Biology subjects

Leong, Y. C.

Publications and source records attributed to Leong, Y. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Individual Differences in Sustained Attention Tune Semantic Abstraction in Neural Encoding of Narratives

Neural encoding modeling for narrative comprehension -- using LLM embeddings to predict the temporal dynamics of neural activation -- is widely used to evaluate how well the brain represents certain semantic information. This approach, however, typically collapses semantic representation into a scalar fidelity score aggregated across participants, overlooking potentially rich individual differences and qualitative differences in naturalistic neural representations. In the current study, we addressed this gap by investigating how neural semantic encoding varies across individuals with sustained attention, and whether this difference is qualitative in addition to quantitative. Using fMRI data from 49 participants listening to an audiobook, Le Petit Prince, in English, we trained encoding models with GPT-2 embeddings at varying layers and forecasting lengths. Encoding models trained on high-level embeddings (from the 8th layer of GPT-2) showed significant brain-LLM alignment in 73 of 122 cortical and subcortical ROIs, concentrated in the temporal cortex and the default mode network. Functional connectivity strength in a validated connectome-based predictive model of sustained attention correlated with encoding performance in 18 ROIs, most strongly in the insula and in control and attention networks, with no ROI showing significant opposite relationship. Decomposing semantic information by levels of abstraction showed that the neural signature of sustained attention was selectively associated with a greater proportion of high-level gist information encoded in the frontoparietal and attention networks, while the opposite relationship emerged for proportion of low-level information. Sustained attention scores further predicted stronger predictive coding of upcoming narrative content across multiple networks across the whole brain (control, default mode, salience/ventral attention, limbic, and somatomotor networks). These findings suggest that sustained attention does not uniformly amplify neural semantic encoding, but instead shifts neural representations toward more compressed, gist-level formats that support anticipation of upcoming content. Individual differences in brain-LLM alignment can be a signature of representational strategy rather than noise, with potential utility for cognitive phenotyping.

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bioRxiv2026

Brain-to-brain synchrony during shared reminiscing predicts connection and memory in romantic couples

Romantic partners often revisit relationship-defining memories together, reconstructing a shared account of their relationship through conversation. Such shared reminiscing can strengthen interpersonal connection by fostering alignment in thoughts, feelings, and perspectives, an experience known as shared reality. Here, we used functional near-infrared spectroscopy to record brain activity simultaneously from romantic couples during naturalistic, face-to-face conversations. Couples first discussed an unresolved conflict and then jointly recounted their relationship origin story, including how they first met and how their relationship developed. Shared reality decreased following the conflict discussion and returned to baseline levels after the origin story. While recounting their origin story, partners exhibited synchronized activity in the right medial frontopolar cortex, a region implicated in autobiographical memory and reasoning about close others. This synchrony was not observed at rest or during the conflict discussion. Greater medial frontopolar synchrony between partners during the origin story discussion was associated with higher post-conversation shared reality, closeness, and relationship satisfaction, even after accounting for baseline relationship quality. It also predicted better subsequent memory for the conversation, an association that was robust to controlling for the importance and familiarity of the memories being discussed. Together, these findings reveal how the interbrain alignment that emerges during shared reminiscing tracks both the connection partners experience and what they later remember. Our work bridges relationship science and social neuroscience through the naturalistic neuroimaging of live social interaction, and offers a window into the neural processes that accompany mutual understanding, social connection, and sharing memories in romantic relationships.

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bioRxiv2026

A common connectome-based neural reference space across affective, autonomic, and wakefulness arousal

