The Role of Rhythmic Activity in the Brain

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The Role of Rhythmic Activity in the Brain
and in Artificial Cognitive Systems
Mike Denham Roman Borisyuk, Centre for
Theoretical and Computational Neuroscience,
Plymouth Miles Whittington, School of Biomedical
Sciences, Leeds
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Rhythmic neural activity is ubiquitous in the
brain

• slow (lt1 Hz) oscillations in the thalamus during
  slow wave sleep
• 5-9 Hz theta rhythm in medial temporal lobe
  episodic memory-related areas
• 8-12 Hz alpha, 12-30 Hz beta and 30-80 Hz
  gamma rhythms in sensory and memory-related
  areas

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From Varela et al., 2001
Rhythms have multiple scales
Aa Synchrony between single units in monkey area
V1 b Local field potentials (LFPs) from eight
recording electrodes in the suprasylvian gyrus of
an awake cat. c Transient episodes of synchrony
within a population of neurons recorded
intracranially over the occipito-temporal
junction in an epileptic patient performing a
visual discrimination task. d When recorded from
a surface electrode, such synchronous patches
appear as spatial summation of cortical responses
that give rise to transient increases in the
gamma band. B Patches of local synchrony in
distant brain sites can enter into synchrony
during cognitive tasks. Black lines link
electrodes that are synchronous during the
perception of the face.
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Rhythmic activity appears to play a major role in
information processing in the brain
Object recognition
Feature extraction/abstraction
Associative learning
Selective attention
Novelty detection
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For example, the function of the gamma rhythm may
be to provide a framework for processing in the
temporal domain
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Quantisation
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Gating
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Combination
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Neural mechanisms involved in rhythmic activity
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Gamma is an INHIBITION-BASED rhythm
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Inhibition-based gamma recruits principal cells
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-55 mV
-55 mV
-70 mV
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Convergence and divergence of synaptic connections
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Theta rhythm may be generated in hippocampus and
reinforced through a dynamic inhibitory interplay
between the septum and the hippocampus, with
ascending brainstem activity controlling the
frequency of oscillation
Brainstem
Denham Borisyuk, 2000
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Mathematical model
We describe the inhibitory feedback circuit as a
Wilson-Cowan model of four coupled populations of
excitatory and inhibitory neurons in which the
parameters are set consistent with experimental
measurements of the dynamic responses of the
neuron types involved.
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Mathematical model
We compute the bifurcation diagrams for these
equations with respect to the value of the
external excitatory input to the septum
Boundaries correspond to the Andronov-Hopf
bifurcation a limit cycle appears if
parameters cross the boundary The natural
frequency of this oscillation is in the theta
range (approximately 6 Hz) and stays almost
constant under variation of the circuit
parameters.
OSCILLATIONS
OSCILLATIONS
OSCILLATIONS
OSCILLATIONS
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There is a great deal of experimental evidence
that rhythms in the brain play a significant role
in perception and cognition
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Theta and gamma rhythms are implicated in the
formation of new episodic memories

• intracranial recordings were made from 793
  cortical and subcortical sites in 10 epileptic
  patients undergoing invasive monitoring at the
  Childrens Hospital Boston
• the results revealed that significant increases
  in oscillatory power in theta and gamma bands
  during encoding were able to predict the
  subsequent recall of lists of common nouns
  (Sederberg et al, 2003)

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Theta rhythm is implicated in cognition function
Cognition-enhancing drugs produced a
dose-dependent increase in stimulated hippocampal
theta rhythm amplitude in rats, suggesting that
theta rhythm may be closely associated with
cognitive function (Kinney et al, 1999)
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EEG measurements of alpha and theta rhythms
appear to reflect cognitive performance

• Good cognitive performance is related to two
  types of EEG phenomena
• a tonic increase in alpha but a decrease in
  theta power, and
• a large phasic (event-related) decrease in
  alpha but increase in theta, depending on the
  type of memory demands.
• (Klimesch, 1999)

