APPLIED COGNITIVE PSYCHOLOGY
Appl. Cognit. Psychol. 13: 561±580 (1999)
Arctic Cognition: A Study of Cognitive Performance in
Summer and Winter at 698N
TIM BRENNEN*, MONICA MARTINUSSEN,
BERNT OLE HANSEN and ODIN HJEMDAL
University of Tromsù, Norway
SUMMARY
Evidence has accumulated over the past 15 years that a€ect in humans is cyclical. In winter
there is a tendency to depression, with remission in summer, and this e€ect is stronger at higher
latitudes. In order to determine whether human cognition is similarly rhythmical, this study
investigated the cognitive processes of 100 participants living at 698N. Participants were tested
in summer and winter on a range of cognitive tasks, including verbal memory, attention and
simple reaction time tasks. The seasonally counterbalanced design and the very northerly
latitude of this study provide optimal conditions for detecting impaired cognitive performance
in winter, and the conclusion is negative: of ®ve tasks with seasonal e€ects, four had
disadvantages in summer. Like the menstrual cycle, the circannual cycle appears to in¯uence
mood but not cognition. Copyright # 1999 John Wiley & Sons, Ltd.
There are three major astronomical cycles that have a period short enough to be
important in the study of behaviour. The ®rst is the 24-hour rotation of the Earth on
its axis, the second is the monthly rotation of the moon about the Earth and the third
is the 12-month orbit of the Earth around the Sun. While cognitive psychologists have
studied the daily cycle using time-of-day as an experimental variable (e.g. Smith,
1989) and the monthly cycle in particular in connection with studies of the menstrual
cycle (e.g. Richardson, 1991a), the annual cycles have been seldom studied from a
cognitive perspective.
An investigation of the e€ect of the seasons upon normal cognitive performance is
timely because evidence is accumulating of seasonal e€ects on the incidence of moodrelated problems. Rosenthal et al. (1984) named this disorder Seasonal A€ective
Disorder (SAD). People who su€er from this disorder have symptoms of depression
that only occur during one part of the year, but that recur from year to year. The vast
majority of SAD patients su€er in winter, with remission in summer, and frequently
reported symptoms include sadness, anxiety, irritation, decreased activity and libido,
leading both to social problems and diculty at work.
*Correspondence to: T. Brennen, Department of Psychology, University of Tromsù, 9037 Tromsù,
Norway. E-mail: Timb@psyk.uit.no
Contract
Contract
Contract
Contract
grant
grant
grant
grant
sponsor: Norwegian Research Council.
number: 114162/330.
sponsor: Nansenfondet, Den Norske Videnskaps-Akademi.
number: 24/97.
CCC 0888±4080/99/060561±20 $17.50
Copyright # 1999 John Wiley & Sons, Ltd.
Accepted 13 April 1999
562
T. Brennen et al.
It has since also been claimed that there exists a weaker version of SAD, called
subsyndromal SAD (sub-SAD), where people report season-related mood swings, but
to a level below clinical signi®cance (Kasper et al., 1989). The sub-SAD idea thus
introduces the notion that season-related swings constitute a normal aspect of human
mental life.
While the bulk of the research on SAD has been undertaken in the United States,
cases of SAD have been documented in other countries too, e.g. Iceland (Magnusson
and Stefansson, 1993) and Britain (Thompson and Isaacs, 1988). Research has
documented the disorder's incidence, and has attempted to pinpoint the biological
mechanisms by which it arises.
One area of consensus regarding SAD is that it is the relative lack of light in winter
that triggers the disorder. Two predictions from this hypothesized link between light
exposure and SAD have been tested. First, SAD should increase with increasing
latitude: places on the equator receive 12 hours of daylight and 12 hours of darkness,
every day of the year. Everywhere else on the planet the total annual amount of
daylight is roughly the same, but it is shared out unevenly over the year. Therefore the
further one goes from the equator, the greater the swing in day and night length, and
thus the prediction is that SAD will be more prevalent at higher latitudes due to the
relative lack of light in winter. Rosen et al. (1990) investigated this using a questionnaire study on populations at four latitudes ranging from 278 to 42.58N. There was a
correlation of 0.11 between latitude and SAD incidence, in the predicted direction.
