Journal of Neuroscience最新文献

{"title":"Decoding the Neural Dynamics of Headed Syntactic Structure Building.","authors":"Junyuan Zhao 赵隽元, Ruimin Gao 高睿敏, Jonathan R Brennan","doi":"10.1523/JNEUROSCI.2126-24.2025","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.2126-24.2025","url":null,"abstract":"<p><p>The brain builds hierarchical phrases during language comprehension; however, the representational details and dynamics of the phrase-building process remain underspecified. This study directly probes whether the neural code of verb phrases involves reactivating the syntactic property of a key subcomponent (the \"head\" verb). To this end, we train a part-of-speech sliding-window neural decoder (verb vs. adverb) on EEG signals recorded while 30 participants (17 females) read sentences in a controlled experiment. The decoder reaches above-chance performance that is spatiotemporally consistent and generalizes to unseen data across sentence positions. Appling the decoder to held-out data yields predicted activation levels for the verbal \"head\" of a verb phrase at a distant non-head word (adverb); the critical adverb appeared either at the end of a verb phrase or at a sequentially and lexically matched position with no verb phrase boundary. There is stronger verb activation beginning at ∼600 milliseconds at the critical adverb when it appears at a verb phrase boundary; this effect is not modulated by the strength of conceptual association between the two subcomponents in the verb phrase nor does it reflect word predictability. Time-locked analyses additionally reveal a negativity waveform component and increased beta-delta inter-trial phase coherence, both previously linked to linguistic composition, in a similar time window. With a novel application of neural decoding, our findings delineate the dynamics by which the brain encodes phrasal representations by, in part, reactivating the representation of key subcomponents. We thus establish a link between cognitive accounts of phrasal representations and electrophysiological dynamics.<b>Significance Statement</b> Neuroimaging studies suggest that the brain constructs hierarchical linguistic representations. However, current evidence does not specify the details of minimal hierarchical units, namely phrases. On the other hand, theoretical consensus postulates phrases represented with properties derived from a key subcomponent, so-called the \"head\". Here, we explore the neural code of headed phrases. Leveraging advances in neural decoding, this study introduces a training-prediction pipeline to probe the activation dynamics of the phrasal head in electrophysiological recordings. Our analysis provides novel evidence regarding the neural representation of phrases that, at phrasal boundaries, the head of a phrase is reactivated and integrated into the higher-level representation. This is a fundamental step to understanding the neural bases of language comprehension at the sentence level.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574418","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":"A shared threat-anticipation circuit is dynamically engaged at different moments by certain and uncertain threat.","authors":"Brian R Cornwell, Paige R Didier, Shannon E Grogans, Allegra S Anderson, Samiha Islam, Hyung Cho Kim, Manuel Kuhn, Rachael M Tillman, Juyoen Hur, Zachary S Scott, Andrew S Fox, Kathryn A DeYoung, Jason F Smith, Alexander J Shackman","doi":"10.1523/JNEUROSCI.2113-24.2025","DOIUrl":"10.1523/JNEUROSCI.2113-24.2025","url":null,"abstract":"<p><p>Temporal dynamics play a central role in models of emotion: <i>\"fear\"</i> is widely conceptualized as a phasic response to certain-and-imminent danger, whereas <i>\"anxiety\"</i> is a sustained response to uncertain-or-distal harm. Yet the underlying neurobiology remains contentious. Leveraging a translationally relevant fMRI paradigm and theory-driven modeling approach in 220 adult humans, we demonstrate that certain- and uncertain-threat anticipation recruit a shared circuit that encompasses the central extended amygdala (EAc), periaqueductal gray, midcingulate, and anterior insula. This circuit exhibits persistently elevated activation when threat is uncertain and distal, and transient bursts of activation just before certain encounters with threat. Although there is agreement that the EAc plays a critical role in orchestrating responses to threat, confusion persists about the respective contributions of its major subdivisions, the bed nucleus of the stria terminalis (BST) and central nucleus of the amygdala (Ce). Here we used anatomical regions-of-interest to demonstrate that the BST and Ce exhibit statistically indistinguishable threat dynamics. Both regions exhibited activation dynamics that run counter to popular models, with the Ce showing sustained responses to uncertain-and-distal threat and the BST showing phasic responses to certain-and-imminent threat. For many scientists, feelings are the hallmark of fear and anxiety. Here we used an independently validated multivoxel brain 'signature' to covertly probe the moment-by-moment dynamics of anticipatory distress for the first time. Results mirrored the dynamics of neural activation. These observations provide fresh insights into the neurobiology of threat-elicited emotions and set the stage for more ambitious clinical and mechanistic research.