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Biological Information in Cortical Communication

Applicant Cook Matthew
Number 143947
Funding scheme Project funding
Research institution Institut für Neuroinformatik Universität Zürich Irchel und ETH Zürich
Institution of higher education University of Zurich - ZH
Main discipline Information Technology
Start/End 01.07.2013 - 30.06.2016
Approved amount 157'848.00
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Keywords (5)

relaxation methods; neural architectures; visual processing; cortex; natural computing

Lay Summary (French)

Lead
Les systèmes biologiques s'organisent à différents niveaux, qu'il s'agisse des interactions moléculaires, des comportements des organismes ou des symbioses interespèces. A chacun de ces niveaux, des principes opérationnels peuvent être identifiés et nous aident à formuler des modèles quantitatifs.
Lay summary

Contenu et objectifs du travail de recherche ====================================

Dans ce projet, nous nous intéressons à un niveau particulièrement peu connu, et pourtant responsable de nombre de comportements chez les mammifères. Il s'agit des principes sous-jacents au traitement de l'information entre les différentes aires corticales.
De nombreuse études anatomiques, electro-physiologiques ou d'IRM fonctionnels montrent que la spécificité des communications et des informations transmises entre différentes aires corticales est à l'origine de la spécificité des tâches accomplies. En se basant non seulement sur la structure relativement uniforme des couches cellulaires formant le neocortex, mais aussi des projections axonales entre différentes aires, il semble que des principes généraux de traitement de l'information sont mis en oeuvre. Cependant, et malgré leur intérêt, ces principes sont très mal connus. De plus, les données biologiques sur la forme exacte de l'information transmise par ces projections sont techniquement très difficiles à obtenir voire impossibles à mesurer directement.
Le but de ce projet est de développer des simulations in-silico des dynamiques et imbrications possibles entre les aires impliquées dans le traitement de l'information visuelle. Le traitement cortical du stimulus visuel est connu pour utiliser un modèle de représentation distribuée, dans lequel différentes aires encodent chacune différents aspects de l'interprétation visuelle.

Contexte scientifique et social du projet de recherche ===========================================
Dans ce projet nous souhaitons tester la pertinence et l'applicabilité de tels modèles dans des tâches du traitement visuel telles que la perception de profondeur, le traitement d'informations tri-dimensionnelles, et l'incorporation d'autres stimuli sensoriels. Ainsi, nous souhaitons développer un ensemble de principes de communications entre ces aires corticales. Ces principes doivent pouvoir nous servir non seulement dans les systèmes que nous élaborons mais aussi dans la prédiction quantitative de dynamiques ou structures du système visuel des mammifères.

Direct link to Lay Summary Last update: 05.08.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
A Demonstration of Tracking using Dynamic Neural Fields on a Programmable Vision Chip: Demo
Martel Julien N.P., Sandamirskaya Yulia, Dudek Piotr (2016), A Demonstration of Tracking using Dynamic Neural Fields on a Programmable Vision Chip: Demo, in ICDSC '16 Proceedings of the 10th International Conference on Distributed Smart Camera, Paris.
A Neuromorphic Approach for Tracking using Dynamic Neural Fields on a Programmable Vision-chip
Martel Julien N.P., Sandamirskaya Yulia (2016), A Neuromorphic Approach for Tracking using Dynamic Neural Fields on a Programmable Vision-chip, in ICDSC '16 Proceedings of the 10th International Conference on Distributed Smart Camera, Paris.
A Real-time High Dynamic Range Vision System with Tone Mapping for Automotive Applications
Martel Julien N.P., Lorenz Müller K., Carey Stephen J., Dudek Piotr (2016), A Real-time High Dynamic Range Vision System with Tone Mapping for Automotive Applications, in CNNA 2016; 15th International Workshop on Cellular Nanoscale Networks and their Applications; Proce, Dresden.
Parallel HDR Tone Mapping and Auto-focus on a Cellular Processor Array Vision Chip
Martel Julien N.P., Müller Lorenz K., Carey Stephen J., Dudek Piotr (2016), Parallel HDR Tone Mapping and Auto-focus on a Cellular Processor Array Vision Chip, in Circuits and Systems (ISCAS), 2016 IEEE International Symposium on, Montreal.
A Framework of Relational Networks to Build Systems with Sensors able to Perform the Joint Approximate Inference of Quantities
Martel Julien N.P., Cook Matthew (2015), A Framework of Relational Networks to Build Systems with Sensors able to Perform the Joint Approximate Inference of Quantities, in IEEE/RSJ International Conference on Intelligent Robots and Systems, Workshop on Unconventional Comp, Hamburg.
Pixel Interlacing to Trade-Off the Resolution of a Cellular Processor Array against more Registers
Martel Julien N.P., Chau Miguel, Cook Matthew, Dudek Piotr (2015), Pixel Interlacing to Trade-Off the Resolution of a Cellular Processor Array against more Registers, in Circuit Theory and Design (ECCTD), 2015 European Conference on, Trondheim.
Toward Joint Approximate Inference of Visual Quantities on Cellular Processors Arrays
Martel Julien N.P., Miguel Chau, Dudek Piotr, Cook Matthew (2015), Toward Joint Approximate Inference of Visual Quantities on Cellular Processors Arrays, in Circuits and Systems (ISCAS), 2015 IEEE International Symposium on, Lisbon.

