Biology subjects

Rungratsameetaweemana, N.

Publications and source records attributed to Rungratsameetaweemana, N..

14 recordsLinked to original sources

bioRxiv2026

Pupil and Neural Dynamics Reveal Belief-Dependent Decision Making Under Ambiguity

Humans make thousands of decisions under ambiguity every day, where most times the probabilities of getting beneficial outcomes are not fully known. Although ambiguity aversion is well characterized at the aggregate level, it remains unclear how individuals internally represent ambiguous outcomes and how these representations shape behavior and physiology. To address these questions, we investigate value-based decision-making under risk and ambiguity using a multimodal approach that combines behavioral, pupillometric, and electroencephalographic (EEG) data. We show that individuals adopt distinct decision strategies that reflect different internal beliefs about unknown outcomes. These belief differences are expressed not only in choice but also in pupil-linked arousal during decision formation. Crucially, physiological differences across strategies persist under an objective valuation rule for ambiguous options but disappear when valuation is computed using each individuals subjective beliefs, indicating that arousal tracks subjective belief rather than objective task structure. Together, our findings show that ambiguity aversion is not a uniform bias but reflects heterogeneous internal belief models, and that multimodal physiology provides a window into the mechanisms through which these beliefs guide value-based choice.

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bioRxiv2026

Task goals reorganize visual codes in human ventral temporal cortex via medial frontal modulation

How sensory representations in the sensory cortex are dynamically and rapidly modulated to support flexible, goal-directed behavior remains a fundamental open question. Using rare simultaneous single-neuron recordings across multiple human brain regions, including the ventral temporal cortex (VTC), a high-level visual area not traditionally associated with context-dependent coding, we show that visual representations in VTC are rapidly reconfigured by the presence or absence of preceding verbal task instructions. Identical visual stimuli evoked distinct responses in VTC depending on whether task instructions were provided or not, with categorical representations sharpened when goals were specified in advance. In contrast, dorsal anterior cingulate cortex (dACC) and the hippocampus carried strong signals related to instruction timing, consistent with known regional specialization in top-down control. Coupling between dACC and VTC increased during periods of instructional uncertainty and high cognitive demand on a rapid timescale during stimulus presentation, and its strength predicted correct performance. Together, these findings uncover a rapid, online feedback mechanism through which the medial frontal cortex dynamically reorganizes sensory population codes in VTC, linking flexible cortical coordination to successful goal-directed computation.

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bioRxiv2026

Computational neural dynamics of goal-directed visual attention in macaques

Goal-directed visual attention requires the dynamic integration of task goals with perceptual and mnemonic processes across distributed cortical networks. Using large-scale recordings from V4, IT, OFC, and LPFC, we identified distinct neural populations selective for attention and category. Population dynamics robustly represented visual categories during cue presentation, sustained cue information across delays, and differentiated categories and attentional states during search. Cue-related activity predicted subsequent search efficiency, linking pre-search processing to behavioral performance. The orthogonal subspace provided a crucial latent representational structure for encoding and maintaining task-relevant information across search stages. Foveal attention enhanced peripheral representations by both increasing pattern separation and reshaping representational geometry in a non-linear, context-dependent manner. Search dynamics further reflected fixation history and target detection, which modulated both response strength and representational structure. Finally, V4 and IT encoded the spatial geometry of the search array, preserving its layout. Together, these findings highlight population-level dynamics as critical mechanisms supporting goal-directed visual search.

