The Function of Synchrony

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

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

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

4. 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

5. 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.

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

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

8. 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

9. 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.

10. 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?

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

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

13. Long Distance Synchrony: Methods • 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. • 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).

14. 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.

15. 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