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Badulescu S, Tabassum A, Le GH, Wong S, Phan L, Gill H, Llach CD, McIntyre RS, Rosenblat J, Mansur R. Glucagon-like peptide 1 agonist and effects on reward behaviour: A systematic review. Physiol Behav 2024; 283:114622. [PMID: 38945189 DOI: 10.1016/j.physbeh.2024.114622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 06/17/2024] [Accepted: 06/25/2024] [Indexed: 07/02/2024]
Abstract
INTRODUCTION The roles of metabolic signals, including Glucagon-like peptide 1 (GLP-1), have been implicated in multiple domains outside metabolic regulation. There is a growing interest in repurposing Glucagon-like peptide 1 receptor agonists (GLP-1RAs) as therapeutics for motivation and reward-related behavioural disturbances. Herein, we aim to systematically review the extant evidence on the potential effects of GLP-1RAs on the reward system. METHODS The study followed PRISMA guidelines using databases such as OVID, PubMed, Scopus, and Google Scholar. The search focused on "Reward Behavior" and "Glucagon Like Peptide 1 Receptor Agonists" and was restricted to human studies. Quality assessment achieved by the NIH's Quality Assessment of Controlled Intervention Studies RESULTS: GLP-1RAs consistently reduced energy intake and influenced reward-related behaviour. These agents have been associated with decreased neurocortical activation in response to higher rewards and food cues, particularly high-calorie foods, and lowered caloric intake and hunger levels. DISCUSSION GLP-1RAs show promise in addressing reward dysfunction linked to food stimuli, obesity, and T2DM. They normalize insulin resistance, and might also modulate dopaminergic signalling and reduce anhedonia. Their effects on glycemic variability and cravings suggest potential applications in addiction disorders.
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Affiliation(s)
- Sebastian Badulescu
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
| | - Aniqa Tabassum
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Gia Han Le
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Sabrina Wong
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada
| | - Lee Phan
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Hartej Gill
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Cristian-Daniel Llach
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Roger S McIntyre
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada
| | - Joshua Rosenblat
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada
| | - Rodrigo Mansur
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
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Kato DD, Bruno RM. Stability of cross-sensory input to primary somatosensory cortex across experience. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.07.607026. [PMID: 39149350 PMCID: PMC11326227 DOI: 10.1101/2024.08.07.607026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Merging information from across sensory modalities is key to forming robust, disambiguated percepts of the world, yet how the brain achieves this feat remains unclear. Recent observations of cross-modal influences in primary sensory cortical areas have suggested that multisensory integration may occur in the earliest stages of cortical processing, but the role of these responses is still poorly understood. We address these questions by testing several hypotheses about the possible functions served by auditory influences on the barrel field of mouse primary somatosensory cortex (S1) using in vivo 2-photon calcium imaging. We observed sound-evoked spiking activity in a small fraction of cells overall, and moreover that this sparse activity was insufficient to encode auditory stimulus identity; few cells responded preferentially to one sound or another, and a linear classifier trained to decode auditory stimuli from population activity performed barely above chance. Moreover S1 did not encode information about specific audio-tactile feature conjunctions that we tested. Our ability to decode auditory audio-tactile stimuli from neural activity remained unchanged after both passive experience and reinforcement. Collectively, these results suggest that while a primary sensory cortex is highly plastic with regard to its own modality, the influence of other modalities are remarkably stable and play a largely stimulus-non-specific role.
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Affiliation(s)
- Daniel D Kato
- Department of Neuroscience, Columbia University, New York, NY 10027, USA
| | - Randy M Bruno
- Department of Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Physiology, Anatomy, & Genetics, University of Oxford, Oxford OX1 3PT, United Kingdom
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3
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Yang R, Zhao P, Wang L, Feng C, Peng C, Wang Z, Zhang Y, Shen M, Shi K, Weng S, Dong C, Zeng F, Zhang T, Chen X, Wang S, Wang Y, Luo Y, Chen Q, Chen Y, Jiang C, Jia S, Yu Z, Liu J, Wang F, Jiang S, Xu W, Li L, Wang G, Mo X, Zheng G, Chen A, Zhou X, Jiang C, Yuan Y, Yan B, Zhang J. Assessment of visual function in blind mice and monkeys with subretinally implanted nanowire arrays as artificial photoreceptors. Nat Biomed Eng 2024; 8:1018-1039. [PMID: 37996614 DOI: 10.1038/s41551-023-01137-8] [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: 01/15/2022] [Accepted: 10/17/2023] [Indexed: 11/25/2023]
Abstract
Retinal prostheses could restore image-forming vision in conditions of photoreceptor degeneration. However, contrast sensitivity and visual acuity are often insufficient. Here we report the performance, in mice and monkeys with induced photoreceptor degeneration, of subretinally implanted gold-nanoparticle-coated titania nanowire arrays providing a spatial resolution of 77.5 μm and a temporal resolution of 3.92 Hz in ex vivo retinas (as determined by patch-clamp recording of retinal ganglion cells). In blind mice, the arrays allowed for the detection of drifting gratings and flashing objects at light-intensity thresholds of 15.70-18.09 μW mm-2, and offered visual acuities of 0.3-0.4 cycles per degree, as determined by recordings of visually evoked potentials and optomotor-response tests. In monkeys, the arrays were stable for 54 weeks, allowed for the detection of a 10-μW mm-2 beam of light (0.5° in beam angle) in visually guided saccade experiments, and induced plastic changes in the primary visual cortex, as indicated by long-term in vivo calcium imaging. Nanomaterials as artificial photoreceptors may ameliorate visual deficits in patients with photoreceptor degeneration.
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Affiliation(s)
- Ruyi Yang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Peng Zhao
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Liyang Wang
- Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai, P. R. China
| | - Chenli Feng
- Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai, P. R. China
| | - Chen Peng
- Laboratory of Advanced Materials, Department of Chemistry, Fudan University, Shanghai, P. R. China
| | - Zhexuan Wang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Yingying Zhang
- Key Laboratory of Brain Functional Genomics (Ministry of Education), East China Normal University, Shanghai, P. R. China
| | - Minqian Shen
- Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai, P. R. China
| | - Kaiwen Shi
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Shijun Weng
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Chunqiong Dong
- Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai, P. R. China
| | - Fu Zeng
- Key Laboratory of Brain Functional Genomics (Ministry of Education), East China Normal University, Shanghai, P. R. China
| | - Tianyun Zhang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Xingdong Chen
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Shuiyuan Wang
- Shanghai Key Lab for Future Computing Hardware and System, School of Microelectronics, Fudan University, Shanghai, P. R. China
| | - Yiheng Wang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Yuanyuan Luo
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Qingyuan Chen
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Yuqing Chen
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Chengyong Jiang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Shanshan Jia
- School of Computer Science, Institute for Artificial Intelligence, Peking University, Beijing, P.R. China
| | - Zhaofei Yu
- School of Computer Science, Institute for Artificial Intelligence, Peking University, Beijing, P.R. China
| | - Jian Liu
- School of Computer Science, University of Birmingham, Birmingham, UK
| | - Fei Wang
- Department of Hand Surgery, the National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, P. R. China
| | - Su Jiang
- Department of Hand Surgery, the National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, P. R. China
| | - Wendong Xu
- Department of Hand Surgery, the National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, P. R. China
- Department of Hand and Upper Extremity Surgery, Jing'an District Central Hospital, Fudan University, Shanghai, P.R. China
| | - Liang Li
- Center of Brain Sciences, Beijing Institute of Basic Medical Sciences, Beijing, P. R. China
| | - Gang Wang
- Center of Brain Sciences, Beijing Institute of Basic Medical Sciences, Beijing, P. R. China
| | - Xiaofen Mo
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Gengfeng Zheng
- Laboratory of Advanced Materials, Department of Chemistry, Fudan University, Shanghai, P. R. China
| | - Aihua Chen
- Key Laboratory of Brain Functional Genomics (Ministry of Education), East China Normal University, Shanghai, P. R. China
| | - Xingtao Zhou
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China
| | - Chunhui Jiang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China.
| | - Yuanzhi Yuan
- Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai, P. R. China.
- Zhongshan Hospital (Xiamen), Fudan University, Xiamen, P.R. China.
| | - Biao Yan
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China.
| | - Jiayi Zhang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, P. R. China.
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4
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Xiao J, Adkinson JA, Myers J, Allawala AB, Mathura RK, Pirtle V, Najera R, Provenza NR, Bartoli E, Watrous AJ, Oswalt D, Gadot R, Anand A, Shofty B, Mathew SJ, Goodman WK, Pouratian N, Pitkow X, Bijanki KR, Hayden B, Sheth SA. Beta activity in human anterior cingulate cortex mediates reward biases. Nat Commun 2024; 15:5528. [PMID: 39009561 PMCID: PMC11250824 DOI: 10.1038/s41467-024-49600-7] [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: 09/15/2023] [Accepted: 06/07/2024] [Indexed: 07/17/2024] Open
Abstract
The rewards that we get from our choices and actions can have a major influence on our future behavior. Understanding how reward biasing of behavior is implemented in the brain is important for many reasons, including the fact that diminution in reward biasing is a hallmark of clinical depression. We hypothesized that reward biasing is mediated by the anterior cingulate cortex (ACC), a cortical hub region associated with the integration of reward and executive control and with the etiology of depression. To test this hypothesis, we recorded neural activity during a biased judgment task in patients undergoing intracranial monitoring for either epilepsy or major depressive disorder. We found that beta (12-30 Hz) oscillations in the ACC predicted both associated reward and the size of the choice bias, and also tracked reward receipt, thereby predicting bias on future trials. We found reduced magnitude of bias in depressed patients, in whom the beta-specific effects were correspondingly reduced. Our findings suggest that ACC beta oscillations may orchestrate the learning of reward information to guide adaptive choice, and, more broadly, suggest a potential biomarker for anhedonia and point to future development of interventions to enhance reward impact for therapeutic benefit.
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Affiliation(s)
- Jiayang Xiao
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Joshua A Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | | | - Raissa K Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Victoria Pirtle
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ricardo Najera
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Andrew J Watrous
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Denise Oswalt
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ron Gadot
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Adrish Anand
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ben Shofty
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, 84112, USA
| | - Sanjay J Mathew
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Wayne K Goodman
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Xaq Pitkow
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Benjamin Hayden
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA.
