Mice are not automatons; subjective experience in premotor circuits guides behavior

Abstract

Subjective experience is a powerful driver of decision-making and continuously accrues. However, most neurobiological studies constrain analyses to task-related variables and ignore how continuously and individually experienced internal, temporal, and contextual factors influence adaptive behavior during decision-making and the associated neural mechanisms. We show mice rely on learned information about recent and longer-term subjective experience of variables above and beyond prior actions and reward, including checking behavior and the passage of time, to guide self-initiated, self-paced, and self-generated actions. These experiential variables were represented in secondary motor cortex (M2) activity and its projections into dorsal medial striatum (DMS). M2 integrated this information to bias strategy-level decision-making, and DMS projections used specific aspects of this recent experience to plan upcoming actions. This suggests diverse aspects of experience drive decision-making and its neural representation, and shows premotor corticostriatal circuits are crucial for using selective aspects of experiential information to guide adaptive behavior.

Neural mechanisms underlying the temporal organization of naturalistic animal behavior

“…Although the model in (Stroud et al, 2018) could not account for the across-repetition temporal variability in action timing, it is tempting to speculate that a generalization of this learning framework to incorporate the metastable attractor models of (Mazzucato et al, 2019) could allow a recurrent circuit to learn flexible gain-modulation via biologically plausible synaptic plasticity mechanisms (Litwin-Kumar and Doiron, 2014). This hypothetical model could potentially explain the contextual effects of learning on action timing observed in (Fan et al, 2012;Schreiner et al, 2021), and the acceleration of reaction times in presence of auditory expectations (Fig. 4A (Jaramillo and Zador, 2011)).…”

“…Trial history effects are complex and action-specific and depend on several other factors, including prior movements, and wane with increasing inter-trial intervals. Inactivation experiments showed that these effect rely on frontal areas such as medial prefrontal and secondary motor cortices (Murakami et al, 2014(Murakami et al, , 2017Schreiner et al, 2021).…”

“…In a lever press task, mice learned to adjust the average duration of the lever press to different criteria, in three different conditions where lever presses were always rewarded regardless of duration, or only rewarded if longer than 800ms or 1600ms. Within each of the three conditions, the distribution of action timing exhibited large temporal variability, yet the average duration was starkly different between the three criteria, as the mice learned the different criteria (Fan et al, 2012;Schreiner et al, 2021). Reaction times to sensory stimuli and self-initiated waiting behavior, in the form of long lever presses or nose-pokes, has emerged as a fruitful approach to test hypotheses on contextual modulations and decisionmaking in naturalistic scenarios.…”

“…While all these results were obtained in restrained animals, it is an open question whether neural activity during naturalistic behavior exhibit temporal hierarchies similar to those observed in behavior. Current evidence from freely moving rodents engaged in waiting tasks (Murakami et al, 2017;Schreiner et al, 2021;Recanatesi et al, 2022) revealed the presence of multiple timescales in single-neuron activity from secondary motor and prefrontal cortices. These timescales range from the subsecond scale (single attractors), to a few seconds seconds (attractor sequences), to tens of seconds or minutes (trial-history dependence).…”

“…Experimental evidence shows that single neurons in M2 are selective to multiple actions (Recanatesi et al, 2022), suggesting that mixed selectivity (Rigotti et al, 2013) could play an important role in generating the high-dimensional hierarchical attractor landscape necessary to capture the complexity of naturalistic behavior. An alternative architecture might involve a distributed cortical circuit where the neural representations of behavioral units at different levels of the hierarchy are encoded in multiple frontal cortical areas, such as action sequences in M2, and activities in prefrontal cortex, which is known to control behavior on longer timescales such as trial-history effects (Murakami et al, 2014(Murakami et al, , 2017Schreiner et al, 2021). In both scenarios, we hypothesize that while behavioral units are encoded as cortical attractors, transitions between attractor rely on feedback loops involving cortico-subcortical circuits (Murray et al, 2017;Logiaco et al, 2021;Recanatesi et al, 2022).…”