{"id":388,"date":"2021-06-23T09:14:02","date_gmt":"2021-06-23T07:14:02","guid":{"rendered":"https:\/\/members.loria.fr\/LBuhry\/?page_id=388"},"modified":"2025-07-07T08:10:43","modified_gmt":"2025-07-07T06:10:43","slug":"news","status":"publish","type":"page","link":"https:\/\/members.loria.fr\/LBuhry\/news\/","title":{"rendered":"News"},"content":{"rendered":"

Job offer 2025:
\nPost-Doc Position in Computational Neurosciences on Retina Modeling for Neuropsychiatry<\/h2>\n

Computational modeling and simulation of the retina electrical activity for the study of pathophysiological mechanisms of schizophrenia<\/em><\/h3>\n

 <\/p>\n

This work will be conducted in Nancy, France, at LORIA – University of Lorraine – CNRS – Inria<\/strong>, in collaboration with Ribelayga’s lab at the University of Houston, Texas, USA, for the animal electrophysiological aspects and with Silverstein’s lab at the University of Rochester, New York, USA, for the clinical and human electrophysiological aspects.<\/p>\n

The post-doc candidate will work for 3 years<\/strong> (1 year renewable) for the MERGES<\/a> project funded by the PIQ Inria programme.<\/p>\n

Candidate profile:<\/strong>
\n– Ph.D. in computational neuroscience or equivalent.
\n– Solid background in computer science, mathematics, or physics.
\n– Strong interest in fine biological processes and clinical applications.<\/p>\n

Application by email. Do not hesitate to meet with me at CNS*2025<\/strong> meeting!<\/p>\n

The University of Lorraine strongly encourage female and ethnic minorities applications.<\/p>\n

 <\/p>\n

\n

 <\/p>\n

Job offer 2023: Ph.D. Position in Computational Neurosciences<\/del> – Position filled<\/h2>\n

Computational biologically realistic modeling of the hippocampal electrical activity and plasticity for the study of pathophysiological mechanisms of schizophrenia<\/em><\/h3>\n

Application website: https:\/\/adum.fr\/as\/ed\/voirproposition.pl?site=adumR&matricule_prop=49787<\/a><\/p>\n

Directrice de th\u00e8se\u00a0: <\/b><\/span><\/span><\/span>Laure Buhry (MCF- HDR \u2013\u00a0 LORIA) – laure.buhry@loria.fr
\n<\/span><\/span><\/span>Co-directeur de th\u00e8se\u00a0: <\/b><\/span><\/span><\/span>Radu Ranta (MCF – HDR \u2013\u00a0 CRAN) – radu.ranta@univ-lorraine.fr <\/span><\/span><\/span>
\nCo-encadrant\u00a0: <\/b><\/span><\/span><\/span>J\u00e9r\u00e9mie Gaidamour (IR CNRS \u2013 IECL) – jeremie.gaidamour@univ-lorraine.fr
\n<\/span><\/span><\/span><\/span><\/span><\/p>\n

Mots-clefs\u00a0:<\/b><\/span><\/span><\/span> neurosciences computationnelles, mod\u00e9lisation math\u00e9matique, schizophr\u00e9nie, s\u00e9paration de sources, mod\u00e8le animal<\/span><\/span><\/span><\/span><\/span><\/p>\n

Contexte et \u00e9tat de l\u2019art<\/b><\/span><\/span><\/span><\/span><\/span><\/p>\n

Les troubles schizophr\u00e9niques sont des troubles psychiatriques qui affectent environ 1% de la population mondiale. D\u2019apr\u00e8s le DSM-V [1], ils sont caract\u00e9ris\u00e9s par un ensemble de sympt\u00f4mes comportementaux et \u00e9motionnels d\u00e9crits comme positifs (hallucinations, etc.), n\u00e9gatifs (anh\u00e9donie, etc.) et cognitifs (affectant apprentissage, m\u00e9moire, attention et prise de d\u00e9cision, etc.). Alors que les sympt\u00f4mes positifs sont g\u00e9n\u00e9ralement contr\u00f4l\u00e9s par les antipsychotiques, les sympt\u00f4mes n\u00e9gatifs et les\u00a0d\u00e9ficits cognitifs ne sont que mal pris en charge par ces traitements pharmacologiques [2]. L\u2019un des principaux obstacles\u00a0au d\u00e9veloppement de th\u00e9rapies efficaces reste notre compr\u00e9hension limit\u00e9e des m\u00e9canismes physiopathologiques sous-jacents. Afin de pallier cette lacune, des mod\u00e8les animaux de schizophr\u00e9nie sont d\u00e9velopp\u00e9s depuis plusieurs ann\u00e9es, mais ils ne permettent pas de r\u00e9pondre seuls aux interrogations.\u00a0Il\u00a0n\u2019est en effet\u00a0pas encore possible de dissocier totalement les propri\u00e9t\u00e9s cellulaires, synaptiques des\u00a0r\u00e9seaux de neurones impliqu\u00e9s\u00a0dans la pathologie.\u00a0<\/span><\/span><\/span><\/span><\/span><\/p>\n

