Biology subjects

De Clercq, P.

Publications and source records attributed to De Clercq, P..

5 recordsLinked to original sources

bioRxiv2023

EEG reveals brain network alterations in chronic aphasia during natural speech listening.

Aphasia is a common consequence of a stroke which affects language processing. In search of an objective biomarker for aphasia, we used EEG to investigate how functional network patterns in the cortex are affected in persons with post-stroke chronic aphasia (PWA) compared to healthy controls (HC) while they are listening to a story. EEG was recorded from 22 HC and 27 PWA while they listened to a 25-min-long story. Functional connectivity between scalp regions was measured with the weighted phase lag index. The Network- Based Statistics toolbox was used to detect altered network patterns and to investigate correlations with behavioural tests within the aphasia group. Differences in network geometry were assessed by means of graph theory and a targeted node-attack approach. Group-classification accuracy was obtained with a support vector machine classifier. PWA showed stronger inter-hemispheric connectivity compared to HC in the theta-band (4.5-7 Hz), whilst a weaker subnetwork emerged in the low-gamma band (30.5-49 Hz). Two subnetworks correlated with semantic fluency in PWA respectively in delta- (1-4 Hz) and low-gamma-bands. In the theta-band network, graph alterations in PWA emerged at both local and global level, whilst only local changes were found in the low-gamma-band network. As assessed with the targeted node-attack, PWA exhibit a more scale-free network compared to HC. Network metrics effectively discriminated PWA and HC (AUC = 83%). Overall, we showed for that EEG-network metrics are effective biomarkers to assess natural speech processing in chronic aphasia. We hypothesize that the detected alterations reflect compensatory mechanisms associated with recovery.

neuroscience↗

bioRxiv2023

Exploring neural tracking of acoustic and linguistic speech representations in individuals with post-stroke aphasia

Aphasia is a communication disorder that affects processing of language at different levels (e.g., acoustic, phonological, semantic). Recording brain activity via EEG while people listen to a continuous story allows to analyze brain responses to acoustic and linguistic properties of speech. When the neural activity aligns with these speech properties, it is referred to as neural tracking. Even though measuring neural tracking of speech may present an interesting approach to studying aphasia in an ecologically valid way, it has not yet been investigated in individuals with stroke-induced aphasia. Here, we explored processing of acoustic and linguistic speech representations in individuals with aphasia in the chronic phase after stroke and age-matched healthy controls. We found decreased neural tracking of acoustic speech representations (envelope and envelope onsets) in individuals with aphasia. In addition, word surprisal displayed decreased amplitudes in individuals with aphasia around 195 ms over frontal electrodes, although this effect was not corrected for multiple comparisons. These results show that there is potential to capture language processing impairments in individuals with aphasia by measuring neural tracking of continuous speech. However, more research is needed to validate these results. Nonetheless, this exploratory study shows that neural tracking of naturalistic, continuous speech presents a powerful approach to studying aphasia. Key pointsO_LIIndividuals with aphasia display decreased encoding of acoustic speech properties (envelope and its onsets) in comparison to healthy controls. C_LIO_LINeural responses to word surprisal reveal decreased amplitudes in individuals with aphasia around 195 ms processing time (not corrected for multiple comparisons). C_LIO_LINeural tracking of natural speech can be used to study speech processing impairments in aphasia. C_LI

neuroscience↗

bioRxiv2022

Tuning in on auditory details is difficult: Individuals with aphasia show impaired acoustic and phonemic processing

