Mental chronometry is the use of response time in perceptual-motor
tasks to infer the content, duration, and temporal sequencing of
Mental chronometry is one of the core paradigms
of experimental and cognitive psychology, and has found application in
various disciplines including cognitive psychophysiology, cognitive
neuroscience, and behavioral neuroscience to elucidate mechanisms
underlying cognitive processing.
Mental chronometry is studied using measurements of reaction time
(RT), which is the elapsed time between the presentation of a sensory
stimulus and the subsequent behavioral response. In psychometric
psychology it is considered to be an index of processing speed.
That is, it indicates how fast the individual can execute the mental
operations needed by the task at hand. In turn, speed of processing is
considered an index of processing efficiency. The behavioral response
is typically a button press but can also be an eye movement, a vocal
response, or some other observable behavior. RT is constrained not
only by the speed of signal transmission in white matter, but also by
the properties of synaptic and neural processing in cortical gray
matter. Its utility as a dependent variable for drawing conclusions
about information processing is constrained by the experimental
design, measurement technology, and mathematical theorizing of the
2 Evolution of methodology
2.1 Galton and differential psychology
2.2 Donders' experiment
2.3 Hick's law
2.4 Sternberg's memory-scanning task
2.5 Shepard and Metzler's mental rotation task
2.6 Sentence-picture verification
2.7 Models of memory
2.8 Posner's letter matching studies
3 Cognitive development
4 Cognitive ability
5 Other factors
6 Application in biological psychology/cognitive neuroscience
7 See also
9 Further reading
10 External links
Reaction time (RT) is the time that elapses between a person being
presented with a stimulus and the person initiating a motor response
to the stimulus. It is usually on the order of 200 ms. The processes
that occur during this brief time enable the brain to perceive the
surrounding environment, identify an object of interest, decide an
action in response to the object, and issue a motor command to execute
the movement. These processes span the domains of perception and
movement, and involve perceptual decision making and motor
Response time is the sum of reaction time and movement time. Usually
the focus in research is on reaction time. There are four basic means
of measuring it:
Simple reaction time is the motion required for an observer to respond
to the presence of a stimulus. For example, a subject might be asked
to press a button as soon as a light or sound appears. Mean RT for
college-age individuals is about 160 milliseconds to detect an
auditory stimulus, and approximately 190 milliseconds to detect visual
stimulus. The mean reaction times for sprinters at the Beijing
Olympics were 166 ms for males and 189 ms for females, but in one out
of 1,000 starts they can achieve 109 ms and 121 ms, respectively.
Interestingly, this study also concluded that longer female reaction
times can be an artifact of the measurement method used, suggesting
that the starting block sensor system might overlook a female
false-start due to insufficient pressure on the pads. The authors
suggested compensating for this threshold would improve false-start
detection accuracy with female runners.
Recognition or go/no-go reaction time tasks require that the subject
press a button when one stimulus type appears and withhold a response
when another stimulus type appears. For example, the subject may have
to press the button when a green light appears and not respond when a
blue light appears.
Choice reaction time (CRT) tasks require distinct responses for each
possible class of stimulus. For example, the subject might be asked to
press one button if a red light appears and a different button if a
yellow light appears. The
Jensen box is an example of an instrument
designed to measure choice reaction time.
Discrimination reaction time involves comparing pairs of
simultaneously presented visual displays and then pressing one of two
buttons according to which display appears brighter, longer, heavier,
or greater in magnitude on some dimension of interest.
Due to momentary attentional lapses, there is a considerable amount of
variability in an individual's response time, which does not tend to
follow a normal (Gaussian) distribution. To control for this,
researchers typically require a subject to perform multiple trials,
from which a measure of the 'typical' or baseline response time can be
calculated. Taking the mean of the raw response time is rarely an
effective method of characterizing the typical response time, and
alternative approaches (such as modeling the entire response time
distribution) are often more appropriate.
