Reaction time in cognitive tasks in relation to age
Kotsavasiloglou C., Nousi Α., Baloyannis S.
Abstract
Processing speed is an age depended property of the brain functionality. There is a decline
of the processing speed with the advance of the age in healthy subjects. Many diseases
affect the reaction time of patients in various cognitive tasks as well. The aim of this study
was the quantitative assessment of the reaction time in various stimuli in healthy people in
relation with the age. In order to investigate this quantitative aspect of specific brain areas,
a set of cognitive tasks was created, with the use of a software tool. Seventy four subjects
were divided in three groups based on the age limits of 40 and 60 years old. The findings
showed statistically significant differences of the reaction time in almost all of the under
investigation parameters between the groups. The use of this tool which measures the
reaction time in cognitive tasks may be very useful in the evaluation of the progression of
the decline of the cognitive performances in subjects with mild cognitive impairment.
KeyWords : ageing, reaction time, cognitive functions
Introduction
The daily human cognitive behavior is a very complicated procedure. The human brain
accomplishes its high level cognitive faculties integrating elementary informations. The results of
these information processes are elaborated according to internal algorithms. In normal
conditions when a person communicates with another a lot of elementary neuronal connections
are activated in milliseconds in various contiguous and not contiguous areas of the brain. For the
investigation of a complex cognitive task a reasonable approach is to find the elementary
cognitive tasks which compose it. For every elementary cognitive task, the investigation must be
oriented both to the qualitative and the quantitative aspects of this task. During a conversation
between two persons the person who hears must translate the changes in the physical sound to
phonemes, the phonemes to words and the words to meanings. The same is valid in the case of
a person which reads a book. The person must translate the optical properties of the content of
a page in words and then must translate these words to meanings. In the first case sounds are
the “medium” that carries the information and the translation is held in the brain area specialized
for the sound’s perception in the temporal lobe. In the second case, light is the “medium” that
carries the information and the translation is held in another brain area specialized in the
elaboration of the images which is located in the occipital lobe. The localization of the brain
areas specialized to the elaboration of a specific type of information and the pattern of its
activation, are examples of qualitative aspects of investigation. A quantitative aspect of an
elementary cognitive function is the time a brain area takes, to accomplish a specific function.
1
Both aspects are useful in combination. The pattern of activation of a brain area or the time that
area takes to complete an elementary task, are parameters which allow us to investigate the
limits between the normal and the pathologic state.
An indirect index of the processing speed of a specific brain area is the reaction time to various
stimuli wich activates this area.
The human brain as a complex dynamic system which interacts continuously with the
environment receives flows of information. All these information are elaborated and responses to
the environment are generated. The responses to the environment are based on the purposes of
the person and are modulated by emotional factors. An external stimulus which is considered by
a person as a threat generates a very intense and rapid response. Other parameters which
influence reaction times are personality traits. Personality traits modulates response times
allocating attentional resources (Hainaut, 2005). On the other hand in depressed individual the
reaction time is longer than in normal persons. Depressed individuals were slow to name the
emotionality of positive information and displayed greater sustained processing in the negative
aspects of the information (Siegle, ).
Compared to normal controls, the AD and depressive patients exhibited a signifcantly impaired
performance in manual motor coordination discrimination reaction time and visual patternmatching tasks. This suggests that these patients are handicapped by deficient basic operational
functions and central information processing depression in the elderly (HOFMAN)
In normal conditions there is a statistical range of Reaction times for every elementary cognitive
task. This range of Reaction times (RT) is related to the age. It is well known from empirical
observations that the RT of a person to external stimuli is proportional to the age. Data from
investigations using evoked potentials suggests a sensorimotor slowing with aging and with task
complexity (Yordanova, 2004). In more complicated procedures where semantic and gender
priming was investigated, longer reaction times were registered during the tasks performed by
the elderly group (Manenti, 2004) The age is not the only factor which affects processing speed.
Many diseases of the CNS have more or less significant impact on the reaction times depending
on their state. In patients with mild cognitive disorders the reaction times are longer than old
aged persons when performing the same tasks (Ritchie, 2001). Brain pathology which affects
performances in processing speed, involves cortical and subcortical brain areas. The smallvessel disease contributes to cognitive decline by affecting processing speed and executive
function (Prins, 2005). In other studies that investigates White matter hyperintesities (WMHs)
and cognitive functions an increase in processing time for various tests like the Stroop test is
recorded (Soderlund).
