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International audience; In the case of hearing loss, cochlear implants (CI) allow for the restoration of hearing. Despite the advantages of CIs for speech perception, CI users still complain about their poor perception of their auditory environment. Aiming to assess non-verbal auditory perception in CI users, we developed five listening tests. These tests measure pitch change detection, pitch direction identification, pitch short-term memory, auditory stream segregation, and emotional prosody recognition, along with perceived intensity ratings. In order to test the potential benefit of visual cues for pitch processing, the three pitch tests included half of the trials with visual indications to perform the task. We tested 10 normal-hearing (NH) participants with material being presented as original and vocoded sounds, and 10 post-lingually deaf CI users. With the vocoded sounds, the NH participants had reduced scores for the detection of small pitch differences, and reduced emotion recognition and streaming abilities compared to the original sounds. Similarly, the CI users had deficits for small differences in the pitch change detection task and emotion recognition, as well as a decreased streaming capacity. Overall, this assessment allows for the rapid detection of specific patterns of non-verbal auditory perception deficits. The current findings also open new perspectives about how to enhance pitch perception capacities using visual cues.

Although olfactory disorders (OD) are among the most significant symptoms of COVID-19, recovery time from COVID-19-related OD and their consequences on the quality of life remain poorly documented. We investigated the characteristics and behavioral consequences of COVID-19-related OD using a large-scale study involving 3111 French respondents (78% women) to an online questionnaire over a period of 9 months covering different epidemic waves (from 8 April 2020 to 13 January 2021). In the patients who subjectively recovered from COVID-19-related OD (N = 609), recovery occurred on average after 16 days and most of the time within 1 month (“normal” recovery range); 49 subjectively recovered in 1–2.5 months, and several cases took up to 6.5 months. Among the patients with ongoing OD (N = 2502), 974 were outside the “normal” recovery range (persistent OD) and reported OD for 1–10 months. Developing a persistent OD was more likely with increasing age and in women and was more often associated with parosmia and phantosmia. The deleterious impact of COVID-19-related OD on the quality of life was significantly aggravated by OD duration and was more pronounced in women. Because persistent OD is not infrequent after COVID-19, has deleterious consequences on the quality of life, and receives few solutions from the health practitioners, it would be beneficial to implement screening and treatment programs to minimize the long-term behavioral consequences of COVID-19-related OD.

International audience; This article provides an exhaustive description of a new short computerized test to assess on a second-to-second basis the ability of individuals to « stay on task », that is, to apply selectively and repeatedly task-relevant cognitive processes. The task (Bron/Lyon Attention Stability Test, or BLAST) lasts around 1 min, and measures repeatedly the time to find a target letter in a two-by-two letter array, with an update of all letters every new trial across thirty trials. Several innovative psychometric measures of attention stability are proposed based on the instantaneous fluctuations of reaction times throughout the task, and normative data stratified over a wide range of age are provided by a large (>6000) dataset of participants aged 8 to 70. We also detail the large-scale brain dynamics supporting the task from an in-depth study of 32 participants with direct electrophysiological cortical recordings (intracranial EEG) to prove that BLAST involves critically large-scale executive attention networks, with a marked activation of the dorsal attention network and a deactivation of the default-mode network. Accordingly, we show that BLAST performance correlates with scores established by ADHD-questionnaires.

Background Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep scoring. New method Here we propose a sleep staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. The performance of the method was evaluated using polysomnographic data from 15 subjects (electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) recordings). The decision tree, or dendrogram, was obtained using a hierarchical clustering technique and a wide range of time and frequency-domain features were extracted. Feature selection was carried out using forward sequential selection and classification was evaluated using k -fold cross-validation. Results The dendrogram-based SVM (DSVM) achieved mean specificity, sensitivity and overall accuracy of 0.92, 0.74 and 0.88 respectively, compared to expert visual scoring. Restricting DSVM classification to data where both experts’ scoring was consistent (76.73% of the data) led to a mean specificity, sensitivity and overall accuracy of 0.94, 0.82 and 0.92 respectively. Comparison with existing methods The DSVM framework outperforms classification with more standard multi-class “one-against-all” SVM and linear-discriminant analysis. Conclusion The promising results of the proposed methodology suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection.

Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microsturctures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is an important component of many sleep studies in healthy subjects and in patients with sleep disorders. Therefore, procedures for automatic spindle and K-complex detections could provide valuable assistance to researchers and clinicians in the field. We recently proposed a framework for joint spindle and K-complex detector (Lajnef et al. Front Human Neurosci. 9, 414, 2015) based on a tunable Q-factor wavelet transform (TQWT) (Selesnick, IEEE Trans Sign Proc, 59, 3560–3575, 2011) and morphological component analysis (MCA). The current paper provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS) (O’Reilly et al. J Sleep Research, 23, 628-635, 2014), using a wide range of performance metrics. Importantly, these scores were compared to those previously reported for other methods tested on the same database. For spindle detection, our method provided higher performance than most of the alternative methods, as evidenced by all the statistics that take into account both sensitivity and precision (i.e., MCC, F1, Cohen k). Finally, our method is made available to the community via an open-source tool we called Spinky (for spindle and K-complex detection).Thanks to GUI implementation, and access to Matlab and Pyhton resources, Spinky is expected to contribute to an open-science approach which will enhance replicability and reliable comparisons of classifier performances for the detection of sleep EEG microstructure in healthy and diseased subjects.

