Consciousness & Cognition
Join the EBRAINS Community Space Consciousness and Cognition.
Collaborative multiscale approach
From the structural point of view, the brain comprises highly intricate networks between neurons, nuclei and areas. From the functional perspective, the brain can express a large variety of dynamical patterns, ranging from highly synchronous (sleep, deep anaesthesia, epilepsy) to asynchronous states (awake, attention). There are other conditions in which different functional states are expressed, as in the presence of drugs (e.g. anaesthesia), or in pathological conditions (e.g. disorders of consciousness, stroke, epilepsia). In this focus area, we aim at the multiscale understanding of different brain states and how they can support consciousness and cognition. It is also our objective to obtain a better, mechanism-based quantification of consciousness levels and contents, as well as new approaches to the treatment of alterations of consciousness following brain damage. To achieve these objectives, we have a collaborative approach between 40 research groups, comprising a large variety of experimental, clinical, analytical and computational methodologies that aim at advancing our understanding of how cognition and consciousness emerge from brain networks. We work hand in hand with philosophers and ethicists to develop a philosophical and ethical framework for the experimental and computational explorations of cognition and consciousness.
A main objective of this focus area is to collaboratively generate integrated data and computational models supporting brain state transitions, network complexity and cognitive functions.
Cognition: Object recognition
To enable perception and recognition of objects through multiple senses, the brain has to segregate (separately identify) and integrate information about their properties. We do not yet understand how these fundamental processes are mediated by neural mechanisms, especially in the neocortex. We investigate critical questions that remain open: how does the brain construct the kind of representations of objects we become aware of? How is it that, in perception, we have the experience of a specific view on an object, but also recognize its identity despite variations in position or viewing angle? And how are cortical circuits involved in object representations? Which cortical laminae and cell types are involved? How can local and long-range circuit mechanisms involving specific cell types with dendritic interactions shape multisensory integration? How can computational mechanisms be scaled up to comprise larger networks, dynamically performing perceptual and cognitive operations? What role do motor systems and the principle of active sensing play in multisensory segregation and integration? By means of experimental models, data analytics, computational models, multi-scale simulations and research in neurorobotics, we are implementing object recognition in an artificial, multisensory agent that uses this cognitive capability to navigate through environments.
A robot on EBRAINS has learned to combine vision and touch - EBRAINS. (n.d.). retrieved June 28, 2022, from https://ebrains.eu/news/robot-on-ebrains-combine-vision-touch/
Dora, S., Bohte, S. M., & Pennartz, C. M. A. (2021). Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy. ORIGINAL RESEARCH article Front. Comput. Neurosci., 28 July 2021
People and Groups
|Cyriel Pennartz - Department of Cognitive and Systems Neuroscience, University of Amsterdam, FNWI, Swammerdam Institute for Life Sciences - NL|
|Giovanni Pezzulo - National Research Council of Italy, Institute of Cognitive Sciences and Technologies (ISTC-CNR), in Rome - IT|
|Markus Diesmann - Forschungszentrum Jülich, Institut für Neurowissenschaften und Medizin (INM) - DE|
|Sacha van Albada - Forschungszentrum Jülich, Institut für Neurowissenschaften und Medizin (INM) - DE|
|Hans Ekkehard Plesser - Norges miljo-og biovitenskaplige universitet, Fakultet for realfag og teknologi, Institutt for datavitenskap - NO|
|Walter Senn - Universitaet Bern, Institut für Physiologie, Computational Neuroscience lab - CH|
|Pieter Roelfsema - Netherlands Institute for Neuroscience - NL|
|Jorge Mejias - Universiteit van Amsterdam, Faculty of Science, Swammerdam Institute for Life Sciences - NL|
|Emrah Duzel - Deutsches Zentrum fuer Neurodegenerative Erkrankungen EV, Clinical Neurophysiology and Memory - DE|
|Matthew Larkum - Humboldt-Universität zu Berlin - DE|
|Lars Muckli - Centre for Cognitive Neuroimaging, School of Psychology & Neuroscience, University of Glasgow - UK|
Quantification and modelling of different brain states
The cerebral cortex network can express a large variety of dynamical patterns, ranging from highly synchronous (sleep, deep anaesthesia, epilepsy) to asynchronous states (awake, attention). Each of these states are associated to different spatiotemporal patterns of activity, network complexity, information processing properties, behaviours and consciousness levels. How can the same network express all those different states and transitions across them? What are the underlying mechanisms? To identify, characterise and understand the network dynamics in such states, we explore the spontaeous activity emerging from the network across the different brain states, with a focus in the transitions across them, and we carry out a multi-scale comparison across levels, ranging from simple in vitro systems to clinical pathological states (disorders of consciousness, stroke) to capture the unique, common properties across them. Data-driven models will provide a unifying framework to single out an effective and reductionistic representation, capable of reproducing in the same system the dynamical regimes observed at different scales. Such an approach gives access to a larger exploration of variables than those experimentally testable, generating predictions and open questions that then can be experimentally tested.