Temporal Coding by Populations of Auditory Receptor Neurons

Abstract

Sabourin P, Pollack GS. Temporal coding by populations of auditory receptor neurons. J Neurophysiol 103: 1614 -1621, 2010. First published January 13, 2010 doi:10.1152/jn.00621.2009. Auditory receptor neurons of crickets are most sensitive to either low or high sound frequencies. Earlier work showed that the temporal coding properties of first-order auditory interneurons are matched to the temporal characteristics of natural low-and high-frequency stimuli (cricket songs and bat echolocation calls, respectively). We studied the temporal coding properties of receptor neurons and used modeling to investigate how activity within populations of low-and high-frequency receptors might contribute to the coding properties of interneurons. We confirm earlier findings that individual low-frequencytuned receptors code stimulus temporal pattern poorly, but show that coding performance of a receptor population increases markedly with population size, due in part to low redundancy among the spike trains of different receptors. By contrast, individual high-frequency-tuned receptors code a stimulus temporal pattern fairly well and, because their spike trains are redundant, there is only a slight increase in coding performance with population size. The coding properties of low-and high-frequency receptor populations resemble those of interneurons in response to low-and high-frequency stimuli, suggesting that coding at the interneuron level is partly determined by the nature and organization of afferent input. Consistent with this, the sound-frequency-specific coding properties of an interneuron, previously demonstrated by analyzing its spike train, are also apparent in the subthreshold fluctuations in membrane potential that are generated by synaptic input from receptor neurons. I N T R O D U C T I O NThe temporal structures of sensory signals often carry behaviorally important information and this is particularly evident in communication systems. For example, in many acoustically communicating animals, including birds, frogs, insects, and humans, information such as the species and individual identity of the signaler, or the signal's "message" (e.g., speech; Shannon et al. 1995), is carried by features such as the durations of sounds and of the intervals between them (Bradbury and Vehrencamp 1998). Sensory neurons are often tuned to these behaviorally relevant temporal features; they may respond most strongly to these features (rate code) or the structure of their spike trains may capture most accurately the timing of these stimulus components (time code; Pollack and Krahe 2009).Two classes of sound stimuli are particularly important for the behavior of crickets: conspecific songs and echolocation calls of insectivorous bats. Both types of stimulus consist of series of discrete sounds (sound pulses), but they differ in tempo. Pulse rates in echolocation calls span a wide range, increasing from 5 to 10 Hz when the bat is searching for a target to Ͼ100 Hz during the final approach to the prey (Jones and Rydell 2003). By contrast, ...

Calcium-dependent control of temporal processing in an auditory interneuron: a computational analysis

“…Indeed, stimulus-dependent separation of Ca 2+ accumulation has been shown in the visual neuropil of flies (Egelhaaf and Borst 1995). It is important to note that this endogenous filtering hypothesis does not eliminate synaptic or pre-synaptic mechanisms (French 1986; Gollisch and Herz 2004; Marsat and Pollack 2004; Sabourin and Pollack 2010). But, taken together with the empirically derived Ca 2+ -sensitive adaptation mechanisms (Sobel and Tank 1994; Baden and Hedwig 2007), the model does argue that variance in these Ca 2+ -dependent parameters alone is sufficient to explain the differences in temporal code, as the model does not need intervening circuits or synaptic filters.…”

“…Although synaptic and receptor filtering are implicated in ON1 responses (Marsat and Pollack 2004; Sabourin and Pollack 2010), this was chosen as an idealized input so that our analysis focused solely on filtering due to the post-synaptic mechanisms of the model and not the input itself (Faulkes and Pollack 2001). The stimulus had a 50% duty cycle, meaning response variance depends only on the rate of stimulation, not on overall energy.…”

“…In particular, ON1 band-pass filters the amplitude modulation of sounds with lower carrier frequencies (i.e., near calling songs) to slow amplitude modulation rates, but exhibits broadly tuned low-pass filtering of amplitude-modulated ultrasound (i.e., bat-like sonar; Marsat and Pollack 2004). Although this can partly be explained by receptor (presynaptic) sensitivity (Sabourin and Pollack 2010), mechanisms in ON1 (postsynaptic) are clearly implicated, as excitation-induced ahp is enhanced for song-like carrier frequencies compared to that generated by ultrasound input (Pollack 1988). Importantly, this difference in ahp may be due to dendritic tonotopy in internal Ca 2+ ([Ca 2+ ] i ): ultrasound stimuli elicit less [Ca 2+ ] i in certain dendritic compartments than calling songs do (Baden and Hedwig 2007).…”

Firing-rate resonances in the peripheral auditory system of the cricket, Gryllus bimaculatus

“…Returning to subthreshold resonances, direct evidence for such a mechanism in the cricket auditory periphery would be provided by intracellular recordings-previous studies involving this technique, however, did so far not indicate subthreshold resonances Huber 1978, 1982;Selverston et al 1985). Evidence for network based over intrinsic mechanisms (in the recorded cells) was provided for T. oceanicus by (Sabourin and Pollack 2010), as information tuning was essentially unchanged when spikes and, presumably, most or all subthreshold conductances, were suppressed by strong hyperpolarization.…”

“…As input to all models we used scaled envelope functions, as the cricket's auditory receptors code for amplitude modulation (Machens et al 2001;Imaizumi and Pollack 2001). To best illustrate the models' own filtering capabilities, we disregarded both the individual and combined transfer characteristics of the cricket's populations of auditory receptors (Sabourin and Pollack 2010;Sharafi et al 2013) and assumed unfiltered inputs. Models were manually tuned to match both peak frequency and Q value of ON1's average rMTF ( f p = 23.9 Hz, Q = 1.34; cf.…”