<b>Significance statement</b> <i>\"Fear\"</i> is widely viewed as a phasic response to certain-and-imminent danger, whereas <i>\"anxiety\"</i> is a sustained response to uncertain-or-distal harm. Prior work has begun to reveal the neural systems recruited by certain and uncertain anticipated threats, but has yet to rigorously plumb the moment-by-moment dynamics anticipated by theory. Here we used a novel combination of neuroimaging techniques to demonstrate that certain and uncertain threat recruit a common threat-anticipation circuit. Activity in this circuit and covert measures of distress showed similar patterns of context-dependent dynamics, exhibiting persistent increases when anticipating uncertain-threat encounters and transient surges just before certain encounters. These observations provide fresh insights into the neurobiology of fear and anxiety, laying the groundwork for more ambitious clinical and mechanistic research.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574411","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":"Hippocampal neural stem cell exosomes promote brain resilience against the impact of tau oligomers.","authors":"Balaji Krishnan, Michela Marcatti, Anna Fracassi, Wen-Ru Zhang, Jutatip Guptarak, Kathia Johnson, Auston Grant, Rakez Kayed, Giulio Taglialatela, Maria-Adelaide Micci","doi":"10.1523/JNEUROSCI.1664-24.2025","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.1664-24.2025","url":null,"abstract":"<p><p>A promising therapeutic intervention for preventing the onset and progression of Alzheimer's Disease (AD) is to protect and improve synaptic resilience, a well-established early vulnerability associated with the toxic effects of oligomers of Aβ (AβO) and Tau (TauO). We have previously reported that exosomes from hippocampal neural stem cells (NSCs) protect synapses against AβO. Here, we demonstrate how exosomes can also shield against TauO toxicity in adult mice synapses, potentially benefiting primary and secondary tauopathies. Exosomes from hippocampal NSCs (NSCexo) or mature neurons (MNexo) were delivered intracerebroventricularly to adult wildtype male mice (C57Bl6/J). After 24 hours, TauO were administered to suppress long-term potentiation (LTP) and memory, measured by electrophysiology and contextual memory deficits measured using novel object recognition (NOR) test. We also assessed TauO binding to synapses using isolated synaptosomes and cultured hippocampal neurons. Furthermore, mimics of select miRNAs present in NSCexo, were delivered ICV to mice prior to assessment of TauO-induced suppression of hippocampal LTP. Our results showed that NSC-, not MN-, derived exosomes, prevented TauO-induced memory impairment, LTP suppression, and reduced Tau accumulation and TauO internalization in synaptosomes. These findings suggest that NSC-derived exosomes can protect against synaptic dysfunction and memory deficits induced by both AβO and TauO, offering a novel therapeutic strategy for multiple neurodegenerative states.<b>Significance Statement</b> NSCexo provide an unprecedented therapeutic strategy targeting an early vulnerability driven by amyloidogenic toxic oligomers associated with multiple neurodegenerative states.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574477","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":"Visual statistical learning alters low-dimensional cortical architecture.","authors":"Keanna Rowchan, Daniel J Gale, Qasem Nick, Jason P Gallivan, Jeffrey D Wammes","doi":"10.1523/JNEUROSCI.1932-24.2025","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.1932-24.2025","url":null,"abstract":"<p><p>Our brains are in a constant state of generating predictions, implicitly extracting environmental regularities to support later cognition and behavior, a process known as statistical learning (SL). While prior work investigating the neural basis of SL has focused on the activity of single brain regions in isolation, much less is known about how distributed brain areas coordinate their activity to support such learning. Using fMRI and a classic visual SL task, we investigated changes in whole-brain functional architecture as human female and male participants implicitly learned to associate pairs of images, and later, when predictions generated from learning were violated. By projecting individuals' patterns of cortical and subcortical functional connectivity onto a low-dimensional manifold space, we found that SL was associated with changes along a single neural dimension describing covariance across the visual-parietal and perirhinal cortex (PRC). During learning, we found regions within the visual cortex expanded along this dimension, reflecting their decreased communication with other networks, whereas regions within the dorsal attention network (DAN) contracted, reflecting their increased connectivity with higher-order cortex. Notably, when SL was interrupted, we found the PRC and entorhinal cortex, which did not initially show learning-related effects, now contracted along this dimension, reflecting their increased connectivity with the default mode and DAN, and decreased covariance with visual cortex. While prior research has linked SL to either broad cortical or medial temporal lobe changes, our findings suggest an integrative view, whereby cortical regions reorganize during association formation, while medial temporal lobe regions respond to their violation.