Literature DB >> 14622166

Complexity and temporal dynamics of frequency coding in the awake rat auditory cortex.

Bernhard H Gaese1, Joachim Ostwald.   

Abstract

Auditory cortical neurons are elements of a neuronal network that decomposes sounds into spectral and temporal information. In particular, their frequency selectivity has been investigated in great detail. Most studies used anaesthetized preparations and found mainly simple V-shaped tuning. The few data available from awake animals indicate that more complex forms of spectral receptive fields, i.e. frequency response areas, can be found there. We investigated frequency response areas in the awake rat primary auditory cortex using statistical evaluation and found complex forms of frequency response areas with several separate subregions in many neurons, besides classical V-shaped tuning. Response areas, as determined with narrow band noise, were very similar to those measured with pure tones. Their width was well correlated to the response strength to white noise stimulation. These results suggest that the excitatory subregions of frequency response areas were the neurons' predominant characteristic, relevant also for the processing of more complex types of stimuli. Investigating the spectrotemporal dynamics of frequency response areas revealed that approximately one-third of the neurons showed long-lasting excitatory or inhibitory components in addition to the typical ON-response. Inhibition was usually of longer duration and occurred mainly in frequency ranges outside the range of initial excitatory responses. These results indicate that auditory cortical neurons in awake animals can represent spectrotemporal information of rather different complexity.

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Year:  2003        PMID: 14622166     DOI: 10.1046/j.1460-9568.2003.03007.x

Source DB:  PubMed          Journal:  Eur J Neurosci        ISSN: 0953-816X            Impact factor:   3.386


  9 in total

1.  Spectral and temporal processing in rat posterior auditory cortex.

Authors:  Pritesh K Pandya; Daniel L Rathbun; Raluca Moucha; Navzer D Engineer; Michael P Kilgard
Journal:  Cereb Cortex       Date:  2007-07-05       Impact factor: 5.357

2.  Discrimination of direction in fast frequency-modulated tones by rats.

Authors:  Bernhard H Gaese; Isabella King; Christian Felsheim; Joachim Ostwald; Wolfger von der Behrens
Journal:  J Assoc Res Otolaryngol       Date:  2006-01-13

3.  [Evolution of auditory response signal-to-noise ratio in ascending auditory pathways].

Authors:  J Wang; C Song; F Liang
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2021-11-20

Review 4.  Representations in auditory cortex.

Authors:  Tomás Hromádka; Anthony M Zador
Journal:  Curr Opin Neurobiol       Date:  2009-08-10       Impact factor: 6.627

5.  Neural responses in the primary auditory cortex of freely behaving cats while discriminating fast and slow click-trains.

Authors:  Chao Dong; Ling Qin; Yongchun Liu; Xinan Zhang; Yu Sato
Journal:  PLoS One       Date:  2011-10-05       Impact factor: 3.240

6.  A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields.

Authors:  Joel Zylberberg; Jason Timothy Murphy; Michael Robert DeWeese
Journal:  PLoS Comput Biol       Date:  2011-10-27       Impact factor: 4.475

7.  The neuronal responses to repetitive acoustic pulses in different fields of the auditory cortex of awake rats.

Authors:  Lanlan Ma; Xuhui Tai; Liye Su; Lijuan Shi; Enhua Wang; Ling Qin
Journal:  PLoS One       Date:  2013-05-16       Impact factor: 3.240

8.  Sparse representation of sounds in the unanesthetized auditory cortex.

Authors:  Tomás Hromádka; Michael R Deweese; Anthony M Zador
Journal:  PLoS Biol       Date:  2008-01       Impact factor: 8.029

9.  The role of adaptation in generating monotonic rate codes in auditory cortex.

Authors:  Jong Hoon Lee; Xiaoqin Wang; Daniel Bendor
Journal:  PLoS Comput Biol       Date:  2020-02-18       Impact factor: 4.475

  9 in total

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