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5
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Padamsey Z, Katsanevaki D, Maeso P, Rizzi M, Osterweil EE, Rochefort NL. Sex-specific resilience of neocortex to food restriction. eLife 2024; 12:RP93052. [PMID: 38976495 PMCID: PMC11230624 DOI: 10.7554/elife.93052] [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] [Indexed: 07/10/2024] Open
Abstract
Mammals have evolved sex-specific adaptations to reduce energy usage in times of food scarcity. These adaptations are well described for peripheral tissue, though much less is known about how the energy-expensive brain adapts to food restriction, and how such adaptations differ across the sexes. Here, we examined how food restriction impacts energy usage and function in the primary visual cortex (V1) of adult male and female mice. Molecular analysis and RNA sequencing in V1 revealed that in males, but not in females, food restriction significantly modulated canonical, energy-regulating pathways, including pathways associated waith AMP-activated protein kinase, peroxisome proliferator-activated receptor alpha, mammalian target of rapamycin, and oxidative phosphorylation. Moreover, we found that in contrast to males, food restriction in females did not significantly affect V1 ATP usage or visual coding precision (assessed by orientation selectivity). Decreased serum leptin is known to be necessary for triggering energy-saving changes in V1 during food restriction. Consistent with this, we found significantly decreased serum leptin in food-restricted males but no significant change in food-restricted females. Collectively, our findings demonstrate that cortical function and energy usage in female mice are more resilient to food restriction than in males. The neocortex, therefore, contributes to sex-specific, energy-saving adaptations in response to food restriction.
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Affiliation(s)
- Zahid Padamsey
- Wellcome-MRC Institute of Metabolic Science, University of CambridgeCambridgeUnited Kingdom
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of EdinburghEdinburghUnited Kingdom
| | - Danai Katsanevaki
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of EdinburghEdinburghUnited Kingdom
- Simons Initiative for the Developing Brain, University of EdinburghEdinburghUnited Kingdom
| | - Patricia Maeso
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of EdinburghEdinburghUnited Kingdom
| | - Manuela Rizzi
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of EdinburghEdinburghUnited Kingdom
| | - Emily E Osterweil
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of EdinburghEdinburghUnited Kingdom
- Simons Initiative for the Developing Brain, University of EdinburghEdinburghUnited Kingdom
- Rosamund Stone Zander Translational Neuroscience Center, F.M. Kirby Center, Boston Children’s Hospital, Harvard Medical SchoolBostonUnited States
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of EdinburghEdinburghUnited Kingdom
- Simons Initiative for the Developing Brain, University of EdinburghEdinburghUnited Kingdom
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6
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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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7
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Devoto F, Mariano M, Gornetti E, Paulesu E, Zapparoli L. Trait food craving predicts functional connectivity between dopaminergic midbrain and the fusiform food area during eating imagery. Front Psychiatry 2024; 15:1396376. [PMID: 38774434 PMCID: PMC11107427 DOI: 10.3389/fpsyt.2024.1396376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 04/18/2024] [Indexed: 05/24/2024] Open
Abstract
Neurofunctional coupling between the dopaminergic midbrain (i.e., ventral tegmental area, VTA) and higher-order visual regions may contribute to food craving, leading to the onset or maintenance of obesity. We recently showed that the VTA resting-state functional connectivity with the occipitotemporal cortex, at the level of the fusiform gyrus (FFG), was specifically associated with trait food craving and the implicit bias for food images, suggesting that VTA-FFG connectivity may reflect the association between the visual representations of food and its motivational properties. To further test this hypothesis, this time we studied task-based functional connectivity in twenty-eight healthy-weight participants while imagining eating their most liked high-calorie (HC) or least liked low-calorie food (LC) or drinking water (control condition). Trait food craving scores were used to predict changes in task-based functional connectivity of the VTA during imagery of HC compared to LC foods (relative to the control condition). Trait food craving was positively associated with the functional connectivity of the VTA with the left FFG: people with higher trait food craving scores show stronger VTA-FFG connectivity, specifically for the imagery of the liked HC foods. This association was not linked to the quality of imagery nor to state measures of craving, appetite, or thirst. These findings emphasize the contribution of the functional coupling between dopaminergic midbrain and higher-order visual regions to food craving, suggesting a neurofunctional mechanism by which the mental representations of the HC food we like can become much more salient if not irresistible.
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Affiliation(s)
- Francantonio Devoto
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - Marika Mariano
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - Edoardo Gornetti
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - Eraldo Paulesu
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
- fMRI Unit, IRCCS Orthopedic Institute Galeazzi, Milan, Italy
| | - Laura Zapparoli
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
- fMRI Unit, IRCCS Orthopedic Institute Galeazzi, Milan, Italy
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8
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Baruchin LJ, Alleman M, Schröder S. Reward Modulates Visual Responses in the Superficial Superior Colliculus of Mice. J Neurosci 2023; 43:8663-8680. [PMID: 37879894 PMCID: PMC7615379 DOI: 10.1523/jneurosci.0089-23.2023] [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: 01/09/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 10/27/2023] Open
Abstract
The processing of sensory input is constantly adapting to behavioral demands and internal states. The drive to obtain reward, e.g., searching for water when thirsty, is a strong behavioral demand and associating the reward with its source, a certain environment or action, is paramount for survival. Here, we show that water reward increases subsequent visual activity in the superficial layers of the superior colliculus (SC), which receive direct input from the retina and belong to the earliest stages of visual processing. We trained mice of either sex to perform a visual decision task and recorded the activity of neurons in the SC using two-photon calcium imaging and high-density electrophysiological recordings. Responses to visual stimuli in around 20% of visually responsive neurons in the superficial SC were affected by reward delivered in the previous trial. Reward mostly increased visual responses independent from modulations due to pupil size changes. The modulation of visual responses by reward could not be explained by movements like licking. It was specific to responses to the following visual stimulus, independent of slow fluctuations in neural activity and independent of how often the stimulus was previously rewarded. Electrophysiological recordings confirmed these results and revealed that reward affected the early phase of the visual response around 80 ms after stimulus onset. Modulation of visual responses by reward, but not pupil size, significantly improved the performance of a population decoder to detect visual stimuli, indicating the relevance of reward modulation for the visual performance of the animal.SIGNIFICANCE STATEMENT To learn which actions lead to food, water, or safety, it is necessary to integrate the receiving of reward with sensory stimuli related to the reward. Cortical stages of sensory processing have been shown to represent stimulus-reward associations. Here, we show, however, that reward influences neurons at a much earlier stage of sensory processing, the superior colliculus (SC), receiving direct input from the retina. Visual responses were increased shortly after the animal received the water reward, which led to an improved stimulus signal in the population of these visual neurons. Reward modulation of early visual responses may thus improve perception of visual environments predictive of reward.
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Affiliation(s)
- Liad J Baruchin
- School of Life Sciences, University of Sussex, Brighton BN1 9QG, United Kingdom
| | - Matteo Alleman
- Institute of Ophthalmology, University College London, London WC1E 6BT, United Kingdom
| | - Sylvia Schröder
- School of Life Sciences, University of Sussex, Brighton BN1 9QG, United Kingdom
- Institute of Ophthalmology, University College London, London WC1E 6BT, United Kingdom
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9
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Gurnani H, Cayco Gajic NA. Signatures of task learning in neural representations. Curr Opin Neurobiol 2023; 83:102759. [PMID: 37708653 DOI: 10.1016/j.conb.2023.102759] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 06/28/2023] [Accepted: 07/20/2023] [Indexed: 09/16/2023]
Abstract
While neural plasticity has long been studied as the basis of learning, the growth of large-scale neural recording techniques provides a unique opportunity to study how learning-induced activity changes are coordinated across neurons within the same circuit. These distributed changes can be understood through an evolution of the geometry of neural manifolds and latent dynamics underlying new computations. In parallel, studies of multi-task and continual learning in artificial neural networks hint at a tradeoff between non-interference and compositionality as guiding principles to understand how neural circuits flexibly support multiple behaviors. In this review, we highlight recent findings from both biological and artificial circuits that together form a new framework for understanding task learning at the population level.
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Affiliation(s)
- Harsha Gurnani
- Department of Biology, University of Washington, Seattle, WA, USA. https://twitter.com/HarshaGurnani
| | - N Alex Cayco Gajic
- Laboratoire de Neuroscience Cognitives, Ecole Normale Supérieure, Université PSL, Paris, France.
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10
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Niraula S, Hauser WL, Rouse AG, Subramanian J. Repeated passive visual experience modulates spontaneous and non-familiar stimuli-evoked neural activity. Sci Rep 2023; 13:20907. [PMID: 38017135 PMCID: PMC10684504 DOI: 10.1038/s41598-023-47957-1] [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: 02/20/2023] [Accepted: 11/20/2023] [Indexed: 11/30/2023] Open
Abstract
Familiarity creates subjective memory of repeated innocuous experiences, reduces neural and behavioral responsiveness to those experiences, and enhances novelty detection. The neural correlates of the internal model of familiarity and the cellular mechanisms of enhanced novelty detection following multi-day repeated passive experience remain elusive. Using the mouse visual cortex as a model system, we test how the repeated passive experience of a 45° orientation-grating stimulus for multiple days alters spontaneous and non-familiar stimuli evoked neural activity in neurons tuned to familiar or non-familiar stimuli. We found that familiarity elicits stimulus competition such that stimulus selectivity reduces in neurons tuned to the familiar 45° stimulus; it increases in those tuned to the 90° stimulus but does not affect neurons tuned to the orthogonal 135° stimulus. Furthermore, neurons tuned to orientations 45° apart from the familiar stimulus dominate local functional connectivity. Interestingly, responsiveness to natural images, which consists of familiar and non-familiar orientations, increases subtly in neurons that exhibit stimulus competition. We also show the similarity between familiar grating stimulus-evoked and spontaneous activity increases, indicative of an internal model of altered experience.
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Affiliation(s)
- Suraj Niraula
- Department of Pharmacology and Toxicology, School of Pharmacy, University of Kansas, Lawrence, KS, 66045, USA
| | - William L Hauser
- Department of Pharmacology and Toxicology, School of Pharmacy, University of Kansas, Lawrence, KS, 66045, USA
| | - Adam G Rouse
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS, 66103, USA
| | - Jaichandar Subramanian
- Department of Pharmacology and Toxicology, School of Pharmacy, University of Kansas, Lawrence, KS, 66045, USA.