Evolution of methodology
Galton and differential psychology
Francis Galton is typically credited as the founder of
differential psychology, which seeks to determine and explain the
mental differences between individuals. He was the first to use
rigorous reaction time tests with the express intention of determining
averages and ranges of individual differences in mental and behavioral
traits in humans. Galton hypothesized that differences in intelligence
would be reflected in variation of sensory discrimination and speed of
response to stimuli, and he built various machines to test different
measures of this, including reaction time to visual and auditory
stimuli. His tests involved a selection of over 10,000 men, women and
children from the London public.
The first scientist to measure reaction time in the laboratory was
Franciscus Donders (1869). Donders found that simple reaction time is
shorter than recognition reaction time, and that choice reaction time
is longer than both.
Donders also devised a subtraction method to analyze the time it took
for mental operations to take place. By subtracting simple reaction
time from choice reaction time, for example, it is possible to
calculate how much time is needed to make the connection.
This method provides a way to investigate the cognitive processes
underlying simple perceptual-motor tasks, and formed the basis of
Although Donders' work paved the way for future research in mental
chronometry tests, it was not without its drawbacks. His insertion
method, often referred to as "pure insertion", was based on the
assumption that inserting a particular complicating requirement into
an RT paradigm would not affect the other components of the test. This
assumption—that the incremental effect on RT was strictly
additive—was not able to hold up to later experimental tests, which
showed that the insertions were able to interact with other portions
of the RT paradigm. Despite this, Donders' theories are still of
interest and his ideas are still used in certain areas of psychology,
which now have the statistical tools to use them more accurately.
Main article: Hick's law
W. E. Hick (1952) devised a CRT experiment which presented a series of
nine tests in which there are n equally possible choices. The
experiment measured the subject's reaction time based on number of
possible choices during any given trial. Hick showed that the
individual's reaction time increased by a constant amount as a
function of available choices, or the "uncertainty" involved in which
reaction stimulus would appear next. Uncertainty is measured in
"bits", which are defined as the quantity of information that reduces
uncertainty by half in information theory. In Hick's experiment, the
reaction time is found to be a function of the binary logarithm of the
number of available choices (n). This phenomenon is called "Hick's
law" and is said to be a measure of the "rate of gain of information".
The law is usually expressed by the formula
displaystyle RT=a+blog _ 2 (n+1)
are constants representing the intercept and slope of the function,
is the number of alternatives. The
Jensen Box is a more recent
application of Hick's law.
Hick's law has interesting modern
applications in marketing, where restaurant menus and web interfaces
(among other things) take advantage of its principles in striving to
achieve speed and ease of use for the consumer.
Sternberg's memory-scanning task
Saul Sternberg (1966) devised an experiment wherein subjects were told
to remember a set of unique digits in short-term memory. Subjects were
then given a probe stimulus in the form of a digit from 0-9. The
subject then answered as quickly as possible whether the probe was in
the previous set of digits or not. The size of the initial set of
digits determined the reaction time of the subject. The idea is that
as the size of the set of digits increases the number of processes
that need to be completed before a decision can be made increases as
well. So if the subject has 4 items in short-term memory (STM), then
after encoding the information from the probe stimulus the subject
needs to compare the probe to each of the 4 items in memory and then
make a decision. If there were only 2 items in the initial set of
digits, then only 2 processes would be needed. The data from this
study found that for each additional item added to the set of digits,
about 38 milliseconds were added to the response time of the subject.
This supported the idea that a subject did a serial exhaustive search
through memory rather than a serial self-terminating search.
Sternberg (1969) developed a much-improved method for dividing
reaction time into successive or serial stages, called the additive
Shepard and Metzler's mental rotation task
Main article: Mental rotation
Shepard and Metzler (1971) presented a pair of three-dimensional
shapes that were identical or mirror-image versions of one another.
