Duration Tuning across Vertebrates

Aubie, Brandon; Sayegh, Riziq; Faure, Paul

doi:10.1523/jneurosci.5624-11.2012

Cited by 50 publications

(53 citation statements)

References 99 publications

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“…This contrasts with other systems, where duration-tuned neurons have been found (Aubie et al, 2012). In the case of processing echolocation signals or speech, knowing the duration of individual calls is likely essential.…”

Section: Linking Computations In the Auditory Pathway With Female Behmentioning

confidence: 89%

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Clemens¹,

Girardin²,

Coen³

et al. 2018

Neuron

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SummaryBrains are optimized for processing ethologically relevant sensory signals. However, few studies have characterized the neural coding mechanisms that underlie the transformation from natural sensory information to behavior. Here, we focus on acoustic communication in Drosophila melanogaster, and use computational modeling to link natural courtship song, neuronal codes, and female behavioral responses to song. We show that melanogaster females are sensitive to long timescale song structure (on the order of tens of seconds). From intracellular recordings, we generate models that recapitulate neural responses to acoustic stimuli. We link these neural codes with female behavior by generating model neural responses to natural courtship song. Using a simple decoder, we predict female behavioral responses to the same song stimuli with high accuracy. Our modeling approach reveals how long timescale song features are represented by the Drosophila brain, and how neural representations can be decoded to generate behavioral selectivity for acoustic communication signals.

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Section: Linking Computations In the Auditory Pathway With Female Behmentioning

confidence: 89%

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Clemens¹,

Girardin²,

Coen³

et al. 2018

Neuron

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“…Because duration-tuned neurons are found in both echolocating and non-echolocating vertebrates, the ability to echolocate cannot be a prerequisite for the evolution of duration selectivity in bats. Nevertheless, this does not preclude a functional role for duration tuning in the neural basis of echolocation (Sayegh et al, 2011;Aubie et al, 2012). Durationtuned neurons have also been reported from the inferior colliculus of LDC and HDC bats, and in both New World and Old World species (e.g.…”

mentioning

confidence: 99%

Evolution of high duty cycle echolocation in bats

Fenton

Faure

Ratcliffe

2012

Journal of Experimental Biology

111

129

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SummaryDuty cycle describes the relative ʻon timeʼ of a periodic signal. In bats, we argue that high duty cycle (HDC) echolocation was selected for and evolved from low duty cycle (LDC) echolocation because increasing call duty cycle enhanced the ability of echolocating bats to detect, lock onto and track fluttering insects. Most echolocators (most bats and all birds and odontocete cetaceans) use LDC echolocation, separating pulse and echo in time to avoid forward masking. They emit short duration, broadband, downward frequency modulated (FM) signals separated by relatively long periods of silence. In contrast, bats using HDC echolocation emit long duration, narrowband calls dominated by a single constant frequency (CF) separated by relatively short periods of silence. HDC bats separate pulse and echo in frequency by exploiting information contained in Doppler-shifted echoes arising from their movements relative to background objects and their prey. HDC echolocators are particularly sensitive to amplitude and frequency glints generated by the wings of fluttering insects. We hypothesize that narrowband/CF calls produced at high duty cycle, and combined with neurobiological specializations for processing Doppler-shifted echoes, were essential to the evolution of HDC echolocation because they allowed bats to detect, lock onto and track fluttering targets. This advantage was especially important in habitats with dense vegetation that produce overlapping, time-smeared echoes (i.e. background acoustic clutter). We make four specific, testable predictions arising from this hypothesis.Key words: Chiroptera, calling behaviour, signal design, Yinpterochiroptera, Yangochiroptera, flutter detection, Doppler shift compensation. Fig.1A-C). For the purpose of this paper, we define LDC bats as those producing signals with a duration <25% of their signal period during the search phase of echolocation. Most LDC bats produce echolocation calls with their larynx, although a handful of species in the family Pteropodidae use tongue clicks (Griffin et al., 1958;Yovel et al., 2010).HDC bats avoid auditory masking by separating pulse and echo in frequency, allowing them to broadcast calls and receive echoes at the same time (Schuller, 1974;Schuller, 1977). HDC bats take advantage of information contained in Doppler-shifted echoes generated by the relative movements of bat and target, including acoustic glints generated by the wingbeats of fluttering insects. Echolocation calls of HDC bats consist of a long CF component followed by a brief, downward FM sweep. In some species, the initial portion of the call also contains a short, upward FM sweep (Henson et al., 1987; Jones and Rayner, 1989). Narrowband calls of HDC bats are typically multi-harmonic with the highest signal energy in the second acoustic element (Pye and Roberts, 1970;Schnitzler and Denzinger, 2011). HDC bats emit long duration calls (e.g. 10 to >50ms) relative to their call period ( Fig.1D-F). We operationally define HDC bats as those whose signal durations are ≥25% of...

