|
Latin American Summer School in Computational Neuroscience and Biomedical Applications, Valparaiso, Chile 2010 |
|
Academic Material for the LACONEU 2010 Summer School
Lecture 1 & 2 : Hebbian Plasticity and Homeostasis in the Visual Cortex and Intrinsic Neural Dynamics and Optimal Stimuli 1. Mato G and Samengo I. (2008). Neural Computation 20, 2418–2440 2. Brown E, Moehlis J, and Holmes P. (2004). Neural Computation 16, 673–715 3. Schwartz O et al (2006). Journal of Vision 6, 484–507
Talk
Lecture 1 & 2: Neural coding: an information theoretic approach 1. Nadal01.NBrunel_JPN_fisher.pdf 3. Nadal03.Butts_Goldman_pbio.0040092.pdf 5. Nadal05.Laughlin-TrendsNeurosci1987.pdf 7. Nadal07.lecture_coding_2010_TuningCurvesPopCod.pdf 8. Nadal08.lecture_coding_2010_LinGauss.pdf 9. Nadal09.lecture_coding_2010_Infomax_Nonlinear-transf-function.pdf Talk 1. JPNtalk01.jpn_valparaiso_2010.pdf
Lecture 1 & 2: Functional organization of the visual cortex: implications to neuronal dynamics 1. Sergio01.Lima-2009-Cereb Cortex.pdf 2. Sergio02.Horton-2005-Philos Trans R Soc Lond B Biol Sci.pdf 3. Sergio03.Engel-2001-Nat. Rev. Neurosci.pdf Talk
Lecture 1: Free viewing of natural images and the activity of the primary visual cortex: En ecological approach to understand brain function Lecture 2: How much we really now about the visual system? Confessions and experimental limitations on the study of brain function 2. Pedro02.Maldonado Grun J Neurophysiolgy 2008.pdf Talk
Lecture 1 & 2 : Neural networks as dynamical systems. We consider neural networks from the point of view of dynamical systems theory. In this spirit we review recent results dealing with the following questions, addressed in the context of specific models.
Characterizing the collective dynamics; Statistical analysis of spikes trains; Interplay between dynamics and network structure; Effects of synaptic plasticity. 1. Cessac01 Talk
Theoretical and computational neuroanatomy Lecture 1: Modelling the development of the cerebral cortex1. Welker (1990) Why does cerebral cortex fissure and fold? A review of determinants of gyri and sulci. Cerebral cortex, Vol. 8 (1990), pp. 3-136 2. Toro and Burnod (2005) A morphogenetic model for the development of cortical convolutions. Cereb Cortex 15(12):1900-1913. 3. Van Essen (1997) A tension-based theory of morphogenesis and compact wiring in the central nervous system. Nature 385, 313 - 318 Lecture 2: Traces of human evolution: analysis of brain size and anatomical variability of the human brain1. Toro et al (2008) Brain size and folding of the human cerebral cortex. Cereb Cortex. 2. Toro et al (2009) Brain volumes and the Val66Met BDNF SNP : local or global effect Brain Structure and Function. 3. Zilles et al (1988) The human pattern of gyrification in the cerebral cortex. Anat Embryol (Berl) 179:173–179. 4. Zilles et al (1989) Gyrification in the cerebral cortex of primates. Brain Behav Evol 34:143–150
Talk
Nonlinear dynamics of neuronal systems. Plenary Lecture. Dynamics of perceptual bistability: Alternating perceptions of ambiguous Lecture 1 : The geometry of neuronal excitability and oscillations and Firing rate models for slow alternating network activity. 1. Rinzel01.Geometry of neuronal excitability_from_EU_2009 2. Rinzel02.Network_rate_models_from_EU_2009 3. Rinzel03.Borisyuk_Rinzel_Chapt_LesHouches_04 5. Rinzel05.Moreno et al_noise induced alterns_JNP_2007 Talk 1. JRtalk01.Intro_neuron_nonlin_Chile_2010.pdf 2. JRtalk02.Type3_Chile_2009.pdf
Lecture 1 & 2 : Network mechanisms of Spatial Working Memory 1. Hansel01.battaglia-brunel-hansel-07.pdf 4. Hansel04.hansel-mato-01.pdf 5. Hansel05.roxin-brunel-hansel-05.pdf 6. Hansel06.shriki-hansel-sompolinsky-03.pdf
Talk
Lecture 1: Stochastic neuron models: gain, resonance and plasticity. Lecture 2: Delayed feedback in sensory processing. 3. Longtin03.pnas2006-middleton 4. Longtin04.pre051917-moe2005 7. Longtin07.PhysRevE_80_041912 Talk