Acoustic and phonemic processing are understudied in aphasia, a language disorder that can affect different levels and modalities of language processing. For successful speech comprehension, processing of the speech envelope is necessary, which relates to amplitude changes over time (e.g., the rise times). Moreover, to identify speech sounds (i.e., phonemes), efficient processing of spectro-temporal changes as reflected in formant transitions is essential. Given the lack of aphasia studies on these aspects, we tested rise time processing and phoneme identification in 29 individuals with post-stroke aphasia and 23 healthy age-matched controls. We found significantly lower performance in the aphasia group than in the control group on both tasks, even when controlling for individual differences in hearing levels and cognitive functioning. Further, by conducting an individual deviance analysis, we found a low-level acoustic or phonemic processing impairment in 76% of individuals with aphasia. Additionally, we investigated whether this impairment would propagate to higher-level language processing and found that rise time processing predicts phonological processing performance in individuals with aphasia. These findings show that it is important to develop diagnostic and treatment tools that target low-level language processing mechanisms.

neuroscience↗

bioRxiv2022

Beyond Linear Neural Envelope Tracking: A Mutual Information Approach

The human brain tracks the temporal envelope of speech, which contains essential cues for speech understanding. Linear models are the most common tool to study neural envelope tracking. However, information on how speech is processed can be lost since nonlinear relations are precluded. As an alternative, mutual information (MI) analysis can detect both linear and nonlinear relations. Yet, several different approaches to calculating MI are applied without consensus on which approach to use. Furthermore, the added value of nonlinear techniques remains a subject of debate in the field. To resolve this, we applied linear and MI analyses to electroencephalography (EEG) data of participants listening to continuous speech. Comparing the different MI approaches, we conclude that results are most reliable and robust using the Gaussian copula approach, which first transforms the data to standard Gaussians. With this approach, the MI analysis is a valid technique for studying neural envelope tracking. Like linear models, it allows spatial and temporal interpretations of speech processing, peak latency analyses, and applications to multiple EEG channels combined. Finally, we demonstrate that the MI analysis can detect nonlinear components on the single-subject level, beyond the limits of linear models. We conclude that the MI analysis is a more informative tool for studying neural envelope tracking. Significance statementIn the present study, we addressed key methodological considerations for MI applications. Traditional MI methodologies require the estimation of a probability distribution at first. We show that this step can introduce a bias in the results and, consequently, severely impact interpretations. As an alternative, we propose using the parametric Gaussian copula method, which we demonstrated to be robust against biases. Second, using the parametric MI analysis, we show that there is nonlinear variance in the EEG data that the envelope of speech can explain at the single-subject level, proving its added value to neural envelope tracking. We conclude that the MI analysis is a statistically more powerful tool for studying neural envelope tracking than linear models. In addition, it retains spatial and temporal characteristics of speech processing which are lost when using more complex deep neural networks.

neuroscience↗

bioRxiv2021

Quest for the Allmitey: Potential of Pronematus ubiquitus (Acari: Iolinidae) as a biocontrol agent against Tetranychus urticae and Tetranychus evansi (Acari: Tetranychidae) on tomato (Solanum lycopersicum L.)

The spider mites Tetranychus evansi Baker & Pritchard and Tetranychus urticae Koch (Acari: Tetranychidae) are key tomato pests worldwide. Biological control of spider mites using phytoseiid predatory mites remains challenging. The glandular trichomes on the tomato leaves and stem severely hamper the movement and establishment of the predatory mites. As a result, smaller predatory mites, able to thrive under the sticky heads of the glandular trichomes, have gained much interest. As some iolinid predatory mites were reported to feed on spider mites, we investigated the potential of Pronematus ubiquitus McGregor to control both T. urticae and T. evansi on tomato plants. On whole tomato plants, P. ubiquitus was able to suppress populations of T. urticae, but not of T. evansi. Based on the marginal number of spider mites killed in laboratory trials, the observed biocontrol effect on full tomato plants might not be due to direct predation but to a plant-mediated indirect impact. The oviposition of T. urticae was found to be significantly lower on tomato leaflets pre-exposed to P. ubiquitus as compared to non-exposed leaflets. The oviposition rate of T. evansi was not affected by previous exposure of the tomato host plant to P. ubiquitus. We demonstrated that P. ubiquitus reduces the population growth of T. urticae on tomato plants. Further large-scale field trials need to confirm the findings of the present study.

zoology↗