AIMC Topic: Reaction Time

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Deep Neural Network for Visual Stimulus-Based Reaction Time Estimation Using the Periodogram of Single-Trial EEG.

Sensors (Basel, Switzerland) Oct 27, 2020
Multiplexed deep neural networks (DNN) have engendered high-performance predictive models gaining popularity for decoding brain waves, extensively collected in the form of electroencephalogram (EEG) signals. In this paper, to the best of our knowledg...
Humans Neural Networks, Computer Algorithms Electroencephalography Reaction Time
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Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision.

PLoS computational biology Oct 2, 2020
Deep feedforward neural network models of vision dominate in both computational neuroscience and engineering. The primate visual system, by contrast, contains abundant recurrent connections. Recurrent signal flow enables recycling of limited computat...
Visual Perception Reaction Time Humans Young Adult Vision, Ocular Computational Biology Adult Neural Networks, Computer Models, Neurological Male Female
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Engaging proactive control: Influences of diverse language experiences using insights from machine learning.

Journal of experimental psychology. General Oct 1, 2020
We used insights from machine learning to address an important but contentious question: Is bilingual language experience associated with executive control abilities? Specifically, we assess proactive executive control for over 400 young adult biling...
Language Female Young Adult Adult Humans Reaction Time Machine Learning Neuropsychological Tests Multilingualism Male Executive Function Adolescent Cognition
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Human Cognition in Interaction With Robots: Taking the Robot's Perspective Into Account.

Human factors Jul 10, 2020
OBJECTIVE: The present study investigated whether and how different human-robot interactions in a physically shared workspace influenced human stimulus-response (SR) relationships.
Reaction Time Workplace Humans Cognition Robotics
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Working memory load-dependent changes in cortical network connectivity estimated by machine learning.

NeuroImage May 1, 2020
Working memory engages multiple distributed brain networks to support goal-directed behavior and higher order cognition. Dysfunction in working memory has been associated with cognitive impairment in neuropsychiatric disorders. It is important to cha...
Cerebral Cortex Neural Pathways Nerve Net Memory, Short-Term Reaction Time Psychomotor Performance Young Adult Adult Male Magnetic Resonance Imaging Brain Mapping Image Processing, Computer-Assisted Support Vector Machine Machine Learning Brain Female Humans
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Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control.

Communications biology Mar 9, 2020
Efficient action control is indispensable for goal-directed behaviour. Different theories have stressed the importance of either attention or response selection sub-processes for action control. Yet, it is unclear to what extent these processes can b...
Motor Activity Conflict, Psychological Female Young Adult Humans Brain Electroencephalography Signal Processing, Computer-Assisted Adolescent Brain Waves Reaction Time Cognition Neuropsychological Tests Attention Adult Support Vector Machine Goals Male Predictive Value of Tests Deep Learning
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Neuromodulated attention and goal-driven perception in uncertain domains.

Neural networks : the official journal of the International Neural Network Society Feb 1, 2020
In uncertain domains, the goals are often unknown and need to be predicted by the organism or system. In this paper, contrastive Excitation Backprop (c-EB) was used in two goal-driven perception tasks - one with pairs of noisy MNIST digits and the ot...
Goals Perception Uncertainty Models, Neurological Reaction Time Humans Attention Neural Networks, Computer
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A deep CNN approach to decode motor preparation of upper limbs from time-frequency maps of EEG signals at source level.

Neural networks : the official journal of the International Neural Network Society Jan 31, 2020
A system that can detect the intention to move and decode the planned movement could help all those subjects that can plan motion but are unable to implement it. In this paper, motor planning activity is investigated by using electroencephalographic ...
Motor Cortex Humans Adult Brain Waves Reaction Time Movement Brain-Computer Interfaces Upper Extremity Deep Learning Models, Neurological
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A simple three layer excitatory-inhibitory neuronal network for temporal decision-making.

Behavioural brain research Jan 20, 2020
Humans and animals do not only keep track of time intervals but they can also make decisions about durations. Temporal bisection is a psychophysical task that is widely used to assess the latter ability via categorization of durations as short or lon...
Neural Networks, Computer Learning Reaction Time Time Perception Neurons Hippocampus Choice Behavior Animals Rats Decision Making
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Finite-time and fixed-time anti-synchronization of Markovian neural networks with stochastic disturbances via switching control.

Neural networks : the official journal of the International Neural Network Society Nov 28, 2019
This paper proposes a unified theoretical framework to study the problem of finite/fixed-time drive-response anti-synchronization for a class of Markovian stochastic neural networks. State feedback switching controllers without the sign function are ...
Stochastic Processes Time Factors Reaction Time Neural Networks, Computer Markov Chains Algorithms Feedback
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