Neuron

Animals exhibit behavior in the absence of external stimuli or explicit tasks. Is the initiation of such spontaneous behavior shaped by internal brain states in a predictable manner? If so, does it engage specific brain circuits independent of behavioral form? Here, we studied the initiation of uninstructed behaviors of head-fixed mice in two contexts: a virtual burrow and a running wheel. Across both contexts, mice spent most of the time in quiet wakefulness and spontaneously initiated bouts of egress (exiting the burrow), running, or grooming. We employed functional ultrasound imaging (fUS) to record whole-brain activity and to identify whether the initiation of spontaneous behavior could be predicted from hemodynamic signals. We first identified distinct hemodynamic patterns associated with each behavior and subsequently performed time-resolved decoding to predict behavioral transitions from fUS data. We found that whole-brain hemodynamic signals could decode spontaneous egress and running around 10 seconds before their onset, a timescale that cannot be accounted for by preceding behavioral changes alone. Furthermore, we found a network of regions, including the medial septum (MS), that decreased their signal several seconds before the onset of egress and running. Mimicking this decrease by inhibiting neurons in the MS via optogenetics increased the probability of egress, running, and grooming. Through this unbiased approach, our work sheds light on a whole-brain transition-prone state that precedes uninstructed behavior transitions.

The ventrolateral prefrontal cortex (vlPFC) is well known for its involvement in high-level functions such as cognitive control and language. However, vlPFCs role in visual processing is less clear. Here, we investigated how neuronal ensembles in the vlPFC dynamically encode different types of visual information. Using chronic recording of spiking activity, we investigated vlPFCs representational geometry in a macaque monkey passively viewing a large set of naturalistic images, and compared this to representations in deep neural networks (DNNs). We found that the vlPFC processes visual information in two stages. First, an "early" response from 50 to 90 ms after stimulus onset encodes the low spatial frequency component of an image. It contains sufficient information to form a coarse estimate of the position and category of a salient object. Then, from 100 ms on, the representational geometry changes and contains much richer information. This late period contains non-categorical information typically present in conscious experiences such as the orientation of a face and natural scenes in the background. The late window also enables sub-category identification, which is boosted by the low spatial category prior. These results suggest that the vlPFC has a dual role in natural vision: first forming fast low-spatial-frequency-based priors shaping feed-forward visual processing, and subsequently maintaining a detailed and rich representation of a visual scene. SignificanceWhat information does the prefrontal cortex represent during natural vision, and how does this relate to conscious experience? Theories of consciousness differ sharply on whether prefrontal activity reflects detailed perceptual content or only high-level, task-related information. Using dense neural recordings during passive viewing of thousands of naturalistic images, we show that the ventrolateral prefrontal cortex processes visual information in two distinct stages: an early, coarse estimate of the visual scene is followed by a richer, high-dimensional representation that includes sub-category identity and other perceptual details. These findings reveal that prefrontal circuits encode more of the content of visual experience than previously assumed, even in the absence of a task.

Cholinergic interneurons (CINs) in the nucleus accumbens (NAc) play a key role in regulating motivated behaviors. Here we examine the connectivity and functional impact of cortical and thalamic inputs onto CINs in the NAc core. We first use cell-type specific retrograde anatomy to identify the prefrontal cortex and thalamus as putative afferents. We then combine ex vivo slice physiology and optogenetics to characterize the properties of synapses onto CINs. We demonstrate that thalamic inputs strongly facilitate, whereas cortical inputs exhibit marked depression. We also show that a combination of AMPA and NMDA receptors contribute to both cortical and thalamic responses. Lastly, we establish how these inputs and receptors evoke action potentials and influence spontaneous firing. Our findings show how CINs in the NAc core process long-range inputs, highlighting differences from equivalent circuits in other parts of striatum. SIGNFICANCE STATEMENTCholinergic interneurons provide the primary source of acetylcholine in the striatum and are important for behavior and disease. The types of afferents that drive these interneurons have been examined in dorsal striatum but remain understudied in the nucleus accumbens. We found that inputs from prefrontal cortex and thalamus are the main drivers in the mouse nucleus accumbens core. We compare the sign, dynamics, and impact of these two excitatory inputs, showing how they engage multiple glutamate receptors to influence cholinergic interneuron firing.

