Journal of Neuroscience最新文献

{"title":"Synergistic Reinforcement Learning by Cooperation of the Cerebellum and Basal Ganglia.","authors":"Tatsumi Yoshida, Hikaru Sugino, Hinako Yamamoto, Sho Tanno, Mikihide Tamura, Jun Igarashi, Yoshikazu Isomura, Riichiro Hira","doi":"10.1523/JNEUROSCI.1464-24.2025","DOIUrl":"10.1523/JNEUROSCI.1464-24.2025","url":null,"abstract":"<p><p>The cerebral cortex, cerebellum, and basal ganglia are essential for flexible learning in mammals. Although traditionally thought to operate under different learning rules, recent evidence suggests that both the basal ganglia and the cerebellum may employ reinforcement learning mechanisms. This raises the question of how these structures coordinate when a common reward prediction error mechanism is active. To address this issue, we first examined output signals from the basal ganglia and cerebellum following the activity of the cerebral cortex. We recorded single-neuron activity from the output regions of the cerebellum and basal ganglia-the cerebellar nuclei (CN) and substantia nigra pars reticulata (SNr)-in both male and female ChR2 transgenic rats. Neurons in the CN and SNr exhibited distinct temporal response patterns; notably, the fast excitatory response in the CN, driven by mossy fiber input, was synchronized with the inhibitory response in the SNr, mediated via the direct pathway. Using these experimental findings together with connectome data, we developed both a semirealistic spiking network model and a reservoir-based reinforcement learning model. In the latter model, successful learning depended on synaptic plasticity in both the cerebellum and basal ganglia with a temporal precision on the order of 10 ms. Furthermore, cortical β-oscillations enhanced learning and optimal reinforcement learning occurred when the output of cerebellar and basal ganglia signal phase-locked at the frequency of cortical oscillation. Taken together, our results suggest that the coordinated output of the cerebellum and basal ganglia, driven by tightly tuned cortical input, underlies brain-wide synergistic reinforcement learning.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12139595/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144024217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcranial Focused Ultrasound Modulates Feedforward and Feedback Cortico-Thalamo-Cortical Pathways by Selectively Activating Excitatory Neurons.","authors":"Huan Gao, Sandhya Ramachandran, Kai Yu, Bin He","doi":"10.1523/JNEUROSCI.2218-24.2025","DOIUrl":"10.1523/JNEUROSCI.2218-24.2025","url":null,"abstract":"<p><p>Transcranial focused ultrasound stimulation (tFUS) is a promising neuromodulation technique capable of noninvasively modulating focal neuronal activities and neural circuits in both animals and humans. The cell-type selectivity of tFUS within targeted areas such as the somatosensory cortex (S1) during sonication has been shown to be parameter related. However, it remains unclear how tFUS affects neural circuits by changing the correlation between neurons and how to optimize the tFUS parameters to modulate neural pathways. In this study, multisite intracranial recordings are used in anesthetized male rats to quantify the neuronal responses to tFUS stimulation recorded from S1 and posterior medial thalamic nucleus (POm) of cortico-thalamo-cortical (CTC) pathway. Different tFUS parameters including ranges of pulse repetition frequencies (PRFs) and duty cycles (DCs) are tested. We find that when targeting at S1, only regular-spiking units (RSUs) respond to specific tFUS parameters during sonication (DC, 6-60%; PRF, 1,500, 3,000 and 4,500 Hz), and RSUs from the POm exhibit a synchronized response. The changes of directional correlation between S1 RSUs and POm RSUs indicate the activation of feedback modulation. Delayed responses and correlation changes were further observed at ∼200 ms postsonication from the neurons in S1 and POm, indicating feedforward modulation. Our results reveal that tFUS can modulate the feedback and feedforward CTC pathways by selectively activating cortical RSUs and adjusting the tFUS parameters, particularly the PRF, to maximize cortical RSU activity could enhance the modulation of the CTC pathway.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12139594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144024593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stimulus Repetition Induces a Two-Stage Learning Process in the Primary Visual Cortex.","authors":"Lihan Cui, Ke Bo, Changhao Xiong, Yujun Chen, Andreas Keil, Mingzhou Ding","doi":"10.1523/JNEUROSCI.1788-24.2025","DOIUrl":"10.1523/JNEUROSCI.1788-24.2025","url":null,"abstract":"<p><p>Repeated stimulus exposure alters the brain's response to the stimulus. Recording fMRI data from both men and women viewing 120 presentations of two Gabor patches (each Gabor repeating 60 times), we evaluated support for two prominent models of stimulus repetition, the fatigue model and the sharpening model. Our results uncovered a two-stage learning process in the primary visual cortex. In Stage 1, univariate BOLD activation in V1 decreased over the first 14 repetitions of the stimuli, replicating the well known effect of repetition suppression. Applying moving-window multivoxel pattern analysis decoding, we found