B&LdJ1 Theoretical Issues in Psychology Philosophy of Science and Philosophy of Mind for Psychologists

B&LdJ2 Chapter 8 Modern approaches to mind (2) Neural networks and connectionism ‘Classical’ versus connectionist architecture The third contender: dynamicism Is there need for ‘mental representations’? Naturalism, reductionism and folk psychology

B&LdJ3 Neurophilosophy (the Churchlands) Contrary to Fodor’s ideas: For answers to philosophical-psychological questions turn to the neurosciences (empirical knowledge - naturalism). No autonomy for psychology. Brain-based view of mind: ‘mind is brain’ (but no mind- brain identity). Eliminate folk-psychological concepts. Against sentential (propositional) LOT-view of knowledge. No solipsism, but evolutionary adaptation.

B&LdJ4 Model of a neural network Set of nodes and connections between them. Activation spreads through the network. Giving weights to the nodes. Three layers: input, output, midden layer of hidden nodes. Network learns by adjustments of weights. According to some learning rule (‘Hebb rule’). Does the training by itself, is tuned to the environment (is not pre-programmed). Maintains fault tolerance, graceful degradation (functional persistence), and satisfies soft constraints (all unlike programs). Knowledge/representations is/are distributed over many connections. Network is model of human mind: ‘connectionism’.

B&LdJ5 Working of a (quasi-neural) network ( here, a network of a submarine, learning sonar signals)

B&LdJ6 Activation space and prototypes Learning to recognize is forming a prototype, a hotspot in a vector or activation space. A concept is a prototype (not a symbol string).

B&LdJ7 Connectionism (Quasi-)neural networks: ‘neural’ patterns of activation (versus symbols and inborn rules); online selforganisation (versus offline programs); support cognitive tasks. Basic cognitive processes (formation of representations) are patterns of activation (not manipulation of symbols). Cognition is basically pattern recognition. Neurophysiology, c.q. neural networks, explains cognition: ‘cognitive neuroscience’, cognitive theories which are neurological plausible and naturalized: no functionalism; no autonomy for psychology.

B&LdJ8 Human brain has: 100 billion neurons = (10 10 ). Every neuron has: synaptic connections with (10 4 ) other neurons. In a human brain: synaptic connections. Weight of each connection can have a value of 1 out of 10. Thus human brain can contain: = cognitive configurations (cfr. total elementary particles in universe estimated ). Representational capacity of human brain

B&LdJ9 Symbolic versus connectionistic systems Fodor: thinking is characterized by productivity, systematicity, i.e. a continuous recombination of discrete symbols: compositionality, like building sentences with words: requires formal structure (networks lack structure and are not strong enough to simulate cognition; leaves you with nothing more than a plain associationpsychology); so, LOT is ‘the only game in town’: thinking occurs in a formal language; the only explanation of structure. Connectionists (a.o. Smolensky): thinking is network activation, compositionality is a by-product of networks: ‘functional compositionality’: doesn’t need a symbolic architecture; productivity of language is not the only possible productivity (Churchland).

B&LdJ10 Third Contender: Dynamism: ‘mobots’ and dynamic systems Dynamic coupling of organism and environment. Activity in environment (no inner representational domain). Online interaction (no innate structure and programs). Evolution and time (no static representations). Adaptation. Dynamic system (no representational structure: LOT or patterns of activation). Cognition is like playing tennis, rather than chess.

B&LdJ11 Dynamism: mobots Mobots : internal representations and computations redundant. Rodney Brooks: robot with response systems, direct interaction with environment, without central representations.

B&LdJ12 Dynamism: Watt governor Cognition is on-line real-time interaction with the environment – Watt governor, continuous following and control of behavior and environment; reciprocal causality.

B&LdJ13 Mental representations redundant? The absent and the abstract: there are ‘representation-hungry’ situations. that require higher cognitive functions like abstract thinking, imagination and reflection. Direct coupling mainly in sensori-motor functions. External symbols for higher cognitive tasks (planning, abstraction). ‘Active externalism’ (extended mind, Ch 9.4): for some cognitive tasks we use external instruments, e.g., paper and pencil, graphical devices; books, internet. ‘Leaky cognition’: brain and environment cannot be separated. Andy Clark (1997, 2003)

B&LdJ Naturalism and neurophilosophy Churchland Naturalism: representation is biological phenomenon, product of evolution. Cognition is pattern recognition, not symbol manipulation. Language appears late in evolution, therefore no LOT. Functionalism is a conservative ‘cheap# explanation. Folk psychology (beliefs and desires) stagnating program, isolated from scientific progress. Folk psychology eliminated and replaced by neuro-speak. 14

B&LdJ15 Naturalistic (neuroscientific) explanations of: knowledge as coded in connection weights; representation and intentionality as processes in the brain; sense of self; morality as cognitive skill; role of oxytocine in building trust and love. Churchland: Naturalism and neurophilosophy

B&LdJ16 Eliminativism and folk psychology Folk psychology (‘belief-desire’) is a kind of theory, explains behavior (Fodor + Churchland). Fodor: in principle correct theory: beliefs and desires exist really as symbol structures in LOT; are causes of behavior; folk ps. vindicated by CTM; intentional laws, generalisations, and predictions indispensable: folk psychology is successful predictor; intentional realism.

B&LdJ17 Eliminativism and folk psychology Churchland: folk psychology obsolete theory: stagnating program (Lakatos); no progress, no connections with current development in science; replace by neuroscience; eliminativism. Clark, Dennett: folk psychology is not a scientific theory, beliefs and desires only descriptive (‘intentional stance’), not internal causes (‘design stance’), not literally true; different explanatory aims; different level from neuroscientific explanation; instrumentalism.

B&LdJ18 CTMConnectionismDynamic systems Formal, syntactical rules, symbols Weights and activation patterns Coupled co-evolving systems, developing over time Preprogrammed, no real development Self-organisation, learning through adapting weights Evolving through state space, circular causality, continuous adaptation Brittle program rules Graceful degradation under damage Smooth mutual adaptation Structured, language-like architecture, concatenating discrete symbols ‘Associationism’Development in time Productivity and systematicity through compositional architecture Functional compositionality Trajectory through state space Functionalism, autonomy for psychology Reductionist, (more or less) brain-like cognition Emergent properties of organism-environment system, and development Representations are symbolic structures Representations are activation patterns No representations needed Solipsism, self-contained mind Representations are products of interaction with environment Body mind and world part of a single system