Biology subjects

Man, V.

Publications and source records attributed to Man, V..

10 recordsLinked to original sources

bioRxiv2025

Distributed activity in the human posterior putamen distinguishes goal-directed from habitual control in humans

How do some individuals rapidly form habits while others maintain flexible, goal-directed control? Using multivariate fMRI decoding in 199 participants, we show that distributed neural activity patterns in the left posterior putamen during initial learning predict individual behavioral strategy on a subsequent outcome devaluation test. This prediction generalized across two independent cohorts of healthy adults and psychiatric patients with heterogeneous diagnoses and was anatomically specific to the posterior putamen. Critically, predictive neural signatures were present during training, before strategy expression after devaluation, enabling prospective classification of habitual versus goal-directed behavior. These findings demonstrate that stable individual differences in behavioral control are reflected in circumscribed brain activity during learning, highlighting the posterior putamen as a candidate neural marker of habit propensity with potential clinical relevance.

neuroscience↗

bioRxiv2025

The neural computations underlying context dependent attribute-based valuation of complex stimuli.

Adaptive decision making requires value computations to be flexible because we often need to value a stimulus differently as the context changes. A stimulus might be highly desirable in one context but completely unappealing in another. However, it is not known how the brain can support such flexible modulation of overall stimulus value. Here we test a model of flexible value construction whereby individual attributes of a stimulus are converted into contextually dependent attribute-specific value representations before being combined into an overall integrated stimulus value. To test this framework, human participants (online n=95, MRI n=35) provided ratings for 75 unique high-dimensional clothing stimuli under three instructed goal-contexts designed to elicit differences in overall value judgments for the items. Integrated value ratings for each stimulus were found to be goal-context dependent, while individual stimulus-attributes varied markedly in how they contributed to value ratings across goal contexts. In the fMRI data, representations of the absolute levels of particular attributes were revealed in visual areas. In contrast, encoding of individual attributes in value space, alongside integrated overall stimulus value, was present within distinct regions of prefrontal cortex. More specifically, behaviorally relevant attributes in value space and integrated stimulus value were found in vmPFC and dmPFC respectively. These findings indicate that the construction of value for high-dimensional stimuli is achieved through the computation of goal-context-dependent attributes in value space, providing mechanistic insight into how the brain can flexibly modulate stimulus-values as context changes.

neuroscience↗

bioRxiv2025

The representation and valuation of subgoals in the human brain during model-based hierarchical behavior

The human capacity to plan and perform long, complex sequences of behavior to achieve distant goals depends in part on a hierarchical organization that divides behavior into structured segments. Such a mechanism requires the internal designation of certain states as subgoals to mark the successful implementation of a behavioral segment. How the brain represents subgoals over time and computes decision values as a function of subgoals is unknown. While most characterizations of hierarchical behavior lack knowledge of the environment, human decision-making also relies on planning with an internal model of the world. Consequently, it remains to be determined how the brain computes values of subgoals using model-based planning in order to drive hierarchical, model-based decisions. Using a sequential-subgoal decision-making task designed to evoke hierarchical, model-based behavior in combination with fMRI, we decoded a representation of the current subgoal in insula and ventromedial prefrontal cortex during decision-making that persisted over time-a critical, latent representation for computing values and orienting behavior in the correct sequence. Using a model-based, hierarchical reinforcement learning model, we also found key decision signals based on values from the model in several regions of frontal cortex. These findings thereby shed light on the neural correlates of subgoal representation and illustrate how value signals can be computed on the basis of these subgoals and knowledge of the environment structure.

