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Publications

M2
Stage
Informations pratiques
LNC2
Laboratoire:

LNC2

Équipe
Mathematics of Neural Circuits
Responsable
Boris Gutkin
Durée du stage
5-6 months
Langue
French and/or English

Alzheimer’s disease (AD) is characterized by progressive cognitive deterioration from early mild cognitive impairment (MCI)) to dementia. The multi-scale causes of such pathologies, from the subcellular to the brain level, remain elusive to experimental approaches alone. The masters project is geared towards developing new models of cell-specific pathologies associated with AD and examining their effects at teh population and functional level. Specifically the models developed will identify AD-linked beta amyloid (Ba) role in neural activity alterations and cognitive impairments. The models, constrained by state-of-the-art data, will relate abnormalities at the receptor and cellular level with deficits in cognitive functions. We will focus on data-based modeling of early AD when low levels of Ba interact with elements of the neuronal circuit (data from collaborator labs). We will examine the Ba action through nicotinic acetylcholine receptors (NNRs) on brain activity seen in AD/MCI: notably the hyperfrontality and perturbations of the theta rhythm.

The intern taking part in this project will work on one of the two aspects to specifically delineate the role of Ba action on NNRs of multiple subtypes (homomeric alpha7, heteromeric alpha7, beta2, alpha 5) in 1. the progressive onset of fronto-cortical hyperactivity or 2. the role of Ba-a7 action on failure of theta rhythm in the hippocampus. This they will be able to participate in one of two specific Aims:

Aim1: Guided by cutting edge data from Maskos lab (Pasteur Institute), we will build on our earlier developed models of NNR action in PFC circuitry to discover precise mechanisms by which soluble Ba acts on the NNR expressed on inhibitory circuitry to provoke hyperactivity. 
 

Aim2: Guided by data from Yakel lab (NIEHS) our framework will extend to a mesoscopic spiking circuit model of theta induction in the hippocampus and Ba-a7 induced dynamics pathology. 

Aim3: We will use these to model key cognitive tasks (e.g. working memory) and identify links between Ba-NNR pathways and MCI. We will profile potential nicotinic agents for functional amelioration. 

Intern will receive training in computational modelling, analysis and the neurobiology of AD. Intern will take part in the scientific life of the GNT: seminars, lectures, presentations.

M2
Internship
Informations pratiques
LNC2
Laboratoire:

LNC2

Équipe
Mathematics of Neural Circuits
Responsable
Boris Gutkin
Durée du stage
5-6 months
Langue
French and/or English

Alzheimer’s disease (AD) is characterized by progressive cognitive deterioration from early mild cognitive impairment (MCI)) to dementia. The multi-scale causes of such pathologies, from the subcellular to the brain level, remain elusive to experimental approaches alone. The masters project is geared towards developing new models of cell-specific pathologies associated with AD and examining their effects at teh population and functional level. Specifically the models developed will identify AD-linked beta amyloid (Ba) role in neural activity alterations and cognitive impairments. The models, constrained by state-of-the-art data, will relate abnormalities at the receptor and cellular level with deficits in cognitive functions. We will focus on data-based modeling of early AD when low levels of Ba interact with elements of the neuronal circuit (data from collaborator labs). We will examine the Ba action through nicotinic acetylcholine receptors (NNRs) on brain activity seen in AD/MCI: notably the hyperfrontality and perturbations of the theta rhythm.

The intern taking part in this project will work on one of the two aspects to specifically delineate the role of Ba action on NNRs of multiple subtypes (homomeric alpha7, heteromeric alpha7, beta2, alpha 5) in 1. the progressive onset of fronto-cortical hyperactivity or 2. the role of Ba-a7 action on failure of theta rhythm in the hippocampus. This they will be able to participate in one of two specific Aims:

Aim1: Guided by cutting edge data from Maskos lab (Pasteur Institute), we will build on our earlier developed models of NNR action in PFC circuitry to discover precise mechanisms by which soluble Ba acts on the NNR expressed on inhibitory circuitry to provoke hyperactivity. 
 