Des \u00e9tudes r\u00e9centes ont mis en \u00e9vidence des perturbations des propri\u00e9t\u00e9s synaptiques hippocampiques dans les mod\u00e8les animaux valid\u00e9s de schizophr\u00e9nie [3] en comparaison \u00e0 des souris sauvages. Ces perturbations pourrait expliquer en partie les troubles cognitifs retrouv\u00e9s chez les patients, en particulier ceux impliquant la m\u00e9moire. Les propri\u00e9t\u00e9s en questions impliquent notamment la balance excitation-inhibition avec un r\u00f4le crucial jou\u00e9 par les r\u00e9cepteurs NMDA et GABA. De plus, des \u00e9tudes immunologiques et g\u00e9n\u00e9tiques, chez l\u2019\u00eatre humain et le rongeur porteurs de troubles schizophr\u00e9niques, ont pu montrer des g\u00e8nes de susceptibilit\u00e9 et des modifications \u00e9pig\u00e9n\u00e9tiques r\u00e9sultant principalement de ph\u00e9nom\u00e8nes inflammatoires capables d\u2019alt\u00e9rer la fonction des canaux ioniques, essentiellement potassiques et calciques [4,5,6]. Ces canaux sont pr\u00e9sents \u00e0 la fois sur le corps cellulaire et au niveau de la synapses, mais la plupart des traitements pharmacologiques propos\u00e9s actuellement visent essentiellement la communication synaptique.<\/span><\/span><\/span><\/span><\/span><\/p>\n

Pertinence, originalit\u00e9 et objectifs<\/b><\/span><\/span><\/span><\/span><\/span><\/p>\n

Ce travail \u00e0 pour objectif\u00a0l\u2019\u00e9tude des m\u00e9canismes physiopathologiques de la schizophr\u00e9nie gr\u00e2ce \u00e0 des approches de mod\u00e9lisation math\u00e9matique, de simulation et de traitement du signal multi-\u00e9chelles en s\u2019appuyant sur un mod\u00e8le animal de la pathologie. Il permettra d\u2019identifier de nouvelles cibles th\u00e9rapeutiques, promettant\u00a0une meilleure personnalisation des traitements pour une m\u00e9decine de pr\u00e9cision.<\/span><\/span><\/span>\u00a0<\/span><\/span>La mod\u00e9lisation math\u00e9matique associ\u00e9e \u00e0 un traitement de signaux \u00e9lectrophysiologiques\u00a0peuvent\u00a0permettre d\u2019extraire la contribution individuelle des dysfonctions\u00a0de canaux ioniques, des perturbations synaptiques et des modifications de connectivit\u00e9 structurelle.<\/span><\/span><\/span>\u00a0<\/span><\/span>Nous \u00e9mettons l\u2019hypoth\u00e8se\u00a0 que les changements de plasticit\u00e9s observ\u00e9s dans les mod\u00e8les animaux pourraient \u00eatre le r\u00e9sultat d\u2019un combinaison de facteurs intrins\u00e8ques \u00e0 la cellules, incluant une dysfonction des canaux ioniques, et de facteurs de connectivit\u00e9 tels que les capacit\u00e9 de lib\u00e9ration de neurotransmetteurs ou la topologie des connexions (balance excitation-inhibition, projections, etc) dont le principal perturbateur serait induit par les modifications de fonctions des canaux ioniques et d\u2019hom\u00e9sotasie ionique. Si cette<\/span><\/span><\/span><\/span><\/span><\/p>\n

hypoth\u00e8se venait \u00e0 \u00eatre confirm\u00e9e, ces canaux cellulaires pourraient \u00eatre consid\u00e9r\u00e9s comme de nouvelles cibles th\u00e9rapeutiques et mener \u00e0 une exploration pharmacologique visant \u00e0 am\u00e9liorer sympt\u00f4mes cognitifs et n\u00e9gatif de la pathologie.<\/span><\/span><\/span>\u00a0 <\/span><\/span><\/span>De plus, dans le contexte de la r\u00e8gle des 3R concernant l\u2019exp\u00e9rimentation animale, mod\u00e9lisation et simulation repr\u00e9sentent\u00a0des outils alternatifs aux approches exp\u00e9rimentales utilisant des animaux\u00a0particuli\u00e8rement adapt\u00e9s pour r\u00e9pondre \u00e0 ces nouveaux enjeux<\/span><\/span><\/span>.<\/span><\/span><\/span><\/p>\n

M\u00e9thodologie et techniques mises en \u0153uvre <\/b><\/span><\/span><\/span><\/span><\/span><\/p>\n