neuroscience↗

bioRxiv2025

The Neural Basis of Habit Formation Measured in Goal-Directed Response Switching

To override ongoing habitual responses requires switching well-learned actions with new goal-directed processing. However, the neural circuits responsible for these processes remain unclear. This study infers habit strength by introducing a novel task capturing the increased cost associated with switching a habitual response. We employed neuroimaging and brain stimulation to examine the dynamic interactions between human brain regions involved in habits and their interference with ongoing incompatible goal-directed behavior. Training S-R links in overtrained stimuli (compared to less trained ones, termed standard-trained stimuli) increased RT switch costs, explained by drift diffusion computations governing both the training and outcome devaluation phases. Training engaged sensorimotor areas and the posterior putamen, whereas standard trained behaviors, recruited the posterior caudate, insula, and prefrontal regions. A cortical network orchestrated habit expression (right S1 with the left anterior insula/prefrontal areas) while also implicating basal ganglia when overriding habits (left premotor with the putamen). Importantly, stimulation of the left premotor played a causal role in habit control, enhancing performance across both the training and devaluation phases. Our findings reveal an interaction between habitual and goal-directed brain regions, highlighting shared neural dynamics when overriding habitual behaviors.

neuroscience↗

bioRxiv2024

Chromatin Remodelling in Damaged Intestinal Crypts Orchestrates Redundant TGFβ and Hippo Signalling to Drive Regeneration

Cell state dynamics underlying regeneration are under-characterized. Intestinal damage prompts reprogramming into revival stem cells (revSCs) that reconstitute Lgr5+ intestinal stem cells (ISCs). Single nuclei multiomics of chromatin accessibility and transcriptomes during regeneration from irradition showed revSCs display epigenetic profiles shared with ISCs and differentiated lineages. Furthermore, while revSC genes are accessible throughout homeostatic epithelia, damage-induced global alterations in crypt and revSC chromatin converge on TGF{beta}, as well as Hippo pathways. We show TGF{beta} directly induces functional revSCs and demonstrate individual revSCs form organoids with reconstituted Lgr5+ ISCs. Despite this, loss of TGF{beta} signalling yielded mild regenerative defects. In contrast, interference in both Hippo and TGF{beta} abolished revSCs, precluded generation of new ISCs and led to rapid intestinal collapse. Thus, the epithelium is poised to engage the revSC regenerative program that relies on crypt-localized, transient morphogen cues that function in a compensatory manner to support intestinal regeneration.

molecular biology↗

bioRxiv2023

Temporally organized representations of reward and risk in the human brain

AO_SCPLOWBSTRACTC_SCPLOWThe value and uncertainty associated with choice alternatives constitute critical features along which decisions are made. While the neural substrates supporting reward and risk processing have been investigated, the temporal organization by which these computations are encoded remains elusive. Here we leverage the high spatiotemporal precision of intracranial electroencephalography (iEEG) to uncover how representations of decision-related computations unfold in time. We present evidence of locally distributed representations of reward and risk variables that are temporally organized across multiple regions of interest. Reward outcome representations across wide-spread regions follow a temporally cascading order along the anteroposterior axis of the brain. In contrast, expected value can be decoded from multiple regions at the same time, and error signals in both reward and risk domains reflect a mixture of sequential and parallel encoding. We highlight the role of the anterior insula in generalizing between reward prediction error (RePE) and risk prediction error (RiPE), within which the encoding of RePE in the distributed iEEG signal predicts RiPE. Together our results emphasize the utility of uncovering temporal dynamics in the human brain for understanding how computational processes critical for value-based decisions under uncertainty unfold.

neuroscience↗

bioRxiv2021

Novelty and uncertainty interact to regulate the balance between exploration and exploitation in the human brain.

Recent evidence suggests that both novelty and uncertainty act as potent features guiding exploration. However, these variables are often conflated with each other experimentally, and an understanding of how these attributes interact to regulate the balance between exploration and exploitation has proved elusive. Using a novel task designed to decouple stimulus novelty and estimation uncertainty, we identify separable behavioral and neural mechanisms by which exploration is colored. We show that uncertainty was avoided except when the information gained through exploration could be reliably exploited in the future. In contrast, and contrary to existing theory, novel options grew increasingly attractive relative to familiar counterparts irrespective of the opportunity to leverage their consequences and despite the uncertainty inherent to novel options. These findings led us to develop a formal computational framework in which uncertainty directed choice adapts to the prospective utility of exploration, while novel stimuli persistently draw favor as a result of inflated reward expectations biasing an exploitative strategy. Crucially, novelty is proposed to actively modulate uncertainty processing, effectively blunting the influence of uncertainty in shaping the subjective utility ascribed to novel stimuli. Both behavioral data and fMRI activity sampled from the ventromedial prefrontal cortex, frontopolar cortex and ventral striatum validate this model, thereby establishing a computational account that can not only explain behavior but also shed light on the functional contribution of these key brain regions to the exploration/exploitation trade-off. Our results point to multiple strategies and neural substrates charged with balancing the explore/exploit dilemma, with each targeting distinct aspects of the decision problem to foster a manageable decomposition of an otherwise intractable task.