Adaptive social behavior requires balancing self-interest with the welfare of others, a core axiom of social decision-making that determines whether actions are selfish or prosocial. Although the medial prefrontal cortex (mPFC) has been implicated in prosocial behavior, the broader cortical-subcortical networks that arbitrate between selfish and prosocial actions remain poorly understood. Moreover, most studies of social decision-making (at both the single-region and circuit levels) have focused on inbred C57BL/6 mice, leaving unclear whether similar neural mechanisms operate across genetically diverse populations. Here, we combined a social decision-making task with c-Fos mapping to examine activity across distributed cortical and subcortical regions in inbred C57BL/6 and outbred CD1 male mice during prosocial and selfish choices. We found that CD1 mice exhibited a stronger bias toward selfish behavior, whereas C57BL/6 mice were more prosocial. This behavioral divergence was associated with elevated c-Fos activity in the mPFC and nucleus accumbens core (NAcC) in CD1 mice compared with C57BL/6 mice, and mPFC activity positively correlated with selfish choice bias. At the network level, social decision-making selectively recruited coordinated activity among the distinct mPFC subregions, ventral tegmental area (VTA), and NAcC. Importantly, prosocial and selfish individuals recruited distinct prefrontal-subcortical network configurations during social decision-making. Together, these findings identify distributed cortical-subcortical network dynamics underlying social choice bias and reveal strain-dependent differences in the neural architecture supporting prosocial and selfish behavior. Significant statementSocial decisions require weighing personal benefit against the welfare of others, yet the neural circuits that bias individuals toward selfish versus prosocial choices remain poorly understood. Here, we show that two mouse strains with opposing social preferences recruit distinct cortical and subcortical network configurations during social choice, despite performing the same task. Rather than reflecting differences in single brain regions, social decision-making engaged coordinated activity across a prefrontal-striatal-midbrain circuit, with prosocial and selfish individuals recruiting different versions of this network. These findings reveal that social choice bias is encoded at the level of distributed circuit organization and that genetic background shapes how the brain implements social decisions.

Neuronal cell death is a hallmark of many neurodegenerative diseases. Effective detection and clearance of cell debris generated during cell death events is essential to prevent a degenerative cascade. Brain resident microglia are responsible for performing these functions through complex cell-cell signaling involving both "find-me" and "eat-me" cues. To examine microglial responses to neuronal cell death in vivo, we investigated neuron/microglia CX3CL1/CX3CR1 signaling using intravital optical imaging in mouse cortex and a single-cell ablation technique called 2Phatal. We find that CX3CL1 aggregates as puncta on microglia and that this pattern is maintained when microglia engulf dying neurons. Additionally, disruption of this signaling via Cx3cr1 deletion when both few and many neurons are dying leads to delayed cell corpse clearance, partly due to a delay in microglial engagement with the dying cells. Overall, our work uncovers a precise role for CX3CL1/CX3CR1 signaling in regulating the microglial response to dying neocortical neurons.

Primate neuroscience has traditionally studied the brain under highly constrained conditions, limiting our understanding of neural function during real-world behavior. The mid-superior temporal sulcus (mSTS) is implicated in social perception, but its role during unconstrained behavior has not been tested. Here we performed wireless depth-electrode recordings from both banks of mSTS in macaques freely exploring a large three-dimensional arena, combined with 3D pose tracking and behavioral segmentation. Neural encoding models revealed mSTS firing rates were jointly modulated by spatial position, body kinematics, and geometric visual proxies, preferentially encoded in allocentric coordinates but with a shift toward body-centric encoding during vertical exploration. Neural populations carried decodable information about discrete behavioral syllables, with broad temporal generalization and neural similarity that tracked the sequential structure of behavior. Population manifold analysis revealed that the same behavior occupied different regions of population space at different spatial locations, and population dynamics showed structured organization around behavioral transitions. Together, these results suggest that mSTS populations carry joint information about spatial context and behavioral state during natural behavior.

Internal states such as motivation and task engagement influence cognitive functions. Working memory, which maintains information over time, is an essential component of cognition and is modulated by motivation. Here, we show motivational states modulated attractor dynamics that supported working memory. Combining population recordings from mouse medial prefrontal cortex (mPFC) with data-constrained recurrent neural network (RNN) modeling, we found task engagement selectively modulated attractor dynamics within a memory-maintenance subspace, while stimulus-evoked responses remained intact. Reverse-engineering the RNNs revealed that task engagement reorganized the dynamical landscape by stabilizing memory-specific attractors. Specifically, task engagement modulated interactions between neurons to change the attractor dynamics. Finally, gradual changes in behavioral engagement were predicted by continuous modulation of attractor geometry in RNNs and mPFC. Together, these results suggest that internal state modulate working memory function by controlling the dynamical regime of mPFC circuits, providing a mechanistic link between internal state, neural dynamics, and cognitive function.