Mod\u00e9lisation biologiquement r\u00e9aliste des r\u00e9seaux de neurones.<\/i><\/span><\/span><\/span>Le travail s\u2019appuiera sur un mod\u00e8le math\u00e9matique d\u2019hippocampe [12,13]d\u00e9j\u00e0 d\u00e9velopp\u00e9 dans le cadre des th\u00e8ses de F. Giovannini<\/span><\/span><\/span>\u00a0<\/span><\/span>et d<\/span><\/span><\/span>\u2019<\/span><\/span>A. Aussel, co-encadr\u00e9e par L. Buhry (LORIA) et R. Ranta (CRAN). La premi\u00e8re \u00e9tape consistera \u00e0 adapter ce mod\u00e8le humain \u00e0 un mod\u00e8le murin en utilisant notamment les donn\u00e9es de connectome du <\/span><\/span><\/span>Allen Institute<\/span><\/span><\/a><\/u><\/span> puis \u00e0 compl\u00e9ter le mod\u00e8le d\u2019hippocampe en y int\u00e9grant diff\u00e9rents types d\u2019interneurones dont les constantes de temps synaptiques et projections topographiques diff\u00e8rent d\u2019une vari\u00e9t\u00e9 \u00e0 l\u2019autre, pouvant jouer un r\u00f4le crucial dans la synchronisation des activit\u00e9s du r\u00e9seau neuronal et donc, l\u2019int\u00e9gration des potentiels d\u2019action dans les m\u00e9canismes de plasticit\u00e9 intervenant dans l\u2019apprentissage. La seconde \u00e9tape visera \u00e0 l\u2019impl\u00e9mentation des m\u00e9canismes de plasticit\u00e9 synaptique et fera intervenir des comp\u00e9tences de programmation parall\u00e8le pour l\u2019impl\u00e9mentation optimis\u00e9e des r\u00e9seaux et la r\u00e9solution d\u2019\u00e9quations d\u2019\u00e9quations diff\u00e9rentielles non lin\u00e9aires dans des graphes de tr\u00e8s grande dimension. Dans cette optique, le.a doctorant.e interagira avec J. Gaidamour (IECL), mais aussi avec nos collaborateurs S. Contassot (Loria) et M. Stimberg (Institut de la Vision) qui est le principal d\u00e9veloppeur du logiciel avec lequel nous avions impl\u00e9ment\u00e9 le mod\u00e8le initial (<\/span><\/span><\/span>Brian<\/i><\/span><\/span><\/a><\/u><\/span>) [15].<\/span><\/span><\/span><\/span><\/span><\/p>\n

Une fois le mod\u00e8le con\u00e7u en conditions non pathologiques, nous explorerons parla simulation diff\u00e9rents scenarios physiopathologiques incluant le r\u00f4le jou\u00e9 par les dysfonctions de canaux ioniques et des propri\u00e9t\u00e9s purement synaptiques, ainsi que l\u2019influence de la connexion structurelle, souvent diff\u00e9rente (consid\u00e9r\u00e9e comme cause ou cons\u00e9quence de m\u00e9canismes de compensation), chez le sujet souffrant de troubles du spectre de la schizophr\u00e9nie, de celle du sujet sain. Certains de ces m\u00e9canismes sont explor\u00e9s actuellement dans le cadre de la th\u00e8se de L. Raison-Aubry et du travail de postdoctorat de L. Naudin, sous la direction de L. Buhry. Ces r\u00e9sultats pr\u00e9liminaires obtenus dans un mod\u00e8le de r\u00e9tine [11, 14] serviront de point de d\u00e9part. L\u2019exploration des diff\u00e9rents r\u00e9gimes de fonctionnement et des param\u00e8tres du mod\u00e8le demandera \u00e9galement des comp\u00e9tences HPC (High Performance Computing) pour lesquels J. Gaidamour sera sollicit\u00e9. <\/span><\/span><\/span><\/span><\/span><\/p>\n

Signaux \u00e9lectrophysiologiques.<\/i><\/span><\/span><\/span>Afin de confronter la mod\u00e9lisation pr\u00e9c\u00e9dente aux signaux r\u00e9els, il est n\u00e9cessaire de rajouter une derni\u00e8re \u00e9tape de mod\u00e9lisation biophysique qui permettra de g\u00e9n\u00e9rer des champs \u00e9lectriques d\u00e9pendants de la morphologie neuronale et de l\u2019anatomie. Dans nos travaux pr\u00e9c\u00e9dents, cette \u00e9tape comprenait essentiellement des contributeurs synaptiques dipolaires [13], et nous souhaitons enrichir le mod\u00e8le en int\u00e9grant des potentiels d\u2019action. Les premiers r\u00e9sultats [7] indiquent que la contribution de ces derniers dans les hautes fr\u00e9quences peut \u00eatre significative (voir aussi [8]), et nous souhaitons confronter ces mod\u00e8les \u00e0 des enregistrements \u00e9lectrophysiologiques strictement contr\u00f4les. Ces enregistrements, effectu\u00e9s sur des tranches d\u2019hippocampe apr\u00e8s stimulation \u00e9lectrique par nos collaborateurs de l\u2019\u00e9quipe COMETE (UMR 1075 INSERM Universit\u00e9 de Caen,sur un mod\u00e8le animal de schizophr\u00e9nie [3]) serviront de r\u00e9f\u00e9rence pour le mod\u00e8le math\u00e9matique pathologique. Ils n\u00e9cessiteront un traitement pr\u00e9alable, afin de s\u00e9parer les diff\u00e9rents contributeurs qui les g\u00e9n\u00e8rent. Les d\u00e9veloppements r\u00e9cents (th\u00e8se de P Jurczinsky et travaux associ\u00e9s) sur la s\u00e9paration spikes-LFP (potentiels d\u2019action-courants synaptiques) [9] et sur l\u2019activit\u00e9 proches vs. propag\u00e9e [10] seront adapt\u00e9es au contexte des enregistrements sur tranche (multi-electrodes arrays MEA).<\/span><\/span><\/span><\/span><\/span><\/p>\n