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11
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Rowland JM, van der Plas TL, Loidolt M, Lees RM, Keeling J, Dehning J, Akam T, Priesemann V, Packer AM. Propagation of activity through the cortical hierarchy and perception are determined by neural variability. Nat Neurosci 2023; 26:1584-1594. [PMID: 37640911 PMCID: PMC10471496 DOI: 10.1038/s41593-023-01413-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/18/2023] [Indexed: 08/31/2023]
Abstract
Brains are composed of anatomically and functionally distinct regions performing specialized tasks, but regions do not operate in isolation. Orchestration of complex behaviors requires communication between brain regions, but how neural dynamics are organized to facilitate reliable transmission is not well understood. Here we studied this process directly by generating neural activity that propagates between brain regions and drives behavior, assessing how neural populations in sensory cortex cooperate to transmit information. We achieved this by imaging two densely interconnected regions-the primary and secondary somatosensory cortex (S1 and S2)-in mice while performing two-photon photostimulation of S1 neurons and assigning behavioral salience to the photostimulation. We found that the probability of perception is determined not only by the strength of the photostimulation but also by the variability of S1 neural activity. Therefore, maximizing the signal-to-noise ratio of the stimulus representation in cortex relative to the noise or variability is critical to facilitate activity propagation and perception.
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Affiliation(s)
- James M Rowland
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Thijs L van der Plas
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Matthias Loidolt
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Laboratory for Molecular Cell Biology, University College London, London, UK
| | - Robert M Lees
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
- Science and Technology Facilities Council, Octopus Imaging Facility, Research Complex at Harwell, Harwell Campus, Oxfordshire, UK
| | - Joshua Keeling
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Jonas Dehning
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Thomas Akam
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Viola Priesemann
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Adam M Packer
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK.
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12
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Niraula S, Hauser WL, Rouse AG, Subramanian J. Repeated passive visual experience modulates spontaneous and non-familiar stimulievoked neural activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.21.529278. [PMID: 36865208 PMCID: PMC9980096 DOI: 10.1101/2023.02.21.529278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Familiarity creates subjective memory of repeated innocuous experiences, reduces neural and behavioral responsiveness to those experiences, and enhances novelty detection. The neural correlates of the internal model of familiarity and the cellular mechanisms of enhanced novelty detection following multi-day repeated passive experience remain elusive. Using the mouse visual cortex as a model system, we test how the repeated passive experience of a 45° orientation-grating stimulus for multiple days alters spontaneous and non-familiar stimuli evoked neural activity in neurons tuned to familiar or non-familiar stimuli. We found that familiarity elicits stimulus competition such that stimulus selectivity reduces in neurons tuned to the familiar 45° stimulus; it increases in those tuned to the 90° stimulus but does not affect neurons tuned to the orthogonal 135° stimulus. Furthermore, neurons tuned to orientations 45° apart from the familiar stimulus dominate local functional connectivity. Interestingly, responsiveness to natural images, which consists of familiar and non-familiar orientations, increases subtly in neurons that exhibit stimulus competition. We also show the similarity between familiar grating stimulus-evoked and spontaneous activity increases, indicative of an internal model of altered experience.
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Affiliation(s)
- Suraj Niraula
- Department of Pharmacology and Toxicology, School of Pharmacy, University of Kansas, Lawrence, KS 66045, USA
| | - William L. Hauser
- Department of Pharmacology and Toxicology, School of Pharmacy, University of Kansas, Lawrence, KS 66045, USA
| | - Adam G. Rouse
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66103, USA
| | - Jaichandar Subramanian
- Department of Pharmacology and Toxicology, School of Pharmacy, University of Kansas, Lawrence, KS 66045, USA
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13
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Mitskopoulos L, Onken A. Discovering Low-Dimensional Descriptions of Multineuronal Dependencies. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1026. [PMID: 37509973 PMCID: PMC10378554 DOI: 10.3390/e25071026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/12/2023] [Accepted: 07/04/2023] [Indexed: 07/30/2023]
Abstract
Coordinated activity in neural populations is crucial for information processing. Shedding light on the multivariate dependencies that shape multineuronal responses is important to understand neural codes. However, existing approaches based on pairwise linear correlations are inadequate at capturing complicated interaction patterns and miss features that shape aspects of the population function. Copula-based approaches address these shortcomings by extracting the dependence structures in the joint probability distribution of population responses. In this study, we aimed to dissect neural dependencies with a C-Vine copula approach coupled with normalizing flows for estimating copula densities. While this approach allows for more flexibility compared to fitting parametric copulas, drawing insights on the significance of these dependencies from large sets of copula densities is challenging. To alleviate this challenge, we used a weighted non-negative matrix factorization procedure to leverage shared latent features in neural population dependencies. We validated the method on simulated data and applied it on copulas we extracted from recordings of neurons in the mouse visual cortex as well as in the macaque motor cortex. Our findings reveal that neural dependencies occupy low-dimensional subspaces, but distinct modules are synergistically combined to give rise to diverse interaction patterns that may serve the population function.
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Affiliation(s)
| | - Arno Onken
- School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK
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14
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Si YG, Su WX, Chen XD, Li ZY, Yan B, Zhang JY. Emerging V1 neuronal ensembles with enhanced connectivity after associative learning. Front Neurosci 2023; 17:1176253. [PMID: 37456996 PMCID: PMC10346858 DOI: 10.3389/fnins.2023.1176253] [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: 02/28/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
Introduction The visual stimulus-specific responses in the primary visual cortex (V1) undergo plastic changes after associative learning. During the learning process, neuronal ensembles, defined as groups of coactive neurons, are well known to be related to learning and memory. However, it remains unclear what effect learning has on ensembles, and which neuronal subgroups within those ensembles play a key role in associative learning. Methods We used two-photon calcium imaging in mice to record the activity of V1 neurons before and after fear conditioning associated with a visual cue (blue light). We first defined neuronal ensembles by thresholding their functional connectivity in response to blue (conditioned) or green (control) light. We defined neurons that existed both before and after conditioning as stable neurons. Neurons which were recruited after conditioning were defined as new neurons. The graph theory-based analysis was performed to quantify the changes in connectivity within ensembles after conditioning. Results A significant enhancement in the connectivity strength (the average correlation with other neurons) was observed in the blue ensembles after conditioning. We found that stable neurons within the blue ensembles showed a significantly smaller clustering coefficient (the value represented the degree of interconnectedness among a node's neighbors) after conditioning than they were before conditioning. Additionally, new neurons within the blue ensembles had a larger clustering coefficient, similar relative degree (the value represented the number of functional connections between neurons) and connectivity strength compared to stable neurons in the same ensembles. Discussion Overall, our results demonstrated that the plastic changes caused by conditioning occurred in subgroups of neurons in the ensembles. Moreover, new neurons from conditioned ensembles may play a crucial role in memory formation, as they exhibited not only similar connection competence in relative degree and connectivity strength as stable neurons, but also showed a significantly larger clustering coefficient compared to the stable neurons within the same ensembles after conditioning.
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Affiliation(s)
- Yue-Guang Si
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Wen-Xin Su
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Eye & ENT Hospital, Fudan University, Shanghai, China
- Department of Psychology, University of Essex, Colchester, United Kingdom
| | - Xing-Dong Chen
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Ze-Yu Li
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Biao Yan
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Jia-Yi Zhang
- State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science, Institute for Medical and Engineering Innovation, Eye & ENT Hospital, Fudan University, Shanghai, China
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15
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Price BH, Jensen CM, Khoudary AA, Gavornik JP. Expectation violations produce error signals in mouse V1. Cereb Cortex 2023; 33:8803-8820. [PMID: 37183176 PMCID: PMC10321125 DOI: 10.1093/cercor/bhad163] [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: 03/07/2023] [Revised: 04/22/2023] [Accepted: 04/25/2023] [Indexed: 05/16/2023] Open
Abstract
Repeated exposure to visual sequences changes the form of evoked activity in the primary visual cortex (V1). Predictive coding theory provides a potential explanation for this, namely that plasticity shapes cortical circuits to encode spatiotemporal predictions and that subsequent responses are modulated by the degree to which actual inputs match these expectations. Here we use a recently developed statistical modeling technique called Model-Based Targeted Dimensionality Reduction (MbTDR) to study visually evoked dynamics in mouse V1 in the context of an experimental paradigm called "sequence learning." We report that evoked spiking activity changed significantly with training, in a manner generally consistent with the predictive coding framework. Neural responses to expected stimuli were suppressed in a late window (100-150 ms) after stimulus onset following training, whereas responses to novel stimuli were not. Substituting a novel stimulus for a familiar one led to increases in firing that persisted for at least 300 ms. Omitting predictable stimuli in trained animals also led to increased firing at the expected time of stimulus onset. Finally, we show that spiking data can be used to accurately decode time within the sequence. Our findings are consistent with the idea that plasticity in early visual circuits is involved in coding spatiotemporal information.
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Affiliation(s)
- Byron H Price
- Center for Systems Neuroscience, Department of Biology, Boston University, Boston, MA 02215, USA
- Graduate Program in Neuroscience, Boston University, Boston, MA 02215, USA
| | - Cambria M Jensen
- Center for Systems Neuroscience, Department of Biology, Boston University, Boston, MA 02215, USA
| | - Anthony A Khoudary
- Center for Systems Neuroscience, Department of Biology, Boston University, Boston, MA 02215, USA
| | - Jeffrey P Gavornik
- Center for Systems Neuroscience, Department of Biology, Boston University, Boston, MA 02215, USA
- Graduate Program in Neuroscience, Boston University, Boston, MA 02215, USA
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16
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Rozells J, Gavornik JP. Optogenetic manipulation of inhibitory interneurons can be used to validate a model of spatiotemporal sequence learning. Front Comput Neurosci 2023; 17:1198128. [PMID: 37362060 PMCID: PMC10288026 DOI: 10.3389/fncom.2023.1198128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/24/2023] [Indexed: 06/28/2023] Open
Abstract
The brain uses temporal information to link discrete events into memory structures supporting recognition, prediction, and a wide variety of complex behaviors. It is still an open question how experience-dependent synaptic plasticity creates memories including temporal and ordinal information. Various models have been proposed to explain how this could work, but these are often difficult to validate in a living brain. A recent model developed to explain sequence learning in the visual cortex encodes intervals in recurrent excitatory synapses and uses a learned offset between excitation and inhibition to generate precisely timed "messenger" cells that signal the end of an instance of time. This mechanism suggests that the recall of stored temporal intervals should be particularly sensitive to the activity of inhibitory interneurons that can be easily targeted in vivo with standard optogenetic tools. In this work we examined how simulated optogenetic manipulations of inhibitory cells modifies temporal learning and recall based on these mechanisms. We show that disinhibition and excess inhibition during learning or testing cause characteristic errors in recalled timing that could be used to validate the model in vivo using either physiological or behavioral measurements.