WMLs are related to impairment of cognitive functions, in particular those that involve a speed
component (de Groot,).
2
Processing speed is the most substantial area of cognitive impairment in subjects suffering from
CADASIL
(Cerebral
autosomal
dominant
arteriopathy
with
subcortical
infarcts
and
leukoencefalopathy) (Peters 2005).
The RT evaluation is an important index of all the levels of the brain functionality. The knowledge
of a quantitative relation between the age and the RT is valuable in defining the limits of the
normal and the pathological response in relation to the age. There is no one specific RT for the
brain as a hole. Each brain function has its own RT index which is related with the age. Various
methods and procedures are used by different research groups for the investigation of the
processing speed in various cognitive and not cognitive tasks.
The last 20 years researchers have been dealing with various aspects of the brain functionality
using computers. The computers promoted the research not just as number elaborating
machines but as tools for creating sophisticated models and interfaces. In this paper we use a
software tool developed in our clinic for the evaluation of the cognitive functions. One set of tests
of this software tool is oriented to the measurement of the reaction time in various stimuli.
The aim of this study was the quantitative assessment of the RT in various stimuli in relation to
the age in healthy people and people without any pathological condition involving directly the
brain.
Methods
Subjects
Seventy five subjects participated in this study. All these persons were either healthy or had
diseases that not affect directly the brain functions. The subjects with a disease were five. Four
of them had well controlled Hypertension under treatment and one had Diabetes type II under
treatment. One of the subjects (72 years old) with hypertension was operated 9 years ago after
an ischemic heart attack (triple bypass). During the tests the systolic and diastolic blood
pressure and the glycemia levels were normal. None of the subjects suffered from any form of
depression. All subjects of the third group had a detailed neurological examination with normal
findings.
The subjects were divided in three groups based on age. Group A had 41 persons with age
between 20 and 39 years old. Group B had 23 subjects with age between 40 and 59 years old.
Group C there were 9 persons over 60 years old. The persons of the third group had a lower
educational level. The possible implications of this parameter in the analysis of the data are
discussed in the Conclusion section of this paper.
Table 1 shows more analytical data about the groups.
3
Table 1.
Groups
Group A
Group B
Group C
Age
Number
Mean age
20 – 39
40 – 59
60 - 80
41
23
9
31,65
47,25
69,15
Standard
deviation
4,42
5,2
6,14
All subjects agreed to participate in this study after a detailed explanation of the procedure and
the scope. The five subjects with a specific pathology, but in a very good mental status, where
included because in the elderly people some pathology is the rule and not the exception. Of
course, many of the diseases of the elderly, affect indirectly the brain and this is a factor to keep
in mind when discussing the results.
Procedure
For the evaluation of the RT we used a software tool developed in our clinic. This software tool
comprises a specific battery of tests for the measurement of the time of reaction in specific
stimuli. This battery consists of 5 tests. In all tests (except the first) the subjects respond to the
apparition of a specific visual stimulus on the screen of a computer by hitting a button. The
subject can use its right or its left hand. In this paper the data are from the use of the “dominant”
hand. In all tests (except for the first preliminary test) there is an elementary sequence of an
“Apparition of a stimulus” and a “Response of the subject”. This elementary sequence lasts a
mean time of 3 seconds. A mean time of 3 seconds separates two elementary sequences. Every
test comprises 20 elementary sequences. The time counter starts with the apparition of the
stimulus and stops when the subject hits the button.
In the first preliminary test the subject pushes the “ENTER” button of a computer keyboard
rapidly many times. The computer stores the time in milliseconds between two hits. This test
serves as a baseline reference.
In the second test the subject hits the same button every time a red full colored circle (0.7 mm of
diameter) appears in random positions on the screen in random time intervals. The random
positions of the object on the screen in all tests were chosen for keeping the attention of the
subject.
In the third test there are two circles, a red and a green one and the subject must hit the button
only when the green circle appears on the screen. These two circles alternate randomly on the
screen. The circle appears 20 times with the green one appearing no less than 7.
In the fourth test the subject sees on the screen two words alternating each other randomly one
at a time. The subject must hit the button only if one of the two words appears on the screen.
These two words are phonetically similar and consist of three syllables. They have in common
the first and the third syllable and they differ in the second syllable. The two words appear 20
times with the target word appearing no less than 7.