Reaction time to determine whether they were identical or not was a
linear function of the angular difference between their orientation,
whether in the picture plane or in depth. They concluded that the
observers performed a constant-rate mental rotation to align the two
objects so they could be compared. Cooper and Shepard (1973)
presented a letter or digit that was either normal or mirror-reversed,
and presented either upright or at angles of rotation in units of 60
degrees. The subject had to identify whether the stimulus was normal
or mirror-reversed. Response time increased roughly linearly as the
orientation of the letter deviated from upright (0 degrees) to
inverted (180 degrees), and then decreases again until it reaches 360
degrees. The authors concluded that the subjects mentally rotate the
image the shortest distance to upright, and then judge whether it is
normal or mirror-reversed.
Mental chronometry has been used in identifying some of the processes
associated with understanding a sentence. This type of research
typically revolves around the differences in processing 4 types of
sentences: true affirmative (TA), false affirmative (FA), false
negative (FN), and true negative (TN). A picture can be presented with
an associated sentence that falls into one of these 4 categories. The
subject then decides if the sentence matches the picture or does not.
The type of sentence determines how many processes need to be
performed before a decision can be made. According to the data from
Clark and Chase (1972) and Just and Carpenter (1971), the TA sentences
are the simplest and take the least time, than FA, FN, and TN
Models of memory
Hierarchical network models of memory were largely discarded due to
some findings related to mental chronometry. The TLC model proposed by
Collins and Quillian (1969) had a hierarchical structure indicating
that recall speed in memory should be based on the number of levels in
memory traversed in order to find the necessary information. But the
experimental results did not agree. For example, a subject will
reliably answer that a robin is a bird more quickly than he will
answer that an ostrich is a bird despite these questions accessing the
same two levels in memory. This led to the development of spreading
activation models of memory (e.g., Collins & Loftus, 1975),
wherein links in memory are not organized hierarchically but by
Posner's letter matching studies
Posner (1978) used a series of letter-matching studies to measure the
mental processing time of several tasks associated with recognition of
a pair of letters. The simplest task was the physical match task, in
which subjects were shown a pair of letters and had to identify
whether the two letters were physically identical or not. The next
task was the name match task where subjects had to identify whether
two letters had the same name. The task involving the most cognitive
processes was the rule match task in which subjects had to determine
whether the two letters presented both were vowels or not vowels.
The physical match task was the most simple; subjects had to encode
the letters, compare them to each other, and make a decision. When
doing the name match task subjects were forced to add a cognitive step
before making a decision: they had to search memory for the names of
the letters, and then compare those before deciding. In the rule based
task they had to also categorize the letters as either vowels or
consonants before making their choice. The time taken to perform the
rule match task was longer than the name match task which was longer
than the physical match task. Using the subtraction method
experimenters were able to determine the approximate amount of time
that it took for subjects to perform each of the cognitive processes
associated with each of these tasks.
Main article: Neo-Piagetian theories of cognitive development
There is extensive recent research using mental chronometry for the
study of cognitive development. Specifically, various measures of
speed of processing were used to examine changes in the speed of
information processing as a function of age. Kail (1991) showed that
speed of processing increases exponentially from early childhood to
early adulthood. Studies of reaction times in young children of
various ages are consistent with common observations of children
engaged in activities not typically associated with chronometry.
This includes speed of counting, reaching for things, repeating words,
and other developing vocal and motor skills that develop quickly in
growing children. Once reaching early maturity, there is then a
long period of stability until speed of processing begins declining
from middle age to senility (Salthouse, 2000). In fact, cognitive
slowing is considered a good index of broader changes in the
functioning of the brain and intelligence.