Arousal is often invoked to explain state-dependent variability in attention, emotion, memory, and decision-making. However, the term is used inconsistently, referring variously to affective experience, autonomic activation, and states of wakefulness. The extent to which different operationalizations of arousal reflect a shared neurobiological basis remains unclear, limiting efforts to unify findings across studies. We applied dynamic connectome predictive models to five fMRI datasets spanning naturalistic movie watching, story listening, wakeful rest, and sleep. We derived measures of affective, autonomic, and wakefulness arousal from subjective ratings, pupil dilation, and EEG, respectively. Models trained to predict arousal in one dataset generalized across datasets, indicating that dynamic connectivity captures shared arousal-related dynamics across measures and task contexts. The models also predicted manually scored sleep stages, suggesting that they capture arousal dynamics that extend to the graded fluctuations in arousal during sleep. Decoded arousal dynamics during movie-viewing predicted how well participants later recalled movie events, reproducing classic arousal-dependent memory enhancement effects. Model predictions were supported by overlapping functional connections, including a subset shared across all models. The largest proportion of shared connections was between the salience and somatomotor networks, suggesting that increased coordination between salience detection and action readiness may be a common feature across multiple operationalizations of arousal. Together, these results are consistent with a connectome-based neural reference space for arousal, in which different varieties share a core set of predictive connections. Our findings offer a quantitative framework for integrating arousal-related findings across tasks and modalities.

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bioRxiv2026

Neural dynamics of updating social impressions during movie watching

Updating impressions of others is essential to navigating social life. As we get to know an individual, we update our impressions of them in accordance with new information. How the brain dynamically revises impressions in real time under naturalistic conditions remains unclear. Here, we address this question using functional magnetic resonance imaging (fMRI) and natural language analysis in a naturalistic social cognition paradigm. Across 10 runs, participants viewed a character-driven TV episode, reported moments of insight, and described their impressions of the characters. Results reveal that impressions progressively evolved over time. Individuals with more similar existing impressions exhibit greater neural synchrony during movie-watching, which predicts convergence in post-movie impressions. Neural synchrony in the right superior temporal sulcus (STS) mediates the influence of initial similarity on later alignment. Insight moments accompany neural pattern shifts widespread across cortical regions, including the temporoparietal junction (TPJ), dorsomedial prefrontal cortex (dmPFC) and STS, and the magnitude of the shifts tracks the degree of impression updating. Specifically, distinct forms of insight selectively update complementary components of impressions: character insight updates person-centered representations, whereas non-character insight shapes social-event structure. Together, these findings show that people update their impressions of others through dynamic shifts in distributed brain activity patterns at moments of insight, providing a novel and ecologically grounded neural account of social cognition. Significance statementPeople do not simply form first impressions and keep them. As we learn new things about others, our judgments change--sometimes gradually, sometimes in a flash of insight. By tracking brain activity while people watched a TV show and described how their impressions of the characters evolved, we found that people who saw a character in more similar ways also show more similar brain responses when watching them onscreen, which in turn leads to convergence in subsequent impressions. Such updating is closely tied to "aha" moments, when a person is suddenly understood in a new way. These moments were marked by rapid shifts in the brain representational patterns, and larger shifts predicted greater changes in impressions. These findings offer a more naturalistic account of how the brain revises our understanding of other people in everyday life.

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bioRxiv2026

Individuals with Intermittent Explosive Disorder Exhibit Idiosyncratic Neural Responses during Social-emotional Processing

Intermittent explosive disorder (IED) is associated with impulsive aggression in ambiguous social contexts. Prior neuroimaging studies have treated IED as a homogenous group, but identical social situations may elicit divergent responses across IED individuals. Here, we test the hypothesis that IED is characterized by idiosyncratic neural responses to social cues during naturalistic social-emotional processing. IED individuals and healthy controls completed a validated paradigm where they were presented with video vignettes of interpersonal interactions while undergoing fMRI. We computed the intersubject correlation (ISC) in neural time courses between pairs of participants to quantify neural similarity, and assessed whether similarity differed between Healthy-Healthy and IED-IED dyads using Bayesian multilevel models, controlling for self-reported emotional responses and intention attributions for each vignette. Healthy-Healthy dyads showed significantly higher ISC than IED-IED dyads, indicating that neural responses to the videos were similar among healthy participants, but idiosyncratic in IED individuals. These effects were observed in regions in the default mode and salience networks, including the precuneus, medial prefrontal cortex, superior temporal sulcus, insula, and dorsal anterior cingulate cortex. Individuals with IED exhibited idiosyncratic neural responses during naturalistic social-emotional processing, even after accounting for differences in emotional reaction and intention attribution. This neural idiosyncrasy may reflect atypical integration of social cues, giving rise to maladaptive interpretations and impulsive aggression. Assessing neural synchrony during ecologically valid paradigms offers a promising tool for identifying neural markers of interpersonal dysfunction and informing targeted interventions.