Encadrement et collaborations<\/b><\/span><\/span><\/span><\/span><\/span><\/p>\n

La th\u00e8se se d\u00e9roulera au LORIA (Neurorhythms), et au CRAN (BioSIS) avec un co-encadrement \u00e0 l\u2019IECL pour ce qui concerne la mise en \u0153uvre de la simulation num\u00e9rique et le HPC. Les expertises du LORIA seront particuli\u00e8rement sollicit\u00e9es pour les aspects de mod\u00e9lisation et de simulation, en particulier pour la mod\u00e9lisation biologiquement r\u00e9aliste des r\u00e9seaux hippocampo-corticaux. La contribution du CRAN concernera davantage la mod\u00e9lisation des ph\u00e9nom\u00e8nes \u00e9lectrophysiologiques (probl\u00e8me direct des mod\u00e8les de sources de courant jusqu\u2019aux capteurs), ainsi que l\u2019analyse des donn\u00e9es exp\u00e9rimentales. Celle de l\u2019IECL concernera les aspects li\u00e9e \u00e0 l\u2019impl\u00e9mentations logiciels des mod\u00e8les de neurones et de plasticit\u00e9 c\u00e9r\u00e9brale, \u00e0 la simulation de syst\u00e8me complexes et \u00e0 l\u2019efficacit\u00e9 des exp\u00e9rimentations envisag\u00e9es.\u00a0 La validation des mod\u00e8les d\u00e9velopp\u00e9s sera faite par confrontation \u00e0 des donn\u00e9es exp\u00e9rimentales in vitro chez le rongeur dans l\u2019\u00e9quipe COMETE. Les d\u00e9veloppements informatiques seront int\u00e9gr\u00e9s dans le logiciel de neurosciences computationnelles Brian, d\u00e9velopp\u00e9 par l\u2019\u00e9quipe de Neurosciences Computationnelles des Syst\u00e8mes Sensoriels, Institut de la Vision, Paris [15]. <\/span><\/span><\/span><\/span><\/span><\/p>\n

Ce sujet est compl\u00e9mentaire d\u2019une collaboration que nous \u00e9tablissons entre les diff\u00e9rents laboratoires dans le cadre d\u2019un d\u00e9p\u00f4t de pr\u00e9-proposition ANR.<\/span><\/span><\/span><\/span><\/span><\/p>\n

R\u00e9f\u00e9rences Bibliographiques<\/b><\/span><\/span><\/span><\/span><\/span><\/p>\n

1- DSM-V (Diagnostic and Statistical Manual of Mental Disorders). American Psychiatric Association. 2015.<\/span><\/span><\/span><\/span><\/span><\/p>\n

\u00a02- Krogmann, A. et al. Keeping up with the therapeutic advances\u00a0in SCZ: A review of novel and emerging pharmacological entities. CNS Spectr. 2019. <\/span><\/span><\/span><\/span><\/span><\/p>\n

3- Percelay S, et al. Functional Dysregulations in CA1 Hippocampal Networks of a 3-Hit Mouse\u00a0 Model of SCZ. Int J Mol Sci. 2021.<\/span><\/span><\/span><\/span><\/span><\/p>\n

4-Lam J, et al. The therapeutic potential of\u00a0 small-cond. KCa2 channels in neurodegenerative and psychiatric\u00a0 diseases. Expert Opin Ther Targets. 2013.<\/span><\/span><\/span><\/span><\/span><\/p>\n

5- Andrade, A. et al. Genetic associations between voltage-gated calcium channels and psychiatric disorders. Int. J. of Mol. Sci. 2019.<\/span><\/span><\/span><\/span><\/span><\/p>\n

6- Dietz, A.G. et al.\u00a0Glial cells in schizophrenia: a unified hypothesis,\u00a0The Lancet Psychiatry,\u00a02020. <\/span><\/span><\/span><\/span><\/span><\/p>\n

