INS Seminar: 10 Jan. 2019 – 14:00 – “Deciphering basal ganglia function using computational models”

From Thursday 10th January 2019 at 14:00
To Thursday 10th January 2019 at 15:00

Location : INS Seminar Room, Campus Timone, Red Wing, 5th Floor

Speaker Jyotika Bahuguna (Forschungszentrum Julich, Germany)
 
Abstract :  Basal ganglia function can be addressed with computational modeling at different levels of abstractions. Here I demonstrate two such examples and an attempt to combine these models. Firsty, we address the question of what is the striatal representation of an motor action.  In order to investigate this issue, we designed a distance dependent spiking neuronal network model of the striatum consisting of D1 and D2 medium spiny neurons (MSNs) and interfaced it to a simulated robot moving in an environment. We demonstrate that this model is able to reproduce key behavioral features (freezing, ambulation and rotation) of 6 out of 7 optogenetic experiments that involved the manipulation of the striatum. The main result of this model was that D1 and D2-MSNs of an action co-operate whereas D1 and D2-MSNs of competing actions inhibit each other during action selection. Basal ganglia being a set of interacting nuclei and forming many functional pathways form a good substrate for degeneracy. This degeneracy might also explain the variability seen in the data in healthy as well as pathological conditions such as Parkinson's disease. In order to investigate this issue, we model the basal ganglia as a firing rate model and perform a parameter search for effective connectivities between its nuclei for healthy and dopamine depleted conditions. The cost function used for constraining this system was derived from empirical firing rates and phase relationships as observed in healthy and dopamine depleted rats. We were able to generate more than 1000 physiological and pathological firing rate models that met the constraints and showed ample variability in the values of effective connectivities. We then projected these models onto a lower dimensional space of dynamical features such as : a) GPi suppression b) Susceptibiity to oscillations. Despite the large variability in effective connectivities, the models clustered together in this space and showed a clear separation between physiological and pathological conditions. This suggests that rather than absolute values of the effective connectivities, it might be their relative values that determine the dynamical state and projecting them on a lower dimensional space of sensible dynamical features might give a better chance at understanding complex pathologies such as Parkinson's disease than a pure structural analysis. And lastly, we use these firing rate models to deconstruct basal ganglia transfer function in response to striatal optogenetic stimulation in order to explain one of the optogenetic experiments that we failed to explain in the first study.
 
For any question, feel free to contact:
Hiba Sheheitli (hiba.sheheitli@univ-amu.fr) or Sophie Chen (sophie.chen@univ-amu.fr)


INS Seminar: 13 Dec. 2018 – 14:00 – “What information dynamics can tell us about brains”

From Thursday 13th December 2018 at 14:00
To Thursday 13th December 2018 at 15:00

Location : INS Seminar Room, Campus Timone, Red Wing, 5th Floor

Speaker: Dr. Joseph T. Lizier, The University of Sydney

Abstract: The space-time dynamics of interactions in neural systems are often described using terminology of information processing, or computation, in particular with reference to information being stored, transferred and modified in these systems. In this talk, we describe an information-theoretic framework -- information dynamics --  that we have used to quantify each of these operations on information, and their dynamics in space and time. Not only does this framework quantitatively align with natural qualitative descriptions of neural information processing, it provides multiple complementary perspectives on how, where and why a system is exhibiting complexity. We will review the application of this framework in computational neuroscience, describing what it can and indeed has revealed in this domain. First, we discuss examples of characterizing behavioral regimes and responses in terms of information processing, including under different neural conditions and around critical states. Next, we show how the space-time dynamics of information storage, transfer and modification directly reveal how distributed computation is implemented in a system, highlighting information processing hot-spots and emergent computational structures, and providing evidence for conjectures on neural information processing such as predictive coding theory. Finally, via applications to several models of dynamical networks and human brain images, we demonstrate how information dynamics relates the structure of complex networks to their function, and how it can invert such analysis to infer structure from dynamics.

For any question, feel free to contact:
Hiba Sheheitli (hiba.sheheitli@univ-amu.fr) or Sophie Chen (sophie.chen@univ-amu.fr)



INS Seminar – 5 Dec. 2018 – 15:00 : “Resonance of Local Field Potentials in the Connectome”

From Wednesday 5th December 2018 at 15:00
To Wednesday 5th December 2018 at 16:00

Location : INS Seminar Room, Campus Timone, Red Wing, 5th Floor

 Speaker : Joana Cabral (University of Oxford, UK & University of Minho, Portugal)

"Resonance of Local Field Potentials in the Connectome "

 Abstract :  I will describe a mechanistic theory for the transient emergence of macroscopic brain rhythms as collective oscillatory modes emerging transiently from reciprocal interactions between local field potentials in the structural skeleton of the Connectome. This mechanism is grounded on theoretical principles governing the formation of frequency-specific coherent attractors in delay-coupled oscillatory systems. Using a reduced phenomenological network model representing interactions between voltage fluctuations generated locally by neuronal ensembles at 40Hz with realistic wiring and propagation times, numerical simulations reveal the transient emergence of spatially-organized collective oscillatory modes peaking between 0.5-30Hz in line with analytic predictions, matching spectral, spatial and temporal signatures of multimodal neuroimaging data.

For any question, feel free to contact:
Hiba Sheheitli (hiba.sheheitli@univ-amu.fr) or Sophie Chen (sophie.chen@univ-amu.fr)



Keynote Seminar: Virginia Penhune (Montreal)

From Wednesday 31st October 2018 at 14:00
To Wednesday 31st October 2018 at 15:30

Location : INS seminar room (5th floor) Faculty of medecine, La timone Marseille

"Music and auditory-motor integration in the human brain"

Music is a complex system of auditory communication found in all human societies. Most people can move spontaneously to music, and predictable musical structures drive both perception and production. These phenomena suggest a strong interaction between the auditory and motor systems. Structural and functional imaging studies show that brain regions of the auditory dorsal stream network are involved in both music learning and performance. This talk will describe work demonstrating the role of specific regions of the dorsal stream in musical processing, with an emphasis on the role of premotor cortex in linking sound and action.

