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Zink, M.

Publications and source records attributed to Zink, M..

2 recordsLinked to original sources

Degraded neural coding of temporal fine structure with age predicts effortful listening in multi-talker environments

Middle age represents a critical window for early detection of neurophysiological decline. Hearing loss is increasingly recognized as both an early marker of neural degeneration and a modifiable risk factor for dementia. Yet many adults report difficulty understanding speech in noise despite normal audiograms, highlighting the limitations of current clinical tests that fail to capture the underlying physiology or effort required for real-world listening. Beyond hearing thresholds, speech comprehension in complex environments depends on precise neural encoding of temporal fine structure (TFS) cues that convey pitch and spatial information. Here, we use a noninvasive EEG-based measure of neural phase-locking (frequency modulation following responses or FMFRs) to quantify TFS encoding in young and middle-aged adults with normal hearing thresholds. Middle-aged listeners exhibited reduced FMFR amplitudes and shallower discriminability slopes, reflecting diminished neural synchrony despite preserved hearing thresholds. Using a multi-talker speech task we further found that pupil-indexed listening effort was significantly greater in middle-aged adults despite matched accuracy across groups. Further, increases in listening effort were predicted by decreases in TFS encoding. Together, these results reveal that degraded neural encoding of TFS underlies subclinical listening difficulties and increased cognitive load, establishing the FMFR as a sensitive biomarker of hidden auditory neural decline. SignificanceUnderstanding speech in noisy environments depends on precise neural encoding of temporal fine structure (TFS) cues. Using a noninvasive EEG metric, the FMFR, we show that neural TFS coding in the peripheral auditory system declines markedly by midlife, even when hearing thresholds and speech performance are normal. These neural deficits predict elevated pupil-indexed listening effort during multi-talker speech perception, revealing that subclinical degradation of temporal coding increases cognitive load in everyday listening. The FMFR thus provides a promising biomarker for early auditory neural decline and its downstream cognitive consequences.

neuroscience↗

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk.

ImportanceBetween-subject variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients. However, such group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature\n\nObjectiveTo compare brain structural variability between individuals with SZ and healthy controls (HC) and to test if respective variability reflects the polygenic risk for SZ (PRS) in HC.\n\nDesign, Setting, and ParticipantsWe compared MRI derived cortical thickness and subcortical volumes between 2,010 healthy controls and 1,151 patients with SZ across 16 cohorts. Secondly, we tested for associations between PRS and MRI features in 12,490 participants from UK Biobank.\n\nMain Outcomes and MeasuresWe modeled mean and dispersion effects of SZ and PRS using double generalized linear models. We performed vertex-wise analyses for thickness, and region-of-interest analysis for cortical, subcortical and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, controlling for intracranial volume and population covariates, test of robustness of PRS threshold, and outlier removal.\n\nResultsCompared to controls, patients with SZ showed higher heterogeneity in cortical thickness, cortical and ventricle volumes, and hippocampal subfields. Higher PRS was associated with thinner frontal and temporal cortices, as well as smaller left CA2/3, but was not significantly associated with dispersion.\n\nConclusion and relevanceSZ is associated with substantial brain structural heterogeneity beyond the mean differences. These findings possibly reflect higher differential sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of SZ. Higher PRS for SZ was associated with thinner fronto-temporal cortices and smaller subcortical volumes, but there were no significant associations with the heterogeneity in these measures, i.e. the variability among individuals with high PRS were comparable to the variability among individuals with low PRS. This suggests that brain variability in SZ results from interactions between environmental and genetic factors that are not captured by the PGR. Factors contributing to heterogeneity in fronto-temporal cortices and hippocampus are thus key to further our understanding of how genetic and environmental factors shape brain biology in SZ.\n\nKey PointsQuestion: Is schizophrenia and its polygenic risk associated with brain structural heterogeneity in addition to mean changes?\n\nFindings: In a sample of 1151 patients and 2010 controls, schizophrenia was associated with increased heterogeneity in fronto-temporal thickness, cortical, ventricle, and hippocampal volumes, besides robust reductions in mean estimates. In an independent sample of 12,490 controls, polygenic risk for schizophrenia was associated with thinner fronto-temporal cortices and smaller CA2/3 of the left hippocampus, but not with heterogeneity.\n\nMeaning: Schizophrenia is associated with increased inter-individual differences in brainstructure, possibly reflecting clinical heterogeneity, gene-environment interactions, or secondary disease factors.

neuroscience↗