Neural mechanisms of interstimulus interval-dependent responses in the primary auditory cortex of awake cats

Sakai, Masashi; Chimoto, Sohei; Qin, Ling; Sato, Yu

doi:10.1186/1471-2202-10-10

Cited by 30 publications

(40 citation statements)

References 76 publications

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“…Specifically, the border between regions β and γ was not altered in a statistically significantly way when the stimulus intensity was changed from the best SPL to 20-dB below it [1,65]. This finding parallels to the relative level-invariance for the order threshold [11] and VOT boundary in psychoacoustics [66].…”

Section: T I M E a F T E R 1 S T P U L S E ( M S ) T I M E A F T E R supporting

confidence: 54%

“…According to our criterion [1], this unit showed 4 response regions (region α−δ). In region α (intervals ≥ 200 ms), only the onset response was evident.…”

Section: T I M E a F T E R 1 S T P U L S E ( M S ) T I M E A F T E R mentioning

confidence: 94%

“…Discharge r a t e (/s) P u l s e i n t e r v a l ( m s ) (1) a single recording session lasted 10-20 min and contained hundreds of stimulus trains; (2) each stimulus train lasted 500 ms during which 1-ms-long rectangular pulses were repetitively delivered with a fixed interpulse interval ranging 1 to 480 ms; (3) the intensity of 20 successive pulses was set at 20-80 dB by 10 dB steps; (4) the data presented here were obtained at the intensity that evoked the most potent stimulus-locking responses (see Sakai et al [1] for details). The units that exhibited excitatory responses were classified into 3 classes (A-C).…”

Section: Rayleigh Valuementioning

confidence: 99%

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Neural Mechanisms of Fine-Grained Temporal Processing in Audition

Sakai¹

2012

Otolaryngology

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Section: T I M E a F T E R 1 S T P U L S E ( M S ) T I M E A F T E R supporting

confidence: 54%

“…According to our criterion [1], this unit showed 4 response regions (region α−δ). In region α (intervals ≥ 200 ms), only the onset response was evident.…”

Section: T I M E a F T E R 1 S T P U L S E ( M S ) T I M E A F T E R mentioning

confidence: 94%

Section: Rayleigh Valuementioning

confidence: 99%

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Neural Mechanisms of Fine-Grained Temporal Processing in Audition

Sakai¹

2012

Otolaryngology

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“…In addition to marmosets, nonsynchronized responses have also been reported in rats and cats (Anderson et al 2006;Lu and Wang 2000;Sakai et al 2009). Failure to observe nonsynchronized responses in auditory cortex (Malone et al 2007) could be due to several issues including species differences, criteria of nonsynchronized responses, acoustic stimuli (sAM vs. narrowband click trains), and the use of anesthesia (Rennaker et al 2007).…”

Section: Comparison With Previous Studiesmentioning

confidence: 99%

Neural Coding of Periodicity in Marmoset Auditory Cortex

Bendor

Wang

2010

Journal of Neurophysiology

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Bendor D, Wang X. Neural coding of periodicity in marmoset auditory cortex. J Neurophysiol 103: 1809 -1822, 2010. First published February 10, 2010 doi:10.1152/jn.00281.2009. Pitch, our perception of how high or low a sound is on a musical scale, crucially depends on a sound's periodicity. If an acoustic signal is temporally jittered so that it becomes aperiodic, the pitch will no longer be perceivable even though other acoustical features that normally covary with pitch are unchanged. Previous electrophysiological studies investigating pitch have typically used only periodic acoustic stimuli, and as such these studies cannot distinguish between a neural representation of pitch and an acoustical feature that only correlates with pitch. In this report, we examine in the auditory cortex of awake marmoset monkeys (Callithrix jacchus) the neural coding of a periodicity's repetition rate, an acoustic feature that covaries with pitch. We first examine if individual neurons show similar repetition rate tuning for different periodic acoustic signals. We next measure how sensitive these neural representations are to the temporal regularity of the acoustic signal. We find that neurons throughout auditory cortex covary their firing rate with the repetition rate of an acoustic signal. However, similar repetition rate tuning across acoustic stimuli and sensitivity to temporal regularity were generally only observed in a small group of neurons found near the anterolateral border of primary auditory cortex, the location of a previously identified putative pitch processing center. These results suggest that although the encoding of repetition rate is a general component of auditory cortical processing, the neural correlate of periodicity is confined to a special class of pitch-selective neurons within the putative pitch processing center of auditory cortex.

