Biology subjects

Grossman, C. D.

Publications and source records attributed to Grossman, C. D..

6 recordsLinked to original sources

bioRxiv2026

Choice-driven remapping of action- and stimulus-anchored value in human single neurons

Whether stimulus- and action-based choices rely on a shared neural architecture remains intensely debated. While lesion and fMRI studies show conflicting regional dissociation and overlap, the underlying single neuron substrates remain unknown. We recorded single neuron activity from the human ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), pre-supplementary motor area (preSMA), and amygdala during distinct action- and stimulus-based reward tasks. Prior to decision-making, neurons across all regions broadly encode value for both choice domains. However, choice commitment triggers domain segregation across the prefrontal cortex. While ACC and vmPFC neurons flexibly track both chosen actions and stimuli, they exhibit a double dissociation for chosen valuation: ACC neurons selectively maintain action-based values, whereas vmPFC neurons selectively maintain stimulus-based values. Conversely, preSMA neurons invariant to task domain track chosen action identity and value. These findings reveal how prefrontal networks transition from domain-general evaluation to domain-segregated choice execution.

neuroscience↗

bioRxiv2025

The representation and valuation of subgoals in the human brain during model-based hierarchical behavior

The human capacity to plan and perform long, complex sequences of behavior to achieve distant goals depends in part on a hierarchical organization that divides behavior into structured segments. Such a mechanism requires the internal designation of certain states as subgoals to mark the successful implementation of a behavioral segment. How the brain represents subgoals over time and computes decision values as a function of subgoals is unknown. While most characterizations of hierarchical behavior lack knowledge of the environment, human decision-making also relies on planning with an internal model of the world. Consequently, it remains to be determined how the brain computes values of subgoals using model-based planning in order to drive hierarchical, model-based decisions. Using a sequential-subgoal decision-making task designed to evoke hierarchical, model-based behavior in combination with fMRI, we decoded a representation of the current subgoal in insula and ventromedial prefrontal cortex during decision-making that persisted over time-a critical, latent representation for computing values and orienting behavior in the correct sequence. Using a model-based, hierarchical reinforcement learning model, we also found key decision signals based on values from the model in several regions of frontal cortex. These findings thereby shed light on the neural correlates of subgoal representation and illustrate how value signals can be computed on the basis of these subgoals and knowledge of the environment structure.

neuroscience↗

bioRxiv2023

Serotonin predictively encodes value

The in vivo responses of dorsal raphe nucleus (DRN) serotonin neurons to emotionally-salient stimuli are a puzzle. Existing theories centred on reward, surprise, or uncertainty individually account for some aspects of serotonergic activity but not others. Here we find a unifying perspective in a biologically-constrained predictive code for cumulative future reward, a quantity called state value in reinforcement learning. Through simulations of trace conditioning experiments common in the serotonin literature, we show that our theory, called value prediction, intuitively explains phasic activation by both rewards and punishments, preference for surprising rewards but absence of a corresponding preference for punishments, and contextual modulation of tonic firing--observations that currently form the basis of many and varied serotonergic theories. Next, we re-analyzed data from a recent experiment and found serotonin neurons with activity patterns that are a surprisingly close match: our theory predicts the marginal effect of reward history on population activity with a precision <<0.1 Hz neuron-1. Finally, we directly compared against quantitative formulations of existing ideas and found that our theory best explains both within-trial activity dynamics and trial-to-trial modulations, offering performance usually several times better than the closest alternative. Overall, our results show that previous models are not wrong, but incomplete, and that reward, surprise, salience, and uncertainty are simply different faces of a predictively-encoded value signal. By unifying previous theories, our work represents an important step towards understanding the potentially heterogeneous computational roles of serotonin in learning, behaviour, and beyond.

neuroscience↗

bioRxiv2021

Norepinephrine Potentiates and Serotonin Depresses Visual Cortical Responses by Transforming Eligibility Traces

Reinforcement allows organisms to learn which stimuli predict subsequent biological relevance. Hebbian mechanisms of synaptic plasticity are insufficient to account for reinforced learning because neuromodulators signaling biological relevance are delayed with respect to the neural activity associated with the stimulus. A theoretical solution is the concept of eligibility traces (eTraces), silent synaptic processes elicited by activity which upon arrival of a neuromodulator are converted into a lasting change in synaptic strength. Previously we demonstrated in visual cortical slices the Hebbian induction of eTraces and their conversion into LTP and LTD by the retroactive action of norepinephrine and serotonin Here we show in vivo in V1 that the induction of eTraces and their conversion to LTP/D by norepinephrine and serotonin respectively potentiates and depresses visual responses. We also show that the integrity of this process is crucial for ocular dominance plasticity, a canonical model of experience-dependent plasticity.

neuroscience↗

bioRxiv2020

Serotonin neurons modulate learning rate through uncertainty

Regulating how fast to learn is critical for flexible behavior. Learning about the consequences of actions should be slow in stable environments, but accelerate when that environment changes. Recognizing stability and detecting change is difficult in environments with noisy relationships between actions and outcomes. Under these conditions, theories propose that uncertainty can be used to modulate learning rates ("meta-learning"). We show that mice behaving in a dynamic foraging task exhibit choice behavior that varied as a function of two forms of uncertainty estimated from a meta-learning model. The activity of dorsal raphe serotonin neurons tracked both types of uncertainty in the foraging task, as well as in a dynamic Pavlovian task. Reversible inhibition of serotonin neurons in the foraging task reproduced changes in learning predicted by a simulated lesion of meta-learning in the model. We thus provide a quantitative link between serotonin neuron activity, learning, and decision making.

neuroscience↗

bioRxiv2020

Parallel social information processing circuits are differentially impacted in autism

Parallel processing circuits are thought to dramatically expand the network capabilities of the nervous system. Magnocellular and parvocellular oxytocin neurons have been proposed to subserve two parallel streams of social information processing, which allow a single molecule to encode a diverse array of ethologically distinct behaviors, although to date direct evidence to support this hypothesis is lacking. Here we provide the first comprehensive characterization of magnocellular and parvocellular oxytocin neurons, validated across anatomical, projection target, electrophysiological, and transcriptional criteria. We next used novel multiple feature selection tools in Fmr1 KO mice to provide direct evidence that normal functioning of the parvocellular but not magnocellular oxytocin pathway is required for autism-relevant social reward behavior. Finally, we demonstrate that autism risk genes are uniquely enriched in parvocellular oxytocin neurons. Taken together these results provide the first evidence that oxytocin pathway specific pathogenic mechanisms account for social impairments across a broad range of autism etiologies. One Sentence SummaryPathoclisis of parvocellular oxytocin neurons plays an important role in the pathogenesis of social impairments in autism.

neuroscience↗