Supported by NIMH
10 Hz Rhythms in the Brain:
Characterization and
Function
Mingzhou Ding
University of Florida
Outline
• Background
• Laminar organization of visual
alpha rhythm in awake-behaving
monkeys
• Somatosensory mu rhythm in
humans and its role in detection
of a weak stimulus
Part I: Background
Human α Rhythm
The α rhythm (7 to 13
Hz) is observed in EEG
over occipital-parietal
cortex
Early Studies
Berger, H. (1929). On the
electroencephalogram of man.
Arch Psychiatr Nervenkr, 11:
689-692
Adrian, E.D. and Matthews,
B.H.C. (1934). The Berger
rhythm potential changes from
the occipital lobes in man.
Brain, 57: 354-385
Human µ Rhythm
The µ rhythm (7 to 13
Hz) is observed in EEG
over sensorimotor cortex
Gastaut (1952)
Topographical Distribution of 10 Hz Power
9
2
Neural Generator
From Bear et al. (2007)
Thalamic Pacemaker Hypothesis
“…the rhythmic tendency is so much
stronger in the thalamus that this structure is
normally the pacemaker. The large degree of
thalamic control over the cortical alpha
rhythm advocates that studies on this rhythm
and the control of it should be directed
toward the thalamic mechanisms involved.”
Per Andersen and Sven A. Anderson
Physiological Basis of the Alpha Rhythm,1968
In Vitro Laminar Analysis
Silva et al. (1991)
Bursting L5 Pyramidal Cells
From Bear et al. (2007)
Spike to Wave Transformation
From Speckmann and Elger (1999)
Rhythmic Bursting and Field Oscillation
100 ms
Part II: Laminar Organization of
Alpha in Visual Cortices of
Awake-behaving Macaques
J Neurosci, 2008
Primate Visual System
Description of Dataset
Monkeys were trained to
perform an auditory
discrimination task. Local
field potential (LFP) and
multiunit activity (MUA)
were recorded with linear
depth electrodes in V2, V4
and inferotemporal cortex
(IT).
Analysis Methods
• Current source density (CSD):
Identifying extracellular current
generators
• CSD and MUA coherence: Identifying
current generators with the potential for
pacemaking
• Granger causality spectra: Identifying
local pacemaker in lieu of the in vitro
trisection method
Alpha Oscillation in V4
Alpha current generators are located in IG, G and SG layers
Laminar Interaction in V4
SG
G
IG
Alpha Oscillation in V2
Alpha current generators are located in IG, G and SG layers
Laminar Interaction in V2
SG
G
IG
Alpha Oscillation in IT
Alpha current generators are located only in IG and SG layers
Pyramidal Neuron Morphology
Elston, G.N. (2002), Journal of Neurocytology 31, 317–335
Laminar Interaction in IT
SG
G
Power
SG IG
SGIG
IGSG
IG
Summary
V4
V2
IT
SG
SG
SG
G
G
G
IG
IG
IG
Canonical Circuit
Part III: Role of µ Rhythm in
Perception of a Weak
Stimulus
J Cogn Neurosci, in press
The Paradigm
Near threshold electrical pulse was delivered to the
Index finger. Subjects pushed a button upon
sensing the stimulation. EEG data were recorded
with a 128 channel BioSemi system.
Behavioral Data
Sensorimotor µ Rhythm
The µ rhythm (7 to 13 Hz)
µ and Stimulus Detection: Inverted U Function
Possible Physiological Mechanisms
• Spontaneous oscillations reflect a depolarizing drive on
principle cells. Input-related release of glutamate, when
coupled with episodes of µ, leads to more vigorous
activation. Thus, the absence or very low levels of µ
activity may fail to bring local neuron populations closer
to firing threshold, resulting in weak subsequent sensory
evoked response.
• Reduced sensory evoked response in the presence of
excessive levels of spontaneous oscillations may be
caused by (1) short-term depression of excitatory
synapses by depletion of synaptic vesicles or (2)
increased inhibitory synaptic influences by activation of
a subset of GABAergic interneurons surrounding the
excitatory neuronal populations.
PFC Control
For the
perceived
stimulus there
is an increased
prestimulus
drive from the
prefrontal
cortex to the
somatosensory
area
PFCSI and µ
PFCSI drive appears to enable the right mix of
local excitation and inhibition that is conducive to
optimized sensory processing
Evoked N1 and Sensory Awareness
µ and Evoked N1
µ and Evoked N1
PFCSI and Evoked N1
Summary
• Intermediate levels of ongoing mu
activity over SI prior to stimulus onset
are conducive to its detection and
perception.
• PFCSI drive provides a biasing
influence on SI that facilitates sensory
processing and improves behavioral
performance.
Collaborators
Monkey Study:
• Anil Bollimunta (UF/BME)
• Yonghong Chen (UF/BME)
• Charlie Schroeder (NKI and Columbia)
Human Study:
• Yan Zhang (UF/BME)
Current Source Analysis
Phase Realigned Averaging Technique
Granger Causality I
Given:
x1 , x2 ,..., xn ,...
y1 , y2 ,..., yn ,...
Linear prediction:
xn = a1 xn −1 + ... + am xn − m + ε n
xn = b1 xn −1 + ... + bk xn − k
+ c1 yn −1 + ... + ck yn − k + ηn
Granger Causality II
If
Var (ε n )
ln
>0
Var (ηn )
in some suitable statistical sense
we say y-series has causal
influence on x-series and represent
it by the symbol FY → X
Granger Causality Spectrum
Geweke (1982) found a spectral
representation of the time domain
Granger causality:
1
FY → X =
I
(
f
)
df
Y
→
X
∫
2π
IY → X ( f ) will be called Granger
causality spectrum.
Statistical Meaning
total power=intrinsic power +
causal power
I=ln(total power/intrinsic power)
Wold Decomposition
X (t ) = b0ε t + b1ε t −1 + ... + bnε t − n + ... = B( L)ε t
B ( L) X (t ) = ε t
−1
X (t ) + a1 X (t − 1) + a2 X (t − 2) + ... = ε t
X (t) + a1X (t −1) +... + am X (t − m) = εt
An indeterministic process can be
represented by an AR model.
MVAR Spectral Analysis
MultiVariate AutoRegressive Models:
X(t ) + A(1) X(t − 1) + A(2) X(t − 2) + ... + A( p) X(t − p) = E(t )
X(t ) ≡ [ x1 (t ), x2 (t ),..., xM (t )]T
X( f ) = H( f )E( f )
E(t ) ≡ N (0, Σ)

− ik 2 π f 
H ( f ) =  ∑ A (k )e

 k =0

p
S( f ) = H ( f ) Σ H* ( f )
−1
Spectral Measures
Power Spectrum: degree of
synchrony in a local population.
Γm ( f ) = Smm ( f )
Pairwise Measures:
Coherence Spectrum:
degree of linear dependence
between two channels at f.
Granger Causality:
Directional influence from
one channel to another.
| Smn ( f ) |2
Cmn ( f ) =
Smm ( f ) Snn ( f )
Σ122
2
(Σ22 − ) H12( f )
Σ11
I2→1( f ) =−ln(1−
)
S11( f )