Neurons in the primary auditory cortex are sensitive to specific temporal patterns: time interval between frequencies and presentation order

1994 ◽  
Vol 19 ◽  
pp. S210
Author(s):  
Hiroshi Riquimaroux
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Temporal Patterns ◽  
Presentation Order ◽  
Time Interval

scholarly journals Temporal Nonlinearity During Recovery From Sequential Inhibition by Neurons in the Cat Primary Auditory Cortex

2006 ◽  
Vol 95 (3) ◽  
pp. 1897-1907 ◽  
Author(s):  
Kyle T. Nakamoto ◽  
Jiping Zhang ◽  
Leonard M. Kitzes
Keyword(s):  
Auditory Cortex ◽  
Recovery Rate ◽  
Primary Auditory Cortex ◽  
Auditory Stimuli ◽  
Time Interval ◽  
Large Set ◽  
Strong Response ◽  
Preceding Stimulus ◽  
Sequential Inhibition ◽  
Response Area

Auditory stimuli occur most often in sequences rather than in isolation. It is therefore necessary to understand how responses to sounds occurring in sequences differ from responses to isolated sounds. Cells in primary auditory cortex (AI) respond to a large set of binaural stimuli when presented in isolation. The set of responses to such stimuli presented at one frequency comprises a level response area. A preceding binaural stimulus can reduce the size and magnitude of level response areas of AI cells. The present study focuses on the effects of the time interval between a preceding stimulus and the stimuli of a level response area in pentobarbital-anesthetized cats. After the offset of a preceding stimulus, the ability of AI cells to respond to succeeding stimuli varies dynamically in time. At short interstimulus intervals (ISI), a preceding stimulus can completely inhibit responses to succeeding stimuli. With increasing ISIs, AI cells respond first to binaural stimuli that evoke the largest responses in the control condition, i.e., not preceded by a stimulus. Recovery rate is nonlinear across the level response area; responses to these most-effective stimuli recover to 70% of control on average 187 ms before responses to other stimuli recover to 70% of their control sizes. During the tens to hundreds of milliseconds that a level response area is reduced in size and magnitude, the selectivity of AI cells is increased for stimuli that evoke the largest responses. This increased selectivity results from a temporal nonlinearity in the recovery of the level response area which protects responses to the most effective binaural stimuli. Thus in a sequence of effective stimuli, a given cell will respond selectively to only those stimuli that evoke a strong response when presented alone.

scholarly journals A comparison of neural responses in the primary auditory cortex, amygdala, and medial prefrontal cortex of cats during auditory discrimination tasks

2019 ◽  
Vol 121 (3) ◽  
pp. 785-798 ◽  
Author(s):  
Zhenling Zhao ◽  
Lanlan Ma ◽  
Yifei Wang ◽  
Ling Qin
Keyword(s):  
Prefrontal Cortex ◽  
Auditory Cortex ◽  
Medial Prefrontal Cortex ◽  
Neural Activity ◽  
Primary Auditory Cortex ◽  
Temporal Patterns ◽  
Auditory Discrimination ◽  
Neural Representation ◽  
Behavioral Choice ◽  
Behavioral Choices

Discriminating biologically relevant sounds is crucial for survival. The neurophysiological mechanisms that mediate this process must register both the reward significance and the physical parameters of acoustic stimuli. Previous experiments have revealed that the primary function of the auditory cortex (AC) is to provide a neural representation of the acoustic parameters of sound stimuli. However, how the brain associates acoustic signals with reward remains unresolved. The amygdala (AMY) and medial prefrontal cortex (mPFC) play keys role in emotion and learning, but it is unknown whether AMY and mPFC neurons are involved in sound discrimination or how the roles of AMY and mPFC neurons differ from those of AC neurons. To examine this, we recorded neural activity in the primary auditory cortex (A1), AMY, and mPFC of cats while they performed a Go/No-go task to discriminate sounds with different temporal patterns. We found that the activity of A1 neurons faithfully coded the temporal patterns of sound stimuli; this activity was not affected by the cats’ behavioral choices. The neural representation of stimulus patterns decreased in the AMY, but the neural activity increased when the cats were preparing to discriminate the sound stimuli and waiting for reward. Neural activity in the mPFC did not represent sound patterns, but it showed a clear association with reward and was modulated by the cats’ behavioral choices. Our results indicate that the initial auditory representation in A1 is gradually transformed into a stimulus–reward association in the AMY and mPFC to ultimately generate a behavioral choice. NEW & NOTEWORTHY We compared the characteristics of neural activities of primary auditory cortex (A1), amygdala (AMY), and medial prefrontal cortex (mPFC) while cats were performing the same auditory discrimination task. Our results show that there is a gradual transformation of the neural code from a faithful temporal representation of the stimulus in A1, which is insensitive to behavioral choices, to an association with the predictive reward in AMY and mPFC, which, to some extent, is correlated with the animal’s behavioral choice.

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 A scoping review of chronotype and temporal patterns of eating of adults: Tools used, findings, and future directions

2021 ◽  
pp. 1-51
Author(s):  
Yan Yin Phoi ◽  
Michelle Rogers ◽  
Maxine P. Bonham ◽  
Jillian Dorrian ◽  
Alison M. Coates
Keyword(s):  
Energy Intake ◽  
Scoping Review ◽  
Assessment Tool ◽  
Temporal Patterns ◽  
Time Interval ◽  
Dark Cycle ◽  
Future Directions ◽  
Meal Skipping ◽  
Optimal Health ◽  
The Difference

Abstract Circadian rhythms, metabolic processes, and dietary intake are inextricably linked. Timing of food intake is a modifiable temporal cue for the circadian system and may be influenced by numerous factors, including individual chronotype—an indicator of an individual’s circadian rhythm in relation to the light-dark cycle. This scoping review examines temporal patterns of eating across chronotypes and assesses tools that have been used to collect data on temporal patterns of eating and chronotype. A systematic search identified thirty-six studies in which aspects of temporal patterns of eating including meal timings; meal skipping; energy distribution across the day; meal frequency; time interval between meals, or meals and wake/sleep times; midpoint of food/energy intake; meal regularity; and duration of eating window were presented in relation to chronotype. Findings indicate that compared to morning chronotypes, evening chronotypes tend to skip meals more frequently, have later mealtimes, and distribute greater energy intake towards later times of the day. More studies should explore the difference in meal regularity and duration of eating window amongst chronotypes. Currently, tools used in collecting data on chronotype and temporal patterns of eating are varied, limiting the direct comparison of findings between studies. Development of a standardised assessment tool will allow future studies to confidently compare findings to inform the development and assessment of guidelines that provide recommendations on temporal patterns of eating for optimal health.

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
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