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The clinical and basic significance of studying
fluctuations of brain coordinated activity
Physiology characterised by not-so-regular rhythms
(L. Glass, Synchronization and rhythmic processes in physiology, Nature 410, 2001)
Physiology characterised by not-so-regular rhythms
(L. Glass, Synchronization and rhythmic processes in physiology, Nature 410, 2001)
Fluctuations due to external input and intrinsic factors – Allow for a ―full
search‖ of the state space ― crucial effects near phase transitions (dynamical
bifurcations) Adaptability
―Noise during rest enables the exploration of the brain‘s dynamic
repertoire‖ (Ghosh et al., PLoS Comp. Biol. 4, 2008)
Low variability in physiological records associated
with disease many times reported
-Tidal volume variability decreases associated with breathing pathologies
-Hormonal secretion variability reduced in acute and chronic illness
- Heart rate variability has been shown to decrease in: cardiac disease
and post-traumatic stress disorder; schizophrenia; panic disorder;
diabetes
Cardiac transplant patients: lower heart rate variability that
increases with time (Koskinen et al., 1996; Chiu et al., 2004)
Sympathetic nerve activity variability is absent in severe heart
failure (van de Borne et al., 1997)
pre- seizure post-
With regards to nervous systems…
The nature of the problem
Coordinated activity integration and segregation
pre- seizure post-
The nature of the problem
Existence of flexible formation of neural activity patterns requires
TRANSIENT COORDINATION…
Too much/too little synchronised activity not too optimal for
information processing…
Existence of flexible formation of neural activity patterns requires
TRANSIENT COORDINATION…
FLUCTUATIONS IN COORDINATED ACTIVITY
Erich Von Holst’s (1908-1962) RELATIVE COORDINATION
Too much/too little synchronised activity not too optimal for
information processing…
• Either directly interacting networks
OR
• Interaction via a third network
What is measured as Brain Coordinated Activity?
Extracted from macroscopic recordings (EEG, MEG, intracerebral). Main
activity recorded is synaptic transmission. The sensors pick up (mostly)
cortical activity that reflects:
Regardless of which type, fluctuations in phase synchrony reflect a re-arrangement of coordination Relative Coordination
Order parameter: captures the macroscopic behaviour resulting
from microscopic fluctuations, thus, they allow for a description of
the dynamics using few variables.
As an index of brain coordinated activity…
Order parameter: captures the macroscopic behaviour resulting
from microscopic fluctuations, thus, they allow for a description of
the dynamics using few variables.
Differences in the oscillating phase: phase relations between
oscillating cell groups establish flexible functional coordination of
activities and dynamic coupling to allow for integration and
segregation of networks needed to process information.
As an index of brain coordinated activity…
The activity of one cell acquires ‗meaning‘ as it relates to other cells‘ activities.
―...one needs to study neurons as members of large ensembles that are constantly
disappearing and arising through their cooperative interactions and in which every neuron
has multiple and changing responses in a context-dependent manner‖
F.J. Varela, E. Thompson, E. Rosch, The Embodied Mind, MIT Press, 1991
X1 X2
X1
X2
Phase synchronization of brain waves
Filter
In phase locking Out-of phase
Analyse phase synchrony
Very basics of phase synchrony analysis
Analytic signal concept (Gabor, 1946)
Synchrony index )( ieR
S index (Surrogates when necessary)
Synchrony index: already a representation of variability in relative
phase
-Variability as S.D. …but
dt
d
- ―Entropy‖ of phase differences
- Rate of fluctuations in phase
differences
SD1 = SD2
R
Fluctuations of phase differences:
- Spatial variability of the phase synchrony pattern
A measure of the spatial heterogeneity (Garcia Dominguez et al., 2008)
Can less fluctuations of phase synchronization be
associated with disease?
