2. The Function of Synchrony Marieke Rohde Reading Group DyStURB (Dynamical Structures to Understand Real Brains)

3. Structure 1.Sound recognition by transient synchrony. (Hopfield & Brody) 2.Long distance synchronisation in Human subjects (Rodriguez et. Al.) 3.Discuss!

4. 1.) Hopfield, Brody: What is a moment? (Puzzle and Answer)

5. Mus Silicium Short time integration in an artificial organism Biologically plausible model, spiking neurons. Auditory task: one syllable recognition – short time integration required to "represent" the world. Mastered robustly

6. Mus Silicium - Anatomy Layer 4: –50% inhibitory, 50% excitatory –Lots of cells and connections no delays, no plasticity Sensors: cells are frequency tuned and respond to –Onsets –Offsets –Peaks Transient decay of neural activity at different decay rates.

7. Mus Silicium - Anatomy The alpha and beta neurons from „cortical layer 4“ exhibit the same properties as the sensory neurons!

8. Mus Silicium: Responses Gamma cells: highly specific to learned syllable.

9. Mus Silicium: The Solution General Principle: Transient synchrony of APs to „signal“ recognition Representation of time of a stimulus by different decay rates spatiotemporal patterns: Convergence of firing rate of decaying currents. Same rate neurons (coupled oscillators) tend to synchronise. (set weights accordingly) Detection by cell with small time constant Invariant to time-warping (rescaling in time), delays and salience

10. Mus Silicium: The Solution 800 lines (different stimuli and decay rates) from area A project on an excitatory and an inhibitory cell Training = find set of coinciding neurons on pattern and mutually couple them (excitatory and inhibitory) Balance between excitation and inhibition, to assure network input current from outside. Connect whole set to a gamma neuron, to yield a reaction.

11. Mus Silicium Extensions: –reactivation of sensors? (several, probablistic activation) –Negative evidence. Destroy synchrony/detection.  Robustness against noise –Multiple patterns: Phase transition n  infty to general synchrony Structure, not weights. Several structures conceivable Biological plausibility. Conclusion: –A „Many are now equal“ operator. –Model spiking networks if you want to explain the brain! How could you have guessed it?

12. 2.) Rodriguez et.al.: Perception's shadow: longdistance synchronization of human brain activity

13. Long Distance Synchrony 30-80 Hz oscillations (gamma) synchronise during a cognitive act. (EEG MEG measurements) Task: Recognition of a degraded stimulus (Mooney face)

14. Long Distance Synchrony: Methods 1.Detect induced gamma response: "wigner ville time frequency transforms“ of single trials and average. first peak is known (much stronger in perception condition) second new, practically the same for both conditions. 1.Phase synchrony: –the phase synchrony profile is very different from the gamma activity profile –baseline: shuffled data. –no perception remains close to baseline. –perception: synchronisation, desynchronisation, synchronisation (zero centered distribution of phase lags).

15. Long Distance Synchrony: Conclusions biological significance for cogntion confirmed. (refutation to different criticisms) High level, rather than low local feature binding New finding: desynchronisation to prepare for next synchronisation (destroy old pattern). gamma activity != synchrony.

16. Discussion Differences: –Local vs. Global (+ role of delays) –Detectors vs. Unknown function. –Low level vs. High level What methods to detect it in organisms? –Phase lag: 0 or different? –Time spans vs. every spike. Synchrony - Asynchrony What function could synchrony have? –Attractive state (type of population code) –Internal clock