TY - GEN
T1 - Regaining Cognitive Control
T2 - 21st International Conference on Computational Science, ICCS 2021
AU - Ullah, Nimat
AU - Treur, Jan
PY - 2021
Y1 - 2021
N2 - Apart from various other neural and hormonal changes caused by stress, frequent and long-term activation of the hypothalamus–pituitary–adrenal (HPA) axis in response to stress leads in an adaptive manner to the inadequacy of the stress response system. This leads to a cognitive dysfunction where the subject is no more able to downregulate his or her stress due to the atrophy in the hippocampus and hypertrophy in the amygdala. These atrophies can be dealt with by antidepressant treatment or psychological treatments like cognitive and behavioural therapies. In this paper, an adaptive neuroscience-based computational network model is introduced which demonstrates such a cognitive dysfunction due to a long-term stressor and regaining of the cognitive abilities through a cognitive behavioural therapy: Mindfulness-Based Cognitive Therapy (MBCT). Simulation results are reported for the model which demonstrates the adaptivity as well as the dynamic interaction of the involved brain areas in the phenomenon.
AB - Apart from various other neural and hormonal changes caused by stress, frequent and long-term activation of the hypothalamus–pituitary–adrenal (HPA) axis in response to stress leads in an adaptive manner to the inadequacy of the stress response system. This leads to a cognitive dysfunction where the subject is no more able to downregulate his or her stress due to the atrophy in the hippocampus and hypertrophy in the amygdala. These atrophies can be dealt with by antidepressant treatment or psychological treatments like cognitive and behavioural therapies. In this paper, an adaptive neuroscience-based computational network model is introduced which demonstrates such a cognitive dysfunction due to a long-term stressor and regaining of the cognitive abilities through a cognitive behavioural therapy: Mindfulness-Based Cognitive Therapy (MBCT). Simulation results are reported for the model which demonstrates the adaptivity as well as the dynamic interaction of the involved brain areas in the phenomenon.
UR - https://www.scopus.com/pages/publications/85111349278
UR - https://www.scopus.com/inward/citedby.url?scp=85111349278&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-77967-2_46
DO - 10.1007/978-3-030-77967-2_46
M3 - Conference contribution
SN - 9783030779665
VL - 3
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 556
EP - 569
BT - Computational Science – ICCS 2021
A2 - Paszynski, Maciej
A2 - Kranzlmüller, Dieter
A2 - Krzhizhanovskaya, Valeria V.
A2 - Dongarra, Jack J.
A2 - Sloot, Peter M.A.
PB - Springer Nature Switzerland AG
Y2 - 16 June 2021 through 18 June 2021
ER -