{"title":"This Week in The Journal","authors":"","doi":"10.1056/NEJMtwj230105","DOIUrl":"https://doi.org/10.1056/NEJMtwj230105","url":null,"abstract":"","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"120 1","pages":"2221 - 2221"},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87961455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1523/jneurosci.twij.43.13.2023
{"title":"This Week in The Journal","authors":"","doi":"10.1523/jneurosci.twij.43.13.2023","DOIUrl":"https://doi.org/10.1523/jneurosci.twij.43.13.2023","url":null,"abstract":"","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135529262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-22DOI: 10.1523/JNEUROSCI.twij.43.12.2023
{"title":"This Week in The Journal","authors":"","doi":"10.1523/JNEUROSCI.twij.43.12.2023","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.twij.43.12.2023","url":null,"abstract":"","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"34 1","pages":"2036 - 2036"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77594369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-15DOI: 10.1523/JNEUROSCI.twij.43.11.2023
{"title":"This Week in The Journal","authors":"","doi":"10.1523/JNEUROSCI.twij.43.11.2023","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.twij.43.11.2023","url":null,"abstract":"","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"303 1","pages":"1858 - 1858"},"PeriodicalIF":0.0,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73617050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-14DOI: 10.1101/2022.09.11.507456
R. L. Suthard, R. Senne, Michelle D. Buzharsky, Angela Y. Pyo, Kaitlyn E. Dorst, A. H. Diep, Rebecca H. Cole, S. Ramirez
Astrocytes are key cellular regulators within the brain. The basolateral amygdala (BLA) is implicated in fear memory processing, yet most research has entirely focused on neuronal mechanisms, despite a significant body of work implicating astrocytes in learning and memory. In the present study, we used in vivo fiber photometry in C57BL/6J male mice to record from amygdalar astrocytes across fear learning, recall, and three separate periods of extinction. We found that BLA astrocytes robustly responded to foot shock during acquisition, their activity remained remarkably elevated across days in comparison to unshocked control animals, and their increased activity persisted throughout extinction. Further, we found that astrocytes responded to the initiation and termination of freezing bouts during contextual fear conditioning and recall, and this behavior-locked pattern of activity did not persist throughout the extinction sessions. Importantly, astrocytes do not display these changes while exploring a novel context, suggesting that these observations are specific to the original fear-associated environment. Chemogenetic inhibition of fear ensembles in the BLA did not affect freezing behavior or astrocytic calcium dynamics. Overall, our work presents a real-time role for amygdalar astrocytes in fear processing and provides new insight into the emerging role of these cells in cognition and behavior. SIGNIFICANCE STATEMENT We show that basolateral amygdala astrocytes are robustly responsive to negative experiences, like shock, and display changed calcium activity patterns through fear learning and memory. Additionally, astrocytic calcium responses become time locked to the initiation and termination of freezing behavior during fear learning and recall. We find that astrocytes display calcium dynamics unique to a fear-conditioned context, and chemogenetic inhibition of BLA fear ensembles does not have an impact on freezing behavior or calcium dynamics. These findings show that astrocytes play a key real-time role in fear learning and memory.
{"title":"Basolateral Amygdala Astrocytes Are Engaged by the Acquisition and Expression of a Contextual Fear Memory","authors":"R. L. Suthard, R. Senne, Michelle D. Buzharsky, Angela Y. Pyo, Kaitlyn E. Dorst, A. H. Diep, Rebecca H. Cole, S. Ramirez","doi":"10.1101/2022.09.11.507456","DOIUrl":"https://doi.org/10.1101/2022.09.11.507456","url":null,"abstract":"Astrocytes are key cellular regulators within the brain. The basolateral amygdala (BLA) is implicated in fear memory processing, yet most research has entirely focused on neuronal mechanisms, despite a significant body of work implicating astrocytes in learning and memory. In the present study, we used in vivo fiber photometry in C57BL/6J male mice to record from amygdalar astrocytes across fear learning, recall, and three separate periods of extinction. We found that BLA astrocytes robustly responded to foot shock during acquisition, their activity remained remarkably elevated across days in comparison to unshocked control animals, and their increased activity persisted throughout extinction. Further, we found that astrocytes responded to the initiation and termination of freezing bouts during contextual fear conditioning and recall, and this behavior-locked pattern of activity did not persist throughout the extinction sessions. Importantly, astrocytes do not display these changes while exploring a novel context, suggesting that these observations are specific to the original fear-associated environment. Chemogenetic inhibition of fear ensembles in the BLA did not affect freezing behavior or astrocytic calcium dynamics. Overall, our work presents a real-time role for amygdalar astrocytes in fear processing and provides new insight into the emerging role of these cells in cognition and behavior. SIGNIFICANCE STATEMENT We show that basolateral amygdala astrocytes are robustly responsive to negative experiences, like shock, and display changed calcium activity patterns through fear learning and memory. Additionally, astrocytic calcium responses become time locked to the initiation and termination of freezing behavior during fear learning and recall. We find that astrocytes display calcium dynamics unique to a fear-conditioned context, and chemogenetic inhibition of BLA fear ensembles does not have an impact on freezing behavior or calcium dynamics. These findings show that astrocytes play a key real-time role in fear learning and memory.