Dataset Information

Analyzing variability in neural responses to complex natural sounds in the awake songbird.

ABSTRACT: Studies of auditory processing in awake, behaving songbirds allow for the possibility of new classes of experiments, including those involving attention and plasticity. Detecting and determining the significance of plasticity, however, requires assessing the intrinsic variability in neural responses. Effects such as rapid plasticity have been investigated in the auditory system through the use of the spectrotemporal receptive field (STRF), a characterization of the properties of sounds to which a neuron best responds. Here we investigated neural response variability in awake recordings obtained from zebra finch field L, the analog of the primary auditory cortex. To quantify the level of variability in the neural recordings, we used three similarity measures: an STRF-based metric, a spike-train correlation-based metric, and a spike-train discrimination-based metric. We then extracted a number of parameters from these measures, quantifying how they fluctuated over time. Our results indicate that 1) awake responses are quite stable over time; 2) the different measures of response are complementary-specifically, the spike-train-based measures yield new information complementary to the STRF; and 3) different STRF parameters show distinct levels of variability. These results provide critical constraints for the design of robust decoding strategies and novel experiments on attention and plasticity in the awake songbird.

SUBMITTER: Grana GD

PROVIDER: S-EPMC2694111 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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Analyzing variability in neural responses to complex natural sounds in the awake songbird.

Graña Gilberto David GD Billimoria Cyrus P CP Sen Kamal K

Journal of neurophysiology 20090408 6

Studies of auditory processing in awake, behaving songbirds allow for the possibility of new classes of experiments, including those involving attention and plasticity. Detecting and determining the significance of plasticity, however, requires assessing the intrinsic variability in neural responses. Effects such as rapid plasticity have been investigated in the auditory system through the use of the spectrotemporal receptive field (STRF), a characterization of the properties of sounds to which ...[more]

PMID: 19357333

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Project description:Significant scientific and translational questions remain in auditory neuroscience surrounding the neural correlates of perception. Relating perceptual and neural data collected from humans can be useful; however, human-based neural data are typically limited to evoked far-field responses, which lack anatomical and physiological specificity. Laboratory-controlled preclinical animal models offer the advantage of comparing single-unit and evoked responses from the same animals. This ability provides opportunities to develop invaluable insight into proper interpretations of evoked responses, which benefits both basic-science studies of neural mechanisms and translational applications, e.g., diagnostic development. However, these comparisons have been limited by a disconnect between the types of spectrotemporal analyses used with single-unit spike trains and evoked responses, which results because these response types are fundamentally different (point-process versus continuous-valued signals) even though the responses themselves are related. Here, we describe a unifying framework to study temporal coding of complex sounds that allows spike-train and evoked-response data to be analyzed and compared using the same advanced signal-processing techniques. The framework uses a set of peristimulus-time histograms computed from single-unit spike trains in response to polarity-alternating stimuli to allow advanced spectral analyses of both slow (envelope) and rapid (temporal fine structure) response components. Demonstrated benefits include: (1) novel spectrally specific temporal-coding measures that are less confounded by distortions due to hair-cell transduction, synaptic rectification, and neural stochasticity compared to previous metrics, e.g., the correlogram peak-height, (2) spectrally specific analyses of spike-train modulation coding (magnitude and phase), which can be directly compared to modern perceptually based models of speech intelligibility (e.g., that depend on modulation filter banks), and (3) superior spectral resolution in analyzing the neural representation of nonstationary sounds, such as speech and music. This unifying framework significantly expands the potential of preclinical animal models to advance our understanding of the physiological correlates of perceptual deficits in real-world listening following sensorineural hearing loss.

Dataset Information

Analyzing variability in neural responses to complex natural sounds in the awake songbird.

Publications

Analyzing variability in neural responses to complex natural sounds in the awake songbird.

Similar Datasets

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