Dynamics of feed-forward and recurrent cortical networks: theory and simulation techniques Lecture 1: Dynamics of feed-forward and recurrent cortical networks 1. Spike-Timing-Dependent Plasticity in Balanced Random Networks 2. The mechanism of synchronization in feed-forward neuronal networks 3. Phenomenological models of synaptic plasticity based on spike timing 4. PyNEST: A convenient interface to the NEST simulator
Talk
Tutorials: Techniques and tools for the correlation analysis of parallel spike data (I/II)Plenary Lecture: Signatures of spiking neuronal assemblies in a mesoscopic signal1. Schrader S, Grün S, Diesmann M, Gerstein G. (2008) Detecting synfire chain activity using massively parallel spike train recording. J Neurophysiol 100(4):2165-2176 2. Gruen01.Gruen09_1126.pdf 3. Gruen02.Staude10_epub.pdf 4. Gruen03.Gruen08_96.pdf 5. Gruen04.LouisEtAl_inpress.pdf Talk
Diego Cosmeli
The view from within : intracerebral EEG and human brain mapping 1. Lachaux01.Jerbi_etal_HBM_Review_2009 2. Lachaux02.LachauxBrainTVPlosOne2007
Talk
Lecture 1: Coordinate transformations and sensory-motor remapping in the visual system Lecture 2: Mental chronometry during fast choices: measuring the speed of perceptual judgments Talk
Angel Caputi Lecture 1 & 2 : Closing the action-perception cycle through periphery: From a single motor spike to many sensory images. 1. Caputi AA. (1999). JEB 202, 1229–1241. 2. Caputi AA. (2004) Journal of Physiology - Paris 98 (2004) 81–97 3. Caputi AA and Budelli R. (2006) J Comp Physiol A 192: 587–600 4. Caputi AA et al (2008) Journal of Physiology - Paris xxx (2008) xxx–xxx Talk
Ruben Budelli Lecture 1: Percection: some models Lecture 2: Electric Image 1. Subharmonic stochastic synchronization and resonance in neuronal systems 2. Theoretical Analysis of Pre-Receptor. Image Conditioning in Weakly Electric Fish 3. Electric fishmeasure distance in the dark
Talk
Neural computation in the retina
Lecture 1: Intro to retinal circuitry Mapping receptive fields and LN models; direction selectivity + circuit mechanism; object motion sensitivity + circuit model; motion anticipation + model; reversal response
Lecture 2: Encoding information with neural populations Brief intro to neural coding; multi-electrode recording in retina; qualitative features of retinal population code: sparseness, precision, heterogeneity, correlation; quantifying information: single cells (role of heterogeneity); definitions of correlation: signal vs. noise; role of correlations: synergy vs. redundancy; redundancy in code; decoding from populations
Talk
Lecture 1: From computer vision to computational neuroscience, when equations program neural networks Lecture 2: Parametric estimation : how to simply estimates complex things, three examples. 1. Variational methods as a computational model for cortical visual maps 2. Real Time implementation of Multimode estimation methods 3. A deterministic biologically plausible classifier 4. Biologically Plausible Trajectory Generator Talk
Lecture 1: Non-invasive recordings : electrophysiological phenomena and brain-computer interfaces. Lecture 2 : Modeling and detection of transient temporal graphic-elements using template-based classifiers.
Talk
Lecture 1 & 2 : The dynamics of action potential initiation and its impact on the collective properties of neocortical networks Talk
Lecture 1 & 2 : "Neural population models for sensory processing involving synaptic time scales and finite axonal conduction speed." 1. Driving neural oscillations with correlated spatial input and topographic feedback 2. Oscillatory activity in excitable neural systems
Talk 1. Axeltalk02.Valparaiso10_2nd.pdf 2. Axeltalk01.Valparaiso10_1st.ppt
Lecture 1 & 2: When Neuronal Models simulate Electrical Brain Activity (or: direct models, from neurons to EEG and EP) 1. Electroencephalogram and visual evoked potential generation 2. A neurophysiologically-based mathematical model
Talk
Lecture 1: Irregular Activity in Large Networks of Neurons. Lecture 2: The Role if Disinhibition in complex movements. 1. Chaotic balance state in a Model of Cortical Circuits. 2. Irregular Activity in Large Networks of Neurons. 3. Tutorial 1: The Fokker-Planck Equation. 4. Tutorial 2: Stochastic Models of Spike Trains. Talk |