Consciousness as Integrated Information

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Presentation on Integrated Information Theory of Consciousness, part of the Complex Systems Seminar, at Chalmers University of Technology

Transcript of Consciousness as Integrated Information

  • 1. Consciousness as Integrated InformationComplex Systems Seminar|SHAMIT BAGCHI |05-Nov-2014"We cannot doubt of our existence while we doubt Ren Descartes (1596 1650)MSc, Complex Adaptive Systems, Chalmers University of Technology

2. Communication between brain networks in people given psilocybin psychedelic drug called magic mushrooms (right) or a non-psychedelic compound (left). Petri et al./Proceedings of the Royal Society InterfaceA hyperconnectedbrainA normal brainConsciousness Alteration -Psychedelic ExperiencesDots and colorscorrespond to connection-rich networksGreater communication across the whole brain after psilocybin (magic mushroom) intakePsychedelic experiences, of sensory mix-up: tasting colors, feeling sounds, seeing smells etc. 3. Agenda:ConsciousnessHere, There, Everywhere?Subjective ExperienceWhat is it?Where Subjective Experience arises: NCCSubjective States and Neural CorrelatesIntegrated InformationIntegrated Information Theory (IIT), EI, Complexes and Qualia SpaceThe Quale as Conscious ExperienceQuantity and Quality of Consciousness 4. Consciousness is HereConsciousness is everything we experience!The past two centuries of clinical and laboratory studies reveal an intimate relationship between the conscious mind and the brainThe exact nature of this relationship remains elusive. 5. Conscious is There!Less ConsciousConscious too? 6. But Not Everywhere!Or is consciousness perhaps everywhere?Pervading the cosmos, as in an old Panpsychisttradition 7. How can Subjective Experience be explained?Perhaps consciousness emerges when an organism is immersed in some complex sensorimotor loop including the environmentPerhaps Consciousness may arise when one part of the brain, acting as the subject (front) looks upon another part as its object (the back) and evaluates or reflects upon its activity 8. However Neurological evidence indicates that neither sensory inputs nor motor outputs are needed to generate consciousness.When watching an engrossing movie, we become so immersed that we may lose the sense of self, the inner voice. 9. Neural Correlates of Consciousness (NCC)The minimal neuronal mechanisms jointly sufficient for any one specific conscious perceptImplies neural structures and neural activity patterns underlie consciousness.Phenomenology= Subjective Experiences 10. NCC for Subjective StatesEvery phenomenal, subjective state will have an associated NCC.State N1 of system N is a neural correlate of phenomenal propertyP if N's being in N1 directly correlates with the subject experiencing P. 11. Neural activity patterns as NCCSustained ActivityNeural activity may contribute to consciousness only if it is sustainedfor a minimum period of time, perhaps around a few hundred ms.Re-entrant ActivityAwareness of a stimulus happens because of the occurrence of a reentrant wave of activity from higher to lower cortical areas.SynchronizationConsciousness may require the synchronization, at a fine temporal scale, of large populations of neuronsdistributed over many cortical areas 12. Two Main Aspects of ConsciousnessThe Quantity or Levelof ConsciousnessConditions that determine to what extent a system has consciousness.The Quality or Contentof ConsciousnessConditions that determine what kind of consciousness a system has.How redisyourred? 13. Integrated Information give Experiences their Subjective flavourWhen somebody smells chocolate the effect that it has on their brain is integrated across many aspects of their memory.An olfactory experience is not localised to any one part of the brainThey are instead widely dispersed and inextricably intertwined with all the rest of the persons memories.This unique integration of a stimulus with existing memories is what gives experiences their subjective (i.e. observer specific) flavour.Is Consciousness Computable? Quantifying Integrated Information Using Algorithmic Information Theory, Phil Maguire, Philippe Moser, Department of Computer ScienceNUI Maynooth, Ireland, Rebecca Maguire, School of Business, National College of Ireland, IFSC, Dublin 1, Ireland, Virgil Griffith, Computation and Neural Systems, Caltech, Pasadena, California 14. A Top-Down Approach works better!Starting from the brain how it could possibly give rise to experience, the problemmay indeed be impossible to solve.Instead Start from consciousness identify its essential properties what kinds of physical mechanismsaccount for the properties 15. Integrated Information Theory (IIT)of ConsciousnessIIT starts from Phenomenologyand tries to give a Mathematical expressionto the fundamental properties of Experience.According to the theory, the most important property of consciousness is that it is extraordinarily informative.Classically, the reduction of uncertainty among a number of alternatives constitutesinformation. 