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bioRxiv2025

Neural heterogeneity shapes the temporal structure of human working memory

Working memory (WM) enables temporary retention of information essential for flexible cognition. Although persistent population activity has long been regarded as a principal mechanism of memory maintenance, continuous single-neuron firing is energetically demanding and difficult to reconcile with the heterogeneous firing properties of cortical neurons. Applying single-trial analyses to a dataset of 902 neurons recorded from 21 neurosurgical patients performing a WM task, we found that maintenance was supported by transient, burst-like episodes of coordinated activity rather than sustained firing. Cross-temporal decoding exhibited localized generalization, and decoding accuracy increased with wider temporal windows, indicating that apparent persistence can emerge from temporally interleaved activity across neurons. We further developed a feature-based, putative cell-type classifier that revealed distinct circuit contributions: pyramidal neurons expressed content in burst-aligned events during maintenance, whereas interneurons were strongly modulated by memory load and behavior. Together, these findings reconcile dynamic and persistent accounts, indicating that human WM can emerge from temporally interleaved, cell-type-specific dynamics that provide a flexible and potentially metabolically efficient substrate for maintaining information over time.

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bioRxiv2025

ALM enables contextual decision-making via dynamic reconfiguration of local circuits

Cognitive operations often require flexible implementation of stimulus-response contingencies, depending on context. We developed an olfactory task in which mice learned to associate a test odor with a directional lick response, conditional on a preceding context odor drawn from a different odor set. Two-photon imaging revealed that anterior lateral motor cortex (ALM) contains distinct populations encoding context, test odors, and choice. Optogenetic silencing during the context and delay periods impaired performance, suggesting that ALM contributes to configuring the appropriate contingency. Although context odors that instructed the same mapping were represented by separate populations, their influence converged at the level of choice-selective neurons. A subpopulation of these neurons exhibited dual selectivity for context and choice, forming what we term "contingency neurons." These findings suggest that ALM supports flexible behavior not by abstracting over context cues, but by dynamically reconfiguring local circuits to route sensory input to the appropriate motor output.

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bioRxiv2025

Asymmetric Social Representations in the Prefrontal Cortex for Cooperative Behavior

Cooperation is a hallmark of social species, enabling individuals to achieve goals that are unattainable alone. Across species, cooperative behaviors are often organized by distinct social roles such as leaders and followers, yet the neural mechanisms supporting such role-based coordination remain elusive. Here we introduce a new paradigm for studying cooperation in mice, where pairs of animals engage in a joint spatial foraging task that naturally gives rise to stable leader-follower roles predictive of learning speed. Disruption of medial prefrontal cortex (mPFC) activity, particularly in followers, impairs cooperation and induces reciprocal shifts in how animals weigh self- and partner-related cues for decision-making. Calcium imaging reveals that mPFC encodes both leadership dynamics and an egocentric social value map of the partners position, each in an asymmetric, role-specific manner. Combining this behavior with a novel multi-agent inverse reinforcement learning framework, we identify latent value functions that guide cooperative decisions and are decodable from mPFC activity. These findings uncover fundamental neural computations that support cooperation, revealing how social roles shape decision-making in real time. Our work opens new avenues for investigating the cellular and circuit basis of social cognition and collective behavior.

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bioRxiv2025

Learning and language in the unconscious human hippocampus

Consciousness is a fundamental component of cognition,1 but the degree to which higher-order pattern recognition relies on it remains disputed.2,3 Here we demonstrate the persistence of oddball discrimination, semantic processing, and online prediction in individuals under general anesthesia-induced loss of consciousness.4,5 Using high-density Neuropixels microelectrodes6 to record both single unit and local field potential neural activity in the human hippocampus while playing a series of tones to anesthetized patients, we found that hippocampal neurons and local oscillations retained some detection of oddball tones. This effect size grew over the course of the experiment ([~]10 minutes), demonstrating representational plasticity. A biologically plausible recurrent neural network model showed that learning and oddball representation are an emergent property of flexible tone discrimination. Moreover, when we played language stimuli, single units and local field potentials carried information about the semantic and grammatical features of natural speech, even predicting semantic information about upcoming words. Together these results indicate that in the hippocampus, which is anatomically and functionally distant from primary sensory cortices,7 complex processing of sensory stimuli occurs even in the unconscious state.