neuroscience↗

bioRxiv2018

Contextual Influences on Value-based Choice

Biases in choice behavior are shaped by both immediately encountered cues as well as the background context in which these cues are embedded. Here we examine the mechanisms that underlie the integration of contextual and cue information, and the manner in which these sources of information shape behavior. We demonstrate contextual influence on choice dissociated from cue information using a value-based multi-alternative choice task while recording neural activity using electroencephalography. Consistent with work on negativity biases, we show that contextual attributes related to loss, reflected along central-parietal sites in the gamma (30-59 Hz) frequency range, are prioritized and drive behavior to prevent loss. We employ a multi-alternative sequential sampling computational model to show that contextual and cue information are integrated through the decision process to shape choice responses, and link this integrative process to a neural signature in the gamma frequency band.

neuroscience↗

bioRxiv2017

Differential spatiotemporal representations along the hippocampal long axis in humans

Increased place field size and signal autocorrelation along the dorsoventral hippocampal axis in rodents are considered a fundamental aspect of hippocampal organization, yet such evidence is lacking in humans. Using fMRI, we report corresponding evidence of increasing neural similarity from posterior to anterior hippocampus (dorsoventral homologues) in humans. These findings help account for observed shifting in representational granularity, from global context (anterior) to local details (posterior), along the hippocampal axis.

neuroscience↗

bioRxiv2017

Decomposing the neural pathways mediating value-based choice

Understanding the neural implementation of value-based choice has been an important focus of neuroscience for several decades. Although a consensus has emerged regarding the brain regions involved, disagreement persists regarding precise regional functions and how value information flows between value-based choice regions.\n\nIn the current study, we isolate neural activity related to decision-making using a gambling task where expected gains and losses are dissociated from the received outcomes of choices. We apply multilevel modelling and mediation analysis to formally test whether brain regions identified as part of the value-based choice network mediate between perceptions of expected value and choices to take or pass a gamble.\n\nA critical function in decision-making is accruing and representing value information to drive choice. Several regions have been assigned this role, including ventromedial prefrontal (vmPFC) and posterior parietal cortex (PPC), and the ventral striatum (VStr). The implied chain of events is one where regions that support the process of gathering relevant information mediate the relationship between choice and representations of value in other brain regions. Here, we formally test whether distinct brain regions express interregional mediation consistent with this chain of processes.\n\nWe observe that activity in vmPFC does not predict choice, but rather is highly associated with outcome evaluation. By contrast, both PPC and VStr (bilaterally) mediate between expected value and choice. Interregional mediation analyses reveal that VStr fully mediates between PPC and choice. Together these results suggest that VStr, and not vmPFC nor PPC, functions as an important driver of late stage choice.\n\nSignificance StatementMaking choices that maximize gain and minimize loss is critical for success. Our paradigm and analytic approach allowed isolation of choice-related neural signals from outcome-related signals. The vmPFC is involved at outcome rather than at choice. Isolating choice-related neural activity, we formally demonstrate that VStr and PPC mediate between expected value and choice. Our approach adds significant innovation by using generalized multilevel modelling to predict behavior with concurrent neural activity and formally testing the fully mediated pathway from stimulus through neural activity to behavior. Applying interregional multilevel mediation analysis, we demonstrate that ventral striatum comprises a final, critical step in processing value-based choice, mediating the relationship between value representation and choice.

neuroscience↗