1
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Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. Perirhinal cortex learns a predictive map of the task environment. Nat Commun 2024; 15:5544. [PMID: 38956015 PMCID: PMC11219840 DOI: 10.1038/s41467-024-47365-7] [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: 08/09/2023] [Accepted: 03/25/2024] [Indexed: 07/04/2024] Open
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
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Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Center for Neurophotonics, Boston University, Boston, MA, 02215, USA.
- Department of Biology, Boston University, Boston, MA, 02215, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, 02215, USA.
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2
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Piet A, Ponvert N, Ollerenshaw D, Garrett M, Groblewski PA, Olsen S, Koch C, Arkhipov A. Behavioral strategy shapes activation of the Vip-Sst disinhibitory circuit in visual cortex. Neuron 2024; 112:1876-1890.e4. [PMID: 38447579 PMCID: PMC11156560 DOI: 10.1016/j.neuron.2024.02.008] [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: 05/31/2023] [Revised: 11/17/2023] [Accepted: 02/08/2024] [Indexed: 03/08/2024]
Abstract
In complex environments, animals can adopt diverse strategies to find rewards. How distinct strategies differentially engage brain circuits is not well understood. Here, we investigate this question, focusing on the cortical Vip-Sst disinhibitory circuit between vasoactive intestinal peptide-postive (Vip) interneurons and somatostatin-positive (Sst) interneurons. We characterize the behavioral strategies used by mice during a visual change detection task. Using a dynamic logistic regression model, we find that individual mice use mixtures of a visual comparison strategy and a statistical timing strategy. Separately, mice also have periods of task engagement and disengagement. Two-photon calcium imaging shows large strategy-dependent differences in neural activity in excitatory, Sst inhibitory, and Vip inhibitory cells in response to both image changes and image omissions. In contrast, task engagement has limited effects on neural population activity. We find that the diversity of neural correlates of strategy can be understood parsimoniously as the increased activation of the Vip-Sst disinhibitory circuit during the visual comparison strategy, which facilitates task-appropriate responses.
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Affiliation(s)
- Alex Piet
- Allen Institute, Mindscope Program, Seattle, WA, USA.
| | - Nick Ponvert
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | | | | | | | - Shawn Olsen
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | - Christof Koch
- Allen Institute, Mindscope Program, Seattle, WA, USA
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3
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Zhu M, Kuhlman SJ, Barth AL. Transient enhancement of stimulus-evoked activity in neocortex during sensory learning. Learn Mem 2024; 31:a053870. [PMID: 38955432 PMCID: PMC11261211 DOI: 10.1101/lm.053870.123] [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: 09/15/2023] [Accepted: 05/07/2024] [Indexed: 07/04/2024]
Abstract
Synaptic potentiation has been linked to learning in sensory cortex, but the connection between this potentiation and increased sensory-evoked neural activity is not clear. Here, we used longitudinal in vivo Ca2+ imaging in the barrel cortex of awake mice to test the hypothesis that increased excitatory synaptic strength during the learning of a whisker-dependent sensory-association task would be correlated with enhanced stimulus-evoked firing. To isolate stimulus-evoked responses from dynamic, task-related activity, imaging was performed outside of the training context. Although prior studies indicate that multiwhisker stimuli drive robust subthreshold activity, we observed sparse activation of L2/3 pyramidal (Pyr) neurons in both control and trained mice. Despite evidence for excitatory synaptic strengthening at thalamocortical and intracortical synapses in this brain area at the onset of learning-indeed, under our imaging conditions thalamocortical axons were robustly activated-we observed that L2/3 Pyr neurons in somatosensory (barrel) cortex displayed only modest increases in stimulus-evoked activity that were concentrated at the onset of training. Activity renormalized over longer training periods. In contrast, when stimuli and rewards were uncoupled in a pseudotraining paradigm, stimulus-evoked activity in L2/3 Pyr neurons was significantly suppressed. These findings indicate that sensory-association training but not sensory stimulation without coupled rewards may briefly enhance sensory-evoked activity, a phenomenon that might help link sensory input to behavioral outcomes at the onset of learning.
