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Stan PL, Smith MA. Recent Visual Experience Reshapes V4 Neuronal Activity and Improves Perceptual Performance. J Neurosci 2024; 44:e1764232024. [PMID: 39187380 PMCID: PMC11466072 DOI: 10.1523/jneurosci.1764-23.2024] [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: 09/18/2023] [Revised: 07/10/2024] [Accepted: 08/13/2024] [Indexed: 08/28/2024] Open
Abstract
Recent visual experience heavily influences our visual perception, but how neuronal activity is reshaped to alter and improve perceptual discrimination remains unknown. We recorded from populations of neurons in visual cortical area V4 while two male rhesus macaque monkeys performed a natural image change detection task under different experience conditions. We found that maximizing the recent experience with a particular image led to an improvement in the ability to detect a change in that image. This improvement was associated with decreased neural responses to the image, consistent with neuronal changes previously seen in studies of adaptation and expectation. We found that the magnitude of behavioral improvement was correlated with the magnitude of response suppression. Furthermore, this suppression of activity led to an increase in signal separation, providing evidence that a reduction in activity can improve stimulus encoding. Within populations of neurons, greater recent experience was associated with decreased trial-to-trial shared variability, indicating that a reduction in variability is a key means by which experience influences perception. Taken together, the results of our study contribute to an understanding of how recent visual experience can shape our perception and behavior through modulating activity patterns in the mid-level visual cortex.
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Affiliation(s)
- Patricia L Stan
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
- Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, Pennsylvania 15213
| | - Matthew A Smith
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
- Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, Pennsylvania 15213
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Mohammadi M, Carriot J, Mackrous I, Cullen KE, Chacron MJ. Neural populations within macaque early vestibular pathways are adapted to encode natural self-motion. PLoS Biol 2024; 22:e3002623. [PMID: 38687807 PMCID: PMC11086886 DOI: 10.1371/journal.pbio.3002623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 05/10/2024] [Accepted: 04/11/2024] [Indexed: 05/02/2024] Open
Abstract
How the activities of large neural populations are integrated in the brain to ensure accurate perception and behavior remains a central problem in systems neuroscience. Here, we investigated population coding of naturalistic self-motion by neurons within early vestibular pathways in rhesus macaques (Macacca mulatta). While vestibular neurons displayed similar dynamic tuning to self-motion, inspection of their spike trains revealed significant heterogeneity. Further analysis revealed that, during natural but not artificial stimulation, heterogeneity resulted primarily from variability across neurons as opposed to trial-to-trial variability. Interestingly, vestibular neurons displayed different correlation structures during naturalistic and artificial self-motion. Specifically, while correlations due to the stimulus (i.e., signal correlations) did not differ, correlations between the trial-to-trial variabilities of neural responses (i.e., noise correlations) were instead significantly positive during naturalistic but not artificial stimulation. Using computational modeling, we show that positive noise correlations during naturalistic stimulation benefits information transmission by heterogeneous vestibular neural populations. Taken together, our results provide evidence that neurons within early vestibular pathways are adapted to the statistics of natural self-motion stimuli at the population level. We suggest that similar adaptations will be found in other systems and species.
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Affiliation(s)
- Mohammad Mohammadi
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Canada
| | - Jerome Carriot
- Department of Physiology, McGill University, Montreal, Canada
| | | | - Kathleen E. Cullen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, Maryland, United States of America
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Tring E, Dipoppa M, Ringach DL. A power law describes the magnitude of adaptation in neural populations of primary visual cortex. Nat Commun 2023; 14:8366. [PMID: 38102113 PMCID: PMC10724159 DOI: 10.1038/s41467-023-43572-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 11/14/2023] [Indexed: 12/17/2023] Open
Abstract
How do neural populations adapt to the time-varying statistics of sensory input? We used two-photon imaging to measure the activity of neurons in mouse primary visual cortex adapted to different sensory environments, each defined by a distinct probability distribution over a stimulus set. We find that two properties of adaptation capture how the population response to a given stimulus, viewed as a vector, changes across environments. First, the ratio between the response magnitudes is a power law of the ratio between the stimulus probabilities. Second, the response direction to a stimulus is largely invariant. These rules could be used to predict how cortical populations adapt to novel, sensory environments. Finally, we show how the power law enables the cortex to preferentially signal unexpected stimuli and to adjust the metabolic cost of its sensory representation to the entropy of the environment.
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Affiliation(s)
- Elaine Tring
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Mario Dipoppa
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Dario L Ringach
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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Li JY, Glickfeld LL. Input-specific synaptic depression shapes temporal integration in mouse visual cortex. Neuron 2023; 111:3255-3269.e6. [PMID: 37543037 PMCID: PMC10592405 DOI: 10.1016/j.neuron.2023.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 06/07/2023] [Accepted: 07/06/2023] [Indexed: 08/07/2023]
Abstract
Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, brief stimulus presentation engages a distinct adaptation mechanism from that previously reported in response to prolonged stimuli, enabling flexible control of sensory encoding across a wide range of timescales.
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Affiliation(s)
- Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA.
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Tring E, Dipoppa M, Ringach DL. On the contrast response function of adapted neural populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.06.561309. [PMID: 37873350 PMCID: PMC10592696 DOI: 10.1101/2023.10.06.561309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The magnitude of neural responses in sensory cortex depends on the intensity of a stimulus and its probability of being observed within the environment. How these two variables combine to influence the overall response of cortical populations remains unknown. Here we show that, in primary visual cortex, the vector magnitude of the population response is described by a separable power-law that factors the intensity of a stimulus and its probability.
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Affiliation(s)
- Elaine Tring
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles
| | - Mario Dipoppa
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles
| | - Dario L Ringach
- Department of Psychology, David Geffen School of Medicine, University of California, Los Angeles
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles
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Tring E, Dipoppa M, Ringach DL. A power law of cortical adaptation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.22.541834. [PMID: 37292876 PMCID: PMC10245856 DOI: 10.1101/2023.05.22.541834] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
How do neural populations adapt to the time-varying statistics of sensory input? To investigate, we measured the activity of neurons in primary visual cortex adapted to different environments, each associated with a distinct probability distribution over a stimulus set. Within each environment, a stimulus sequence was generated by independently sampling form its distribution. We find that two properties of adaptation capture how the population responses to a given stimulus, viewed as vectors, are linked across environments. First, the ratio between the response magnitudes is a power law of the ratio between the stimulus probabilities. Second, the response directions are largely invariant. These rules can be used to predict how cortical populations adapt to novel, sensory environments. Finally, we show how the power law enables the cortex to preferentially signal unexpected stimuli and to adjust the metabolic cost of its sensory representation to the entropy of the environment.
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Affiliation(s)
- Elaine Tring
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles
| | - Mario Dipoppa
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles
| | - Dario L Ringach
- Department of Psychology, David Geffen School of Medicine, University of California, Los Angeles
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles
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Li JY, Glickfeld LL. Input-specific synaptic depression shapes temporal integration in mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.30.526211. [PMID: 36778279 PMCID: PMC9915496 DOI: 10.1101/2023.01.30.526211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation, but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, distinct mechanisms are engaged following brief and prolonged stimulus presentation and together enable flexible control of sensory encoding across a wide range of time scales.
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Affiliation(s)
- Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
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