Electrophysiological differences and similarities in audiovisual speech processing in CI users with unilateral and bilateral hearing loss.

Hearing with a cochlear implant (CI) is limited compared to natural hearing. Although CI users may develop compensatory strategies, it is currently unknown whether these extend from auditory to visual functions, and whether compensatory strategies vary between different CI user groups. To better understand the experience-dependent contributions to multisensory plasticity in audiovisual speech perception, the current event-related potential (ERP) study presented syllables in auditory, visual, and audiovisual conditions to CI users with unilateral or bilateral hearing loss, as well as to normal-hearing (NH) controls. Behavioural results revealed shorter audiovisual response times compared to unisensory conditions for all groups. Multisensory integration was confirmed by electrical neuroimaging, including topographic and ERP source analysis, showing a visual modulation of the auditory-cortex response at N1 and P2 latency. However, CI users with bilateral hearing loss showed a distinct pattern of N1 topography, indicating a stronger visual impact on auditory speech processing compared to CI users with unilateral hearing loss and NH listeners. Furthermore, both CI user groups showed a delayed auditory-cortex activation and an additional recruitment of the visual cortex, and a better lip-reading ability compared to NH listeners. In sum, these results extend previous findings by showing distinct multisensory processes not only between NH listeners and CI users in general, but even between CI users with unilateral and bilateral hearing loss. However, the comparably enhanced lip-reading ability and visual-cortex activation in both CI user groups suggest that these visual improvements are evident regardless of the hearing status of the contralateral ear

The timecourse of multisensory speech processing in unilaterally stimulated cochlear implant users revealed by ERPs.

A cochlear implant (CI) is an auditory prosthesis which can partially restore the auditory function in patients with severe to profound hearing loss. However, this bionic device provides only limited auditory information, and CI patients may compensate for this limitation by means of a stronger interaction between the auditory and visual system. To better understand the electrophysiological correlates of audiovisual speech perception, the present study used electroencephalography (EEG) and a redundant target paradigm. Postlingually deafened CI users and normal-hearing (NH) listeners were compared in auditory, visual and audiovisual speech conditions. The behavioural results revealed multisensory integration for both groups, as indicated by shortened response times for the audiovisual as compared to the two unisensory conditions. The analysis of the N1 and P2 event-related potentials (ERPs), including topographic and source analyses, confirmed a multisensory effect for both groups and showed a cortical auditory response which was modulated by the simultaneous processing of the visual stimulus. Nevertheless, the CI users in particular revealed a distinct pattern of N1 topography, pointing to a strong visual impact on auditory speech processing. Apart from these condition effects, the results revealed ERP differences between CI users and NH listeners, not only in N1/P2 ERP topographies, but also in the cortical source configuration. When compared to the NH listeners, the CI users showed an additional activation in the visual cortex at N1 latency, which was positively correlated with CI experience, and a delayed auditory-cortex activation with a reversed, rightward functional lateralisation. In sum, our behavioural and ERP findings demonstrate a clear audiovisual benefit for both groups, and a CI-specific alteration in cortical activation at N1 latency when auditory and visual input is combined. These cortical alterations may reflect a compensatory strategy to overcome the limited CI input, which allows the CI users to improve the lip-reading skills and to approximate the behavioural performance of NH listeners in audiovisual speech conditions. Our results are clinically relevant, as they highlight the importance of assessing the CI outcome not only in auditory-only, but also in audiovisual speech conditions

Sociodemographic and clinical predictors of depression in children and adolescents: results of a two-year follow-up study

Depressive disorders are a main cause of disability-adjusted life years already in children and adolescents, in whom the clinical picture somewhat differs from adult-onset depression. Thus, we studied sociodemographic and clinical predictors of depression/dysthymia in a sample of minors. Our baseline sample (N=676) included patients at clinical high-risk for psychosis (CHR-P, n=183), inpatients admitted for non-psychotic, non-affective disorders (n=277), and community participants (n=216) of age 7.0 to 17.9 years (43.8% male). They were assessed by clinical psychologists for mental disorders and symptoms with various clinical interviews including the Mini International Neuropsychiatric Interview for Children and Adolescents, which was also used to assess depression/dysthymia in the CHR-P group at 1- and 2-year-follow up (n=117 and 73, respectively). Analyses followed a stepwise procedure at baseline with stepwise logistic regression analyses to identify the final baseline model that was tested in the follow-up samples. The final cross-sectional model included nationality and 13 clinical variables Mild depressive symptoms in particular played a decisive role here. Variables contributing significantly to the prediction varied over time, indicating that CAD depression/dysthymia may require different predictors depending on the follow-up time. Furthermore, the prospective accuracy of ruling out depression/dysthymia was superior to the accuracy of ruling it in. This lower positive likelihood ratio might be overcome in future by stepwise approaches that further stratify risk in those initially identified as at increased risk of depression/dysthymia

In vitro culturing of porcine tracheal mucosa as an ideal model for investigating the influence of drugs on human respiratory mucosa

It has been previously shown that fresh mucosa from different mammals could serve as raw material for in vitro culturing with the differentiation of cilia, which are the most important morphological structures for the function of the mucociliary system. Increasing legal restrictions on the removal of human tissue and changing surgical techniques have led to a lack of fresh human mucosa for culturing. Most of the animals that have been used as donors up to now are genetically not very close to human beings and must all be sacrificed for such studies. We, therefore, established a modified system of culturing mucosa cells from the trachea of pigs, which is available as a regular by-product after slaughtering. With respect to the possibility of developing “beating” cilia, it could be shown that the speed of cell proliferation until adhesion to the coated culture dishes, the formation of conjunctions of cell clusters and the proliferation of cilia were comparable for porcine and human mucosa. Moreover, it could be demonstrated that the porcine cilia beat frequency of 7.57 ± 1.39 Hz was comparable to the human mucosa cells beat frequency of 7.3 ± 1.4 Hz and that this beat frequency was absolutely constant over the investigation time of 360 min. In order to prove whether the reaction to different drugs is comparable between the porcine and human cilia, we initially tested benzalkonium chloride, which is known to be toxic for human cells, followed by naphazoline, which we found in previous studies on human mucosa to be non-toxic. The results clearly showed that the functional and morphological reactions of the porcine ciliated cells to these substances were similar to the reaction we found in the in vitro cultured human mucosa

