically over tens of milliseconds Feedback to V1 improves visual stimulus encoding required for behavior The dynamics of feedback influences depend on the behavioral context
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Affiliation(s)
- Mitra Javadzadeh
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
| | - Sonja B Hofer
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
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13
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Diversity of spatiotemporal coding reveals specialized visual processing streams in the mouse cortex. Nat Commun 2022; 13:3249. [PMID: 35668056 PMCID: PMC9170684 DOI: 10.1038/s41467-022-29656-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 03/23/2022] [Indexed: 12/23/2022] Open
Abstract
The cerebral cortex contains diverse neural representations of the visual scene, each enabling distinct visual and spatial abilities. However, the extent to which representations are distributed or segregated across cortical areas remains poorly understood. By determining the spatial and temporal responses of >30,000 layer 2/3 pyramidal neurons, we characterize the functional organization of parallel visual streams across eight areas of the mouse cortex. While dorsal and ventral areas form complementary representations of spatiotemporal frequency, motion speed, and spatial patterns, the anterior and posterior dorsal areas show distinct specializations for fast and slow oriented contrasts. At the cellular level, while diverse spatiotemporal tuning lies along a continuum, oriented and non-oriented spatial patterns are encoded by distinct tuning types. The identified tuning types are present across dorsal and ventral streams. The data underscore the highly specific and highly distributed nature of visual cortical representations, which drives specialization of cortical areas and streams. The cerebral cortex contains different neural representations of the visual scene. Here, the authors show diverse and stereotyped tuning composing specialized representations in the dorsal and ventral areas of the mouse visual cortex, suggesting parallel processing channels and streams.
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14
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Yu Y, Stirman JN, Dorsett CR, Smith SL. Selective representations of texture and motion in mouse higher visual areas. Curr Biol 2022; 32:2810-2820.e5. [PMID: 35609609 DOI: 10.1016/j.cub.2022.04.091] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 03/22/2022] [Accepted: 04/28/2022] [Indexed: 10/18/2022]
Abstract
The mouse visual cortex contains interconnected higher visual areas, but their functional specializations are unclear. Here, we used a data-driven approach to examine the representations of complex visual stimuli by L2/3 neurons across mouse higher visual areas, measured using large-field-of-view two-photon calcium imaging. Using specialized stimuli, we found higher fidelity representations of texture in area LM, compared to area AL. Complementarily, we found higher fidelity representations of motion in area AL, compared to area LM. We also observed this segregation of information in response to naturalistic videos. Finally, we explored how receptive field models of visual cortical neurons could produce the segregated representations of texture and motion we observed. These selective representations could aid in behaviors such as visually guided navigation.
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Affiliation(s)
- Yiyi Yu
- Department of Electrical & Computer Engineering, Center for BioEngineering, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Jeffrey N Stirman
- Neuroscience Research Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Christopher R Dorsett
- Neuroscience Research Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Spencer L Smith
- Department of Electrical & Computer Engineering, Center for BioEngineering, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA.
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15
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Day-Cooney J, Cone JJ, Maunsell JHR. Perceptual Weighting of V1 Spikes Revealed by Optogenetic White Noise Stimulation. J Neurosci 2022; 42:3122-3132. [PMID: 35232760 PMCID: PMC8994541 DOI: 10.1523/jneurosci.1736-21.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 01/17/2022] [Accepted: 01/19/2022] [Indexed: 11/21/2022] Open
Abstract
During visually guided behaviors, mere hundreds of milliseconds can elapse between a sensory input and its associated behavioral response. How spikes occurring at different times are integrated to drive perception and action remains poorly understood. We delivered random trains of optogenetic stimulation (white noise) to excite inhibitory interneurons in V1 of mice of both sexes while they performed a visual detection task. We then performed a reverse correlation analysis on the optogenetic stimuli to generate a neuronal-behavioral kernel, an unbiased, temporally precise estimate of how suppression of V1 spiking at different moments around the onset of a visual stimulus affects detection of that stimulus. Electrophysiological recordings enabled us to capture the effects of optogenetic stimuli on V1 responsivity and revealed that the earliest stimulus-evoked spikes are preferentially weighted for guiding behavior. These data demonstrate that white noise optogenetic stimulation is a powerful tool for understanding how patterns of spiking in neuronal populations are decoded in generating perception and action.SIGNIFICANCE STATEMENT During visually guided actions, continuous chains of neurons connect our retinas to our motoneurons. To unravel circuit contributions to behavior, it is crucial to establish the relative functional position(s) that different neural structures occupy in processing and relaying the signals that support rapid, precise responses. To address this question, we randomly inhibited activity in mouse V1 throughout the stimulus-response cycle while the animals did many repetitions of a visual task. The period that led to impaired performance corresponded to the earliest stimulus-driven response in V1, with no effect of inhibition immediately before or during late stages of the stimulus-driven response. This approach offers experimenters a powerful method for uncovering the temporal weighting of spikes from stimulus to response.
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Affiliation(s)
- Julian Day-Cooney
- Department of Neurobiology and Neuroscience Institute, University of Chicago, Chicago, Illinois 60637
| | - Jackson J Cone
- Department of Neurobiology and Neuroscience Institute, University of Chicago, Chicago, Illinois 60637
| | - John H R Maunsell
- Department of Neurobiology and Neuroscience Institute, University of Chicago, Chicago, Illinois 60637
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16
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Resulaj A. Projections of the Mouse Primary Visual Cortex. Front Neural Circuits 2021; 15:751331. [PMID: 34867213 PMCID: PMC8641241 DOI: 10.3389/fncir.2021.751331] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 10/28/2021] [Indexed: 11/13/2022] Open
Abstract
Lesion or damage to the primary visual cortex (V1) results in a profound loss of visual perception in humans. Similarly, in mice, optogenetic silencing of V1 profoundly impairs discrimination of orientated gratings. V1 is thought to have such a critical role in perception in part due to its position in the visual processing hierarchy. It is the first brain area in the neocortex to receive visual input, and it distributes this information to more than 18 brain areas. Here I review recent advances in our understanding of the organization and function of the V1 projections in the mouse. This progress is in part due to new anatomical and viral techniques that allow for efficient labeling of projection neurons. In the final part of the review, I conclude by highlighting challenges and opportunities for future research.
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Affiliation(s)
- Arbora Resulaj
- Department of Biology, University of Toronto Mississauga, Mississauga, ON, Canada.,Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
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17
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Speed A, Haider B. Probing mechanisms of visual spatial attention in mice. Trends Neurosci 2021; 44:822-836. [PMID: 34446296 PMCID: PMC8484049 DOI: 10.1016/j.tins.2021.07.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/05/2021] [Accepted: 07/30/2021] [Indexed: 11/25/2022]
Abstract
The role of spatial attention for visual perception has been thoroughly studied in primates, but less so in mice. Several behavioral tasks in mice reveal spatial attentional effects, with similarities to observations in primates. Pairing these tasks with large-scale, cell-type-specific techniques could enable deeper access to underlying mechanisms, and help define the utility and limitations of resolving attentional effects on visual perception and neural activity in mice. In this Review, we evaluate behavioral and neural evidence for visual spatial attention in mice; assess how specializations of the mouse visual system and behavioral repertoire impact interpretation of spatial attentional effects; and outline how several measurement and manipulation techniques in mice could precisely test and refine models of attentional modulation across scales.
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Affiliation(s)
- Anderson Speed
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA
| | - Bilal Haider
- Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA, USA.
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