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“…One model suggests a temporal filtering process based on synaptic mechanisms that produces the short recovery time constants required for neuronal following of temporally modulated environmental sounds (Eggermont 2002), another model includes a frequency response parameter, modified by synaptic dynamics, that is responsible for the enhanced, behaviorally driven rate tuning observed experimentally in the AI (Saeb et al 2007), and a third model emphasizes temporal interactions between excitation and inhibition mechanisms and short-term plasticity at the thalamocortical synapse (Sakai et al 2009). Two influential models have been developed that emphasize the contributions of the cholinergic basal forebrain system (Weinberger and Bakin 1998) and the corticofugal system (Suga and Ma 2003) to learning-induced modification of spectral receptive field properties in AI neurons.…”

Section: Mechanisms and Models For Cortical Temporal Processingmentioning

confidence: 99%

Behavioral training enhances cortical temporal processing in neonatally deafened juvenile cats

Beitel

Vollmer

Raggio

et al. 2011

Journal of Neurophysiology

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Beitel RE, Vollmer M, Raggio MW, Schreiner CE. Behavioral training enhances cortical temporal processing in neonatally deafened juvenile cats. J Neurophysiol 106: 944 -959, 2011. First published May 4, 2011 doi:10.1152/jn.00731.2010.-Deaf humans implanted with a cochlear prosthesis depend largely on temporal cues for speech recognition because spectral information processing is severely impaired. Training with a cochlear prosthesis is typically required before speech perception shows improvement, suggesting that relevant experience modifies temporal processing in the central auditory system. We tested this hypothesis in neonatally deafened cats by comparing temporal processing in the primary auditory cortex (AI) of cats that received only chronic passive intracochlear electric stimulation (ICES) with cats that were also trained with ICES to detect temporally challenging trains of electric pulses. After months of chronic passive stimulation and several weeks of detection training in behaviorally trained cats, multineuronal AI responses evoked by temporally modulated ICES were recorded in anesthetized animals. The stimulus repetition rates that produced the maximum number of phase-locked spikes (best repetition rate) and 50% cutoff rate were significantly higher in behaviorally trained cats than the corresponding rates in cats that received only chronic passive ICES. Behavioral training restored neuronal temporal following ability to levels comparable with those recorded in naïve prior normal-hearing adult deafened animals. Importantly, best repetitition rates and cutoff rates were highest for neuronal clusters activated by the electrode configuration used in behavioral training. These results suggest that neuroplasticity in the AI is induced by behavioral training and perceptual learning in animals deprived of ordinary auditory experience during development and indicate that behavioral training can ameliorate or restore temporal processing in the AI of profoundly deaf animals. auditory deprivation; deafness; neuroplasticity; perceptual learning; primary auditory cortex; signal detection training IN ORDINARY LISTENING CONDITIONS, humans with normal hearing rely on the spectral content and temporal features of the speech signal for speech recognition and comprehension (Ahisssar et al. 2001;Rosen 1992;Shannon et al. 1995). If spectral information is degraded while the temporal envelope pattern of the speech signal is preserved, the temporal information alone is often sufficient for speech recognition (Drullman 1995;Shannon et al. 1995).Moreover, temporal processing of speech is an essential feature of neural coding in the auditory cortex for speech comprehension to occur. Evoked potential responses to lowfrequency temporal modulation are observed at the cortical level, and phase locking to the temporal envelope of a sentence is correlated with comprehension of the sentence (Ahissar et al. 2001;Joris et al. 2004). These findings indicate that neural responses in the human auditory cortex represent slow temporal eve...

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Neural mechanisms of interstimulus interval-dependent responses in the primary auditory cortex of awake cats

Cited by 30 publications

References 76 publications

Neural Mechanisms of Fine-Grained Temporal Processing in Audition

Neural Mechanisms of Fine-Grained Temporal Processing in Audition

Neural Coding of Periodicity in Marmoset Auditory Cortex

Behavioral training enhances cortical temporal processing in neonatally deafened juvenile cats

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