16. Motivation ExamplesWhen a human identifies a smell as chocolate they are generating a response which distinguishes between 10,000 possible states, yielding 210,000 = 13.3 bits of information. vsA photodiode enters one of its two possible alternative states onA human facing it enters one out of an extraordinarily large number of possible statesThe photodiode's repertoire is minimally differentiatedEntropy measure:The average amount of information contained in each message drawn from a distribution or data stream. Entropy characterizes our uncertainty about our source of information. 17. -Measure of integrated informationA measure of integrated information called , quantifying the reduction of uncertaintywhen a system enters a particular state through causal interactions among its partsThe parts should be chosen in such a way that they can account for as much non-integrated (independent) information as possible. 18. How to measure ? Take a SystemConsider a neural system.Each element could be a cortical minicolumnImagine the system is disconnected from external inputs, like the brain is virtually disconnected from the environment when dreaming. 19. How to measure ? MethodologyConsider asubset S of elements + diagram of causal interactions among themHow to measure the information generated when S enters a particular state from causal interactions within the system?Divide S into two complementary parts A and B, and evaluate the responses of B that can be caused by all possible inputs from A. 20. Effective information (EI)Measuring EI(AB):Inject maximum entropy Hmaxinto the outgoing connections from AMeasure the entropy of the states of B that is due to the input from AEI for the bipartition:EI(A B) = EI(AB) + EI(BA). 21. Minimum Information Bipartition (MIB)Subset S = {1,2,3,4}Horizontal bipartition {1,3}/{2,4} yields a positive value of EIBipartition {1,2}/{3,4} yields EI = 0 (min information bipartition -MIB)Other bipartitions of subset S have EI > 0 22. Analysis of ComplexesConsider all subsets of system X, identify its complexes and rank them by the respective values of value of EI for their MIBAssume other elements in X are disconnected, observe > 0 for subset {3,4} and {1,2}Subsets {3,4} and {1,2} not part of a larger subset having higher , and constitute complexes 23. Quantity of ConsciousnessThe level of consciousness of a physical system is related to the repertoire of causal states available to the system as a wholeThe quantityof consciousness is determined by the capacity to integrate information, which can be measured as the value of a complex of elements is defined as the amount of causally effective informationthat can be exchanged across the minimum information bipartitionof a complex (its informational weakest link). A complex is a subset of elements with > 0 and no inclusive subset of higher . 24. Information Integration Architecturea. Functional Specialization and IntegrationHeterogeneous arrangement of the incoming and outgoing connections:Each element is connected to a different subset of elements, with different weights.b. No functional SpecializationThe same amount of connectivity, distributed homogeneously to eliminate functional specialization,Yields a complex with much lower values of ( = 20 bits)c. No functional Specialization or IntegrationReduction of information integration through loss of integration 25. Brain Comprising of ComplexesThe brain is likely to contain more than one complex, many small ones with low values, and perhaps a few large onesAt any given time in the brain, there is a complex of comparatively much higher , which we call the main complex .The complex, and not its elements, is the locus of consciousness. 26. All bipartitionsare indicated by listing one part (subset A) on the upper row and the complementary part (subset B) on the lower row.In between are values of effective information from A to B and from B to A for each bipartition.Effective Information Matrix of a ComplexComplex 1Complex 2 27. Qualia as Effective Information Matrix & Quality of ConsciousnessThe effective information matrix defines the set of informational relationships, or "qualia space" for each complex.This relational space is sufficient to specify the quality of conscious experience.The qualia space specifies the probability of past and future states of the system. 28. State diagram for Complexes & Quale5 representative states of a complex, each represented by 4 elementsAssume the 5 states evolve in time due to intrinsic dynamics of the system or due to inputs from the environmentLast 4 columns:special states corresponding to activation of one element at a time, correspond most closely to the specific "quale" / quality contributed by that particular element in its corresponding complex.Active ElementsInactive ElementsComplex 1Complex 2 29. Quale & Conscious ExperienceThese highly selective states represent the closest approximation to experiencing that element's specific contribution to consciousness its quality or "quale".A conscious experienceis specified by th