A ReviewinProgress by David Batten

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Causality and Complexity in Adaptive Neural
Systems

• A Review-in-Progress by David Batten
• CSIRO, Australia

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Goal and Method

• To explore and review the concepts of causality
  and complexity in brain research and cognition
• From the perspective of a complex systems
  scientist only vaguely familiar with advances in
  neuroscience
• Making use of
• Published papers and books in neuroscience and in
  related fields (e.g. psychology,
  psychophysiology, etc.)
• Special issues of leading journals (e.g. the 2006
  special issue of the International Journal of
  Psychophysiology on the Quiet Revolutions in
  Neuroscience)
• Important Conferences (e.g. the Brain Network
  Dynamics Conference at UC Berkeley in honour of
  Walter Freemans 80th Birthday, 2007)
• In order to better understand, and perhaps
  eventually to better model, causal and influence
  networks that evolve within the human brain ?
  human aspirations

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What is Consciousness?

• According to Walter Freeman, the pertinent
  questions are
• How and in what senses does consciousness cause
  the functions of our brains and bodies?
• How do brain and body functions cause
  consciousness?
• How do actions cause perceptions?
• How do perceptions cause awareness?
• How do states of awareness cause actions?
• Analysis of causality is a necessary step towards
  a better comprehension of consciousness
• The types of answers depend on the choice among
  meanings that are assigned to the word cause
• linear causality
• circular causality
• non-causal interrelationships

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Linear Causality of the Observer
Source Walter Freeman (1999)
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Linear Causality in Action

• A stimulus Sn initiates a chain of events
  including
• Activation of receptors
• Transmission by serial synapses to cortex
• Integration with memory
• Selection of a motor pattern
• Descending transmission to motor neurons
• Activation of muscles
• At nodes along the chain, awareness occurs, and
  meaning and emotion are attached to the response
• Temporal sequencing is crucial no effect can
  precede or occur simultaneously with its cause
• At some instant, each effect becomes a cause
• This conceptualization is inherently limited,
  because awareness cannot be defined at a point in
  time.

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Circular Causality of the Self
real time
death
Source Walter Freeman (1999)
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Circular Causality in Action

• The double dot shows a point moving
  counterclockwise on a trajectory idealized as a
  circle, showing that an event exists as a state
  through a period of inner time, which we reduce
  to a point in real time.
• Stimuli from the outside world impinge on this
  state.
• So also do stimuli arising from the
  self-organizing, interactive dynamics within the
  brain.
• Most stimuli are ineffective, but occasionally
  one does succeed as a "hit" on the brain state,
  and a response occurs.
• The impact and motor action are followed by a
  change in brain structure that begins a new
  orbit.
• So, changing our (state of) mind changes the
  neural structure of our brains

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Circular Causality Systemic Causality?

• A succession of orbits can be conceived as a
  cylinder with its axis in real time, extending
  from birth to death in an individual and its
  brain
• Trajectories in inner time may be viewed as
  fusing past and future into an extended present
  by way of state transitions
• Circular causality expresses the interrelations
  between levels in a hierarchy
• A top-down macroscopic state simultaneously
  influences its microscopic elements, and
• The microscopic elements create and sustain the
  macroscopic state from the bottom up
• The circular and hierarchical relationship
  between such microscopic and macroscopic entities
  is essential for explaining brains also lasers
  (see Haken, 1983).

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Some of Freemans Conclusions

• Awareness cannot be explained by linear causality
• Intentionality cannot be explained by linear
  causality
• Interactions between microscopic and macroscopic
  domains of the brain accord with the laws of
  self-organization
• Circular causality in a self-organizing brain is
  a concept that is useful to describe interactions
  between microscopic neurons in assemblies and the
  macroscopic emergent state variable that
  organizes them.
• New methods are needed to explain how all those
  neurons simultaneously get together in a virtual
  instant switch from one harmonious pattern to
  another in an orderly dance!
• A surprisingly similar pattern switching holds
  for
• the excitation of atoms in a laser to produce
  light (Haken)
• the metamorphosis of caterpillars into
  butterflies
• the inflammatory spread of epidemics or
  behavioural fads

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New Method 1 S-O and Synergetics

• Synergetics and self-organization of brain
  function and cognition (Haken, Kelso, Freeman,
  Lewis)
• Circular causality describes bidirectional
  causation between different levels of a system
  (Haken, 1977). Maurice Merleau-Ponty introduced
  the concept, claiming that every action and every
  sensation is both a cause and an effect.
• Brain dynamics is governed by an adaptive order
  parameter that regulates everywhere neocortical
  mean neural firing rates at the microscopic
  level, finding expression in the maintenance of a
  global state of self-organized criticality
  (Freeman, 2004)
• The concept of circular causality should be
  discarded (Bakker)
• Circular causality suggests an interaction
  between separable entities that does not exist.
• The micro-macro relationship is one of
  correspondence rather than causation

