the visual system v neuronal codes in the visual system
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
The visual system
VNeuronal codes in the
visual system
time
What‘s the code?
Firing rate Spike timing
- Synchrony- Timing patterns
’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?
The codes – firing rate
Latham & London (submitted)
Identical inputon every trial
t=0
The codes – firing rate
Latham & London (submitted)
large noise
one extra spike on trial 2
small noise
t=0
Identical inputon every trial
Latham & London (submitted)
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)
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
100 ms
θ
Latham & London (submitted)
V
100 ms
θ
extra spike
Latham & London (submitted)
V
100 ms
θ
small effect
Latham & London (submitted)
V
100 ms
θ
Latham & London (submitted)
small effect
V
100 ms
θ
Latham & London (submitted)
big effect!!!
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)
large noise
one extra spike on trial 2
small noise
t=0
Identical inputon every trial
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’
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
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
Gollisch & Meister (2008)
Fast OFF cell Biphasic OFF cell
Time[ms] Time[ms]
Onset latencies in vision
Gollisch & Meister (2008)
From external to internal timing
Experimental setup
• Anaesthesia
• Primary visual
cortex
• Grating stimuli
• 16 channels per
recording probe
• Multi- and single
unit activity
0.2 mm
Raw data
Time [ms]
Neuro
n #
Raw data
Time [ms]
Neuro
n #
Raw data
Time [ms]
Neuro
n #
Raw data
Time [ms]
Neuro
n #
Preferred firing sequences
Preferred relative firing time [ms]
Stimulus-dependent changes
Relative firing time [ms]
Stability
Relative firing time [ms]
7 ho
urs
Firing sequences and firing rates
rtotal = 0.28
r2total = 0.08
Firing rate
Firing time
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
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
Lewen et al. (2001)
Time (sec)
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)
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)
Strength and structure of inputs complement each other
Inputs modulate both rate and timing
Kuffler (1953)
Incr
ease
in s
tim
ulu
s in
tensi
ty
Stimulus onset50 ms
Inputs modulate both rate and timing
Fries et al. (2007)
Input
Input
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.