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Heliyon Jun 2024Autism spectrum disorder (ASD) is a behaviorally defined complex neurodevelopmental syndrome characterized by persistent social communication and interaction deficit.... (Review)
Review
Autism spectrum disorder (ASD) is a behaviorally defined complex neurodevelopmental syndrome characterized by persistent social communication and interaction deficit. Transcranial magnetic stimulation (TMS) is a promising and emerging tool for the intervention of ASD by reducing both core and associate symptoms. Several reviews have been published regarding TMS-based ASD treatment, however, a systematic review on study characteristics, specific stimulating parameters, localization techniques, stimulated targets, behavioral outcomes, and neuroimage biomarker changes is lagged behind since 2018. Here, we performed a systematic search on literatures published after 2018 in PubMed, Web of Science, and Science Direct. After screening, the final systematic review included 17 articles, composing seven randomized controlled trial studies and ten open-label studies. Two studies are double-blind, while the other studies have a moderate to high risk of bias attributing to inadequate subject- and evaluator-blinding to treatment allocation. Five studies utilize theta-burst stimulation mode, and the others apply repetitive TMS with low frequency (five studies), high frequency (six studies), and combined low and high frequency stimulation (one study). Most researchers prioritize the bilateral dorsolateral prefrontal lobe as stimulation target, while parietal lobule, inferior parietal lobule, and posterior superior temporal sulci have also emerged as new targets of attention. One third of the studies use neuronavigation based on anatomical magnetic resonance imaging to locate the stimulation target. After TMS intervention, discernible enhancements across a spectrum of scales are evident in stereotyped behavior, repetitive behavior, and verbal social domains. A comprehensive review of literature spanning the last five years demonstrates the potential of TMS treatment for ASD in ameliorating the clinical core symptoms.
PubMed: 38933955
DOI: 10.1016/j.heliyon.2024.e32251 -
Sensors (Basel, Switzerland) Jun 2024Existing end-to-end speech recognition methods typically employ hybrid decoders based on CTC and Transformer. However, the issue of error accumulation in these hybrid...
Existing end-to-end speech recognition methods typically employ hybrid decoders based on CTC and Transformer. However, the issue of error accumulation in these hybrid decoders hinders further improvements in accuracy. Additionally, most existing models are built upon Transformer architecture, which tends to be complex and unfriendly to small datasets. Hence, we propose a Nonlinear Regularization Decoding Method for Speech Recognition. Firstly, we introduce the nonlinear Transformer decoder, breaking away from traditional left-to-right or right-to-left decoding orders and enabling associations between any characters, mitigating the limitations of Transformer architectures on small datasets. Secondly, we propose a novel regularization attention module to optimize the attention score matrix, reducing the impact of early errors on later outputs. Finally, we introduce the tiny model to address the challenge of overly large model parameters. The experimental results indicate that our model demonstrates good performance. Compared to the baseline, our model achieves recognition improvements of 0.12%, 0.54%, 0.51%, and 1.2% on the Aishell1, Primewords, Free ST Chinese Corpus, and Common Voice 16.1 datasets of Uyghur, respectively.
Topics: Humans; Speech Recognition Software; Algorithms; Speech; Nonlinear Dynamics; Pattern Recognition, Automated
PubMed: 38931629
DOI: 10.3390/s24123846 -
Scientific Reports Jun 2024Accommodating talker variability is a complex and multi-layered cognitive process. It involves shifting attention to the vocal characteristics of the talker as well as...
Accommodating talker variability is a complex and multi-layered cognitive process. It involves shifting attention to the vocal characteristics of the talker as well as the linguistic content of their speech. Due to an interdependence between voice and phonological processing, multi-talker environments typically incur additional processing costs compared to single-talker environments. A failure or inability to efficiently distribute attention over multiple acoustic cues in the speech signal may have detrimental language learning consequences. Yet, no studies have examined effects of multi-talker processing in populations with atypical perceptual, social and language processing for communication, including autistic people. Employing a classic word-monitoring task, we investigated effects of talker variability in Australian English autistic (n = 24) and non-autistic (n = 28) adults. Listeners responded to target words (e.g., apple, duck, corn) in randomised sequences of words. Half of the sequences were spoken by a single talker and the other half by multiple talkers. Results revealed that autistic participants' sensitivity scores to accurately-spotted target words did not differ to those of non-autistic participants, regardless of whether they were spoken by a single or multiple talkers. As expected, the non-autistic group showed the well-established processing cost associated with talker variability (e.g., slower response times). Remarkably, autistic listeners' response times did not differ across single- or multi-talker conditions, indicating they did not show perceptual processing costs when accommodating talker variability. The present findings have implications for theories of autistic perception and speech and language processing.