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Affiliation(s)
- Mo Zhu
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Sandra J Kuhlman
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Alison L Barth
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
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4
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Do J, Jung MW, Lee D. Automating licking bias correction in a two-choice delayed match-to-sample task to accelerate learning. Sci Rep 2023; 13:22768. [PMID: 38123637 PMCID: PMC10733387 DOI: 10.1038/s41598-023-49862-z] [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: 08/03/2023] [Accepted: 12/12/2023] [Indexed: 12/23/2023] Open
Abstract
Animals often display choice bias, or a preference for one option over the others, which can significantly impede learning new tasks. Delayed match-to-sample (DMS) tasks with two-alternative choices of lickports on the left and right have been widely used to study sensory processing, working memory, and associative memory in head-fixed animals. However, extensive training time, primarily due to the animals' biased licking responses, limits their practical utility. Here, we present the implementation of an automated side bias correction system in an olfactory DMS task, where the lickport positions and the ratio of left- and right-rewarded trials are dynamically adjusted to counterbalance mouse's biased licking responses during training. The correction algorithm moves the preferred lickport farther away from the mouse's mouth and the non-preferred lickport closer, while also increasing the proportion of non-preferred side trials when biased licking occurs. We found that adjusting lickport distances and the proportions of left- versus right-rewarded trials effectively reduces the mouse's side bias. Further analyses reveal that these adjustments also correlate with subsequent improvements in behavioral performance. Our findings suggest that the automated side bias correction system is a valuable tool for enhancing the applicability of behavioral tasks involving two-alternative lickport choices.
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Affiliation(s)
- Jongrok Do
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Min Whan Jung
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, 34141, Republic of Korea.
| | - Doyun Lee
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
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5
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Alisha A, Bettina V, Simon P. Representational drift in barrel cortex is receptive field dependent. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.20.563381. [PMID: 37961727 PMCID: PMC10634719 DOI: 10.1101/2023.10.20.563381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Cortical populations often exhibit changes in activity even when behavior is stable. How behavioral stability is maintained in the face of such 'representational drift' remains unclear. One possibility is that some neurons are stable despite broader instability. We examine whisker touch responses in superficial layers of primary vibrissal somatosensory cortex (vS1) over several weeks in mice stably performing an object detection task with two whiskers. While the number of touch neurons remained constant, individual neurons changed with time. Touch-responsive neurons with broad receptive fields were more stable than narrowly tuned neurons. Transitions between functional types were non-random: before becoming broadly tuned neurons, unresponsive neurons first pass through a period of narrower tuning. Broadly tuned neurons with higher pairwise correlations to other touch neurons were more stable than neurons with lower correlations. Thus, a small population of broadly tuned and synchronously active touch neurons exhibit elevated stability and may be particularly important for downstream readout.
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Affiliation(s)
- Ahmed Alisha
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Voelcker Bettina
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
| | - Peron Simon
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003
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6
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Lee DG, McLachlan CA, Nogueira R, Kwon O, Carey AE, House G, Lagani GD, LaMay D, Fusi S, Chen JL. PERIRHINAL CORTEX LEARNS A PREDICTIVE MAP (INTERNAL MODEL) OF THE TASK ENVIRONMENT. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.532214. [PMID: 36993645 PMCID: PMC10055158 DOI: 10.1101/2023.03.17.532214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chemogenetic inactivation demonstrated that Prh is involved in task learning. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that expand in a retrospective manner and generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.
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Affiliation(s)
- David G Lee
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
| | - Caroline A McLachlan
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Ramon Nogueira
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Osung Kwon
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Alanna E Carey
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Garrett House
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Gavin D Lagani
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Danielle LaMay
- Department of Biology, Boston University, Boston MA 02215, USA
| | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Neuroscience, Columbia University, New York NY 10027, USA
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston MA 02215, USA
- Center for Neurophotonics, Boston University, Boston MA 02215, USA
- Department of Biology, Boston University, Boston MA 02215, USA
- Center for Systems Neuroscience, Boston University, Boston MA 02215, USA
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7
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Rodgers CC. A detailed behavioral, videographic, and neural dataset on object recognition in mice. Sci Data 2022; 9:620. [PMID: 36229608 PMCID: PMC9561117 DOI: 10.1038/s41597-022-01728-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 09/12/2022] [Indexed: 11/09/2022] Open
Abstract
Mice adeptly use their whiskers to touch, recognize, and learn about objects in their environment. This behavior is enabled by computations performed by populations of neurons in the somatosensory cortex. To understand these computations, we trained mice to use their whiskers to recognize different shapes while we recorded activity in the barrel cortex, which processes whisker input. Here, we present a large dataset of high-speed video of the whiskers, along with rigorous tracking of the entire extent of multiple whiskers and every contact they made on the shape. We used spike sorting to identify individual neurons, which responded with precise timing to whisker contacts and motion. These data will be useful for understanding the behavioral strategies mice use to explore objects, as well as the neuronal dynamics that mediate those strategies. In addition, our carefully curated labeled data could be used to develop new computer vision algorithms for tracking body posture, or for extracting responses of individual neurons from large-scale neural recordings.
