Biology subjects

Wu, S.-W.

Publications and source records attributed to Wu, S.-W..

5 recordsLinked to original sources

bioRxiv2023

System Neglect and the Neurocomputational Substrates for Over- and Underreactions to Change

AO_SCPLOWBSTRACTC_SCPLOWThe world constantly changes, with the underlying state of the world shifting from one regime to another. The ability to detect a regime shift, such as the onset of a pandemic or the end of a recession, significantly impacts individual decisions as well as governmental policies. However, determining whether a regime has changed is usually not obvious, as signals are noisy and reflective of the volatility of the environment. We designed an fMRI paradigm that examines a stylized regime-shift detection task. Human participants showed systematic over- and underreaction: Overreaction was most commonly seen when signals were noisy but when environments were stable and change is possible but unlikely. By contrast, underreaction was observed when signals were precise but when environments were unstable and hence change was more likely. These behavioral signatures are consistent with the system-neglect computational hypothesis, which posits that sensitivity or lack thereof to system parameters (noise and volatility) is central to these behavioral biases. Guided by this computational framework, we found that individual subjects sensitivity to system parameters were represented by two distinct brain networks. Whereas a frontoparietal network selectively represented individuals sensitivity to signal noise but not environment volatility, the ventromedial prefrontal cortex (vmPFC) showed the opposite pattern. Further, these two networks were involved in different aspects of regime-shift computations: while vmPFC correlated with subjects beliefs about change, the frontoparietal network represented the strength of evidence in favor of regime shifts. Together, these results suggest that regime-shift detection recruits belief-updating and evidence-evaluation networks and that under- and overreactions arise from how sensitive these networks are to the system parameters. SO_SCPLOWIGNIFICANCEC_SCPLOW SO_SCPLOWTATEMENTC_SCPLOWJudging whether the world has changed, from the onset of a market boom to the end of a pandemic, is ubiquitous. The ability to detect regime shifts not only impacts individual decisions but also governmental policies. However, these judgments are hard to make because the signals we receive are noisy and reflective of the volatility of the environment. We find that people overreact to changes when they receive noisy signals in stable environments, but underreact when facing precise signals in unstable environments. Under- and overreactions can be read out by distinct brain networks according to their sensitivity in responding to different environmental parameters that impact regime changes. This suggests that parameter selectivity at the network level guides regime-shift detection.

neuroscience↗

bioRxiv2022

Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex

During economic choice, evidence from monkeys and humans suggest that activity in the orbitofrontal cortex (OFC) encodes the subjective values of options under consideration. Monkey data further suggests that value representations in the OFC are context dependent, representing subjective value in a way influenced by the decision makers recent experience. Using stereo electroencephalography (sEEG) in human subjects, we investigated the neural representations of both past and present subjective values in the OFC, insula, cingulate and parietal cortices, amygdala, hippocampus and striatum. Patients with epilepsy (n=20) reported their willingness to pay--a measure of subjective value--for snack food items in a Becker-DeGroot-Marschack (BDM) auction task. We found that the high frequency power (gamma and high-gamma bands) in the OFC positively correlated with the current subjective value but negatively correlated with the subjective value of the good offered on the last trial - a kind of temporal context dependency not yet observed in humans. These representations were observed at both the group level (across electrode contacts and subjects) and at the level of individual contacts. Noticeably, the majority of significant contacts represented either the present or past subjective value, but not both. A dynamic dimensionality-reduction analysis of OFC population trajectories suggested that the past trial begin to influence activity early in the current trial after the current offer was revealed, and that these two properties--current and past subjective values--dominate the electrophysiological signals. Together, these findings indicate that information about the value of the past and present rewards are simultaneously represented in the human OFC, and offer insights into the algorithmic structure of context-dependent computation during human economic choice.

neuroscience↗

bioRxiv2019

Base-rate neglect and neural computations for subjective weight in probabilistic inference

