An inducing algorithm for LTP in hippocampal CA1 neurons studied bytemporal pattern stimulation

摘要

To investigate the effect of the time structure of input spikentrains for CA1 neurons in eliciting LTP, the authors examined thenrelationship between statistical properties (mean rate, serialncorrelation coefficient) of stimulus sequences and the induction of LTP.nThe statistical stimuli were Markov stimuli with different second ordernstatistics (type 1 is positive correlations between successiveninter-stimulus intervals, type 2 is negative, and type 3 is independent)nbut with identical mean rate. The magnitude of LTP induced by thesenstimuli showed clear order relationships, type 3>typen1>control>type 2. From the experimental data, a dynamical learningnrule in CA1 neural networks was derived that extracts the temporalninformation of input stimuli and transforms it into the weight space ofnsynaptic connection in CA1 hippocampal networks