Abnormal negative feedback processing in individuals with autistic traits in the Iowa gambling task: Evidence from behavior and event-related potentials

Application of a FL Time Series Building Model in Mobile Network Interaction Anomaly Detection in the Internet of Things Environment

“…For the FL time series component model of the Internet of ings, it is necessary to classify all the data first and select the corresponding component model. But not for the model, a model for all the analysis of the situation, different simulation component model, is only able to reflect the data collection of now, cannot fully reflect all the law, and therefore, can only from the perspective of a different combination of the corresponding model, using comprehensive consideration, to maximize the analysis of existing data, in order to further improve the corresponding analysis results [14,15]. e corresponding mobile network time series as is set as x t , t � 1, 2, L 􏼈 􏼉, and the mobile interaction volume (x n is the real value) of the existing time period N is analyzed.…”

“…In addition, specific classification of abnormal behaviors is realized based on the discrimination of abnormal data by the wavelet model [10,12,13]. However, these methods have certain limitations, especially in feature extraction and direction recognition, which are difficult to be finely divided [14].…”

Decision making in Autism: a narrative review

“…Although not assessing explicit knowledge, South and colleagues reported that autistic adolescents improved in their rate of learning compared to comparison adolescents (despite initially equivalent rates of learning, and overall performance); a similar study found that autistic traits were not correlated with learning rate (but higher autistic traits were correlated with poorer performance in the volatile condition; Goris et al, 2021). Yet, Chen et al, (2021) found that high-trait individuals performed worse on the final two blocks compared to low-trait individuals (despite equivalent performance on the first four blocks). Of the five remaining studies in this category (11.6%), two studies reported more preservative errors in autistic versus comparisons adolescents (Chantiluke et al, 2015;Yeung et al, 2016), one study reported a lower tendency to select low frequency losses in autistic compared with comparison participants (Mussey et al, 2015).…”

High-Definition Transcranial Direct Current Stimulation Improves Decision-Making Ability: A Study Based on EEG

“…Previous studies suggested that the processing of feedback information involves several distinct processes, which are subserved by oscillations of different frequencies [ 41 ]. Theta oscillation was a prominent time-frequency component implicated during decision task which was widely used in nervous and psychiatric disorders, such as autism spectrum disorder, Parkinson’s disease, schizophrenia [ 35 , 67 , 68 ]. Numerous electrophysiologic literature suggested this reward-related theta activity may be generated by frontal cortex, while anterior cingulate cortex and orbitofrontal cortex were possible contributions of brain regions [ 46 , 69 , 70 ].…”