Circuit Mechanisms of Sensorimotor Learning

Abstract

SUMMARY The relationship between the brain and the environment is flexible, forming the foundation for our ability to learn. Here we review the current state of our understanding of the modifications in the sensorimotor pathway related to sensorimotor learning. We divide the process in three hierarchical levels with distinct goals: 1) sensory perceptual learning, 2) sensorimotor associative learning, and 3) motor skill learning. Perceptual learning optimizes the representations of important sensory stimuli. Associative learning and the initial phase of motor skill learning are ensured by feedback-based mechanisms that permit trial-and-error learning. The later phase of motor skill learning may primarily involve feedback-independent mechanisms operating under the classic Hebbian rule. With these changes under distinct constraints and mechanisms, sensorimotor learning establishes dedicated circuitry for the reproduction of stereotyped neural activity patterns and behavior.

Dynamic perceptual feature selectivity in primary somatosensory cortex upon reversal learning

“…This is remarkable, since upon reversal learning the capacity of the cortex to discriminate lower-order sensory features does not need to be altered in order for the mouse to perform the task. Nonetheless, the finding is congruent with the idea that learning continuously optimizes sensory representations in cortex, and strongly depends on the context (Chen et al, 2015;Makino et al, 2016;Poort et al, 2015). In our study, the altered reward contingency could represent such a contextual change, since the animal has to suddenly shift its attention to the opposite texture to obtain a reward.…”

“…The mammalian cortex encodes a myriad of sensory signal characteristics which are represented by neuronal assemblies, each with a preference for specific stimulus parameters (Holtmaat and Caroni, 2016;Makino et al, 2016). It is believed that these assemblies are organized in a hierarchical fashion.…”

Prominent Inhibitory Projections Guide Sensorimotor Computation: An Invertebrate Perspective

“…[37] Integrated sensory information can change animals' navigation strategies. [41,[44][45][46][47][48][49] Neural circuits have thus evolved to execute sensorimotor integration with everincreasing involvement from mnemonic contributions and executive control, for example in the mammalian brain, the circuits that plan, control, execute, and monitor action generation. [41,42] The rate of turns is regulated by the sensory experience across time scales as the worm adapts to its environment, e.g., a high number of turns are observed following the initial disappearance of food and if food sparsity continues, the number of turns will eventually decrease to a base level.…”

“…With increased mnemonic load, complex neural circuits progressively integrate longterm information storage capability to the circuits that perform sensorimotor integration that constitute the neural basis of perceptual and motor learning. [41,[44][45][46][47][48][49] Neural circuits have thus evolved to execute sensorimotor integration with everincreasing involvement from mnemonic contributions and executive control, for example in the mammalian brain, the circuits that plan, control, execute, and monitor action generation. [50][51][52][53]…”

Impact of transcranial direct current stimulation on structural plasticity of the somatosensory system

“…Altogether these findings highlight changes in response to tactile training in the GM compartment of the brain that primarily target the precuneus and resemble changes observed for the blind. Given the current state of research, the primary mechanism of plasticity associated with the observed decreases in GM is the refinement of existing inhibitory machinery by selection of the most informative input and consecutive pruning (Makino, Hwang, Hedrick, & Komiyama, ). Only intensive practice has been suggested to induce the formation of new connections and therefore an increase in GM (Sampaio‐Baptista et al, ).…”