A minimum-error, energy-constrained neural code is an instantaneous-rate code

2016 ◽  
Vol 40 (2) ◽  
pp. 193-206 ◽  
Author(s):  
Erik C. Johnson ◽  
Douglas L. Jones ◽  
Rama Ratnam
2017 ◽  
Author(s):  
Joe Z. Tsien ◽  
Meng Li

AbstractOne important goal of BRAIN projects is to crack the neural code — to understand how information is represented in patterns of electrical activity generated by ensembles of neurons. Yet the major stumbling block in the understanding of neural code isneuronal variability- neurons in the brain discharge their spikes with tremendous variability in both thecontrolresting states and across trials within the same experiments. Such on-going spike variability imposes a great conceptual challenge to the classic rate code and/or synchrony-based temporal code. In practice, spike variability is typically removed via over-the-trial averaging methods such as peri-event spike histogram. In contrast to view neuronal variability as a noise problem, here we hypothesize that neuronal variability should be viewed as theself-information processor. Under this conceptual framework, neurons transmit their information by conforming to the basic logic of the statistical Self-Information Theory: spikes with higher-probability inter-spike-intervals (ISI) contain less information, whereas spikes with lower-probability ISIs convey more information, termed assurprisal spikes. In other words, real-time information is encoded not by changes in firing frequency per se, but rather by spike’s variability probability. When these surprisal spikes occur as positive surprisals or negative surprisals in a temporally coordinated manner across populations of cells, they generate cell-assembly neural code to convey discrete quanta of information in real-time. Importantly, such surprisal code can afford not only robust resilience to interference, but also biochemical coupling to energy metabolism, protein synthesis and gene expression at both synaptic sites and cell soma. We describe how this neural self-information theory might be used as a general decoding strategy to uncover the brain’s various cell assemblies in an unbiased manner.


Author(s):  
Mais Sami Ali ◽  
Abdulkareem Abdulrahman Kadhim

1988 ◽  
Vol 60 (1) ◽  
pp. 1-29 ◽  
Author(s):  
E. D. Young ◽  
J. M. Robert ◽  
W. P. Shofner

1. The responses of neurons in the ventral cochlear nucleus (VCN) of decerebrate cats are described with regard to their regularity of discharge and latency. Regularity is measured by estimating the mean and standard deviation of interspike intervals as a function of time during responses to short tone bursts (25 ms). This method extends the usual interspike-interval analysis based on interval histograms by allowing the study of temporal changes in regularity during transient responses. The coefficient of variation (CV), equal to the ratio of standard deviation to mean interspike interval, is used as a measure of irregularity. Latency is measured as the mean and standard deviation of the latency of the first spike in response to short tone bursts, with 1.6-ms rise times. 2. The regularity and latency properties of the usual PST histogram response types are shown. Five major PST response type classes are used: chopper, primary-like, onset, onset-C, and unusual. The presence of a prepotential in a unit's action potentials is also noted; a prepotential implies that the unit is recorded from a bushy cell. 3. Units with chopper PST histograms give the most regular discharge. Three varieties of choppers are found. Chop-S units (regular choppers) have CVs less than 0.35 that are approximately constant during the response; chop-S units show no adaptation of instantaneous rate, as measured by the inverse of the mean interspike interval. Chop-T units have CVs greater than 0.35, show an increase in irregularity during the response and show substantial rate adaptation. Chop-U units have CVs greater than 0.35, show a decrease in irregularity during the response, and show a variety of rate adaptation behaviors, including negative adaptation (an increase in rate during a short-tone response). Irregular choppers (chop-T and chop-U units) rarely have CVs greater than 0.5. Choppers have the longest latencies of VCN units; all three groups have mean latencies at least 1 ms longer than the shortest auditory nerve (AN) fiber mean latencies. 4. Chopper units are recorded from stellate cells in VCN (35, 42). Our results for chopper units suggest a model for stellate cells in which a regularly firing action potential generator is driven by the summation of the AN inputs to the cell, where the summation is low-pass filtered by the membrane capacitance of the cell.(ABSTRACT TRUNCATED AT 400 WORDS)


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