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Affiliation(s)
| | - Jeffrey P. Gavornik
- Center for Systems Neuroscience, Department of Biology, Boston University, Boston, MA, United States
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17
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Kay K, Bonnen K, Denison RN, Arcaro MJ, Barack DL. Tasks and their role in visual neuroscience. Neuron 2023; 111:1697-1713. [PMID: 37040765 DOI: 10.1016/j.neuron.2023.03.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 04/13/2023]
Abstract
Vision is widely used as a model system to gain insights into how sensory inputs are processed and interpreted by the brain. Historically, careful quantification and control of visual stimuli have served as the backbone of visual neuroscience. There has been less emphasis, however, on how an observer's task influences the processing of sensory inputs. Motivated by diverse observations of task-dependent activity in the visual system, we propose a framework for thinking about tasks, their role in sensory processing, and how we might formally incorporate tasks into our models of vision.
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Affiliation(s)
- Kendrick Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA.
| | - Kathryn Bonnen
- School of Optometry, Indiana University, Bloomington, IN 47405, USA
| | - Rachel N Denison
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Mike J Arcaro
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19146, USA
| | - David L Barack
- Departments of Neuroscience and Philosophy, University of Pennsylvania, Philadelphia, PA 19146, USA
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18
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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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19
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Henschke JU, Pakan JMP. Engaging distributed cortical and cerebellar networks through motor execution, observation, and imagery. Front Syst Neurosci 2023; 17:1165307. [PMID: 37114187 PMCID: PMC10126249 DOI: 10.3389/fnsys.2023.1165307] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 03/27/2023] [Indexed: 04/29/2023] Open
Abstract
When we interact with the environment around us, we are sometimes active participants, making directed physical motor movements and other times only mentally engaging with our environment, taking in sensory information and internally planning our next move without directed physical movement. Traditionally, cortical motor regions and key subcortical structures such as the cerebellum have been tightly linked to motor initiation, coordination, and directed motor behavior. However, recent neuroimaging studies have noted the activation of the cerebellum and wider cortical networks specifically during various forms of motor processing, including the observations of actions and mental rehearsal of movements through motor imagery. This phenomenon of cognitive engagement of traditional motor networks raises the question of how these brain regions are involved in the initiation of movement without physical motor output. Here, we will review evidence for distributed brain network activation during motor execution, observation, and imagery in human neuroimaging studies as well as the potential for cerebellar involvement specifically in motor-related cognition. Converging evidence suggests that a common global brain network is involved in both movement execution and motor observation or imagery, with specific task-dependent shifts in these global activation patterns. We will further discuss underlying cross-species anatomical support for these cognitive motor-related functions as well as the role of cerebrocerebellar communication during action observation and motor imagery.
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Affiliation(s)
- Julia U. Henschke
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Janelle M. P. Pakan
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Universitätsplatz, Magdeburg, Germany
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20
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De Martino B, Cortese A. Goals, usefulness and abstraction in value-based choice. Trends Cogn Sci 2023; 27:65-80. [PMID: 36446707 DOI: 10.1016/j.tics.2022.11.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 10/26/2022] [Accepted: 11/01/2022] [Indexed: 11/27/2022]
Abstract
Colombian drug lord Pablo Escobar, while on the run, purportedly burned two million dollars in banknotes to keep his daughter warm. A stark reminder that, in life, circumstances and goals can quickly change, forcing us to reassess and modify our values on-the-fly. Studies in decision-making and neuroeconomics have often implicitly equated value to reward, emphasising the hedonic and automatic aspect of the value computation, while overlooking its functional (concept-like) nature. Here we outline the computational and biological principles that enable the brain to compute the usefulness of an option or action by creating abstractions that flexibly adapt to changing goals. We present different algorithmic architectures, comparing ideas from artificial intelligence (AI) and cognitive neuroscience with psychological theories and, when possible, drawing parallels.
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Affiliation(s)
- Benedetto De Martino
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK; Computational Neuroscience Laboratories, ATR Institute International, 619-0288 Kyoto, Japan.
| | - Aurelio Cortese
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK; Computational Neuroscience Laboratories, ATR Institute International, 619-0288 Kyoto, Japan.
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21
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Matteucci G, Guyoton M, Mayrhofer JM, Auffret M, Foustoukos G, Petersen CCH, El-Boustani S. Cortical sensory processing across motivational states during goal-directed behavior. Neuron 2022; 110:4176-4193.e10. [PMID: 36240769 DOI: 10.1016/j.neuron.2022.09.032] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 07/25/2022] [Accepted: 09/24/2022] [Indexed: 11/06/2022]
Abstract
Behavioral states can influence performance of goal-directed sensorimotor tasks. Yet, it is unclear how altered neuronal sensory representations in these states relate to task performance and learning. We trained water-restricted mice in a two-whisker discrimination task to study cortical circuits underlying perceptual decision-making under different levels of thirst. We identified somatosensory cortices as well as the premotor cortex as part of the circuit necessary for task execution. Two-photon calcium imaging in these areas identified populations selective to sensory or motor events. Analysis of task performance during individual sessions revealed distinct behavioral states induced by decreasing levels of thirst-related motivation. Learning was better explained by improvements in motivational state control rather than sensorimotor association. Whisker sensory representations in the cortex were altered across behavioral states. In particular, whisker stimuli could be better decoded from neuronal activity during high task performance states, suggesting that state-dependent changes of sensory processing influence decision-making.
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Affiliation(s)
- Giulio Matteucci
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, 1206 Geneva, Switzerland
| | - Maëlle Guyoton
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, 1206 Geneva, Switzerland
| | - Johannes M Mayrhofer
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), EPFL-SV-BMI-LSENS Station 19, CH-1015 Lausanne, Switzerland
| | - Matthieu Auffret
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), EPFL-SV-BMI-LSENS Station 19, CH-1015 Lausanne, Switzerland
| | - Georgios Foustoukos
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), EPFL-SV-BMI-LSENS Station 19, CH-1015 Lausanne, Switzerland
| | - Carl C H Petersen
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), EPFL-SV-BMI-LSENS Station 19, CH-1015 Lausanne, Switzerland.
| | - Sami El-Boustani
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, 1206 Geneva, Switzerland; Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), EPFL-SV-BMI-LSENS Station 19, CH-1015 Lausanne, Switzerland.
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22
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Liu Q, Ely BA, Stern ER, Xu J, Kim JW, Pick DG, Alonso CM, Gabbay V. Neural function underlying reward expectancy and attainment in adolescents with diverse psychiatric symptoms. Neuroimage Clin 2022; 36:103258. [PMID: 36451362 PMCID: PMC9668660 DOI: 10.1016/j.nicl.2022.103258] [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: 08/05/2022] [Revised: 10/31/2022] [Accepted: 11/02/2022] [Indexed: 11/08/2022]
Abstract
Reward dysfunction has been hypothesized to play a key role in the development of psychiatric conditions during adolescence. To help capture the complexity of reward function in youth, we used the Reward Flanker fMRI Task, which enabled us to examine neural activity during expectancy and attainment of both certain and uncertain rewards. Participants were 84 psychotropic-medication-free adolescents, including 67 with diverse psychiatric conditions and 17 healthy controls. Functional MRI used high-resolution acquisition and high-fidelity processing techniques modeled after the Human Connectome Project. Analyses examined neural activation during reward expectancy and attainment, and their associations with clinical measures of depression, anxiety, and anhedonia severity, with results controlled for family-wise errors using non-parametric permutation tests. As anticipated, reward expectancy activated regions within the fronto-striatal reward network, thalamus, occipital lobe, superior parietal lobule, temporoparietal junction, and cerebellum. Unexpectedly, however, reward attainment was marked by widespread deactivation in many of these same regions, which we further explored using cosine similarity analysis. Across all subjects, striatum and thalamus activation during reward expectancy negatively correlated with anxiety severity, while activation in numerous cortical and subcortical regions during reward attainment positively correlated with both anxiety and depression severity. These findings highlight the complexity and dynamic nature of neural reward processing in youth.
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Affiliation(s)
- Qi Liu
- Department of Psychiatry & Behavioral Science, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Benjamin A Ely
- Department of Psychiatry & Behavioral Science, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Emily R Stern
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States; Department of Psychiatry, New York University School of Medicine, New York, NY, United States
| | - Junqian Xu
- Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Joo-Won Kim
- Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Danielle G Pick
- Department of Psychiatry & Behavioral Science, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Carmen M Alonso
- Department of Psychiatry & Behavioral Science, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Vilma Gabbay
- Department of Psychiatry & Behavioral Science, Albert Einstein College of Medicine, Bronx, NY, United States; Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States.
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23
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Wiesbrock C, Musall S, Kampa BM. A flexible Python-based touchscreen chamber for operant conditioning reveals improved visual perception of cardinal orientations in mice. Front Cell Neurosci 2022; 16:866109. [PMID: 36299493 PMCID: PMC9588922 DOI: 10.3389/fncel.2022.866109] [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: 01/30/2022] [Accepted: 09/09/2022] [Indexed: 11/17/2022] Open
Abstract
Natural scenes are composed of a wide range of edge angles and spatial frequencies, with a strong overrepresentation of vertical and horizontal edges. Correspondingly, many mammalian species are much better at discriminating these cardinal orientations compared to obliques. A potential reason for this increased performance could be an increased number of neurons in the visual cortex that are tuned to cardinal orientations, which is likely to be an adaptation to the natural scene statistics. Such biased angular tuning has recently been shown in the mouse primary visual cortex. However, it is still unknown if mice also show a perceptual dominance of cardinal orientations. Here, we describe the design of a novel custom-built touchscreen chamber that allows testing natural scene perception and orientation discrimination performance by applying different task designs. Using this chamber, we applied an iterative convergence towards orientation discrimination thresholds for cardinal or oblique orientations in different cohorts of mice. Surprisingly, the expert discrimination performance was similar for both groups but showed large inter-individual differences in performance and training time. To study the discrimination of cardinal and oblique stimuli in the same mice, we, therefore, applied, a different training regime where mice learned to discriminate cardinal and oblique gratings in parallel. Parallel training revealed a higher task performance for cardinal orientations in an early phase of the training. The performance for both orientations became similar after prolonged training, suggesting that learning permits equally high perceptual tuning towards oblique stimuli. In summary, our custom-built touchscreen chamber offers a flexible tool to test natural visual perception in rodents and revealed a training-induced increase in the perception of oblique gratings. The touchscreen chamber is entirely open-source, easy to build, and freely available to the scientific community to conduct visual or multimodal behavioral studies. It is also based on the FAIR principles for data management and sharing and could therefore serve as a catalyst for testing the perception of complex and natural visual stimuli across behavioral labs.
