Transcript CIN_W4_Presentation_Thu_Batten

Sources: David Lagnado and Anil Seth
Causality and Complexity in Adaptive
Neural Systems
Workshop on “Causality in Complex Systems”, ISC-PIF, Paris, 25-27 November 2009
Question 8 – Changing our minds?
• When we change our mind about something, how
does it change the physical structure of our brains?
• Could the mental process of “changing one’s mind”
correspond to the physical process of switching
between attractors in our brain?
• Is brain dynamics governed by an adaptive order
parameter that finds expression in the maintenance
of a global state of self-organized criticality?
• Would a complex systems perspective centred on
self-organizing, attractor neural networks be helpful in
ordering our thinking about how internal psychic and
neurodynamic processes lead us to reason and
behave in one way or another?
My 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 Freeman’s
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
What is Consciousness?
• According to 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
Some of Freeman’s 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 kind of 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
Combination of “New” Methods?
Self-Organisation
and Synergetics
Causal Networks
Attractor Neural
Networks
Something else?
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 MerleauPonty 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 or
association rather than causation
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 Hebb’s ideas and
proposals on the neural assembly, the learning rule, the role
of connectivity in the assembly and the neural dynamics.
• Attractor neural networks 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
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
Conclusions re our Workshop series
• Causality and complexity have been discussed at length
by several scholars in the field of neuroscience
• especially linear versus circular circularity
• especially with respect to neural nets and causal networks
• At the forefront of causality discussions have been:
•
•
•
•
•
•
Walter Freeman, UC Berkeley
Hermann Haken, U of Stuttgart
Steve Bressler, Florida Atlantic U – accepted
Anil Seth, U of Sussex – accepted for Paris workshop
Several scholars at The Neurosciences Institute (San Diego)
George Lakoff, UC Berkeley
• All the above have been invited to join us
Thank you
Dr. David Batten
CSIRO, Australia
Phone:
Email:
+61 3 9239 4420
[email protected]
Thank you!
Contact Us
Phone: 1300 363 400 or +61 3 9545 2176
Email: [email protected] Web: www.csiro.au