7 – Aussel, A. et al. Extracellular synaptic and action potential signatures in the hippocampal formation: a modelling study. CNS*2019, Barcelona. <\/span><\/span><\/span><\/span><\/span><\/p>\n

8- Scheffer-Teixeira R et al. On high-frequency field oscillations (>100 Hz) and the spectralleakage of spiking activity. J Neurosci. 2013.<\/span><\/span><\/span><\/span><\/span><\/p>\n

9- Le Cam S. et al. A Bayesian approach for simultaneous spike\/LFP separation and spike sorting, J. of Neural Eng., submitted 2022<\/span><\/span><\/span><\/span><\/span><\/p>\n

10- Juczinsky P et al Separating local and propagated contributors to the <\/span><\/span><\/span>Behnke<\/u><\/span><\/span><\/span>-Fried microelectrode recordings, BioSignals, 2021<\/span><\/span><\/span><\/span><\/span><\/p>\n

11- Naudin, L. et al.. A general pattern of non-spiking neuron dynamics under the effect of K and Ca channel modifications. J. Comp. Neurosci.11.2022.<\/span><\/span><\/span><\/span><\/span><\/p>\n

12-Giovannini, F.\u00a0 et al. The CAN-In network : a biologically inspired model for self-sustained theta-oscillations and memory maintenance in the hippocampus. Hippocampus, 2017. <\/span><\/span><\/span><\/span><\/span><\/p>\n

13- Aussel, A.et al. A detailed anatomical and mathematical model of the hippocampal formation for the generation of SWR and theta-nested gamma oscillations. J. Comp. Neurosci.\u00a0 2018<\/span><\/span><\/span><\/span><\/span><\/p>\n

14- Raison-Aubry, L. et al.. Mod\u00e9lisation des m\u00e9canismes sous-jacents de l\u2019ERG\u00a0 pathologique dans la schizophr\u00e9nie. L\u2019Enc\u00e9phale, Paris, 2022.<\/span><\/span><\/span><\/span><\/span><\/p>\n

15- Stimberg, M. et al. Brian 2, an\u00a0 Intuitive and Efficient Neural Simulator. eLife 8, 2019:\u00a0 e47314.<\/span><\/span><\/span><\/span><\/span><\/p>\n

\n

Workshop on Clinical Computational Neuroscience:<\/strong>
\nHow computational neuroscience can solve problems from the clinic<\/h2>\n

\u00a0July 7th 2021
\nat OCNS*2021 Online<\/h3>\n

To register to the OCNS meeting<\/strong>: https:\/\/www.cnsorg.org\/cns-2021<\/a><\/em><\/p>\n

Organizers:<\/strong> Xenia Kobeleva and Laure Buhry<\/p>\n

Date:<\/strong> July 7th\u00a0 — 9:30 am to 5:45 pm (Paris Time)<\/p>\n

Abstract and Programme:<\/strong><\/p>\n

Despite great advances in understanding of brain function using computational neuroscience, complex neural activity analyses and models are rarely used for clinical purposes. This workshop aims to bridge this gap and to bring computational neuroscientists and clinicians together to discuss current challenges and solutions for bringing more computational neuroscience to patient-oriented questions. Topics will include translation from animal models to patients, exploration of virtual therapies and personalized medicine. Apart from several success stories of clinical computational neuroscience, we will also have discussion rounds to deep dive into current challenges of the computational neuroscience community and their potential solutions. The outcome of the workshop will be to:
\n– inform interested researchers on clinically relevant questions
\n– provide an overview of computational tools that can be used to answer these questions
\n– establish a working group on clinical computational neuroscience for all interested clinicians and researchers and discuss practical steps to work on the roadblocks that were identified during the workshop<\/p>\n

The day will be organized around three \u00ab\u00a0challenges\u00a0\u00bb:
\nChallenge 1: Translation from animal models to patients: bridging species and scales
\n<\/b>Challenge 2: Virtual therapies: exploring new options and refining existing treatments
\n<\/b>Challenge 3: Personalized medicine: how to make models fit the patient<\/b><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Times in CET<\/b><\/p>\n<\/td>\n

Agenda<\/b><\/td>\n<\/tr>\n
09:30-09:45<\/td>\nIntroduction to clinical computational neuroscience and the workshop<\/b><\/td>\n<\/tr>\n
<\/td>\nChallenge 1: Translation from animal models to patients: bridging species and scales<\/b><\/td>\n<\/tr>\n
9:45-10:15<\/td>\n\n

Talk 1: Kirk Leech (confirmed)<\/p>\n<\/td>\n<\/tr>\n

10:15-10:45<\/td>\n\n

Talk 2: Matthieu Gilson (confirmed)<\/p>\n<\/td>\n<\/tr>\n

10:45-11:15<\/td>\n\n

Panel discussion: What are the current challenges? What tools and methods do we need to solve the challenges?<\/p>\n

with Kirk Leech, Matthieu Gilson and Julien Modolo<\/p>\n<\/td>\n<\/tr>\n

\n

11:15-11:30<\/p>\n<\/td>\n

\n

Break<\/p>\n<\/td>\n<\/tr>\n

<\/td>\n\n

Challenge 2: Virtual therapies: exploring new options and refining existing treatments<\/b><\/p>\n<\/td>\n<\/tr>\n