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Affiliation(s)
- Christopher Wiesbrock
- Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
- Research Training Group 2416 MultiSenses—MultiScales, RWTH Aachen University, Aachen, Germany
- *Correspondence: Christopher Wiesbrock Björn M. Kampa
| | - Simon Musall
- Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
- Bioelectronics, Institute of Biological Information Processing-3, Forschungszentrum Jülich, Jülich, Germany
| | - Björn M. Kampa
- Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
- Research Training Group 2416 MultiSenses—MultiScales, RWTH Aachen University, Aachen, Germany
- JARA BRAIN, Institute for Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany
- *Correspondence: Christopher Wiesbrock Björn M. Kampa
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24
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Mitskopoulos L, Amvrosiadis T, Onken A. Mixed vine copula flows for flexible modeling of neural dependencies. Front Neurosci 2022; 16:910122. [PMID: 36213754 PMCID: PMC9546167 DOI: 10.3389/fnins.2022.910122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 09/05/2022] [Indexed: 11/18/2022] Open
Abstract
Recordings of complex neural population responses provide a unique opportunity for advancing our understanding of neural information processing at multiple scales and improving performance of brain computer interfaces. However, most existing analytical techniques fall short of capturing the complexity of interactions within the concerted population activity. Vine copula-based approaches have shown to be successful at addressing complex high-order dependencies within the population, disentangled from the single-neuron statistics. However, most applications have focused on parametric copulas which bear the risk of misspecifying dependence structures. In order to avoid this risk, we adopted a fully non-parametric approach for the single-neuron margins and copulas by using Neural Spline Flows (NSF). We validated the NSF framework on simulated data of continuous and discrete types with various forms of dependency structures and with different dimensionality. Overall, NSFs performed similarly to existing non-parametric estimators, while allowing for considerably faster and more flexible sampling which also enables faster Monte Carlo estimation of copula entropy. Moreover, our framework was able to capture low and higher order heavy tail dependencies in neuronal responses recorded in the mouse primary visual cortex during a visual learning task while the animal was navigating a virtual reality environment. These findings highlight an often ignored aspect of complexity in coordinated neuronal activity which can be important for understanding and deciphering collective neural dynamics for neurotechnological applications.
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Affiliation(s)
- Lazaros Mitskopoulos
- School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom
- *Correspondence: Lazaros Mitskopoulos
| | - Theoklitos Amvrosiadis
- Centre for Discovery Brain Sciences, Edinburgh Medical School: Biomedical Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Arno Onken
- School of Informatics, Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom
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25
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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: 14] [Impact Index Per Article: 7.0] [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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26
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Schumacher JW, McCann MK, Maximov KJ, Fitzpatrick D. Selective enhancement of neural coding in V1 underlies fine-discrimination learning in tree shrew. Curr Biol 2022; 32:3245-3260.e5. [PMID: 35767997 PMCID: PMC9378627 DOI: 10.1016/j.cub.2022.06.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/29/2022] [Accepted: 06/07/2022] [Indexed: 11/17/2022]
Abstract
Visual discrimination improves with training, a phenomenon that is thought to reflect plastic changes in the responses of neurons in primary visual cortex (V1). However, the identity of the neurons that undergo change, the nature of the changes, and the consequences of these changes for other visual behaviors remain unclear. We used chronic in vivo 2-photon calcium imaging to monitor the responses of neurons in the V1 of tree shrews learning a Go/No-Go fine orientation discrimination task. We observed increases in neural population measures of discriminability for task-relevant stimuli that correlate with performance and depend on a select subset of neurons with preferred orientations that include the rewarded stimulus and nearby orientations biased away from the non-rewarded stimulus. Learning is accompanied by selective enhancement in the response of these neurons to the rewarded stimulus that further increases their ability to discriminate the task stimuli. These changes persist outside of the trained task and predict observed enhancement and impairment in performance of other discriminations, providing evidence for selective and persistent learning-induced plasticity in the V1, with significant consequences for perception.
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Affiliation(s)
- Joseph W Schumacher
- Functional Architecture and Development of Cerebral Cortex, Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA
| | - Matthew K McCann
- Functional Architecture and Development of Cerebral Cortex, Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA
| | - Katherine J Maximov
- Functional Architecture and Development of Cerebral Cortex, Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA
| | - David Fitzpatrick
- Functional Architecture and Development of Cerebral Cortex, Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA.
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27
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Avitan L, Stringer C. Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas. Neuron 2022; 110:3064-3075. [PMID: 35863344 DOI: 10.1016/j.neuron.2022.06.019] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 06/20/2022] [Accepted: 06/22/2022] [Indexed: 11/27/2022]
Abstract
Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances in technology, allowing large-scale neural recordings in the awake and behaving animal, have transformed our understanding of spontaneous activity. Studies using these recordings have discovered high-dimensional spontaneous activity patterns, correlation between spontaneous activity and behavior, and dissimilarity between spontaneous and sensory-driven activity patterns. These findings are supported by evidence from developing animals, where a transition toward these characteristics is observed as the circuit matures, as well as by evidence from mature animals across species. These newly revealed characteristics call for the formulation of a new role for spontaneous activity in neural sensory computation.
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Affiliation(s)
- Lilach Avitan
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
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28
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Existing function in primary visual cortex is not perturbed by new skill acquisition of a non-matched sensory task. Nat Commun 2022; 13:3638. [PMID: 35752622 PMCID: PMC9233699 DOI: 10.1038/s41467-022-31440-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/16/2022] [Indexed: 02/07/2023] Open
Abstract
Acquisition of new skills has the potential to disturb existing network function. To directly assess whether previously acquired cortical function is altered during learning, mice were trained in an abstract task in which selected activity patterns were rewarded using an optical brain-computer interface device coupled to primary visual cortex (V1) neurons. Excitatory neurons were longitudinally recorded using 2-photon calcium imaging. Despite significant changes in local neural activity during task performance, tuning properties and stimulus encoding assessed outside of the trained context were not perturbed. Similarly, stimulus tuning was stable in neurons that remained responsive following a different, visual discrimination training task. However, visual discrimination training increased the rate of representational drift. Our results indicate that while some forms of perceptual learning may modify the contribution of individual neurons to stimulus encoding, new skill learning is not inherently disruptive to the quality of stimulus representation in adult V1.
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29
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Hong SZ, Mesik L, Grossman CD, Cohen JY, Lee B, Severin D, Lee HK, Hell JW, Kirkwood A. Norepinephrine potentiates and serotonin depresses visual cortical responses by transforming eligibility traces. Nat Commun 2022; 13:3202. [PMID: 35680879 PMCID: PMC9184610 DOI: 10.1038/s41467-022-30827-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 05/19/2022] [Indexed: 11/18/2022] Open
Abstract
Reinforcement allows organisms to learn which stimuli predict subsequent biological relevance. Hebbian mechanisms of synaptic plasticity are insufficient to account for reinforced learning because neuromodulators signaling biological relevance are delayed with respect to the neural activity associated with the stimulus. A theoretical solution is the concept of eligibility traces (eTraces), silent synaptic processes elicited by activity which upon arrival of a neuromodulator are converted into a lasting change in synaptic strength. Previously we demonstrated in visual cortical slices the Hebbian induction of eTraces and their conversion into LTP and LTD by the retroactive action of norepinephrine and serotonin Here we show in vivo in mouse V1 that the induction of eTraces and their conversion to LTP/D by norepinephrine and serotonin respectively potentiates and depresses visual responses. We also show that the integrity of this process is crucial for ocular dominance plasticity, a canonical model of experience-dependent plasticity.
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Affiliation(s)
- Su Z Hong
- Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Lukas Mesik
- Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Cooper D Grossman
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Jeremiah Y Cohen
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Boram Lee
- Department of Pharmacology, University of California at Davis, Davis, CA, 95616, USA
| | - Daniel Severin
- Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Hey-Kyoung Lee
- Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Johannes W Hell
- Department of Pharmacology, University of California at Davis, Davis, CA, 95616, USA
| | - Alfredo Kirkwood
- Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, 21218, USA.
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, 21205, USA.
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30
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Corbo J, McClure JP, Erkat OB, Polack PO. Dynamic Distortion of Orientation Representation after Learning in the Mouse Primary Visual Cortex. J Neurosci 2022; 42:4311-4325. [PMID: 35477902 PMCID: PMC9145234 DOI: 10.1523/jneurosci.2272-21.2022] [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: 11/16/2021] [Revised: 01/24/2022] [Accepted: 02/13/2022] [Indexed: 11/21/2022] Open
Abstract
Learning is an essential cognitive mechanism allowing behavioral adaptation through adjustments in neuronal processing. It is associated with changes in the activity of sensory cortical neurons evoked by task-relevant stimuli. However, the exact nature of those modifications and the computational advantages they may confer are still debated. Here, we investigated how learning an orientation discrimination task alters the neuronal representations of the cues orientations in the primary visual cortex (V1) of male and female mice. When comparing the activity evoked by the task stimuli in naive mice and the mice performing the task, we found that the representations of the orientation of the rewarded and nonrewarded cues were more accurate and stable in trained mice. This better cue representation in trained mice was associated with a distortion of the orientation representation space such that stimuli flanking the task-relevant orientations were represented as the task stimuli themselves, suggesting that those stimuli were generalized as the task cues. This distortion was context dependent as it was absent in trained mice passively viewing the task cues and enhanced in the behavioral sessions where mice performed best. Those modifications of the V1 population orientation representation in performing mice were supported by a suppression of the activity of neurons tuned for orientations neighboring the orientations of the task cues. Thus, visual processing in V1 is dynamically adapted to enhance the reliability of the representation of the learned cues and favor generalization in the task-relevant computational space.SIGNIFICANCE STATEMENT Performance improvement in a task often requires facilitating the extraction of the information necessary to its execution. Here, we demonstrate the existence of a suppression mechanism that improves the representation of the orientations of the task stimuli in the V1 of mice performing an orientation discrimination task. We also show that this mechanism distorts the V1 orientation representation space, leading stimuli flanking the task stimuli orientations to be generalized as the task stimuli themselves.
