The visual system V Neuronal codes in the visual system
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The visual system
VNeuronal codes in the
visual system
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time
What‘s the code?
Firing rate Spike timing
- Synchrony- Timing patterns
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’Firing rates are the only code that ALWAYS works’
The codes – firing rate
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We start with the question
Does the brain use rate or precise timing?
We turn that into:
How noisy are networks?
The codes – firing rate
Latham & London (submitted)
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Identical inputon every trial
t=0
The codes – firing rate
Latham & London (submitted)
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large noise
one extra spike on trial 2
small noise
t=0
Identical inputon every trial
Latham & London (submitted)
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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 arecaused by one extra presynaptic spike?
The codes – firing rate
Latham & London (submitted)
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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)
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V
100 ms
θ
Latham & London (submitted)
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V
100 ms
θ
extra spike
Latham & London (submitted)
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V
100 ms
θ
small effect
Latham & London (submitted)
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V
100 ms
θ
Latham & London (submitted)
small effect
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V
100 ms
θ
Latham & London (submitted)
big effect!!!
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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)
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large noise
one extra spike on trial 2
small noise
t=0
Identical inputon every trial
Latham & London (submitted)
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Manipulation of firing rates influences visual perception
Salzman et al., (1992)
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Manipulation of firing rates influences visual perception
Salzman et al., (1992)
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The codes – synchrony
’Perception is about association. Synchrony is too.’
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The codes – synchrony
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The codes – synchrony
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The codes – synchrony
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Center-surround interactions
Biederlack et al. (2006)
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Center-surround interactions
Biederlack et al. (2006)
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The escape of the bullfrog
Ishikane et al. (2005)
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The escape of the bullfrog
Ishikane et al. (2005)
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The codes – precise timing
’If it works, precise timing has incredible coding capacity’
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20 ms per stage!
1 spike per neuron!
Thorpe & Fabre-Thorpe (2001)
The codes – precise timing
20-40 ms
30-50 ms40-50 ms
50-70 ms
70-90 ms
80-100 ms
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What can one spike tell us?
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What can one spike tell us?
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Theories on spike timing in the cortex
Van Rullen & Thorpe (2001)
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Onset latencies in vision
Gollisch & Meister (2008)
Fast OFF cell Biphasic OFF cell
Time[ms] Time[ms]
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Onset latencies in vision
Gollisch & Meister (2008)
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From external to internal timing
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Experimental setup
• Anaesthesia
• Primary visual
cortex
• Grating stimuli
• 16 channels per
recording probe
• Multi- and single
unit activity
0.2 mm
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Raw data
Time [ms]
Neuro
n #
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Raw data
Time [ms]
Neuro
n #
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Raw data
Time [ms]
Neuro
n #
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Raw data
Time [ms]
Neuro
n #
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Preferred firing sequences
Preferred relative firing time [ms]
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Stimulus-dependent changes
Relative firing time [ms]
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Stability
Relative firing time [ms]
7 ho
urs
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Firing sequences and firing rates
rtotal = 0.28
r2total = 0.08
Firing rate
Firing time
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Firing sequences and firing rates
Time [sec]
# of
act
ion
pote
ntia
ls
Rel
ativ
e fir
ing
time
[ms]
Time [sec]
rtotal = 0.01
r2total = 0.00
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Neuronal coding in the real world
– what is a response?
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Responses are multi-dimensional
Basole et al. (2003)
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Information from ‘non-responsive‘ areas
Haxby et al. (2001)
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Natural vision is dynamic
Things move.The body moves.Your eyes move.
Everything moves.
Vision is made to be a dynamic process.
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´Lab´ activation
Mainen & Sejnowski (1995)
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´Natural´ activation
Mainen & Sejnowski (1995)
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Retinal responses to dynamic stimuli
Meister & Berry (1999)
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The fly in the woods
Lewen et al. (2001)
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The fly in the woods
Lewen et al. (2001)
Time (sec)
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Sparse responses in natural vision
What‘s the
code?!
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Neuronal coding in the real world –
what is a signal?
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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)
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Rall (1964)
Strength and structure of inputs complement each other
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Rall (1964)
Strength and structure of inputs complement each other
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Rall (1964)
Strength and structure of inputs complement each other
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Rall (1964)
Strength and structure of inputs complement each other
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Rall (1964)
Strength and structure of inputs complement each other
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Rall (1964)
Strength and structure of inputs complement each other
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Rall (1964)
Strength and structure of inputs complement each other
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Euler & Denk (2004) Stiefel & Sejnowski (2007)
Strength and structure of inputs complement each other
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Inputs modulate both rate and timing
Kuffler (1953)
Incr
ease
in s
tim
ulu
s in
tensi
ty
Stimulus onset50 ms
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Inputs modulate both rate and timing
Fries et al. (2007)
Input
Input
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Inputs modulate both rate and timing
Lengyel et al. (2005) Stiefel et al. (2005)
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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
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The code is…
Everything.