Multichannel recordings of the human brainstem frequency-following response: Scalp topography, source generators, and distinctions from the transient ABR

Bidelman, Gavin M.

doi:10.1016/j.heares.2015.01.011

Cited by 146 publications

(160 citation statements)

References 84 publications

Supporting

Mentioning

143

Contrasting

Order By: Relevance

“…Synchronization, therefore, may require a high degree of temporal precision in auditory neural processing. Supporting this idea, participants with variable synchronization demonstrate greater trial-to-trial variability in the frequency-following response to speech (Tierney & Kraus, 2013a;Woodruff Carr et al, 2016), which reflects processing within the auditory midbrain (Warrier et al, 2011;Bidelman, 2015). Prior work from our laboratory has shown that synchronization ability is related to high-frequency but not low-frequency inter-trial phase locking .…”

Section: Neural Correlates Of Rhythmic Skillmentioning

confidence: 96%

“…This auditorymotor error correction may depend upon the connection between the auditory midbrain, which precisely represents temporal information on a rapid time scale (Liu, Palmer, & Wallace, 2006;Warrier, Nicol, Abrams, & Kraus, 2011), and the cerebellum, which is responsible for updating motor timing based on sensory feedback (Perrett, Ruiz, & Mauk, 1993). Supporting this idea, inter-trial phase consistency in the fast frequency-following response (FFR), which in part reflects auditory midbrain processing (Chandrasekaran & Kraus, 2010;Warrier et al 2011;Bidelman, 2015), is linked to the variability of synchronization (Tierney & Kraus, 2013a) and the ability to adapt to perturbations while synchronizing .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Individual Differences in Rhythm Skills: Links with Neural Consistency and Linguistic Ability

Tierney¹,

White-Schwoch²,

MacLean³

et al. 2017

Journal of Cognitive Neuroscience

View full text Add to dashboard Cite

Durational patterns provide cues to linguistic structure, and so variations in rhythm skills may have consequences for language development. Understanding individual differences in rhythm skills, therefore, could help explain variability in language ability across the population. We investigated the neural foundations of rhythmic proficiency and its relation to language skills in young adults. We hypothesized that rhythmic abilities can be characterized by at least two constructs, which are tied to independent language abilities and neural profiles. Specifically, we hypothesized that rhythm skills that require integration of information across time rely upon the consistency of slow, low-frequency auditory processing, which we measured using the evoked cortical response. On the other hand, we hypothesized that rhythmic skills that require fine temporal precision rely upon the consistency of fast, higher-frequency auditory processing, which we measured using the frequency following response. Performance on rhythm tests aligned with two constructs: rhythm sequencing and synchronization. Rhythm sequencing and synchronization were linked to the consistency of slow cortical and fast frequency-following responses, respectively. Furthermore, while rhythm sequencing ability was linked to verbal memory, reading, and nonverbal auditory temporal processing, synchronization ability was linked only to nonverbal auditory temporal processing. Thus, rhythm perception at different time scales reflects distinct abilities, which rely on distinct auditory neural resources. In young adults slow rhythmic processing makes the more extensive contribution to language skill.

show abstract

Section: Neural Correlates Of Rhythmic Skillmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Individual Differences in Rhythm Skills: Links with Neural Consistency and Linguistic Ability

Tierney¹,

White-Schwoch²,

MacLean³

et al. 2017

Journal of Cognitive Neuroscience

View full text Add to dashboard Cite

show abstract

“…This vCv contains only voiced elements and is thus optimal for eliciting brainstem FFRs which require low pitched, periodic stimuli. 13 Speech tokens were processed to extract the temporal envelope and fine structure using the Hilbert transform 2 ( Fig. 1).…”

Section: Tfs and Env Speech Stimulimentioning

confidence: 99%

“…13,14 The FFR reflects sustained, subcortical neural phase-locking to the time-frequency characteristics of acoustic signals including speech. 13 Previous FFR studies demonstrate weakened and delayed brainstem responses to speech in the presence of acoustic interferences (e.g., noise and reverberation). 15 While these studies a) Also at: Institute for Intelligent Systems, University of Memphis, Memphis, Tennessee 38152, USA.…”

Section: Introductionmentioning

confidence: 99%

Relative contribution of envelope and fine structure to the subcortical encoding of noise-degraded speech

Bidelman¹

2016

The Journal of the Acoustical Society of America

Self Cite

View full text Add to dashboard Cite

Brainstem frequency-following responses (FFR) were elicited to the speech token /ama/ in noise containing only envelope (ENV) or fine structure (TFS) cues to assess the relative contribution of these temporal features to the neural encoding of degraded speech. Successive cue removal weakened FFRs with noise having the most deleterious effect on TFS coding. Neuro-acoustic and response-to-response correlations revealed speech-FFRs are dominated by stimulus ENV for clean speech, with TFS making a stronger contribution in moderate noise levels. Results suggest that the relative weighting of temporal ENV and TFS cues to the neural transcription of speech depends critically on the degree of noise in the soundscape.

show abstract

“…Electrophysiological recording procedures followed typical procedures used in our laboratory (Bidelman, 2015;Bidelman and Lee, 2015). Participants reclined comfortably in an electro-acoustically shielded booth to facilitate recording of neurophysiologic responses.…”

Section: Data Acquisition and Preprocessingmentioning

confidence: 99%

Tone-language speakers show hemispheric specialization and differential cortical processing of contour and interval cues for pitch

Bidelman

Chung

2015

Neuroscience

View full text Add to dashboard Cite

Multichannel recordings of the human brainstem frequency-following response: Scalp topography, source generators, and distinctions from the transient ABR

Cited by 146 publications

References 84 publications

Individual Differences in Rhythm Skills: Links with Neural Consistency and Linguistic Ability

Individual Differences in Rhythm Skills: Links with Neural Consistency and Linguistic Ability

Relative contribution of envelope and fine structure to the subcortical encoding of noise-degraded speech

Tone-language speakers show hemispheric specialization and differential cortical processing of contour and interval cues for pitch

Contact Info

Product

Resources

About