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bioRxiv2026

Trait anxiety is associated with idiosyncratic neural event boundaries during naturalistic movie-watching

Anxiety is associated with altered patterns of attention to images and objects, but how it influences the perception of continuous experiences remains underexplored. Here, we examined whether trait anxiety is associated with differences in how the brain segments continuous experience into events. Using a large-scale open-access dataset and data-driven methods to detect neural event boundaries, we compared neural event segmentation between healthy adults with high (N=60) and low trait-level anxiety (N=60) as they viewed a short suspenseful film. While the cortical temporal hierarchy was preserved across groups, high-anxiety individuals had more idiosyncratic event boundaries, exhibiting reduced alignment to both low-anxiety individuals and one another. This divergence was most pronounced in the dorsal attention and frontoparietal control networks, suggesting that trait anxiety is associated with idiosyncratic temporal organization in systems involved in attentional control. Furthermore, boundary variability in high-anxiety participants was greater during moments rated as more anxiety-provoking by a large language model, controlling for arousal, valence, and low-level visual features. Together, these findings suggest that anxious individuals organize continuous experience in a more individualized manner. More broadly, they offer a neurocomputational framework for investigating how trait-level variability interacts with narrative content to shape naturalistic event perception.

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bioRxiv2025

A neural network with episodic memory learns causal relationships between narrative events

Humans reflect on memories to make sense of ongoing events. Past work has shown that people retrieve causally related memories during comprehension, but the mechanisms underlying this process remain unclear. Here, we used a recurrent neural network augmented with a key-value episodic memory buffer and trained it to predict upcoming scenes while watching a television episode. At each time step, the model transformed the current scene into a value representing memory content and a key representing memory address, both stored as episodic memory. The model retrieved selective past values by applying self-attention over stored keys and integrated these memories with the current scene representation to generate predictions. The model retrieved memories similar to those retrieved by human participants watching the same episode during fMRI. Importantly, this similarity disappeared when causal relationships between events were controlled for. The model also represented causally related events with similar patterns, similar to how the human brain represents these events. These findings suggest that using two distinct memory representations allows the model to retrieve memories and organize events based on causal relationships, beyond semantic or perceptual similarities. Together, this work proposes a key-value episodic memory system as a candidate computational mechanism for how humans retrieve causally related memories to comprehend naturalistic events.

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bioRxiv2025

Ongoing thoughts at rest reflect functional brain organization and behavior

Resting-state functional connectivity (rsFC)--brain connectivity observed when people rest with no external tasks--predicts individual differences in behavior. Yet, rest is not idle; it involves streams of thoughts. Are these ongoing thoughts reflected in FC and do they contribute to the relationship between rsFC and behavior? To test this question, we developed an annotated rest paradigm where participants rated and verbally described their thoughts after each rest period during functional MRI (N = 60). Our findings revealed rich and idiosyncratic thoughts across individuals. Similarity in thoughts was associated with more similar FC patterns within and across individuals. In addition, both thought ratings and topics could be decoded from FC. Furthermore, neuromarkers of these thoughts generalized to unseen individuals in the Human Connectome Project dataset (N = 908), where decoded thought patterns during rest predicted positive vs. negative trait-level individual differences. Together, our findings reveal that ongoing thoughts at rest are reflected in brain dynamics and these network patterns predict everyday cognition and experiences. Understanding subjective in-scanner experiences is thus crucial in characterizing the relationship between individual differences in functional brain organization and behavior.