How does cortical connectivity support decision-making? Behavioral tasks often involve multiple sequential phases that implement different computations. For perceptual decision-making during navigation these can include evidence accumulation, decision commitment, and motor program read out. How are these different phases implemented in circuits with fixed anatomical synaptic connectivity? One potential contribution is that the connectivity of neurons is modulated in the different phases, but this has never been tested. Here we used an all-optical method to probe the causal connectivity of excitatory neurons in layer 2/3 of mouse retrosplenial cortex during different behavioral epochs of a navigation-based decision-making task, as well as in the absence of the task. In-task connectivity was different from no-task connectivity: furthermore, these differences were selective to the cue / decision phase, tapering off in later stages of the task. We propose that fast modulation of connectivity is a prevalent mechanism in neural circuit function.

Many stroke survivors with aphasia struggle to map their thoughts into words or motor plans. Neuroprostheses that decode concept representations could help these individuals communicate by predicting the words, phrases, or sentences that they are struggling to produce. Here we decoded concept representations measured using functional magnetic resonance imaging (fMRI) from participants with different aphasia profiles. The decoders generated continuous word sequences that could describe the concepts that the participants were hearing about, seeing, or imagining. To forecast how this approach would generalize across the heterogeneity of aphasia profiles, we characterized how stroke affects the anatomical organization and information capacity of conceptual processing. Mapping how concepts are organized across the brain, we found that conceptual tuning during non-linguistic processing was largely consistent between the participants with aphasia and neurologically healthy participants. Comparing information processing between the participants with aphasia and neurologically healthy participants, we found that both groups processed similar amounts of non-linguistic information. Our findings indicate that concept representations can be largely spared in individuals with aphasia and demonstrate how these representations can be decoded to support communication.

Transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (dlPFC) is an FDA-cleared treatment for depression, yet how cortical stimulation influences single neurons in deep brain circuits remains unknown. Using intracranial microelectrode recordings in four neurosurgical patients, we resolved single-neuron spikes as early as 8 ms from 185 single neurons after single-pulse left dlPFC TMS. TMS elicited time-locked firing responses in 46% of neurons across deep cortical and subcortical structures bilaterally. TMS facilitated putative interneuron spiking in striato-thalamic regions from [~]8 ms, peaking at [~]80-100 ms, and lasting to [~]1000 ms, while suppressing putative pyramidal cell spiking with a delayed and slower time course. Trial-by-trial single-neuron modulations were positively correlated with cortico-striato-thalamic network activity and anti-correlated with limbic network activity. These findings reveal that dlPFC TMS facilitates inhibitory firing in executive control networks while suppressing limbic excitatory drive, providing a cellular mechanism for how cortical stimulation modulates distributed brain networks.

Learning to navigate a changing environment requires the ability to detect when a reward no longer matches a previous expectation. While the hippocampus is essential for adapting behavior strategies when reward expectations are violated and is known to integrate goal-related information into spatial maps, the precise dynamics by which these maps update during an unexpected reduction in reward magnitude is not well understood. Using longitudinal calcium imaging of neuronal activity in behaving mice, we found that hippocampal CA1 population activity encodes reward magnitude through elevated event rates at high value locations. Within this population, we discovered a specialized group of reward tethered place cells that bind spatial context to reward magnitude. These reward tethered place cells exhibit spatial fields across the environment while simultaneously exhibiting activity anchored to high-value reward locations. Upon reward reduction, CA1 population activity equalizes and these neurons undergo a selective and rapid remapping that precedes behavioral adjustment to the reward downshift. The broader spatial map remains intact, indicating that this change allows the animal to update the value of a goal while preserving a stable representation of its surroundings. This selective reorganization of hippocampal firing patterns could support adaptive decision making by updating internal models of the world when expectations are violated. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC="FIGDIR/small/725501v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@1725be8org.highwire.dtl.DTLVardef@eff7c1org.highwire.dtl.DTLVardef@72d4b3org.highwire.dtl.DTLVardef@ea3e41_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract.C_FLOATNO Masala N., Donahue M., etal. C_FIG

