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Elements of robustness:. feedback. degeneracy. competition. modularity. Feedback. A classic example of feedback in neural circuits: error correction during smooth pursuit. feedback. retinal inputs. Feedback Controller. ~100 ms. Sensed Variable. Feedforward Controller. eye

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Elements of robustness:

feedback

degeneracy

competition

modularity



A classic example of feedback in neural circuits error correction during smooth pursuit
A classic example of feedback in neural circuits: error correction during smooth pursuit

feedback

retinal

inputs

Feedback

Controller

~100 ms

Sensed

Variable

Feedforward

Controller

eye

movement

Goal

Eyeball

+




Neuron-level degeneracy:

robustness of bursting in cerebellar Purkinje cells

cell 1

cell 2

acutely dissociated Purkinje somata

Swensen & Bean, J. Neurosci. 2005


Neuron-level degeneracy:

robustness of bursting in cerebellar Purkinje cells

cell 1

cell 2

cell 3

cell 4

cell 5

cell 6

Swensen & Bean, J. Neurosci. 2005


Neuron-level degeneracy:

robustness of bursting in cerebellar Purkinje cells

Swensen & Bean, J. Neurosci. 2005


Neuron-level degeneracy:

robustness of bursting in cerebellar Purkinje cells

An acute decrease in Na+ conductance produces a compensatory increase in voltage-dependent and Ca2+–dependent K+ conductances.

Swensen & Bean, J. Neurosci. 2005


Neuron-level degeneracy:

robustness of bursting in cerebellar Purkinje cells

Swensen & Bean, J. Neurosci. 2005


Neuron-level degeneracy:

robustness of bursting in cerebellar Purkinje cells

A chronic decrease in Na+ conductance produces a compensatory increase in Ca2+ conductance.

Swensen & Bean, J. Neurosci. 2005


Degeneracy and feedback

system

variables

output

input

homeostat

set point


Degeneracy and feedback

set point

homeostat

system

variables

output

input


Mapping the state space of neuron-level degeneracy:

robustness of bursting in stomatogastric ganglion neurons

model stomatogastric ganglion neuron

Goldman, Golowasch, Marder, & Abbott, J. Neurosci. 2001


Mapping the state space of neuron-level degeneracy:

robustness of bursting in stomatogastric ganglion neurons

model stomatogastric ganglion neuron

Goldman, Golowasch, Marder, & Abbott, J. Neurosci. 2001


Evolution

- adaptation by natural selection

Evolvability

- the capacity to adapt by natural selection

Degeneracy can increase evolvability by distributing system outcomes near phenotypic transition boundaries.


Circuit-level degeneracy:

robustness of patterns in the stomastogastric ganglion

data

Prinz et al. Nature 2004


Circuit-level degeneracy:

robustness of patterns in the stomastogastric ganglion

model

Prinz et al. Nature Neuroscience 2004



A classic example of competition in neural circuits:

the developing neuromuscular junction

Luo & O’Leary, Ann. Rev. Neurosci. 2005


Another classic example of competition in neural circuits:

developing ocular dominance columns

Luo & O’Leary, Ann. Rev. Neurosci. 2005


Competitive synaptic interactions:

spike-timing dependent plasticity

pre leads post

pre lags post

Song & Abbott, Nat. Neurosci. 1999

Abbott, Zoology 2003


Competitive synaptic interactions:

spike-timing dependent plasticity

presynaptic rate = 10 Hz

presynaptic rate = 13 Hz

Homeostatic control of total excitatory drive over a range of presynaptic firing rates.

Song & Abbott, Nat. Neurosci. 1999

Abbott, Zoology 2003



A classic example of modularity in biology:

the domain structure of genes and proteins

“Exon shuffling” was recognized early in molecular biology as a potential mechanism to generate diverse novel proteins based on existing functional building-blocks.


Modularity in neural circuits

a putative example: “cerebellar-like” circuits

Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008

Oertel & Young, Trends Neurosci. 2004

Roberts & Portfors, Biol. Cybern. 2008


Modularity in neural circuits

“cerebellar-like” circuits in vertebrates

mammalian cerebellum

teleost cerebellum

mammalian dorsal cochlear nucleus

teleost medial octavolateral nucleus

mormyrid electrosensory lobe

gymnotid electrosensory lobe

Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008

Oertel & Young, Trends Neurosci. 2004

Roberts & Portfors, Biol. Cybern. 2008


Modularity in neural circuits

  • common anatomical features of cerebellar-like circuits:

  • large principal cells (often GABAergic) having large spiny dendrites

  • principal cells receive excitatory input from a very large population of granule cells forming parallel axon bundles that target the spiny dendrites of principal cells

  • principal cells also receive excitatory ascending input from sensory regions targeting the perisomatic/proximal region of principal cells

  • common functional features of cerebellar-like circuits:

  • parallel fibers carry “higher-level” information (higher-level sensory signals, corollary discharges, proprioceptive info)

  • ascending inputs by contrast carry lower-level information (pertaining to the same sensory modality or sensorimotor task)

  • parallel fiber signals can in principle “predict” the lower-level signals

  • “prediction” is learned by pairing parallel fiber input with ascending sensory input

  • pairing produces a depression of parallel fiber inputs (anti-Hebbian plasticity)

Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008

Oertel & Young, Trends Neurosci. 2004

Roberts & Portfors, Biol. Cybern. 2008


Modularity in neural circuits

re-routing experiments show that auditory cortex can process visual inputs

Modularity can permit an organism to process a new input without evolving an entirely novel circuit from scratch—in effect, building diverse objects using existing building-blocks.

What “modules” (if any) might be the circuit-level equivalent of protein domains at the molecular level?

Sharma, Angelucci, & Sur, Nature 2001

von Melchner, Pallas, & Sur, Nature 2001


  • add an assessment (probably >300 words)

  • identify major problems, if any

  • identify unusual strengths, if any

  • for each major point, state the implications clearly

  • for each major problem, indicate appropriate solutions


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