Palinkas et al. (1996) investigated whether SAD incidence would increase among 70
people who spent a year on Antarctica. They administered two questionnaires twice,
once between three and four months before the Antarctic winter solstice and once one
to two months after it. The number of people found to be su€ering from sub-SAD
increased from seven to 19 over the Antarctic winter, and the number of people with
SAD went from nought to one. Thus spending a winter in the Antarctic increased
SAD symptoms.
Second, the e€ect of light therapy to relieve the SAD symptoms during the winter
months has been much investigated, initially by Rosenthal et al. (1984). A metaanalysis that included studies totalling 332 patients showed that it had bene®cial
e€ects and research is trying to pinpoint exactly when in the day, and for how long,
light should be used to maximize the e€ect (Terman et al., 1989).
CIRCANNUAL COGNITIVE RHYTHMS IN SAD
Whereas the psychiatric and neuropharmacological correlates of SAD have been
much studied, it is only more recently that the relationship between SAD and cognition has been investigated (Drake et al., 1997; Michalon et al., 1997; O'Brien et al.,
1993).
O'Brien et al. (1993) reported signi®cant de®cits on six out of seven cognitive tasks
in 11 SAD patients compared with ten normal control subjects. These tasks included
pattern recognition, spatial recognition, delayed match-to-sample tests and paired
associate learning. On the remaining task, a simultaneous match-to-sample test, the
trend was clearly for SAD patients to perform worse than controls. In other words,
this study showed reliable cognitive impairments in SAD patients on a wide variety of
tasks.
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
Arctic Cognition in Summer and Winter
563
Michalon et al. (1997) administered a wide range of cognitive tests to 30 SAD
patients and 29 controls in three consecutive winters. They reported de®cits for the
SAD patients on recognition memory for faces and on two tasks involving copying
and recalling the Rey Complex Figure. An evaluation of the ecacy of light therapy
in improving SAD patients' scores for these tests was inconclusive. A subset of their
sample also carried out the tests one summer and while the de®cit in face recognition
was absent, the Rey Complex Figure de®cits were still present.
In Drake et al.'s (1997) study all subjects had winter and summer testing sessions.
They tested ten SAD patients and nine controls on a Stroop task and a patternrecognition task. Season did not a€ect the SAD patients di€erently from the controls
on either task, but on Stroop performance there was a main e€ect of season, with
summer better than winter. However, since all subjects were tested ®rst in winter and
then in summer, the di€erence in Stroop performance may be due to a practice e€ect.
In other words, the confound between season and testing order makes it unsafe to
conclude that, in both patients and controls, there are seasonal rhythms in Stroop
performance.
COGNITION AND EXTREME LATITUDE
As described above, Palinkas et al. (1996) studied seasonal mood swings on normals
at extreme latitudes. By contrast, there is hardly any research on seasonal cognitive
swings in normals at such latitudes. Taylor and Duncum (1987) investigated digit
span and a ®ve-digit discrimination task in 33 people wintering over in Antarctica.
They were tested before and after their one-year stay, though the months of testing are
not mentioned. However there were no di€erences in performance, despite the
subjects' self-report of mental sluggishness.
Establishing whether or not circannual cognitive swings exist is appropriate now
for four reasons. First, research on SAD has established that mood swings covary
with seasons and a follow-up question regards whether seasonal swings in cognitive
performance are also important for humans. In other words, the extent to which
humans are seasonal will be investigated in a domain other than mood.
Second, the current evidence for human seasonality, from SAD, largely uses selfreport methodology. This study, in contrast, will measure swings in actual human
performance.
