We propose a new model-free method based on the feed-forward artificial neuronal network for detecting functional connectivity in coupled systems. The developed method which does not require large computational costs and which is able to work with short data trials can be used for analysis and reconstruction of connectivity in experimental multichannel data of different nature. We test this approach on the chaotic Rössler system and demonstrate good agreement with the previous well-known results. Then, we use our method to predict functional connectivity thalamo-cortical network of epileptic brain based on ECoG data set of WAG/Rij rats with genetic predisposition to absence epilepsy. We show the emergence of functional interdependence between cortical layers and thalamic nuclei after epileptic discharge onset.
Skip Nav Destination
Feed-forward artificial neural network provides data-driven inference of functional connectivity
Article navigation
September 2019
Research Article|
September 05 2019
Feed-forward artificial neural network provides data-driven inference of functional connectivity

Nikita Frolov
;
Nikita Frolov
1
Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University
, 420500 Innopolis, The Republic of Tatarstan, Russia
Search for other works by this author on:
Vladimir Maksimenko
;
Vladimir Maksimenko
1
Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University
, 420500 Innopolis, The Republic of Tatarstan, Russia
Search for other works by this author on:
Annika Lüttjohann
;
Annika Lüttjohann
2
Institute of Physiology I, University of Münster
, Münster 48149, Germany
Search for other works by this author on:
Alexey Koronovskii
;
Alexey Koronovskii
3
Faculty of Nonlinear Processes, Saratov State University
, 410012 Saratov, Russia
Search for other works by this author on:
Alexander Hramov
Alexander Hramov
a)
1
Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University
, 420500 Innopolis, The Republic of Tatarstan, Russia
Search for other works by this author on:
a)
Electronic mail: a.hramov@innopolis.ru
Chaos 29, 091101 (2019)
Article history
Received:
June 30 2019
Accepted:
August 10 2019
Connected Content
A companion article has been published:
New method can help identify brain disorders simply and effectively
See also
Citation
Nikita Frolov, Vladimir Maksimenko, Annika Lüttjohann, Alexey Koronovskii, Alexander Hramov; Feed-forward artificial neural network provides data-driven inference of functional connectivity. Chaos 1 September 2019; 29 (9): 091101. https://doi.org/10.1063/1.5117263
Download citation file:
Sign in
Don't already have an account? Register
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Sign in via your Institution
Sign in via your InstitutionPay-Per-View Access
$40.00