Biology subjects

Wallis, J. D.

Publications and source records attributed to Wallis, J. D..

10 recordsLinked to original sources

bioRxiv2026

Effects of overt and covert attention on decision-making dynamics in prefrontal cortex

Value-based decision-making is a dynamic and idiosyncratic process which requires appraising the value of options and comparing the values to select the best choice. An emerging view of orbitofrontal cortex (OFC) is that it achieves this by representing values serially during deliberation, alternating back-and-forth between transient states that encode the value of different options. While the time spent in each value state is known to reflect choice behavior, the source of the alternating dynamics remains unclear. One possibility is that fluctuations in value may be driven by attentional shifts between the choice options. Conversely, value dynamics in OFC may be generated locally, enabling OFC value signals to influence decision-making independently from attention. To test these hypotheses, we recorded from OFC and lateral prefrontal cortex (LPFC), a major attentional area in prefrontal cortex, to determine whether their population-level activity correlated in a manner consistent with crosstalk between neuronal systems involved in value and spatial attention. We found that OFC and LPFC selectively encoded option values and spatial locations, respectively, reflecting their specialized roles in cognition. Despite this functional dissociation, both OFC and LPFC dynamics were strongly affected by overt attention: which caused the value and spatial location of the fixated option to be represented at the same time. Additionally, fluctuations in the encoding strength of value in OFC and space in LPFC were temporally correlated above and beyond the effect of gaze, reflecting the effect of covert attention.

neuroscience↗

bioRxiv2026

Learning to select computations in recurrent neural circuits

Two hallmarks of biological computation are its flexibility and efficiency. These features are often attributed to cognitive control processes that balance external utility against computational cost. However, how the brain could implement such adaptive control remains unknown. Here, we provide one possible answer by combining the computational theory of rational meta-reasoning with a meta-learning algorithm recently proposed as a model of prefrontal cortex. This yields a recurrent neural network model that learns to select computations. In simple choice tasks, the model approximates the algorithms and representations of optimal symbolic models and reproduces neural dynamics observed in macaque orbitofrontal cortex. In multi-step planning tasks, the model replicates key behavioral signatures of human planning strategies and captures human neural dynamics associated with step-by-step mental simulation. Our framework unifies meta-reasoning and meta-learning by showing that learning to reason can be understood as learning to learn from information generated by ones own cognitive operations, providing a mechanistic account of how adaptive control of thought can be implemented in neural systems.

neuroscience↗

bioRxiv2025

Selective engagement of the primate orbitofrontal cortex during value-based but not perceptual decisions

A fundamental question in neuroscience is whether the brain uses specialized sub-systems for different types of decisions or relies on a unified decision-making network. The orbitofrontal cortex (OFC) provides an ideal test case for this question: it has a well-established role in value-based decisions but it remains unknown whether this reflects functional specialization or participation in a broader, general decision network. To distinguish between these possibilities, we used Neuropixels to monitor large ensembles of OFC neurons as a monkey performed both value-based and perceptual decision tasks. Consistent with prior reports, OFC was robustly engaged during value-based decisions. In contrast, OFC was minimally engaged during perceptual decisions, with no significant encoding of task parameters at either the single neuron or population level. This highlights the functional specialization of the OFC for value-based decisions and suggests that the different cognitive demands underlying different types of decisions recruit distinct neural circuits.