4
The last test is more complex. In the screen appears randomly in random positions one of 10
words at a time. Five of these words mean “PAST” and five means “FUTURE”. The subject must
hit the button when in the screen appears a word meaning “PAST”. The word appears 20 times.
Words meaning “PAST” appear no less than 8 times.
For every person for every test and for every single response the software stored each reaction
time separately. The times were measured in milliseconds. They were short for the first test and
increased gradually seeking the maximum measured time in the last test.
In the third and the forth test the exclusion criteria was the 10% of wrong choices.
The measured parameters for every test are:
0. Basic hit time (BHT): It was used to measure the time of the physical movement of the finger
hit on the button and the eye fixation movements on the screen.
1. Reaction Time for one color (RT1C): This parameter was calculated in a 2 phase process. For
every subject the mean value of the BHT was subtracted from the mean value of the measures
of the second test. The mean value for every group was calculated from these resulting values.
2. Reaction Time for the recognition of one color between two colors (RT2C): This parameter
was calculated in a 2 phase process. For every subject the mean value of the BHT was
subtracted from the mean value of the measures of the third test. The mean value for every
group was calculated from these resulting values.
3. Reaction Time for the recognition of a word among two similar words (RTW): This parameter
was calculated in a 2 phase process. For every subject the mean value of the BHT was
subtracted from the mean value of the measures of the forth test. The mean value for every
group was calculated from these resulting values.
4. Reaction Time for the perception of the meaning of a word (RTM): This parameter was
calculated in a 2 phase process. For every subject the mean value of the BHT was subtracted
from the mean value of the measures of the fifth test. The mean value for every group was
calculated from these resulting values.
The data from the 3 groups, collected by the computer, were compared according to the
following three combinations. 1) Group A versus group B. 2) Group B versus group C. 3) Group
A versus group C. These comparisons between the three age periods for the above mentioned
parameters offer a good evaluation of the decline of the performances in relation to the age.
For the statistical evaluation the Independent Samples t-Test were used. For the statistically
significant difference the Levene’s test for Equality of variances was considered. The statistically
significant difference was evaluated at 0.05 and 0.01.
5
Results
Group analysis
Table 2.
Reaction Time for one color (RT1C)
Groups
A
B
C
Subjects Mean
Std.
(msec)
Deviation
41
128.21
75.43
24
195.16
91.45
9
238.33
114.25
Std. Error Mean
11.78
18.66
38.08
Comparisons
Group A – Group B
Group A – Group C
Group B – Group C
P < 0.05
P < 0.05
No diff.
In the test “Reaction time for one color” the subject must find the target shape that appears in
random positions on the screen. This test revealed statistically significant difference between the
first and second group and between the first and the third group. The comparison among the
second and the third group revealed no difference. The results for this test may suggest that there
is a significant decline around the age of 40 years old that is followed by a normal decline.
Table 3.
Reaction Time for the recognition of one color among two colors (RT2C)
Groups
A
B
C
Subjects Mean
Std.
Std. Error
(msec)
Deviation Mean
41
207.65
89.28
13.94
23
263.13
92.76
19.34
9
344.55
145.82
48.60
Comparisons
Group A – Group B
Group A – Group C
Group B – Group C
P < 0.05
P < 0.05
No diff.
In the next test (Reaction Time for the recognition of a color among two colors) the subject must
find the target shape on the screen and then press the button if the shape is green. The results
from this test are similar to the results of the previous test. This means that the reactions times for
the discrimination of the two colors follow the same rules as the test for one color. There is a
greater reaction time in the test for the recognition of one color among two randomly appearing
colors. This greater reaction time is due to the additional brain neuronal processes for the
selection of the green color.
Table 4.
Reaction Time for the recognition of a word among two similar words (RTW):
Groups
TEST 3
A
B
C
Comparisons
Subjects Mean
(msec)
41
384.21
24
572.66
8
908.50
Std.
Deviation
107.13
154.68
247.99
6
Std. Error
Mean
16.73
31.57
87.68
Group A – Group B
Group A – Group C
Group B – Group C
P < 0.01
P < 0.01
P < 0.05
As in the previous test the subject must perform two sequential sub processes. The first is to find
the target word that appears randomly on the screen and the second is the identification of the
target word. The first sub procedure involves the same brain structures for the fixation of a target
as in the previous tests. The second sub process involves the brain areas for the word recognition.
