Opposing regulation of short-term memory by basal ganglia direct and indirect pathways that are coactive during behavior

Abstract

The basal ganglia direct and indirect pathways are viewed to mediate opposing functions in movement. However, this classic model is challenged by recent findings that both pathways are coactive during behavior. We examined the roles of direct (dSPNs) and indirect (iSPNs) pathway spiny projection neurons in a decision-making task with a short-term memory (STM) component. Optogenetic stimulation of cortical-input-defined dSPNs and iSPNs during STM oppositely biased upcoming licking choice, without affecting licking execution. Optogenetically identified dSPNs and iSPNs showed similar response patterns, although with quantitative difference in spatiotemporal organization. To understand how coactive dSPNs and iSPNs play opposing roles, we recorded population activity in frontal cortex and the basal ganglia output nucleus SNr. Stimulation of dSPNs and iSPNs bidirectionally regulated cortical decision variable through the differential modulation of SNr ramping activity. These results reconcile different views by demonstrating that coactive dSPNs and iSPNs precisely shape cortical activity in a push-pull balance.

Opponent control of behavior by dorsomedial striatal pathways depends on task demands and internal state

“…Taken together with previous work, our findings may thus imply limits in the use of artificial activations in assessing striatal pathway function. Our results may also imply that DMS pathways would not necessarily display opposing correlates of movements 14 , 18 , 38 – 41 , but rather opposing correlates of a decision process 12 , 13 , 20 , 22 , 34 , 37 .…”

“…In support of this view, many influential studies have shown that pathway-specific activation of the striatum produces opposing behavioral biases 2 – 14 . For example, direct or indirect pathway activation oppositely influences locomotion 2 – 4 , 14 , licking 5 , 11 , 15 , left/right rotations 2 , 3 , 11 , 16 , repetition/cessation of activation-paired behaviors 6 – 8 , and left/right movements to report value-based decisions 9 , 13 .…”

“…Despite this pioneering work, it remains unresolved whether the endogenous activity of the two pathways provides opposing control over the generation of movements, or instead contributes to the cognitive process of deciding which movement to perform. This is in part because pathway-specific manipulations have disproportionately relied on artificial and synchronous activation, rather than inhibition of endogenous activity 2 – 11 , 13 . The imbalance towards reports of activation suggests a wealth of negative results from inhibition, raising questions about the function of the endogenous activity, and whether it contributes to cognition.…”

Vector-valued dopamine improves learning of continuous outputs in the striatum

“…A vector-valued error would likely appear as tunings to various motor and task variables in experimental animals (Requirement 2 ), especially in the phase before the animals are so overtrained their error is zero. Indeed, cells in the SNr (Fan et al, 2012;Barter et al, 2015;Tang et al, 2021) as well as the SNc (Howe and Dombeck, 2016;Dodson et al, 2016;Coddington and Dudman, 2018;Avvisati et al, 2022) respond to a plethora of behavioral and task variables.…”

“…A vector-valued error would likely appear as tunings to various motor and task variables in experimental animals ( Requirement 2 ), especially in the phase before the animals are so overtrained their error is zero. Indeed, cells in the SNr (Fan et al, 2012; Barter et al, 2015; Tang et al, 2021) as well as the SNc (Howe and Dombeck, 2016; Dodson et al, 2016; Coddington and Dudman, 2018; Avvisati et al, 2022) respond to a plethora of behavioral and task variables. We deliberately excluded the details of how this error may be computed in the brain, but we speculate at least three possible algorithmic ways in which it could appear: Bran region regions such as motor cortex or cerebellum could have a forward model of the world as well as the target, and thus, can directly compute the error and send it to the midbrain. The brain could be wired as a set of hierarchical control loops, in which each loop provides the target for the level below (as proposed by Yin, 2014).…”