Spatio-temporal fluctuations in cortical coordination
patterns associated with cognition and pathologies:
- Epilepsy
- Autism
- Traumatic brain injury
- Cardiac arrest/stroke
“Normal” neurophysiologic fluctuations
Fluctuations in synaptic activity enhance reliability of neuronal spike firing (Mainen & Sejnowski, Science,
1995); correlated variability in spike firing improves accuracy of neural population codes (Abbott &
Dayan, 1999)
Fluctuations in cell activity in sensory cortices determine perceptual judgments/binocular rivalry (Deco
& Romo, Trends Neurosci., 2008)
Fluctuations (reduction) of phase synchronization in brain activity correlate with the subjective
experience of visual recognition (Perez Velazquez et al., J. Biol. Phys., 2007)
Variability in brain signals increased with development and is associated with less behavioural
variability (McIntosh et al., PLoS Comp. Biol., 2008)
Spontaneous fluctuations in brain activity measured with neuroimaging or
electrophysiological methods (Fox & Raichle, Nat. Rev. Neurosci. 2007); fluctuations in
baseline fMRI or MEG signals related to subsequent perceptual responses (Palva et
al., J. Neurosci., 2005; Boly et al., Hum. Brain Mapp., 2008; Busch et al., J. Neurosci, 2009); variability in
evoked responses resulting from ongoing baseline fluctuations (Arieli et al., Science
1996); similar collective states in spontaneous and evoked activity (Tsodyks et al., Science
1999)
etc… etc… etc…
Many origins of fluctuations in the nervous system:
-From outside— Environmental input arrival at sensory terminals
-From inside — Ion channel opening & closing
— Neuronal membrane potential near threshold
— Poisson-like spike firing
— Synaptic potential arrival at dendrites
Spatio-temporal fluctuations in phase synchronization
during seizures
-Spatial ―complexity‖ of
the coordination pattern
diminishes during ictal
events time
pre- seizure post-
(Garcia Dominguez et al., 2008)
Spatio-temporal fluctuations in phase synchronization
during seizures
time
-Temporal variability of
the phase difference
Seizure
Rate of fluctuations in phase difference in
intracerebral recordings (amygdala)
pre- seizure post-
dt
d
time
-Spatial ―complexity‖ of
the coordination pattern
diminishes during ictal
events (Garcia Dominguez et al., 2008)
J.L. Perez Velazquez, L. Garcia Dominguez, R. Wennberg, The fluctuating brain: dynamics of neuronal activity, in
Nonlinear Phenomena Research Perspectives, (C.W. Wang, ed.) pp. 417-444, Nova Science Publishers, 2007
Fluctuations of phase difference, a precursor of seizures?
0.5
0.6
0.7
0.8
8 minR
0.4
0.01
0.02
0.03
unwrapped phase diff.
Flu
ctu
atio
ns
J.L. Perez Velazquez, L. Garcia Dominguez, V. Nenadovic, R. Wennberg (2011)
Experimental observation of increased fluctuations in an order parameter before epochs of extended brain
synchronization. Journal of Biological Physics 37, 141-152
Fluctuations of phase difference, a precursor of seizures?
MEG Intracranial
Fluctuations of phase difference, a precursor of highly
synchronised activity in general?
Hyperventilation-induced synchronous activity
J.L. Perez Velazquez, L. Garcia Dominguez, V. Nenadovic, R. Wennberg (2011)
Experimental observation of increased fluctuations in an order parameter before epochs of extended brain
synchronization. Journal of Biological Physics 37, 141-152
Hyperventilation
Bad outcome Good outcome
“Simpler” spatial coordination patterns associated with
traumatic brain injury (TBI) and cardiac arrest
TBI
Appearances are deceiving…
Introducing the determination of variability in
bedside brain monitoring
Patient A (PCPC = 1) Patient B (PCPC =4) Control Subject
Variable temporal pattern between synchronization (darkest red) and
desynchronization (darkest blue) among EEG channels for patients with good
outcome and control participants.
PCPC: Paediatric cerebral performance category score
Correlation between PCPC and synchrony magnitude
in TBI and cardiac arrest
-Lower temporal variability (SD) in cortical coordinated activity,
derived from EEG phase synchrony, associated with poor prognosis
after traumatic brain injury (Nenadovic et al., 2008)
- Decreased spatial ―complexity‖ of the spatial synchronization
patterns associated with worse outcome (PCPC) after cardiac arrest
in children (Nenadovic et al., 2009)
- Tendency towards lower spatial ―complexity‖ in patients who died
post-stroke/TBI/cardiac arrest.
-Less fluctuations (entropy) in inter-hemispheric phase differences
in coma.