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression

Importance Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to young patients with depressive syndromes remains unclear. Objectives To evaluate whether psychosis transition can be predicted in patients with CHR or recent-onset depression (ROD) using multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging (sMRI), and polygenic risk scores (PRS) for schizophrenia; to assess models' geographic generalizability; to test and integrate clinicians' predictions; and to maximize clinical utility by building a sequential prognostic system. Design, Setting, and Participants This multisite, longitudinal prognostic study performed in 7 academic early recognition services in 5 European countries followed up patients with CHR syndromes or ROD and healthy volunteers. The referred sample of 167 patients with CHR syndromes and 167 with ROD was recruited from February 1, 2014, to May 31, 2017, of whom 26 (23 with CHR syndromes and 3 with ROD) developed psychosis. Patients with 18-month follow-up (n = 246) were used for model training and leave-one-site-out cross-validation. The remaining 88 patients with nontransition served as the validation of model specificity. Three hundred thirty-four healthy volunteers provided a normative sample for prognostic signature evaluation. Three independent Swiss projects contributed a further 45 cases with psychosis transition and 600 with nontransition for the external validation of clinical-neurocognitive, sMRI-based, and combined models. Data were analyzed from January 1, 2019, to March 31, 2020. Main Outcomes and Measures Accuracy and generalizability of prognostic systems. Results A total of 668 individuals (334 patients and 334 controls) were included in the analysis (mean [SD] age, 25.1 [5.8] years; 354 [53.0%] female and 314 [47.0%] male). Clinicians attained a balanced accuracy of 73.2% by effectively ruling out (specificity, 84.9%) but ineffectively ruling in (sensitivity, 61.5%) psychosis transition. In contrast, algorithms showed high sensitivity (76.0%-88.0%) but low specificity (53.5%-66.8%). A cybernetic risk calculator combining all algorithmic and human components predicted psychosis with a balanced accuracy of 85.5% (sensitivity, 84.6%; specificity, 86.4%). In comparison, an optimal prognostic workflow produced a balanced accuracy of 85.9% (sensitivity, 84.6%; specificity, 87.3%) at a much lower diagnostic burden by sequentially integrating clinical-neurocognitive, expert-based, PRS-based, and sMRI-based risk estimates as needed for the given patient. Findings were supported by good external validation results. Conclusions and RelevanceThese findings suggest that psychosis transition can be predicted in a broader risk spectrum by sequentially integrating algorithms' and clinicians' risk estimates. For clinical translation, the proposed workflow should undergo large-scale international validation.Question Can a transition to psychosis be predicted in patients with clinical high-risk states or recent-onset depression by optimally integrating clinical, neurocognitive, neuroimaging, and genetic information with clinicians' prognostic estimates? Findings In this prognostic study of 334 patients and 334 control individuals, machine learning models sequentially combining clinical and biological data with clinicians' estimates correctly predicted disease transitions in 85.9% of cases across geographically distinct patient populations. The clinicians' lack of prognostic sensitivity, as measured by a false-negative rate of 38.5%, was reduced to 15.4% by the sequential prognostic model. Meaning These findings suggest that an individualized prognostic workflow integrating artificial and human intelligence may facilitate the personalized prevention of psychosis in young patients with clinical high-risk syndromes or recent-onset depression.</p

Objective frequency-specific measurement of hearing threshold using narrow-band chirp stimuli with level-adaptive simultaneous masking

Background In the past, various simulation and measurement paradigms have been introduced and evaluated in order to improve frequency-specific measurement of the hearing threshold using early auditory evoked potentials (EAEP). A promising approach for improvement of detection of stimulus response is the usage of frequency-modulated chirp signals, which optimize the temporal synchrony of neuronal responses along a region of the basilar membrane. Aim of the study This study validated the performance of three generated narrow-band chirp stimuli in combination with a level-adaptive simultaneous masker on a collective of normally hearing subjects. Material and methods In this study 25 normal hearing subjects took part after undergoing pure tone audiometry as well as an objective estimation of the auditory threshold using low, middle and high chirp stimuli. The characteristic EAEP parameters were visually identified before statistical analysis. The characteristic latency level function was conducted using measurements within a stimulus level range from 80 to 0dB HL. Afterwards a comparison of objectively verified auditory threshold and subjective auditory threshold was conducted. Results All objectively determined thresholds of the frequency-specific evoked EAEP were on average below 10dB HL: low chirp at 8.2dB HL, middle chirp at 5.8dB HL and high chirp at 5.4dB HL. The mean difference compared to subjectively determined auditory thresholds at all frequencies was below 3dB and was not significant. Conclusion Brainstem evoked response audiometry (BERA) using a band-limited and level-specific masked chirp stimulus is an efficient method for the determination of frequency-specific excitation thresholds in the clinical routine. The small, insignificant difference compared to the subjectively determined auditory thresholds makes usage of correction factors mostly redundant. Confirming the study results concerning low chirp stimuli so far, the low chirp BERA currently seems to be the method of choice for estimation of auditory threshold at low frequency ranges around 500Hz