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"25 1","pages":"4997 - 5013"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81300221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Category selectivity is a fundamental principle of organization of perceptual brain regions. Human occipitotemporal cortex is subdivided into areas that respond preferentially to faces, bodies, artifacts, and scenes. However, observers need to combine information about objects from different categories to form a coherent understanding of the world. How is this multicategory information encoded in the brain? Studying the multivariate interactions between brain regions of male and female human subjects with fMRI and artificial neural networks, we found that the angular gyrus shows joint statistical dependence with multiple category-selective regions. Adjacent regions show effects for the combination of scenes and each other category, suggesting that scenes provide a context to combine information about the world. Additional analyses revealed a cortical map of areas that encode information across different subsets of categories, indicating that multicategory information is not encoded in a single centralized location, but in multiple distinct brain regions. SIGNIFICANCE STATEMENT Many cognitive tasks require combining information about entities from different categories. However, visual information about different categorical objects is processed by separate, specialized brain regions. How is the joint representation from multiple category-selective regions implemented in the brain? Using fMRI movie data and state-of-the-art multivariate statistical dependence based on artificial neural networks, we identified the angular gyrus encoding responses across face-, body-, artifact-, and scene-selective regions. Further, we showed a cortical map of areas that encode information across different subsets of categories. These findings suggest that multicategory information is not encoded in a single centralized location, but at multiple cortical sites which might contribute to distinct cognitive functions, offering insights to understand integration in a variety of domains.
{"title":"Angular Gyrus Responses Show Joint Statistical Dependence with Brain Regions Selective for Different Categories","authors":"Mengting Fang, Aidas Aglinskas, Yichen Li, Stefano Anzellotti","doi":"10.32470/ccn.2022.1036-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1036-0","url":null,"abstract":"Category selectivity is a fundamental principle of organization of perceptual brain regions. Human occipitotemporal cortex is subdivided into areas that respond preferentially to faces, bodies, artifacts, and scenes. However, observers need to combine information about objects from different categories to form a coherent understanding of the world. How is this multicategory information encoded in the brain? Studying the multivariate interactions between brain regions of male and female human subjects with fMRI and artificial neural networks, we found that the angular gyrus shows joint statistical dependence with multiple category-selective regions. Adjacent regions show effects for the combination of scenes and each other category, suggesting that scenes provide a context to combine information about the world. Additional analyses revealed a cortical map of areas that encode information across different subsets of categories, indicating that multicategory information is not encoded in a single centralized location, but in multiple distinct brain regions. SIGNIFICANCE STATEMENT Many cognitive tasks require combining information about entities from different categories. However, visual information about different categorical objects is processed by separate, specialized brain regions. How is the joint representation from multiple category-selective regions implemented in the brain? Using fMRI movie data and state-of-the-art multivariate statistical dependence based on artificial neural networks, we identified the angular gyrus encoding responses across face-, body-, artifact-, and scene-selective regions. Further, we showed a cortical map of areas that encode information across different subsets of categories. These findings suggest that multicategory information is not encoded in a single centralized location, but at multiple cortical sites which might contribute to distinct cognitive functions, offering insights to understand integration in a variety of domains.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"38 1","pages":"2756 - 2766"},"PeriodicalIF":0.0,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77344129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-09DOI: 10.1101/2022.07.22.501038
Sam Z. Bacharach, David A. Martin, Cassie A. Stapf, Fangmiao Sun, Yulong Li, J. Cheer, Donna J. Calu
Sign-tracking (ST) rats show enhanced cue sensitivity before drug experience that predicts greater discrete cue-induced drug seeking compared with goal-tracking or intermediate rats. Cue-evoked dopamine in the nucleus accumbens (NAc) is a neurobiological signature of sign-tracking behaviors. Here, we examine a critical regulator of the dopamine system, endocannabinoids, which bind the cannabinoid receptor-1 (CB1R) in the ventral tegmental area (VTA) to control cue-evoked striatal dopamine levels. We use cell type-specific optogenetics, intra-VTA pharmacology, and fiber photometry to test the hypothesis that VTA CB1R receptor signaling regulates NAc dopamine levels to control sign tracking. We trained male and female rats in a Pavlovian lever autoshaping (PLA) task to determine their tracking groups before testing the effect of VTA → NAc dopamine inhibition. We found that this circuit is critical for mediating the vigor of the ST response. Upstream of this circuit, intra-VTA infusions of rimonabant, a CB1R inverse agonist, during PLA decrease lever and increase food cup approach in sign-trackers. Using fiber photometry to measure fluorescent signals from a dopamine sensor, GRABDA (AAV9-hSyn-DA2m), we tested the effects of intra-VTA rimonabant on NAc dopamine dynamics during autoshaping in female rats. We found that intra-VTA rimonabant decreased sign-tracking behaviors, which was associated with increases in NAc shell, but not core, dopamine levels during reward delivery [unconditioned stimulus (US)]. Our results suggest that CB1R signaling in the VTA influences the balance between the conditioned stimulus-evoked and US-evoked dopamine responses in the NAc shell and biases behavioral responding to cues in sign-tracking rats. SIGNIFICANCE STATEMENT Substance use disorder (SUD) is a chronically relapsing psychological disorder that affects a subset of individuals who engage in drug use. Recent research suggests that there are individual behavioral and neurobiological differences before drug experience that predict SUD and relapse vulnerabilities. Here, we investigate how midbrain endocannabinoids regulate a brain pathway that is exclusively involved in driving cue-motivated behaviors of sign-tracking rats. This work contributes to our mechanistic understanding of individual vulnerabilities to cue-triggered natural reward seeking that have relevance for drug-motivated behaviors.
