High-Frequency EEG Variations in Children with Autism Spectrum Disorder during Human Faces Visualization

Paula, Celina A Reis; Reategui, Camille; Costa, Bruna Karen de Sousa; Fonseca, Caio Queiroz da; Silva, Luana da; Morya, Edgard; Brasil, Fabrício Lima

doi:10.1155/2017/3591914

Cited by 14 publications

(8 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The smaller value of scaling factor, a signified a smaller magnitude of time and it was inversely proportional to frequency which correlated with the work of Paula [45]. The result also indicated a unique observation in the data of ASD children in which the higher scaling factor, a at 256 has also resulted in a good match similar to TD children.…”

Section: ) Asd Childrensupporting

confidence: 71%

“…Thus, further investigation was conducted to scrutinize the procedure and analysis. As reported by Paula [45], the power spectrum of EEG signals collected from the ASD children when subjected to visual stimulus of happy, neutral, and angry faces revealed that there was an increase in power in the higher frequencies region of the signals recorded from frontal, occipital, and center-parietal areas when compared to control group. Thus, there was a need to look into the empirical evidence in the approach as there was high probability that ASD children might emit different pattern of signals alike TD children.…”

Section: ) Asd Childrensupporting

confidence: 58%

See 1 more Smart Citation

Implementation of Wavelet Analysis on Thermal Images for Affective States Recognition of Children With Autism Spectrum Disorder

et al. 2020

View full text Add to dashboard Cite

Children with Autism Spectrum Disorder are identified as a group of people who has difficulties in socio-emotional interaction. Most of them lack the proper context in producing social response through facial expression and speech. Since emotion is the key for effective social interaction, it is justifiably vital for them to comprehend the correct emotion expressions and recognitions. Emotion is a type of affective states and can be detected through physical reaction and physiological signals. In general, recognition of affective states from physical reaction such as facial expression and speech for autistic children is often unpredictable. Hence, an alternative method of identifying the affective states through physiological signals is proposed. Though considered non-invasive, most of the current recognition methods require sensors to be patched on to the skin body to measure the signals. This would most likely cause discomfort to the children and mask their "true" affective states. The study proposed the use of thermal imaging modality as a passive medium to analyze the physiological signals associated with the affective states nonobtrusively. The study hypothesized that, the impact of cutaneous temperature changes due to the pulsating blood flow in the blood vessels at the frontal face area measured from the modality could have a direct impact to the different affective states of autistic children. A structured experimental setup was designed to measure thermal imaging data generated from different affective state expressions induced using different sets of audio-video stimuli. A wavelet-based technique for pattern detection in time series was deployed to spot the changes measured from the region of interest. In the study, the affective state model for typical developing children aged between 5 and 9 years old was used as the baseline to evaluate the performance of the affective state classifier for autistic children. The results from the classifier showed the efficacy of the technique and accorded good performance of classification accuracy at 88% in identifying the affective states of autistic children. The results were momentous in distinguishing basic affective states and the information could provide a more effective response towards improving social-emotion interaction amongst the autistic children. INDEX TERMS Autism, Affective States, Facial Skin Temperatures, Thermoregulation, Thermal Images, Wavelet I. INTRODUCTION F OR decades, numbers of research have been conducted in the field of affective state recognition, using numerous modalities and exploiting various features from the signal generated by the Autonomous Nervous System (ANS). ANS together with hypothalamus, regulates the blood pressure, breathing, pulse and arousal in response to different emotional features. Seeing the big potentials of affective state

show abstract

Section: ) Asd Childrensupporting

confidence: 71%

Section: ) Asd Childrensupporting

confidence: 58%

Implementation of Wavelet Analysis on Thermal Images for Affective States Recognition of Children With Autism Spectrum Disorder

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Fast Fourier Transforms (FFTs) for the values of 1.5, 2, 2.5, and 3 show a significant change in their appearance (figure 5(A)), which confirms a disorder in network function 69,71,72 .…”