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bioRxiv2025

Cortical reinstatement of causally related events sparks narrative insights by updating neural representation patterns

We make sense of everyday events by reasoning about their underlying causes. When we connect causal links between events separated in time, we often experience a sudden feeling of "aha!", or a moment of insight. What cognitive and neural processes underlie these moments of understanding? We hypothesized that narrative insight accompanies retrieving causally related past events in memory and updating the current event representation. To test this, we designed an fMRI study in which participants watched a TV episode that was cut into multiple events and presented in temporally scrambled orders. Participants pressed an "aha" button whenever they understood something new and verbally explained why they pressed in those moments at the end of each run. Supporting our prediction, more than 40% of insights included the retrieval of past events that were causally related to the current event. Neural patterns representing causally related past events were reinstated in cortical areas. This neural reinstatement drove sudden shifts in cortical representation patterns [~]2 s prior to aha button presses, reflecting an update in situational representation at moments of insight. Moreover, distributed areas in the brain represented causally related events with similar neural patterns, beyond their shared semantic or perceptual features. Together, the study suggests that we comprehend events by reinstating causally related past events via shared neural patterns, followed by updating neural patterns at moments of insight.

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bioRxiv2025

Emotional arousal enhances narrative memories through functional integration of large-scale brain networks

Emotional events tend to be vividly remembered. While growing evidence suggests that emotions have their basis in brain-wide network interactions, it is unclear if and how these whole-brain dynamics contribute to memory encoding. We combined fMRI, graph theory, text analyses, and pupillometry in a naturalistic context where participants recalled complex narratives in their own words. Across three independent datasets, emotionally arousing moments during narrative perception were associated with an integrated brain state characterized by increased cohesion across functional modules, which in turn predicted the fidelity of subsequent recall. Network integration mediated the influence of emotional arousal on recall fidelity, with consistent within- and between-network interactions supporting the mediation across datasets. Together, these results suggest that emotional arousal enhances memory encoding via strengthening functional integration across brain networks. Our findings advance a cross-level understanding of emotional memories that bridges large-scale brain network dynamics, affective states and ongoing cognition.

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bioRxiv2024

Predicting whole-brain neural dynamics from prefrontal cortex fNIRS signal during movie-watching

Functional near-infrared spectroscopy (fNIRS) offers a portable, cost-effective alternative to functional magnetic resonance imaging (fMRI) for non-invasively measuring neural activity. However, fNIRS measurements are limited to cortical regions near the scalp, missing important medial and deeper brain areas. We introduce a predictive model that maps prefrontal fNIRS signals to whole-brain fMRI activity during movie-watching. By aligning neural responses to a common audiovisual stimulus, our approach leverages shared dynamics across imaging modalities to map fNIRS signals to broader neural activity patterns. We scanned participants with fNIRS and utilized a publicly available fMRI dataset of participants watching the same TV episode. The model was trained on the first half of the episode and tested on a held-out participant watching the second half to assess cross-individual and cross-stimulus generalizability. The model significantly predicted fMRI time courses in 66 out of 122 brain regions, including in areas otherwise inaccessible to fNIRS. The predicted fMRI time course also replicated intersubject functional connectivity patterns and retained semantic information about the movie content. Our publicly available model enables researchers to infer broader neural dynamics from localized fNIRS data, offering new opportunities for studying the neural basis of complex cognitive processes during naturalistic tasks.

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bioRxiv2023

Dynamic Functional Connectivity Encodes Generalizable Representations of Emotional Arousal But Not Valence

Human affective experience varies along the dimensions of valence (positivity or negativity) and arousal (high or low activation). It remains unclear how these dimensions are encoded in the brain and if the representations are shared across different individuals and diverse situational contexts. Here we utilized two publicly available functional MRI datasets of participants watching movies to build predictive models of moment-to-moment valence and arousal from dynamic functional brain connectivity. We tested the models both within and across datasets and identified a generalizable arousal representation characterized by the interaction between multiple large-scale functional networks. The arousal representation generalized to two additional movie-watching datasets. Predictions based on multivariate patterns of activation underperformed connectome-based predictions and did not generalize. In contrast, we found no evidence of a generalizable valence representation. Taken together, our findings reveal a generalizable representation of arousal encoded in patterns of dynamic functional connectivity, revealing an underlying similarity in how arousal is encoded across individuals and situational contexts.

