Evolution IN the brain?

1. Evolution IN the brain? Munich Eörs Szathmáry Collegium Budapest Eötvös University

2. The neuronal replicator hypothesis Chrisantha Fernando, Eörs Szathmáry University of SussexAND Collegium Budapest

3. Units of evolution • multiplication • heredity • variability Some hereditary traits affect survival and/or fertility

4. The importance of cumulative selection Natural selection is a non-random process. Evolution by natural selection is a cumulative process. Cumulative selection can produce novel useful complex structures in relatively short periods of time.

5. The extended evolutionary synthesis Extending the Modern Synthesis in depth: e.g. questions of evolvability and evolution of development Extending the Modern Synthesis in width: e.g. chemical, linguistic and neuronal replicators Forthcoming Book from the Altenberg meeting (Konrad Lorenz Institute)

6. Von Kiedrowski’s replicator

7. What makes us human? Note the different time-scales involved Cultural transmission: language transmits itself as well as other things A novel inheritance system

8. Evolution OF the brain

9. Fluid Construction Grammar with replicating constructs (with Luc Steels) • selective amplification by linked replication • mutation, recombination, etc.

10. William James, 1890 Every scientific conception is, in the first instance, a 'spontaneous variation' in someone's brain. For one that proves useful and applicable there are a thousand that perish through their worthlessness. Their genesis is strictly akin to that of the flashes of poetry and sallies of wit to which the instable brain-paths equally give rise. But whereas the poetry and wit (like the science of the ancients) are their own excuse for being ... the 'scientific' conceptions must prove their worth by being 'verified'. This test, however, is the cause of their preservation, not of their production…

11. Baldwin, 1889 And how far the method of law called by Darwin "natural selection" goes, what its range really is, we are now beginning to see in its varied applications in the sciences of life and mind. It seems to be--unless future investigations set positive limits to its application--a universal principle; for the intelligence itself, in its procedure of tentative experimentation, or "trial and error," appears to operate in accordance withit.

12. Monod, 1971 For a biologist it is tempting to draw a parallel between the evolution of ideas and that of the biosphere. For while the abstract kingdom stands at a yet greater distance above the biosphere than the latter does above the nonliving universe, ideas have retained some of the properties of organisms. Like them, they tend to perpetuate their structure and to breed; they too can fuse, recombine, segregate their content; indeed they too can evolve, and in this evolution selection must surely play an important role. I shall not hazard a theory of the selection of ideas. But one may at least try to define some of the principal factors involved in it. This selection must necessarily operate at two levels: that of the mind itself and that of performance.

13. Dawkins 1971, 1976 Selective neurone death as a possible memory mechanism (1971) Conceptualization of the meme as the cultural analogue of a gene that spectacularly evolve in a population of human brains (1976) There is a „neuronal genotype of memes”

14. Campbell, 1974 A blind-variation-and-selective-retention process is fundamental to all inductive achievements, to all genuine increases in knowledge, to all increases in the fit of system to environment… in going beyond what is already known, one cannot but go blindly. If one can go wisely, this indicates already achieved wisdom of some general sort.

15. Changeux, 1973 There is selection, but without the capacity for the modification of a heuristic search (permitted by the full natural selection algorithm). This fundamentally important limitation is admitted by the authors who write "an organism can not learn more than is initially present in its pre-representations."

16. Variation and selection in neural development (Changeux) There is vast overproduction of synapses Transient redundancy is selectively eliminated according to functional needs The statistics and the pruning rules for the network architecture are under genetic control

17. Edelman, 1987 Edelmans theory of neuronal group selection proposes that a primary repertoire of neuronal groups within the brain compete with each other for stimulus and reward resources. This results in selection of a secondary repertoire of behaviourally proficient groups

18. Crick on Edelman (1989)

19. Crick, continued…

20. There are no units of evolution here! We propose that the algorithms of Edelman and Changeux fundamentally consist of a population of stochastic hill-climbers. Each neuronal group is randomly initialized, and those groups that are closest to a good solution obtain a greater quantity of synaptic resources allowing them to ‘grow’ and/or ‘change’. Thus groups become strengthened but not replicated.

21. A crucial limitation Replication has the advantage of leaving the original solution intact, so that a non-functional variant does not result in loss of the original solution. Unless the neuronal group has the capacity to revert to its original state given a harmful variation, in which case it is effectively behaving as a 1+1 Evolutionary Strategy (Beyer 2001), there is the potential that good solutions are lost.

22. We shall hazard a theory of the selection of neuronal replicators. One may at least try to define some of the principal factors involved in it.

23. The copying problem of neuronal connectivity DNA neuronal network

24. An elementary copying circuit

25. Maps and copies Hebbian synapse: neurons that fire together wire together: CORRELATIONS Spike-time dependent plasticity (STDP): if A fires before B, then the connection from A to B is strengthened, otherwise it is weakened: CAUSALITY

26. With error correction and sparse activation

27. Cycles of copying and assessment 1. The circuit to be copied exists in the lowerlayer L0. The black connections in L0 show the original circuit. 2. Horizontal UP connections are activated, e.g. by opening neuromodulatory gating.These are the equivalent of the h-bonds in DNA copying. 3. A copy of the topology of L0 is made in L1, using STDP and error correction. 4. The layersare functionally separated by closing neuromodulatory gating of the UP connections. The fitness of each layer is assessed independently. 5. The layerwith the lowest fitness is erased or reset, i.e. strong synaptic connections are reduced. In the above diagram we see that L1 fitness greater than L0 fitness, so L0experiences weight unlearning. 6. DOWN vertical connection gates are opened. 7. STDP in layer 0 copies the connections in L1. 8. After DOWNconnections are closed, fitness is assessed and the cycle continues.

28. Why is natural selection better than stochastic search? Population diversity allows parallel exploration with resources biased on current success. It allows the evolution of evolvability (cf. sex)

29. Dynamical Neuronal Replicators The minimal unit of activity replication consists of two reciprocally coupled bistable neurons (black circles), gating by two associated inhibitory neurons (red circles). 8 of these units can be chained together to form the experimental setup The gates controlling the output of parent 0 for example can be switched on and off together.

30. A Copying Event

31. The Hierarchical IF and only IF (HIFF) problem A rugged fitness landscape that is difficult to climb

32. Recombination Instead of a one to one reciprocal circuit, there is a many to one reciprocal circuit. Instead of a gating vector, there is a gating matrix. The top diagram shows the minimal unit from which the system is composed. It consists of a population size of 3, with genome length = 1. Gating can determine which of the parental states are to be copied to the offspring. The bottom figure shows 5 of these units combined together forming 3 parents with genome length = 5. Recombination is simply undertaken by opening for example gates, A1, B1, C1 and D2, E2. Once the offspring has been formed and its fitness assessed, it is recopied back to the parent that most resembles it.

33. Functions Structured search in rugged problems, e.g. insight problems, working memory Memory consolidation from dynamical to topological replicators Function passing rather than data passing Repair of connectivity patterns A neuronal basis for causal inference

34. Insight problems How to connect all the dots with three straight lines only? Sleep helps Lots of spontaneous intrinsic neuronal activity!

35. What is neuronal fitness? We know that reward systems DO exist in the brain Maximize learning progress (i.e. 1st derivative of predictability) Maximize mutual information between future and past

36. We have just scratched the surface! Hypothetical mechanisms how it MIGHT work The brain is a breeder, „evolution” in the brain could be more similar to artificial than natural selection! Encourage more competent people to come up with other variants of the idea Test the ideas against experimental evidence: behaviour, dynamic neuronal phenomena at a high resolution Select for or against the idea

37. GRAZIE…