Section: Resultsmentioning

confidence: 75%

Phase synchronization and criticality in a network of neural mass models

Kazemi

Jamali

2021

Preprint

View full text Add to dashboard Cite

Synchronization has an important role in neural networks, and their dynamics are mostly accompanied by cognitive activities such as memory, learning, and perception. These activities arise from the collective neural behaviors and are not totally understood yet. This paper aims to investigate a cortical model from this perspective. In this paper, we investigated a network of neural populations in a way the dynamics of each node corresponded to the Jansen-Rit neural mass model. First, we put this dynamic on a single mass of four different input levels. Then, we considered a Watts-Strogatz network of Jansen-Rit oscillators. We observed an epileptic activity in the weak input level. The network to change various parameters is considered. The detailed results including the mean times series, phase spaces and power spectrum revealed a wide range of different behaviors such as epilepsy, unimpaired, and a transition between synchrony and asynchrony states. Since the critical state is a dynamic candidate for healthy brains, we considered some measures of criticality and investigated them on phase transition points. We showed that the criticality hypothesis is not all or nothing theory. It means that due to the nature of specific indicators selected for studying the criticality, the phase transition point can be a critical point or not. Indeed, some markers of criticality can exist in phase transition points, and others may not. As a result, we do not claim that neural models show criticality or not, but we can only admit that they have a percentage of criticality.

show abstract

“…Additionally, Elhabashy et al and Azouz et al 41,42 reported that children with ASD have quantitative EEG abnormalities that underlie their symptomatology and suggesting neural connectivity abnormalities may be a major deficit leading to the symptoms of ASD. Paula et al 43 reported that ASD presented a stronger power spectrum in higher frequencies than the control group for some brain areas and differences were more evident in the occipital and interparietal regions.…”

Section: Discussionmentioning

confidence: 99%

<p>Assessments of Amino Acids, Ammonia and Oxidative Stress Among Cohort of Egyptian Autistic Children: Correlations with Electroencephalogram and Disease Severity</p>

Saleem¹,

Shehata²,

Toghan³

et al. 2020

NDT

View full text Add to dashboard Cite

Objective: The current study aimed to assess the profiles of plasma amino acids, serum ammonia and oxidative stress status among autistic children in terms of electroencephalogram findings and clinical severity among the cohort of autistic Egyptian children. Patients and methods: The present study included 118 Egyptian children categorized into 54 children with autism who were comparable with 64 healthy controls. Clinical assessments of cases were performed using CARS in addition to EEG records. Plasma amino acids were measured using high-performance liquid chromatography (HPLC), while, serum ammonia and oxidative stress markers were measured using colorimetric methods for all included children. Results: The overall results revealed that 37.04% of cases had abnormal EEG findings. Amino acid profile in autistic children showed statistically significant lower levels of aspartic acid, glycine, β-alanine, tryptophan, lysine and proline amino acids with significantly higher asparagine amino acid derivative levels among autistic patients versus the control group (p˂0.05). There were significantly higher serum ammonia levels with significantly higher total oxidant status (TOS) and oxidative stress index (OSI) values among the included autistic children vs controls (p˂0.05). There were significantly negative correlations between CARS with aspartic acid (r=−0.269, P=0.049), arginine (r=-0.286, p= 0.036), and TAS (r= −0.341, p= 0.012), and significantly positive correlations between CARS with TOS (r=0.360, p= 0.007) and OSI (r= 0.338, p= 0.013). Conclusion: Dysregulated amino acid metabolism, high ammonia and oxidative stress were prevalent among autistic children and should be considered in autism management. Still EEG records were inconclusive among autistic children, although may be helpful in assessment autism severity.

show abstract

High-Frequency EEG Variations in Children with Autism Spectrum Disorder during Human Faces Visualization

Cited by 14 publications

References 30 publications

Implementation of Wavelet Analysis on Thermal Images for Affective States Recognition of Children With Autism Spectrum Disorder

Implementation of Wavelet Analysis on Thermal Images for Affective States Recognition of Children With Autism Spectrum Disorder

Phase synchronization and criticality in a network of neural mass models

<p>Assessments of Amino Acids, Ammonia and Oxidative Stress Among Cohort of Egyptian Autistic Children: Correlations with Electroencephalogram and Disease Severity</p>

Contact Info

Product

Resources

About