Modulation of cortical intrinsic bistability and complexity in the cortical network

Maria V. Sanchez-Vives, Julia F. Weinert, Beatriz Rebollo, Adenauer G. Casali, Andrea Pigorini, Marcello Massimini, Mattia D’Andola

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Slow waves emerge from the cortical network during states of functional disconnection (non-REM sleep, anesthesia) and anatomical disconnection (slices, deafferented cortex) as if it were its default activity [1]. Such emergent activity and its spatiotemporal patterns reveal features about the underlying network. By using an observational approach of these emergent slow waves we have identified alterations in the cortical emergent patterns in transgenic models of neurological disease [2]. Here, we present a perturbational approach where we probe the network by electrical stimulation using two different approaches: (1) By means of DC electric fields we explore the modulation of the emergent activity, (2) By means of electric pulses we measure the complexity of the cortical network’s responses. To this end we have adapted to cortical slices the perturbational complexity index (PCI) recently introduced in humans to quantify the information content of deterministic patterns evoked in the brain by transcranial magnetic stimulation [3]. Our in vitro perturbational study reveals that the spontaneous intrinsic cortical bistability breaks-off complexity in the neural network. We also explore the mechanisms modulating network complexity under different brain states.

Original languageEnglish
Title of host publicationArtificial Neural Networks and Machine Learning - 25th International Conference on Artificial Neural Networks, ICANN 2016, Proceedings
PublisherSpringer Verlag
Number of pages1
Volume9886 LNCS
ISBN (Print)9783319447773
Publication statusPublished - 2016
Event25th International Conference on Artificial Neural Networks, ICANN 2016 - Barcelona, Spain
Duration: Sep 6 2016Sep 9 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9886 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349


Other25th International Conference on Artificial Neural Networks, ICANN 2016


  • Cerebral cortex
  • Complexity
  • Cortical network
  • Electric fields
  • Oscillations
  • Slow waves
  • Synchronization
  • Up states

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


Dive into the research topics of 'Modulation of cortical intrinsic bistability and complexity in the cortical network'. Together they form a unique fingerprint.

Cite this