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There is evidence that beta (12-30 Hz) and gamma
(30-80 HZ) rhythms play a differential role in
synchronisation of neural activity
Experimental data indicates that gamma rhythms
are used for relatively local computations
whereas beta rhythms are used for higher level
interactions involving more distant structures
and longer conduction delays, corresponding to
signals travelling a significant distance in the
brain. Kopell et al, 2000.
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The role of alpha rhythm (8-12 Hz) in perception?
Is perception discrete or continuous ?
(VanRullen Koch, TICS, 2003)
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Perception of an event can be influenced by its
relation to the phase of the occipital EEG alpha
rhythm
From VanRullen Koch, 2003, adapted from Gho
Varela, 1988.
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However, contradictory to Kochs ideas, it would
appear that alpha rhythm is mostly present in
sensory areas AFTER a sensory event. For
example, EEG alpha is suppressed by opening the
eyes and with increased attentiveness (Vanni et
al, 1997)
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The role of the parietal-occipital alpha rhythm
may be increasing S/N ratios within cortex by
inhibition of unnecessary or conflicting stimuli
or processes
Alpha synchronisation (ERS) increases in foot
area when hand is activated and vice-versa
(Suffczynski et al, 2001)
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Gamma-theta interaction
From VanRullen Koch, 2003
(Lisman Idiart, 1995).
Hypothesis is that each period of the fast gamma
rhythm underlies a specific representation.
Gamma is superimposed on a slower rhythm (alpha
or theta) that effectively multiplexes the
representations This mechanism could explain how
the interactions between neuronal rhythms
participate in shaping the holding in short-term
(working) memory of perceptual events the fast
wave representations would constitute the
contents of each discrete snapshot, the entire
percept being mediated by the slow waves.
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Summary
The emergence of a unified cognitive moment
appears to rely on the temporal coordination of
scattered mosaics of functionally specialized
brain regions. The mechanisms of large-scale
integration that counterbalance the distributed
anatomical and functional organization of brain
activity and enable the emergence of coherent
behaviour and cognition are still largely
unknown The most plausible candidate appears to
be the formation of dynamic links mediated by
synchrony over multiple frequency bands. Varela
et al, Nature Reviews Neuroscience, 2003
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Future Research Agenda
Future computational architectures for cognitive
systems are similarly likely to involve spatially
distributed, functionally-specialised information
processing regions, like those in the brain, and
will similarly require mechanisms for
coordinating activity across these distributed
processes . The synchronisation of rhythmic
activity between distributed processes may be a
candidate mechanism to enable the efficient
operation of such architectures.
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Future Research Agenda

• To address this question it will be necessary to
  fully understand
• the neural mechanisms of rhythmic activity and
  synchronisation, both locally and across widely
  distributed regions,
• the interplay between slow and fast brain
  rhythms, and
• the role of synchronisation over different
  frequency bands.

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Future Research Agenda
It will also be necessary to understand how such
mechanisms might be implemented in future
computer hardware architectures This will require
the combined research efforts of several
disciplines experimental, theoretical and
computational neuroscience, computer science,
mathematics and cognitive neuropsychology
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Key questions

• How does the brain build a coherent perceptual
  account of a sensory event in the case that the
  component features of the event are processed
  asynchronously in widely distributed areas of the
  cortex?
• Is rhythmic activity fundamental to this process?
  
• Will future articifial sensory systems require
  similar mechanisms?

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Key questions

• Rhythmic activity is observed in regions of the
  brain strongly linked to memory storage and
  retrieval processes, in particular episodic
  memories.
• Does rhythmic activity play a role in the
  organisation, storage and retrieval of episodic
  memories, and if so, what role, eg "chunking" of
  individual perceptual/cognitive experiences into
  a complete "episode"?
• Does this have any impact on the way information
  composed of sequences of events might be
  stored/retrieved in future artificial cognitive
  systems?

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Key questions

• If future artificial cognitive systems employ
  "massively" distributed asynchronous processing
  hardware architectures, will they face the same
  problems as the brain in providing coherent
  behaviour?
• Is rhythmic, synchronised activity in the brain
  dependent on intrinsic neural mechanisms or is it
  an "emergent" behaviour of the brain resulting
  from inherent self-organising, adaptive
  processes?
• If so, would we expect to observe it as an
  emergent feature of any massively parallel,
  distributed self-organising computational
  architecture when it is required to deliver
  coherent behaviour?