Prefrontal-hippocampal communication, supported by both direct and indirect anatomical pathways, is essential for a range of cognitive functions, including spatial navigation. The midline thalamic nucleus reuniens (RE) has been proposed as a key hub along this indirect pathway, coordinating bidirectional interactions between the hippocampus (HC) and prefrontal cortex (PFC). Here, we investigated functional dynamics within the HC-RE-PFC network as adult male rats learned to navigate a complex maze. Initial behavioral analyses revealed three distinct learning phases: exploration, goal-oriented learning, and efficient navigation. Aligning neural data with subject-specific transitions between these phases uncovered distinct neural signatures associated with each learning phase. Notably, the transition from exploratory to goal-directed behavior was accompanied by the emergence of persistent HC-RE beta-band (15-25Hz) interactions, including elevated beta coherence, theta-beta phase-amplitude coupling, and HC-to-RE Granger causality. The interactions further scaled with navigational efficiency, showing increased HC-RE beta coherence in trials without errors. Together, these findings provide new evidence for dynamic HC-RE interactions during goal-directed navigation and support an emerging view that RE functions as a working memory buffer for route-related information, revealing a potential network mechanism underlying flexible spatial behavior. HighlightsO_LIBeta-band hippocampus-reuniens coupling emerges during goal-directed navigation. C_LIO_LIPAC between HC theta and RE beta increased during goal learning. C_LIO_LIHC-RE coupling strength increases with navigational efficiency. C_LIO_LIDirectional hippocampus-to-reuniens communication emerges during learning C_LIO_LIReuniens supports hippocampal-prefrontal integration for flexible behavior C_LI Significance StatementFlexible spatial navigation requires coordinated communication between the hippocampus (HC) and the prefrontal cortex (PFC), yet the thalamic mechanisms coordinating HC-PFC interaction remain poorly understood. This study reveals that the nucleus reuniens (RE) of the midline thalamus plays a critical role in mediating HC-PFC communication during spatial learning. By combining detailed behavioral analysis with simultaneous multi-site electrophysiological recording, we identify beta-band HC-RE coupling as a neural signature of the transition from exploration to goal-directed navigation. The strength and directionality of this interaction tracked improvements in navigational efficiency, revealing a thalamic mechanism for integrating hippocampal output into prefrontal circuits. These findings highlight the RE as a working memory buffer for route-related information and advance our understanding of how thalamic hubs contribute to the circuit-level dynamics underlying flexible behavior.

Hippocampal pyramidal neurons function as place cells, showing location-specific activity during navigation, to form an internal spatial map of the environment. They are hypothesized to be the neural substrate of episodic memory. However, place cell receptive fields tend to drift or have poor tuning in low demand tasks, lacking operant goals such as random foraging, or in sensory context-deprived environments. Through chronic two-photon calcium imaging of hippocampal area CA1, we directly compare stability in a low versus a high demand task within the same animals over the course of learning and recall in the same environment. We find that compared to random foraging, an odor-context based navigational task stabilizes place cell representations and increases place cell quality and quantity. To investigate the circuit mechanism that may support this stability, we manipulated the activity of lateral entorhinal cortex (LEC) excitatory neurons, which provide both indirect and direct multisensory inputs about context, odor, and time to CA1. We chemogenetically suppressed activity of excitatory neurons in LEC during recall of the odor-context based navigation task and found that context discrimination is impaired at both the behavioral and neural level. With LEC silencing, mice had lower behavioral performance, less stable population activity, and greater similarity between opposing trial types. Our study finds that increasing task demand increases CA1 stability and that this stability is partially supported by LEC.

Understanding how motor cortical circuits flexibly transform sensory and contextual information into behavior remains a central challenge. Whether neurons in primary vibrissal motor cortex (M1) multiplex across behaviors or are selectively engaged in context-specific actions is still unclear. To address this question, we trained mice on multiple vibrissal sensorimotor tasks, including a cue-triggered whisking-to-touch task and an air-puff-triggered licking task. Fast-spiking and regular-spiking neurons in layers 2/3 and 5 in vM1 responded robustly within [~]15 ms to air-puff stimulation. In contrast, these same neurons were only weakly modulated during goal-directed whisking-to-touch behavior. Unexpected air-puffs evoked responses in fewer neurons than expected stimuli. Trials in which stimulation elicited whisker movements produced smaller neural responses than trials without whisking. Stimulus-evoked activity in M1 was organized along a spectrum of response profiles with neurons exhibiting varying responses dynamics that cut across laminar and physiological distinctions. This organization of responses is consistent with context-dependent recruitment of M1 neurons. Together, these findings indicate that M1 activity is more closely associated with the selection of specific behavioral responses than with generalized sensory-motor encoding. SignificanceHow motor cortex links sensory input to behavior remains a central question in neuroscience. Do neurons that respond to vibrissal stimuli also participate in whisker-based behaviors, or do they reflect distinct functional states? Here, we show that activity in vM1 is context dependent. Across multiple behaviors, sensory inputs recruit different neuronal populations depending on behavioral context: air-puff stimuli evoke rapid and robust responses, whereas the same neurons are only weakly engaged during goal-directed whisking-to-touch. In addition, expected and unexpected stimuli activate partially distinct ensembles, and sensory responses are attenuated when stimuli directly trigger movement. These findings indicate that M1 does not uniformly encode sensory input; instead, activity reflects context-dependent action selection where neuronal populations are engaged according to behavioral demands.

