bioRxiv Science⌕ Search

Biology subjects

Glimcher, P. W.

Publications and source records attributed to Glimcher, P. W..

3 recordsLinked to original sources

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↗

Input-Specific Inhibitory Plasticity Improves Decision Accuracy Under Noise

Inhibitory interneurons regulate excitability, information flow, and plasticity in neural circuits. Inhibitory synapses are also plastic and can be modified by changes in experience or activity, often together with changes to excitatory synapses. However, given the diversity of inhibitory cell types within the cerebral cortex, it is unclear if plasticity is similar for various inhibitory inputs or what the functional significance of inhibitory plasticity might be. Here we examined spike-timing-dependent plasticity of inhibitory synapses from four major subtypes of GABAergic cells onto layer 2/3 pyramidal cells in mouse auditory cortex. The likelihood of inhibitory potentiation varied across cell types, with somatostatin-positive (SST+) interneuron inputs exhibiting the most potentiation on average. A network simulation of perceptual decision-making revealed that plasticity of SST+-like inputs provided robustness from higher input noise levels to maintain decision accuracy. Differential plasticity at specific inhibitory inputs therefore may be important for network function and sensory perception.

neuroscience↗

Flexible control of representational dynamics in a disinhibition-based model of decision making

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.

neuroscience↗