Third, a particular problem with some studies of SAD incidence is that recruiting
subjects by advertising the project as an investigation into winter depression is likely
to lead to overestimation of true SAD incidence because people with relatively minor
seasonal swings are less likely to volunteer. This makes estimates of incidence of SAD
and generalizations about human seasonality unreliable. In the present study, participants were recruited without reference to winter depression or the possible e€ects of
the seasons on cognition. It was presented as a long-term study of memory and
attention, which, of course, was precisely what it was ± no more, no less. In this way,
we sidestepped the problem of attracting participants particularly prone to, or
interested in, seasonal swings.
Fourth, the practical consequences of any seasonal cognitive swings are obvious in
occupations demanding a high level of performance, e.g. piloting, driving.
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
564
T. Brennen et al.
TROMSé
In this paper we report a study that recorded performance of a battery of cognitive
tests by a large group of people living in Tromsù, in northern Norway, at a latitude of
698N, over 300 kilometres north of the Arctic Circle. They were tested in summer and
in winter, in order to detect seasonal swings in cognitive performance.
Tromsù's population is just below 60,000 and there is no town of that size at a
higher latitude anywhere on the planet. By way of comparison, in the Southern
hemisphere the 698S parallel passes through Antarctica. Tromsù is a fully ¯edged
town: it has a university with over 7000 students, a major teaching hospital, a football
team in the highest national division, two daily newspapers, a plethora of bars and
restaurants, and over 20 scheduled ¯ights to Oslo per day.
Thus Tromsù stands as a rebuttal to Palinkas et al.'s (1996) claim that the diculties experienced by those wintering over in the Antarctic (`prolonged separation
from family and friends, the lack of privacy in cramped quarters, and boredom caused
by lack of environmental and social stimulation', p. 533) would also be characteristic
of more densely populated high-latitude environments! The e€ect of the seasons on
life in Tromsù was broached directly by Rosenthal (1993, pp. 217±18). With the main
source of information apparently a New Yorker article, Tromsù comes across as a
town where in winter work and sleep were dicult, and in summer there was
`widespread celebration' as people went ®shing, hunting and having fun. This is a
romanticized exaggeration, and it is therefore not an `excellent description' because it
is factually wrong in several respects.
At 698N the astronomical seasonal swings are extreme. The `ocial' period of
midnight sun is from 21 May until 21 July, but in fact there is constant daylight for
perhaps a month on either end of that, and one does not see night for even longer than
that if one has a normal sleep pattern.
In winter, the ocial period of `mùrketida' (darkness), where the sun does not
come above the horizon, is from 21 November until 21 January. A common
interpretation of this by non-Arctic people is that it must be pitch black for two
months of the year. This is not the case. Even at the winter solstice, the sky is blue at
midday in Tromsù, but the days of e€ective daylight are nevertheless very short.
We are using Tromsù as a natural laboratory that provides participants who
experience the seasons at 698N. If humans have seasonally driven cognitive swings
then they are surely to be found in Tromsù. Indeed, there is plenty of anecdotal
evidence suggesting that Tromsù's inhabitants are mentally slower in winter than
summer (see e.g. Rosenthal, 1993). Note that the seasonal variation in amount of
light in Tromsù is as extreme as the circadian variation in non-Arctic places.
The predictions are that performance in winter will be worse than performance in
summer. On most tasks this will be re¯ected as higher error rates or longer reaction
times. Additionally, some tests have inbuilt measures of `confusability', e.g. the
di€erence between consistent and inconsistent trials on the Stroop task. The
prediction is that these will increase in winter.
THE POWER AND THE DESIGN OF THIS STUDY
Due to the paucity of studies that have investigated cognition at extreme latitudes,
there is no straightforward way of estimating expected e€ect sizes (and hence the
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
Arctic Cognition in Summer and Winter
565
power) of the seasonal manipulation in this study. Instead, since giving a precise
estimate of e€ect size is not possible, the power of our study was worked out for
di€erent possible e€ect sizes. A within-subjects study with 100 participants and a
signi®cance level of 0.05 has a power of 0.98 for an e€ect size of 0.4 SD, 0.84 for an
e€ect size of 0.3 SD, and 0.51 for an e€ect size of 0.2 SD (Borenstein et al., 1997).