<b>Significance statement</b> The current work is the first to investigate changes in whole-brain manifold architecture that underlie visual statistical learning (SL). We found that areas of the visual cortex and dorsal attention network showed significant connectivity changes during learning, reflecting their decreased, and increased covariance with other networks, respectively. Notably, when SL was later disrupted, regions within the medial temporal lobe, which had shown no evidence of initial learning, now began to increase connectivity with higher-order cortex. Together, these findings not only reveal the widespread neural interactions that underlie visual SL, but also extend prior work, suggesting separable cortical and medial temporal lobe contributions for the encoding versus violation of learned associations.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574489","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":"Novel verbal instructions recruit abstract neural patterns of time-variable information dimensionality.","authors":"Paula Pena, Ana F Palenciano, Carlos González-García, María Ruz","doi":"10.1523/JNEUROSCI.1964-24.2025","DOIUrl":"https://doi.org/10.1523/JNEUROSCI.1964-24.2025","url":null,"abstract":"<p><p>Human performance is endowed by neural representations of information that is relevant for behavior, some of which are also activated in a preparatory fashion to optimize later execution. Most studies to date have focused on highly practiced actions, leaving largely unaddressed the novel re-configuration of information to generate unique whole task-sets. Using electroencephalography (EEG), this study investigated the dynamics of the content and geometry reflected on the neural patterns of control representations during re-configuration of information. We designed a verbal instruction paradigm where each trial involved novel combinations of multi-component task information. By manipulating three task-relevant factors in a sample of 40 participants (26 females, 14 males), we observed complex coding schemes throughout the trial, during both preparation and implementation stages. The temporal profiles were consistent with a hierarchical structure: whereas task information was active in a sustained manner, the coding of more concrete stimulus features was more transient. Data showed both high dimensionality and abstraction, particularly during instruction encoding and target processing. Our results suggest that whenever task content could be recovered from neural patterns of activity, there was evidence of abstract coding, with an underlying geometry that favored generalization. During target processing, where potential interference across stimulus and response factors increased, orthogonal configurations also appeared. Overall, our findings uncover the dynamic manner with which control representations operate during novel recombination unique scenarios, with changes in dimensionality and abstraction adjusting along processing stages.<b>Significance Statement</b> The neural mechanisms that support task performance in novel contexts have been largely overlooked. Cognitive control is thought to enable complex behavior through the active maintenance of task sets, containing essential information for execution. However, how novel whole combinations of information are organized in neural patterns and their temporal dependencies remain unknown. Here, using a novel complex instruction paradigm, we observed that coding of informational content and its underlying geometry followed a dynamic temporal pattern. Our results reveal varying dimensionality and abstraction throughout the trial, with neural codes generally structured in a geometry favoring generalization of relevant information across task demands. These findings provide a first glimpse into the temporal computations engaged by the brain when encountering novel recombination settings.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143574462","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":"Choice Behaviors and Prefrontal-Hippocampal Coupling Are Disrupted in a Rat Model of Fetal Alcohol Spectrum Disorders.","authors":"Hailey L Rosenblum, SuHyeong Kim, John J Stout, Anna Y Klintsova, Amy L Griffin","doi":"10.1523/JNEUROSCI.1241-24.2025","DOIUrl":"10.1523/JNEUROSCI.1241-24.2025","url":null,"abstract":"<p><p>Fetal alcohol spectrum disorders (FASDs) are characterized by a range of physical, cognitive, and behavioral impairments. Determining how temporally specific alcohol exposure (AE) affects neural circuits is crucial to understanding the FASD phenotype. Third trimester AE can be modeled in rats by administering alcohol during the first two postnatal weeks, which damages the medial prefrontal cortex (mPFC) and hippocampus (HPC), structures whose