Topics: Humans; Male; Female; Adult; Speech Perception; Autistic Disorder; Young Adult; Reaction Time; Speech; Attention; Middle Aged; Language
PubMed: 38926416
DOI: 10.1038/s41598-024-62429-w -
Science Advances Jun 2024Lip language recognition urgently needs wearable and easy-to-use interfaces for interference-free and high-fidelity lip-reading acquisition and to develop accompanying...
Lip language recognition urgently needs wearable and easy-to-use interfaces for interference-free and high-fidelity lip-reading acquisition and to develop accompanying data-efficient decoder-modeling methods. Existing solutions suffer from unreliable lip reading, are data hungry, and exhibit poor generalization. Here, we propose a wearable lip language decoding technology that enables interference-free and high-fidelity acquisition of lip movements and data-efficient recognition of fluent lip language based on wearable motion capture and continuous lip speech movement reconstruction. The method allows us to artificially generate any wanted continuous speech datasets from a very limited corpus of word samples from users. By using these artificial datasets to train the decoder, we achieve an average accuracy of 92.0% across individuals ( = 7) for actual continuous and fluent lip speech recognition for 93 English sentences, even observing no training burn on users because all training datasets are artificially generated. Our method greatly minimizes users' training/learning load and presents a data-efficient and easy-to-use paradigm for lip language recognition.
Topics: Humans; Wearable Electronic Devices; Speech; Language; Lip; Movement; Male; Female; Adult; Lipreading; Motion Capture
PubMed: 38924408
DOI: 10.1126/sciadv.ado9576 -
Frontiers in Sociology 2024With growing commercial, regulatory and scholarly interest in use of Artificial Intelligence (AI) to profile and interact with human emotion ("emotional AI"), attention...
With growing commercial, regulatory and scholarly interest in use of Artificial Intelligence (AI) to profile and interact with human emotion ("emotional AI"), attention is turning to its capacity for people, relating to factors impacting on a person's decisions and behavior. Given prior social disquiet about AI and profiling technologies, surprisingly little is known on people's views on the benefits and harms of emotional AI technologies, especially their capacity for manipulation. This matters because regulators of AI (such as in the European Union and the UK) wish to stimulate AI innovation, minimize harms and build public trust in these systems, but to do so they should understand the public's expectations. Addressing this, we ascertain UK adults' perspectives on the potential of emotional AI technologies for manipulating people through a two-stage study. Stage One (the qualitative phase) uses design fiction principles to generate adequate understanding and informed discussion in 10 focus groups with diverse participants ( = 46) on how emotional AI technologies may be used in a range of mundane, everyday settings. The focus groups primarily flagged concerns about manipulation in two settings: emotion profiling in social media (involving deepfakes, false information and conspiracy theories), and emotion profiling in child oriented "emotoys" (where the toy responds to the child's facial and verbal expressions). In both these settings, participants express concerns that emotion profiling covertly exploits users' cognitive or affective weaknesses and vulnerabilities; additionally, in the social media setting, participants express concerns that emotion profiling damages people's capacity for rational thought and action. To explore these insights at a larger scale, Stage Two (the quantitative phase), conducts a UK-wide, demographically representative national survey ( = 2,068) on attitudes toward emotional AI. Taking care to avoid leading and dystopian framings of emotional AI, we find that large majorities express concern about the potential for being manipulated through social media and emotoys. In addition to signaling need for civic protections and practical means of ensuring trust in emerging technologies, the research also leads us to provide a policy-friendly subdivision of what is meant by manipulation through emotional AI and related technologies.
PubMed: 38912311
DOI: 10.3389/fsoc.2024.1339834 -
Noise & HealthDigital noise reduction (DNR) minimizes the effect of noise on speech signals by continuously monitoring frequency bands in the presence of noise. In the present study,...
AIMS
Digital noise reduction (DNR) minimizes the effect of noise on speech signals by continuously monitoring frequency bands in the presence of noise. In the present study, we explored the effect of DNR technology on speech intelligibility in individuals using hearing aids (HAs) and investigated implications for daily use.
METHODS AND MATERIAL
Eighteen participants with bilateral moderate sensorineural hearing loss (aged 16-45 years) were included. Bilateral receiver-in-the-ear HAs were fitted in the participants. The adaptive and nonadaptive (with a signal-to-noise ratio (SNR) of +5 and -5 dB, respectively) Turkish matrix sentence test (TURMatrix) in noise and free-field hearing assessments, including hearing thresholds with hearing aids, speech recognition thresholds (SRT), and speech discrimination scores, were conducted in two different conditions: HA in the DNR-on and DNR-off conditions.