that (1) the decoding accuracy between the two Gabors decreased from the above-chance level (∼60 to ∼70%) at the beginning of the stage to the chance level at the end of the stage (∼50%). This result, together with the accompanying weight map analysis, suggested that the learning dynamics in Stage 1 were consistent with the predictions of the fatigue model. In Stage 2, univariate BOLD activation for the remaining 46 repetitions of the two stimuli exhibited significant fluctuations but no systematic trend. The moving-window decoding accuracy between the two Gabor patches was at the chance level initially and became progressively higher as stimulus repetition continued, rising above and staying above the chance level starting at the ∼36th repetition. Thus, results from the second stage supported the notion that sustained and prolonged stimulus repetition prompts sharpened representations. Additional analyses addressed (1) whether the neural patterns within each learning stage remained stable and (2) whether new neural patterns were evoked in Stage 2 relative to Stage 1.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12139588/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Representational Organization of Static and Dynamic Visual Features in the Human Cortex.","authors":"Hamed Karimi, Jianxin Wang, Stefano Anzellotti","doi":"10.1523/JNEUROSCI.1164-24.2025","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.1164-24.2025","url":null,"abstract":"<p><p>Visual information consists of static and dynamic properties. How is their representation organized in the visual system? Static information has been associated with ventral temporal regions and dynamic information with lateral and dorsal regions. Investigating the representation of static and dynamic information is complicated by the correlation between static and dynamic information within continuous visual input. Here, we used two-stream deep convolutional neural networks (DCNNs) to separate static and dynamic features in quasi-naturalistic videos and to investigate their neural representations. One DCNN stream was trained to represent static features by recognizing action labels using individual video frames. The second DCNN stream was trained to encode dynamic features by recognizing actions from optic flow information that describes changes across different frames. To investigate the representation of these different types of features in the visual system, we used representational similarity analysis (RSA) to compare the neural network models to the neural responses in different visual pathways of 14 human participants (6 females). First, we found that both static and dynamic features are encoded across all visual pathways. Second, we found that distinct visual pathways represent overlapping as well as unique static and dynamic visual information. Finally, multivariate analysis revealed that ventral and dorsal visual pathways share a similar posterior-to-anterior gradient in the representation of static and dynamic visual features.<b>Significance statement</b> How does the human cortex represent static and dynamic visual features? Investigating the representation of static and dynamic information in realistic stimuli is difficult: separating static and dynamic features requires specially designed artificial stimuli. We tackled this challenge by using neural networks and investigated separately the representation of static and dynamic information in quasi-naturalistic videos. Our results challenge the common belief that associates static features with the ventral visual pathway and dynamic features with the dorsal pathway. We found that different visual pathways represent unique as well as overlapping static and dynamic features. We also identified a gradient in the representational pattern of static and dynamic visual features from posterior to anterior regions, spanning both ventral and dorsal visual pathways.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robustness of working memory to prefrontal cortex microstimulation.","authors":"Joana Soldado-Magraner, Yuki Minai, Byron M Yu, Matthew A Smith","doi":"10.1523/JNEUROSCI.2197-24.2025","DOIUrl":"10.1523/JNEUROSCI.2197-24.2025","url":null,"abstract":"<p><p>Delay period activity in the dorso-lateral prefrontal cortex (dlPFC) has been linked to the maintenance and control of sensory information in working memory. The stability of working memory related signals found in such delay period activity is believed to support robust memory-guided behavior during sensory perturbations, such as distractors. Here, we directly probed dlPFC's delay period activity with a diverse set of activity perturbations, and measured their consequences on neural activity and behavior. We applied patterned microstimulation to the dlPFC of two male rhesus macaques implanted with multi-electrode arrays by electrically stimulating different electrodes in the array while they performed a memory-guided saccade task. We found that the microstimulation perturbations affected spatial working memory-related signals in individual dlPFC neurons. However, task performance remained largely unaffected. These apparently contradictory observations could be understood by examining different dimensions of the dlPFC population activity. In dimensions where working memory related signals naturally evolved over time, microstimulation impacted neural activity. In contrast, in dimensions containing working memory related signals that were stable over time, microstimulation minimally impacted neural activity. This dissociation could explain how working memory-related information may be stably maintained in dlPFC despite the activity changes induced by microstimulation. Thus, working memory processes are robust to a variety of activity perturbations in the dlPFC.