For any question, feel free to contact:
Benjamin Morillon (bnmorillon@gmail.com)

 

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Keynote Seminar: Robert Zatorre (Montreal)

From Tuesday 30th October 2018 at 11:00
To Tuesday 30th October 2018 at 12:00

Location : INT Gastaut room Faculty of medecine, La timone Marseille

"Predispositions and Plasticity in Auditory-Motor Learning: Hemispheric Asymmetries"

Our lab has focused on music as a powerful model for understanding plasticity in a human cognitive neuroscience context. This talk will present evidence that musical training modifies auditory and motor networks, and their functional and anatomical relationships, and that important asymmetries exist across the two hemispheres in these systems. We will also discuss evidence that individual differences in learning are related to functional features that may serve as predictors of later learning success. Our goal is to develop a better model of how the large-scale organization and asymmetries of auditory-motor networks relate to the experience-dependent plasticity that underlies complex skills such as playing a musical instrument, which may also have implications for speech.

For any question, feel free to contact:
Benjamin Morillon (bnmorillon@gmail.com)

 

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INS Seminars :: Lisa Genzel and Francesco Battaglia

From Thursday 27th September 2018 at 11am
To Thursday 27th September 2018 at 2pm

Location : INS Seminar Room

Lisa Genzel:  ''Sleep for Systems Consolidation''

Francesco Battaglia:  ''Finding cell assemblies in brain activity''

 

 Special INS Seminar welcoming two guests at 11am and 2pm:

11.am Seminar  

Lisa Genzel:  ''Sleep for Systems Consolidation''

-abstract: 

''Sleep is important for memory consolidation. More specifically, it is thought that during sleep recent memories are replayed in the hippocampus and prefrontal cortex to allow for abstraction of salient information across events and consolidation from the initial, hippocampal storage to the long-term representation in the cortex.  In this talk data from both humans and rats will be presented, providing evidence for this process.''

 

2.pm Seminar

 Francesco Battaglia:  ''Finding cell assemblies in brain activity''

 

-abstract: 

 ''The brain encodes information in the activity of “cell assemblies”, groups of neurons that are tied together by synaptic plasticity and are likely to activate in a synchronous way. In turn, cell assemblies activate in sequences, reflecting the temporal ordering of the events forming e.g. the memory of an episode. Spontaneous activity (taking place as the subject is inactive) is highly structured, and contains the activation of many cell assemblies, which may reflect stored memories, imagery, or planning of future actions. I present two methods for finding cell assemblies: In the first, we reconstruct the “functional connectivity matrix” by mapping recorded neural data on an  a spin-glass network, and infer the maximum entropy model, in what is known as “reverse Ising inference”. From the connectivity matrix, cell assemblies can be reconstructed and their activity analyzed. 

The second method tackles directly the temporal dimension by defining a distance between spike patterns inspired to the Earth Mover’s distance from Optimal Transportation theory, and then applying density-based clustering on the resulting distance matrix. Application of the method to simulated and real data reconstructs the structure of data and of the behavioral circumstances the animal experiences, in a completely unsupervised fashion. 
I will frame these method in the context of systems neuroscience research, with particular focus on the study of memory systems''

 

Find some information about their work: http://www.memorydynamics.org/

 



INS PhD Defense of Marisa Saggio

From Monday 17th September 2018 at 14
To Monday 17th September 2018 at 16

Marisa Saggio will defend her PhD entitled: 

 "Epidynamics: Seizures in the Unfolding of a High Codimension Singularity ."

The defence will take place on Monday the 17th of Septembre 2018 at 14.00, in the salle de Thèse 1, blue wing, ground floor, at the Faculté de Médecine Campus Timone, 27 bd Jean Moulin - 13005 Marseille : https://medecine.univ-amu.fr/fr/salle-theses-ndeg1
 

Jury Composition:

Rapporteur : BRAZDIL MILAN, Masaryk University, Brno, Czech Republic 
Rapporteur : TERRY JOHN,  University of Exeter, UK
Examinateur : DESTEXHE ALAIN, Unité de Neurosciences, Information & Complexité, Gif-sur-Yvette, France 
Examinateur : MCGONIGAL AILEEN, Hôpital de la Timone, Marseille, France 
Examinateur : BERNARD CHRISTOPHE, Aix-Marseille Université (INS) 
Directeur de thèse : JIRSA VIKTOR, Aix-Marseille Université (INS) 

Abstract

Epilepsy is one of the most common neurological disorders. Around one third of epileptic patients are drug resistant and these patients may be candidates for surgery. Different treatment strategies can be tested computationally using personalized large-scale brain models, providing in silico tools for testing clinical hypothesis and performing virtual surgeries. Electrographic seizures can be classified using knowledge from dynamical system theory in a taxonomy of sixteen possible seizure classes. In this Ph.D. project we created a single model able to produce bursting activity for most of the classes of the taxonomy, with the aim of further personalizing the large-scale brain model using the patient specific class. We validated the taxonomy based on dynamics on a large cohort of human data. Results are consistent with the theoretical framework inspired by our model, which we called Epidynamics, in particular the most surprising finding is that most patients have more than one class of seizures contrary to standard clinic teachings, and that transitions between classes can occur during a single seizure. The Epidynamics framework highlights the role of processes acting on at least three different timescales in the generation, evolution and termination of a seizure. We performed an initial exploration of the impact of the class on recruitment, that is a key feature determining seizure propagation.