In this test the absolute reaction times are greater than the previous two tests. This suggests that
the neural substrate for the word elaboration is more complex from the neural substrate for the
recognition of the colors. Therefore it demands more time. Another observation in this test is that
there is a relation among the complexity of the neuronal connections and the level of the statically
significant differences. In this test the differences are clearer (p<0.01). There are two cut off
points. The first is around 40 year’s old age and the second is around 60 years old age.
Table 5.
Reaction Time for the perception of the meaning of a word (RTM)
Groups
TEST 4
A
B
C
Subjects Mean
40
23
7
Std.
Std. Error
Deviation Mean
521.87
192.30
30.40
715.08
220.16
45.90
936.28
173.95
65.74
Comparisons
Group A – Group B
Group A – Group C
Group B – Group C
P < 0.01
P < 0.01
P < 0.05
The last test is more complex. The subject must perform three sequential sub processes. The first
is to fixate the eyes on the word that appears randomly on the screen. The second is the
identification of the word and the third is the assignment of the meaning in that word. The area
responsible for the identification of the word is strictly connected to another adjacent area in the
posterior portion of the temporal lobe that gives a meaning to that word. The activation of this
area demand more time and therefore the reaction times registered are longer.
The performance differences between the three groups are statistically significant.
In order to clarify the influence of the hypertension and diabetes on the performances of the third
group we performed a statistical analysis between the persons of the Group C dividing them in
two subgroups. The first subgroup comprised the persons with a known pathology and the second
the healthy remains. There was no statistically significant difference between the two subgroups.
The number of the subjects was small and therefore this issue must be further evaluated.
7
Correlation analysis
For the evaluation of a probable statistical correlation among the age and the performances for
every test for all subjects, the Pearson correlation coefficient was calculated. The results are
shown in the next table.
Table 6.
Correlation of the age and the performances for all subjects.
Test 1
Number of subjects
Pearson Correlation
P < 001
75
0.401
Test 2
Number of subjects
Pearson Correlation
P < 001
73
0.389
Test 3
Number of subjects
Pearson Correlation
P < 001
74
0.704
Test 4
Number of subjects
Pearson Correlation
P < 001
71
0.497
These findings suggest a direct relation between the age and the performances of the subjects.
They also corroborate the results of the comparisons among the groups. The groups represents
periods of age. The statistically significant differences between the groups are differences of
performances among periods of age.
Conclusions
In this paper we investigate the quantitative aspects of 4 specific cognitive tasks in relation to the
age. These tasks investigate mainly optical areas of the brain. The last task investigates the time
of perception of the meaning of a word. Therefore investigates the functionality of the brain area
that assigns to “optical” words their meaning.
There is a question to be discussed. The educational level of the third group is lower than the
educational levels of the other two groups. May this difference in the educational level have an
influence on the reaction times of the subjects of the third group, when they perform the last two
tasks? To respond to this question we must consider in what way the education of a person may
influence their performances. The education may affect the performances mainly in two ways.
8
The first is the frequency of the use of words of the test and the second is the frequency of the use
of this specific brain area by the person.
In the third task the person had to react hitting the “Enter” button in the apparition of a specific
word. There were only two words alternating randomly. These words were of common use.
In the forth task the subjects response were oriented to the classification of a series of words
based on their meaning. The target concept was “PAST” and the stimuli was common words as
“Yesterday”, “Tomorrow”, “After”, in Greek. We think that the educational level has little
influence on the performances of this task because of the use of simple common words. In papers
were the education was evaluated in relation to the progression of cognitive deficits the results
suggested more a greater ‘cognitive reserve capacity’ in highly educated subjects than a true
protective effect of education against Alzheimer’s disease (Amieva 2005). Nevertheless the
educational level is a parameter to be farther evaluated.
Another aspect to be discussed is the presence of hypertension and diabetes in five persons of the
third group. None of these subjects had any clinical evidence involving the central nervous
system. This is a conclusion based on a detailed clinical examination and an accurate anamnesis.
The statistical analysis performed in the two subgroups (Subjects with no disease versus subjects
with hypertension and diabetes) of the group C revealed no statistically significant difference.
The sample size is considered small and therefore this result is not very reliable.
