Biology subjects

Paton, J. J.

Publications and source records attributed to Paton, J. J..

5 recordsLinked to original sources

bioRxiv2023

Dorsolateral striatum encodes a temporal basis for the organization of behavior

To behave adaptively, the brain must register temporal structure in the environment and use it to organize behavior. The dorsolateral striatum (DLS) integrates sensorimotor input, and is necessary for accurate timing and structuring behavior in general. However, if DLS provides the basis for mapping temporal features in the environment to behavior, its activity should predict variation in that mapping. A reanalysis of DLS population activity in rats comparing the duration of two sequentially presented vibratory stimuli revealed a striking correspondence between neural activity and behavior. Varying vibration intensity of the second stimulus induced systematic biases in temporal judgments, and corresponding biases in multiple features of DLS activity during stimulus presentation, including population coding of time. In contrast, the same intensity manipulations applied to the first stimulus affected neither behavior nor neural activity. Furthermore, neuronal response profiles were best described as a continuum, arguing against hypotheses where categories of responses, e.g., ramping activity, selectively underpin temporal processing. These data represent important additional evidence that striatal population dynamics support the organization of behavior by mapping temporal information to action.

neuroscience↗

bioRxiv2023

Dopamine neurons encode a multidimensional probabilistic map of future reward

Learning to predict rewards is a fundamental driver of adaptive behavior. Midbrain dopamine neurons (DANs) play a key role in such learning by signaling reward prediction errors (RPEs) that teach recipient circuits about expected rewards given current circumstances and actions. However, the algorithm that DANs are thought to provide a substrate for, temporal difference (TD) reinforcement learning (RL), learns the mean of temporally discounted expected future rewards, discarding useful information concerning experienced distributions of reward amounts and delays. Here we present time-magnitude RL (TMRL), a multidimensional variant of distributional reinforcement learning that learns the joint distribution of future rewards over time and magnitude using an efficient code that adapts to environmental statistics. In addition, we discovered signatures of TMRL-like computations in the activity of optogenetically identified DANs in mice during a classical conditioning task. Specifically, we found significant diversity in both temporal discounting and tuning for the magnitude of rewards across DANs, features that allow the computation of a two dimensional, probabilistic map of future rewards from just 450ms of neural activity recorded from a population of DANs in response to a reward-predictive cue. In addition, reward time predictions derived from this population code correlated with the timing of anticipatory behavior, suggesting the information is used to guide decisions regarding when to act. Finally, by simulating behavior in a foraging environment, we highlight benefits of access to a joint probability distribution of reward over time and magnitude in the face of dynamic reward landscapes and internal physiological need states. These findings demonstrate surprisingly rich probabilistic reward information that is learned and communicated to DANs, and suggest a simple, local-in-time extension of TD learning algorithms that explains how such information may be acquired and computed.

animal behavior and cognition↗

bioRxiv2020

Manipulation of striatal population dynamics using temperature warps judgment of time

The basal ganglia (BG) are thought to contribute to decision-making and motor control by influencing action selection based on consequences. These functions are critically dependent on timing information that can be extracted from the evolving state of neural populations in the striatum, the major input area of the BG. However, it is debated whether striatal activity underlies latent, dynamic decision processes or kinematics of overt movement. Here, we measured the impact of temperature on striatal population activity and the behavior of rats and compared the observed effects to neural activity and behavior collected in multiple versions of a temporal categorization task. Cooler temperatures caused dilation, and warmer temperatures contraction, of both neural activity and patterns of judgment in time, mimicking endogenous decision-related variability in striatal activity. However, temperature did not similarly affect movement kinematics. These data provide compelling evidence that the time course of evolving striatal population activity dictates the speed of a latent process that is used to guide choices, but not moment by moment kinematics. More broadly, they establish temporal scaling of population activity as a likely cause and not simply a correlate of timing behavior in the brain.

neuroscience↗

bioRxiv2020

Dorsolateral striatal circuits support broadly opponent aspects of action suppression and production

Imbalance between action suppression and production characterizes several neurological disorders of the basal ganglia (BG)1. Relatedly, two major circuits of the BG, the direct and indirect pathways, are hypothesized to function in opposition, promoting and suppressing actions, respectively2. Yet activity of neurons initiating the two pathways, striatal direct (dMSNs) and indirect (iMSNs) medium spiny neurons, appears to be positively correlated around movement, apparently contradicting direct-indirect functional opponency3. Here we show that while coactivation occurs during movement, action suppression produces systematic features of functional opponency between the two pathways. First, suppression produced elevated iMSN activity and diminished dMSN activity in dorsolateral striatum of mice. Second, as the need to suppress movements to one or the other side of the body evolved over time, so too did the relative levels of activity in the two hemispheres, and in opposite patterns in the two pathways. Lastly, optogenetic inhibition of dMSNs, but not iMSNs, slowed movements without affecting their likelihood, whereas inhibition of iMSNs, but not dMSNs, disrupted whether and when mice suppressed or produced particular actions. These data demonstrate large-scale opponency in the activity of neurons that initiate the direct and indirect pathways of the BG, but suggest distinct action-related functions of each pathway. Specifically, the data support a novel model of sensorimotor striatum wherein the direct pathway appears to be necessary for augmenting generalized movement vigor, and the indirect pathway for the proactive suppression of specific behaviors.

neuroscience↗

bioRxiv2020

Dopamine responses reveal efficient coding of cognitive variables

Reward expectations based on internal knowledge of the external environment are a core component of adaptive behavior. However, internal knowledge may be inaccurate or incomplete due to errors in sensory measurements. Some features of the environment may also be encoded inaccurately to minimise representational costs associated with their processing. We investigate how reward expectations are affected by differences in internal representations by studying rodents behaviour and dopaminergic activity while they make time based decisions. Several possible representations allow a reinforcement learning agent to model animals choices during the task. However, only a small subset of highly compressed representations simultaneously reproduce, both, animals behaviour and dopaminergic activity. Strikingly, these representations predict an unusual distribution of response times that closely matches animals behaviour. These results can inform how constraints of representational efficiency may be expressed in encoding representations of dynamic cognitive variables used for reward based computations.

neuroscience↗