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The visual system V
Neuronal codes in the
visual system
What‘s the code?
time
Firing rate
Spike timing
- Synchrony
- Timing patterns
The codes – firing rate
’Firing rates are the only code that ALWAYS works’
The codes – firing rate
We start with the question
Does the brain use rate or precise timing?
We turn that into:
How noisy are networks?
Latham & London (submitted)
The codes – firing rate
Identical input
on every trial
t=0
Latham & London (submitted)
one extra spike
on trial 2
Identical input
on every trial
small noise
large noise
t=0
Latham & London (submitted)
The codes – firing rate
We start with the question
Does the brain use rate or precise timing?
We turn that into:
How noisy are networks?
And finally:
How many extra postsynaptic spikes are
caused by one extra presynaptic spike?
Latham & London (submitted)
Experimental details:
• in vivo whole cell recordings
• layer 5 pyramidal cells of rat barrel cortex
• urethane anesthetic
• with and without whisker stimulation
• current injection rather than PSPs
Latham & London (submitted)
V
θ
100 ms
Latham & London (submitted)
extra spike
V
θ
100 ms
Latham & London (submitted)
V
θ
small effect
Latham & London (submitted)
100 ms
V
θ
small effect
Latham & London (submitted)
100 ms
V
θ
big effect!!!
Latham & London (submitted)
100 ms
number of extra spikes caused by just one extra spike
=
p1 × number of connections per neuron
≈
p1 × 1000
≈
0.025 × 1000
= 25
Latham & London (submitted)
one extra spike
on trial 2
Identical input
on every trial
small noise
large noise
t=0
Latham & London (submitted)
Manipulation of firing rates influences
visual perception
Salzman et al., (1992)
Manipulation of firing rates influences
visual perception
Salzman et al., (1992)
The codes – synchrony
’Perception is about association. Synchrony is too.’
The codes – synchrony
The codes – synchrony
The codes – synchrony
Center-surround interactions
Biederlack et al. (2006)
Center-surround interactions
Biederlack et al. (2006)
The escape of the bullfrog
Ishikane et al. (2005)
The escape of the bullfrog
Ishikane et al. (2005)
The codes – precise timing
’If it works, precise timing has incredible coding capacity’
The codes – precise timing
20 ms per stage!
40-50 ms
30-50 ms
1 spike per neuron!
20-40 ms
50-70 ms
70-90 ms
80-100 ms
Thorpe & Fabre-Thorpe (2001)
What can one spike tell us?
What can one spike tell us?
Theories on spike timing in the
cortex
Van Rullen & Thorpe (2001)
Onset latencies in vision
Fast OFF cell
Time[ms]
Gollisch & Meister (2008)
Biphasic OFF cell
Time[ms]
Onset latencies in vision
Gollisch & Meister (2008)
From external to internal timing
Experimental setup
• Anaesthesia
0.2 mm
• Primary visual cortex
• Grating stimuli
• 16 channels per
recording probe
• Multi- and single unit
activity
Neuron #
Raw data
Time [ms]
Neuron #
Raw data
Time [ms]
Neuron #
Raw data
Time [ms]
Neuron #
Raw data
Time [ms]
Preferred firing sequences
Preferred relative firing time [ms]
Stimulus-dependent changes
Relative firing time [ms]
7 hours
Stability
Relative firing time [ms]
Firing sequences and firing rates
Firing
rate
Firing
time
rtotal = 0.28
r2total = 0.08
# of action potentials
Relative firing time [ms]
Firing sequences and firing rates
Time [sec]
Time [sec]
rtotal = 0.01
r2total = 0.00
Neuronal coding in
the real world –
what is a
response?
Responses are multi-dimensional
Basole et al. (2003)
Information from ‘non-responsive‘
areas
Haxby et al. (2001)
Natural vision is dynamic
Things move.
The body moves.
Your eyes move.
Everything moves.
Vision is made to be a dynamic process.
´Lab´ activation
Mainen & Sejnowski (1995)
´Natural´ activation
Mainen & Sejnowski (1995)
Retinal responses to dynamic
stimuli
Meister & Berry (1999)
The fly in the woods
Lewen et al. (2001)
The fly in the woods
Time (sec)
Lewen et al. (2001)
Sparse responses in natural vision
What‘s the
code?!
Neuronal coding in the real world –
what is a signal?
Strength and structure of inputs
complement each other
• Synaptic efficacy is boosted by bursting of
a single neuron and synchrony of several
neurons (Usrey et al.,1998, 2000;
Swadlow & Gusev, 2001)
• Integration time of retinal and LGN cells
changes from 1 ms to 100 ms depending
on visual circumstances (Berry & Meister
1999, Butts & Stanley, 2007)
Strength and structure of inputs
complement each other
Rall (1964)
Strength and structure of inputs
complement each other
Rall (1964)
Strength and structure of inputs
complement each other
Rall (1964)
Strength and structure of inputs
complement each other
Rall (1964)
Strength and structure of inputs
complement each other
Rall (1964)
Strength and structure of inputs
complement each other
Rall (1964)
Strength and structure of inputs
complement each other
Rall (1964)
Strength and structure of inputs
complement each other
Euler & Denk (2004)
Stiefel & Sejnowski (2007)
Increase in stimulus intensity
Inputs modulate both rate and timing
Stimulus onset
Kuffler (1953)
50 ms
Inputs modulate both rate and timing
Input
Input
Fries et al. (2007)
Inputs modulate both rate and timing
Lengyel et al. (2005)
Stiefel et al. (2005)
Summary V –
Neuronal codes in the visual
system…
• are often brought into conceptual competition although in
every day vision, they coexist naturally
• can rarely be tested directly to find out whether they are
crucial for perception
• are diverse and have all proven successful in different
visual tasks and circumstances
The code is…
Everything.
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