Aim2: Guided by data from Yakel lab (NIEHS) our framework will extend to a mesoscopic spiking circuit model of theta induction in the hippocampus and Ba-a7 induced dynamics pathology. 

Aim3: We will use these to model key cognitive tasks (e.g. working memory) and identify links between Ba-NNR pathways and MCI. We will profile potential nicotinic agents for functional amelioration. 

Intern will receive training in computational modelling, analysis and the neurobiology of AD. Intern will take part in the scientific life of the GNT: seminars, lectures, presentations.

Article dans une revue internationale  

Bobashev, G., Costenbader, E. & Gutkin, B. (2007). Comprehensive mathematical modeling in drug addiction sciences. Drug and Alcohol Dependence, 89(1), 102-106. doi:10.1016/j.drugalcdep.2006.12.029

Article dans une revue internationale  

Bobashev, G., Holloway, J., Solano, E. & Gutkin, B. (2017). A Control Theory Model of Smoking. Methods report (RTI Press), 10. doi:10.3768/rtipress.2017.op.0040.1706

Article dans une revue internationale  

Brumberg, J. & Gutkin, B. (2007). Cortical pyramidal cells as non-linear oscillators: Experiment and spike-generation theory. Brain Research, 1171(1), 122-137. doi:10.1016/j.brainres.2007.07.028

Article dans une revue internationale  

Buchin, A., Chizhov, A., Huberfeld, G., Miles, R. & Gutkin, B. (2016). Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model. The Journal of Neuroscience, 36(46), 11619--11633. doi:10.1523/JNEUROSCI.4228-15.2016

Article dans une revue internationale  

Buchin, A., Rieubland, S., Häusser, M., Gutkin, B. & Roth, A. (2016). Inverse Stochastic Resonance in Cerebellar Purkinje Cells. PLoS computational biology, 12(8), e1005000. doi:10.1371/journal.pcbi.1005000

Article dans une revue internationale  

Canavier, C., Evans, R., Oster, A., Pissadaki, E., Drion, G., Kuznetsov, A. & Gutkin, B. (2016). Implications of cellular models of dopamine neurons for disease. Journal of neurophysiology, 116(6), 2815-2830. doi:10.1152/jn.00530.2016

Acte de conférence non expertisé  

Caze, R., Humphries, M., Gutkin, B. & Schultz, S. (2013). A difficult classification for neurons without dendrites. In Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on, San Diego, CA, USA, IEEE, 215-218. doi:10.1109/NER.2013.6695910

Article dans une revue internationale  

Caze, R., Humphries, M. & Gutkin, B. (2013). Modulation of computational capacity of neurons due to dendritic synaptic interactions. PLoS Comput. Biol., 9(2)

Chapitre d'ouvrage  

Caze, R., Humphries, M. & Gutkin, B. (2013). Dendrites enhance both single neuron and network computation. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Article dans une revue internationale  

Chalk, M., Masset, P., Denève, S. & Gutkin, B. (2017). Sensory noise predicts divisive reshaping of receptive fields. PLoS computational biology, 13(6), e1005582. doi:10.1371/journal.pcbi.1005582

Article dans une revue internationale  

Chalk, M., Gutkin, B. & Denève, S. (2016). Neural oscillations as a signature of efficient coding in the presence of synaptic delays. eLife, . doi:10.7554/eLife.13824

Article dans une revue internationale  

Delorme, C., Salvador, A., Valabrègue, R., Roze, E., Palminteri, S., Vidailhet, M., De Wit, S., Robbins, T., Hartmann, A. & Worbe, Y. (2015). Enhanced habit formation in Gilles de la Tourette syndrome. Brain, 139(2), 605-615. doi:10.1093/brain/awv307

Article dans une revue internationale  

Dipoppa, M. & Gutkin, B. (2013). Flexible frequency control of cortical oscillations enables computations required for working memory. Proceedings of the National Academy of Sciences of the United States of America, 110(31), 12828-12833. doi:10.1073/pnas.1303270110