Apart from this result the question remains. To what extend hypertension and diabetes affects the
performances in the tests? Various studies have shown an association between elevated blood
pressure and white matter lesions (De Leeuw, 1999). White matter lesions are correlated with
lower performances in various cognitive tests in subjects with Cerebral small vessel disease and
multiple sclerosis. Therefore some degree of negative influence exists. These persons were
included in the third group because the presence of these two diseases is common in the elderly.
The first aim of this work was the quantification of the response times to specific stimuli in order
to have an objective evaluation. This was achieved by setting up a procedure with the use of a
software tool.
The second aim was the definition of the age limits with abrupt decline of the performances. The
age limits of 40 and 60 years old, were chosen after evaluation of the results of various
combinations of comparisons of age limits. We think that these age limits needs farther
evaluation with more subjects.
The findings suggest that for the specific tasks the reaction times are increasing with the age.
There are statistically significant differences between the groups in almost all the tasks.
9
In the first tests the reaction time to one colored shape (red), appearing randomly on the screen on
casual positions is evaluated. Of course this test does not evaluate the time of recognition of the
red color because the subject reacts to the apparition of an object that happens to be red. In the
same test when other colors were used, there where no statistically significant difference. This
means that the subject’s reaction time is not depended by the color of the projected object.
In the second test two colored (red, green) shapes alternates randomly on the screen. The subject
must hit the button when the green one appears. This is a test for the evaluation of the green color
recognition time. The subject must first recognize the green color and then hit the button. The
reaction times registered was greater from those of the previous test. This time difference is
expected because the selection of the right color demands the involvement of a specific brain area
in the occipital lobe for the color recognition.
The third test involves again the occipital lobe. Between two randomly appearing words on the
screen the subject must select one. The times we registered in this third test were greater than
those of the previous one. An indirect conclusion is that the brain area for the recognition of the
words is more complicated in some way. It is logical to suppose that the number of neurons and
the number of synapses for every elementary volume unit are statistically similar in the area of
color recognition and the brain area of the reading. Therefore the greater response time in this test
may suggest a longer signal path which corresponds to an extended elaborative brain area
involving the occipitoparietal area of the cortex. This seems quite expected. In the recognition of
a color the brain has to identify a simple information pattern, a specific wave length, which is
repeated in all the elementary points that compose the shape. In the case of the words in the
reading area of the brain, the work of the neural network is the identification of a specific
sequence of letters. But every letter has its own identity and its own specific characteristics. The
elementary units that compose every word are different and therefore more neurons and synapses
are required.
In the last test the subject must hit the button when the word that appears randomly on the screen
has a specific meaning. The reaction times registered in this test were longer than those of the
previous test. This is an expected finding as well. This task involves the same reading area as in
the previous test but the signal is propagated to a neiberhood area between occipital and temporal
lobe. The function of this brain area is the extraction of the meaning of the words. The signal path
is longer and therefore the reaction time is longer.
The utility of the quantification of the various cognitive elementary tasks is quite obvious. Every
elementary task is accomplished by a specific brain area. The identification of statistically
constant reaction times for every elementary task, allows us to investigate the dysfunction states
10
of the brain. In the last years the incidence of people with impairment of their cognitive functions
is increasing in time. It is well known that the brain can mask its small areas of dysfunction for
long periods of time. It is known that
Degenerative diseases like Alzheimer disease are
characterized by low performances in various cognitive tasks many years before their onset
(Amieva 2005).
For a more accurate classification of preclinical states of Degenerative diseases like Alzheimer
disease the term Mild cognitive impairment (MCI) has been proposed (Flicker 1991, Petersen
1999). The identification of a preclinical situation like MCI is very important because gives a
possibility of intervention in delaying the progression of the disease.
In the present study the diagnostic method we used was sensible in detecting the differences in
the processing speed in specific cognitive tasks in subjects with age from 20 to 80 years old. This
means that may detect decline in performances before all criteria for MCI is fulfilled.
The tests we present here are a first approach. They need further elaboration and larger groups of
subjects for an objective set up of reaction times.
11
References
The 9 year cognitive decline before dementia of the Alzheimer type: a prospective
population-based study.
Helene Amieva,1 Helene Jacqmin-Gadda,2 Jean-Marc Orgogozo,1,3 Nicolas Le Carret,1 Catherine
Helmer,1 Luc Letenneur,1 Pascale Barberger-Gateau,1 Colette Fabrigoule1 and Jean-Francois
Dartigues
Brain (2005), 128, 1093–1101
Mild cognitive impairment: clinical characterization and outcome.
Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E
Arch Neurol. 1999 Mar;56(3):303-8.
Mild cognitive impairment in the elderly: predictors of dementia.
Flicker C, Ferris SH, Reisberg B.
Neurology. 1991 Jul;41(7):1006-9.
A Follow-Up Study of Blood Pressure and Cerebral White Matter Lesions
Frank-Erik de Leeuw, MD,*† Jan Cees de Groot, MD,* Matthijs Oudkerk, MD,‡
Jacqueline C. M. Witteman, PhD,* Albert Hofman, MD,* Jan van Gijn, FRCPE,†
and Monique M. B. Breteler, MD*
Annals of Neurology Vol 46 No 6 December 1999
ALZHEIMER'S DISEASE, DEPRESSION AND NORMAL AGEING: MERIT OF
SIMPLE PSYCHOMOTOR AND VISUOSPATIAL TASKS
MARC HOFMAN, ERICH SEIFRITZ, KURT KRAÈ UCHI, CHRISTOPH HOCK, HARALD
HAMPEL, ALEXANDRA NEUGEBAUER AND FRANZ MUÈ LLER-SPAHN
Int. J. Geriat. Psychiatry 15, 31±39 (2000)
Cerebral small-vessel disease and decline in information processing speed, executive
function and memory
Niels D. Prins, Ewoud J. van Dijk, Tom den Heijer, Sarah E. Vermeer, Jellemer Jolles,
Peter J. Koudstaal, Albert Hofman and Monique M. B. Breteler
Brain (2005), 128, 2034–2041
Cerebral changes on MRI and cognitive function: The CASCADE study
Hedvig Soderlund a,b,., Lars-Goran Nilsson b, Klaus Berger c, Monique M. Breteler d,
Carole Dufouil e, Rebecca Fuhrer f,1, Simona Giampaoli g, Albert Hofmand, Andrzej Pajak h,
Maria de Ridder d, Susana Sans i, Reinhold Schmidt j, Lenore J. Launer k
Neurobiology of Aging 27 (2006) 16–23
Cerebral White Matter Lesions and Cognitive Function: The Rotterdam Scan Study
Jan Cees de Groot, MD,* Frank-Erik de Leeuw, MD,*† Matthijs Oudkerk, MD,‡ Jan van Gijn,
FRCPE,† Albert Hofman, MD,* Jellemer Jolles, PhD,§ and Monique M. B. Breteler, MD*
Annals of Neurology Vol 47 No 2 February 2000
12
Classification criteria for mild cognitive impairment. A population-based validation study
Karen Ritchie, PhD; Sylvaine Artero, MA; and Jacques Touchon, MD
NEUROLOGY 2001;56:37–42
The effects of ageing and Alzheimer’s disease on semantic and gender priming
Rosa Manenti, Claudia Repetto, Simone Bentrovato, Alessandra Marcone, Elizabeth Bates,
and Stefano F. Cappa1
Brain (2004), 127, 2299–2306
Moderate state-anxiety differently modulates visual and auditory
response times in normal- and very low trait-anxiety subjects
J.-P. Hainaut, B. Bolmont .
Neurosci Lett. 2005 Nov 17
Periventricular Cerebral White Matter Lesions Predict Rate of Cognitive Decline
Jan Cees de Groot, MD, Frank-Erik de Leeuw, MD, Matthijs Oudkerk, MD, Jan van Gijn,
FRCPE, Albert Hofman, MD, Jellemer Jolles, PhD, and Monique M. B. Breteler, MD1
Ann Neurol 2002;52:335–341
Sensorimotor slowing with ageing is mediated by a functional dysregulation of motorgeneration processes: evidence from high-resolution event-related potentials
Juliana Yordanova, Vasil Kolev, Joachim Hohnsbein and Michael Falkenstein
Brain (2004), 127, 351±362
The Pattern of Cognitive Performance in CADASIL: A Monogenic Condition Leading to
Subcortical Ischemic Vascular Dementia
Nils Peters, M.D., Christian Opherk, M.D., Adrian Danek, M.D., Clive Ballard, M.D., Jürgen
Herzog, M.D., Martin Dichgans, M.D.
Am J Psychiatry 2005; 162:2078–2085)
13