Biology subjects

Hayden, B.

Publications and source records attributed to Hayden, B..

8 recordsLinked to original sources

bioRxiv2018

Orbitofrontal neuron ensembles contribute to inhibitory control

Stopping, or inhibition, is a form of self-control that is a core part of adaptive behavior. We hypothesize that inhibition commands originate, in part, from the orbitofrontal cortex (OFC). We recorded activity of OFC neurons in macaques performing a stop signal task. Decoding analyses revealed a clear difference in ensemble responses that distinguish successful from failed inhibition that begins after the stop signal and before the stop signal reaction time. We also found a different and unrelated ensemble pattern that distinguishes successful from failed stopping before the beginning of the trial. These signals were distinct from, and orthogonal to, value encoding, which was also observed in these neurons. The timing of the early and late signals was, respectively, consistent with the idea that OFC contributes both proactively and reactively to inhibition. These results support the view, inspired by anatomy, that OFC gathers diverse sensory inputs to compute early-stage executive signals.

neuroscience↗

bioRxiv2018

Overlapping neural processes for stopping and economic choice in orbitofrontal cortex

Economic choice and stopping are not traditionally treated as related phenomena. However, we were motivated by foraging models of economic choice to hypothesize that they may reflect similar neural processes occurring in overlapping brain circuits. We recorded neuronal activity in orbitofrontal cortex (OFC), while macaques performed a stop signal task interleaved with a structurally matched economic choice task. Decoding analyses show that OFC ensembles predict successful versus failed stopping both before the trial and immediately after the stop signal, even after controlling for value predictions. These responses indicate that OFC contributes both proactively and reactively to stopping. Moreover, OFC neurons engagement in one task positively predicted their engagement in the other. Finally, firing patterns that distinguished low from high value offers in the economic task distinguished failed and successful trials in the stopping task. These results endorse the idea that economic choice and inhibition may be subject to theoretical unification.

neuroscience↗

bioRxiv2018

Monkeys are Curious about Counterfactual Outcomes

While many non-human animals show basic exploratory behaviors, it remains unclear whether any animals possess human-like curiosity. We propose that human-like curiosity satisfies three formal criteria: (1) willingness to pay (or to sacrifice reward) to obtain information, (2) that the information provides no instrumental or strategic benefit (and the subject understands this), and (3) the amount the subject is willing to pay scales with the amount of information available. Although previous work, including our own, demonstrates that some animals will sacrifice juice rewards for information, that information normally predicts upcoming rewards and their ostensible curiosity may therefore be a byproduct of reinforcement processes. Here we get around this potential confound by showing that macaques sacrifice juice to obtain information about counterfactual outcomes (outcomes that could have occurred had the subject chosen differently). Moreover, willingness-to-pay scales with the information (Shannon entropy) offered by the counterfactual option. These results demonstrate human-like curiosity in non-human animals according to our strict criteria, which circumvent several confounds associated with less stringent criteria.

animal behavior and cognition↗

bioRxiv2018

On the flexibility of basic risk attitudes in monkeys

Monkeys and other animals appear to share with humans two risk attitudes predicted by prospect theory: an inverse-S-shaped probability weighting function and a steeper utility curve for losses than for gains. These findings suggest that such preferences are stable traits with common neural substrates. We hypothesized instead that animals tailor their preferences to subtle changes in task contexts, making risk attitudes flexible. Previous studies used a limited number of outcomes, trial types, and contexts. To gain a broader perspective, we examined two large datasets of male macaques risky choices: one from a task with real (juice) gains and another from a token task with gains and losses. In contrast to previous findings, monkeys were risk-seeking for both gains and losses (i.e. lacked a reflection effect) and showed steeper gain than loss curves (loss-seeking). Utility curves for gains were substantially different in the two tasks. Monkeys showed nearly linear probability weightings in one task and S-shaped ones in the other; neither task produced a consistent inverse-S-shaped curve. To account for these observations, we developed and tested various computational models of the processes involved in the construction of reward value. We found that adaptive differential weighting of prospective gamble outcomes could partially account for the observed differences in the utility functions across the two experiments and thus, provide a plausible mechanism underlying flexible risk attitudes. Together, our results support the idea that risky choices are flexibly constructed at the time of elicitation and place important constraints on neural models of economic choice.