Collaboration

Group / person Country
Types of collaboration
The University of Manchester, Microelectronics Lab Great Britain and Northern Ireland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Proc. of the Internat. Workshop on Cellular Nanoscale Networks and Applications, CNNA'16 Talk given at a conference A real-time high dynamic range vision system with tone mapping for automotive applications 23.08.2016 Dresden, Germany Martel Julien;
IEEE Internat. Symp. on Circuits and Systems, ISCAS'16 Talk given at a conference Parallel HDR Tone Mapping and Auto-focus on a Cellular Processor Array Vision Chip 22.05.2016 Montreal, Canada Martel Julien;
IEEE European Conf. on Circuits Theory and Design, ECCTD'15 Talk given at a conference Pixel Interlacing to Trade-off the Resolution of a Cellular Processor Array against more Registers 24.08.2015 Trondheim, Norway Martel Julien;
IEEE Internat. Symp. on Circuits and Systems, ISCAS'15 Talk given at a conference Toward Joint Approximate Inference of Visual Quantities on Cellular Processor Arrays 24.05.2015 Lisbon, Portugal Martel Julien;


Communication with the public

Communication Title Media Place Year
Talks/events/exhibitions Scientifica: Zurich Science Days German-speaking Switzerland 2015

Awards

Title Year
CSN Fellowship, for the Capocaccia Neuromorphic Engineering Workshop 2015 2015
EU-CSNII Fellowship, for the Telluride Neuromorphic Cognition Workshop 2014

Abstract

Biological systems have evolved at many scales, ranging from molecular pathways to organism behavior to inter-species symbiosis. At each level, operational principles can be identified which help us to form quantitatively meaningful models. In this proposal, we aim at a particularly poorly understood level of mammalian systems which is responsible for most mammalian behaviors: the form of information processing between cortical areas. Anatomy, electrophysiology, and fMRI all make it abundantly clear that specific cortical areas communicate specific types of information with each other to accomplish specific tasks. Given the relatively uniform layered pattern of cells forming the neocortex, including the inter-areal axonal projections, it seems certain that general information processing principles must be at work. However, surprisingly little is known about these principles. Biological data on the exact form of the information transmitted by these projections is technically very difficult if not impossible to measure directly. To get around this problem, we have started a collaboration combining the disciplines of algorithms, graph theory, neuroinformatics, complex systems, and emergent processes. Our approach is based on developing in silico simulations of the dynamic interplay among the component cells of large systems that we design using high-level cortical principles which are based on the best understood areas, namely those in the visual pathway. Cortical processing of visual input is known to use a distributed representation, with different areas encoding different aspects of the visual interpretation. While current engineering habits tempt us to think of this processing in terms of a pipelined sequence of filters and other feed-forward processing stages, cortical anatomy suggests a radically different architecture, using strong recurrent connectivity between visual areas. Based on these observations, we have designed a system to interpret input from a retina-like sensor using a network of recurrently interconnected areas, each of which encodes a different aspect of the visual interpretation, such as light intensity or optical flow. As each area of the network tries to be consistent with the information in neighboring areas, the visual interpretation converges towards global mutual consistency. Rather than applying input in a traditional feed-forward manner, the sensory input is only used to weakly influence the information flowing both ways through the middle of the network. This weak form of input is analogous to the thalamo-cortical fibers which provide the information from the optic nerve using just a tiny percentage of the synapses into highly recurrent primary visual cortex. Even with this seemingly weak use of input, our network of interacting visual areas is able to maintain its interpretation of the visual scene in real time, suggesting the viability of this model for studying and understanding the principles of inter-areal cortical information processing. Armed with this highly encouraging preliminary work, in this project we will apply this type of model to more realistic visual processing tasks, developing a set of principles of inter-areal communication which can be used not only in systems of our own design, but also to allow quantitative predictions regarding the mammalian visual system's structure and dynamics.
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