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The peristimulus time histogram is sometimes called perievent time histogram, and post-stimulus and peri-stimulus are often hyphenated. The prefix peri, for through, is typically used in the case of periodic stimuli, in which case the PSTH show neuron firing times wrapped to one cycle of the stimulus.
It works for stationary as well as for time-dependent stimuli. To experimentally measure the time-dependent firing rate, the experimenter records from a neuron while stimulating with some input sequence. The same stimulation sequence is repeated several times and the neuronal response is reported in a Peri-Stimulus-Time Histogram (PSTH). The ...
By detecting the combined photon emissions of pairs p- and n-channel transistors contained in logic gates, it is possible to use the resulting histogram to determine the locations in time of the rising and falling edges of the signal at that node. The waveform produced is not representative of a true voltage waveform, but more accurately ...
Diagram showing how the STA is calculated. A stimulus (consisting here of a checkerboard with random pixels) is presented, and spikes from the neuron are recorded. The stimuli in some time window preceding each spike (here consisting of 3 time bins) are selected (color boxes) and then averaged (here just summed for clarity) to obtain the STA.
Choice reaction time (CRT) tasks require distinct responses for each possible class of stimulus. In a choice reaction time task which calls for a single response to several different signals, four distinct processes are thought to occur in sequence: First, the sensory qualities of the stimuli are received by the sensory organs and transmitted ...
The spike response model (SRM) [1] is a spiking neuron model in which spikes are generated by either a deterministic [2] or a stochastic [1] threshold process. In the SRM, the membrane voltage V is described as a linear sum of the postsynaptic potentials (PSPs) caused by spike arrivals to which the effects of refractoriness and adaptation are added.
Integrate-and-fire models with output noise can be used to predict the peristimulus time histogram (PSTH) of real neurons under arbitrary time-dependent input. [22] For non-adaptive integrate-and-fire neurons, the interval distribution under constant stimulation can be calculated from stationary renewal theory .
In 1973, M. M. Taylor [1] suggested that if synapses were strengthened for which a presynaptic spike occurred just before a postsynaptic spike more often than the reverse (Hebbian learning), while with the opposite timing or in the absence of a closely timed presynaptic spike, synapses were weakened (anti-Hebbian learning), the result would be an informationally efficient recoding of input ...