Temporal resolution of the human primary auditory cortex in gap detection

Neuroreport ◽  
2002 ◽  
Vol 13 (17) ◽  
pp. 2203-2207 ◽  
Author(s):  
Andr?? Rupp ◽  
Alexander Gutschalk ◽  
Sebastian Hack ◽  
Michael Scherg
2000 ◽  
Vol 84 (3) ◽  
pp. 1453-1463 ◽  
Author(s):  
Jos J. Eggermont

Responses of single- and multi-units in primary auditory cortex were recorded for gap-in-noise stimuli for different durations of the leading noise burst. Both firing rate and inter-spike interval representations were evaluated. The minimum detectable gap decreased in exponential fashion with the duration of the leading burst to reach an asymptote for durations of 100 ms. Despite the fact that leading and trailing noise bursts had the same frequency content, the dependence on leading burst duration was correlated with psychophysical estimates of across frequency channel (different frequency content of leading and trailing burst) gap thresholds in humans. The duration of the leading burst plus that of the gap was represented in the all-order inter-spike interval histograms for cortical neurons. The recovery functions for cortical neurons could be modeled on basis of fast synaptic depression and after-hyperpolarization produced by the onset response to the leading noise burst. This suggests that the minimum gap representation in the firing pattern of neurons in primary auditory cortex, and minimum gap detection in behavioral tasks is largely determined by properties intrinsic to those, or potentially subcortical, cells.


2020 ◽  
Vol 30 (8) ◽  
pp. 4465-4480 ◽  
Author(s):  
Bshara Awwad ◽  
Maciej M Jankowski ◽  
Israel Nelken

Abstract The ability to detect short gaps in noise is an important tool for assessing the temporal resolution in the auditory cortex. However, the mere existence of responses to temporal gaps bounded by two short broadband markers is surprising, because of the expected short-term suppression that is prevalent in auditory cortex. Here, we used in-vivo intracellular recordings in anesthetized rats to dissect the synaptic mechanisms that underlie gap-related responses. When a gap is bounded by two short markers, a gap termination response was evoked by the onset of the second marker with minimal contribution from the offset of the first marker. Importantly, we show that the gap termination response was driven by a different (potentially partially overlapping) synaptic population than that underlying the onset response to the first marker. This recruitment of additional synaptic resources is a novel mechanism contributing to the important perceptual task of gap detection.


1999 ◽  
Vol 81 (5) ◽  
pp. 2570-2581 ◽  
Author(s):  
Jos J. Eggermont

Neural correlates of gap detection in three auditory cortical fields in the cat. Mimimum detectable gaps in noise in humans are independent of the position of the gap, whereas in cat primary auditory cortex (AI) they are position dependent. The position dependence in other cortical areas is not known and may resolve this contrast. This study presents minimum detectable gap-in-noise values for which single-unit (SU), multiunit (MU) recordings and local field potentials (LFPs) show an onset response to the noise after the gap. The gap, which varied in duration between 5 and 70 ms, was preceded by a noise burst of either 5 ms (early gap) or 500 ms (late gap) duration. In 10 cats, simultaneous recordings were made with one electrode each in AI, anterior auditory field (AAF), and secondary auditory cortex (AII). In nine additional cats, two electrodes were inserted in AI and one in AAF. Minimum detectable gaps based on SU, MU, or LFP data in each cortical area were the same. In addition, very similar minimum early-gap values were found in all three areas (means, 36.1–41.7 ms). The minimum late-gap values were also similar in AI and AII (means, 11.1 and 11.7 ms), whereas AAF showed significantly larger minimum late-gap durations (mean 21.5 ms). For intensities >35 dB SPL, distributions of minimum early-gap durations in AAF and AII had modal values at ∼45 ms. In AI, the distribution was more uniform. Distributions for minimum late-gap duration were skewed toward low values (mode at 5 ms), but high values (≤60 ms) were found infrequently as well. A small fraction of units showed a response after the gap only for early-gap durations <20 ms. In AI and AII, the mean minimum early- and late-gap durations decreased significantly with increase in the neuron’s characteristic frequency (CF), whereas the lower boundary for the minimum early gap was CF independent. The findings suggest that human within-perceptual-channel gap detection, showing no dependence of the minimum detectable gap on the duration of the leading noise burst, likely is based on the lower envelope of the distribution of neural minimum gap values of units in AI and AAF. In contrast, across-perceptual-channel gap detection, which shows a decreasing minimum detectable gap with increasing duration of the leading noise burst, likely is based on the comparison ofon responses from populations of neurons that converge on units in AII.


2017 ◽  
Author(s):  
Alina Baltus ◽  
Christoph Siegfried Herrmann

AbstractRecent research provides evidence for a functional role of brain oscillations for perception. For example, auditory temporal resolution seems to be linked to individual gamma frequency of auditory cortex. Individual gamma frequency not only correlates with performance in between-channel gap detection tasks but can be modulated via auditory transcranial alternating current stimulation. Modulation of individual gamma frequency is accompanied by an improvement in gap detection performance. Aging changes electrophysiological frequency components and sensory processing mechanisms. Therefore, we conducted a study to investigate the link between individual gamma frequency and gap detection performance in elderly people using auditory transcranial alternating current stimulation. In a within-subject design, nine participants were electrically stimulated with two individualized transcranial alternating current stimulation frequencies: 3 Hz above their individual gamma frequency (experimental condition) and 4 Hz below their individual gamma frequency (control condition) while they were performing a between-channel gap detection task. As expected, individual gamma frequencies correlated significantly with gap detection performance at baseline and in the experimental condition, transcranial alternating current stimulation modulated gap detection performance. In the control condition, stimulation did not modulate gap detection performance. In addition, in elderly, the effect of transcranial alternating current stimulation on auditory temporal resolution seems to be dependent on endogenous frequencies in auditory cortex: elderlies with slower individual gamma frequencies and lower auditory temporal resolution profit from auditory transcranial alternating current stimulation and show increased gap detection performance during stimulation. Our results strongly suggest individualized transcranial alternating current stimulation protocols for successful modulation of performance.


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

Author(s):  
Vidhusha Srinivasan ◽  
N. Udayakumar ◽  
Kavitha Anandan

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.


2021 ◽  
Author(s):  
Diana Amaro ◽  
Dardo N. Ferreiro ◽  
Benedikt Grothe ◽  
Michael Pecka

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