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Affiliation(s)
- Chris C Rodgers
- Department of Neurosurgery, Emory University, Atlanta, GA, 30322, USA.
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8
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Sych Y, Fomins A, Novelli L, Helmchen F. Dynamic reorganization of the cortico-basal ganglia-thalamo-cortical network during task learning. Cell Rep 2022; 40:111394. [PMID: 36130513 PMCID: PMC9513804 DOI: 10.1016/j.celrep.2022.111394] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 05/31/2022] [Accepted: 08/29/2022] [Indexed: 11/19/2022] Open
Abstract
Adaptive behavior is coordinated by neuronal networks that are distributed across multiple brain regions such as in the cortico-basal ganglia-thalamo-cortical (CBGTC) network. Here, we ask how cross-regional interactions within such mesoscale circuits reorganize when an animal learns a new task. We apply multi-fiber photometry to chronically record simultaneous activity in 12 or 48 brain regions of mice trained in a tactile discrimination task. With improving task performance, most regions shift their peak activity from the time of reward-related action to the reward-predicting stimulus. By estimating cross-regional interactions using transfer entropy, we reveal that functional networks encompassing basal ganglia, thalamus, neocortex, and hippocampus grow and stabilize upon learning, especially at stimulus presentation time. The internal globus pallidus, ventromedial thalamus, and several regions in the frontal cortex emerge as salient hub regions. Our results highlight the learning-related dynamic reorganization that brain networks undergo when task-appropriate mesoscale network dynamics are established for goal-oriented behavior. Multi-fiber photometry reveals brain network adaptations during learning Activity in most regions temporally shifts from reward to predictive stimulus Cross-regional interactions in the CBGTC network increase and stabilize with learning Internal pallidum, VM thalamus, and prefrontal cortex regions emerge as hubs
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Affiliation(s)
- Yaroslav Sych
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland.
| | - Aleksejs Fomins
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland; Neuroscience Center Zurich, 8057 Zurich, Switzerland
| | - Leonardo Novelli
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland
| | - Fritjof Helmchen
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland; Neuroscience Center Zurich, 8057 Zurich, Switzerland.
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9
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Rabinovich RJ, Kato DD, Bruno RM. Learning enhances encoding of time and temporal surprise in mouse primary sensory cortex. Nat Commun 2022; 13:5504. [PMID: 36127340 PMCID: PMC9489862 DOI: 10.1038/s41467-022-33141-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 09/02/2022] [Indexed: 11/09/2022] Open
Abstract
Primary sensory cortex has long been believed to play a straightforward role in the initial processing of sensory information. Yet, the superficial layers of cortex overall are sparsely active, even during sensory stimulation; additionally, cortical activity is influenced by other modalities, task context, reward, and behavioral state. Our study demonstrates that reinforcement learning dramatically alters representations among longitudinally imaged neurons in superficial layers of mouse primary somatosensory cortex. Learning an object detection task recruits previously unresponsive neurons, enlarging the neuronal population sensitive to touch and behavioral choice. Cortical responses decrease upon repeated stimulus presentation outside of the behavioral task. Moreover, training improves population encoding of the passage of time, and unexpected deviations in trial timing elicit even stronger responses than touches do. In conclusion, the superficial layers of sensory cortex exhibit a high degree of learning-dependent plasticity and are strongly modulated by non-sensory but behaviorally-relevant features, such as timing and surprise. Activity in the superficial layers of the sensory cortex is believed to be largely driven by incoming sensory stimuli. Here the authors demonstrate how learning changes neural responses to sensations according to both behavioral relevance and timing, suggesting a high degree of non-sensory modulation.
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Affiliation(s)
- Rebecca J Rabinovich
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA.,Kavli Institute for Brain Science, Columbia University, New York, NY, 10027, USA.,Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, 10027, USA
| | - Daniel D Kato
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA.,Kavli Institute for Brain Science, Columbia University, New York, NY, 10027, USA.,Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, 10027, USA
| | - Randy M Bruno
- Department of Neuroscience, Columbia University, New York, NY, 10027, USA. .,Kavli Institute for Brain Science, Columbia University, New York, NY, 10027, USA. .,Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, 10027, USA. .,Department of Physiology, Anatomy & Genetics, University of Oxford, Oxford, UK.