Demetriou and colleagues,
using various methods of measuring speed of processing, showed that it
is closely associated with changes in working memory and thought
(Demetriou, Mouyi, & Spanoudis, 2009). These relations are
extensively discussed in the neo-Piagetian theories of cognitive
During senescence, RT deteriorates (as does fluid intelligence), and
this deterioration is systematically associated with changes in many
other cognitive processes, such as executive functions, working
memory, and inferential processes. In the theory of Andreas
Demetriou, one of the neo-Piagetian theories of cognitive
development, change in speed of processing with age, as indicated by
decreasing reaction time, is one of the pivotal factors of cognitive
Researchers have reported medium-sized correlations between reaction
time and measures of intelligence: There is thus a tendency for
individuals with higher IQ to be faster on reaction time
Research into this link between mental speed and general intelligence
(perhaps first proposed by Charles Spearman) was re-popularised by
Arthur Jensen, and the "Choice reaction Apparatus" associated with his
name became a common standard tool in reaction time-IQ research.
The strength of the RT-IQ association is a subject of research.
Several studies have reported association between simple reaction time
and intelligence of around (r=−.31), with a tendency for larger
associations between choice reaction time and intelligence
(r=−.49). Much of the theoretical interest in reaction time was
driven by Hick's Law, relating the slope of reaction time increases to
the complexity of decision required (measured in units of uncertainty
Claude Shannon as the basis of information theory).
This promised to link intelligence directly to the resolution of
information even in very basic information tasks. There is some
support for a link between the slope of the reaction time curve and
intelligence, as long as reaction time is tightly controlled.
Standard deviations of reaction times have been found to be more
strongly correlated with measures of general intelligence (g) than
mean reaction times. The reaction times of low-g individuals are more
spread-out than those of high-g individuals.
The cause of the relationship is unclear. It may reflect more
efficient information processing, better attentional control, or the
integrity of neuronal processes.
Research has shown that reaction times may be improved by chewing gum:
"The results showed that chewing gum was associated with greater
alertness and a more positive mood. Reaction times were quicker in the
gum condition, and this effect became bigger as the task became more
Application in biological psychology/cognitive neuroscience
Regions of the Brain Involved in a Number Comparison Task Derived from
EEG and fMRI Studies. The regions represented correspond to those
showing effects of notation used for the numbers (pink and hatched),
distance from the test number (orange), choice of hand (red), and
errors (purple). Picture from the article: 'Timing the Brain: Mental
Chronometry as a Tool in Neuroscience'.
With the advent of the functional neuroimaging techniques of PET and
fMRI, psychologists started to modify their mental chronometry
paradigms for functional imaging (Posner, 2005). Although
psycho(physio)logists have been using electroencephalographic
measurements for decades, the images obtained with PET have attracted
great interest from other branches of neuroscience, popularizing
mental chronometry among a wider range of scientists in recent years.
The way that mental chronometry is utilized is by performing reaction
time based tasks which show through neuroimaging the parts of the
brain which are involved in the cognitive process.
With the invention of functional magnetic resonance imaging (fMRI),
techniques were used to measure activity through electrical
event-related potentials in a study when subjects were asked to
identify if a digit that was presented was above or below five.
According to Sternberg’s additive theory, each of the stages
involved in performing this task includes: encoding, comparing against
the stored representation for five, selecting a response, and then
checking for error in the response. The fMRI image presents the
specific locations where these stages are occurring in the brain while
performing this simple mental chronometry task.
In the 1980s, neuroimaging experiments allowed researchers to detect
the activity in localized brain areas by injecting radionuclides and
using positron emission tomography (PET) to detect them. Also, fMRI
was used which have detected the precise brain areas that are active
during mental chronometry tasks. Many studies have shown that there is
a small number of brain areas which are widely spread out which are
involved in performing these cognitive tasks.
Current medical reviews indicate that signaling through the dopamine
pathways originating in the ventral tegmental area is strongly
positively correlated with improved (shortened) reaction time;
e.g., dopaminergic pharmaceuticals like amphetamine have been shown to
expedite responses during interval timing, while dopamine antagonists
D2-type receptors) produce the opposite effect.
CDR computerized assessment system
Implicit association test
Movement in learning
Timed antagonistic response alethiometer
^ a b c d e Jensen, A. R. (2006). Clocking the mind: Mental
chronometry and individual differences. Amsterdam: Elsevier.