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Affiliation(s)
- Julien Corbo
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, New Jersey 07102
| | - John P McClure
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, New Jersey 07102
- Behavioral and Neural Sciences Graduate Program, Rutgers University-Newark, Newark, New Jersey 07102
| | - O Batuhan Erkat
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, New Jersey 07102
- Behavioral and Neural Sciences Graduate Program, Rutgers University-Newark, Newark, New Jersey 07102
| | - Pierre-Olivier Polack
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, New Jersey 07102
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31
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Pütz C, van den Berg B, Lorist MM. Dynamic modulation of neural feedback processing and attention during spatial probabilistic learning. iScience 2022; 25:104302. [PMID: 35602968 PMCID: PMC9118728 DOI: 10.1016/j.isci.2022.104302] [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: 11/22/2021] [Revised: 03/04/2022] [Accepted: 04/21/2022] [Indexed: 11/25/2022] Open
Abstract
Learned stimulus-reward associations can modulate behavior and the underlying neural processing of information. We investigated the cascade of these neurocognitive mechanisms involved in the learning of spatial stimulus-reward associations. Using electroencephalogram recordings while participants performed a probabilistic spatial reward learning task, we observed that the feedback-related negativity component was more negative in response to loss feedback compared to gain feedback but showed no modulation by learning. The late positive component became larger in response to losses as the learning set progressed but smaller in response to gains. In addition, feedback-locked alpha frequency oscillations measured over occipital sites were predictive of N2pc amplitudes—a marker of spatial attention orienting—observed on the next trial. This relationship was found to become stronger with learning set progression. Taken together, we elucidated neurocognitive dynamics underlying feedback processing during spatial reward learning, and the subsequent effects of these learned spatial stimulus-reward associations on spatial attention. We can learn which spatial location relates to the highest probability of reward Neural processing of feedback valence was not influenced by learning LPC amplitude was dynamically modulated by learning, reflecting context updating Feedback-locked alpha power was predictive of ensuing orientation of attention
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Affiliation(s)
- Celina Pütz
- Department of Experimental Psychology, University of Groningen, Grote Kruisstraat 2/1, Groningen 9712TS, the Netherlands.,Department of Neurobiology, University of Groningen, P.O. Box 11103, Groningen 9700CC, the Netherlands.,Department of Neurology, University Medical Center Groningen, Postbus 30001, Groningen 9700RB, the Netherlands
| | - Berry van den Berg
- Department of Experimental Psychology, University of Groningen, Grote Kruisstraat 2/1, Groningen 9712TS, the Netherlands
| | - Monicque M Lorist
- Department of Experimental Psychology, University of Groningen, Grote Kruisstraat 2/1, Groningen 9712TS, the Netherlands
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32
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An increase in spontaneous activity mediates visual habituation. Cell Rep 2022; 39:110751. [PMID: 35476991 PMCID: PMC9109218 DOI: 10.1016/j.celrep.2022.110751] [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: 03/05/2019] [Revised: 10/13/2021] [Accepted: 04/06/2022] [Indexed: 11/27/2022] Open
Abstract
The cerebral cortex is spontaneously active, but the function of this ongoing activity remains unclear. To test whether spontaneous activity encodes learned experiences, we measured the response of neuronal populations in mouse primary visual cortex with chronic two-photon calcium imaging during visual habituation to a specific oriented stimulus. We find that, during habituation, spontaneous activity increases in neurons across the full range of orientation selectivity, eventually matching that of evoked levels. This increase in spontaneous activity robustly correlates with the degree of habituation. Moreover, boosting spontaneous activity with two-photon optogenetic stimulation to the levels of visually evoked activity accelerates habituation. Our study shows that cortical spontaneous activity is linked to habituation, and we propose that habituation unfolds by minimizing the difference between spontaneous and stimulus-evoked activity levels. We conclude that baseline spontaneous activity could gate incoming sensory information to the cortex based on the learned experience of the animal.
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33
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Montgomery DP, Hayden DJ, Chaloner FA, Cooke SF, Bear MF. Stimulus-Selective Response Plasticity in Primary Visual Cortex: Progress and Puzzles. Front Neural Circuits 2022; 15:815554. [PMID: 35173586 PMCID: PMC8841555 DOI: 10.3389/fncir.2021.815554] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 12/29/2021] [Indexed: 11/23/2022] Open
Abstract
Stimulus-selective response plasticity (SRP) is a robust and lasting modification of primary visual cortex (V1) that occurs in response to exposure to novel visual stimuli. It is readily observed as a pronounced increase in the magnitude of visual evoked potentials (VEPs) recorded in response to phase-reversing grating stimuli in neocortical layer 4. The expression of SRP at the individual neuron level is equally robust, but the qualities vary depending on the neuronal type and how activity is measured. This form of plasticity is highly selective for stimulus features such as stimulus orientation, spatial frequency, and contrast. Several key insights into the significance and underlying mechanisms of SRP have recently been made. First, it occurs concomitantly and shares core mechanisms with behavioral habituation, indicating that SRP reflects the formation of long-term familiarity that can support recognition of innocuous stimuli. Second, SRP does not manifest within a recording session but only emerges after an off-line period of several hours that includes sleep. Third, SRP requires not only canonical molecular mechanisms of Hebbian synaptic plasticity within V1, but also the opposing engagement of two key subclasses of cortical inhibitory neuron: the parvalbumin- and somatostatin-expressing GABAergic interneurons. Fourth, pronounced shifts in the power of cortical oscillations from high frequency (gamma) to low frequency (alpha/beta) oscillations provide respective readouts of the engagement of these inhibitory neuronal subtypes following familiarization. In this article we will discuss the implications of these findings and the outstanding questions that remain to gain a deeper understanding of this striking form of experience-dependent plasticity.
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Affiliation(s)
- Daniel P. Montgomery
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Dustin J. Hayden
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Francesca A. Chaloner
- MRC Centre for Neurodevelopmental Disorders (CNDD), King’s College London, London, United Kingdom
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Samuel F. Cooke
- MRC Centre for Neurodevelopmental Disorders (CNDD), King’s College London, London, United Kingdom
- Department of Basic and Clinical Neuroscience, The Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Mark F. Bear
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States
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34
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Padamsey Z, Katsanevaki D, Dupuy N, Rochefort NL. Neocortex saves energy by reducing coding precision during food scarcity. Neuron 2022; 110:280-296.e10. [PMID: 34741806 PMCID: PMC8788933 DOI: 10.1016/j.neuron.2021.10.024] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 09/07/2021] [Accepted: 10/15/2021] [Indexed: 11/21/2022]
Abstract
Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy use are regulated during food scarcity. Using whole-cell recordings and two-photon imaging in layer 2/3 mouse visual cortex, we found that food restriction reduced AMPA receptor conductance, reducing synaptic ATP use by 29%. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting potential. Consequently, neurons spiked at similar rates as controls but spent less ATP on underlying excitatory currents. This energy-saving strategy had a cost because it amplified the variability of visually-evoked subthreshold responses, leading to a 32% broadening of orientation tuning and impaired fine visual discrimination. This reduction in coding precision was associated with reduced levels of the fat mass-regulated hormone leptin and was restored by exogenous leptin supplementation. Our findings reveal that metabolic state dynamically regulates the energy spent on coding precision in neocortex.
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Affiliation(s)
- Zahid Padamsey
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK.
| | - Danai Katsanevaki
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
| | - Nathalie Dupuy
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, UK; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh EH8 9XD, UK.
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35
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Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships. PLoS Comput Biol 2022; 18:e1009799. [PMID: 35089913 PMCID: PMC8827448 DOI: 10.1371/journal.pcbi.1009799] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 02/09/2022] [Accepted: 01/02/2022] [Indexed: 11/19/2022] Open
Abstract
One of the main goals of current systems neuroscience is to understand how neuronal populations integrate sensory information to inform behavior. However, estimating stimulus or behavioral information that is encoded in high-dimensional neuronal populations is challenging. We propose a method based on parametric copulas which allows modeling joint distributions of neuronal and behavioral variables characterized by different statistics and timescales. To account for temporal or spatial changes in dependencies between variables, we model varying copula parameters by means of Gaussian Processes (GP). We validate the resulting Copula-GP framework on synthetic data and on neuronal and behavioral recordings obtained in awake mice. We show that the use of a parametric description of the high-dimensional dependence structure in our method provides better accuracy in mutual information estimation in higher dimensions compared to other non-parametric methods. Moreover, by quantifying the redundancy between neuronal and behavioral variables, our model exposed the location of the reward zone in an unsupervised manner (i.e., without using any explicit cues about the task structure). These results demonstrate that the Copula-GP framework is particularly useful for the analysis of complex multidimensional relationships between neuronal, sensory and behavioral variables. Understanding the relationship between a set of variables is a common problem in many fields, such as weather forecast or stock market data. In neuroscience, one of the main challenges is to characterize the dependencies between neuronal activity, sensory stimuli and behavioral outputs. A method of choice for modeling such statistical dependencies is based on copulas, which disentangle dependencies from single variable statistics. To account for changes in dependencies, we model changes in copula parameters by means of Gaussian Processes, conditioned on a task-related variable. The novelty of our approach includes 1) explicit modeling of the dependencies; and 2) combining different copulas to describe experimentally observed variability. We validate the goodness-of-fit as well as information estimates on synthetic data and on recordings from the visual cortex of mice performing a behavioral task. Our parametric model demonstrates significantly better performance in describing high dimensional dependencies compared to other commonly used techniques. We demonstrate that our model can estimate information and predict behaviorally-relevant parameters of the task without providing any explicit cues to the model. Our results indicate that our model is interpretable in the context of neuroscience applications, scalable to large datasets and suitable for accurate statistical modeling and information estimation.
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Abstract
Learned associations between stimuli in different sensory modalities can shape the way we perceive these stimuli. However, it is not well understood how these interactions are mediated or at what level of the processing hierarchy they occur. Here we describe a neural mechanism by which an auditory input can shape visual representations of behaviorally relevant stimuli through direct interactions between auditory and visual cortices in mice. We show that the association of an auditory stimulus with a visual stimulus in a behaviorally relevant context leads to experience-dependent suppression of visual responses in primary visual cortex (V1). Auditory cortex axons carry a mixture of auditory and retinotopically matched visual input to V1, and optogenetic stimulation of these axons selectively suppresses V1 neurons that are responsive to the associated visual stimulus after, but not before, learning. Our results suggest that cross-modal associations can be communicated by long-range cortical connections and that, with learning, these cross-modal connections function to suppress responses to predictable input.
