Computational Models of Millisecond Level Duration Tuning in Neural Circuits

Aubie, Brandon; Becker, Suzanna; Faure, Paul

doi:10.1523/jneurosci.1085-09.2009

Cited by 43 publications

(60 citation statements)

References 49 publications

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“…Some are circuit-based models that rely on the temporal interaction and integration of excitatory and inhibitory synaptic inputs at the DTN (Casseday et al, , 2000Fuzessery and Hall, 1999;Aubie et al, 2009). Another proposes that slowly changing ionic conductances, induced solely by sustained hyperpolarization (i.e., sustained inhibition), result in duration-dependent currents and duration-selective responses (Hooper et al, 2002).…”

Section: Conceptual Mechanisms Of Duration Tuningmentioning

confidence: 99%

“…A symmetrical window of coincidence will naturally result in a bandpass duration-tuned response (Fig. 2 A, B); however, the coincidence detection mechanism can also produce short-pass duration-tuned responses when the excitatory in-puts maximally coincide at the shortest stimulus durations (Aubie et al, 2009). Fuzessery and Hall (1999) noticed that many short-pass DTNs in the IC of the pallid bat had responses locked to stimulus onset rather than stimulus offset, suggesting these neurons lacked an offsetevoked excitatory input.…”

Section: Coincidence Detection Mechanismmentioning

confidence: 99%

“…2C,D). Therefore, the anti-coincidence mechanism naturally results in short-pass duration-tuned responses; however, modified anti-coincidence mechanisms can also produce bandpass duration tuning when the excitatory input is weak or absent at the shortest stimulus durations (Aubie et al, 2009).…”

Section: Coincidence Detection Mechanismmentioning

confidence: 99%

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Duration Tuning across Vertebrates

Aubie

Sayegh²,

Faure³

2012

J. Neurosci.

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Signal duration is important for identifying sound sources and determining signal meaning. Duration-tuned neurons (DTNs) respond preferentially to a range of stimulus durations and maximally to a best duration (BD). Duration-tuned neurons are found in the auditory midbrain of many vertebrates, although studied most extensively in bats. Studies of DTNs across vertebrates have identified cells with BDs and temporal response bandwidths that mirror the range of species-specific vocalizations. Neural tuning to stimulus duration appears to be universal among hearing vertebrates. Herein, we test the hypothesis that neural mechanisms underlying duration selectivity may be similar across vertebrates. We instantiated theoretical mechanisms of duration tuning in computational models to systematically explore the roles of excitatory and inhibitory receptor strengths, input latencies, and membrane time constant on duration tuning response profiles. We demonstrate that models of duration tuning with similar neural circuitry can be tuned with species-specific parameters to reproduce the responses of in vivo DTNs from the auditory midbrain. To relate and validate model output to in vivo responses, we collected electrophysiological data from the inferior colliculus of the awake big brown bat, Eptesicus fuscus, and present similar in vivo data from the published literature on DTNs in rats, mice, and frogs. Our results support the hypothesis that neural mechanisms of duration tuning may be shared across vertebrates despite species-specific differences in duration selectivity. Finally, we discuss how the underlying mechanisms of duration selectivity relate to other auditory feature detectors arising from the interaction of neural excitation and inhibition.

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Section: Conceptual Mechanisms Of Duration Tuningmentioning

confidence: 99%

Section: Coincidence Detection Mechanismmentioning

confidence: 99%

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Duration Tuning across Vertebrates

Aubie

Sayegh²,

Faure³

2012

J. Neurosci.

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“…Long-pass DTNs in the IC require a minimum stimulus duration before spiking, and this minimum duration remains constant or increases with increasing SPL (Faure et al 2003;Aubie et al 2009). Theoretically, stimulus duration could be decoded from the responses of a long-pass DTN, or any neuron with tonic responses, by simply integrating spike counts; however, a neural decoder trying to discriminate between two responses with long spike trains would face a similar problem to a decoder trying to discriminate between two responses with long latencies (e.g., the brain may find it difficult to differentiate between a 24-ms stimulus that evoked 20 spikes and a 25-ms stimulus that evoked 21 spikes).…”

Section: Decoding Stimulus Durationmentioning

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%

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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Neural Coding of Signal Duration and Complex Acoustic Objects

Faure

Firzlaff

2016

Bat Bioacoustics

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Computational Models of Millisecond Level Duration Tuning in Neural Circuits

Cited by 43 publications

References 49 publications

Duration Tuning across Vertebrates

Duration Tuning across Vertebrates

Decoding stimulus duration from neural responses in the auditory midbrain

Neural Coding of Signal Duration and Complex Acoustic Objects

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