1. Brain Rhythms

2. Brain Rhythms • Need rigorous application of information theory to analyse possible role of neuronal stimulus-dependent synchronisation • How would rhythms help to solve computational problems in the brain? Need formal computational models • Would stimulus-dependent neuronal synchronisation help with the binding problem? No – just with grouping? • Rhythms/oscillations are a property of imperfectly operating neuronal feedback systems? E.g. sleep (alpha waves when no driving input with eyes closed), e.g. theta waves in rats, less in monkeys • Synchronisation of neuronal firing runs the risk of making the brain into a discrete-time processor – and this would slow it down enormously, as its speed is related to its continuous dynamics and spontaneous neuronal firing • 30 ms is sufficient time for a cortical area to perform computational sufficient for visual object recognition (as shown by backward masking experiments). This is insufficient time for binding by synchronisation. • Are rhythms useful or a hindrance to brain function? • Computers can address data packets – may not need rhythms to bind data

3. Brain Rhythms • Link physical and life scientists’ approaches • Address whether rhythms in the brain serve useful computational purposes in the brain or are they artefacts of its operation • Recent MEG opportunities • Can stimulus-dependent synchronisation be useful in solving the binding problem? • Can rhythms in coupled oscillators be used to store multiple short-term memories in a single network? • Cross-fertilisation between the physical and life sciences may work best when both work together in the same laboratory for a period. Possible job release opportunities? • Rhythms in the brain could be useful additionally for: • Time estimation • Ability to detect rhythm

4. Brain Rhythms • Control: Discrete clocking vs continuous dynamics • Continuous dynamics perhaps speed up processing • Hence discrete synchronisation (clocking) may have a drawback • Use-dependence • Required to know the purpose of rhythms: • Are they more than simple feedback control? • Are they mere correlates/symptoms or do they reflect causal control? • e.g. alpha waves (appear when eyes shut, with no driving input) • e.g. theta waves exist in rat hippocampus, hence it could be useful for computation there - possibly for pacing events • Phase (synchronicity) is important, not just frequency; however it is understood more at the macroscale, not enough at the microscale • Nonlinear dynamics in coupled oscillators could be investigated more • Neuroscientists could benefit from formal models • Variability of theta frequency

5. Brain Rhythms • Design issues in asynchronous processing • Multistable states and bursting • Binding problem: • Would stimulus-dependent neuronal synchronisation help? • No – just with grouping? • Neural processes versus actual perception: importance of transient synchronous events • Computers can address data packets – may not need rhythms to bind data • Phase synchronisation already occurs in virus attacks; can now something useful be done? • Possibility of emergent rhythmic behaviour from master-slave pairs • Need rigorous application of information theory to analyse possible role of neuronal stimulus-dependent synchronisation • Some collaboration already underway, e.g. MEG/MRI in conjunction with computer scientists • Time estimation • Ability to detect rhythm

6. Brain Rhythms • A general AI representation currently is not as useful as specific ANNs • Modern trend toward combining spatial and temporal information: many disciplines will need to converge to analyse this successfully • Study of diseased/damaged brains: What have they taught us about rhythms? • Parkinson’s: tremors • Epilepsy: the price we pay for episodic memory • More recent subtler connections