Neural adaptation to silence in the human auditory cortex: a magnetoencephalographic study.
Ontology highlight
ABSTRACT: Introduction
Previous studies demonstrated that a decrement in the N1m response, a major deflection in the auditory evoked response, with sound repetition was mainly caused by bottom-up driven neural refractory periods following brain activation due to sound stimulations. However, it currently remains unknown whether this decrement occurs with a repetition of silences, which do not induce refractoriness.Methods
In the present study, we investigated decrements in N1m responses elicited by five repetitive silences in a continuous pure tone and by five repetitive pure tones in silence using magnetoencephalography.Results
Repetitive sound stimulation differentially affected the N1m decrement in a sound type-dependent manner; while the N1m amplitude decreased from the 1st to the 2nd pure tone and remained constant from the 2nd to the 5th pure tone in silence, a gradual decrement was observed in the N1m amplitude from the 1st to the 5th silence embedded in a continuous pure tone.Conclusions
Our results suggest that neural refractoriness may mainly cause decrements in N1m responses elicited by trains of pure tones in silence, while habituation, which is a form of the implicit learning process, may play an important role in the N1m source strength decrements elicited by successive silences in a continuous pure tone.
SUBMITTER: Okamoto H
PROVIDER: S-EPMC4212114 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Neural responses recorded from auditory cortex exhibit adaptation, a stimulus-specific decrease that occurs when the same sound is presented repeatedly. Stimulus-specific adaptation is thought to facilitate perception in noisy environments. Although adaptation is assumed to arise independently from cortex, this has been difficult to validate directly in vivo. In this study, we used a neural network model of auditory cortex with multicompartmental cell modeling to investigate cortical adaptation. We found that repetitive, non-adapted inputs to layer IV neurons in the model elicited frequency-specific decreases in simulated single neuron, population-level and local field potential (LFP) activity, consistent with stimulus-specific cortical adaptation. Simulated recordings of LFPs, generated solely by excitatory post-synaptic inputs and recorded from layers II/III in the model, showed similar waveform morphologies and stimulus probability effects as auditory evoked responses recorded from human cortex. We tested two proposed mechanisms of cortical adaptation, neural fatigue and neural sharpening, by varying the strength and type of inter- and intra-layer synaptic connections (excitatory, inhibitory). Model simulations showed that synaptic depression modeled in excitatory (AMPA) synapses was sufficient to elicit a reduction in neural firing rate, consistent with neural fatigue. However, introduction of lateral inhibition from local layer II/III interneurons resulted in a reduction in the number of responding neurons, but not their firing rates, consistent with neural sharpening. These modeling results demonstrate that adaptation can arise from multiple neural mechanisms in auditory cortex.
| S-EPMC6133953 | biostudies-literature
Project description:In auditory cortex, neural responses decrease with stimulus repetition, known as adaptation. Adaptation is thought to facilitate detection of novel sounds and improve perception in noisy environments. Although it is well established that adaptation occurs in primary auditory cortex, it is not known whether adaptation also occurs in higher auditory areas involved in processing complex sounds, such as speech. Resolving this issue is important for understanding the neural bases of adaptation and to avoid potential post-operative deficits after temporal lobe surgery for treatment of focal epilepsy. Intracranial electrocorticographic recordings were acquired simultaneously from electrodes implanted in primary and association auditory areas of the right (non-dominant) temporal lobe in a patient with complex partial seizures originating from the inferior parietal lobe. Simple and complex sounds were presented in a passive oddball paradigm. We measured changes in single-trial high-gamma power (70-150 Hz) and in regional and inter-regional network-level activity indexed by cross-frequency coupling. Repetitive tones elicited the greatest adaptation and corresponding increases in cross-frequency coupling in primary auditory cortex. Conversely, auditory association cortex showed stronger adaptation for complex sounds, including speech. This first report of multi-regional adaptation in human auditory cortex highlights the role of the non-dominant temporal lobe in suppressing neural responses to repetitive background sounds (noise). These results underscore the clinical utility of functional mapping to avoid potential post-operative deficits including increased listening difficulties in noisy, real-world environments.
