CANON. Investigating the canonical organization of neocortical circuits for sensory integration
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1 Investigating the canonical organization of neocortical circuits for sensory integration Collaborators: CA Bosman, U Olcese, L Gentet, Z Somogyvári, L Négyessy
2 The organizational principles of the brain DeFelipe, J (2011) Frontiers Neuroanat 5:29
3 Circuit organization across the cortical column 1 2 3A 3B 4A 4B 4C 5A 5B 6 Cortical Microcircuit Canonical Microcircuit Columnar microcircuits convey adaptive advantages to perform several neuronal computations Bosman, CA & Aboitiz, F (2015) Frontiers Neurosci 9:303 Douglas, R & Martin, KAC (2004) Annu Rev Neurosci 27: 419
4 This circuit organization increases the efficiency of cortical computations Neuronal subtypes are functionally organized across layers and specific neuronal subtypes exert specific computations Circuit microarchitecture promotes oscillatory compartmentalization The mechanisms underlying cortical microcircuits functionality are not yet fully understood Olcese et al. (2013) Neuron 79: 593 van Kekoerle et al. (2014) PNAS 111: 14332
5 CANON aims to reveal the functional micro-architecture governing cortico-cortical integration Questions to answer: 1. How are the different forms of cortical communication (e.g feedforward, feedback) performed at the level of distinct layers and neuronal subtypes? 2. How do the feedforward and feedback forms of cortical oscillatory activity relate to the function of individual neurons and to specific computations? 3. Do different mammals share the same micro-architecture for cortical integration? Can we observe traces of a similar architecture in intracranial recordings in humans?
6 Circuit architectures for multisensory integration 1. Multi-species approach Mice Ferrets Humans Data Model
7 2. Multi-level approach Two-photon targeted patch clamp recordings of pyramidal cells and parvalbumin-expressing interneurons, combined with Local Field Potentials (LFPs) Contribution of different neuronal subtypes A Primary Area + Association Area LFP pia pia intra L2/3 L4 PV transfer of information L5 L6 PYR PYR extra Perrenoud et al. (2016) PLOS Biol e
8 2. Multi-level approach A B Laminar recordings in awake mice and ferrets using the same experimental paradigm Fixation Visual+Auditory Stimuli Neuronal population features in cortical computations. Species comparison Time Expected Animal Response IR beam reward L2/3 L4 L5/6 A1 L2/3 L4 L5/6 V1 V 1 mm A1 V1
9 3. Model of Cortical Computations spike Current Source Density, (scsd) is a method able to reconstruct full spatio-temporal CSD dynamics of single neurons Cell type specific laminar distribution of synaptic currents A B C Somogyvári et al. (2012) Eur J Neurosci, 36: 3299
10 4. Comparative functional architectures in mice, ferrets and humans d ~ "c "'7",,, / 1 / I i I ' In,o n 3 1 l I II! Test the predictions derived from the model about computational architecture in electrophysiological data obtained from humans (collaboration with Matthew Self and Pieter Roelfsema from NIN, NL). A apical dendrite den soma basal dendrite Time axon collaterals axon g 1. Localization of the microwires and retinotopy. Self et al. (2016) PLOS Biol e
11 Work Plan WP2! Contribution!of!neuronal!cell!types!to! information!content WP1) WP4) WP5) WP6) Development!of!common! experimental!platform The!computational!architecture!of! sensory!integration Comparative!functional!architecture!in! mice,!ferrets!and!humans Coordination!and! Dissemination WP3) Population!features!of!neuronal! computations!in!mice!and!ferrets
12 Expected Synergies with HBP SP1-SP2: Comparison between species SP5 SP2 SP1 SP3: Unveiling Neuronal Circuits for Cognitive Architectures SP5: New Neuroinformatics tools SP3 CANON Other FLAG-ERA projects: FIIND SloW-Dyn CHAMP-Mouse
13 Thanks!!
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