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BME 6938 Neurodynamics

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BME 6938 Neurodynamics Instructor: Dr Sachin S Talathi Neurocomputational Properties Integrators: Non-existence of sub-threshold oscillations (Saddle Node on ... – PowerPoint PPT presentation

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Title: BME 6938 Neurodynamics


1
BME 6938Neurodynamics
  • Instructor Dr Sachin S Talathi

2
Neurocomputational Properties
  • Integrators Non-existence of sub-threshold
    oscillations (Saddle Node on Invariant Circle and
    Homoclinic Bifurcation)
  • Resonators Existence of subthreshold bifurcation
    (Hopf-Bifurcation)

Coexistence of Resting and Spiking State
Yes
No
Saddle-Node Saddle-Node on Invariant Circle
Subcritical-Hopf Bifurcation Supercritical-Hopf Bifurcation
Integrator
Subthreshold oscillations
Resonator
3
Neurocomputational Properties
4
Sub-threshold oscillations
  • Distinguishable feature of an oscillator near the
    threshold for Hopf Bifurcation
  • Fast low threshold potassium currents are
    primarily involved in the generation of these
    sub-threshold oscillations
  • Noise makes these oscillations sustainable
  • Slow sub-threshold oscillations however are not
    related to the particular bifurcation mechanism
    and result from interplay of slow currents with
    fast channel kinetics

Fast
Slow
5
Frequency Preference
Input
Output
Impedence
Resonator
Impedence Amplitude of Evoked potential/Amplitude
of stimulating oscillating current
6
Frequency preference of circuits
7
Frequency Preference
  • Integrators prefer high frequency
  • Inputs
  • They act as coincidence detectors
  • Resonators prefer selective frequency inputs,
    that is dependent on the natural frequency of
    their sub-threshold oscillations.

8
Mechanism of Frequency Selectivity in Resonators
9
What makes resonance interesting
10
Threshold for spiking?
Std method to determine threshold
The Dilema!
Threshold Manifolds
Well-define threshold manifolds
Threshold manifolds not well defined
11
Post Inhibitory Spike-Prolonged hyperpolarization
  • Prolonged injection of hyperpolarization current
    and sudden release can produce a rebound spike.
  • This can happen in both integrator and resonator
    models and is independent of bifurcation.
  • Often these are caused by hyperpolarization
    activated h currents, which slowly
  • build up

12
Post inhibitory spike-brief hyperpolarization
  • Post inhibitory spike resulting from brief
  • hyperpolarization is dependent on the type of
  • bifurcation
  • Integrators cannot exhibit post inhibitory spike
  • After brief hyperpolarization

Integrator
Resonator
Resonator-Postinhibitory facilitation
13
Inhibition induced spiking
Neurons with slow hyperpolarization activated h
currents and T-currents can produced inhibition
induced spiking
Resonators can exhibit this phenomenon
independent of particular ion channel properties
14
Spike Latency
Potassium A-channels (with fast activation and
slow deactivation) are typically responsible for
the observation of spike latency in neuron
models. They activate immediately on
depolarization, preventing the neuron from
producing action potential
Existence of spike latency is an
innate neurocomputational property of integrators
15
Flipping from Integrator to Resonator
16
Fast-Slow Dynamics
Fast variable includes Membrane voltage
dynamics, fast sodium currents etc.. Slow
variable includes Slow membrane currents such as
h-current
17
Neurocomputational properties resulting from
fast-slow interactions
  • Spike Frequency adaptation Decrease in
    instantaneous spiking frequency
  • A feature commonly observed in many cortical
    neurons. Slow resonant variables play an
    important role in this dynamics. It builds up
    with each spiking and slows down the spiking
    frequency

18
I-V Curve Fast Slow subsystem
Example of a Fast Slow System
  • Fast subsystem governs the spike generation
    mechanism through SNIC
  • On long time scale IK(M) dominates making the IV
    curve monotonic. The model can now indeed exhibit
    some resonant properties such as post inhibitory
    rebound.

19
Slow sub-threshold oscillations
  • One possible mechanism involving slow variables
    resulting in this observation is
  • I-V curve has two stable fixed points and the
    slow resonant variable changes the dynamics
    between these 2 states

20
Rebound response and voltage sag
  • Slow resonating h-currents generate voltage sag
    and corresponding rebound spike (cortical
    pyramidal cells)
  • Slow amplifying low threshold calcium currents
    generate rebound spikes without voltage sag (eg.
    Thalamocortical neurons)

21
After-hyperpolarization and depolarization
(AHP/ADP)
  • Slow resonating currents such as calcium
    activated potassium currents result in AHP
  • Slow amplifying currents such as T-type calcium
    currents generate ADP.
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