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“…Detailed procedures for single unit recording from the ICc of the bat and identifying DTN responses are reported elsewhere (Faure et al 2003;Fremouw et al 2005;Aubie et al 2012). Briefly, a stainless steel post was affixed to the dorsal surface of the skull with cyanoacrylate adhesive 24 -48 h before the first recording session.…”

Section: Electrophysiological Recordingsmentioning

confidence: 99%

“…Long-pass DTNs respond only when the stimulus exceeds some minimum duration. Unlike typical sensory neurons that integrate stimulus energy, the minimum duration for evoking a response in a long-pass DTN does not decrease with increasing stimulus amplitude/energy (Faure et al 2003;Sayegh et al 2011;Aubie et al 2012). Because long-pass DTNs do not have a BD, they were not included in this study.…”

Section: Obtaining Single Unit Responsesmentioning

confidence: 99%

“…We measured spike counts and latencies from auditory DTNs in the mammalian IC to characterize the information content of duration-selective neural responses. Previous studies, including those by the authors, have characterized the spiking profile of DTNs by the shape of the duration tuning curve (i.e., short-pass, band-pass, or long-pass) and defined the neuronal best duration (BD) to be the stimulus duration that evoked the peak spike count (Casseday et al 1994(Casseday et al , 2000Ehrlich et al 1997;Faure et al 2003;Aubie et al 2009Aubie et al , 2012Sayegh et al 2011). To test this hypothesis, we measured information content of DTN spiking responses by calculating the stimulus-specific information (SSI) and estimated observed Fisher information (FI).…”

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confidence: 99%

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Decoding stimulus duration from neural responses in the auditory midbrain

Aubie

Sayegh

Fremouw

et al. 2014

Journal of Neurophysiology

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(DTNs). Temporal specificity in their spiking suggests that one function of DTNs is to encode stimulus duration; however, the efficacy of duration encoding by DTNs has yet to be investigated. Herein, we characterize the information content of individual cells and a population of DTNs from the mammalian inferior colliculus (IC) by measuring the stimulus-specific information (SSI) and estimated Fisher information (FI) of spike count responses. We found that SSI was typically greatest for those stimulus durations that evoked maximum spike counts, defined as best duration (BD) stimuli, and that FI was maximal for stimulus durations off BD where sensitivity to a change in duration was greatest. Using population data, we demonstrate that a maximum likelihood estimator (MLE) can accurately decode stimulus duration from evoked spike counts. We also simulated a two-alternative forced choice task by having MLE models decide whether two durations were the same or different. With this task we measured the just-noticeable difference threshold for stimulus duration and calculated the corresponding Weber fractions across the stimulus domain. Altogether, these results demonstrate that the spiking responses of DTNs from the mammalian IC contain sufficient information for the CNS to encode, decode, and discriminate behaviorally relevant auditory signal durations. big brown bat; Eptesicus fuscus; Fisher information, inferior colliculus; just-noticeable difference; stimulus-specific information, temporal processing; Weber fraction DURATION-TUNED NEURONS (DTNs) are ideal candidates for encoding spectral, intensity, and temporal information about an auditory stimulus because they respond selectively to the frequency, amplitude, and duration of acoustic signals. First reported in the torus semicircularis of frogs and subsequently the inferior colliculus (IC) of bats, DTNs have now been recorded from the auditory midbrain, thalamus, and cortex in a variety of vertebrates, and from the mammalian visual cortex (see Sayegh et al. 2011, for review). To date, the electrophysiological properties and underlying synaptic inputs responsible for creating the temporally selective responses of DTNs have been a major research focus, but a quantitative analysis of the information content and encoding efficiency of any neural system is important for linking neurophysiology to behavior and perception because it can suggest limits on the efficacy of information representation. Information theoretic measurements have previously been used to characterize the spiking responses of visual (Strong et al. 1998;Tolhurst et al. 2009 Sensory neurons in general, and auditory neurons in particular, are often viewed as feature detectors that have a preferred value in stimulus domains such as frequency or amplitude, and they encode the domain with spike counts (or rates) and latencies that vary as a function of the stimulus. We measured spike counts and latencies from auditory DTNs in the mammalian IC to characterize the information content of duration-selective ne...

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Duration Tuning across Vertebrates

Cited by 50 publications

References 99 publications

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Evolution of high duty cycle echolocation in bats

Decoding stimulus duration from neural responses in the auditory midbrain

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