Showing papers by "Anthony M. Zador published in 2002"

Binary Coding in Auditory Cortex

Abstract: Cortical neurons have been reported to use both rate and temporal codes. Here we describe a novel mode in which each neuron generates exactly 0 or 1 action potentials, but not more, in response to a stimulus. We used cell-attached recording, which ensured single-unit isolation, to record responses in rat auditory cortex to brief tone pips. Surprisingly, the majority of neurons exhibited binary behavior with few multi-spike responses; several dramatic examples consisted of exactly one spike on 100% of trials, with no trial-to-trial variability in spike count. Many neurons were tuned to stimulus frequency. Since individual trials yielded at most one spike for most neurons, the information about stimulus frequency was encoded in the population, and would not have been accessible to later stages of processing that only had access to the activity of a single unit. These binary units allow a more efficient population code than is possible with conventional rate coding units, and are consistent with a model of cortical processing in which synchronous packets of spikes propagate stably from one neuronal population to the next.

Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex

Abstract: How do cortical neurons represent the acoustic environment? This question is often addressed by probing with simple stimuli such as clicks or tone pips. Such stimuli have the advantage of yielding easily interpreted answers, but have the disadvantage that they may fail to uncover complex or higher-order neuronal response properties. Here we adopt an alternative approach, probing neuronal responses with complex acoustic stimuli, including animal vocalizations and music. We have used in vivo whole cell methods in the rat auditory cortex to record subthreshold membrane potential fluctuations elicited by these stimuli. Whole cell recording reveals the total synaptic input to a neuron from all the other neurons in the circuit, instead of just its output—a sparse binary spike train—as in conventional single unit physiological recordings. Whole cell recording thus provides a much richer source of information about the neuron's response. Many neurons responded robustly and reliably to the complex stimuli in our ensemble. Here we analyze the linear component—the spectro-temporal receptive field (STRF)—of the transformation from the sound (as represented by its time-varying spectrogram) to the neuron's membrane potential. We find that the STRF has a rich dynamical structure, including excitatory regions positioned in general accord with the prediction of the simple tuning curve. We also find that in many cases, much of the neuron's response, although deterministically related to the stimulus, cannot be predicted by the linear component, indicating the presence of as-yet-uncharacterized nonlinear response properties.