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10
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Waiblinger C, McDonnell ME, Reedy AR, Borden PY, Stanley GB. Emerging experience-dependent dynamics in primary somatosensory cortex reflect behavioral adaptation. Nat Commun 2022; 13:534. [PMID: 35087056 PMCID: PMC8795122 DOI: 10.1038/s41467-022-28193-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 01/05/2022] [Indexed: 11/09/2022] Open
Abstract
Behavioral experience and flexibility are crucial for survival in a constantly changing environment. Despite evolutionary pressures to develop adaptive behavioral strategies in a dynamically changing sensory landscape, the underlying neural correlates have not been well explored. Here, we use genetically encoded voltage imaging to measure signals in primary somatosensory cortex (S1) during sensory learning and behavioral adaptation in the mouse. In response to changing stimulus statistics, mice adopt a strategy that modifies their detection behavior in a context dependent manner as to maintain reward expectation. Surprisingly, neuronal activity in S1 shifts from simply representing stimulus properties to transducing signals necessary for adaptive behavior in an experience dependent manner. Our results suggest that neuronal signals in S1 are part of an adaptive framework that facilitates flexible behavior as individuals gain experience, which could be part of a general scheme that dynamically distributes the neural correlates of behavior during learning. Waiblinger et al. investigate the role of primary sensory cortex in flexible behaviors. They show that neuronal signals in S1 are part of an adaptive and dynamic framework that facilitates flexible behavior as an individual gains experience, indicating a role for S1 in long-term adaptive strategies.
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Affiliation(s)
- Christian Waiblinger
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Megan E McDonnell
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - April R Reedy
- Integrated Cellular Imaging Core, Emory University School of Medicine, Emory University, Atlanta, GA, USA
| | - Peter Y Borden
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
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11
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Varani S, Vecchia D, Zucca S, Forli A, Fellin T. Stimulus Feature-Specific Control of Layer 2/3 Subthreshold Whisker Responses by Layer 4 in the Mouse Primary Somatosensory Cortex. Cereb Cortex 2021; 32:1419-1436. [PMID: 34448808 PMCID: PMC8971086 DOI: 10.1093/cercor/bhab297] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 07/29/2021] [Accepted: 07/29/2021] [Indexed: 02/01/2023] Open
Abstract
In the barrel field of the rodent primary somatosensory cortex (S1bf), excitatory cells in layer 2/3 (L2/3) display sparse firing but reliable subthreshold response during whisker stimulation. Subthreshold responses encode specific features of the sensory stimulus, for example, the direction of whisker deflection. According to the canonical model for the flow of sensory information across cortical layers, activity in L2/3 is driven by layer 4 (L4). However, L2/3 cells receive excitatory inputs from other regions, raising the possibility that L4 partially drives L2/3 during whisker stimulation. To test this hypothesis, we combined patch-clamp recordings from L2/3 pyramidal neurons in S1bf with selective optogenetic inhibition of L4 during passive whisker stimulation in both anesthetized and awake head-restrained mice. We found that L4 optogenetic inhibition did not abolish the subthreshold whisker-evoked response nor it affected spontaneous membrane potential fluctuations of L2/3 neurons. However, L4 optogenetic inhibition decreased L2/3 subthreshold responses to whisker deflections in the preferred direction, and it increased L2/3 responses to stimuli in the nonpreferred direction, leading to a change in the direction tuning. Our results contribute to reveal the circuit mechanisms underlying the processing of sensory information in the rodent S1bf.
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Affiliation(s)
- Stefano Varani
- Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Dania Vecchia
- Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Stefano Zucca
- Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Angelo Forli
- Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Tommaso Fellin
- Optical Approaches to Brain Function Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy
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12
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Pardasani M, Marathe SD, Purnapatre MM, Dalvi U, Abraham NM. Multimodal learning of pheromone locations. FASEB J 2021; 35:e21836. [PMID: 34407246 PMCID: PMC7611819 DOI: 10.1096/fj.202100167r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 06/28/2021] [Accepted: 07/20/2021] [Indexed: 11/11/2022]
Abstract
Memorizing pheromonal locations is critical for many mammalian species as it involves finding mates and avoiding competitors. In rodents, pheromonal information is perceived by the main and accessory olfactory systems. However, the role of somatosensation in context-dependent learning and memorizing of pheromone locations remains unexplored. We addressed this problem by training female mice on a multimodal task to locate pheromones by sampling volatiles emanating from male urine through the orifices of varying dimensions or shapes that are sensed by their vibrissae. In this novel pheromone location assay, female mice’ preference toward male urine scent decayed over time when they were permitted to explore pheromones vs neutral stimuli, water. On training them for the associations involving olfactory and whisker systems, it was established that they were able to memorize the location of opposite sex pheromones, when tested 15 days later. This memory was not formed either when the somatosensory inputs through whisker pad were blocked or when the pheromonal cues were replaced with that of same sex. The association between olfactory and somatosensory systems was further confirmed by the enhanced expression of the activity-regulated cytoskeleton protein. Furthermore, the activation of main olfactory bulb circuitry by pheromone volatiles did not cause any modulation in learning and memorizing non-pheromonal volatiles. Our study thus provides the evidence for associations formed between different sensory modalities facilitating the long-term memory formation relevant to social and reproductive behaviors.