AO_SCPLOWBSTRACTC_SCPLOWHumans show systematic biases when estimating probability of uncertain events. Base-rate neglect is a well-known bias that describes the tendency to underweight information from the past relative to the present. In this study, we characterized base-rate neglect at the computational and neural implementation levels. At the computational level, we established that base-rate neglect arises from insufficient adjustment to weighting prior information in response to changes in prior variability. At the neural implementation level, we found that orbitofrontal cortex (OFC) and medial prefrontal cortex (mPFC) represent subjective weighting of information that reflects base-rate neglect. Critically, both subjective-weight and subjective-value signals that guide choice were found in mPFC. However, subjective-weight signals preceded subjective-value signals. These results indicate that when facing multiple sources of information, estimation bias such as base-rate neglect arises from information weighting computed in OFC and mPFC, which directly contributes to subjective-value computations that guide decisions under uncertainty.\n\nSO_SCPLOWIGNIFICANCEC_SCPLOW SO_SCPLOWTATEMENTC_SCPLOWFacing uncertainty, estimating the probability of different potential outcomes carries significant weight in affecting how we act and decide. Decades of research show that humans are prone to giving biased estimation but it remains elusive how these biases arise in the brain. We focus on base-rate neglect, a well-known bias in probability estimation and find that it is tightly associated with activity in the medial prefrontal cortex and orbitofrontal cortex. These regions represent the degree to which human participants weigh different sources of information, suggesting that base-rate neglect arises from information-weighting computations in the brain. As technology provides us the opportunity to seek and gather information at an ever-increasing pace, understanding information-weighting and its biases also carry important policy implications.

neuroscience↗

bioRxiv2019

Context-dependent probability estimation and its neurocomputational substrates

Many decisions rely on how we evaluate potential outcomes associated with the options under consideration and estimate their corresponding probabilities of occurrence. Outcome valuation is subjective as it requires consulting internal preferences and is sensitive to context. In contrast, probability estimation requires extracting statistics from the environment and therefore imposes unique challenges to the decision maker. Here we show that probability estimation, like outcome valuation, is subject to context effects that bias probability estimates away from other stimuli present in the same context. However, unlike valuation, these context effects appeared to be scaled by estimated uncertainty, which is largest at intermediate probabilities. BOLD imaging showed that patterns of multivoxel activity in dorsal anterior cingulate cortex (dACC) and ventromedial prefrontal cortex (VMPFC) predicted individual differences in context effects on probability estimate. These results establish VMPFC as the neurocomputational substrate shared between valuation and probability estimation and highlight the additional involvement of dACC that can be uniquely attributed to probability estimation. As probability estimation is a required component of computational accounts from sensory inference to higher cognition, the context effects found here may affect a wide array of cognitive computations.\n\nHighlightsO_LIContext impacts subjective estimates on reward probability - Stimuli carrying greater variance are more strongly affected by other stimuli present in the same context\nC_LIO_LIThis phenomenon can be explained by reference-dependent computations that are gated by reward variance\nC_LIO_LIMultivoxel patterns of dACC and VMPFC activity predicts individual differences in context effect on probability estimate\nC_LI

neuroscience↗

bioRxiv2018

Dynamic combination of sensory and reward information under time pressure

When making choices, collecting more information is beneficial but comes at the cost of sacrificing time that could be allocated to making other potentially rewarding decisions. To investigate how the brain balances these costs and benefits, we conducted a series of novel experiments in humans and simulated various computational models. Under six levels of time pressure, subjects made decisions either by integrating sensory information over time or by dynamically combining sensory and reward information over time. We found that during sensory integration, time pressure reduced performance as the deadline approached, and choice was more strongly influenced by the most recent sensory evidence. By fitting performance and reaction time with various models we found that our experimental results are more compatible with leaky integration of sensory information with an urgency signal or a decision process based on stochastic transitions between discrete states modulated by an urgency signal. When combining sensory and reward information, subjects spent less time on integration than optimally prescribed when reward decreased slowly over time, and the most recent evidence did not have the maximal influence on choice. The suboptimal pattern of reaction time was partially mitigated in an equivalent control experiment in which sensory integration over time was not required, indicating that the suboptimal response time was influenced by the perception of imperfect sensory integration. Meanwhile, during combination of sensory and reward information, performance did not drop as the deadline approached, and response time was not different between correct and incorrect trials. These results indicate a decision process different from what is involved in the integration of sensory information over time. Together, our results not only reveal limitations in sensory integration over time but also illustrate how these limitations influence dynamic combination of sensory and reward information.

neuroscience↗