RESULTS
No significant difference was observed between free-field hearing assessments with the HA in the DNR-off and DNR-on conditions (P > 0.05). Furthermore, the adaptive and nonadaptive TURMatrix revealed significant differences between the scores under the DNR-on and DNR-off conditions (P < 0.05). Nevertheless, under the DNR-on condition, there was no correlation between free-field hearing assessments with HA and TURMatrix results (P > 0.05). However, a significant correlation was observed between SRT scores with HA and TURMatrix scores (adaptive and nonadaptive, +5 and -5 dB SNR, respectively) under the DNR-off condition (P < 0.05).
CONCLUSION
Our study findings suggest that DNR can improve speech intelligibility in noisy environments. Therefore, DNR can enhance an individual's auditory comfort by improving their capacity to grasp speech in background noise.
Topics: Humans; Hearing Aids; Adult; Noise; Male; Middle Aged; Hearing Loss, Sensorineural; Female; Young Adult; Adolescent; Speech Intelligibility; Signal-To-Noise Ratio; Auditory Threshold; Speech Perception; Speech Reception Threshold Test
PubMed: 38904826
DOI: 10.4103/nah.nah_67_23 -
Communications Biology Jun 2024Human language relies on the correct processing of syntactic information, as it is essential for successful communication between speakers. As an abstract level of...
Human language relies on the correct processing of syntactic information, as it is essential for successful communication between speakers. As an abstract level of language, syntax has often been studied separately from the physical form of the speech signal, thus often masking the interactions that can promote better syntactic processing in the human brain. However, behavioral and neural evidence from adults suggests the idea that prosody and syntax interact, and studies in infants support the notion that prosody assists language learning. Here we analyze a MEG dataset to investigate how acoustic cues, specifically prosody, interact with syntactic representations in the brains of native English speakers. More specifically, to examine whether prosody enhances the cortical encoding of syntactic representations, we decode syntactic phrase boundaries directly from brain activity, and evaluate possible modulations of this decoding by the prosodic boundaries. Our findings demonstrate that the presence of prosodic boundaries improves the neural representation of phrase boundaries, indicating the facilitative role of prosodic cues in processing abstract linguistic features. This work has implications for interactive models of how the brain processes different linguistic features. Future research is needed to establish the neural underpinnings of prosody-syntax interactions in languages with different typological characteristics.
Topics: Humans; Speech Perception; Male; Female; Adult; Language; Brain; Speech; Young Adult; Magnetoencephalography; Linguistics; Cues
PubMed: 38902370
DOI: 10.1038/s42003-024-06444-7 -
Behavioral and Brain Functions : BBF Jun 2024Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with higher incidence in males and is characterized by atypical verbal/nonverbal communication,...
BACKGROUND
Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with higher incidence in males and is characterized by atypical verbal/nonverbal communication, restricted interests that can be accompanied by repetitive behavior, and disturbances in social behavior. This study investigated brain mechanisms that contribute to sociability deficits and sex differences in an ASD animal model.
METHODS
Sociability was measured in C58/J and C57BL/6J mice using the 3-chamber social choice test. Bulk RNA-Seq and snRNA-Seq identified transcriptional changes in C58/J and C57BL/6J amygdala within which DMRseq was used to measure differentially methylated regions in amygdala.
RESULTS
C58/J mice displayed divergent social strata in the 3-chamber test. Transcriptional and pathway signatures revealed immune-related biological processes differ between C58/J and C57BL/6J amygdala. Hypermethylated and hypomethylated genes were identified in C58/J versus C57BL/6J amygdala. snRNA-Seq data in C58/J amygdala identified differential transcriptional signatures within oligodendrocytes and microglia characterized by increased ASD risk gene expression and predicted impaired myelination that was dependent on sex and sociability. RNA velocity, gene regulatory network, and cell communication analysis showed diminished oligodendrocyte/microglia differentiation. Findings were verified using Bulk RNA-Seq and demonstrated oxytocin's beneficial effects on myelin gene expression.
LIMITATIONS
Our findings are significant. However, limitations can be noted. The cellular mechanisms linking reduced oligodendrocyte differentiation and reduced myelination to an ASD phenotype in C58/J mice need further investigation. Additional snRNA-Seq and spatial studies would determine if effects in oligodendrocytes/microglia are unique to amygdala or if this occurs in other brain regions. Oxytocin's effects need further examination to understand its' potential as an ASD therapeutic.
