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Download The Brain Doesn`t Work That Way: From Microgenesis to Cognition
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The Microgenetic Dynamics of Cortical Attractor Landscapes Mark H. Bickhard Lehigh University [email protected] http://bickhard.ws/ Abstract • Attractor landscapes are dispositional models of neural processes, but those landscapes themselves have a dynamics. I will outline how such landscapes are ongoingly created and modified, and how primitive representation emerges from these processes. Context: The Broader Model • Ontological Emergence • Conceptual barriers from Pre-Socratics – Hume – Kim • Emergence of Normativity • Also ancient problems – Biological function – Representation Representation • Cognition and Representation emerge in interaction systems – Self-maintenant systems – Recursively self-maintenant systems • Selection of interaction = presupposition of appropriateness; anticipation of appropriateness – ‘Appropriateness’ is normative – Derives from underlying model of normative function • Yields truth value — representation Pragmatism • An interaction based, pragmatic, model of representation – Kinship to Piaget • More complex representations – Objects – Abstractions: e.g., numbers Interaction Requires Timing • Successful interaction requires timing coordination – This is coordinative, neither too fast nor too slow • Turing machines cannot handle timing • Computers have central clocks – Not plausible for the brain Timing Requires Oscillators • Solution: Put clocks everywhere • But clocks are “just” oscillators – Functional relationships are relationships among oscillators: modulations – Trivially at least TM powerful • Need a tool kit of different forms and scales of modulation – Modulations of modulations … of oscillatory activity And This is What We Find • Neurons are standardly modeled as: – Threshold switches – Connectionist nodes – Frequency encoders • All have in common the assumption that neurons are ‘just’ input processors • And that neurons are the only functional units Both Are Wrong • Neurons and neural circuits are endogenously active – In multiple ways – They do not just process inputs • And neurons are not the only functional units – Glia, for example, are also functional, not just supportive Neurons And local circuits • Oscillators – Resonators • Multiple interesting implications – Modulations of endogenous activity, not switches of otherwise inert units Neurons II • • • • Silent neurons Interneurons Short connections Volume transmitters • L-Dopa • Graded release of transmitters • Gap junctions • Why multiple transmitters if all synapses are classical? • Transmitters evolved from hormones • Classical synapses evolved from volume transmitters Astrocytes (Glia) • • • • • • • Receive transmitters Emit transmitters Form functional “bubbles” Gap junction connections Calcium waves Modulate synaptogenesis Modulate synaptic functioning – Release, uptake, degree of volume diffusion, … Confirmation of Implication of Model of Representation • So, we do find a rich toolbox of multiple scales of modulatory relations Now In Reverse • CNS functioning implies anticipatory cognition Multiple Scales • These are all modulatory influences at multiple scales – Large and small spatial scales – Slow and fast temporal scales – There are also variations in delay times • Evolution has created a large tool box of multiple kinds and scales of modulatory influences Microgenesis: Large Temporal Scale • Larger and slower processes set the context for smaller and faster processes • They set the parameters for the faster and smaller processes – Ion and transmitter concentrations – Modes of synaptic functioning • They generate vast concurrent micro-(and meso-) modes of processing across the brain: Microgenesis Dynamic Programming • Parameter setting for dynamic processes is the dynamic equivalent of programming in a discrete system • Microgenesis sets and changes the programs across the brain • Microgenesis is ongoing and occurs in real time Functional Anticipation • Microgenetic set-up may or may not be appropriate to the actual flow of interactive processing that occurs in the organism • Microgenesis is functionally anticipatory – The anticipation is that the microgenetic set-up will be appropriate Emergence of Truth Value • Microgenetic anticipations can be true or false – And can be functionally determined to be false if the interaction violates anticipations • This is the emergence of representational truth value out of pragmatic functional success and failure Content • Microgenetic anticipations will be true in some environmental conditions, and false in others • Microgenetic anticipations, then, presuppose that the appropriate conditions — whatever they are — obtain in the current environment. – The flow of anticipated conditions is implicit in the flow of microgenesis • Those conditions