A time-comparison circuit in the electric fish midbrain. I. Behavior and physiology

Abstract

Behavioral experiments show that the weakly electric fish, Eigenmannia, detects differences in timing as small as 400 nsec between electric signals from different parts of its body surface. The neural basis of this remarkable temporal resolution was investigated by recording from elements of the phase-coding system, a chain of electrotonically connected neurons devoted to the processing of temporal information. Each element of this system fires a single action potential for every cycle of the electric signal (either the fish's own electric organ discharge or a sinusoidal signal of similar frequency). For phase-coding primary afferents and midbrain neurons, the temporal resolution was determined by measuring each unit's capacity to lock its spike to a particular phase of the stimulus cycle. The jitter of a neuron's response (measured as the standard deviation of the timing of the spikes with respect to the stimulus) decreases from the level of the primary afferent (mean = 30 ctsec) to the midbrain torus (mean = 11 rsec); these results can be correlated with morphological measures of convergence. The temporal resolution of single neurons is still inferior to that displayed at the behavioral level.The detection of small temporal disparities between two signals is a process of general interest in sensory physiology, mediating localization of sound in the auditory system and providing an illusion of depth perception in vision (Pulfrich phenomenon). We employ a behavioral assay, the Jamming Avoidance Response (JAR), to demonstrate that the weakly electric fish, Eigenmannia, is able to detect temporal disparities of electrical signals as small as 400 nsec. In order to understand the origins of this sensitivity, we used intracellular recording techniques to identify the individual elements of the underlying neuronal circuit with respect to their response properties and morphology. In a subsequent study (Carr et al., in press), ultrastructural techniques have been used to reconstruct the midbrain circuit that performs these time comparisons.Eigenmannia is a South American gymnotiform fish which produces a high-frequency wave-type electric organ discharge. It uses this discharge both for electrolocation and for social communication. These fish possess a simple behavior, the JAR, whereby they shift the frequency of their electric organ discharge so as to avoid being jammed by a neighboring conspecific with a similar frequency (usually within +/-20 Hz; Bullock et al.,

Representation of Accurate Temporal Information in the Electrosensory System of the African Electric Fish,Gymnarchus niloticus

“…Neurons in the nucleus of magnocellularis of the barn owl show vector strength from 0.5 to 0.7 at low frequencies, which corresponds to a jitter of several tens of microseconds (Sullivan and Konishi, 1984;Carr and Konishi, 1990). Jitter measurement in phase-locked neurons of an electric fish, Eigenmannia, (Rose and Heiligenberg, 1985b;Carr et al, 1986a) shows somewhat larger values than those found here in Gymnarchus. The temporal accuracy of the PLNs of Gymnarchus roughly corresponds to the sensitivity of differential-phase-sensitive neurons in the ELL, which are presumed to receive direct inputs from PLNs (Kawasaki and Guo, 1996).…”

“…JARs occurred even when a large artificial jitter (ϳ60 sec) was introduced to a stimulus that mimicked fish's own EOD and the time disparity for JAR was diminished to 1 sec. This immunity of JAR to the EOD jitter is explained by the insensitivity of the differential-phase-sensitive neurons in the ELL to a common phase modulation.The JAR of the South American electric fish, Eigenmannia, also occurs in response to stimuli that generate comparably small phase differences (Rose and Heiligenberg, 1985b;Carr et al, 1986a). The present study revealed that the independently evolved Eigenmannia and Gymnarchus exhibit a comparative level of remarkable temporal accuracy.…”

“…The JAR of the South American electric fish, Eigenmannia, also occurs in response to stimuli that generate comparably small phase differences (Rose and Heiligenberg, 1985b;Carr et al, 1986a). The present study revealed that the independently evolved Eigenmannia and Gymnarchus exhibit a comparative level of remarkable temporal accuracy.…”

Dynamical mean-field theory of spiking neuron ensembles: Response to a single spike with independent noises

“…In recent years, however, an alternative temporal code has been proposed in which detailed spike timings are assumed to play an important role in information transmission: information is encoded in interspike intervals or in relative timings between firing times of spikes [8]- [10]. Indeed, experimental evidences have accumulated in the last several years, indicating a use of the temporal coding in neural systems [11]- [15]. Human visual systems, for example, have shown to classify patterns within 250 ms despite the fact that at least ten synaptic stages are involved from retina to the temporal brain [15].…”

Maxsim, software for the analysis of multiple axonal arbors and their simulated activation

“…Auditory nuclei and nuclei which decode electric signals can extract information by analyzing synchronism in the Ž . m s range Carr et al, 1986;Carr and Konishi, 1990 . Recent electrophysiological and theoretical work stress the importance of synchronous activity of neural groups in Ž .…”