Reaction time e€ects smaller than 0.2 SD are, for many purposes, trivial.
One centrally important aspect of this study is that one subgroup of participants
was tested ®rst in summer and then in winter, and the other subgroup was tested ®rst
in winter and then in summer. Any seasonal e€ects cannot therefore be due to order
of testing, and spurious e€ects cannot arise due to a confound either. On the other
hand, seasonal e€ects for any one subgroup cannot unambiguously be interpreted as
seasonal swings: they may be a practice e€ect or a boredom e€ect. However, a
seasonally counterbalanced design allows one to conclude that any seasonal swings
detected are true circannual swings.
An overall seasonal e€ect may emerge either as a main e€ect of season or as a
particular form of interaction between season and subgroup, namely where the
practice e€ect for one subgroup is reduced or eliminated and for the other subgroup is
increased. This would be due to the e€ect of season working against practice for one
subgroup and in the same direction for the other subgroup.
This study is a ®rst step: it is a thorough investigation of cognitive swings at a
location where the seasonal swings of the environment are enormous. It will be left to
subsequent research to determine which of the many variables that are confounded
with season (e.g. light, temperature, length of time since a holiday) is responsible for
any di€erences found. In other words, this study is designed to detect putative
cognitive rhythms, but in the case of an armative answer will not specify what the
key causal variables are. If, on the other hand, circannual cognitive rhythms cannot
be found among Tromsù's inhabitants, then any e€ects cannot be very large, and can
hardly be of practical consequence.
There are several features of this study that make it suited to detecting even small
circannual cognitive rhythms: (1) reaction time is used as a measure, (2) the number of
participants is large, (3) a wide range of tests is used, (4) the studied population live at
698N, and thus experience enormous seasonal swings, and (5) a seasonally counterbalanced design is used.
METHOD
Participants
Posters advertising the study were placed around Tromsù in May 1997, in the buildings of the town council and the county council, in schools, in cafeÂs frequented by bus
and taxi drivers, at the hospital, and at the university. People who were interested in
taking part in a study of memory and attention where one would perform various
tasks like recognizing faces, counting dots or naming colours, and where one would
be tested several times, were asked to ring Tim Brennen or Monica Martinussen. In
this way, 110 participants were recruited, who were to participate in summer and
winter 1997. The same procedure was repeated in November 1997, when 71
participants were recruited.
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
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T. Brennen et al.
There were dropouts from the ®rst testing session to the second. These either broke
appointments or could not be reached by letter, telephone or e-mail. In total, 62
(56%) of the original 110 summer±winter participants were retested in winter 1997,
and 38 (54%) of the original 71 winter±summer participants were retested in summer
1998. The mean age of the 62 returning summer±winter participants was 30.0 years,
SD ˆ 10.1 (range 16±61), and 26 (42%) were women. The mean age of the 38
returning winter±summer participants was 31.6 years, SD ˆ 12.9 (range 18±63), and
19 (50%) were women. Note that although dropout rates were relatively high, running
participants on the battery for a second time was equally dicult in winter and in
summer, and that the age and gender makeup of the resulting samples were very
similar.
Of the 100 subjects, 53 had lived in northern Norway all their lives. At the time of
their ®rst test session the remaining subjects had lived in the area for a mean of 9.3
years (SD ˆ 10.0; range ˆ 0 to 56 years), and for the sample as a whole the mean
number was 19.1 years (SD ˆ 13.9).
DESIGN
The independent variable of main interest is season, a within-subjects factor with the
levels of summer and winter. All participants performed the tests in summer and in
winter.
One group of participants began their tests in summer and another group in winter,
giving the control between-subjects factor of subgroup. The two subgroups will be
referred to as the summer±winter and the winter±summer groups respectively. Any
di€erence (or absence thereof) between summer and winter will thus not be attribut7able to practice e€ects that carried over from one session to the next.