constitute the content of the representing – An implicit content How Does This Differ? • Endogenously active • Interaction based, not input processing • Future oriented, not past oriented “spectator” model (Dewey) • Inherently modal: anticipations of interaction possibilities, not foundationally built on encoding correspondences with actual particulars • Implicit, thus unbounded, not explicit – Frame problems • Etc. Two Way Implication • So, analysis of representation yields a required substrate of multi-scale modulatory, interactive brain processes • And an oscillatory/modulatory tool kit is precisely what we find • And, analysis of how the brain functions yields an anticipatory, interactive model of representation • Each implies the other Microgenesis: Larger Spatial Scale — Attractor Landscapes • The slower scale processes engage in microgenetic programming of faster processes • The larger scale of these processes — astrocytes, volume transmitters, short range connections, reciprocal — induces weak coupling among oscillatory processes • Such weak coupling induces attractor landscapes connections with thalamus, etc. – Within which faster processes proceed Modulation of Attractor Landscapes • Modulation of microgenesis, therefore, modulates attractor landscapes \ Modulation of slower, larger scale process — astrocytes, etc. — modulates attractor landscapes • Provides a new framework for interpreting functionality of prefrontal - basal ganglia thalamus - cortex loops – As engaged in modulation of attractor landscapes Thought • These loops generate a kind of internal interaction with the dynamic spaces within which other CNS processes take place • This fits well with Pragmatic/Piagetian conception of thought as internal (inter)action Further Issues • Other models of representation – Millikan – Dretske – Fodor – Cummins – Encodingism Further Issues II • Other phenomena of mind • • • • • • • • • • • Perception Memory Motivation Learning Emotions Reflective consciousness Language Rationality Social ontology Personality, psychopathology Ethics Conclusion • In being intrinsically interactive, representation and cognition are inherently: • • • • • • Future oriented, anticipative Pragmatic Modal Situated Embodied … Conclusion II • And they are realized in: – Internal interactive modulations of – Attractor landscapes for – Oscillatory/ modulatory control of – Interactions of organism with environment Fini What’s Wrong with Standard Models of Representation? • Encodingism – Error, system detectable error — radical skeptical argument – Which correspondence? – Copy argument — Piaget – Externally related content: regress of interpreters – Partial recognition of problems: empty symbol problem, grounding problem What’s Wrong With Standard Models? II • Millikan – Representation as function – Etiological function is causally epiphenomena • Dretske – Etiological function again, learning history rather than evolutionary history • Fodor – Asymmetrically dependent counterfactual relations • Counter example of crank molecule What’s Wrong With Standard Models? III • Error – From observer perspective • Millikan OK • Dretske OK • Fodor Sort of OK • System detectable error – Content is not system accessible for any of these models – Comparing content with what is supposed to be being represented to determine truth or error is representational problem all over again – They are circular with respect to this criterion What’s Wrong With Standard Models? IV • Symbol system hypothesis – Transduced encoding • Connectionism – Trained encoding What’s Wrong With Standard Models? V • Dynamic systems • The interactive model is clearly a dynamic, process model • Dynamic approaches, however, are often anti-representational – E.g., Van Gelder, Thelen Dynamic Systems Approaches • But, dynamic systems as agents must select interactions, \ must functionally indicate interaction potentialities, \ must yield representational truth value \ must involve normative representation, whether that terminology is used or not – Criticisms of representation are in fact criticisms of encodingist approaches to representation Encodingism • Encodings do exist – But they borrow content – E.g., Morse code – They cannot generate emergent content • Serious problem for learning • E.g., Fodor’s innatism • Encodingism assumes that all representation is of encoding form • Encodingism does not work Further Issues • Contemporary work pervasively assumes encodingism: – – – – – – – – Perception Rationality Language Memory Learning Emotions Consciousness … Conclusion I • Representation is interactive, future oriented, pragmatic, non-encoding, modal, situated, embodied, and so on. Conclusion II • These force multiple further changes: – Perception – Language – Memory – Motivation – Learning – Models of Brain Processes – And so on Conclusion III • A major reworking of our models of and approaches to the whole person is required – The Whole Person