1. The Neuronal Replicator Hypothesis Chrisantha Fernando 1,2,3 Eörs Szathmary 1,4,5 1 Collegium Budapest (Institute for Advanced Study), Budapest, Hungary 2 Centre for Computational Neuroscience and Robotics, Sussex University, UK 3 MRC National Institute for Medical Research, Mill Hill, London, UK 4 Parmenides Foundation, Kardinal-Faulhaber-Strase 14a, D-80333 Munich, Germany 5 Institute of Biology, Eötvös University, Pázmány Péter sétány 1/c, H-1117 Budapest, Hungary

2. Origin of Life and the Origin of Mind Wallace didn’t believe the mind could be explained by evolution. Darwin did. Is there natural selection in the brain? Could it explain human generative problem solving, curiosity, and creativity? Natural selection destroyed the explanatory power of Divine creativity. Would natural selection in the brain destroy the explanatory power of Self?

3. What I don’t need to explain… Performance on tasks where random variation with reward biased selection could work…  Stroop Task  WCST  Tower of London Instrumental tasks with low dimensionality

5. Instrumental Conditioning: Random exploration + stabilization of good changes.

6. But SHC can’t explain generative creativity in insight problems How do we solve insight problems? What neural mechanisms underlie complex operant behaviour? Why do we play, listen to music, do PhDs, and go to Rothko exhibitions?

7. But we think that Natural Selection CAN explain generative creativity Natural selection happens when you’ve got units that can  Reproduce (replication with errors)  Transmit heritable variations For example  The adaptive immune system works by natural selection. (controlled)  So do genetic algorithms for engineering airbus wing shapes, etc… (artificial)

8. Darwinism is not just Selectionism A good solution can be copied and varied, i.e. parallel search resources can be appropriately distributed. Offspring are mutated rather than oneself.  Larger population sizes and elitism can a. increase the sensitivity of selection to beneficial variants, b. prevent loss of good solutions.  Important when most changes are harmful. Variability can be structured by natural selection.  If there is variation in variability, i.e. non-trivial neutrality and lineage selection X A B A’ B’ If(F(A’) > F(B’) & F(A’) > F(X)) choose A If(F(B’)> F(A’) & F(B’) > F(X)) choose B Else(kill A & B and try again) (1 + 2 + 4) ES

9. But how could replication happen in the brain? We propose at least two kinds of mechanism.  Copying of connectivity patterns (SLOW)  Copying of activity patterns (FAST)

10. Connectivity Copying 2. Causal Inference 1.Formation of 1->1 Mapping 2.(Topographicity)

11. Parents killing children, and children killing parents 4. Fitness calculation 3. Activity gating

12. Stop activity spread Error Correction Neurons

13. I could evolve bigger networks with these extra mechanisms

14. Activity Copying 1.Topograpicity 2. Bistability 3. Gating

15. Minimal unit of activity replication = 2 bistable neurons

16. Parents killing children, and children killing parents (again)

17. Structuring Search of Activity Replicators It is possible to combine Hebbian learning and natural selection to achieve structured variability. Previously successful evolutionary solutions can be used to bias future evolutionary search. Lamarckian inheritance in the brain.

18. Richard Watson’s HIFF

27. - Search in biased towards the previous local optima

29. Recombination

30. Further Work How does the brain  evolve representations of complex state-action spaces? Neuronal chromosomes (chunking/hierarchical coupling) of state action pairs (options by synchrony). Episodic memory may be a step in constructing such spaces (IAC algorithm).  assign value (fitness) to state-action pairs? Maximize first derivative of predictability Requires feed-forward emulators (Probabalistic robotics) Co-evolution of goals/solutions  Select actions to execute? Select actions that maximize intrinsic fitness.

31. Further Work Find behavioural evidence for neuronal replicators.  Instrumental Learning: Find behaviours that exhibit phenotypes consistent with multiple underlying neuronal replicators.  Entropic irreversibility (in the absence of memory/convergent evolution).  Behavioural pathologies in instrumental learning tasks best explainable by historical contingency.

33. Further Work Find neurophysiological evidence for neuronal replicators  Topographic mapping, STDP, bistability, and gating are known processes.  Rapid synaptic remodelling has been observed  Spontaneous neuronal activity (e.g. in sleep)

34. Thanks to Richard Goldstein Richard Watson K.K. Karishma Phil Husbands