Literature DB >> 15451379

Spectral-shape preference of primary auditory cortex neurons in awake cats.

Ling Qin1, Sohei Chimoto, Masashi Sakai, Yu Sato.   

Abstract

The study of the influence of spectral envelopes of complex tones on cortical neuron discharges is important with respect to understanding the formant processing of vowels. That the sharpness of formants can contribute to the vowel quality has previously been shown in psychophysical experiments. However, it is unknown how this parameter is reflected by cortical neuron discharges, especially when a formant falls into different portions of the neuronal frequency receptive field (FRF). To show this is the aim of this study focusing on the sustained discharging neurons in the low frequency portion of cat primary auditory cortex (A1). The stimuli were multi-frequency tones whose spectral envelope was sinusoidally modulated with a peak fixed at a neuron's best frequency. The modulation depth, defined as damping-amplitude (DA), varied systematically. Stimulus bandwidth also varied systematically. Large DA at off-center frequencies produces a prominent spectral peak with steep slope, whereas small DA has a less well-defined spectral peak with gentle slope. Single frequency and two tone stimuli served to delineate the excitatory and inhibitory subfields of FRF. The A1 neuron preferred large DA when the sound energy fell into FRF with the relatively large inhibitory-subfield, while the same cell preferred small DA when it fell into FRF with the relatively small inhibitory-subfield. It is concluded that the A1 neuron can estimate steepness of slope of a spectral peak, and that a preference for steep slopes stems from a shift of balance toward the spectral inhibition, whereas a preference for gentle slopes, toward the spectral excitation.

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Year:  2004        PMID: 15451379     DOI: 10.1016/j.brainres.2004.07.061

Source DB:  PubMed          Journal:  Brain Res        ISSN: 0006-8993            Impact factor:   3.252


  1 in total

1.  Cortical activity patterns predict speech discrimination ability.

Authors:  Crystal T Engineer; Claudia A Perez; YeTing H Chen; Ryan S Carraway; Amanda C Reed; Jai A Shetake; Vikram Jakkamsetti; Kevin Q Chang; Michael P Kilgard
Journal:  Nat Neurosci       Date:  2008-04-20       Impact factor: 24.884

  1 in total

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