| S-EPMC5422464 | biostudies-literature
Project description:Speech communication in real-world environments requires adaptation to changing acoustic conditions. How the human auditory cortex adapts as a new noise source appears in or disappears from the acoustic scene remain unclear. Here, we directly measured neural activity in the auditory cortex of six human subjects as they listened to speech with abruptly changing background noises. We report rapid and selective suppression of acoustic features of noise in the neural responses. This suppression results in enhanced representation and perception of speech acoustic features. The degree of adaptation to different background noises varies across neural sites and is predictable from the tuning properties and speech specificity of the sites. Moreover, adaptation to background noise is unaffected by the attentional focus of the listener. The convergence of these neural and perceptual effects reveals the intrinsic dynamic mechanisms that enable a listener to filter out irrelevant sound sources in a changing acoustic scene.
| S-EPMC6555798 | biostudies-literature
Project description:How is music represented in the brain? While neuroimaging has revealed some spatial segregation between responses to music versus other sounds, little is known about the neural code for music itself. To address this question, we developed a method to infer canonical response components of human auditory cortex using intracranial responses to natural sounds, and further used the superior coverage of fMRI to map their spatial distribution. The inferred components replicated many prior findings, including distinct neural selectivity for speech and music, but also revealed a novel component that responded nearly exclusively to music with singing. Song selectivity was not explainable by standard acoustic features, was located near speech- and music-selective responses, and was also evident in individual electrodes. These results suggest that representations of music are fractionated into subpopulations selective for different types of music, one of which is specialized for the analysis of song.
| S-EPMC9092957 | biostudies-literature
Project description:Natural environments elicit both phase-locked and non-phase-locked neural responses to the stimulus in the brain. The interpretation of the BOLD signal to date has been based on an association of the non-phase-locked power of high-frequency local field potentials (LFPs), or the related spiking activity in single neurons or groups of neurons. Previous studies have not examined the prediction of the BOLD signal by phase-locked responses. We examined the relationship between the BOLD response and LFPs in the same nine human subjects from multiple corresponding points in the auditory cortex, using amplitude modulated pure tone stimuli of a duration to allow an analysis of phase locking of the sustained time period without contamination from the onset response. The results demonstrate that both phase locking at the modulation frequency and its harmonics, and the oscillatory power in gamma/high-gamma bands are required to predict the BOLD response. Biophysical models of BOLD signal generation in auditory cortex therefore require revision and the incorporation of both phase locking to rhythmic sensory stimuli and power changes in the ensemble neural activity.
| S-EPMC6139034 | biostudies-literature
Project description:It is well established that movement planning recruits motor-related cortical brain areas in preparation for the forthcoming action. Given that an integral component to the control of action is the processing of sensory information throughout movement, we predicted that movement planning might also modulate early sensory cortical areas, readying them for sensory processing during the unfolding action. To test this hypothesis, we performed 2 human functional magnetic resonance imaging studies involving separate delayed movement tasks and focused on premovement neural activity in early auditory cortex, given the area's direct connections to the motor system and evidence that it is modulated by motor cortex during movement in rodents. We show that effector-specific information (i.e., movements of the left vs. right hand in Experiment 1 and movements of the hand vs. eye in Experiment 2) can be decoded, well before movement, from neural activity in early auditory cortex. We find that this motor-related information is encoded in a separate subregion of auditory cortex than sensory-related information and is present even when movements are cued visually instead of auditorily. These findings suggest that action planning, in addition to preparing the motor system for movement, involves selectively modulating primary sensory areas based on the intended action.
| S-EPMC8107793 | biostudies-literature
Project description:Studies in all sensory modalities have demonstrated amplification of early brain responses to attended signals, but less is known about the processes by which listeners selectively ignore stimuli. Here we use MEG and a new paradigm to dissociate the effects of selectively attending, and ignoring in time. Two different tasks were performed successively on the same acoustic stimuli: triplets of tones (A, B, C) with noise-bursts interspersed between the triplets. In the COMPARE task subjects were instructed to respond when tones A and C were of same frequency. In the PASSIVE task they were instructed to respond as fast as possible to noise-bursts. COMPARE requires attending to A and C and actively ignoring tone B, but PASSIVE involves neither attending to nor ignoring the tones. The data were analyzed separately for frontal and auditory-cortical channels to independently address attentional effects on low-level sensory versus putative control processing. We observe the earliest attend/ignore effects as early as 100 ms post-stimulus onset in auditory cortex. These appear to be generated by modulation of exogenous (stimulus-driven) sensory evoked activity. Specifically related to ignoring, we demonstrate that active-ignoring-induced input inhibition involves early selection. We identified a sequence of early (<200 ms post-onset) auditory cortical effects, comprised of onset response attenuation and the emergence of an inhibitory response, and provide new, direct evidence that listeners actively ignoring a sound can reduce their stimulus related activity in auditory cortex by 100 ms after onset when this is required to execute specific behavioral objectives.