{"title":"Decreased Ventral Tegmental Area CB1R Signaling Reduces Sign Tracking and Shifts Cue–Outcome Dynamics in Rat Nucleus Accumbens","authors":"Sam Z. Bacharach, David A. Martin, Cassie A. Stapf, Fangmiao Sun, Yulong Li, J. Cheer, Donna J. Calu","doi":"10.1101/2022.07.22.501038","DOIUrl":"https://doi.org/10.1101/2022.07.22.501038","url":null,"abstract":"Sign-tracking (ST) rats show enhanced cue sensitivity before drug experience that predicts greater discrete cue-induced drug seeking compared with goal-tracking or intermediate rats. Cue-evoked dopamine in the nucleus accumbens (NAc) is a neurobiological signature of sign-tracking behaviors. Here, we examine a critical regulator of the dopamine system, endocannabinoids, which bind the cannabinoid receptor-1 (CB1R) in the ventral tegmental area (VTA) to control cue-evoked striatal dopamine levels. We use cell type-specific optogenetics, intra-VTA pharmacology, and fiber photometry to test the hypothesis that VTA CB1R receptor signaling regulates NAc dopamine levels to control sign tracking. We trained male and female rats in a Pavlovian lever autoshaping (PLA) task to determine their tracking groups before testing the effect of VTA → NAc dopamine inhibition. We found that this circuit is critical for mediating the vigor of the ST response. Upstream of this circuit, intra-VTA infusions of rimonabant, a CB1R inverse agonist, during PLA decrease lever and increase food cup approach in sign-trackers. Using fiber photometry to measure fluorescent signals from a dopamine sensor, GRABDA (AAV9-hSyn-DA2m), we tested the effects of intra-VTA rimonabant on NAc dopamine dynamics during autoshaping in female rats. We found that intra-VTA rimonabant decreased sign-tracking behaviors, which was associated with increases in NAc shell, but not core, dopamine levels during reward delivery [unconditioned stimulus (US)]. Our results suggest that CB1R signaling in the VTA influences the balance between the conditioned stimulus-evoked and US-evoked dopamine responses in the NAc shell and biases behavioral responding to cues in sign-tracking rats. SIGNIFICANCE STATEMENT Substance use disorder (SUD) is a chronically relapsing psychological disorder that affects a subset of individuals who engage in drug use. Recent research suggests that there are individual behavioral and neurobiological differences before drug experience that predict SUD and relapse vulnerabilities. Here, we investigate how midbrain endocannabinoids regulate a brain pathway that is exclusively involved in driving cue-motivated behaviors of sign-tracking rats. This work contributes to our mechanistic understanding of individual vulnerabilities to cue-triggered natural reward seeking that have relevance for drug-motivated behaviors.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"103 1","pages":"4684 - 4696"},"PeriodicalIF":0.0,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84869281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-08DOI: 10.1523/JNEUROSCI.twij.43.10.2023
{"title":"This Week in The Journal","authors":"","doi":"10.1523/JNEUROSCI.twij.43.10.2023","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.twij.43.10.2023","url":null,"abstract":"","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"19 1","pages":"1657 - 1657"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87781102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1101/2023.02.28.530443
T. Desbordes, Yair Lakretz, V. Chanoine, M. Oquab, J. Badier, A. Trébuchon, R. Carron, C. Bénar, S. Dehaene, J. King
A sentence is more than the sum of its words: its meaning depends on how they combine with one another. The brain mechanisms underlying such semantic composition remain poorly understood. To shed light on the neural vector code underlying semantic composition, we introduce two hypotheses: (1) the intrinsic dimensionality of the space of neural representations should increase as a sentence unfolds, paralleling the growing complexity of its semantic representation; and (2) this progressive integration should be reflected in ramping and sentence-final signals. To test these predictions, we designed a dataset of closely matched normal and jabberwocky sentences (composed of meaningless pseudo words) and displayed them to deep language models and to 11 human participants (5 men and 6 women) monitored with simultaneous MEG and intracranial EEG. In both deep language models and electrophysiological data, we found that representational dimensionality was higher for meaningful sentences than jabberwocky. Furthermore, multivariate decoding of normal versus jabberwocky confirmed three dynamic patterns: (1) a phasic pattern following each word, peaking in temporal and parietal areas; (2) a