Quantitative properties of the creation and activation of a cell-intrinsic engram
Gallistel, C. R.; Johansson, F.; Jirenhed, D.-A.; Rasmussen, A.; Ricci, M.; Hesslow, G.
Show abstract
The conditional pause in the spontaneous firing of the cerebellar Purkinje, which determines the timing of the conditional eyeblink response, is mediated by a cell-intrinsic engram (Johansson, et al. 2014) that encodes the interstimulus interval. Our trial-by-trial analysis of the pause parameters reveals that it consists of a single unusually long interspike interval, whose onset and offset latencies are stochastically independent scalar functions of the interstimulus interval. The coefficients of variation are comparable to those observed in the timing of the overt conditional eyeblink. The onsets of the long interspike interval are step changes; there is no prior build-up of inhibition. A single spike volley in the parallel fiber input triggers the read-out of the engram into the long interspike interval; subsequent volleys have no effect on the pause. The high spontaneous firing rate on which the one-interval firing pause supervenes is markedly non-stationary (Fano factors >> 1).
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Improvement in auditory spatial discrimination from ambiguous visual stimuli is not explained by ideal observer causal inference 92%
- Hey, look over there: Distraction effects on rapid sequence recall 91%
- Cumulative multisensory discrepancies shape the ventriloquism aftereffect but not the ventriloquism bias 91%
Similar papers in this journal
- Interaction between theta-phase and spike-timing dependent plasticity simulates theta induced memory effects 94%
- Complementary effects of adaptation and gain control on sound encoding in primary auditory cortex 94%
- Inter-animal variability in activity phase is constrained by synaptic dynamics in an oscillatory network 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.