competition

degeneracy

modularity

feedback

Elements of robustness:

Feedback

FeedbackController

~100 msretinalinputs

GoalFeedforward

Controller Eyeball+ eyemovement

SensedVariable

feedback

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

Degeneracy

A classic example of degeneracy in biology: the genetic code

Swensen & Bean, J. Neurosci. 2005

cell 1 cell 2

Neuron-level degeneracy:robustness of bursting in cerebellar Purkinje cells

acutely dissociated Purkinje somata

Swensen & Bean, J. Neurosci. 2005

cell 1

cell 2

cell 3

cell 4

cell 5

cell 6

Neuron-level degeneracy:robustness of bursting in cerebellar Purkinje cells

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

Swensen & Bean, J. Neurosci. 2005

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

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

Swensen & Bean, J. Neurosci. 2005

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

Degeneracy and feedback

input outputsystemvariables

set point

homeostat

input outputsystemvariables

set point homeostat

Degeneracy and feedback

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

Mapping the state space of neuron-level degeneracy:robustness of bursting in stomatogastric ganglion neurons

model stomatogastric ganglion neuron

Evolvability - the capacity to adapt by natural selection

Evolution - adaptation by natural selection

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

Prinz et al. Nature 2004

Circuit-level degeneracy:robustness of patterns in the stomastogastric ganglion

data

Prinz et al. Nature Neuroscience 2004

Circuit-level degeneracy:robustness of patterns in the stomastogastric ganglion

model

Competition

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

Song & Abbott, Nat. Neurosci. 1999Abbott, Zoology 2003

pre leads post pre lags post

presynaptic rate = 10 Hz presynaptic rate = 13 Hz

Competitive synaptic interactions: spike-timing dependent plasticity

Song & Abbott, Nat. Neurosci. 1999Abbott, Zoology 2003

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

Modularity

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.

Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008Oertel & Young, Trends Neurosci. 2004Roberts & Portfors, Biol. Cybern. 2008

Modularity in neural circuitsa putative example: “cerebellar-like” circuits

Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008Oertel & Young, Trends Neurosci. 2004Roberts & Portfors, Biol. Cybern. 2008

Modularity in neural circuits

mammalian cerebellum mammalian dorsal cochlear nucleusteleost cerebellum

teleost medial octavolateral nucleus mormyrid electrosensory lobe gymnotid electrosensory lobe

“cerebellar-like” circuits in vertebrates

Bell, Han, & Sawtell, Annu. Rev. Neurosci. 2008Oertel & Young, Trends Neurosci. 2004Roberts & 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)

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 2001von Melchner, Pallas, & Sur, Nature 2001

Modularity in neural circuitsre-routing experiments show that auditory cortex can process visual inputs

• shorten summary (to ~400 words)

• 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