neuroscience↗

bioRxiv2017

A neuronal theory of sequential economic choice

Principles derived from recent studies have begun to converge and point to a consensus for the neural basis of economic choice. These principles include the idea that evaluation is limited to the option within the focus of attention and that we accept or reject that option relative to the entire set of alternatives. Rejection leads attention to a new option, although it can later switch back to a previously rejected one. The referent of a value-coding neuron is dynamically determined by attention and not stably by labeled lines. Comparison results not from explicit competition between discrete representations, but from value-dependent changes in responsiveness. Consequently, comparison can occur within a single pool of neurons rather than by competition between two or more neuronal populations. Comparison may nonetheless occur at multiple levels (including premotor levels) simultaneously through a distributed consensus. This framework suggests a solution to a set of otherwise unresolved neuronal binding problems that result from the need to link options to values, comparisons to actions, and choices to outcomes.

neuroscience↗

bioRxiv2017

The foraging perspective on economic choice

Foraging theory offers an alternative foundation for understanding economic choice, one that sees economic choices as the outcome of psychological processes that evolved to help our ancestors search for food. Most of the choices encountered by foragers are between pursuing an encountered prey (accept) or ignoring it in favor of continued search (reject). Binary choices, which typically occur between simultaneously presented items, are special case, and are resolved through paired alternating accept-reject decisions limited by the narrow focus of attention. The foraging approach also holds out promise for helping to understand self-control and invites a reconceptualization of the mechanisms of binary choice, the relationship between choosing and stopping, and of the meaning of reward value.\n\nHighlightsO_LIForaging provides a basis for modeling economic choice based on adaptiveness\nC_LIO_LIForaging choices are accept-reject; foraging models interpret binary choice accordingly\nC_LIO_LIThe foraging view offers a different perspective on self-control decisions\nC_LIO_LIEconomic and stopping decisions may have a common basis\nC_LI

neuroscience↗

bioRxiv2016

Neuronal responses support a role for orbitofrontal cortex in cognitive set reconfiguration

We are often faced with the need to abandon no-longer beneficial rules and adopt new ones. This process, known as cognitive set reconfiguration, is a hallmark of executive control. Although cognitive functions like reconfiguration are most often associated with dorsal prefrontal structures, recent evidence suggests that the orbitofrontal cortex (OFC) may play an important role as well. We recorded activity of OFC neurons while rhesus macaques performed a version of the Wisconsin Card Sorting Task that involved a trial-and-error stage. OFC neurons demonstrated two types of switch-related activity, an early (switch-away) signal and a late (switch-to) signal, when the new task set was established. We also found a pattern of match modulation: a significant change in activity for the stimulus that matched the current rule (and would therefore be selected). These results extend our understanding of the executive functions of the OFC. They also allow us to directly compare OFC with complementary datasets we previously collected in ventral (VS) and dorsal (DS) striatum. Although both effects are observed in all three areas, the timing of responses aligns OFC more closely with DS than with VS.

neuroscience↗

bioRxiv2016

Robust mixture modeling reveals category-free selectivity in reward region neuronal ensembles

Classification of neurons into clusters based on their response properties is an important tool for gaining insight into neural computations. However, it remains unclear to what extent neurons fall naturally into discrete functional categories. We developed a Bayesian method that models the tuning properties of neural populations as a mixture of multiple types of task-relevant response patterns. We applied this method to data from several cortical and striatal regions in economic choice tasks. In all cases, neurons fell into only two clusters: one mixed-selectivity cluster containing all task-sensitive cells and another of no selectivity (i.e. pure noise) cells. The single cluster of task-sensitive cells argues against robust categorical tuning in these areas. The no selectivity cells were unanticipated; their identification allows for improved measurement of ensemble effects. Our findings provide a valuable tool for analysis of neural data and place strong constraints on neurocomputational models of choice and control.

neuroscience↗