Spike-frequency adaptation is a prominent feature of many neurons. However, little is known about its computational role in processing behaviorally relevant natural stimuli beyond filtering out slow changes in stimulus intensity. Here, we present a more complex example in which we demonstrate how spike-frequency adaptation plays a key role in separating transient signals from slower oscillatory signals. We recorded in vivo from very rapidly adapting electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus. The firing-frequency response of electroreceptors to fast communication stimuli ("small chirps") is strongly enhanced compared with the response to slower oscillations ("beats") arising from interactions of same-sex conspecifics. We are able to accurately predict the electroreceptor afferent response to chirps and beats, using a recently proposed general model for spike-frequency adaptation. The parameters of the model are determined for each neuron individually from the responses to step stimuli. We conclude that the dynamics of the rapid spike-frequency adaptation is sufficient to explain the data. Analysis of additional data from step responses demonstrates that spike-frequency adaptation acts subtractively rather than divisively as expected from depressing synapses. Therefore, the adaptation dynamics is linear and creates a high-pass filter with a cutoff frequency of 23 Hz that separates fast signals from slower changes in input. A similar critical frequency is seen in behavioral data on the probability of a fish emitting chirps as a function of beat frequency. These results demonstrate how spike-frequency adaptation in general can facilitate extraction of signals of different time scales, specifically high-frequency signals embedded in slower oscillations.

Weakly electric fish generate a periodic electric field as a carrier signal for active location and communication tasks. Highly sensitive P-type receptors on their surface fire in response to carrier amplitude modulations (AM's) in a noisy phase locked fashion. A simple generic model of receptor activity and signal encoding is presented. Its suprathreshold dynamics, memory and receptor noise reproduce observed firing interval distributions and correlations. The model ultimately explains how smooth responses to AM's are compatible with its nonlinear phase locking properties, and reveals how receptor noise can sometimes enhance the encoding of small yet suprathreshold AM's.

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1. Three parallel maps of the distribution of tuberous electroreceptor inputs are found in the medullary electrosensory lateral line lobe (ELL) of weakly electric fish. Pyramidal cells in each map are known to respond differentially to the frequency of amplitude modulations (AMs) of external electric fields in vivo. We used an in vitro ELL slice preparation of Apteronotus leptorhynchus to compare the characteristics of spontaneously active single units across the three tuberous maps. It was our objective to determine whether spontaneous bursting activity of pyramidal cells in each map correlates with the known AM frequency selectivities of pyramidal cells in vivo. 2. Single-unit discharges were recorded from the pyramidal cell layer of the centromedial segment (CMS), centrolateral segment (CLS), and lateral segment (LS) of the ELL. Stochastic analysis of interspike intervals (ISIs) was used to identify bursting and nonbursting unit activity, and to separately analyze intra- and interburst ISIs. Four ISI patterns were identified as 1) bursting, 2) regular spiking, 3) irregular spiking, and 4) highly irregular spiking. This work focuses primarily on the characteristics of bursting units across the ELL segments. 3. Spontaneous bursting discharge was identified in all three maps (68 of 97 units), with several characteristics changing in a gradual manner across the maps. The coefficient of variation (CV) of ISIs and intraburst ISIs decreased significantly from the CMS to the LS, whereas the CV of burst periods increased significantly from the CMS to the LS. Autocorrelations and power spectral density analysis identified units discharging in an oscillatory manner with the following ratio: CMS, 75%; CLS, 4%; LS, 8%. 4. The mean period of spike bursts decreased significantly across the segments (CMS, 2.7 s; CLS, 1.2 s; LS, 1.1 s) primarily because of a shortening of mean burst duration (CMS, 1.0 s; CLS, 0.1 s; LS, 0.05 s). The average number of spikes per burst decreased significantly across the maps (CMS, 61; CLS, 8; LS, 8), whereas the average frequency of spikes per burst increased (CMS, 90 Hz; CLS, 130 Hz; LS, 178 Hz), mainly through an increase in the maximal frequencies attained by units within each map. 5. Bursts in the CMS were unstructured in that the intraburst ISIs were serially independent, whereas for many units in the CLS and especially the LS there were serial dependencies of successive spikes, with alternating short and long ISIs during the burst. 6. These data reveal that the characteristics of bursting unit activity differ between the CMS, CLS, and LS maps in vitro, implying a modulation of the factors underlying burst discharge across multiple sensory maps. Because the pattern of change in burst activity between these maps parallels that of pyramidal cell AM frequency selectivity in vivo, oscillatory and burst discharge may represent the cellular mechanism used to tune these cells to specific frequencies of afferent input during electrolocation and electrocommunication.

Several types of N-methyl-D-aspartate (NMDA) receptor-dependent synaptic plasticity are characterized by differences in polarity, induction parameters, and duration, which depend on the interactions of NMDARs with intracellular synaptic and signaling proteins. Here, we examine the NMDAR signaling components in the brain of the weakly electric fish Apteronotus leptorhynchus. Compared with mammalian orthologs, high levels of sequence conservation for known functional sites in both NMDAR subunits (NR1, NR2A-C) and signaling proteins (fyn tyrosine kinase, RasGRF-1 and -2) were found. In situ hybridization analysis demonstrated that, similar to the case in the adult mammal brain, NR2A and NR2B are expressed at moderate levels in most brain regions and at very high levels in the dorsal telencephalon. RasGRF-1 and fyn have a similar distribution and appear to be coexpressed with NR2B in telencephalic regions known to support learning and long-term memory. Both NR2A and NR2B are highly expressed in pyramidal cells of the electrosensory lateral line lobe (ELL) known to exhibit the short-term synaptic plasticity that underlies adaptive feedback cancellation of redundant sensory input. In contrast, nonplastic pyramidal cells expressed only the NR2A subunit. Furthermore, field recordings show that ifenprodil-sensitive NR2B-containing NMDARs predominate for the plastic feedback input to ELL pyramidal cells. However, RasGRF-1 and fyn are expressed only at low levels in a subset of these pyramidal cells. Our data suggest that NMDAR functions are highly conserved between fish and mammals and that synaptic plasticity dynamics in different brain regions are related to the expression patterns of the synaptic signaling proteins interacting with NMDARs.

The acousticolateral area of fishes containsa vestibular area and a lateral line area. The vestibular area appears to be very constant with respect to its internal structure, its input, and its relation to the lateral line area. It is more difficult to understand the lateral line area, since this region appears to undergo greater evolutionary modification in various families of fish. The most consistent analysis to date subdivides the acousticolateral area into a nucleus medialis (ant. lobe) and a nucleus dorsalis (post. lobe), but this may be modified when further experimental data becomes available. The vestibulolateral lobe of the cerebellum is, as Larsell already indicated, closely related to the acousticolateral area. This cerebellar region contains an eminentia granulans aligned with the nucleus medialis, and an auricle (lobus caudalis) aligned with the nucleus dorsalis. The molecular layer of the vestibulolateral lobe of the cerebellum continues as the crista cerebellaris of the acousticolateral area; our data for the weakly electric fish indicates that the crista cerebellaris contains: (1) axons of interneurons of the acousticolateral area, and (2) vestibulolateral efferents organized as parallel fibers. Direct afferent input from the lateral line to the crista cerebellaris may be an uncommon specialization.

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