Localization of human supratemporal auditory areas from intracerebral auditory evoked potentials using distributed source models

Yvert, Blaise; Fischer, Catherine; Bertrand, Olivier; Pernier, J.

doi:10.1016/j.neuroimage.2005.05.056

Cited by 114 publications

(107 citation statements)

References 51 publications

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“…The corresponding locations in the right hemisphere are numerically indistinguishable. The difference in ECD location observed in the left hemisphere could reflect a subtle difference in the distributions of neural activity occurring within overlapping regions of the STG, leading to differently estimated locations for the modeled sources (44).…”

Section: Resultsmentioning

confidence: 99%

Perceptual learning of degraded speech by minimizing prediction error

Sohoglu

Davis

2016

Proc. Natl. Acad. Sci. U.S.A.

105

154

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Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single-and dualmechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learninginduced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech.perceptual learning | predictive coding | speech perception | magnetoencephalography | vocoded speech S uccessful perception in a dynamic and noisy environment critically depends on the brain's capacity to change how sensory input is processed based on past experience. Consider the way in which perception is enhanced by accurate prior knowledge or expectations. Sudden and dramatic changes in subjective experience can occur when a distorted and otherwise unrecognizable perceptual object is seen or heard after the object's identity is revealed (1-4). Such effects occur almost immediately; striking changes in perceptual outcomes occur over a timescale of seconds or less. However, not all effects of past experience emerge as rapidly as these effects of prior knowledge. With perceptual learning, practice in perceiving certain types of stimuli results in gradual and incremental improvements in perception that develop over a timescale of minutes or longer (Fig. 1A) (5, 6, 7). Critically, perceptual learning can generalize beyond the stimuli experienced during training, e.g., to visual forms presented in dif...

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Section: Resultsmentioning

confidence: 99%

Perceptual learning of degraded speech by minimizing prediction error

Sohoglu

Davis

2016

Proc. Natl. Acad. Sci. U.S.A.

105

154

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“…It should be noted that the N1 and P2 activities are likely generated by several cortical sources and were not confined to one point as reported here. For example, a recent study by Yvert et al [27], where distributed source model was used to localize the N1 activity applied to intracranial recordings, suggested a more distributed activity for the N1 wave, which spanned Heschl's gyrus and sulcus, planum temporale, and superior temporal gyrus. Discrete modeling of these activities (used here) may reflect the location of the center of mass of all generators, biased toward the predominant contributor.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity of EEG and MEG to the N1 and P2 Auditory Evoked Responses Modulated by Spectral Complexity of Sounds

et al. 2007

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Acoustic complexity of a stimulus has been shown to modulate the electromagnetic N1 (latency ~110 ms) and P2 (latency ~190 ms) auditory evoked responses. We compared the relative sensitivity of electroencephalography (EEG) and magnetoencephalography (MEG) to these neural correlates of sensation. Simultaneous EEG and MEG were recorded while participants listened to three variants of a piano tone. The piano stimuli differed in their number of harmonics: the fundamental frequency (f 0 ), only,or f 0 and the first two or eight harmonics. The root mean square (RMS) of the amplitude of P2 but not N1 increased with spectral complexity of the piano tones in EEG and MEG. The RMS increase for P2 was more prominent in EEG than MEG, suggesting important radial sources contributing to the P2 only in EEG. Source analysis revealing contributions from radial and tangential sources was conducted to test this hypothesis. Source waveforms revealed a significant increase in the P2 radial source amplitude in EEG with increased spectral complexity of piano tones. The P2 of the tangential source waveforms also increased in amplitude with increased spectral complexity in EEG and MEG. The P2 auditory evoked response is thus represented by both tangential (gyri) and radial (sulci) activities. The radial contribution is expressed preferentially in EEG, highlighting the importance of combining EEG with MEG where complex source configurations are suspected.

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“…Indeed, the modulation of the positive auditory component peaking ϳ120 ms is the analog of the auditory N1 decrease found in scalp ERPs using the exact same experimental paradigm (Besle et al, 2004b). This component is recorded with a positive polarity in intracranial data, because electrodes are located under the supratemporal cortical surface (Godey et al, 2001;Yvert et al, 2005). Modulation of earlier auditory components and visual responses in auditory cortex were not observed on the scalp, probably because they are All latencies (in ms) are measured relative to the auditory syllable onset; 600ϩ indicates that the response continues after 600 ms.…”

Section: Two Forms Of Audiovisual Interaction In the Secondary Auditomentioning

confidence: 90%

“…Some 10 milliseconds later, the superior temporal cortex was activated with a spatial profile very similar to that of the transient auditory components peaking ϳ65 or 120 ms at the same electrode. Because these transient auditory components are known to be generated in the auditory cortex (Liégeois-Chauvel et al, 1994;Yvert et al, 2005), this visual response was thus probably also generated in the auditory cortex. Those first two types of visual responses (in MT/V5 and in auditory cortex) occurred well before visual activations in other parts of the brain (at least those investigated in the study).…”

Section: Direct Feedforward Visual Activation Of the Secondary Auditomentioning

confidence: 99%

Visual Activation and Audiovisual Interactions in the Auditory Cortex during Speech Perception: Intracranial Recordings in Humans

Besle¹,

Fischer²,

et al. 2008

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Hemodynamic studies have shown that the auditory cortex can be activated by visual lip movements and is a site of interactions between auditory and visual speech processing. However, they provide no information about the chronology and mechanisms of these crossmodal processes. We recorded intracranial event-related potentials to auditory, visual, and bimodal speech syllables from depth electrodes implanted in the temporal lobe of 10 epileptic patients (altogether 932 contacts). We found that lip movements activate secondary auditory areas, very shortly (Ϸ10 ms) after the activation of the visual motion area MT/V5. After this putatively feedforward visual activation of the auditory cortex, audiovisual interactions took place in the secondary auditory cortex, from 30 ms after sound onset and before any activity in the polymodal areas. Audiovisual interactions in the auditory cortex, as estimated in a linear model, consisted both of a total suppression of the visual response to lipreading and a decrease of the auditory responses to the speech sound in the bimodal condition compared with unimodal conditions. These findings demonstrate that audiovisual speech integration does not respect the classical hierarchy from sensory-specific to associative cortical areas, but rather engages multiple cross-modal mechanisms at the first stages of nonprimary auditory cortex activation.

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Localization of human supratemporal auditory areas from intracerebral auditory evoked potentials using distributed source models

Cited by 114 publications

References 51 publications

Perceptual learning of degraded speech by minimizing prediction error

Perceptual learning of degraded speech by minimizing prediction error

Sensitivity of EEG and MEG to the N1 and P2 Auditory Evoked Responses Modulated by Spectral Complexity of Sounds

Visual Activation and Audiovisual Interactions in the Auditory Cortex during Speech Perception: Intracranial Recordings in Humans

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