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Biomedical subjects

A Zador

Publications and source records attributed to A Zador.

12 recordsLinked to original sources
PubMed2001

Efficient temporal processing with biologically realistic dynamic synapses.

Synapses play a central role in neural computation: the strengths of synaptic connections determine the function of a neural circuit. In conventional models of computation, synaptic strength is assumed to be a static quantity that changes only on the slow timescale of learning. In biological systems, however, synaptic strength undergoes dynamic modulation on rapid timescales through mechanisms such as short term facilitation and depression. Here we describe a general model of computation that exploits dynamic synapses, and use a backpropagation-like algorithm to adjust the synaptic parameters. We show that such gradient descent suffices to approximate a given quadratic filter by a rather small neural system with dynamic synapses. We also compare our network model to artificial neural networks designed for time series processing. Our numerical results are complemented by theoretical analyses which show that even with just a single hidden layer such networks can approximate a surprisingly large class of nonlinear filters: all filters that can be characterized by Volterra series. This result is robust with regard to various changes in the model for synaptic dynamics.

Algorithms↗
PubMed2000

Neural representation and the cortical code.

The principle function of the central nervous system is to represent and transform information and thereby mediate appropriate decisions and behaviors. The cerebral cortex is one of the primary seats of the internal representations maintained and used in perception, memory, decision making, motor control, and subjective experience, but the basic coding scheme by which this information is carried and transformed by neurons is not yet fully understood. This article defines and reviews how information is represented in the firing rates and temporal patterns of populations of cortical neurons, with a particular emphasis on how this information mediates behavior and experience.

Animals↗
PubMed1998

Impact of synaptic unreliability on the information transmitted by spiking neurons.

The spike generating mechanism of cortical neurons is highly reliable, able to produce spikes with a precision of a few milliseconds or less. The excitatory synapses driving these neurons are by contrast much less reliable, subject both to release failures and quantal fluctuations. This suggests that synapses represent the primary bottleneck limiting the faithful transmission of information through cortical circuitry. How does the capacity of a neuron to convey information depend on the properties of its synaptic drive? We address this question rigorously in an information theoretic framework. We consider a model in which a population of independent unreliable synapses provides the drive to an integrate-and-fire neuron. Within this model, the mutual information between the synaptic drive and the resulting output spike train can be computed exactly from distributions that depend only on a single variable, the interspike interval. The reduction of the calculation to dependence on only a single variable greatly reduces the amount of data required to obtain reliable information estimates. We consider two factors that govern the rate of information transfer: the synaptic reliability and the number of synapses connecting each presynaptic axon to its postsynaptic target (i.e., the connection redundancy, which constitutes a special form of input synchrony). The information rate is a smooth function of both mechanisms; no sharp transition is observed from an "unreliable" to a "reliable" mode. Increased connection redundancy can compensate for synaptic unreliability, but only under the assumption that the fine temporal structure of individual spikes carries information. If only the number of spikes in some relatively long-time window carries information (a "mean rate" code), an increase in the fidelity of synaptic transmission results in a seemingly paradoxical decrease in the information available in the spike train. This suggests that the fine temporal structure of spike trains can be used to maintain reliable transmission with unreliable synapses.

Animals↗
PubMed1996

Synaptic transmission: noisy synapses and noisy neurons.

The finding that the synapses relaying sensory input to the cortex may have different properties than intracortical synapses has implications not only for sensory processing, but for the role of noise in neural computation as well.

Animals↗
PubMed1994

Linearized models of calcium dynamics: formal equivalence to the cable equation.

The dynamics of calcium and other diffusible second messengers play an important role in intracellular signaling. We show here the conditions under which nonlinear equations governing the diffusion, extrusion, and buffering of calcium can be linearized. Because the resulting partial differential equation is formally identical to the one-dimensional cable equation, quantities analogous to the input resistance, space constant, and time constant--familiar from the study of passive electrical propagation--can be defined. Using simulated calcium dynamics in an infinite cable and in a dendritic spine as examples, we bound the errors due to the linearization, and show that parameter uncertainty is so large that most nonlinearities can usually be ignored: robust phenomena in the nonlinear model are also present in the linear model.

Animals↗
PubMed1990

Antigenic requirements for stimulation and target cell recognition by immune and non-immune cytotoxic T lymphocytes.

The molecular requirements for recognition of antigen-modified cells by cytotoxic T lymphocyte precursors (CTLp) and their activated progeny, cytotoxic T lymphocytes (CTL), have been compared using haptenated stimulator and target cells. The antigen density requirements of T cell recognition by fluorescein-specific CTLp and CTL derived both from naive mice and from animals previously primed in vivo were determined. The cell surface hapten concentration required to stimulate CTLp cannot be distinguished from that required on target cells for lysis by their mature daughter CTL 5-7 days later. However, if the CTL (and their precursor CTLp) are derived from mice primed in vivo with hapten-conjugated cells, they require lower cell surface hapten densities for recognition than do the analogous T cell populations from naive animals. Thus, the maturation of CTLp into CTL during 5-7 days in vitro does not result in any functionally relevant change in the nature or density of antigen receptors on the surface of the T cell. This is in contrast to the apparent selection which occurs over longer time periods in vivo following priming.

Animals↗
PubMed1990

Biophysical model of a Hebbian synapse.

We present a biophysical model of electrical and Ca(2+) dynamics following activation of N-methyl-D-aspartate (NMDA) receptors located on a dendritic spine. The model accounts for much of the phenomenology of the induction of long-term potentiation at a Hebbian synapse in hippocampal region CA1. Computer simulations suggested four important functions of spines in this Ca(2+)-dependent synaptic modification: (i) compartmentalizing transient changes in [Ca(2+)] to just those synapses that satisfy the conjunctive requirement for synaptic modification; (ii) isolating the spine head from changes in the [Ca(2+)] at the dendritic shaft; (iii) amplifying the concentration changes at those synapses; and (iv) increasing the voltage dependence of the processes underlying long term potentiation induction. This proposed role of spines in the regulation of Ca(2+) dynamics contrasts with traditional approaches to spine function that have stressed electronic properties. This model can be used to explore the computational implications of Hebbian synapses.

Animals↗