ramping pattern, characteristic of bilateral inferior and middle frontal gyri; and (3) a sentence-final pattern in left superior frontal gyrus and right orbitofrontal cortex. These results provide a first glimpse into the neural geometry of semantic integration and constrain the search for a neural code of linguistic composition. SIGNIFICANCE STATEMENT Starting from general linguistic concepts, we make two sets of predictions in neural signals evoked by reading multiword sentences. First, the intrinsic dimensionality of the representation should grow with additional meaningful words. Second, the neural dynamics should exhibit signatures of encoding, maintaining, and resolving semantic composition. We successfully validated these hypotheses in deep neural language models, artificial neural networks trained on text and performing very well on many natural language processing tasks. Then, using a unique combination of MEG and intracranial electrodes, we recorded high-resolution brain data from human participants while they read a controlled set of sentences. Time-resolved dimensionality analysis showed increasing dimensionality with meaning, and multivariate decoding allowed us to isolate the three dynamical patterns we had hypothesized.
{"title":"Dimensionality and Ramping: Signatures of Sentence Integration in the Dynamics of Brains and Deep Language Models","authors":"T. Desbordes, Yair Lakretz, V. Chanoine, M. Oquab, J. Badier, A. Trébuchon, R. Carron, C. Bénar, S. Dehaene, J. King","doi":"10.1101/2023.02.28.530443","DOIUrl":"https://doi.org/10.1101/2023.02.28.530443","url":null,"abstract":"A sentence is more than the sum of its words: its meaning depends on how they combine with one another. The brain mechanisms underlying such semantic composition remain poorly understood. To shed light on the neural vector code underlying semantic composition, we introduce two hypotheses: (1) the intrinsic dimensionality of the space of neural representations should increase as a sentence unfolds, paralleling the growing complexity of its semantic representation; and (2) this progressive integration should be reflected in ramping and sentence-final signals. To test these predictions, we designed a dataset of closely matched normal and jabberwocky sentences (composed of meaningless pseudo words) and displayed them to deep language models and to 11 human participants (5 men and 6 women) monitored with simultaneous MEG and intracranial EEG. In both deep language models and electrophysiological data, we found that representational dimensionality was higher for meaningful sentences than jabberwocky. Furthermore, multivariate decoding of normal versus jabberwocky confirmed three dynamic patterns: (1) a phasic pattern following each word, peaking in temporal and parietal areas; (2) a ramping pattern, characteristic of bilateral inferior and middle frontal gyri; and (3) a sentence-final pattern in left superior frontal gyrus and right orbitofrontal cortex. These results provide a first glimpse into the neural geometry of semantic integration and constrain the search for a neural code of linguistic composition. SIGNIFICANCE STATEMENT Starting from general linguistic concepts, we make two sets of predictions in neural signals evoked by reading multiword sentences. First, the intrinsic dimensionality of the representation should grow with additional meaningful words. Second, the neural dynamics should exhibit signatures of encoding, maintaining, and resolving semantic composition. We successfully validated these hypotheses in deep neural language models, artificial neural networks trained on text and performing very well on many natural language processing tasks. Then, using a unique combination of MEG and intracranial electrodes, we recorded high-resolution brain data from human participants while they read a controlled set of sentences. Time-resolved dimensionality analysis showed increasing dimensionality with meaning, and multivariate decoding allowed us to isolate the three dynamical patterns we had hypothesized.","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"11 1","pages":"5350 - 5364"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86010828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1523/JNEUROSCI.twij.43.9.2023
{"title":"This Week in The Journal","authors":"","doi":"10.1523/JNEUROSCI.twij.43.9.2023","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.twij.43.9.2023","url":null,"abstract":"","PeriodicalId":22786,"journal":{"name":"The Journal of Neuroscience","volume":"3 1","pages":"1455 - 1455"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74703717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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