\n

11:30-12:00<\/p>\n<\/td>\n

\n

Talk 1: Yujiang Wang (confirmed)<\/p>\n<\/td>\n<\/tr>\n

\n

12:00-12:30<\/p>\n<\/td>\n

\n

Talk 2: Jil Meyer (confirmed)<\/p>\n<\/td>\n<\/tr>\n

\n

12:30-13:00<\/p>\n<\/td>\n

\n

Discussion and brainstorming: What are the current challenges? What tools and methods do we need to solve the challenges?<\/p>\n

with Yujiang Wang and Jil Meyer<\/p>\n<\/td>\n<\/tr>\n

\n

13:00-14:00<\/p>\n<\/td>\n

\n

Break<\/p>\n<\/td>\n<\/tr>\n

<\/td>\nChallenge 3: Personalized medicine: how to make models fit the patient<\/b><\/td>\n<\/tr>\n
\n

14:00-14:30<\/p>\n<\/td>\n

\n

Talk 1: Christian Meisel (confirmed)<\/p>\n<\/td>\n<\/tr>\n

\n

14:30-15:00<\/p>\n<\/td>\n

\n

Talk 2: Vesna Vuksanovic (confirmed)<\/p>\n<\/td>\n<\/tr>\n

\n

15:00-15:30<\/p>\n<\/td>\n

\n

Talk 3: Peter Hitchcock (confirmed)<\/p>\n<\/td>\n<\/tr>\n

15:30-16:00<\/td>\n\n

Discussion and brainstorming: What are the current challenges? What tools and methods do we need to solve the challenges?<\/p>\n

with Christian Meisel, Peter Hitchcock, Vesna Vuksanovic<\/p>\n<\/td>\n<\/tr>\n

16:00-16:30<\/td>\nFinal break<\/td>\n<\/tr>\n
\n

16:30-17:30<\/p>\n<\/td>\n

\n

Final discussion<\/b><\/p>\n

Clinical computational neuroscience- challenges, needs and opportunities of the OCNS community, planning the road ahead<\/p>\n

with all speakers and panel discussion members<\/p>\n<\/td>\n<\/tr>\n

\n

17:30…<\/p>\n<\/td>\n

\n

Get together with virtual coffee and drinks (<\/b>small <\/b>Zoom <\/b>chat rooms<\/b>?)<\/b><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

<\/b>Speakers:<\/strong><\/p>\n

– Kirk Leech, Executive Director of The European Animal Research Association (EARA)
\n– Matthieu Gilson, Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), J\u00fclich Research Centre, J\u00fclich, Germany, and Center for Brain and Cognition, Department of Information and Telecommunication technologies, Universitat Pompeu Fabra, Barcelona, Spain
\n– Julien Modolo (panel discussion), Research Scientist at INSERM, LTSI (Laboratory of Signal and Image processing) Rennes, France
\n– Yujiang Wang, CNNP Lab, Interdisciplinary Computing and ComplexBioSystems Group, School of Computing, Newcastle University, Newcastle uponTyne, United Kingdom
\n– Jil Meier, Berlin Institute of Health at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Berlin, Germany, and Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
\n– Christian Meisel, Department of Neurology, Charit\u00e9 – Universit\u00e4tsmedizin Berlin and Berlin Institute of Health, Berlin, Germany
\n– Vesna Vuksanovic, Swansea University Medical School and Health Data Research United Kingdom
\n– Peter Hitchcock, Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI<\/p>\n

 <\/p>\n

Talk abstracts:<\/strong><\/p>\n

Challenge 1: Translation from animal models to patients: bridging species and scales<\/b><\/u><\/p>\n

Kirk Leech<\/em>
\n<\/b>Executive Director of The European Animal Research Association (EARA)<\/p>\n

Title:<\/em> <\/strong>Update on the use of animals in research<\/em><\/p>\n

Abstract: The goal of this talk would be, for computational neuroscientists, to gain insight into the place of computational approaches in the translation from animal models to patients.<\/p>\n

The talk will focus on the need for the research community to more pro-actively engage with regulators, media and public on the need for animals in research. I will use the recent example of EURL ECVAM proposals to immediately end the use of animal derived anti-bodies in research as an example of the dangers of the research community \u2018falling asleep at the wheel\u2019 whilst those totally opposed to animal use are increasing their engagement with regulators. I will also explain how European transparency agreements work \u2013 there are now 5 in operation, involving close to 340 institutions (with three more agreements close) \u2013 to show how they can play a role in improving public understanding and acceptance of animal research, including where we can and currently can\u2019t move away from animal use.<\/p>\n