CONCLUSIONS
Our work demonstrates the C58/J mouse model's utility in evaluating the influence of sex and sociability on the transcriptome in concomitant brain regions involved in ASD. Our single-nucleus transcriptome analysis elucidates potential pathological roles of oligodendrocytes and microglia in ASD. This investigation provides details regarding regulatory features disrupted in these cell types, including transcriptional gene dysregulation, aberrant cell differentiation, altered gene regulatory networks, and changes to key pathways that promote microglia/oligodendrocyte differentiation. Our studies provide insight into interactions between genetic risk and epigenetic processes associated with divergent affiliative behavior and lack of positive sociability.
Topics: Animals; Male; Microglia; Mice; Amygdala; Female; Oligodendroglia; Autism Spectrum Disorder; Mice, Inbred C57BL; Social Behavior; Gene Expression Profiling; Phenotype; Sex Characteristics; Transcriptome; Disease Models, Animal; Oxytocin
PubMed: 38898502
DOI: 10.1186/s12993-024-00240-3 -
Nutrients May 2024The main purpose of this study was to determine the effects of a high-intensity interval training (HIIT) intervention in the context of moderate alcohol consumption on... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
The main purpose of this study was to determine the effects of a high-intensity interval training (HIIT) intervention in the context of moderate alcohol consumption on cognitive performance in healthy young adults.
METHODS
We conducted a 10-week HIIT program along with four types of beverages with/without alcohol content. A total of 75 healthy adults (18-40 years old; 46% female) were allocated to either a control Non-Training group or an HIIT program group (2 days/week). Using block randomization, participants in the HIIT group were further allocated to an HIIT-Alcohol group (alcohol beer or sparkling water with vodka added, 5.4%) or an HIIT-NonAlcohol group (sparkling water or non-alcohol beer, 0.0%). The control group was instructed to maintain an active lifestyle but did not undergo any regular training. A comprehensive neuropsychological battery was used to evaluate cognitive performance (i.e., memory, working memory, processing speed, inhibitory control, and verbal fluency). Changes from baseline to week 10 were included in the main analyses.
RESULTS
All groups improved in all neuropsychological measures (all ≤ 0.001), independent of sex and alcohol consumption, with no statistical differences between groups (all > 0.05). Furthermore, larger increases in maximal oxygen uptake were associated with greater improvements in processing speed, inhibitory control, and verbal fluency (all < 0.050).
CONCLUSIONS
Although the improvements found in cognitive performance cannot be attributed to the HIIT intervention, no significant impairments in cognitive functions were noted due to moderate alcohol intake. Furthermore, our results confirmed that exercise-induced physical fitness improvements were associated with cognitive performance enhancements in young healthy adults.
Topics: Humans; Female; Male; High-Intensity Interval Training; Cognition; Young Adult; Adult; Alcohol Drinking; Adolescent; Neuropsychological Tests; Oxygen Consumption; Alcoholic Beverages
PubMed: 38892613
DOI: 10.3390/nu16111680 -
PloS One 2024Language is rooted in our ability to compose: We link words together, fusing their meanings. Links are not limited to neighboring words but often span intervening words....
Language is rooted in our ability to compose: We link words together, fusing their meanings. Links are not limited to neighboring words but often span intervening words. The ability to process these non-adjacent dependencies (NADs) conflicts with the brain's sampling of speech: We consume speech in chunks that are limited in time, containing only a limited number of words. It is unknown how we link words together that belong to separate chunks. Here, we report that we cannot-at least not so well. In our electroencephalography (EEG) study, 37 human listeners learned chunks and dependencies from an artificial grammar (AG) composed of syllables. Multi-syllable chunks to be learned were equal-sized, allowing us to employ a frequency-tagging approach. On top of chunks, syllable streams contained NADs that were either confined to a single chunk or crossed a chunk boundary. Frequency analyses of the EEG revealed a spectral peak at the chunk rate, showing that participants learned the chunks. NADs that cross boundaries were associated with smaller electrophysiological responses than within-chunk NADs. This shows that NADs are processed readily when they are confined to the same chunk, but not as well when crossing a chunk boundary. Our findings help to reconcile the classical notion that language is processed incrementally with recent evidence for discrete perceptual sampling of speech. This has implications for language acquisition and processing as well as for the general view of syntax in human language.
Topics: Humans; Electroencephalography; Female; Male; Adult; Language; Young Adult; Speech Perception; Speech; Learning; Brain
PubMed: 38889141
DOI: 10.1371/journal.pone.0305333