<b>Significance statement</b> Memory-guided behavior is remarkably robust to sensory perturbations, such as distractors. The dorso-lateral prefrontal cortex (dlPFC) is believed to underlie this robustness, given that it stably maintains working memory-related information in the presence of distractors. Here, we sought to understand the extent to which dlPFC circuits can robustly maintain working memory information during memory-guided behavior. We found that behavior was robust to electrical microstimulation perturbations in dlPFC, and that working memory signals were stably maintained in dlPFC despite widespread changes in the neural activity caused by the perturbations. Our findings indicate that working memory is robust to direct activity perturbations in the dlPFC, an ability that may be due to the processes that mediate similar robustness in the face of distractors.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144188408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural Distinction Between Visual Word and Object Recognition: An fMRI Study Using Pictographs.","authors":"Jiahong Zeng, Yudan Luo, Xiangqi Luo, Saiyi Jiao, Ke Wang, Zhenjiang Cui, Chunyu Zhao, Zhiyun Dai, Yuxin Liu, Yidong Jiang, Zaizhu Han","doi":"10.1523/JNEUROSCI.2322-24.2025","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.2322-24.2025","url":null,"abstract":"<p><p>It remains an open question in visual neuroscience whether the recognition of written words and visual objects engages distinct neural mechanisms intrinsically, unaffected by confounding factors such as stimulus properties and task demands, and if so, where these differences are localized. Previous studies comparing these two processes have faced challenges in simultaneously controlling stimulus properties, including low-level visual features and high-level phonological and semantic attributes, as well as task demands. Here, we addressed these issues using Chinese pictographs, visually identical stimuli that can be interpreted either as words (lexical symbols) or as objects (visual depictions), and that were rigorously matched in visual form, phonology, and semantics. During fMRI, 36 male and female human participants performed three language tasks (realness judgment, sound retrieval, and meaning judgment) on pictographs that were contextually recognized as words or objects, with each task applied to both recognition types under identical procedures. Results revealed robust word-object differences in the inferior parietal lobule (IPL), anterior cingulate cortex (ACC), and their associated networks. Compared to object recognition, word recognition elicited stronger activation in the IPL and reduced deactivation in the ACC. Furthermore, both regions exhibited distinct multivoxel activation patterns between the word and object recognition, and showed stronger functional connectivity with other brain regions specifically during word recognition. This study provides well-controlled evidence for intrinsic neural dissociations between word and object recognition, highlighting a parietal-cingulate network as a core substrate differentiating these processes.<b>Significance statement</b> Understanding how the brain distinguishes written words from visual objects is fundamental to reading and visual cognition. However, previous studies have struggled to separate intrinsic neural differences from confounding factors like visual appearance, phonological and semantic content, and task demands. Using a novel design based on Chinese pictographs, visually identical stimuli interpretable as either words or objects, this study eliminates these confounds, enabling direct comparison under identical task. fMRI results reveal robust differences in activation, multivariate pattern, and connectivity, highlighting the inferior parietal lobule, anterior cingulate cortex, and their associated networks as key neural substrates. These findings offer well-controlled evidence for intrinsic neural differences between word and object recognition, with implications for reading research, literacy education, and disorders like dyslexia.