| S-EPMC2926275 | biostudies-other
Project description:Sparse sampling functional MRI (ssfMRI) enables stronger primary auditory cortex blood oxygen level-dependent (BOLD) signal by acquiring volumes interspersed with silence, reducing the physiological artifacts associated with scanner noise. Recent calculations of type I error rates associated with resting-state fMRI suggest that the techniques used to model the hemodynamic response function (HRF) might be resulting in higher false positives than is generally acceptable. In the present study, we analyze ssfMRI to determine type I error rates associated with whole brain and primary auditory cortex voxel-wise activation patterns. Study participants (n = 15, age 27.62 ± 3.21 years, range: 22-33 years; 6 females) underwent ssfMRI. An optimized paradigm was used to determine the HRF to auditory stimuli, which was then substituted for silent stimuli to ascertain false positives. We report that common techniques used for analyzing ssfMRI result in high type I error rates. The whole brain and primary auditory cortex voxel-wise analysis resulted in similar error distributions. The number of type I errors for P < 0.05, P < 0.01, and P < 0.001 for the whole brain was 7.88 ± 9.29, 2.37 ± 3.54, and 0.53 ± 0.96% and for the auditory cortex was 9.02 ± 1.79, 2.95 ± 0.91, and 0.58 ± 0.21%, respectively. When conducting a ssfMRI analysis, conservative α level should be employed (α < 0.001) to bolster the results in the face of false positive results.
| S-EPMC6554478 | biostudies-literature
Project description:The human auditory system displays a robust capacity to adapt to sudden changes in background noise, allowing for continuous speech comprehension despite changes in background environments. However, despite comprehensive studies characterizing this ability, the computations that underly this process are not well understood. The first step towards understanding a complex system is to propose a suitable model, but the classical and easily interpreted model for the auditory system, the spectro-temporal receptive field (STRF), cannot match the nonlinear neural dynamics involved in noise adaptation. Here, we utilize a deep neural network (DNN) to model neural adaptation to noise, illustrating its effectiveness at reproducing the complex dynamics at the levels of both individual electrodes and the cortical population. By closely inspecting the model's STRF-like computations over time, we find that the model alters both the gain and shape of its receptive field when adapting to a sudden noise change. We show that the DNN model's gain changes allow it to perform adaptive gain control, while the spectro-temporal change creates noise filtering by altering the inhibitory region of the model's receptive field. Further, we find that models of electrodes in nonprimary auditory cortex also exhibit noise filtering changes in their excitatory regions, suggesting differences in noise filtering mechanisms along the cortical hierarchy. These findings demonstrate the capability of deep neural networks to model complex neural adaptation and offer new hypotheses about the computations the auditory cortex performs to enable noise-robust speech perception in real-world, dynamic environments.
| S-EPMC10510744 | biostudies-literature
Project description:In interpersonal communication, the listener can often see as well as hear the speaker. Visual stimuli can subtly change a listener's auditory perception, as in the McGurk illusion, in which perception of a phoneme's auditory identity is changed by a concurrent video of a mouth articulating a different phoneme. Studies have yet to link visual influences on the neural representation of language with subjective language perception. Here we show that vision influences the electrophysiological representation of phonemes in human auditory cortex prior to the presentation of the auditory stimulus. We used the McGurk effect to dissociate the subjective perception of phonemes from the auditory stimuli. With this paradigm we demonstrate that neural representations in auditory cortex are more closely correlated with the visual stimuli of mouth articulation, which drive the illusory subjective auditory perception, than the actual auditory stimuli. Additionally, information about visual and auditory stimuli transfer in the caudal-rostral direction along the superior temporal gyrus during phoneme perception as would be expected of visual information flowing from the occipital cortex into the ventral auditory processing stream. These results show that visual stimuli influence the neural representation in auditory cortex early in sensory processing and may override the subjective auditory perceptions normally generated by auditory stimuli. These findings depict a marked influence of vision on the neural processing of audition in tertiary auditory cortex and suggest a mechanistic underpinning for the McGurk effect.
| S-EPMC3762867 | biostudies-literature