Matthieu Gilson<\/em>
\n<\/b>Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), J\u00fclich Research Centre, J\u00fclich, Germany<\/p>\n

Center for Brain and Cognition, Department of Information and Telecommunication technologies, Universitat Pompeu Fabra, Barcelona, Spain<\/p>\n

Title:<\/em> <\/strong>Bridging spatial scales in biophysical models for translational clinical applications<\/em><\/p>\n

Abstract: A great deal of dynamic models have been developed to reproduce signals obtained from neuroimaging techniques in order to formalize the relationship between structure and function. Such models typically relate empirical data like anatomical connectivity with mechanisms that describe the neuronal dynamics, which may be modelled at the microscopic level using spiking neurons or at a more mesoscopic level using neuronal population nodes. For neurology or neuropsychiatry, the computational models have been extended to incorporate data like neuromodulator or gene expression maps, which are of importance for neuropathologies. The goal is then to uncover their influence in shaping the activity patterns at the whole brain level. Such a model construction implies a number of choices in the design for the mechanisms, as well as parameters to estimate or set.<\/p>\n

In this talk I will focus on models for functional magnetic resonance imaging (fMRI) and review recent advances in the direction of clinical research. Meanwhile pointing at strengths and limitations of those studies, I will argue for a modelling that keeps a balance between predictability and interpretability. The former is to be understood in the sense of enabling a robust decoding of the fMRI activity patterns for distinct conditions (e.g. patients versus controls, or different pathological subtypes) using the estimated model parameters to derive biomarkers. The latter is necessary to relate the model parameters back to biological variables, and uncover the mechanisms involved in the neuropathological activity, beyond a \u00ab\u00a0simple\u00a0\u00bb phenomenological or statistical analysis of the empirical data. This perspective has been recently developed in an opinion article [1], which proposes to combine decoding and biophysical models to achieve the desired modelling requirements.<\/p>\n

Julien Modolo (panel discussion)<\/em>
\n<\/b>Research Scientist at INSERM, LTSI (Laboratory of Signal and Image processing) Rennes, France<\/p>\n

Expertise abstract:<\/em><\/strong> The translation of neuromodulation strategies from in vivo to in clinico is notoriously challenging. Among those challenges, emerging approaches attempt at combining morphological and computational approaches of electric field dosimetry combined with realistic models of neuronal activity to predict the response of brain tissue to specific neuromodulation sequences. In this discussion panel, I will discuss existing strategies on the topic, along with their assumptions and capabilities, and how this could bring neuromodulation faster from animal to human studies.<\/p>\n

Challenge 2: Virtual therapies: exploring new options and refining existing treatments<\/b><\/u><\/p>\n

Yujiang Wang
\n<\/em><\/b>CNNP Lab, Interdisciplinary Computing and ComplexBioSystems Group, School of Computing, Newcastle University, Newcastle uponTyne, United Kingdom<\/p>\n

Title:<\/em> <\/strong>Towards time-adaptive treatments in epilepsy using data-driven subject-specific models<\/em><\/p>\n

Abstract: Epilepsy is increasingly being recognised as a dynamic disease, where seizure characteristics and severity change over time in each patient. Understanding why, in the same patient, one seizure is severe and debilitating, while the next seizure is relatively mild in symptoms is crucial for developing time-adaptive treatments that can render severe seizure into more benign forms.<\/p>\n

To this end, we recently investigated over 500 seizure EEGs and found variable electrographic seizure dynamics within individual patients [1]. A detailed analysis of the nature of this within-subject variability revealed that specific recurrent patterns of brain dynamics during seizures can be of variable duration in each seizure or be completely absent [2]. Importantly, the variability appeared to follow subject-specific circadian or longer timescale modulations.<\/p>\n

We hypothesise that markers of these modulations on different timescales can be captured on continuously recorded EEG data over days to years. In this talk I will show that several features in the continuously recorded EEG display fluctuations on ultradian, circadian, and infradian timescales, and several subject-specific timescales are strongly associated with the presence\/absence or duration of recurrent patterns in each patient. Finally, I will also demonstrate that these fluctuations on different timescale provide a good explanation (above chance level) for how seizures change over time in each patient [3].<\/p>\n

Our results indicate that slow (ultradian, circadian, and infradian) fluctuations captured from continuously recorded EEG may serve as a biomarker to track and predict how seizures change over time. This is an important step in interacting and controlling the seizure-modulating fluctuation. Ultimately, time-adaptive treatments (e.g. via drug-delivery systems) could not only render severe seizure into more benign forms, but may be able to suppress symptomatic seizures altogether, whilst reducing side-effects.<\/p>\n

Jil Meier<\/em>
\n<\/b>Berlin Institute of Health at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Berlin, Germany
\nCharit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany<\/p>\n