Spatio-temporal fluctuations in phase synchronization
associated with traumatic brain injury/stroke
MLC11MLC12
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RF
RPLP
O
LF
The case of high parietal coordinated activity in autism
MLC11MLC12
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MLP11MLP12
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MLC11MLC12
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RF
RPLP
O
LF
The case of high parietal coordinated activity in autism
Changes in magnitude of synchrony between any two areas varies
with task performance
In ―controls‖
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The case of high parietal coordinated activity in autism
High intraparietal synchrony regardless of condition
In ASD
0.50 0.52 0.54 0.56 0.5820
30
40
50
60
70
80
90
100
Per
form
ance
ASDnon-ASD
Parietal synchrony relative to parieto-frontal synchrony
associated with task performance serves to ―classify‖ normal
or ASD individuals
0.50 0.52 0.54 0.56 0.5820
30
40
50
60
70
80
90
100
Per
form
ance
ASDnon-ASD
Georgopoulos et al., 2007
Parietal synchrony relative to parieto-frontal synchrony
associated with task performance serves to ―classify‖ normal
or ASD individuals
Cross-correlations from MEG
signals serves to classify patients
Our Summary of Variability in Brain Synchrony
Reduced spatio-temporal variability in
- seizures
- traumatic brain injury
- stroke and cardiac arrest
- autism
Parkinson‘s disease: enhanced tendency to synchronised activities in cortico-
thalamic areas and basal ganglia (EEG, MEG, intracerebral recordings in patients
and animals)
Schizophrenia: Increased bilateral coherence between auditory cortices during
auditory hallucinations (Sritharan et al., 2005); altered coordination dynamics (Breakspear et al., 2003, Spencer et al., 2003; Uhlhaas et al., 2006)
Chronic hypoxia in patients with obstructive sleep apnea syndrome: enhanced
global synchronization (Toth et al., 2009)
Depression: slower decay of long-range correlations in EEG signals (Lee et al.,
2007)
Alzheimer‘s disease: increased local synchronization (but loss of long-distance
coordination, Stam et al., 2006)
More evidence for higher brain synchronised activity
associated with disease
Time scales: -length of periods of high synchronization
-slow or fast time scale synchrony [Maximal information exchange when units sychronise in slow time scale and
desynchronise at fast (Baptista & Kurths, 2008)]
State dependency: behavioural context
Control parameters: - alterations in subcortical inputs
- alterations in excitability
Considerations on the high synchronized
activity associated with ―pathology‖
Long-lasting (several seconds):
Deviation/pathology Control/baseline
-Seizures: R>0.7 R<0.3
-ASD: R(intraparietal) >0.34 Non-ASD < 0.3
-Coma (post cardiac arrest) >0.6 R<0.52
-Coma-TBI (entropy of phase angles) S<2.15 S>2.17
-Hyperventilation: R>0.55 R<0.4
Relative bounds in magnitude of the synchrony index
Short-lasting (associated with task performance) :
ASD: R(Prefrontal) <0.28 Non-ASD >0.32
Bounds in the variability of brain coordinated
activity in health and disease?
Further questions
- How can physiological cycles work despite fluctuations? (Bounds
of variability?)
- How can cycles ―use‖ fluctuations to tune rhythms to changing
stimuli?
Further questions
- How can physiological cycles work despite fluctuations? (Bounds
of variability?)
- How can cycles ―use‖ fluctuations to tune rhythms to changing
stimuli?
Models of biochemical
cycles – the ‗inverted U‘
Models of biochemical
cycles – the ‗inverted U‘
Optimal information exchange
Info
rmat
ion e
xch
ang
e
Synchronization
Not too optimal
Further questions
- How can physiological cycles work despite fluctuations? (Bounds
of variability?)
- How can cycles ―use‖ fluctuations to tune rhythms to changing
stimuli?
More inverted Us…
Spatio-temporal patterns as expressions of the tendency to
maximal information exchange constrained by the conditions.
Tononi et al., 1998 ~Statistical complexity
(Crutchfield & Young
1989)
Complexity lies between order and disorder (Badii & Politi, 1997)
Coordination = Probability of interaction
Optimal information exchange
Info
rmat
ion e
xch
ang
e
Coordination
Information exchange ~ F(probability of interaction)
No segregation
No integration
P(int)=1
P(int)=0
Spatio-temporal patterns as expressions of the tendency to
maximal information exchange constrained by the conditions.
Not too optimal
!!
!
kNk
N
k
N
Nu
mb
er o
f k
ou
tco
mes
The easiest manner to obtain an inverted U: binomial coefficient
Number of combinations of k items that can be
selected from a set of N items
!!
!
kNk
N
k
N
Info
rmat
ion e
xch
ang
e
Coordination
Number of (k-element) arrangements of units exchanging
information from a set of N units − Does maximising the
number of configurations of units exchanging
information make the system more viable?
The easiest manner to obtain an inverted U: binomial coefficient
Optimal information exchange
