MCB 161 Lec 11 Neural circuits and computations

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  1. What structure is highly conserved across species?
    Neocortical circuits
  2. What is the cortex composed of?
    • A crystalline array of a repeated unit
    • The cortical column
  3. How many cortical layers are there and what are they?
    • 4 excitatory cortical layers
    • Layers 2/3, 4, 5, 6
    • Different in anatomy and connectivity that columns
  4. What's the physical basis of all neural computation?
    Circuits
  5. How do we understand neural computation?
    • Need to understand a wiring diagram
    • It's necessary but not sufficient
  6. Why is a wiring diagram not sufficient to understand neural computation?
    • Can't reconstruct thoughts
    • Dont have connection strength in simple wiring diagrams
    • Don't know the types of neurotransmitters in synapses
    • Don't know lots of info and dynamics
  7. Neurons and synapses are highly ______.
    dynamic
  8. What do we need both of to understand neural computation?
    Both anatomy (wiring) and function (dynamics)
  9. What is functional mapping of circuit activity?
    Looking at synapses in real neurons in real circuits
  10. How do we identify microcircuits?
    Record two connected cells in the same layer with two electrodes to measure if there is an action potential and see if there is also a postsynaptic potential
  11. What kind of recording is used to identify the microcircuits with two electrodes?
    "paired electrophysiological recording'
  12. What has functional mapping provided a 'roadmap' for?
    The flow of excitation in neural circuits
  13. What are the 5 strongest connections btwn layers?
    • L4 → L2
    • L3 → L3
    • L4 → L4
    • L5A → L5A
    • L3 → L5B
  14. What are the ascending connections?
    • L4 → L3
    • L4 → L2
    • L3 → L2
  15. What are the descending connections?
    • L2 → L5A
    • L3 → L5A
    • L3 → L5B
    • L4 → L5A
    • L4 → L5B
    • L4 → L6
    • L5A → L5B
  16. Between which layers do the greatest number of synapses come from?
    • Greatest number of synapses in any layer comes from neuron in the same layer
    • Talking most to neighbors
  17. Why are there a lot more synapses in the same layer?
    Important for amplifying signals and stuff
  18. Circuit analysis in the 'age of light'??
    Laser scanning photo-stimulation??
  19. Laser scanning photo-stimulation??
    • Can target one cell and stimulate all presynaptic cells connected to it
    • Can see most input from neighbors nearby
  20. Inhibition in the CNS can perform what kind of operations?
    Can mediate both subtraction and division
  21. What are some of the putative functions of inhibition?
    • Spike timing
    • Spatial control
    • Oscillations
    • Gain control
    • Sharpening feature selectivity (orientation tuning, direction selectivity, etc.)
    • Sparse representation
    • Decorrelation
  22. What does gain control do?
    • Doesn't transform signals
    • Just changes dial of "loudness" of signals
    • Matches signals w/ range of hearing for example
  23. What is decorrelation?
    When you don't want all neurons spiking at the same time cuz that'll be redundant
  24. Image UploadWhat is this image showing?
    Ultra precise timing of neural firing in trigeminal ganglion (1st order neurons)
  25. Image UploadWhat is this image showing us?
    • Very precise timing of neural firing in the thalamus (VPM)
    • Thalamus = relay from periphery to cortex
    • AP's pretty precise with noisy stimulus
  26. What should biophysical properties of neurons and synapses do as information is transferred to the cortex?
    Degrade temporal fidelity
  27. What is temporal fidelity?
    • The precision of spikes in time
    • Ex. Jitter of spikes low if high fidelity
  28. What are some of the biophysical properties of neurons and synapses that degrade temporal fidelity (take more than a ms)?
    • Axon conduction
    • Channel gating
    • Synaptic release
    • Membrane time constant (low pass filter on synaptic potentials)
  29. Where is there also precise timing?
    In the somatosensory cortex
  30. How do circuits achieve precise firing?
    Feed-forward inhibition
  31. Why is feed-forward inhibition important?
    Fundamental and conserved circuit motif across entire CNS
  32. In the cortex, which follows which? (inhibition/excitation)
    • Excitation is always followed by inhibition
    • (Inhibition comes after excitation)
  33. When is there a mix of excitation and inhibition in post synaptic cell?
    When in between both reversal potentials of GABA and glutamate
  34. Image UploadWhat's this image telling us?
    • Figure 1
    • Stimulate excitatory cells
    • Each produce EPSP
    • But each one by itself not sufficient to spike cell
    • But b/c each is about 50%, if two come at exact same time, can spike

    Delayed them to see window of operation/opportunity when two inputs summate to get a post syn potential
  35. What does FFI enforce?
    Temporal fidelity
  36. What is FFI?
    Feed-forward inhibition
  37. What generates brief windows for activation?
    Fast somatic disynaptic ihibition
  38. Image UploadWhat is this a basic schematic of?
    Lateral inhibition
  39. What is lateral inhibition?
    • Get inhibition from sides onto center
    • (similar to horizontal cells in retina but actually fire APs)
  40. Why have lateral inhibition in cortex?
    Increases salience of response?
  41. What was lateral inhibition tested on?
    Somatosensation on cat leg
  42. Why was lateral inhibition tested on somatosensation on cats?
    • Somatosensory map on cortex
    • So when you stimulate one part of leg next to another, similar thing happening on cortex
  43. What happened when a neuron on the leg was stimulated then another neuron next to it was also stimulated?
    Second stimulation suppressed the firing of first
  44. How is lateral inhibition helpful?
    • General principle across sensory modalities that may improve the resolution of sensory processing
    • Sharpens edge resolution
  45. What is surround suppression good for?
    • Mutual inhibition helps distinguish objects?
    • Suppression could help discriminate and judge the size of objects
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MCB 161 Lec 11 Neural circuits and computations
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2016-02-19 13:37:29
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MCB 161 Lec 11 Neural Circuits Computation
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MCB 161 Lec 11 Neural circuits and computations
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