functional interactions are required for working memory and executive function. Therefore, we hypothesized that AE during this period would impair working memory, disrupt choice behaviors, and alter mPFC-HPC oscillatory synchrony. To test this hypothesis, we recorded local field potentials from the mPFC and dorsal HPC as male and female AE and sham-intubated (SI) rats performed a spatial working memory task in adulthood and implemented algorithms to detect vicarious trial and errors (VTEs), behaviors associated with deliberative decision-making. We found that, compared with the SI group, the AE group performed fewer VTEs and demonstrated a disturbed relationship between VTEs and choice outcomes, while spatial working memory was unimpaired. This behavioral disruption was accompanied by alterations to mPFC and HPC oscillatory activity in the theta and beta bands, respectively, and a reduced prevalence of mPFC-HPC synchronous events. When trained on multiple behavioral variables, a machine learning algorithm could accurately predict whether rats were in the AE or SI group, thus characterizing a potential phenotype following third trimester AE. Together, these findings indicate that third trimester AE disrupts mPFC-HPC oscillatory interactions and choice behaviors.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11884398/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143124052","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":"Network Mechanisms Underlying the Regional Diversity of Variance and Time Scales of the Brain's Spontaneous Activity Fluctuations.","authors":"Adrián Ponce-Alvarez","doi":"10.1523/JNEUROSCI.1699-24.2024","DOIUrl":"10.1523/JNEUROSCI.1699-24.2024","url":null,"abstract":"<p><p>The brain's activity fluctuations have different temporal scales across the brain regions, with associative regions displaying slower timescales than sensory areas. This hierarchy of timescales has been shown to correlate with both structural brain connectivity and intrinsic regional properties. Here, using publicly available human resting-state fMRI and dMRI data, it was found that, while more structurally connected brain regions presented activity fluctuations with longer timescales, their activity fluctuations presented lower variance. The opposite relationships between the structural connectivity and the variance and temporal scales of resting-state fluctuations, respectively, were not trivially explained by simple network propagation principles. To understand these structure-function relationships, two commonly used whole-brain models were studied, namely, the Hopf and Wilson-Cowan models. These models use the brain's connectome to couple local nodes (representing brain regions) displaying noise-driven oscillations. The models show that the variance and temporal scales of activity fluctuations can oppositely relate to connectivity within specific parameter regions, even when all nodes have the same intrinsic dynamics-but also when intrinsic dynamics are constrained by the myelinization-related macroscopic gradient. These results show that, setting aside intrinsic regional differences, connectivity and network state are sufficient to explain the regional differences in fluctuations' scales. State dependence supports the vision that structure-function relationships can serve as biomarkers of altered brain states. Finally, the results indicate that the hierarchies of timescales and variances reflect a balance between stability and responsivity, with greater and faster responsiveness at the network periphery, while the network core ensures overall system robustness.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11884397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143025507","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":"Neural Correlates of Perceptual Plasticity in the Auditory Midbrain and Thalamus.","authors":"Rose Ying, Daniel J Stolzberg, Melissa L Caras","doi":"10.1523/JNEUROSCI.0691-24.2024","DOIUrl":"10.1523/JNEUROSCI.0691-24.2024","url":null,"abstract":"<p><p>Hearing is an active process in which listeners must detect and identify sounds, segregate and discriminate stimulus features, and extract their behavioral relevance. Adaptive changes in sound detection can emerge rapidly, during sudden shifts in acoustic or environmental context, or more slowly as a result of practice. Although we know that context- and learning-dependent changes in the sensitivity of auditory cortical (ACX) neurons support many aspects of perceptual plasticity, the contribution of subcortical auditory regions to this process is less understood. Here, we recorded single- and multiunit activity from the central nucleus of the inferior colliculus (ICC) and the ventral subdivision of the medial geniculate nucleus (MGV) of male and female Mongolian gerbils under two different behavioral contexts: as animals performed an amplitude modulation (AM) detection task and as they were passively exposed to AM sounds. Using a signal detection framework to estimate neurometric sensitivity, we found that neural thresholds in both regions improve during task performance, and this improvement is largely driven by changes in the firing rate rather than phase locking. We also found that ICC and MGV neurometric thresholds improve as animals learn to detect small AM depths during a multiday perceptual training paradigm. Finally, we revealed that in the MGV, but not the ICC, context-dependent enhancements in AM sensitivity grow stronger during perceptual training, mirroring prior observations in the ACX. Together, our results suggest that the auditory midbrain and thalamus contribute to changes in sound processing and perception over rapid and slow timescales.