SOME PRINCIPLES OF STIMULUS EVOKED CORTICAL DYNAMICS OF VISUAL AREAS

1. 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

2. 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. Roland 2002

3. How do single neurons work together and at which scale ? CORTICAL DYNAMICS Definition: in vivo spatial and temporal organization of computations and communications by cortical neurons in real time

4. 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

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

6. We stain the cortex with a Voltage sensitive dye The voltage sensitive dye binds to the membranes of all neurons. When the membrane depolarizes, the dye changes conformation < 1s and emit fluorescence at a higher wavelength Antic et al 1999

7. A STATIONARY OBJECT

8. Stimulus a 133 ms luminance contrast square

9. 25 ms 50 ms 83 ms 133 ms 250 ms No stim

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

11. A Small square lasting 83 ms

12. Time derivative of population membrane potentials = C inward current

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

16. The feedback wave

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

18. p < 0.0001 Roland et al. 2006

20. Single stationary square

21. The excitatory connexions in the cerebral cortex (Roland 2008)

22. The spike train elicited by a luminance contrast defined object interacts with the ongoing activity in area 17 and evokes Thalamo-cortical feed-forward firing IV spreading to III and II and inducing a (relative) depolarization in area 17. The onset of firing in the layers goes in the order IV, III, V, II and VI. Lateral spreading of the (relative) depolarization and firing of neurons representing the object background, continuing until feedback (4) Feed-forward (relative) depolarization of areas 19 and 21 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 a spreading decrease of excitation from the area 17 object representation And presumably a second broad feed-forward excitation of area 18,19, 21 and higher The visual system computes scenes rather than objects

23. 2. OBJECT MOTION

24. UP FROM PERIPHERY DOWN FROM PERIPHERY

25. Object Background x,y Retina stationary All that is mapped on the cortex is mapped with a Delay 40 ms So how can animals & humans ever catch or avoid an object? t3-t4 x,y ds/dt t1-t2

26. A MOVING OBJECT WILL BE MAPPED IN MANY VISUAL AREAS Ferret visual cortex

27. 2 x 1O bar moving upwards Harvey et al subm

28. UP FROM PERIPH DOWN FROM PERIPH

30. 1. STATIONARY

32. Membrane potentials form layers I-III; Firing from layer IV DOWN FROM PERIPH 25º/sec 824ms

33. Membrane potentials from layers I-III. Firing from layers V-VI DOWN FROM PERIPH 25º/sec 824ms

35. 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 prepare and execute limb movement. Meanwhile, the object mappings move over the cortex in phase, due to the predepolarization in area 17

36. 3. APPARENT MOTION

38. Apparent motion Ahmed et al. 2008

39. Apparent motion, population membrane potential Ahmed et al. 2008

40. Ahmed et al. 2008

41. The square is first mapped as stationary until 116 ms

42. Split motion Ahmed et al. 2008

43. d(V(t)rel,AM-V(t)rel;sum)/dt or the difference in dynamics between AM signal and the sum of signals to stationary single squares at identical positions and times Ahmed et al. 2008

45. Ahmed et al. 2008

46. 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 square The mapping of the square in area 19/21 moves towards the second square A feedback signal from area 19/21 instructs area 17 to depolarize the path in the direction of apparent motion and 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 object motion

47. General conclusions (so far) At the mesoscopic scale, the cerebral cortex is well behaved In 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 objects the computations and communications goes on.

48. 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

49. A: single square at 3 positions in 3 different trials B: apparent motion, square successively at the 3 positions initially mapped as stationary