neuroscience↗

bioRxiv2024

Neuronal representation of the decisional reference point in monkeys

The decisional reference point serves as a hidden benchmark for evaluating options in decision-making. Despite extensive behavioral evidence for the existence of the reference point, its neural instantiation remains unclear. To identify reference point encoding at both the single-neuron and population levels, we analyzed neural activity from macaques performing a wealth accumulation task that dissociated objective reward values from the reference point. Across six frontal regions, we found that reference-related signals were broadly distributed at the single-neuron level. However, at the population level, only the ventral bank of the anterior cingulate cortex (vbACC) encoded the reference point significantly. In contrast, the dorsal bank of ACC and dorsolateral prefrontal cortex showed population-level encoding of reference-dependent subjective value signals. The temporal sequence of these signals and their known anatomical connectivity hints at a dedicated neural circuit for reference-dependence, with the vbACC potentially serving as a global source of reference point signal modulating activity in downstream value-encoding regions. SIGNIFICANCEAll experiences are evaluated relative to an internal benchmark called the reference point. Despite its central role in all modern theories of decision-making, its neural basis has remained unclear. In this study, using dense single-neuron recordings from macaque frontal cortex, we found that only the ventral bank of the anterior cingulate cortex encoded the reference point consistently at the population level. We also found population-level reference-dependent value signals representing anticipated and earned rewards in the dorsal bank of the anterior cingulate cortex and the dorsolateral prefrontal cortex, respectively. Both were inversely modulated by the reference point as predicted by theory. These findings together with known anatomical connectivity support the existence of a dedicated neural circuit for reference-dependent valuation.

neuroscience↗

bioRxiv2023

Context-dependent decision-making in the primate hippocampal-prefrontal circuit

What is good in one scenario might be bad in another. Despite the ubiquity of such contextual reasoning in everyday choice, how the brain flexibly utilizes different valuation schemes across contexts remains unknown. We addressed this question by monitoring neural activity from the hippocampus (HPC) and orbitofrontal cortex (OFC) of two monkeys performing a state-dependent choice task. We found that HPC neurons encoded state information as it became available and then, at the time of choice, relayed this information to OFC via theta synchronization. During choice, OFC represented value in a state-dependent manner: many OFC neurons uniquely coded for value in only one state but not the other. This suggests a functional dissociation whereby HPC encodes contextual information that is broadcast to OFC via theta synchronization to select a state-appropriate value subcircuit, thus allowing for contextual reasoning in value-based choice.

neuroscience↗

bioRxiv2023

Distinct neural representations during a brain-machine interface and manual reaching task in motor cortex, prefrontal cortex, and striatum

Although brain-machine interfaces (BMIs) are directly controlled by the modulation of a select local population of neurons, distributed networks consisting of cortical and subcortical areas have been implicated in learning and maintaining control. Previous work in rodent BMI has demonstrated the involvement of the striatum in BMI learning. However, the prefrontal cortex has been largely ignored when studying motor BMI control despite its role in action planning, action selection, and learning abstract tasks. Here, we compare local field potentials simultaneously recorded from the primary motor cortex (M1), dorsolateral prefrontal cortex (DLPFC), and the caudate nucleus of the striatum (Cd) while nonhuman primates perform a two-dimensional, self-initiated, center-out task under BMI control and manual control. Our results demonstrate the presence of distinct neural representations for BMI and manual control in M1, DLPFC, and Cd. We find that neural activity from DLPFC and M1 best distinguish between control types at the go cue and target acquisition, respectively. We also found effective connectivity from DLPFC[->]M1 throughout trials across both control types and Cd[->]M1 during BMI control. These results suggest distributed network activity between M1, DLPFC, and Cd during BMI control that is similar yet distinct from manual control.

neuroscience↗

bioRxiv2022

Abstraction of reward context facilitates relative reward coding in dorsal and ventral anterior cingulate cortex