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11884394/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142928130","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":"Reduced Neural Responses to Natural Foreground versus Background Sounds in the Auditory Cortex.","authors":"Gregory R Hamersky, Luke A Shaheen, Mateo López Espejo, Jereme C Wingert, Stephen V David","doi":"10.1523/JNEUROSCI.0121-24.2024","DOIUrl":"10.1523/JNEUROSCI.0121-24.2024","url":null,"abstract":"<p><p>In everyday hearing, listeners face the challenge of understanding behaviorally relevant foreground stimuli (speech, vocalizations) in complex backgrounds (environmental, mechanical noise). Prior studies have shown that high-order areas of human auditory cortex (AC) preattentively form an enhanced representation of foreground stimuli in the presence of background noise. This enhancement requires identifying and grouping the features that comprise the background so they can be removed from the foreground representation. To study the cortical computations supporting this process, we recorded single-unit activity in AC of male and female ferrets during the presentation of concurrent natural sounds from these two categories. In contrast to expectations from studies in high-order AC, single-unit responses to foreground sounds were strongly reduced relative to the paired background in primary and secondary AC. The degree of reduction could not be explained by a neuron's preference for the foreground or background stimulus in isolation but could be partially explained by spectrotemporal statistics that distinguish foreground and background categories. Responses to synthesized sounds with statistics either matched or randomized relative to natural sounds showed progressively decreased reduction of foreground responses as natural sound statistics were removed. These results challenge the expectation that cortical foreground representations emerge directly from a mixed representation in the auditory periphery. Instead, they suggest the early AC maintains a robust representation of background noise. Strong background representations may produce a distributed code, facilitating selection of foreground signals from a relatively small subpopulation of AC neurons at later processing stages.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11884389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015316","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":"Noninvasive Brain Stimulation over the Frontopolar Cortex Promotes Willingness to Exert Cognitive Effort in a Foraging-Like Sequential Choice Task.","authors":"Mario Bogdanov, Laura A Bustamante, Sean Devine, Signy Sheldon, A Ross Otto","doi":"10.1523/JNEUROSCI.0647-24.2024","DOIUrl":"10.1523/JNEUROSCI.0647-24.2024","url":null,"abstract":"<p><p>Individuals avoid spending cognitive effort unless expected rewards offset the perceived costs. Recent work employing tasks that provide explicit information about demands and incentives suggests causal involvement of the frontopolar cortex (FPC) in effort-based decision-making. Using transcranial direct current stimulation (tDCS), we examined whether the FPC's role in motivating effort generalizes to sequential choice problems in which task demand and reward rates vary indirectly and as a function of experience. In a double-blind, within-subject design, 46 participants (36 female, 8 male, 1 \"neither/other\") received anodal (i.e., excitatory) or sham stimulation over the right FPC during an Effort Foraging Task, which required choosing between harvesting patches for successively decreasing resources or traveling to replenished patches by performing a cognitive task with environment-specific difficulty. As expected, participants exited patches later (i.e., exhibited lower exit thresholds) when traveling required greater (versus less) effort, indicating increased travel costs in high-effort environments. Under anodal tDCS, the difference in exit thresholds between environments was significantly smaller relative to sham. Finally, individual differences analyses hint that participants with lower self-reported motivation to exert effort exhibited greater travel cost reductions following tDCS. Together, these findings support the theorized causal role of the FPC in motivating cognitively effortful behavior, expand its role to more ecologically valid serial decisions, and highlight the potential for tDCS as a tool to increase motivation with potential clinical applications.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11884395/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015308","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}