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New Method 2 Attractor Neural Networks

• Hopfield introduced the general concept of an
  attractor neural network (ANN)
• In his 1982 paper on neural networks as physical
  systems with emergent computational abilities, he
  defined an associative memory model based on
  formal neurons ? the first mathematical
  formalisation of Hebbs ideas and proposals on
  the neural assembly, the learning rule, the role
  of connectivity in the assembly and the neural
  dynamics.
• ANNs are being used to confirm the hypothesis
  that a collective phenomenon is at the origin of
  our memory function (Amit and others).
• Important associated concepts are
• Synaptic plasticity based on Hebbian rules
• Continuous ANNs

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New Method 3 Causal Networks

• Neurons engage in causal interactions with one
  another (self-organization) and with the
  surrounding body and environment (adaptation)
• Neural systems can thus be analyzed in terms of
  causal networks, without assumptions about info
  processing
• e.g. using Granger causality graph theory
• A neurobiotic model of the hippocampus
  surrounding area identified shifting causal
  pathways during learning of a spatial navigation
  task
• Selection of specific causal pathways causal
  cores
• Causal network approach may help to characterise
  the complex neural dynamics underlying
  consciousness
• Causal density as a candidate measure of neural
  complexity
• The Neurosciences Institute Seth, Edelman,
  Tononi

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Distinguishing Causal Interactions (Seth)
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Granger Causality

• Clive Granger Nobel prizewinner in economics
  for his work in econometrics on time-series
  analysis
• Granger causality is a method for determining
  whether one time series is useful in forecasting
  another
• Ordinarily, regressions reflect "mere"
  correlations, but Granger argued that there is an
  interpretation of a set of tests that can reveal
  something useful about causality.
• Statistical, not physical
• Causality can be unidirectional or reciprocal
• Many extensions to suit neurodynamics
• e.g. Multivariate Granger causality
• e.g. Nonlinear Granger causality
• Granger causality interactions can
• be represented as a directed graph

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Lakoff on Frames and Metaphors

• Frames are mental models of limited scope
• e.g. our traditional frame for war includes
  semantic roles like nations at war, leaders,
  armies with soldiers and commanders, weapons,
  attacks, battlefields, etc.
• Such frames metaphors (e.g. nerves of steel)
  in our brain define our common sense
• Human thinking in frames and metaphors gives rise
  to inferences that dont fit the laws of logic or
  deductive rationality as e.g. economists have
  formulated them
• Because facts matter, undistorted framing is
  needed to communicate the truth about our
  economic, social and political realities
• Differing worldviews or aspirations often lead to
  the proliferation of distorted frames and
  metaphors

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Two Competing Worldviews

• There may be as many worldviews as human beings?
• In the social sciences, a few worldviews crop up
  time and again
• Sheep and Explorers (in traffic)
• Imitators and Innovators (in technology)
• Cartesians and Stochasts (in fishing strategies)
• Conservatives and Progressives (in politics)
• They correspond to 2 extremes in terms of
  risk-taking behaviour or creativity
• Lakoff 2 parenting models ? 2 worldviews
• Strict father model ? Conservatives ? Linear
  Causality
• Nurturant parent model ? Progressives ? Systemic
  Causality
• Many people retain active versions of both models
  in different parts of their brain, and use them
  in different parts of their lives

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Conclusions for our Workshop series

• Causality and complexity have been discussed at
  length by scholars in the field of neuroscience
• especially linear versus circular circularity
• especially with respect to neural nets and causal
  networks
• Thus it could be worth focusing on neuroscience
  as a subtheme at one of our workshops
• At the forefront of causality discussions have
  been
• Walter Freeman, UC Berkeley
• Hermann Haken, U of Stuttgart
• Anil Seth, U of Sussex
• Steve Bressler, Florida Atlantic U
• Several scholars at The Neurosciences Institute,
  San Diego
• Several others could be worth our attention
• e.g. George Lakoff, UC Berkeley

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Thank you
Dr. David Batten CSIRO, Australia Phone 61
3 9239 4420 Email david.batten_at_csiro.au
Thank you!
Contact UsPhone 1300 363 400 or 61 3 9545
2176Email Enquiries_at_csiro.au Web www.csiro.au
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Three Worldviews

• Individualism
• Reduce all social constructs to collections of
  individuals (micro, no emergence)
• There is no such thing as society Thatcher
• Holism
• Structure dominates composition (macro, no
  emergence)
• Any society does not consist of individuals but
  expresses the sum of relationships and
  conditions that the individual actor is
  forming Marx
• Systemism
• Model entities by composition, environment,
  structure and mechanism (micro and micro,
  emergence)
• Systemism makes room for both agency and
  structure Bugne

Source Alex Ryan (2007)
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What is a System?

• Interdisciplinary concept with 2 core influences
• Emergence and Hierarchy (General Systems Theory)
• Communication and Control (Cybernetics)

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Contemporary Systems Approaches