The anterior cingulate cortex (ACC) is believed to be involved in many cognitive processes, including linking goals to actions and tracking decision-relevant contextual information. ACC neurons robustly encode expected outcomes, but how this relates to putative functions of ACC remains unknown. Here, we approach this question from the perspective of population codes by analyzing neural spiking data in the ventral and dorsal banks of the ACC in monkeys trained to perform a stimulus-motor mapping task. We found that neural populations favor a representational geometry that emphasizes contextual information, while facilitating the independent, abstract representation of multiple task-relevant variables. In addition, trial outcomes were primarily encoded relative to task context, suggesting that the population structures we observe could be a mechanism allowing feedback to be interpreted in a context-dependent manner. Together, our results point to a prominent role for ACC in context-setting and relative interpretation of outcomes, facilitated by abstract, or "untangled," representations of task variables. Author SummaryThe ability to interpret events in light of the current context is a critical facet of higher-order cognition. The anterior cingulate cortex is suggested to be important for tracking information about current contexts, while alternate views hold that its function is more related to the motor system and linking goals to appropriate motor responses. Here, we evaluated these two possibilities by recording anterior cingulate neurons from monkeys performing a stimulus-motor mapping task in which compound cues both defined the current reward context and instructed appropriate motor responses. By analyzing geometric properties of neural population activity, we found that the ACC prioritized context information, representing it as a dominant, abstract concept. Ensuing trial outcomes were then coded relative to these contexts, suggesting an important role for these representations in context-dependent evaluation. Such mechanisms may be critical for the abstract reasoning and generalization characteristic of biological intelligence.

neuroscience↗

bioRxiv2020

Hippocampal neurons construct a map of an abstract value space

The hippocampus is thought to encode a cognitive map, a structural organization of knowledge about relationships in the world. Place cells, spatially selective hippocampal neurons that have been extensively studied in rodents, are one component of this map, describing the relative position of environmental features. However, whether this map extends to abstract, cognitive information remains unknown. Using the relative reward value of cues to define continuous paths through an abstract value space, we show that single neurons in primate hippocampus encode this space through value place fields, much like a rodents place neurons encode paths through physical space. Value place fields remapped when cues changed, but also became increasingly correlated across contexts, allowing maps to become generalized. Our findings help explain the critical contribution of the hippocampus to value-based decision-making, providing a mechanism by which knowledge of relationships in the world can be incorporated into reward predictions for guiding decisions.

neuroscience↗

bioRxiv2020

Hybrid local and distributed coding in PMd/M1 provides separation and interaction of bilateral arm signals

Pronounced activity is observed in both hemispheres of the motor cortex during preparation and execution of unimanual movements. The organizational principles of bi-hemispheric signals and the functions they serve throughout motor planning remain unclear. Using an instructed-delay reaching task in monkeys, we identified two components in population responses spanning PMd and M1. A "dedicated" component, which segregated activity at the level of individual units, emerged in PMd during preparation. It was most prominent following movement when M1 became strongly engaged, and principally involved the contralateral hemisphere. In contrast to recent reports, these dedicated signals solely accounted for divergence of arm-specific neural subspaces. The other "distributed" component mixed signals for each arm within units, and the subspace containing it did not discriminate between arms at any stage. The statistics of the population response suggest two functional layers of the cortical network: one that spans both hemispheres for supporting preparatory and ongoing processes, and another that is predominantly housed in the contralateral hemisphere and specifies unilateral output.

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bioRxiv2017

Reconciling persistent and dynamic hypotheses of working memory coding in prefrontal cortex

Competing accounts propose that working memory (WM) is subserved either by persistent activity in single neurons or by dynamic (time-varying) activity across a neural population. Here we compare these hypotheses across four regions of prefrontal cortex (PFC) in a spatial WM task, where an intervening distractor indicated the reward available for a correct saccade. WM representations were strongest in ventrolateral PFC (VLPFC) neurons with higher intrinsic temporal stability (time-constant). At the population-level, although a stable mnemonic state was reached during the delay, this tuning geometry was reversed relative to cue-period selectivity, and was disrupted by the distractor. Single-neuron analysis revealed many neurons switched to coding reward, rather than maintaining task-relevant spatial selectivity until saccade. These results imply WM is fulfilled by dynamic, population-level activity within high time-constant neurons. Rather than persistent activity supporting stable mnemonic representations that bridge distraction, PFC neurons may stabilise a dynamic population-level process that supports WM.

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