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Lee J, Urban-Ciecko J, Park E, Zhu M, Myal SE, Margolis DJ, Barth AL. FosGFP expression does not capture a sensory learning-related engram in superficial layers of mouse barrel cortex. Proc Natl Acad Sci U S A 2021; 118:e2112212118. [PMID: 34930843 PMCID: PMC8719899 DOI: 10.1073/pnas.2112212118] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/07/2021] [Indexed: 11/18/2022] Open
Abstract
Immediate-early gene (IEG) expression has been used to identify small neural ensembles linked to a particular experience, based on the principle that a selective subset of activated neurons will encode specific memories or behavioral responses. The majority of these studies have focused on "engrams" in higher-order brain areas where more abstract or convergent sensory information is represented, such as the hippocampus, prefrontal cortex, or amygdala. In primary sensory cortex, IEG expression can label neurons that are responsive to specific sensory stimuli, but experience-dependent shaping of neural ensembles marked by IEG expression has not been demonstrated. Here, we use a fosGFP transgenic mouse to longitudinally monitor in vivo expression of the activity-dependent gene c-fos in superficial layers (L2/3) of primary somatosensory cortex (S1) during a whisker-dependent learning task. We find that sensory association training does not detectably alter fosGFP expression in L2/3 neurons. Although training broadly enhances thalamocortical synaptic strength in pyramidal neurons, we find that synapses onto fosGFP+ neurons are not selectively increased by training; rather, synaptic strengthening is concentrated in fosGFP- neurons. Taken together, these data indicate that expression of the IEG reporter fosGFP does not facilitate identification of a learning-specific engram in L2/3 in barrel cortex during whisker-dependent sensory association learning.
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Affiliation(s)
- Jiseok Lee
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Joanna Urban-Ciecko
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland
| | - Eunsol Park
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Mo Zhu
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Stephanie E Myal
- University of Pittsburgh School of Medicine, Pittsburgh, PA 15213
| | - David J Margolis
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ 08854
| | - Alison L Barth
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213;
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Bramlage L, Cortese A. Generalized attention-weighted reinforcement learning. Neural Netw 2021; 145:10-21. [PMID: 34710787 DOI: 10.1016/j.neunet.2021.09.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 08/19/2021] [Accepted: 09/24/2021] [Indexed: 11/26/2022]
Abstract
In neuroscience, attention has been shown to bidirectionally interact with reinforcement learning (RL) to reduce the dimensionality of task representations, restricting computations to relevant features. In machine learning, despite their popularity, attention mechanisms have seldom been administered to decision-making problems. Here, we leverage a theoretical model from computational neuroscience - the attention-weighted RL (AWRL), defining how humans identify task-relevant features (i.e., that allow value predictions) - to design an applied deep RL paradigm. We formally demonstrate that the conjunction of the self-attention mechanism, widely employed in machine learning, with value function approximation is a general formulation of the AWRL model. To evaluate our agent, we train it on three Atari tasks at different complexity levels, incorporating both task-relevant and irrelevant features. Because the model uses semantic observations, we can uncover not only which features the agent elects to base decisions on, but also how it chooses to compile more complex, relational features from simpler ones. We first show that performance depends in large part on the ability to compile new compound features, rather than mere focus on individual features. In line with neuroscience predictions, self-attention leads to high resiliency to noise (irrelevant features) compared to other benchmark models. Finally, we highlight the importance and separate contributions of both bottom-up and top-down attention in the learning process. Together, these results demonstrate the broader validity of the AWRL framework in complex task scenarios, and illustrate the benefits of a deeper integration between neuroscience-derived models and RL for decision making in machine learning.
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Affiliation(s)
- Lennart Bramlage
- Faculty of Technology, Bielefeld University, 33615, Germany; Computational Neuroscience Labs, ATR Institute International, 619-0288, Japan.
| | - Aurelio Cortese
- Computational Neuroscience Labs, ATR Institute International, 619-0288, Japan.
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39
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Sun W, Choi I, Stoyanov S, Senkov O, Ponimaskin E, Winter Y, Pakan JMP, Dityatev A. Context value updating and multidimensional neuronal encoding in the retrosplenial cortex. Nat Commun 2021; 12:6045. [PMID: 34663792 PMCID: PMC8523535 DOI: 10.1038/s41467-021-26301-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Accepted: 09/24/2021] [Indexed: 11/26/2022] Open
Abstract
The retrosplenial cortex (RSC) has diverse functional inputs and is engaged by various sensory, spatial, and associative learning tasks. We examine how multiple functional aspects are integrated on the single-cell level in the RSC and how the encoding of task-related parameters changes across learning. Using a visuospatial context discrimination paradigm and two-photon calcium imaging in behaving mice, a large proportion of dysgranular RSC neurons was found to encode multiple task-related dimensions while forming context-value associations across learning. During reversal learning requiring increased cognitive flexibility, we revealed an increased proportion of multidimensional encoding neurons that showed higher decoding accuracy for behaviorally relevant context-value associations. Chemogenetic inactivation of RSC led to decreased behavioral context discrimination during learning phases in which context-value associations were formed, while recall of previously formed associations remained intact. RSC inactivation resulted in a persistent positive behavioral bias in valuing contexts, indicating a role for the RSC in context-value updating.
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Affiliation(s)
- Weilun Sun
- grid.424247.30000 0004 0438 0426Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany ,grid.418723.b0000 0001 2109 6265Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
| | - Ilseob Choi
- grid.424247.30000 0004 0438 0426Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany ,grid.418723.b0000 0001 2109 6265Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
| | - Stoyan Stoyanov
- grid.424247.30000 0004 0438 0426Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Oleg Senkov
- grid.424247.30000 0004 0438 0426Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Evgeni Ponimaskin
- grid.10423.340000 0000 9529 9877Department of Cellular Neurophysiology, Hannover Medical School, Hannover, Germany
| | - York Winter
- grid.7468.d0000 0001 2248 7639Institute for Biology, Humboldt University, Berlin, Germany
| | - Janelle M. P. Pakan
- grid.418723.b0000 0001 2109 6265Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany ,grid.5807.a0000 0001 1018 4307Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Alexander Dityatev
- grid.424247.30000 0004 0438 0426Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany ,grid.418723.b0000 0001 2109 6265Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany ,grid.5807.a0000 0001 1018 4307Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany
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Dylda E, Pakan JMP. Visual plasticity: Illuminating the role of the hippocampus in cortical sensory encoding. Curr Biol 2021; 31:R1087-R1089. [PMID: 34582817 DOI: 10.1016/j.cub.2021.07.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
The primary visual cortex has the capacity to store stimulus-specific information locally. A new study reveals a direct role for the hippocampus in experience-dependent cortical plasticity when visual stimuli are presented in a predictable temporal order.
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Affiliation(s)
- Evelyn Dylda
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany; Center for Behavioral Brain Sciences, Universitätsplatz 2, 39120 Magdeburg, Germany
| | - Janelle M P Pakan
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany; Center for Behavioral Brain Sciences, Universitätsplatz 2, 39120 Magdeburg, Germany; German Centre for Neurodegenerative Diseases, Leipziger Str. 44, 39120 Magdeburg, Germany.
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41
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Pérez-Ortega J, Alejandre-García T, Yuste R. Long-term stability of cortical ensembles. eLife 2021; 10:e64449. [PMID: 34328414 PMCID: PMC8376248 DOI: 10.7554/elife.64449] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 07/29/2021] [Indexed: 12/25/2022] Open
Abstract
Neuronal ensembles, coactive groups of neurons found in spontaneous and evoked cortical activity, are causally related to memories and perception, but it is still unknown how stable or flexible they are over time. We used two-photon multiplane calcium imaging to track over weeks the activity of the same pyramidal neurons in layer 2/3 of the visual cortex from awake mice and recorded their spontaneous and visually evoked responses. Less than half of the neurons remained active across any two imaging sessions. These stable neurons formed ensembles that lasted weeks, but some ensembles were also transient and appeared only in one single session. Stable ensembles preserved most of their neurons for up to 46 days, our longest imaged period, and these 'core' cells had stronger functional connectivity. Our results demonstrate that neuronal ensembles can last for weeks and could, in principle, serve as a substrate for long-lasting representation of perceptual states or memories.
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Affiliation(s)
- Jesús Pérez-Ortega
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
| | | | - Rafael Yuste
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
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42
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Over-representation of fundamental decision variables in the prefrontal cortex underlies decision bias. Neurosci Res 2021; 173:1-13. [PMID: 34274406 DOI: 10.1016/j.neures.2021.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 06/15/2021] [Accepted: 07/13/2021] [Indexed: 11/24/2022]
Abstract
The brain is organized into anatomically distinct structures consisting of a variety of projection neurons. While such evolutionarily conserved neural circuit organization underlies the innate ability of animals to swiftly adapt to environments, they can cause biased cognition and behavior. Although recent studies have begun to address the causal importance of projection-neuron types as distinct computational units, it remains unclear how projection types are functionally organized in encoding variables during cognitive tasks. This review focuses on the neural computation of decision making in the prefrontal cortex and discusses what decision variables are encoded by single neurons, neuronal populations, and projection type, alongside how specific projection types constrain decision making. We focus particularly on "over-representations" of distinct decision variables in the prefrontal cortex that reflect the biological and subjective significance of the variables for the decision makers. We suggest that task-specific over-representation in the prefrontal cortex involves the refinement of the given decision making, while generalized over-representation of fundamental decision variables is associated with suboptimal decision biases, including pathological ones such as those in patients with psychiatric disorders. Such over-representation of the fundamental decision variables in the prefrontal cortex appear to be tightly constrained by afferent and efferent connections that can be optogenetically intervened on. These ideas may provide critical insights into potential therapeutic targets for psychiatric disorders, including addiction and depression.
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43
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Francioni V, Harnett MT. Rethinking Single Neuron Electrical Compartmentalization: Dendritic Contributions to Network Computation In Vivo. Neuroscience 2021; 489:185-199. [PMID: 34116137 DOI: 10.1016/j.neuroscience.2021.05.038] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/11/2021] [Accepted: 05/29/2021] [Indexed: 12/15/2022]
Abstract
Decades of experimental and theoretical work support a now well-established theory that active dendritic processing contributes to the computational power of individual neurons. This theory is based on the high degree of electrical compartmentalization observed in the dendrites of single neurons in ex vivo preparations. Compartmentalization allows dendrites to conduct semi-independent operations on their inputs before final integration and output at the axon, producing a "network-in-a-neuron." However, recent in vivo functional imaging experiments in mouse cortex have reported surprisingly little evidence for strong dendritic compartmentalization. In this review, we contextualize these new findings and discuss their impact on the future of the field. Specifically, we consider how highly coordinated, and thus less compartmentalized, activity in soma and dendrites can contribute to cortical computations including nonlinear mixed selectivity, prediction/expectation, multiplexing, and credit assignment.