^ Kuang, S. (2017). "Is reaction time an index of white matter
connectivity during training?". Cognitive Neuroscience. 8: 126–128.
^ Luce, R.D. (1986). Response times: Their role in inferring
elementary mental organization. New York: Oxford University Press.
^ Wong, Aaron L.; Haith, Adrian M.; Krakauer, John W. (August 2015).
"Motor Planning". The Neuroscientist: A Review Journal Bringing
Neurobiology, Neurology and Psychiatry. 21 (4): 385–398.
doi:10.1177/1073858414541484. ISSN 1089-4098.
^ a b Kosinski, R. J. (2008). A literature review on reaction time,
Clemson University. Archived 2010-06-11 at the Wayback Machine.
^ Taoka, George T. (March 1989). "Brake Reaction Times of Unalerted
Drivers" (PDF). ITE Journal. 59 (3): 19–21.
^ Lipps, D.B.; Galecki, A.T.; Ashton-Miller, J.A. "On the Implications
of a Sex Difference in the Reaction Times of Sprinters at the Beijing
Olympics". PLoS ONE. 6 (10): e26141. Bibcode:2011PLoSO...626141L.
doi:10.1371/journal.pone.0026141. PMC 3198384 .
^  Whelan, R. (2008). Effective analysis of reaction time data. The
Psychological Record, 58, 475-482.
^ a b Donders, F.C. (1869). On the speed of mental processes. In W. G.
Attention and Performance II. Acta Psychologica, 30,
412-431. (Original work published in 1868.)
^ Hick's Law at Encyclopedia.com Originally from Colman, A. (2001). A
Dictionary of Psychology. Retrieved February 28, 2009.
^ W. Lidwell, K. Holden and J. Butler: Universal. Principles of
Design. Rockport, Gloucester, MA, 2003.
^ Sternberg, S. (1966). "High speed scanning in human memory".
Science. 153 (3736): 652–654. Bibcode:1966Sci...153..652S.
doi:10.1126/science.153.3736.652. PMID 5939936.
^ Sternberg, S. (1969). "The discovery of processing stages:
Extensions of Donders' method". Acta Psychologica. 30: 276–315.
^ Shepard, R.N.; Metzler, J. (1971). "
Mental rotation of
three-dimensional objects". Science. 171 (3972): 701–703.
^ Cooper, L. A., & Shepard, R. N. (1973). Chronometric studies of
the rotation of mental images. New York: Academic Press.
^ Clark, H. H.; Chase, W. G. (1972). "On the process of comparing
sentences against pictures". Cognitive Psychology. 3 (3): 472–517.
^ Just, M. A.; Carpenter, P. A. (1971). "Comprehension of negation
with quantification". Journal of Verbal Learning and Verbal Behavior.
10 (3): 244–253. doi:10.1016/S0022-5371(71)80051-8.
^ Collins, A. M.; Loftus, E. F. (1975). "A spreading activation theory
of semantic processing". Psychological Review. 82 (6): 407–428.
^ Collins, A. M.; Quillian, M. R. (1969). "Retrieval time from
semantic memory". Journal of Verbal Learning and Verbal Behavior. 8
(2): 240–247. doi:10.1016/S0022-5371(69)80069-1.
^ Posner, M. I. (1978). Chronometric explorations of mind. Hillsdale,
NJ: Erlbaum, 1978.
^ Kail, R. (1991). "Developmental functions for speed of processing
during childhood and adolescence". Psychological Bulletin. 109 (3):
490–501. doi:10.1037/0033-2909.109.3.490. PMID 2062981.
^ Case, Robbie (1985). Intellectual development: birth to adulthood.
Boston: Academic Press. ISBN 0-12-162880-9.
^ Salthouse, T. A. (2000). "Aging and measures of processing speed".