Title:<\/strong> Multiscale co-simulation of deep brain stimul<\/em>ation<\/p>\n

Deep brain stimulation (DBS) has been successfully applied in various neurodegenerative diseases as an effective symptomatic treatment. However, its mechanisms of action within the brain network are still poorly understood. Many virtual DBS models analyze a subnetwork around the basal ganglia and its dynamics as a spiking network with their details validated by experimental data. However, connectomic evidence shows widespread effects of DBS affecting many different cortical and subcortical areas. From a clinical perspective, various effects of DBS besides the motoric impact have been demonstrated. The neuroinformatics platform The Virtual Brain (TVB) offers a modeling framework allowing us to virtually perform stimulation, including DBS, and forecast the outcome from a dynamic systems perspective prior to invasive surgery with DBS lead placement. For an accurate prediction of the effects of DBS, we implement a detailed spiking model of the basal ganglia, which we combine with TVB via our previously developed co-simulation environment. In the first demonstration of our model, we show that virtual DBS can move the basal ganglia firing rates of a Parkinson\u2019s disease patient\u2019s network towards the healthy regime. This study represents a proof of concept to perform virtual DBS in a co-simulation environment with TVB. The developed modeling approach has the potential to optimize DBS lead placement and configuration and forecast the success of DBS treatment for individual patients.<\/p>\n

Challenge 3: Personalized medicine: how to make models fit the patient<\/b><\/u><\/p>\n

Vesna Vuksanovic
\n<\/b><\/em>Swansea University Medical School and Health Data Research United Kingdom<\/p>\n

Title: <\/strong><\/em>Data-driven approach to neuroimaging analysis to identify dementia subtypes<\/em><\/p>\n

Abstract: Understanding variations in neurodegeneration across brain disorders that cause dementia represents one of the main challenges in clinical neuroscience. Combining advanced neuroimaging with computational models in network neuroscience has already contributed to the understanding of biological bases of such variations. Here, I will present data on the analysis of the cortical networks, derived from magnetic resonance brain scans, to assess which organisational patterns of these networks are characteristics of dementia subtypes. Statistical methods of graph theory combined with hierarchical clustering was used to analyse topology of the cortical interactions across two types of dementia, frontotemporal dementia (its behavioural variant) and Alzheimer\u2019s disease. The aim was to identify patients with more homogenous patterns of neurodegeneration.<\/p>\n

Christian Meisel<\/em>
\n<\/b>Department of Neurology, Charit\u00e9 – Universit\u00e4tsmedizin Berlin and Berlin Institute of Health, Berlin, Germany<\/p>\n

Title: <\/strong><\/em>Resilience in neural systems: from an understanding based on dynamical principles towards clinical diagnostics<\/em><\/p>\n

Abstract: In the recent years it has become apparent that dynamical system frameworks and bifurcation theory may apply to biomedical systems, beyond the systems classically considered in physics. Here, we will provide a critical survey of recent research in this field. We will discuss approaches building on dynamical systems theory to develop a better understanding of resilience and risk to rapid state changes, such as the onset of epileptic seizures, and how these theory-driven insights may provide clinical diagnostic markers.<\/p>\n

Peter Hitchcock<\/em>
\n<\/b>Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI<\/p>\n

Title:<\/strong> On the Importance of Incorporating Time and Context in Computational Psychiatry Models<\/em><\/p>\n

Abstract: Why has computational psychiatry been slow to influence routine clinical practice? I will argue that one reason is the field has had difficulty recognizing the variability among mental health problems\u2014and, consequently, the need to model context and temporal dynamics for many problems. I will propose three heuristics for deciding when modeling time and context is important. And as a case study of when such modeling is important, I will highlight contextual factors and temporal dynamics relevant to rumination and worry and thus to depression and anxiety disorders.<\/p>\n","protected":false},"excerpt":{"rendered":"

Job offer 2025:
\nPost-Doc Position in Computational Neurosciences on Retina Modeling for Neuropsychiatry
\nComputational modeling and simulation of the retina electrical activity for the study of pathophysiological mechanisms of schizophrenia<\/em><\/p>\n

 <\/p>\n

This work will be conducted in Nancy, France, at LORIA – University of Lorraine – CNRS – Inria, in collaboration with Ribelayga’s lab at the University of Houston, Texas, USA, for the animal electrophysiological aspects and with Silverstein’s lab at the University of Rochester, New York, USA, for the clinical and human electrophysiological aspects.<\/p>\n

The post-doc candidate will work for 3 years (1 year renewable) for the MERGES<\/a> project funded by the PIQ Inria programme.<\/p>\n","protected":false},"author":67,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-388","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/pages\/388","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/users\/67"}],"replies":[{"embeddable":true,"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/comments?post=388"}],"version-history":[{"count":25,"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/pages\/388\/revisions"}],"predecessor-version":[{"id":479,"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/pages\/388\/revisions\/479"}],"wp:attachment":[{"href":"https:\/\/members.loria.fr\/LBuhry\/wp-json\/wp\/v2\/media?parent=388"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}