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144188407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single Neuron Contributions to the Auditory Brainstem EEG.","authors":"Paula T Kuokkanen, Ira Kraemer, Christine Köppl, Catherine E Carr, Richard Kempter","doi":"10.1523/JNEUROSCI.1139-24.2025","DOIUrl":"10.1523/JNEUROSCI.1139-24.2025","url":null,"abstract":"<p><p>The auditory brainstem response (ABR) is an acoustically evoked EEG potential that is an important diagnostic tool for hearing loss, especially in newborns. The ABR originates from the response sequence of auditory nerve and brainstem nuclei, and a click-evoked ABR typically shows three positive peaks (\"waves\") within the first six milliseconds. However, an assignment of the waves of the ABR to specific sources is difficult, and a quantification of contributions to the ABR waves is not available. Here, we exploit the large size and physical separation of the barn owl first-order cochlear nucleus magnocellularis (NM) to estimate single-cell contributions to the ABR. We simultaneously recorded NM neurons' spikes and the EEG in owls of both sexes, and found that [Formula: see text] spontaneous single-cell spikes are necessary to isolate a significant spike-triggered average (STA) response at the EEG electrode. An average single-neuron contribution to the ABR was predicted by convolving the STA with the cell's peri-stimulus time histogram. Amplitudes of predicted contributions of single NM cells typically reached 32.9 ± 1.1 nV (mean ± SE, range: 2.5-162.7 nV), or [Formula: see text] (median ± SE; range from 0.01% to 1%) of the ABR amplitude. The time of the predicted peak coincided best with the peak of the ABR wave II, independent of the click sound level. Our results suggest that individual neurons' contributions to an EEG can vary widely, and that wave II of the ABR is shaped by NM units.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121712/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multimodal MEG and Microstructure-MRI Investigations of the Human Hippocampal Scene Network.","authors":"Marie-Lucie Read, Carl J Hodgetts, Andrew D Lawrence, C John Evans, Krish D Singh, Katja Umla-Runge, Kim S Graham","doi":"10.1523/JNEUROSCI.1700-24.2025","DOIUrl":"10.1523/JNEUROSCI.1700-24.2025","url":null,"abstract":"<p><p>Although several studies have demonstrated that perceptual discrimination of complex scenes relies on an extended hippocampal posteromedial system, we currently have limited insight into the specific functional and structural properties of this system in humans. Here, combining electrophysiological (magnetoencephalography) and advanced microstructural (multishell diffusion magnetic resonance imaging; quantitative magnetization transfer) imaging in healthy human adults (30 females/10 males), we show that both theta power modulation of the hippocampus and fiber restriction/hindrance (reflecting axon packing/myelination) of the fornix (a major input/output pathway of the hippocampus) were independently related to scene, but not face, perceptual discrimination accuracy. Conversely, microstructural features of the inferior longitudinal fasciculus (a long-range occipitoanterotemporal tract) correlated with face, but not scene, perceptual discrimination accuracy. Our results provide new mechanistic insight into the neurocognitive systems underpinning complex scene discrimination, providing novel support for the idea of multiple processing streams within the human medial temporal lobe.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121706/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144013012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decomposing Cognitive Processes in the mPFC during Self-Thinking.","authors":"Marie Levorsen, Ryuta Aoki, Constantine Sedikides, Keise Izuma","doi":"10.1523/JNEUROSCI.2378-24.2025","DOIUrl":"10.1523/JNEUROSCI.2378-24.2025","url":null,"abstract":"<p><p>Past cognitive neuroscience research has demonstrated that thinking about both the self and other activates the medial prefrontal cortex (mPFC), a central hub of the default mode network. The mPFC is also implicated in other cognitive processes, such as introspection and autobiographical memory, rendering elusive its exact role during thinking about the self. Specifically, it is unclear whether the same cognitive process explains the common mPFC involvement or distinct processes are responsible for the mPFC activation overlap. In this preregistered functional magnetic resonance imaging study with 35 male and female human participants, we investigated whether and to what extent mPFC activation patterns during self-reference judgment could be explained by activation patterns during the tasks of other-reference judgment, introspection, and autobiographical memory. Multivoxel pattern analysis showed that only in the mPFC were neural responses both concurrently different and similar across tasks. Furthermore, multiple regression and variance partitioning analyses indicated that each task (i.e., other-reference, introspection, and memory) uniquely and jointly explained significant variances in mPFC activation during self-reference. These findings suggest that the self-reference task engages multiple cognitive processes shared with other tasks, with the mPFC serving as a crucial hub where essential information is integrated to support judgments based on internally constructed representations.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144006210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Neural Development of Social Interaction Perception in the Superior Temporal Sulcus.","authors":"Waldir M Sampaio","doi":"10.1523/JNEUROSCI.0253-25.2025","DOIUrl":"10.1523/JNEUROSCI.0253-25.2025","url":null,"abstract":"","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":"45 22","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121699/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144175611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}