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bioRxiv2025

Behavioral investigation of allocentric and egocentric cognitive maps in human spatial memory

Spatial memory is a fundamental cognitive function that enables humans and other species to encode and recall the locations of items in their environments. Humans employ diverse strategies to support spatial memory, including the use of cognitive maps. Cognitive maps are mental representations of the environment that organize its content along two or more continuous dimensions. In allocentric cognitive maps, these dimensions form a Cartesian coordinate system referenced to the environment. In egocentric cognitive maps, the dimensions form a polar coordinate system centered on the subject. To better understand how humans employ allocentric and egocentric cognitive maps for spatial memory, we performed a behavioral study with a novel task designed to directly and explicitly assess both types of cognitive maps. During encoding periods, participants navigated through a virtual environment and encountered objects at different locations. During recall periods, participants aimed at remembering these locations in abstract allocentric and egocentric coordinate systems. Our results show that relationships between the objects and the environment, such as their distance to boundaries and corners, were associated with allocentric memory performance. Relationships between the objects and the participant, including their distance and orientation to the participants starting position, were linked to egocentric memory performance. Spatial feedback during recall supported performance within allocentric and egocentric domains, but not across domains. These findings are compatible with the notion that allocentric and egocentric cognitive maps operate as (partially) independent systems for spatial memory, each specialized in processing specific types of spatial relationships.

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bioRxiv2023

Top-down signaling dynamically mediates information processing in biologically inspired RNNs

Recent studies have proposed employing biologically plausible recurrent neural networks (RNNs) to investigate flexible decision-making in the brain. However, the mechanisms underlying the integration of bottom-up sensory inputs and temporally varying top-down factors (such as task instructions and selective attention) remain poorly understood, both within the context of these models and the brain. To address this knowledge gap, we trained biologically inspired RNNs on complex cognitive tasks that require adaptive integration of these factors. Through comprehensive analyses of RNNs and neural activity from mouse primary visual cortex, we show that sensory neurons in low-level areas possess the remarkable ability to multiplex and dynamically combine both bottom-up and top-down information via local inhibitory-to-inhibitory connections. Our results shed light on the role of disinhibitory circuits in the intricate interplay between bottom-up and top-down factors to enable flexible decision processes.

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bioRxiv2023

Categorization dynamically alters representations in human visual cortex

Everyday perceptual tasks require sensory stimuli to be dynamically encoded and analyzed according to changing behavioral goals. For example, when searching for an apple at the supermarket, one might first find the Granny Smith apples by separating all visible apples into the categories "green" and "non-green". However, suddenly remembering that your family actually likes Fuji apples would necessitate reconfiguring the boundary to separate "red" from "red-yellow" objects. This flexible processing enables identical sensory stimuli to elicit varied behaviors based on the current task context. While this phenomenon is ubiquitous in nature, little is known about the neural mechanisms that underlie such flexible computation. Traditionally, sensory regions have been viewed as mainly devoted to processing inputs, with limited involvement in adapting to varying task contexts. However, from the standpoint of efficient computation, it is plausible that sensory regions integrate inputs with current task goals, facilitating more effective information relay to higher-level cortical areas. Here we test this possibility by asking human participants to visually categorize novel shape stimuli based on different linear and non-linear boundaries. Using fMRI and multivariate analyses of retinotopically-defined visual areas, we found that shape representations in visual cortex became more distinct across relevant decision boundaries in a context-dependent manner, with the largest changes in discriminability observed for stimuli near the decision boundary. Importantly, these context-driven modulations were associated with improved categorization performance. Together, these findings demonstrate that codes in visual cortex are adaptively modulated to optimize object separability based on currently relevant decision boundaries.

