Keeping track of who said what: Performance on a modified auditory n-back task with young and older adults

Selective visual and crossmodal impairment in the discrimination of anger and fear expressions in severe alcohol use disorder

BACKGROUND

Severe alcohol use disorder (SAUD) is associated with impaired discrimination of emotional expressions. This deficit appears increased in crossmodal settings, when simultaneous inputs from different sensory modalities are presented. However, so far, studies exploring emotional crossmodal processing in SAUD relied on static faces and unmatched face/voice pairs, thus offering limited ecological validity. Our aim was therefore to assess emotional processing using a validated and ecological paradigm relying on dynamic audio-visual stimuli, manipulating the amount of emotional information available.

METHOD

Thirty individuals with SAUD and 30 matched healthy controls performed an emotional discrimination task requiring to identify five emotions (anger, disgust, fear, happiness, sadness) expressed as visual, auditory, or auditory-visual segments of varying length. Sensitivity indices (d') were computed to get an unbiased measure of emotional discrimination and entered in a Generalized Linear Mixed Model. Incorrect emotional attributions were also scrutinized through confusion matrices.

RESULTS

Discrimination levels varied across sensory modalities and emotions, and increased with stimuli duration. Crucially, performances also improved from unimodal to crossmodal conditions in both groups, but discrimination for anger crossmodal stimuli and fear crossmodal/visual stimuli remained selectively impaired in SAUD. These deficits were not influenced by stimuli duration, suggesting that they were not modulated by the amount of emotional information available. Moreover, they were not associated with systematic emotional error patterns reflecting specific confusions between emotions.

CONCLUSIONS

These results clarify the nature and extent of crossmodal impairments in SAUD and converge with earlier findings to ascribe a specific role for anger and fear in this pathology.

Age-Related Differences in Lexical Access Relate to Speech Recognition in Noise

Vocabulary size has been suggested as a useful measure of “verbal abilities” that correlates with speech recognition scores. Knowing more words is linked to better speech recognition. How vocabulary knowledge translates to general speech recognition mechanisms, how these mechanisms relate to offline speech recognition scores, and how they may be modulated by acoustical distortion or age, is less clear. Age-related differences in linguistic measures may predict age-related differences in speech recognition in noise performance. We hypothesized that speech recognition performance can be predicted by the efficiency of lexical access, which refers to the speed with which a given word can be searched and accessed relative to the size of the mental lexicon. We tested speech recognition in a clinical German sentence-in-noise test at two signal-to-noise ratios (SNRs), in 22 younger (18–35 years) and 22 older (60–78 years) listeners with normal hearing. We also assessed receptive vocabulary, lexical access time, verbal working memory, and hearing thresholds as measures of individual differences. Age group, SNR level, vocabulary size, and lexical access time were significant predictors of individual speech recognition scores, but working memory and hearing threshold were not. Interestingly, longer accessing times were correlated with better speech recognition scores. Hierarchical regression models for each subset of age group and SNR showed very similar patterns: the combination of vocabulary size and lexical access time contributed most to speech recognition performance; only for the younger group at the better SNR (yielding about 85% correct speech recognition) did vocabulary size alone predict performance. Our data suggest that successful speech recognition in noise is mainly modulated by the efficiency of lexical access. This suggests that older adults’ poorer performance in the speech recognition task may have arisen from reduced efficiency in lexical access; with an average vocabulary size similar to that of younger adults, they were still slower in lexical access.