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Affiliation(s)
- Valerio Francioni
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Mark T Harnett
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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44
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Evaluating Visual Cues Modulates Their Representation in Mouse Visual and Cingulate Cortex. J Neurosci 2021; 41:3531-3544. [PMID: 33687964 DOI: 10.1523/jneurosci.1828-20.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 02/12/2021] [Accepted: 02/17/2021] [Indexed: 11/21/2022] Open
Abstract
Choosing an action in response to visual cues relies on cognitive processes, such as perception, evaluation, and prediction, which can modulate visual representations even at early processing stages. In the mouse, it is challenging to isolate cognitive modulations of sensory signals because concurrent overt behavior patterns, such as locomotion, can also have brainwide influences. To address this challenge, we designed a task, in which head-fixed mice had to evaluate one of two visual cues. While their global shape signaled the opportunity to earn reward, the cues provided equivalent local stimulation to receptive fields of neurons in primary visual (V1) and anterior cingulate cortex (ACC). We found that mice evaluated these cues within few hundred milliseconds. During this period, ∼30% of V1 neurons became cue-selective, with preferences for either cue being balanced across the recorded population. This selectivity emerged in response to the behavioral demands because the same neurons could not discriminate the cues in sensory control measurements. In ACC, cue evaluation affected a similar fraction of neurons; emerging selectivity, however, was stronger than in V1, and preferences in the recorded population were biased toward the cue promising reward. Such a biased selectivity regime might allow the mouse to infer the promise of reward simply by the overall level of activity. Together, these experiments isolate the impact of task demands on neural responses in mouse cerebral cortex, and document distinct neural signatures of cue evaluation in V1 and ACC.SIGNIFICANCE STATEMENT Performing a cognitive task, such as evaluating visual cues, not only recruits frontal and parietal brain regions, but also modulates sensory processing stages. We trained mice to evaluate two visual cues, and show that, during this task, ∼30% of neurons recorded in V1 became selective for either cue, although they provided equivalent visual stimulation. We also show that, during cue evaluation, mice frequently move their eyes, even under head fixation, and that ignoring systematic differences in eye position can substantially obscure the modulations seen in V1 neurons. Finally, we document that modulations are stronger in ACC, and biased toward the reward-predicting cue, suggesting a transition in the neural representation of task-relevant information across processing stages in mouse cerebral cortex.
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45
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Bean NL, Stein BE, Rowland BA. Stimulus value gates multisensory integration. Eur J Neurosci 2021; 53:3142-3159. [PMID: 33667027 DOI: 10.1111/ejn.15167] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 02/18/2021] [Accepted: 02/22/2021] [Indexed: 11/28/2022]
Abstract
The brain enhances its perceptual and behavioral decisions by integrating information from its multiple senses in what are believed to be optimal ways. This phenomenon of "multisensory integration" appears to be pre-conscious, effortless, and highly efficient. The present experiments examined whether experience could modify this seemingly automatic process. Cats were trained in a localization task in which congruent pairs of auditory-visual stimuli are normally integrated to enhance detection and orientation/approach performance. Consistent with the results of previous studies, animals more reliably detected and approached cross-modal pairs than their modality-specific component stimuli, regardless of whether the pairings were novel or familiar. However, when provided evidence that one of the modality-specific component stimuli had no value (it was not rewarded) animals ceased integrating it with other cues, and it lost its previous ability to enhance approach behaviors. Cross-modal pairings involving that stimulus failed to elicit enhanced responses even when the paired stimuli were congruent and mutually informative. However, the stimulus regained its ability to enhance responses when it was associated with reward. This suggests that experience can selectively block access of stimuli (i.e., filter inputs) to the multisensory computation. Because this filtering process results in the loss of useful information, its operation and behavioral consequences are not optimal. Nevertheless, the process can be of substantial value in natural environments, rich in dynamic stimuli, by using experience to minimize the impact of stimuli unlikely to be of biological significance, and reducing the complexity of the problem of matching signals across the senses.
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Affiliation(s)
- Naomi L Bean
- Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Barry E Stein
- Wake Forest School of Medicine, Winston-Salem, NC, USA
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Bale MR, Bitzidou M, Giusto E, Kinghorn P, Maravall M. Sequence Learning Induces Selectivity to Multiple Task Parameters in Mouse Somatosensory Cortex. Curr Biol 2021; 31:473-485.e5. [PMID: 33186553 PMCID: PMC7883307 DOI: 10.1016/j.cub.2020.10.059] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 09/01/2020] [Accepted: 10/20/2020] [Indexed: 11/20/2022]
Abstract
Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence discrimination, we developed a task in which mice distinguished between tactile "word" sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a "detection of change" problem, but enhanced their performance when responding later. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory "barrel" cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal's action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal's learned action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were found in naive mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf, sequence learning results in neurons whose activity reflects the learned association between target sequence and licking rather than a refined representation of sensory features.
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Affiliation(s)
- Michael R Bale
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Malamati Bitzidou
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Elena Giusto
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Paul Kinghorn
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK
| | - Miguel Maravall
- Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK.
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47
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Flossmann T, Rochefort NL. Spatial navigation signals in rodent visual cortex. Curr Opin Neurobiol 2020; 67:163-173. [PMID: 33360769 DOI: 10.1016/j.conb.2020.11.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/04/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022]
Abstract
During navigation, animals integrate sensory information with body movements to guide actions. The impact of both navigational and movement-related signals on cortical visual information processing remains largely unknown. We review recent studies in awake rodents that have revealed navigation-related signals in the primary visual cortex (V1) including speed, distance travelled and head-orienting movements. Both cortical and subcortical inputs convey self-motion related information to V1 neurons: for example, top-down inputs from secondary motor and retrosplenial cortices convey information about head movements and spatial expectations. Within V1, subtypes of inhibitory neurons are critical for the integration of navigation-related and visual signals. We conclude with potential functional roles of navigation-related signals in V1 including gain control, motor error signals and predictive coding.
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Affiliation(s)
- Tom Flossmann
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom
| | - Nathalie L Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom; Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD, United Kingdom.
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48
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Losacco J, George NM, Hiratani N, Restrepo D. The Olfactory Bulb Facilitates Use of Category Bounds for Classification of Odorants in Different Intensity Groups. Front Cell Neurosci 2020; 14:613635. [PMID: 33362477 PMCID: PMC7759615 DOI: 10.3389/fncel.2020.613635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 11/16/2020] [Indexed: 11/22/2022] Open
Abstract
Signal processing of odor inputs to the olfactory bulb (OB) changes through top-down modulation whose shaping of neural rhythms in response to changes in stimulus intensity is not understood. Here we asked whether the representation of a high vs. low intensity odorant in the OB by oscillatory neural activity changed as the animal learned to discriminate odorant concentration ranges in a go-no go task. We trained mice to discriminate between high vs. low concentration odorants by learning to lick to the rewarded group (low or high). We recorded the local field potential (LFP) in the OB of these mice and calculated the theta-referenced beta or gamma oscillation power (theta phase-referenced power, or tPRP). We found that as the mouse learned to differentiate odorant concentrations, tPRP diverged between trials for the rewarded vs. the unrewarded concentration range. For the proficient animal, linear discriminant analysis was able to predict the rewarded odorant group and the performance of this classifier correlated with the percent correct behavior in the odor concentration discrimination task. Interestingly, the behavioral response and decoding accuracy were asymmetric as a function of concentration when the rewarded stimulus was shifted between the high and low odorant concentration ranges. A model for decision making motivated by the statistics of OB activity that uses a single threshold in a logarithmic concentration scale displays this asymmetry. Taken together with previous studies on the intensity criteria for decisions on odorant concentrations, our finding suggests that OB oscillatory events facilitate decision making to classify concentrations using a single intensity criterion.
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Affiliation(s)
- Justin Losacco
- Neuroscience Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Nicholas M. George
- Neuroscience Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Naoki Hiratani
- Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
| | - Diego Restrepo
- Neuroscience Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
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49
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Takagaki K, Krug K. The effects of reward and social context on visual processing for perceptual decision-making. CURRENT OPINION IN PHYSIOLOGY 2020. [DOI: 10.1016/j.cophys.2020.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Laliberté G, Othman R, Vaucher E. Mesoscopic Mapping of Stimulus-Selective Response Plasticity in the Visual Pathways Modulated by the Cholinergic System. Front Neural Circuits 2020; 14:38. [PMID: 32719589 PMCID: PMC7350895 DOI: 10.3389/fncir.2020.00038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 05/22/2020] [Indexed: 11/13/2022] Open
Abstract
The cholinergic potentiation of visual conditioning enhances visual acuity and discrimination of the trained stimulus. To determine if this also induces long-term plastic changes on cortical maps and connectivity in the visual cortex and higher associative areas, mesoscopic calcium imaging was performed in head-fixed awake GCaMP6s adult mice before and after conditioning. The conditioned stimulus (0.03 cpd, 30°, 100% contrast, 1 Hz-drifting gratings) was presented 10 min daily for a week. Saline or Donepezil (DPZ, 0.3 mg/kg, s.c.), a cholinesterase inhibitor that potentiates cholinergic transmission, were injected prior to each conditioning session and compared to a sham-conditioned group. Cortical maps of resting state and evoked response to the monocular presentation of conditioned or non-conditioned stimulus (30°, 50 and 75% contrast; 90°, 50, 75, and 100% contrast) were established. Amplitude, duration, and latency of the peak response, as well as size of activation were measured in the primary visual cortex (V1), secondary visual areas (AL, A, AM, PM, LM, RL), retrosplenial cortex (RSC), and higher cortical areas. Visual stimulation increased calcium signaling in all primary and secondary visual areas, the RSC, but no other cortices. There were no significant effects of sham-conditioning or conditioning alone, but DPZ treatment during conditioning significantly decreased the integrated neuronal activity of superficial layers evoked by the conditioned stimulus in V1, AL, PM, and LM. The activity of downstream cortical areas was not changed. The size of the activated area was decreased in V1 and PM, and the signal-to-noise ratio was decreased in AL and PM. Interestingly, signal correlation was seen only between V1, the ventral visual pathway, and the RSC, and was decreased by DPZ administration. The resting state activity was slightly correlated and rarely affected by treatments, except between binocular and monocular V1 in both hemispheres. In conclusion, cholinergic potentiation of visual conditioning induced change in visual processing in the superficial cortical layers. This effect might be a key mechanism in the establishment of the fine cortical tuning in response to the conditioned visual stimulus.
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Affiliation(s)
- Guillaume Laliberté
- Laboratoire de Neurobiologie de la Cognition Visuelle, École d'Optométrie, Université de Montréal, Montréal, QC, Canada
| | - Rahmeh Othman
- Laboratoire de Neurobiologie de la Cognition Visuelle, École d'Optométrie, Université de Montréal, Montréal, QC, Canada.,Départment de Pharmacologie et Physiologie, Faculté de Médecine, Université de Montréal, Montréal, QC, Canada
| | - Elvire Vaucher
- Laboratoire de Neurobiologie de la Cognition Visuelle, École d'Optométrie, Université de Montréal, Montréal, QC, Canada
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