Plasticity of population coding in primary sensory cortex

Abstract

That experience shapes sensory tuning in primary sensory cortex is well understood. But effective neural population codes depend on more than just sensory tuning. Recent population imaging and recording studies have characterized population codes in sensory cortex, and tracked how they change with sensory manipulations and training on perceptual learning tasks. These studies confirm sensory tuning changes, but also reveal other features of plasticity, including sensory gain modulation, restructuring of firing correlations, and differential routing of information to output pathways. Unexpectedly strong day-to-day variation exists in single-neuron sensory tuning, which stabilizes during learning. These are novel dimensions of plasticity in sensory cortex, which refine population codes during learning, but whose mechanisms are unknown.

Tactile enrichment drives emergence of functional columns and improves sensory coding in L2/3 of mouse S1

“…Thus enrichment sharpened the L2/3 PYR cell map and strengthened CW responses at both the microscopic (cellular-resolution) and macroscopic levels, with more subtle changes in the L4 map. These L2/3 map changes could reflect use-dependent strengthening of L4-L2/3 or local recurrent projections (Clem and Barth, 2006; Ko et al, 2013), reorganization of cross-columnar projections (Finnerty et al, 1999), or changes in POm thalamic input (Audette et al, 2018) or top-down input (LeMessurier and Feldman, 2018) to L2/3.…”

“…The origins and function of such dispersed maps are unclear. L2/3 maps are also robustly plastic to sensory experience (Buonomano and Merzenich, 1998; Feldman and Brecht, 2005; LeMessurier and Feldman, 2018). Appropriate sensory experience is often required for development of normal map topography (Katz and Shatz, 1996), raising the question of whether dispersed, salt-and-pepper maps are a natural feature of L2/3, or may reflect incomplete activity-dependent development due to impoverished sensory experience in rodent laboratory housing.…”

Experience shapes activity dynamics and stimulus coding of VIP inhibitory and excitatory cells in visual cortex

“…A recent study showed that experience-induced reductions in the fraction of active cells can be specific to distinct functional subpopulations: 'transient' cells were reduced with experience, but 'sustained' and 'suppressed by contrast' cells showed no change in the fraction of active cells (Weskelblatt and Niell, 2019). Reduced activity for highly familiar stimuli may serve to more efficiently code for stimuli which are predictable, utilizing a smaller population of cells to represent learned information (LeMessurier and Feldman, 2018). On the other hand, enhanced activity for novel stimuli may be involved in the detection of salient and behaviorally meaningful events by augmenting output to downstream targets and facilitating associative plasticity (Ranganath and Rainer, 2003).…”

“…The inter-stimulus activity of VIP cells during sessions with familiar images in the change detection task may be similarly important for enhancing the responses of subsets of excitatory cells to an expected change stimulus, via disinhibition through SST cells. In contrast, during sessions with novel images, VIP activity is driven by stimulus presentation and could serve to increase the gain of stimulus evoked excitatory responses to facilitate learning of new images via associative plasticity (LeMessurier and Feldman, 2018;Ranganath and Rainer, 2003). Future studies examining the evolution of VIP activity across multiple behavior sessions as novel images become familiar, as well as concurrent recordings of VIP and excitatory cells and other inhibitory classes including SST cells, will be critical to determine the time course and mechanistic nature of these interactions.…”

“…It is increasingly clear that cortical activity, even in primary sensory areas, is influenced by behavioral context, internal states, and other factors beyond external stimulus features including movement, arousal, motivation, and task engagement (Batista-Brito et al, 2018;Busse et al, 2017;Gilbert and Li, 2013;Kuchibhotla and Bathellier, 2018;McGinley et al, 2015;Pakan et al, 2018). Moreover, cortical circuits are not fixed but change with experience and learning, leading to the modification of sensory representations (De Lange et al, 2018;LeMessurier and Feldman, 2018;Ranganath and Rainer, 2003), including changes in response gain, selectivity, correlations, and population dynamics (Jurjut et al, 2017;Makino and Komiyama, 2015;Poort et al, 2015;Weskelblatt and Niell, 2019;Woloszyn and Sheinberg, 2012). Sensory experience has been also associated with the emergence of predictive activity in visual cortex such as reward anticipation (Poort et al, 2015;Shuler and Bear, 2006), spatial expectation (Fiser et al, 2016), pattern completion (Gavornik and Bear, 2014), and prediction error signals (Fiser et al, 2016;Hamm and Yuste, 2016;Homann et al, 2017).…”