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bioRxiv2023

Hostile attribution bias shapes neural synchrony in the left ventromedial prefrontal cortexduring ambiguous social narratives

Hostile attribution bias refers to the tendency to interpret social situations as intentionally hostile. While previous research has focused on its developmental origins and behavioral consequences, the underlying neural mechanisms remain underexplored. Here, we employed functional near infrared spectroscopy (fNIRS) to investigate the neural correlates of hostile attribution bias. While undergoing fNIRS, participants listened to and provided attribution ratings for 21 hypothetical scenarios where a characters actions resulted in a negative outcome for the listener. Ratings of hostile intentions were averaged to obtain a measure of hostile attribution bias. Using intersubject-representational similarity analysis, we found that participants with similar levels of hostile attribution bias exhibited higher levels of neural synchrony during narrative listening, suggesting shared interpretations of the scenarios. This effect was localized to the left ventromedial prefrontal cortex (VMPFC), and was particularly prominent in scenarios where the characters intentions were highly ambiguous. We then grouped participants into high and low bias groups based on a median split of their hostile attribution bias scores. A similarity-based classifier trained on the neural data classified participants as having high or low bias with 76% accuracy, indicating that the neural time courses during narrative listening was systematically different between the two groups. Furthermore, hostile attribution bias correlated negatively with attributional complexity, a measure of ones tendency to consider multifaceted causes when explaining behavior. Our study sheds light on the neural mechanisms underlying hostile attribution bias and highlights the potential of using fNIRS to develop non-intrusive and cost-effective neural markers of this socio-cognitive bias. Significance StatementInferring the intentions from behavior is crucial for adaptive social functioning. A predisposition towards interpreting intentions as hostile is a significant predictor of interpersonal conflict and aggressive tendencies. Using fNIRS, we found that individual differences in hostile attribution bias shaped neural synchrony in the VMPFC while processing real-world social situations. Additionally, we were able to distinguish between participants with high and low hostile attribution bias from neural activity time courses. These results reveal how subjective interpretations of social situations are influenced by hostile attribution bias and reflected in the temporal dynamics of the VMPFC. Our findings lay the groundwork for future studies aimed at understanding the neurobiological basis of socio-cognitive biases, as well as interventions aimed at mitigating these biases.

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bioRxiv2021

Trial-by-trial fluctuations in amygdala activity track motivational enhancement of desirable sensory evidence during perceptual decision-making

People are biased towards seeing outcomes that they are motivated to see. For example, sports fans often perceive the same ambiguous foul in favor of the team they support. Here, we test the hypothesis that motivational biases in perceptual decision-making arise from amygdala-dependent biases in sensory processing. Human participants were rewarded for correctly categorizing an ambiguous image into one of two categories while undergoing fMRI. On each trial, we used a financial bonus to motivate participants to see one category over another. The reward maximizing strategy was to perform the categorizations accurately, but participants were biased towards categorizing the images as the category we motivated them to see. Heightened amygdala activity was associated with motivation consistent categorizations, and tracked trial-by-trial enhancement of neural activity in sensory cortices that was specific to the desirable category. Analyses using a drift diffusion model provide converging evidence that trial-by-trial amygdala activity was associated with stronger biases in the accumulation of sensory evidence. Prior work examining biases in perceptual decision-making have focused on the role of frontoparietal regions. Our work highlights an important contribution of the amygdala. When people are motivated to see one outcome over another, the amygdala biases perceptual decisions towards those outcomes.

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bioRxiv2020

Narratives: fMRI data for evaluating models of naturalistic language comprehension

The "Narratives" collection aggregates a variety of functional MRI datasets collected while human subjects listened to naturalistic spoken stories. The current release includes 345 subjects, 891 functional scans, and 27 diverse stories of varying duration totaling ~4.6 hours of unique stimuli (~43,000 words). This data collection is well-suited for naturalistic neuroimaging analysis, and is intended to serve as a benchmark for models of language and narrative comprehension. We provide standardized MRI data accompanied by rich metadata, preprocessed versions of the data ready for immediate use, and the spoken story stimuli with time-stamped phoneme- and word-level transcripts. All code and data are publicly available with full provenance in keeping with current best practices in transparent and reproducible neuroimaging.

