Bo Shen

Noise is a fundamental problem for information processing in neural systems. In decision-making, noise is thought to cause stochastic errors in choice. However, little is known about how noise arising from different sources may contribute differently to value coding and choice behaviors. Here, we examine how noise arising early versus late in the decision process differentially impacts context-dependent choice behavior. We find in model simulations that under early noise, contextual information enhances choice accuracy, while under late noise, context degrades choice accuracy. Furthermore, we verify these opposing predictions in experimental human choice behavior. Manipulating early and late noise – by inducing uncertainty in option values and controlling time pressure – produces dissociable positive and negative context effects. These findings reconcile controversial experimental findings in the literature, suggesting a unified mechanism for context-dependent choice. More broadly, these findings highlight how different sources of noise can interact with neural computations to differentially modulate behavior.

When deciding from whom to proactively seek help in adverse situations, one might take into account both the potential cost of being rejected (rejection cost) and the potential cost of being unable to repay other’s favor (repayment cost). Little is known about how these two social costs arise, compete and generate decisions in real-time and how their temporal dynamics is modulated by situational factors (e.g., the extra benefit after securing help and the initial benefit before seeking help). We address this question by developing a mouse-tracking-based interpersonal task and applying computational modeling. In the task, when facing large or small gain/loss of endowment, participants may seek help, by moving a mouse cursor from the bottom-center to the upper left or right box on the screen, from one of the two co-players. The probability of being rejected by each co-player and the probability of being able to repay were parametrically manipulated and presented in each box. The extra benefit of securing help was manipulated and indicated before mouse moving was executed. Results showed that the processing of rejection cost was overall earlier than that of repayment cost. This temporal asynchrony was enlarged as a function of extra benefit when initial endowment was small, and was weakened when initial endowment was large. The extents of temporal asynchrony could predict participants’ final choice preferences. These findings provide mechanistic explanations for the generations and adjustments of help-seeking decisions from a temporal dynamical perspective, and provide avenues to understanding the cooperative behaviors that follow help-seeking.

Noise is a fundamental problem for information processing in neural systems. In decision-making, noise is assumed to have a primary role in errors and stochastic choice behavior. However, little is known about how noise arising from different sources contributes to value coding and choice behaviors, especially when it interacts with neural computation. Here we examine how noise arising early versus late in the choice process differentially impacts context-dependent choice behavior. We found in model simulations that early and late noise predict opposing context effects: under early noise, contextual information enhances choice accuracy; while under late noise, context degrades choice accuracy. Furthermore, we verified these opposing predictions in experimental human choice behavior. Manipulating early and late noise – by inducing uncertainty in option values and controlling time pressure – produced dissociable positive and negative context effects. These findings reconcile controversial experimental findings in the literature reporting either context-driven impairments or improvements in choice performance, suggesting a unified mechanism for context-dependent choice. More broadly, these findings highlight how different sources of noise can interact with neural computations to differentially modulate behavior. Significance The current study addresses the role of noise origin in decision-making, reconciling controversies around how decision-making is impacted by context. We demonstrate that different types of noise – either arising early during evaluation or late during option comparison - leads to distinct results: with early noise, context enhances choice accuracy, while with late noise, context impairs it. Understanding these dynamics offers potential strategies for improving decision-making in noisy environments and refining existing neural computation models. Overall, our findings advance our understanding of how neural systems handle noise in essential cognitive tasks, suggest a beneficial role for contextual modulation under certain conditions, and highlight the profound implications of noise structure in decision-making.

Inhibition is crucial for brain function, regulating network activity by balancing excitation and implementing gain control. Recent evidence suggests that beyond simply inhibiting excitatory activity, inhibitory neurons can also shape circuit function through disinhibition. While disinhibitory circuit motifs have been implicated in cognitive processes, including learning, attentional selection, and input gating, the role of disinhibition is largely unexplored in the study of decision-making. Here, we show that disinhibition provides a simple circuit motif for fast, dynamic control of network state and function. This dynamic control allows a disinhibition-based decision model to reproduce both value normalization and winner-take-all dynamics, the two central features of neurobiological decision-making captured in separate existing models with distinct circuit motifs. In addition, the disinhibition model exhibits flexible attractor dynamics consistent with different forms of persistent activity seen in working memory. Fitting the model to empirical data shows it captures well both the neurophysiological dynamics of value coding and psychometric choice behavior. Furthermore, the biological basis of disinhibition provides a simple mechanism for flexible top-down control of the network states, enabling the circuit to capture diverse task-dependent neural dynamics. These results suggest a biologically plausible unifying mechanism for decision-making and emphasize the importance of local disinhibition in neural processing.

Two behavioral motivations co-exist in transgressors following an interpersonal transgression – approaching and compensating the victim, and avoiding the victim. Little is known about how these motivations arise, compete, and drive transgressors’ decisions. The present study adopted a social interaction task to manipulate participants’ (i.e., the transgressor) responsibility for another’s (i.e., the victim) monetary loss and measure the participants’ tradeoff between compensating the victim and avoiding face-to-face interactions with the victim. Following each transgression, participants used a computer mouse to choose between two options differing in the amount of compensation to the victim and the probability of face-to-face contact with the victim. Results showed that as participants’ responsibility increased, (1) the decision weights on contact avoidance relative to compensation increased, and (2) the onset of the contact-avoidance attribute was expedited and that of the compensation attribute was delayed. These results demonstrate how competing social motivations following transgression evolve and determine social decision-making and shed a light on how motivations modulate the dynamics of decision-making in general.

Current models utilize two primary circuit motifs to replicate neurobiological decision making. Recurrent gain control implements normalization-driven relative value coding, while recurrent excitation and non-selective pooled inhibition together implement winner-take-all (WTA) dynamics. Despite evidence for concurrent valuation and selection computations in individual brain regions, existing models focus selectively on either normalization or WTA dynamics and how both arise in a single circuit architecture is unknown. Here we show that a novel hybrid motif unifies both normalized representation and WTA competition, with dynamic control of circuit state governed by local disinhibition. In addition to capturing empirical psychometric and chronometric data, the model produces persistent activity consistent with working memory. Furthermore, the biological basis of disinhibition provides a simple mechanism for flexible top-down control of network states, enabling the circuit to capture diverse task-dependent neural dynamics. These results suggest a new biologically plausible mechanism for decision making and emphasize the importance of local disinhibition in neural processing.

Humans are averse to both having less (i.e., disadvantageous inequity aversion) and having more than others (i.e., advantageous inequity aversion). However, the social-affective traits that drive individual differences in inequity aversion (IA) are not well understood. Here, by combining a modified Dictator Game and a computational model, we found in a sample of incarcerated adolescents (N = 67) that callous-unemotional traits were specifically associated with low advantageous but not disadvantageous IA. We replicated and extended the finding in a large- scale university student sample (N = 2,250) by adopting a dimensional approach to social- affective trait measures. We showed that advantageous IA was strongly and negatively associated with a trait dimension characterized by callousness and lack of social emotions (e.g., guilt and compassion). A supportive family environment negatively correlated with this trait dimension and positively with advantageous IA. These results identify a core set of social- affective dimensions specifically associated with advantageous IA.

Social norms provide a set of expectations regarding context-specific appropriate behavior that aids in navigating social environments ([Bicchieri, 2006][1]). Classic studies have demonstrated that people tend to conform to these norms even at the cost of their own interest ([Fehr and Fischbacher,