New zeroing neural dynamics models for diagonalization of symmetric matrix stream

2019 ◽  
Vol 85 (3) ◽  
pp. 849-866 ◽  
Author(s):  
Yunong Zhang ◽  
Huanchang Huang ◽  
Min Yang ◽  
Yihong Ling ◽  
Jian Li ◽  
...  
Keyword(s):  
Symmetric Matrix ◽  
Neural Dynamics ◽  
Dynamics Models

Migration and the Internet

2017 ◽  
Vol 14 (3) ◽  
pp. 331-342 ◽  
Author(s):  
Thomas John Cooke ◽  
Ian Shuttleworth
Keyword(s):  
United States ◽  
Information And Communication Technologies ◽  
Unobserved Heterogeneity ◽  
Panel Study ◽  
The United States ◽  
Negative Effect ◽  
Information And Communication ◽  
Using Data ◽  
And Migration ◽  
Dynamics Models

It is widely presumed that information and communication technologies, or ICTs, enable migration in several ways; primarily by reducing the costs of migration. However, a reconsideration of the relationship between ICTs and migration suggests that ICTs may just as well hinder migration; primarily by reducing the costs of not moving.  Using data from the US Panel Study of Income Dynamics, models that control for sources of observed and unobserved heterogeneity indicate a strong negative effect of ICT use on inter-state migration within the United States. These results help to explain the long-term decline in internal migration within the United States.

Behavioural and EEG atypicalities during rest, visual perception, and cognitive control in autistic adults

2020 ◽  
Author(s):  
Amandine Lassalle ◽  
Michael X Cohen ◽  
Laura Dekkers ◽  
Elizabeth Milne ◽  
Rasa Gulbinaite ◽  
...  
Keyword(s):  
Visual Perception ◽  
Cognitive Control ◽  
Visual Processing ◽  
Autism Spectrum ◽  
Neural Dynamics ◽  
Simple Explanation ◽  
Control Task ◽  
Neural Structure ◽  
Eeg Power ◽  
Autistic Adults

Background: People with an Autism Spectrum Condition diagnosis (ASD) are hypothesized to show atypical neural dynamics, reflecting differences in neural structure and function. However, previous results regarding neural dynamics in autistic individuals have not converged on a single pattern of differences. It is possible that the differences are cognitive-set-specific, and we therefore measured EEG in autistic individuals and matched controls during three different cognitive states: resting, visual perception, and cognitive control.Methods: Young adults with and without an ASD (N=17 in each group) matched on age (range 20 to 30 years), sex, and estimated Intelligence Quotient (IQ) were recruited. We measured their behavior and their EEG during rest, a task requiring low-level visual perception of gratings of varying spatial frequency, and the “Simon task” to elicit activity in the executive control network. We computed EEG power and Inter-Site Phase Clustering (ISPC; a measure of connectivity) in various frequency bands.Results: During rest, there were no ASD vs. controls differences in EEG power, suggesting typical oscillation power at baseline. During visual processing, without pre-baseline normalization, we found decreased broadband EEG power in ASD vs. controls, but this was not the case during the cognitive control task. Furthermore, the behavioral results of the cognitive control task suggest that autistic adults were better able to ignore irrelevant stimuli.Conclusions: Together, our results defy a simple explanation of overall differences between ASD and controls, and instead suggest a more nuanced pattern of altered neural dynamics that depend on which neural networks are engaged.

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