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bioRxiv2020

Pupil-linked arousal biases evidence accumulation towards desirable percepts during perceptual decision-making

People are biased towards seeing outcomes they are motivated to see. The arousal system coordinates the bodys response to motivationally significant events, and is well positioned to regulate motivational effects on sensory perception. However, it remains unclear whether arousal would enhance or reduce motivational biases. Here we measured pupil dilation as a measure of arousal while participants performed a visual categorization task. We used monetary bonuses to motivate participants to see one category over another. Even though the reward-maximizing strategy was to perform the task accurately, participants were more likely to report seeing the motivationally desirable category. Furthermore, higher arousal levels were associated with making motivationally biased responses. Analyses using computational models suggest that arousal enhanced motivational effects by biasing evidence accumulation in favor of motivationally desirable percepts. These results suggest heightened arousal biases people towards what they want to see and away from an objective representation of the environment. Statement of RelevanceWhen confronted with an event of motivational significance (e.g., an opportunity to earn a huge reward), people often experience a strong arousal response that includes increased sweating, faster heart-rate and larger pupils. Does this arousal response help individuals make more accurate decisions, or does it instead bias and impair decision-making? This work examines the effects of arousal on how people decide what they see when they are motivated to see a particular outcome. We found that heightened arousal, as measured by larger pupils, was associated with a bias in how participants accumulated sensory evidence to make their decisions. As a result, participants became more likely to report seeing an ambiguous visual image as the interpretation they were motivated to see. Our results suggest that arousal biases perceptual judgments towards desirable percepts, and that modulating arousal levels could be a promising approach in reducing motivational biases in decision-making.

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bioRxiv2020

Conservative and liberal attitudes drive polarized neural responses to political content

People tend to interpret political information in a manner that confirms their prior beliefs, a cognitive bias that contributes to rising political polarization. In this study, we combined functional magnetic resonance imaging with semantic content analyses to investigate the neural mechanisms that underlie the biased processing of real-world political content. We scanned American participants with conservative-leaning or liberal-leaning immigration attitudes while they watched news clips, campaign ads, and public speeches related to immigration policy. We searched for evidence of "neural polarization": activity in the brain that diverges between people who hold liberal versus conservative political attitudes. Neural polarization was observed in the dorsomedial prefrontal cortex (DMPFC), a brain region associated with the interpretation of narrative content. Neural polarization in the DMPFC intensified during moments in the videos that included risk-related and moral-emotional language, highlighting content features most likely to drive divergent interpretations between conservatives and liberals. Finally, participants whose DMPFC activity closely matched that of the average conservative or the average liberal participant were more likely to change their attitudes in the direction of that groups position. Our work introduces a novel multi-method approach to study the neural basis of political cognition in naturalistic settings. Using this approach, we characterize how political attitudes biased information processing in the brain, the language most likely to drive polarized neural responses, and the consequences of biased processing for attitude change. Together, these results shed light on the psychological and neural underpinnings of how identical information is interpreted differently by conservatives and liberals. Significance StatementPartisan biases in processing political information contribute to rising divisions in society. How do such biases arise in the brain? We measured the neural activity of participants watching videos related to immigration policy. Despite watching the same videos, conservative and liberal participants exhibited divergent neural responses. This "neural polarization" between groups occurred in a brain area associated with the interpretation of narrative content, and intensified in response to language associated with risk, emotion, and morality. Furthermore, polarized neural responses predicted attitude change in response to the videos. These findings suggest that biased processing in the brain drives divergent interpretations of political information and subsequent attitude polarization.

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bioRxiv2018

Neurocomputational mechanisms underlying motivated seeing

People tend to believe their perceptions are veridical representations of the world, but also commonly report perceiving what they want to see or hear, a phenomenon known as motivated perception. It remains unclear whether this phenomenon reflects an actual change in what people perceive or merely a bias in their responding. We manipulated the percept participants wanted to see as they performed a visual categorization task for reward. Even though the reward maximizing strategy was to perform the task accurately, this manipulation biased participants perceptual judgments. Motivation increased activity in voxels within visual cortex selective for the motivationally relevant category, indicating a bias in participants neural representation of the presented image. Using a drift diffusion model, we decomposed motivated seeing into response and perceptual components. Response bias was associated with anticipatory activity in the nucleus accumbens, whereas perceptual bias tracked category-selective neural activity. Our results highlight the role of the reward circuitry in biasing perceptual processes and provide a computational description of how the drive for reward can lead to inaccurate representations of the world.

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