The hippocampus and the prefrontal cortex interact across a range of cognitive functions, yet how these regions represent space and how these representations evolve across learning remains poorly understood. We recorded large-scale neural activity from the hippocampus (CA1) and the medial prefrontal cortex (mPFC) as rats acquired proficiency in radial maze tasks over weeks. We identified a form of trial-by-trial flickering in which one hippocampal place field gradually overtook the other across successive trials, whereas mPFC firing fields switched randomly. While hippocampal flickering decreased as the task was mastered, mPFC flickering remained random and persisted throughout learning. Population-level UMAP embeddings revealed that mPFC states transitioned smoothly across trials, with the within-session representational drift stabilizing only after a two-week period. These findings suggest that while the hippocampus stabilizes its spatial maps during learning, the mPFC maintains a flexible, flickering representation that facilitates the extraction of abstract task structure and the rapid adaptation required for behavioral flexibility.

From birth, human infants engage in multi-modal social exchanges with caregivers that involve the coordination of gaze and touch to guide attention and support neurodevelopment. However, little is known about the association between these first interactive experiences and the functional organization of the developing brain during the first postnatal month, a window of remarkable brain growth in humans. We address this gap by combining microanalytic coding of caregiver- infant interactions with task-free functional connectivity (FC), measured using high-density diffuse optical tomography (HD-DOT) in infants homes during the first postnatal month. Task-free FC measures the intrinsic functional organization of the developing brain, shedding light on the early development of neural systems supporting perception, regulation, and social interactions. Infants were assessed up to three times (1 week, 2 weeks, 1 month), enabling characterization of both early FC and its rapid developmental change. Caregiver-infant interactions were associated with both concurrent organization and rapid longitudinal change in FC. Dyadic engagement in the context of face-to-face interaction was associated with the refinement of short-range connectivity and the integration of long-range connectivity particularly between social brain regions, while affectionate touch was associated with general increases in long-distance connectivity. These results demonstrate that caregiving experiences influence the development of the brains functional architecture in the first postnatal month, highlighting a critical window for shaping infant brain function. Significance StatementThe first postnatal weeks are a period of rapid brain development, when the brain may be especially sensitive to experience. A key early experience is social interaction between infants and their caregivers, yet it remains unknown if these interactions influence neonate brain function. By combining observations of caregiver-infant interactions at one month with repeated home-based brain imaging, we show that variations in dyadic engagement and affectionate touch influence how infant brain functional connectivity is organized and develops. These findings highlight the importance of supporting perinatal life and early interactions for infant brain development.

Phenotype-driven forward screening offers a powerful strategy to discover neuronal substrates underlying physical and behavioral traits without prior anatomical or functional assumptions. Historically, such approaches have identified many important neuronal circuits using invertebrate model organisms, but application to mammals has remained limited by the lack of appropriate strategies. Here we quantitatively profiled 56 neurological phenotypic features across more than 200 adult mice when neurodevelopmentally classified neurons were activated or inhibited by chemogenetics. This screen yielded a wide spectrum of robust neurological phenotypes. Upon analyzing these phenotypes computationally, we narrowed down to the hypothesis that activation of cortical neurons enlarges pupil size. Experimental evidence using optogenetics and in utero electroporation indicated that this hypothesis is true. Our results provide proof of principle that phenotype-driven forward approach in mammals is a powerful alternative as a laboratory approach to uncover brain substrates, and offers a general framework for systematically mapping neural circuits that regulate physical and behavioral phenotypes.

