SOME PRINCIPLES OF STIMULUS EVOKED CORTICAL DYNAMICS OF VISUAL AREAS

Per.E.Roland

Bashir Ahmed

Michel Harvey

Akitoshi Hanazawa

Calle Undeman

David Eriksson

Sarah Wehner

Sonata Valentiniene

Brain Research, Dept. Neuroscience, Karolinska Institute , Stockholm, Sweden

Roland 2002

Neuron computations start by afferent inputs to the synapses (pre- and postsynaptic), propagate into the dendrites, which perform nonlinear operations, and end by producing electrical spike activity, action potential (AP), or no action potentials .

The result of the computation is a spike train. Neurons communicate by APs and transmitter diffusion. No single neuron can drive the brain.

CORTICAL DYNAMICS

Definition: in vivo spatial and temporal organization of computations

and communications by cortical neurons in real time

How do single neurons work together and at which scale ?

Complex dynamic systems are characterized by their

Architecture (invariant for shorter time periods)

And

Their dynamics

Transients induce dynamics which is different from dynamic states

One cannot predict the dynamics form the architecture

Ferret brain (mustela putorius) working at the mesoscopic scale in vivo

The voltage sensitive dye binds to themembranes of all neurons. When themembrane depolarizes, the dye changes conformation < 1s and emit fluorescence at a higher wavelength

Antic et al 1999

We stain the cortex with a Voltage sensitive dye

1. A STATIONARYOBJECT

Stimulus a 133 ms luminance contrast square

25 ms

50 ms

83 ms

133 ms

250 ms

No stim

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Single trial: luminance contrast square exposed for 133 ms, start 0

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A Small square lasting 83 ms

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Time derivative of population membrane potentials = C inward current

Laminar recording area 17/18 to stationary square in center of field of view

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The feedback wave

Neurons from area 21,19 and 18 fire to the feedback wave

p < 0.0001

Roland et al. 2006

Single stationary square

The excitatory connexions in the cerebral cortex (Roland 2008)

The spike train elicited by a luminance contrast defined object interacts with the ongoing activity in area 17 and evokes

1. Thalamo-cortical feed-forward firing IV spreading to III and II and inducinga (relative) depolarization in area 17. The onset of firing in the layers goes in the order IV, III, V, II and VI.

2. Lateral spreading of the (relative) depolarization and firing of neurons representing the object background, continuing until feedback (4)

3. Feed-forward (relative) depolarization of areas 19 and 21

4. With a further delay a Feedback wave of (relative) depolarization of most of areas 19,18 and 17 interacting first with the neurons at the 17 object representation to increase and then decrease the membrane potential here and apparently segment the object from background

2. a spreading decrease of excitation from the area 17 object representation

3. And presumably a second broad feed-forward excitation of area 18,19, 21 and higher

The visual system computes scenes rather than objects

2. OBJECT MOTION

UP FROM PERIPHERYUP FROM PERIPHERY

DOWN FROM DOWN FROM PERIPHERYPERIPHERY

t3-t4

t1-t2

ObjectBackgroundx,y

x,y ds/dt

All that is mapped on the cortex is mapped with a Delay 40 ms

Retina stationary

So how can animals & humans ever catch or avoid an object?

Ferret visual cortex

A MOVING OBJECT WILL BE MAPPED IN MANY VISUAL AREAS

2 x 1O bar moving upwards

Harvey et al subm

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UP FROM PERIPHUP FROM PERIPH

DOWN FROM PERIPHDOWN FROM PERIPH

1. 1. STATIONARYSTATIONARY

DOWN FROM PERIPHDOWN FROM PERIPH

25º/sec 824ms25º/sec 824ms

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Membrane potentials form layers I-III; Firing from layer IV

DOWN FROM PERIPHDOWN FROM PERIPH

25º/sec 824ms25º/sec 824ms

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Membrane potentials from layers I-III. Firing from layers V-VI

Moving objects on the retina are mapped, with a delay of ~50 ms,moving in retinotopic organized visual areas.

Area 17/18 send feed-forward the object motion to areas 19/21 (layer IV).

In the examples of linear motion, area 19/21 compute a prediction of the future trajectory of the object after ~ 130 ms.

This prediction is sent as feedback to area 17 (layers V VI) instructing area 17 neurons to compute similar prediction and predepolarizing the future cortical path.

The prediction maps the future position 250 ms ahead of the object’s position in cortex.

This gives the animal (human) sufficient time to saccade or prepareand execute limb movement.

Meanwhile, the object mappings move over the cortex in phase, due to the predepolarization in area 17

3. APPARENT MOTION

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Apparentmotion

Ahmed et al. 2008

Apparent motion, population membrane potential

Ahmed et al. 2008

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Ahmed et al. 2008

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The square is first mapped as stationary until 116 ms

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Ahmed et al. 2008

Split motion

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d(V(t)rel,AM-V(t)rel;sum)/dt or the difference in dynamics between AM signaland the sum of signals to stationary single squares at identical positions and times

Ahmed et al. 2008

Ahmed et al. 2008

Signals that humans perceive as moving objects. When the identical Square stimuli are shown to the ferret, The square stimuli are initially mapped in area 17 as stationary, but

Time-locked to the offset of the first square1. The mapping of the square in area 19/21 moves towards the

second square 2. A feedback signal from area 19/21 instructs area 17 to

depolarize the path in the direction of apparent motion and 3. The mapping of the square in area 17 moves towards the site

of the next square

The mapping of the square in 19/21 was computed as moving, but computed as stationary in area 17. This discrepancy elicit a feedback from the higher order area forcing are 17 to compute objectmotion

At the mesoscopic scale, the cerebral cortex is well behavedIn real time studies

Communications are reflected in changes of the membrane potentials of the target populations of neurons Examples of communications: feed-forward, feedback with different messages, lateral spreading depolarizations.

Higher order areas may enslave lower order areas though feedback.

The lateral spreading depolarizations and the feedbacks engage very large neuron populations in all visual areas so far measured.

For stationary objects the feed-forward -feedback computations are finished < 120-130 ms. For moving objectsthe computations and communications goes on.

General conclusions (so far)

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Temporal derivative of population membrane potentials, d(∆V(t))/dt, of all animals aligned to cytoarchitectural borders: area 19/21 teaching area 17 the prediction

A: single square at 3 positions in 3 different trials

B: apparent motion, square successively at the 3 positions initially mapped as stationary

The offset ofshort duration stimulielicit a decrease inthe inward currentthat postpones the OFF response

ConsequentlyThe time intervalBetween the ONand OFF firing peakIs prolonged forStimuli < 100 ms

r(t) firing rate