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bioRxiv2022

Internal noise promotes heterogeneous synaptic dynamics important for working memory in recurrent neural networks

Recurrent neural networks (RNNs) based on model neurons that communicate via continuous signals have been widely used to study how cortical neurons perform cognitive tasks. Training such networks to perform tasks that require information maintenance over a brief period (i.e., working memory tasks) remains a challenge. Critically, the training process becomes difficult when the synaptic decay time constant is not fixed to a large constant number for all the model neurons. Here, we show that introducing random noise to the RNNs not only speeds up the training but also produces stable models that can maintain information longer than the RNNs trained without internal noise. Importantly, this robust working memory performance induced by internal noise during training is attributed to an increase in synaptic decay time constants of a distinct subset of inhibitory units, resulting in slower decay of stimulus-specific activity critical for memory maintenance.

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bioRxiv2021

Intermittent brain network reconfigurations and the resistance to social media influence

Since their development, social media has grown as a source of information and has a significant impact on opinion formation. Individuals interact with others and content via social media platforms in a variety of ways but it remains unclear how decision making and associated neural processes are impacted by the online sharing of informational content, from factual to fabricated. Here, we use EEG to estimate dynamic reconfigurations of brain networks and probe the neural changes underlying opinion change (or formation) within individuals interacting with a simulated social media platform. Our findings indicate that the individuals who changed their opinions are characterized by less frequent network reconfigurations while those who did not change their opinions tend to have more flexible brain networks with frequent reconfigurations. The nature of these frequent network configurations suggests a fundamentally different thought process between intervals in which individuals are easily influenced by social media and those in which they are not. We also show that these reconfigurations are distinct to the brain dynamics during an in-person discussion with strangers on the same content. Together, these findings suggest that brain network reconfigurations may not only be diagnostic to the informational context but also the underlying opinion formation. Author SummaryDistinctive neural underpinnings of opinion formation and change during in-person and online social interactions are not well understood. Here, we analyze EEG recordings of the participants interacting with a simulated social media platform and during an in-person discussion using a network-based analysis approach. We show that the structure of network reconfigurations during these interactions is diagnostic of the opinion change and the context in which information was received.

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bioRxiv2021

Brain network dynamics codify heterogeneity in seizure propagation

Dynamic functional brain connectivity facilitates adaptive cognition and behavior. Abnormal alterations within such connectivity could result in disrupted functions observed across various neurological conditions. As one of the most common neurological disorders, epilepsy is defined by the seemingly random occurrence of spontaneous seizures. A central but unresolved question concerns the mechanisms by which extraordinarily diverse dynamics of seizures emerge. Here, we apply a graph-theoretical approach to assess dynamic reconfigurations in the functional brain connectivity before, during, and after seizures that display heterogeneous propagation patterns despite sharing similar origins. We demonstrate unique reconfigurations in globally-defined network properties preceding seizure onset that predict propagation patterns of impending seizures, and in locally-defined network properties that differentiate post-onset dynamics. These results characterize quantitative network features underlying the heterogeneity of seizure dynamics and the accompanying clinical manifestations. Decoding these network properties could improve personalized preventative treatment strategies for epilepsy as well as other neurological disorders.

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bioRxiv2018

The speed-accuracy tradeoff reveals flexible access to accumulating sensory evidence during human decision making

Decisions made about identical perceptual stimuli can be radically different under changing task demands. For example, the need to make a fast decision undermines the accuracy of that decision, a well-documented effect termed the speed-accuracy tradeoff (SAT). Models of the SAT are generally based on theories of decision making in which responses are triggered only after sensory evidence accumulation terminates at a set threshold. Within this accumulate-to-bound framework, speed pressure operates by lowering the response threshold, allowing for faster responses at the expense of accumulated sensory evidence. To empirically examine the mechanisms necessary for adaptively adjusting the speed and accuracy of decisions, we used an event-related potential that indexes sensory evidence accumulation in the human brain. Instead of lowering response thresholds, we found that speed pressure adaptively shifts responses to occur close to where the rate of evidence accumulation peaks. Moreover, responses are not triggered automatically by the termination of the accumulation process, as sensory evidence continues to build after speeded decisions. Together these results suggest that response processes adaptively access accumulating sensory evidence depending on task demands and support parallel over serial models of decision making.

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