Neuronala nätverk och system metodik och exempel

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1 Kaniza s triangel Neuronala nätverk och system metodik och exempel Typexempel på nätverksmodellering! Rytmgenerering i nejonögats ryggmärg Från jonkanal och cell till beteende! Hebbska cellgrupper Modell av kortikalt associativt minne nput Ambiguous input the Necker cube Perceptual rivalry! llustration av modellering med olika detaljeringsgrad Reducerade cellmodeller Hebbska synapser och cellgrupper Matrisminnesmodeller Hebb D O, 1949: The Organization of Behavior Bliss and ömo, 1973 evy and Steward, 1978! Cellgrupp = mentalt objekt! Gestalt perception Perceptuell komplettering Perceptuell rivalitet! Associationskedjor! Vidareutveckling, simulering 1

2 Binärt matrisminne Multi-compartmental model of pyramidal cell Willshaw and onguet-higgins, 1969 r C C m g g Na g K Na K Hodgkin-Huxley formalism Na,K,K Ca, Ca-channels Ca AP and Ca NMDA pools Fast synaptic transmission: Glutamatergic excitation (AMPA/kainate & NMDA) Glycinergic inhibition Är Hebb s cellgruppsteori biologisk plausibel? Synaptisk transmission! Orealistiskt nätverk (alla-till-alla, symmetriskt)! Höga fyrningsfrekvenser Pga ömsesidig excitation! Frekvenskod i hjärnan?! Dålig minneskapacitet! ångsam minnesåtkomst Pga låga fyrningsfrekvenser! Glutamat AMPA NMDA ångsam kinetik Spännings&transmittor beroende Saturerande (jfr hippocampus)! GABA A! edningsfördröjningar Kortikala nätverk och moduler Nätverksmodellen! Synaptiska konduktanser Från abstrakt (Bayesiansk) matrisminnesmodell (ANN) 2

3 n utskuren cellgrupp Modulation av K Ca! åg serotonin t ex => starkt adapterande pyramidcell Mönsterkomplettering, rivalitet Modulation av K Ca! Hög serotonin t ex => svagt adapterande pyramidcell Motorneuron vs Pyramidcell Kca-modulation och sustained aktivitet 3

4 Kortikala oscillationer ntensiv modelleringsaktivitet! Sustained activity som arbetsminne Prefrontal kortex! Spiksynkronisering och binding! Synaptisk plasticitet Spike-timing dependent plasticitet! konvergens i hypoteserna! men osäkerheten/spridningen är fortfarande stor! Skalning till realistisk nätverksstorlek Reducerade cellmodeller, integrate-and-fire! Drastiskt subsamplad modell Överdrivna PSP:er Är dom rimliga??! Storskalig modell neuron 4,4 milj synapser! Teoretisk skalning till 6x6 mm minikolumner 1,9 milj celler, 2 miljarder synapser Cellerna ska se samma strömmar, men via många flera synapser, 1% aktivitet Ger rimliga PSP:er, ca mv Är Hebb s cellgruppsteori biologisk plausibel?! Orealistiskt nätverk? NJ Minikolumner = ANN-enheter Skalning ger rimliga resultat! Höga fyrningsfrekvenser? NJ Saturerande synapser, NMDA ca 50% nhibition reglerar! Frekvenskod i hjärnan? OFTA Kodar konfidens, tex av observerad feature! Dålig minneskapacitet? NJ Gles aktivitet "många mönster kan lagras Glömska begränsande! ångsam minnesåtkomst? NJ! Psykologiskt rimliga åtkomsttider Ca 5 spikar/cell, 100 ms Detailed Computational Modeling of amprey Spinal and Brainstem ocomotor Circuits # Collaboration with Grillner lab at Karolinska institutet 4

5 Synopsis amprey locomotor system! Description of lamprey preparation! arly model and simulation results! arge-scale model and simulations results! Reduced network units! Traveling wave and intersegmental co-ordination! Neuro-mechanical simulation! Conclusions amprey locomotion! xperimental model for vertebrate locomotion! Swims by undulatory movements! Traveling motor wave! <1 10 Hz! Wave-length = Body length Distributed spinal rhythm generating network 100 segments (ventral root pairs) Brainstem control of speed, direction and vertical orientation Sensory feedback ocal spinal rhythm generating network M Actual number of cells per hemisegment, ca:! 20-30,! 0-1(lateralinterneurons)! 50 M (motor neurons)! Other Subsampling: One or few model neurons of each type M 1sec n vitro preparation fictive swimming Multi-compartmental model of lamprey neuron r C C m g g Na g K Na K Hodgkin-Huxley formalism Na,K,K Ca, Ca-channels Ca AP and Ca NMDA pools Fast synaptic transmission: Glutamatergic excitation (AMPA/kainate & NMDA) Glycinergic inhibition 5

6 Rhythm generation kainate/ampa activation Parallelizing simulator - SPT Rhythm generation NMDA activation! Hammarlund, keberg et al 1996, KTH Multiple platforms BM SP-2, MMD, 250 processors compartment neurons (attractor memory network) 4.4 milj synapses 100 ms simulation took minutes (8 processors) P- 600 MHz, 256 MB compartment neurons synapses 1 sec simulation took 11 min Simulating the local spinal rhythm generating network Modulation of late AHP by 5-HT M M One premotor neuron of each type Bath activation of AMPA/NMDA receptors 6

7 Previous modeling studies! ocal burst generation Frequency range, burst proportion, NMDA- and AMPA-drive 5-HT modulation of K Ca Role of Ca-dynamics and K Ca channels VA channel effects Synaptic meta-plasticity, subst P, 5-HT... Full-scale, non-segmented network model! 10 segments! 30x2x0.5mm! 1000 neurons (+)! synapses (10 %)! 25 % size variability! Non-segmented network Traveling neural/motor wave ntersegmental co-ordination Neuro-mechanical model 2D, 3D 1. Bath activation glutamate NMDA, AMPA 2. Reticulospinal drive Why large-scale models? Neuron subsampling effects Summary large-scale models One or very few model neurons of each type xaggerated synaptic conductances High spike frequencies 1sec More realistic single neuron interactions and activity! Burst structure and dynamic range reproduced! Turning rebound effects reproduced + Quantitative evaluation + Full-scale model Previous population model Reduced model of the lamprey CPG FT Hellgren et al., Biol. Cybernetics, 1992 => large/full-scale model of the spinal cord RGHT! Single compartment! Slow currents retained No Na - K for spiking! Step-wise reduction!! A population unit Pin-points basic mechanisms necessary components Formal treatment bifurcation analysis τ a Σ, τ m 7

8 A neuro-mechanical model of swimming Ca NMDA Stationary Oscillatory Distributed lamprey CPG A suite of models for one system Closed loop, neuromechanical model Behavior ocal CPG xtended ongitudinal connectivity Full-scale simulation cells (premotor interneurons) synapses SPT simulator Hammarlund & keberg, J Comput Neurosci, 1998 arge/full-scale population network model arge/full-scale network model Compartmental model neurons Biochemical network model Global network dynamics Network dynamics Cellular morphology and physiology ntracellular signaling networks A neuro-mechanical model of swimming! To study the swimming movements generated! To study the role of sensory feedback Population units forming distributed CPG ongitudinal connectivity, traveling wave Simulated body and water interacations 2D nterpretation of simulation results! The model is a quantitative hypothesis not the truth! nteraction experiment model is central! Typically several different models can explain the same set of experimental data the problem is underdetermined! The model is a tool to identify critical steps and to design maximally informative experiments 8