Activity in Barrel Cortex Related to Trace Eyeblink Conditioning

Abstract

In mammals several memory systems are responsible for learning and storage of associative memory. Even apparently simple behavioral tasks, like Pavlovian conditioning, have been suggested to engage, for instance, implicit and explicit memory processes. Here we used single whisker tactile trace eyeblink conditioning (TTEBC) to investigate learning and its neuronal bases in the mouse barrel column, the primary neocortical tactile representation of one whisker. Behavioral analysis showed that conditioned responses (CR) are spatially highly restricted, they generalize from the principal whisker only to its direct neighbors. Within the respective neural representation, the principal column and its direct neighbors, spike activity showed a learning-related spike rate suppression starting during the late phase of conditioning stimulus (CS) presentation that was sustained throughout the stimulus-free trace period (Trace). Trial-by-trial analysis showed that learning-related activity was independent from the generation of eyelid movements within a trial, and set in around the steepest part of the learning curve. Optogenetic silencing of responses and their learning-related changes during CS and Trace epochs blocked CR acquisition, but not its recall after learning. Silencing during the Trace alone, which carried major parts of the learning-related changes, had no effect. In summary, we demonstrate specific barrel column spike rate plasticity during TTEBC that can be partially decoupled from the CR, the learned eye closure, a hallmark of implicit learning. Our results, thus, point to a possible role of the barrel column in contributing to other kinds of memory as well.Significance StatementAssociation learning relies on different memory systems. The Pavlovian eyeblink reflex conditioning paradigm already involves the generation of a new movement ('move the eyelid', implicit memory), and to learn the task contingencies ('know the rule of the game', explicit memory). Using this paradigm, we study the involvement of whisker-related mouse primary somatosensory cortex (S1) in different memory systems. With recording and causal stimulation techniques, we found spike plasticity in S1 during presentation of the conditioned stimulus that is causal for implicit learning. Notably, however, blocking learning-related changes during stimulus-free trace period did not impair implicit memory. We conclude that S1 activity is related to the implicit and at least one other memory system, presumably the explicit one.

Discerning state estimation and sensory gating, two presumptive predictive signals in mouse barrel cortex

“…5). The pattern of sinks and sources in barrel cortex, a few milliseconds after a brisk whisker stimulus, is well-documented 25,26 and allowed us to assign the location of layer 4 (L4) and the border between layers 5 and 6 (L5/6) within the 16 recordings on the silicon shank. The depth scale was established by using the peak of the sink at L4 (position zero) and the electrode spacing on the silicone shank to be able to compare data across mice.…”

“…5A). Layering information was extracted from the CSD data based on the well corroborated fact that the CSD signal at a fixed latency of 5-10 ms after a pulse-like whisker deflection is known to show two sinks, one centered on L4, the other on the border of L5 and L6 (=L5/6) 25,26 . We did not find any depth profile of the specific ranking of stimulus types.…”

kCSD-python, reliable current source density estimation with quality control

“…Their main reason for selecting kCSD was the ease of handling irregular spacing between electrodes occurring even on regular grids of electrodes when certain contacts do not satisfy quality control. Similarly, in their studies of activity in the barrel cortex related to trace eyeblink conditioning, Silva-Prieto et al [ 31 ] used 2D kCSD to facilitate identification of borders of cortical columns and layers.…”

“…Its main advantages over previous methods are self-consistent CSD distributions in whole brain regions, ease of estimation from arbitrarily distributed contacts, possibility of restricting sources to specific regions, and separation of experimental setup (electrode distribution) from analytical setup (choice and distribution of basis sources). It was used in several projects where this flexibility was advantageous [13,14,16,[23][24][25][26][27][28][29][30][31].…”