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Mild Cognitive Impairment Is Characterized by Deficient Brainstem and Cortical Representations of Speech

2017· article· en· W2592540987 on OpenAlexaff
Gavin M. Bidelman, Jill E. Lowther, Sunghee H. Tak, Claude Alain

Bibliographic record

VenueJournal of Neuroscience · 2017
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsPsychologyBrainstemNeuroscienceSensory processingAudiologyCognitionNeuropsychologyNeuroimagingSensory systemPerceptionMedicine

Abstract

fetched live from OpenAlex

Mild cognitive impairment (MCI) is recognized as a transitional phase in the progression toward more severe forms of dementia and is an early precursor to Alzheimer's disease. Previous neuroimaging studies reveal that MCI is associated with aberrant sensory–perceptual processing in cortical brain regions subserving auditory and language function. However, whether the pathophysiology of MCI extends to speech processing before conscious awareness (brainstem) is unknown. Using a novel electrophysiological approach, we recorded both brainstem and cortical speech-evoked brain event-related potentials (ERPs) in older, hearing-matched human listeners who did and did not present with subtle cognitive impairment revealed through behavioral neuropsychological testing. We found that MCI was associated with changes in neural speech processing characterized as hypersensitivity (larger) brainstem and cortical speech encoding in MCI compared with controls in the absence of any perceptual speech deficits. Group differences also interacted with age differentially across the auditory pathway; brainstem responses became larger and cortical ERPs smaller with advancing age. Multivariate classification revealed that dual brainstem–cortical speech activity correctly identified MCI listeners with 80% accuracy, suggesting its application as a biomarker of early cognitive decline. Brainstem responses were also a more robust predictor of individuals' MCI severity than cortical activity. Our findings suggest that MCI is associated with poorer encoding and transfer of speech signals between functional levels of the auditory system and advance the pathophysiological understanding of cognitive aging by identifying subcortical deficits in auditory sensory processing mere milliseconds (<10 ms) after sound onset and before the emergence of perceptual speech deficits. SIGNIFICANCE STATEMENT Mild cognitive impairment (MCI) is a precursor to dementia marked by declines in communication skills. Whether MCI pathophysiology extends below cerebral cortex to affect speech processing before conscious awareness (brainstem) is unknown. By recording neuroelectric brain activity to speech from brainstem and cortex, we show that MCI hypersensitizes the normal encoding of speech information across the hearing brain. Deficient neural responses to speech (particularly those generated from the brainstem) predicted the presence of MCI with high accuracy and before behavioral deficits. Our findings advance the neurological understanding of MCI by identifying a subcortical biomarker in auditory–sensory processing before conscious awareness, which may be a precursor to declines in speech understanding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.353
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations99
Published2017
Admission routes1
Has abstractyes

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