Download Yuste-Banbury-2006 - The Swartz Foundation

Neuron. 1991 Mar;6(3):333-44.
Control of postsynaptic Ca2+ influx in developing neocortex by excitatory and inhibitory
neurotransmitters.
Yuste R, Katz LC.
Laboratory of Neurobiology, Rockefeller University, New York, New York 10021.
We assessed the pathways by which excitatory and inhibitory neurotransmitters elicit postsynaptic
changes in [Ca2+]i in brain slices of developing rat and cat neocortex, using fura 2. Glutamate, NMDA,
and quisqualate transiently elevated [Ca2%]i in all neurons. While the quisqualate response relied
exclusively on voltage-gated Ca2+ channels, almost all of the NMDA-induced Ca2+ influx was via the
NMDA ionophore itself, rather than through voltage-gated Ca2+ channels. Glutamate itself altered
[Ca2+]i almost exclusively via the NMDA receptor. Furthermore, synaptically induced Ca2+ entry relied
almost completely on NMDA receptor activation, even with low-frequency stimulation. The inhibitory
neurotransmitter GABA also increased [Ca2+]i, probably via voltage-sensitive Ca2+ channels, whereas
the neuromodulator acetylcholine caused Ca2+ release from intracellular stores via a muscarinic
receptor. Low concentrations of these agonists produced nonperiodic [Ca2+]i oscillations, which were
temporally correlated in neighbouring cells. Optical recording with Ca2(+)-sensitive indicators may thus
permit the visualization of functional networks in developing cortical circuits.
Calcium imaging of cortical microcircuits
2+
Single-cell resolution imaging of Ca influx due to action potentials
• L5 pyramid loaded with 50µM fura
• imaged by photodiode array at 1.6 kHz (0.6ms/frame)
Whole-cell filled
AM filled
Trains of action potentials
40 Hz
50 Hz
Cortical circuits in vitro are spontaneously active:
spontaneous activity as a tool, let the circuit speak
QuickTime™ and a
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Automatic identification of cells
II/III
IV
V
Detection of calcium transients
Spontaneous synchronizations of a small % of neurons
Low temporal resolution- 1sec/frame
a
Cell number
700
500
300
% cells active / frame
100
7
6
5
4
3
2
1
0
*
*
p < 0.05
*
**
**
Spontaneous coactivations have specific spatial patterns
Synchronizations correspond to UP states
1
2
3
4
1
2
3
4
-70 mV, 0 pA
9 mV
500 ms
9 mV
5s
9 mV
500 ms
9 mV
1.3 s
UP states can last several seconds
Stereotyped dynamics of circuit coactivations
Cortical motifs and songs: repeated sequences of activity
Intermediate temporal resolution- 50 msec/frame
Shuffling tests
Photodiode array: 0.6 msec/frame
Local synchronizations
Sequential activations of cells
Pacemakers
Pacemakers are more regular
Repeated network activity measured in a single cell
10 KHz resolution
i
iii
iv
Repeated motifs of spontaneous activity in slices
10 pA
200 ms
Millisecond precision
Correlation between intracellular and optical repetitions
Repetitions in vivo
Ilan Lampl/David Ferster
What is role of thalamic stimulation on cortical dynamics?
L2/3
L4
L5
Adapted from Brecht
et al 2003
Imaging Layer 4 response to thalamic stimulation
“Barrel” Cortex
Thalamus
4-8 stimuli
40 Hz
200 ms
50 – 100 mA
Stimulation Electrode
Thalamic Stimulation
Thalamic stimulation generates cortical UP states
20 mV
Vm -70 mV
1s
•
•
•
•
Prolonged depolarizations
~ 10 mV depolarized from rest
Preferential state for action potential
generation
Coincident with multiple nearby neurons
UP states
Spontaneous activity also generates cortical UP
states
20 mV
500 ms
Spontaneous
Spontaneous activity and thalamic stimulation engage the same neurons !!!
Triggered
X5
Spontaneous
X4
Overlap
Triggered Core
Spontaneous Core
Overlap Core
Similar Spontaneous and Evoked Intracellular UP states
Triggered
Spontaneous
Overlap
5mV
# of
APs
20mV
Amplitude
1s
Duration
Correlation of UPstates within cells
Amplitude
Duration
No. APs
500 ms
Identical Network Dynamics during Spontaneous
and Evoked Network Events- 100 msec/frame
Triggered
Spontaneous
2
3
Time
Frame Number
1
Core
Millisecond Precision in the Repetition of
Synaptic inputs during spontaneous and thalamic UP states
10 mV
500 ms
5 mV
100 ms
Novel types of spontaneous network dynamics
Data:
• Reverberating activity is prevalent at all temporal scales
• Spatiotemporal patterns are real: statistics, two techniques,
spatial profile, UP states, they can be triggered
• Sparse dynamics: small number of cells
• Single neurons can participate in many patterns
• Repetitions never exact
• Thalamic stimulation triggers internal states
Speculation:
• Spatially organized ensembles: related to circuit features?
• Preferred states: attractors or metastable states?
• Precisely repeated dynamics: Abeles’ synfire chains?
• Cortex as a giant CPG?
Cortex as a giant CPG
Spinal Central Pattern Generator
Cortical Microcircuit
Buqing Mao-postdoc
Rosa Cossart-postdoc
Dimitry Aronov-undergraduate student
Yuji Ikegaya-visiting professor
Gloster Aaron-postdoc
Jason McLean-postdoc
Brendon Watson-MD PhD student
National Eye Institute- HHMI
Synfire chains hypothesis- Moshe Abeles
Synchronous firing
Nonlinear gain paradoxically reduces jitter
Faithful propagation
Faithful repetition
Precise Firing Sequences
Two theories of brain function:
Feed forward:
Sherrington
Hubel &Wiesel
Receptive fields
Speed of processing
Feedback:
Brown
Lorente/Hebb
Llinás
Recurrent connectivity
Spontaneous activity
Pyramidal neurons in layer 5
An Already Existing Network Mediates the Observed
Dynamics
Triggered
Naive
2
3
Time
Frame Number
1
Core
An Already Existing Network Mediates the
Observed
Dynamics
10 mV
500 ms
Even in L4, the vast majority of
excitatory synapses arise
locally within cortex
40 %
30 %
<10 %
Thalamus
(20 % long corticocortical
excitatory connections)
Circuit attractors
Input
Attractors
Inputs
Adapted from Wilson, 1999
Memories
Example of an emergent computation
Synfire chains
Evidence for synfire chains
Abeles PFS
Spatial navigation in hippocampus
Birdsong sequences
CPGs
Arguments against
Statistics
Nonlinear null hypotheses
Mechanism unknown
UP states promote precise firing patterns
in response to thalamic input
Single Thalamic Stimulation
During DOWN state
50 mV
-72 mV
Train of Stimuli
During DOWN state
1st
Spike
40 ms jitter
-52 mV
-72 mV
1st Spike
2nd Spike
Train of Stimuli<2 ms jitter
<5 ms jitter
During UP state
-52 mV
-72 mV
25 ms
Searching for
repeats of activity in
a single neuronal
recording
Examine the covariance, h(), between segments:
(AxB), (AxC),...(BxC), (BxD),......
Two competing world views:
How is perception shaped?
Empiricism
Feed Forward
Nativism
Feedback
Synchronizations correspond to maximum organization