Rule learning is associated with lasting changes in prefrontal activity. However, experiments typically focus on learning a single set of rules or task and there remains a significant gap regarding how related mechanisms may reflect behavioral improvements in different contexts, especially when examining across different tasks and modalities. We therefore recorded single units from chronic electrode arrays implanted in the prefrontal cortex of four monkeys as they were trained to perform spatial and object working memory tasks with the goal of assessing the resulting activity changes that would be induced by rule learning. Progression of training allowed behavioral improvements to be correlated with a variety of neural effects that could be observed across different task contexts, including increases or decreases of both firing rate and decoding, increases in the proportion of firing rate variance that was unexplained by sensory stimuli and motor actions, and the increased separation of population response trajectories in state space. Our results thus reveal how rule learning induces plasticity of prefrontal cortical activity, and the aspects of neural activity changes that were unique to individual tasks and modalities or common across them. Our results ultimately reveal new patterns of training effects, identifying the generalized prefrontal mechanisms that are responsible for rule learning.

Human interactions span a range of contexts, from cooperation to competition. Negotiation, in particular, is a complex and extended social process in which individuals must reach mutually acceptable decisions despite conflicting incentives. The neural computations that support strategic behavior in such social dilemmas remain insufficiently understood. Here, we combine cognitive computational modeling, electroencephalography (EEG), functional Magnetic Resonance Imaging (fMRI), and fMRI-guided Transcranial Magnetic Stimulation (TMS) to demonstrate that oscillatory activity anchored in the temporoparietal junction (TPJ) causally shifts social learning during strategic bargaining. We found that TPJ metabolic activity and alpha-band oscillations are associated with the use of a feedback-based learning strategy during bargaining. Causal perturbation with rhythmic alpha-frequency TMS selectively modulates this strategy, increasing endogenous alpha oscillations and shifting behavioral learning parameters. Together, these findings reveal a frequency-specific mechanism within the neural substrates of social cognition that implements adaptive social learning, offering insights into potential neuromodulatory targets for ameliorating social dysfunction in neuropsychiatric conditions. Significance StatementStrategic negotiation requires predicting how others will respond to our actions, yet the neural computations supporting this form of social learning have remained elusive. By integrating computational modeling with EEG, fMRI, and frequency-specific TMS, we identify a mechanistic link between alpha-band activity in the temporoparietal junction (TPJ) and feedback-based learning during social exchange. Trial-by-trial estimates of this learning strategy were tracked by TPJ metabolic and oscillatory signals, and rhythmic alpha TMS causally enhanced both the neural signature and the behavioral expression of this strategy. These findings provide causal evidence for a frequency-specific mechanism within the neural systems that supports adaptive social learning. They also highlight the TPJ-alpha system as a promising target for neuromodulatory interventions to improve social functioning in neuropsychiatric conditions. Key FindingsO_LIModel-based behavioral analyses revealed two distinct strategies during social negotiation: a feedback-based learning mechanism (U-strategy) and a reputation-based updating mechanism (A-strategy). C_LIO_LIBoth strategies robustly predicted participants adaptive behavior across samples and conditions, and their modulation accounted for differences in negotiation outcomes. C_LIO_LIEEG analyses revealed frequency-specific alpha and beta power modulation linked to U-strategy computations during partner anticipation, localized to right temporoparietal regions. C_LIO_LIfMRI analyses revealed that trial-by-trial U-strategy estimates selectively modulated BOLD activity within the temporoparietal network associated with mentalizing. C_LIO_LIRhythmic alpha-frequency TMS over individually localized Theory-of-Mind TPJ sites causally altered negotiation behavior, shifting U-learning parameters toward a more conservative strategy. C_LIO_LITMS-EEG analyses demonstrated that alpha-frequency TMS induced time-locked alpha activity in functionally connected frontal sites, consistent with enhanced anticipatory computations. C_LIO_LITogether, these multimodal findings establish a causal, frequency-specific mechanism in the TPJ that implements social value learning during strategic bargaining. C_LI

To understand human thought and behaviour, it is vital to understand how internal representations in mind interface with external sensations in the outside world. It is well-established that representations in working memory can involuntarily draw attention towards objects in the outside world with corresponding visual features. Here, we establish that this interface involves a two-way stream by demonstrating that external sensations also involuntarily draw attention to corresponding internal representations in working memory. We demonstrate this across four dedicated experiments in which an unpredictive external stimulus selectively colour-matched working-memory contents, while being completely irrelevant to the working-memory task. We provide converging evidence for this "externally driven internal attention" from tracking attentional dynamics over time through spatial biases in microsaccades as well as from memory performance. We further highlight that engagement with the external stimulus critically shapes the strength of this attentional capture from perception to memory. Together, our findings delineate the properties and consequences of this underexplored attentional pathway, opening novel avenues for research at the interface of perception and memory, and their disorders.