Biological Psychology. 54 (1–3): 35–54.
doi:10.1016/S0301-0511(00)00052-1. PMID 11035219.
^ a b Demetriou, A.; Mouyi, A.; Spanoudis, G. (2008). "Modeling the
structure and development of g". Intelligence. 36 (5): 437–454.
^ Demetriou, A., Mouyi, A., & Spanoudis, G. (2010). The
development of mental processing. Nesselroade, J. R. (2010). Methods
in the study of life-span human development: Issues and answers. In W.
F. Overton (Ed.), Biology, cognition and methods across the life-span.
Volume 1 of the Handbook of life-span development (pp. 36-55),
Editor-in-chief: R. M. Lerner. Hoboken, NJ: Wiley.
^ Deary, I. J.; Der, G.; Ford, G. (2001). "Reaction times and
intelligence differences: A population-based cohort study".
Intelligence. 29 (5): 389–399.
^ Bates, T. C.; Stough, C. (1998). "Improved Reaction
Information Processing Speed, and Intelligence". Intelligence. 26 (1):
^ van Ravenzwaaij, Don; Brown, Scott; Wagenmakers, Eric-Jan (2011).
"An integrated perspective on the relation between response speed and
intelligence" (PDF). Cognition. 119 (3): 381–93.
doi:10.1016/j.cognition.2011.02.002. PMID 21420077.
^ Smith, A. (2009). Effects of chewing gum on mood, learning, memory
and performance of an intelligence test. Nutritional Neuroscience,
^ Posner, Michael I. (2005). "Timing the Brain: Mental
a Tool in Neuroscience". PLoS Biology. 3 (2): e51.
doi:10.1371/journal.pbio.0030051. PMC 548951 .
^ Sternberg, S. (1975). "Memory scanning: New findings and current
controversies". Quarterly Journal of Experimental Psychology. 27:
^ a b Parker KL, Lamichhane D, Caetano MS, Narayanan NS (October
2013). "Executive dysfunction in Parkinson's disease and timing
deficits". Front. Integr. Neurosci. 7: 75.
doi:10.3389/fnint.2013.00075. PMC 3813949 . PMID 24198770.
The neurotransmitter dopamine is released from projections originating
in the midbrain. Manipulations of dopaminergic signaling profoundly
influence interval timing, leading to the hypothesis that dopamine
influences internal pacemaker, or "clock," activity (Maricq and
Church, 1983; Buhusi and Meck, 2005, 2009; Lake and Meck, 2013). For
instance, amphetamine, which increases concentrations of dopamine at
the synaptic cleft (Maricq and Church, 1983; Zetterström et al.,
1983) advances the start of responding during interval timing (Taylor
et al., 2007), whereas antagonists of D2 type dopamine receptors
typically slow timing (Drew et al., 2003; Lake and Meck,
2013). ... Depletion of dopamine in healthy volunteers impairs
timing (Coull et al., 2012), while amphetamine releases synaptic
dopamine and speeds up timing (Taylor et al., 2007).
Luce, R.D. (1986). Response Times: Their Role in Inferring Elementary
Mental Organization. New York: Oxford University Press.
Meyer, D.E.; Osman, A.M.; Irwin, D.E.; Yantis, S. (1988). "Modern
mental chronometry". Biological Psychology. 26 (1–3): 3–67.
doi:10.1016/0301-0511(88)90013-0. PMID 3061480.
Townsend, J.T.; Ashby, F.G. (1984). Stochastic Modeling of Elementary
Psychological Processes. Cambridge, UK: Cambridge University Press.
Weiss, V; Weiss, H (2003). "The golden mean as clock cycle of brain
waves". Chaos, Solitons and Fractals. 18 (4): 643–652.
Time Test - Measuring Mental
Chronometry on the Web
Historical Introduction to Cognitive Psychology
Timing the Brain: Mental
Chronometry as a Tool in Neuroscience
Sample Chronometric Test on the web
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