Introduction
·
cognitive neuropsychology :
study of relation between structure and function of the bresin and specific cognitive functions .
·
neuesl communication :
-sinusoidal
time oscillation
input action potentials membrane potential depokrizes hyperpolarizes
6
n e u ro n : ove r -
or
·
signal : membrane polential of post-synaptic n e u ro n
changes in function of received input -
frequency rok of signal change
·
phose
:
·
112 :
completing full cycle in one second electrophysical changes s re connected
N 23
frequency 2 other kind of
·
components >
-
, implitude , phose to changes
Implitude
frequency spectrum frequencies
·
messured of
:
range
filtering attenuating excluding certain of messured frequency
·
: or port spectrum
of signal component moment time
·
spechrogram :
strength each of each in
·
clustering : n e u ro n s of similar functional properties give m o re svenged signal in m o re n o n i nva s i ve methods .
·
temporal resolution : smallest unit of time that can be differentialed by a method.
·
spatial resolution smallest unit of which be resolved
space
:
can
hemodynamic
·
i nva s i ve n e ss :
majority of methods eller fully i nva s i ve or not ot all
, excilstory inhibitor
EEG -tracking of time of stages with EPSPs IPSPs
-
ms
course
precision
electroencephalography signed n e u ro n s - stronger EEG
-
·
electrical electrical dipoles of pyramidal cells
m e a s u re s brain activity ,
postsynaptic potentials create
·
strong signal summed ove r
many similarly behoving and some oriented n e u ro n s
biological
~ provides
difference reference beselime Active Reference
scolp electrode electrode electrode
·
voltage between and non-cortical ,
Ground ,
(A - G) (R G)
·
electrode placement >
- He international 1 0.2 0 system
>
- - -
=
A -
R - noise in
high
·
resistance-
signal through shall and scolp conductive get to A end R reduced by G
>
-
common
·
to time that
sample Rate :
avologue EEG is
digitized have series represent voltage values. data analysis :
frequency fitting segmentation
·
Role of digitalization He Nyquist-Shommon samplingKeorem
sampling preprocessing -
in >
-
: noise , ,
·
slissing :
undersampling sample Role 2u fastest frequencies main
signal processing
-
·
AD level >
-
m o re levels ,
better representation statistical lesting repected ANOVA
>
N170 ,
MMN ,
N400 P6OO , ,
LPP
for
ERPs potentials thats re to negative-up plotting
·
: event-related ,
EEG changes time locked sensory ,
motor or
cognitive events look out
SIN of to ratio speak-to-pesh
·
rato-quality ERP i n c re a s e SIN i n c re a s e number of heids
i
,
M
O re s
continuous ability to stimulus
occurring brain
>
- between and response
m e s s u re m e ss u re
processes
r
o
early peaks =
sensory processing ; like peahs =
cognitive processing "
,
V > ~
2
combination of bose-to-peah
·
neural s o u rc e s
Speak Istency
frequency
·
Fourier transformation :
decompose signal in to components that make up original signal .
·
highest pesh for frequency with largest implitude in "power spectrum" m o re elphy power-less brain
activity
binding signals heists
·
gamms activity
>
-
problem no: sy needed
many
MVPA multivorisle
·
:
pottern analysis >
-
predict labels of stimuli based on EEG data
·
identify differences picked by Regular ERP analysis especially with unknown locus
up ,
·
cognitive neuropsychology :
study of relation between structure and function of the bresin and specific cognitive functions .
·
neuesl communication :
-sinusoidal
time oscillation
input action potentials membrane potential depokrizes hyperpolarizes
6
n e u ro n : ove r -
or
·
signal : membrane polential of post-synaptic n e u ro n
changes in function of received input -
frequency rok of signal change
·
phose
:
·
112 :
completing full cycle in one second electrophysical changes s re connected
N 23
frequency 2 other kind of
·
components >
-
, implitude , phose to changes
Implitude
frequency spectrum frequencies
·
messured of
:
range
filtering attenuating excluding certain of messured frequency
·
: or port spectrum
of signal component moment time
·
spechrogram :
strength each of each in
·
clustering : n e u ro n s of similar functional properties give m o re svenged signal in m o re n o n i nva s i ve methods .
·
temporal resolution : smallest unit of time that can be differentialed by a method.
·
spatial resolution smallest unit of which be resolved
space
:
can
hemodynamic
·
i nva s i ve n e ss :
majority of methods eller fully i nva s i ve or not ot all
, excilstory inhibitor
EEG -tracking of time of stages with EPSPs IPSPs
-
ms
course
precision
electroencephalography signed n e u ro n s - stronger EEG
-
·
electrical electrical dipoles of pyramidal cells
m e a s u re s brain activity ,
postsynaptic potentials create
·
strong signal summed ove r
many similarly behoving and some oriented n e u ro n s
biological
~ provides
difference reference beselime Active Reference
scolp electrode electrode electrode
·
voltage between and non-cortical ,
Ground ,
(A - G) (R G)
·
electrode placement >
- He international 1 0.2 0 system
>
- - -
=
A -
R - noise in
high
·
resistance-
signal through shall and scolp conductive get to A end R reduced by G
>
-
common
·
to time that
sample Rate :
avologue EEG is
digitized have series represent voltage values. data analysis :
frequency fitting segmentation
·
Role of digitalization He Nyquist-Shommon samplingKeorem
sampling preprocessing -
in >
-
: noise , ,
·
slissing :
undersampling sample Role 2u fastest frequencies main
signal processing
-
·
AD level >
-
m o re levels ,
better representation statistical lesting repected ANOVA
>
N170 ,
MMN ,
N400 P6OO , ,
LPP
for
ERPs potentials thats re to negative-up plotting
·
: event-related ,
EEG changes time locked sensory ,
motor or
cognitive events look out
SIN of to ratio speak-to-pesh
·
rato-quality ERP i n c re a s e SIN i n c re a s e number of heids
i
,
M
O re s
continuous ability to stimulus
occurring brain
>
- between and response
m e s s u re m e ss u re
processes
r
o
early peaks =
sensory processing ; like peahs =
cognitive processing "
,
V > ~
2
combination of bose-to-peah
·
neural s o u rc e s
Speak Istency
frequency
·
Fourier transformation :
decompose signal in to components that make up original signal .
·
highest pesh for frequency with largest implitude in "power spectrum" m o re elphy power-less brain
activity
binding signals heists
·
gamms activity
>
-
problem no: sy needed
many
MVPA multivorisle
·
:
pottern analysis >
-
predict labels of stimuli based on EEG data
·
identify differences picked by Regular ERP analysis especially with unknown locus
up ,
