Ripple Analysis in Ferret Primary Auditory Cortex. 3. Prediction of Unit Responses to Arbitrary Spectral Profiles

1995 ◽  
Author(s):  
Shihab A. Shamma ◽  
Huib Versnel
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Spectral Profiles

scholarly journals Analysis of dynamic spectra in ferret primary auditory cortex. II. Prediction of unit responses to arbitrary dynamic spectra

1996 ◽  
Vol 76 (5) ◽  
pp. 3524-3534 ◽  
Author(s):  
N. Kowalski ◽  
D. A. Depireux ◽  
S. A. Shamma
Keyword(s):  
Auditory Cortex ◽  
Transfer Functions ◽  
Superposition Principle ◽  
Primary Auditory Cortex ◽  
Impulse Response Functions ◽  
Spectral Profile ◽  
Complex Dynamic ◽  
Dynamic Spectra ◽  
Spectral Profiles ◽  
Linear Manner

1. Responses of single units and multiunit clusters were recorded in the ferret primary auditory cortex (AI) with the use of broadband complex dynamic spectra. Previous work has demonstrated that simpler spectra consisting of single moving ripples (i.e., sinusoidally modulated spectral profiles that travel at a constant velocity along the logarithmic frequency axis) could be used effectively to characterize the response fields and transfer functions of AI cells. 2. A complex dynamic spectral profile can be thought of as being the sum of moving ripple spectra. Such a decomposition can be computed from a two-dimensional spectrotemporal Fourier transform of the dynamic spectral profile with moving ripples as the basis function. 3. Therefore, if AI units were essentially linear, satisfying the superposition principle, then their responses to arbitrary dynamic spectra could be predicted from the responses to single moving ripples, i.e., from the units' response fields and transfer functions (spectral and temporal impulse response functions, respectively). 4. This conjecture was tested and confirmed with data from 293 combinations of moving ripples, involving complex spectra composed of up to 15 moving ripples of different ripple frequencies and velocities. For each case, response predictions based on the unit transfer functions were compared with measured responses. The correlation between predicted and measured responses was found to be consistently high (84% with rho > 0.6). 5. The distribution of response parameters suggests that AI cells may encode the profile of a dynamic spectrum by performing a multiscale spectrotemporal decomposition of the dynamic spectral profile in a largely linear manner.

Intensity Tuning of Neurons in The Primary Auditory Cortex of Albino Mouse

2013 ◽  
Vol 40 (4) ◽  
pp. 365
Author(s):  
Qiao-Zhen QI ◽  
Wen-Juan SI ◽  
Feng LUO ◽  
Xin WANG
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex

Influence of Primary Auditory Cortex in the Characterization of Autism Spectrum in Young Adults using Brain Connectivity Parameters and Deep Belief Networks: An fMRI Study

2020 ◽  
Vol 16 (9) ◽  
pp. 1059-1073
Author(s):  
Vidhusha Srinivasan ◽  
N. Udayakumar ◽  
Kavitha Anandan
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Language Processing ◽  
Brain Connectivity ◽  
Primary Auditory Cortex ◽  
Autism Spectrum ◽  
Belief Networks ◽  
Deep Belief Networks ◽  
High Functioning ◽  
Low Functioning

Background: The spectrum of autism encompasses High Functioning Autism (HFA) and Low Functioning Autism (LFA). Brain mapping studies have revealed that autism individuals have overlaps in brain behavioural characteristics. Generally, high functioning individuals are known to exhibit higher intelligence and better language processing abilities. However, specific mechanisms associated with their functional capabilities are still under research. Objective: This work addresses the overlapping phenomenon present in autism spectrum through functional connectivity patterns along with brain connectivity parameters and distinguishes the classes using deep belief networks. Methods: The task-based functional Magnetic Resonance Images (fMRI) of both high and low functioning autistic groups were acquired from ABIDE database, for 58 low functioning against 43 high functioning individuals while they were involved in a defined language processing task. The language processing regions of the brain, along with Default Mode Network (DMN) have been considered for the analysis. The functional connectivity maps have been plotted through graph theory procedures. Brain connectivity parameters such as Granger Causality (GC) and Phase Slope Index (PSI) have been calculated for the individual groups. These parameters have been fed to Deep Belief Networks (DBN) to classify the subjects under consideration as either LFA or HFA. Results: Results showed increased functional connectivity in high functioning subjects. It was found that the additional interaction of the Primary Auditory Cortex lying in the temporal lobe, with other regions of interest complimented their enhanced connectivity. Results were validated using DBN measuring the classification accuracy of 85.85% for high functioning and 81.71% for the low functioning group. Conclusion: Since it is known that autism involves enhanced, but imbalanced components of intelligence, the reason behind the supremacy of high functioning group in language processing and region responsible for enhanced connectivity has been recognized. Therefore, this work that suggests the effect of Primary Auditory Cortex in characterizing the dominance of language processing in high functioning young adults seems to be highly significant in discriminating different groups in autism spectrum.

scholarly journals Source identity shapes spatial preference in primary auditory cortex during active navigation

2021 ◽  
Author(s):  
Diana Amaro ◽  
Dardo N. Ferreiro ◽  
Benedikt Grothe ◽  
Michael Pecka
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Spatial Preference

scholarly journals Neuronal figure-ground responses in primate primary auditory cortex

Cell Reports ◽  
2021 ◽  
Vol 35 (11) ◽  
pp. 109242
Author(s):  
Felix Schneider ◽  
Fabien Balezeau ◽  
Claudia Distler ◽  
Yukiko Kikuchi ◽  
Jochem van Kempen ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex

scholarly journals Recovery of functional and structural age-related changes in the rat primary auditory cortex with operant training

2010 ◽  
Vol 107 (31) ◽  
pp. 13900-13905 ◽  
Author(s):  
E. de Villers-Sidani ◽  
L. Alzghoul ◽  
X. Zhou ◽  
K. L. Simpson ◽  
R. C. S. Lin ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Age Related ◽  
Age Related Changes ◽  
Operant Training
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