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  • Intro PattRecog Simulation Optimization Conclusions

    COMPUTATIONAL INTELLIGENCE FOR NEUROSCIENCE

    Concha Bielza, Pedro Larrañaga

    Departamento de Inteligencia Artificial Universidad Politécnica de Madrid

    Discovery Science and Algorithmic Learning Theory - 2009 Porto, October 3, 2009

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    Outline

    1 Introduction

    2 Pattern recognition Neuroimaging -omics Clustering of neurons Classification of neurons

    3 Computer simulation of dendritic morphology Dendritic morphology Simulation models of dendritic morphology Comparing virtual and real cells

    4 Parameter and structural optimization in neuronal and brain models Compartmental model Brain networks

    5 Conclusions Challenging More material

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    Outline

    1 Introduction

    2 Pattern recognition Neuroimaging -omics Clustering of neurons Classification of neurons

    3 Computer simulation of dendritic morphology Dendritic morphology Simulation models of dendritic morphology Comparing virtual and real cells

    4 Parameter and structural optimization in neuronal and brain models Compartmental model Brain networks

    5 Conclusions Challenging More material

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    Introduction

    COMPUTATIONAL INTELLIGENCE

    FOR NEUROSCIENCE

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    Introduction

    COMPUTATIONAL INTELLIGENCE

    FOR NEUROSCIENCE

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    Introduction

    COMPUTATIONAL INTELLIGENCE

    FOR NEUROSCIENCE

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    Neuroscience

    Neuroscience, the science of the brain Goal: understand the relationship between the physical brain and the functional mind

    —how we perceive, move, think, and remember

    A principle: all behavior is an expression of neural activity

    Involves answers to scientific fundamental questions:

    How does the brain develop? Are specific mental processes located in specific brain regions? How do nerve cells in the brain communicate with one another? How do different patterns of interconnections give rise to different perceptions and motor acts? How is communication between neurons modified by experience? How is it altered by diseases or drugs?

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The human brain

    Brain

    real sagittal view

    The most complex organ of our central nervous system and the most complex biological structure known

    Weight = 1.5kg, width = 140 mm, length = 167mm, height = 93mm

    Consumes 20 % of total body oxygen

    Stops growing at age 18

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The human brain

    Brain regions

    regions lobes

    Neuroanatomists distinguish main regions. Each has a complex internal structure

    Left-right hemispheres covered by a thin layer of gray matter known as the cerebral cortex

    Cerebral cortex, the most recently evolved region of the vertebrate brain, divided into four areas

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The human brain

    Brain areas: cerebral cortex

    Some areas, such as the cortex and cerebellum, consist of layers, folded to fit within the available space

    In mammals, neocortex: complex 6-layered structure, greatly enlarged in primates, especially frontal lobe part (in humans, extreme enlargement). Concerned with the most evolved human behavior

    Outermost=layer 1, innermost=layer 6

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The human brain

    Functions of each area (as currently understood) Medulla: sensory and motor functions

    Cerebellum: fine motor coordination and body movement, posture, and balance (not needed, but it makes actions hesitant and clumsy)

    Thalamus: acts as a switching center for nerve messages

    Hypothalamus: control of sleep/wake cycles, eating and drinking, hormone

    Hippocampus: involved in memory storage

    Olfactory bulb: processes olfactory sensory signals

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The human brain

    Functions of cortex (as currently understood)

    Occipital lobe: visual information

    Temporal lobe: auditory signals, processing language, meaning of words

    Parietal lobe: touch, taste, pressure, pain, temperature

    Frontal lobe: motor activity, integration of muscle activity, speech, thought

    Remaining parts associated with higher thought processes, planning, memory, personality and other human activities

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The human brain

    Brain at microscopic level

    Composed of neurons, blood vessels, glial cells (supporting cells of the CNS)

    Neuron is the basic structural and functional unit of the nervous system –neuron doctrine– (S. Ramón y Cajal, late 19th century)

    Just 4 microns thick→ could fit 30,000 neurons on the head of a pin ∼100,000 million= 1011 interconnected neurons

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The neuron

    3 parts of a neuron

    1 Dendrites receive info from another cell and transmit the message to soma 2 Cell body (or soma) contains the nucleus, mitochondria and other organelles

    typical of eukaryotic cells 3 Axon conducts messages away to the next neuron via a specialized structure

    –synapse– Axons fill most of the space in the brain→ >150,000 km in the human brain!! Each neuron connected to 1,000 neighboring neurons

    10,000 synaptic connections each→ 3 · 1014 synapses (adult) and 1015 (child)

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The neuron

    Variable in size and shape Neurons are more varied than cells in any other part of the body

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The neuron

    Different shapes for different functions?

    Pyramidal activate other neurons, sometimes making connections far away→ long axons to carry the electrical impulses

    Interneurons (e.g., chandelier, double bouquet, spiny stellate, basket cells) create network interactions between neighboring neurons→ short dendrites and axons

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The neuron

    Synapse: junction between 2 neurons

    Messages travel within the neuron as electrochemical impulses called action potentials, lasting less than a thousandth of a second at 1-100 m/s

    Action potential arrives at a synapse and causes a chemical called a neurotransmitter, stored in small synaptic vesicles, to be released

    Neurotransmitter binds to receptor molecules in the membrane of the target cell

    Excitatory receptors (↑ rate of action potentials in the target cell) vs. inhibitory Parkinson’s disease has a deficiency of the neurotransmitter dopamine. Alcohol weakens connections between neurons. Drugs such as caffeine, nicotine, heroin, cocaine, Prozac, act on some particular neurotransmitters

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The neuron

    Synapse Your brain generates nearly 25 watts of power while you’re awake, which is enough to light up a light bulb

    —-See video

    C. Bielza, P. Larrañaga Computational Intelligence for Neuroscience

  • Intro PattRecog Simulation Optimization Conclusions

    The neuron

    Special parts involved in synapses: spines

    Spines are found on the dendrites of most principal neurons in the brain

    Synapses typically formed on dendritic spines (discovered by Ramón y Cajal)

    Many different shapes too. Spines with strong synaptic contacts typically have a large spine head

    Dendritic spines are very “plastic”, i.e. change significantly in shape, volume, and number in small periods

    Spine plasticity is implicated in motivation, learning, and memory

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