Congenital amusia is a lifelong disorder of music perception and production. The present study investigated the cerebral bases of impaired pitch perception and memory in congenital amusia using behavioural measures, magnetoencephalography and voxel-based morphometry. Congenital amusics and matched control subjects performed two melodic tasks (a melodic contour task and an easier transposition task); they had to indicate whether sequences of six tones (presented in pairs) were the same or different. Behavioural data indicated that in comparison with control participants, amusics' short-term memory was impaired for the melodic contour task, but not for the transposition task. The major finding was that pitch processing and short-term memory deficits can be traced down to amusics' early brain responses during encoding of the melodic information. Temporal and frontal generators of the N100m evoked by each note of the melody were abnormally recruited in the amusic brain. Dynamic causal modelling of the N100m further revealed decreased intrinsic connectivity in both auditory cortices, increased lateral connectivity between auditory cortices as well as a decreased right fronto-temporal backward connectivity in amusics relative to control subjects. Abnormal functioning of this fronto-temporal network was also shown during the retention interval and the retrieval of melodic information. In particular, induced gamma oscillations in right frontal areas were decreased in amusics during the retention interval. Using voxel-based morphometry, we confirmed morphological brain anomalies in terms of white and grey matter concentration in the right inferior frontal gyrus and the right superior temporal gyrus in the amusic brain. The convergence between functional and structural brain differences strengthens the hypothesis of abnormalities in the fronto-temporal pathway of the amusic brain. Our data provide first evidence of altered functioning of the auditory cortices during pitch perception and memory in congenital amusia. They further support the hypothesis that in neurodevelopmental disorders impacting high-level functions (here musical abilities), abnormalities in cerebral processing can be observed in early brain responses.

Event-related potentials (ERPs) were recorded while subjects were involved in three gender-processing tasks based on human faces and on human hands. In one condition all stimuli were only of one gender, preventing any gender discrimination. In a second condition, faces (or hands) of men and women were intermixed but the gender was irrelevant for the subject's task; hence gender discrimination was assumed to be incidental. In the third condition, the task required explicit gender discrimination; gender processing was therefore assumed to be intentional. Gender processing had no effect on the occipito-temporal negative potential at approximately 170 ms after stimulation (N170 component of the ERP), suggesting that the neural mechanisms involved in the structural encoding of faces are different from those involved in the extraction of gender-related facial features. In contrast, incidental and intentional processing of face (but not hand) gender affected the ERPs between 145 and 185 ms from stimulus onset at more anterior scalp locations. This effect was interpreted as evidence for the direct visual processing of faces as described in Bruce and Young's model [Bruce, V. & Young, A. (1986) Br. J. Psychol., 77, 305-327]. Additional gender discrimination effects were observed for both faces and hands at mid-parietal sites around 45-85 ms latency, in the incidental task only. This difference was tentatively assumed to reflect an early mechanism of coarse visual categorization. Finally, intentional (but not incidental) gender processing affected the ERPs during a later epoch starting from approximately 200 ms and ending at approximately 250 ms for faces, and approximately 350 ms for hands. This later effect might be related to attention-based gender categorization or to a more general categorization activity.

MMN oddball paradigms are frequently used to assess auditory (dys)functions in clinical populations, or the influence of various factors (such as drugs and alcohol) on auditory processing. A widely used procedure is to compare the MMN responses between two groups of subjects (e.g. patients vs controls), or between experimental conditions in the same group. To correctly interpret these comparisons, it is important to take into account the multiple brain generators that produce the MMN response. To disentangle the different components of the MMN, we describe the advantages of scalp current density (SCD)—or surface Laplacian—computation for ERP analysis. We provide a short conceptual and mathematical description of SCDs, describe their properties, and illustrate with examples from published studies how they can benefit MMN analysis. We conclude with practical tips on how to correctly use and interpret SCDs in this context.

In noisy environments, we use auditory selective attention to actively ignore distracting sounds and select relevant information, as during a cocktail party to follow one particular conversation. The present electrophysiological study aims at deciphering the spatiotemporal organization of the effect of selective attention on the representation of concurrent sounds in the human auditory cortex. Sound onset asynchrony was manipulated to induce the segregation of two concurrent auditory streams. Each stream consisted of amplitude modulated tones at different carrier and modulation frequencies. Electrophysiological recordings were performed in epileptic patients with pharmacologically resistant partial epilepsy, implanted with depth electrodes in the temporal cortex. Patients were presented with the stimuli while they either performed an auditory distracting task or actively selected one of the two concurrent streams. Selective attention was found to affect steady-state responses in the primary auditory cortex, and transient and sustained evoked responses in secondary auditory areas. The results provide new insights on the neural mechanisms of auditory selective attention: stream selection during sound rivalry would be facilitated not only by enhancing the neural representation of relevant sounds, but also by reducing the representation of irrelevant information in the auditory cortex. Finally, they suggest a specialization of the left hemisphere in the attentional selection of fine-grained acoustic information.