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Affiliation(s)
- Meenakshi Pardasani
- Laboratory of Neural Circuits and Behaviour (LNCB), Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, India
| | - Shruti D Marathe
- Laboratory of Neural Circuits and Behaviour (LNCB), Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, India
| | - Maitreyee Mandar Purnapatre
- Laboratory of Neural Circuits and Behaviour (LNCB), Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, India.,Institute of Bioinformatics & Biotechnology, Savitribai Phule Pune University, Pune, India
| | - Urvashi Dalvi
- Laboratory of Neural Circuits and Behaviour (LNCB), Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, India.,Institute of Bioinformatics & Biotechnology, Savitribai Phule Pune University, Pune, India
| | - Nixon M Abraham
- Laboratory of Neural Circuits and Behaviour (LNCB), Department of Biology, Indian Institute of Science Education and Research (IISER), Pune, India
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13
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Rodgers CC, Nogueira R, Pil BC, Greeman EA, Park JM, Hong YK, Fusi S, Bruno RM. Sensorimotor strategies and neuronal representations for shape discrimination. Neuron 2021; 109:2308-2325.e10. [PMID: 34133944 PMCID: PMC8298290 DOI: 10.1016/j.neuron.2021.05.019] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 01/28/2021] [Accepted: 05/14/2021] [Indexed: 10/21/2022]
Abstract
Humans and other animals can identify objects by active touch, requiring the coordination of exploratory motion and tactile sensation. Both the motor strategies and neural representations employed could depend on the subject's goals. We developed a shape discrimination task that challenged head-fixed mice to discriminate concave from convex shapes. Behavioral decoding revealed that mice did this by comparing contacts across whiskers. In contrast, a separate group of mice performing a shape detection task simply summed up contacts over whiskers. We recorded populations of neurons in the barrel cortex, which processes whisker input, and found that individual neurons across the cortical layers encoded touch, whisker motion, and task-related signals. Sensory representations were task-specific: during shape discrimination, but not detection, neurons responded most to behaviorally relevant whiskers, overriding somatotopy. Thus, sensory cortex employs task-specific representations compatible with behaviorally relevant computations.
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Affiliation(s)
- Chris C Rodgers
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA.
| | - Ramon Nogueira
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - B Christina Pil
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Esther A Greeman
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Jung M Park
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Y Kate Hong
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Stefano Fusi
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - Randy M Bruno
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA.
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14
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Brown J, Oldenburg IA, Telian GI, Griffin S, Voges M, Jain V, Adesnik H. Spatial integration during active tactile sensation drives orientation perception. Neuron 2021; 109:1707-1720.e7. [PMID: 33826906 PMCID: PMC8944414 DOI: 10.1016/j.neuron.2021.03.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 07/24/2020] [Accepted: 03/11/2021] [Indexed: 01/07/2023]
Abstract
Active haptic sensation is critical for object identification, but its neural circuit basis is poorly understood. We combined optogenetics, two-photon imaging, and high-speed behavioral tracking in mice solving a whisker-based object orientation discrimination task. We found that orientation discrimination required animals to summate input from multiple whiskers specifically along the whisker arc. Animals discriminated the orientation of the stimulus per se as their performance was invariant to the location of the presented stimulus. Populations of barrel cortex neurons summated across whiskers to encode each orientation. Finally, acute optogenetic inactivation of the barrel cortex and cell-type-specific optogenetic suppression of layer 4 excitatory neurons degraded performance, implying that infragranular layers alone are not sufficient to solve the task. These data suggest that spatial summation over an active haptic array generates representations of an object's orientation, which may facilitate encoding of complex three-dimensional objects during active exploration.
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Affiliation(s)
- Jennifer Brown
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Ian Antón Oldenburg
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Gregory I Telian
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Sandon Griffin
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Mieke Voges
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Vedant Jain
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, 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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