Reading Sequences of Interspike Intervals in Biological Neural Circuits

Abstract

Sensory systems pass information about an animal's environment to higher nervous system units through sequences of action potentials. When these action potentials have essentially equivalent waveforms, all information is contained in the interspike intervals (ISIs) of the spike sequence. We address the question: How do neural circuits recognize and read these ISI sequences? Our answer is given in terms of a biologically inspired neural circuit that we construct using biologically realistic neurons. The essential ingredients of the ISI Reading Unit (IRU) are (i) a tunable time delay circuit modelled after one found in the anterior forebrain pathway of the birdsong system and (ii) a recently observed rule for inhibitory synaptic plasticity. We present a circuit that can both learn the ISIs of a training sequence using inhibitory synaptic plasticity and then recognize the same ISI sequence when it is presented on subsequent occasions. We investigate the ability of this IRU to learn in the presence of two kinds of noise: jitter in the time of each spike and random spikes occurring in the ideal spike sequence. We also discuss how the circuit can be detuned by removing the selected ISI sequence and replacing it by an ISI sequence with ISIs drawn from a probability distribution. We have investigated realizations of the time delay circuit using Hodgkin-Huxley conductance based neurons connected by realistic excitatory and inhibitory synapses. Our models for the time delay circuit are tunable from about 10 ms to 100 ms allowing one to learn and recognize ISI sequences within that range of ISIs. ISIs down to a few ms and longer than 100 ms are possible with other intrinsic and synaptic currents in the component neurons.