It was necessary to have two forms of the verbal ¯uency task, the face-recognition
task and the word-memory task, to prevent savings or long-term repetition priming
confounding the results. The order of presentation of the two forms of test was
crossed with the subgroup factor, so that in both subgroups some participants
performed one test ®rst and others performed the other one ®rst. In this way,
artifactual explanations of any e€ects of season on these tests are ruled out.
APPARATUS
All computer-based tasks were run on a 166 MHz PC with a colour monitor. The
software package used was ERTS from Berisoft (Beringer, 1992). For some of the
tasks, the ®rst author developed a version of a script written by Berisoft; for other
tasks the script was written from scratch. For the reaction time tasks participants
responded by use of a response pad directly connected to the hard drive, accurate to
within 1 ms (Beringer, 1992).
PROCEDURE
Participants were tested individually by a research assistant in one of two labs at the
University of Tromsù. Two research assistants ran approximately half the
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
Arctic Cognition in Summer and Winter
567
participants each.1 The twelve tests were administered in the same order for all
participants in both sessions. In all three test sessions, the research assistants were
available to run participants from 8 a.m. until 6 p.m. The summer sessions began in
mid-May and were run until early July. The winter session began in early December
and ran until mid-January.
Participants sat in front of the computer at a distance of approximately 60 cm.
Their posture was not restricted, e.g. by a chin-rest, due to the length of the test
session. All instructions were shown on the computer screen.
TASKS
Reaction time
Speed
Participants had to respond by pressing a button as quickly as possible to a yellow
circle presented in the middle of the screen, where the background colour was grey.
This was thus a simple reaction time task. The temporal characteristics of this test
were as follows. There was a 4-second gap between the participant's key press to clear
the instructions and the presentation of the ®rst stimulus. Thereafter the length of the
interval between a participant's response and the presentation of the next stimulus
was determined by an exponentially decreasing random process, with a maximum of
7500 ms. There were forty trials.
Dot numerosity judgements
In this task the screen was divided by a vertical line down the middle. On each trial
participants had to decide on which side there were more dots, pressing the left or
right button accordingly. On half of the trials there were more dots on the left side and
on the other half there were more on the right. On each trial, one side had 20 dots in a
random pattern. The other side had the same 20-dot pattern plus from one to ®ve
extra dots. All dots were presented simultaneously. The visual stimulus remained on
screen until the participant's response or 3000 ms were reached, whichever came ®rst.
The dots were yellow on a grey background and there were forty trials in total. On
each trial, after the participant had responded, feedback was given by showing the
location of the key `extra' dots in blue.
Attention tasks
Stroop
This Stroop task used manual responses on a four-button response pad. The four
colours were red, yellow, green and blue, and the words were the equivalent
Norwegian colour words: rùd, gul, grùnn and blaÊ. Participants were instructed to
respond to the colour of the stimulus and not the word. There were sixty trials of
which 24 were consistent (e.g. `blaÊ' written in blue) and 36 were inconsistent (e.g. `blaÊ'
written in yellow). Feedback was provided on the screen on each trial as to whether
the participant's response was correct or not.
1
The same two research assistants (BOH and OH) shared the running of the great majority of participants
equally in all three sessions. Kristin Johannessen and Tim Brennen stepped in when either of them was
unable to work.
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
568
T. Brennen et al.
Mapping
On each trial either an X or an O was presented, either left or right of centre. The
participants' task was to press the left-hand button when an O was presented and the
right-hand button when an X was presented. This is thus a task where confusion
arises due to response mapping con¯ict: a stimulus is presented on the left-hand side
and the correct response is to press the right-hand button. There were forty trials. The
visual angle subtended by the X and the O was 28, and the eccentricity was 78.
Time estimation
Participants were given the task of estimating time intervals. Participants initiated
each trial by a key press which triggered a tone that indicated the beginning of the
time period. The participant pressed the button when he or she reckoned the time
period was up. There were three trials, carried out in the following order: 60 seconds,
30 seconds, 15 seconds. Throughout each trial the target number of seconds was on
screen.
Memory tasks
Sternberg
This task required scanning of short-term memory, and was based on Sternberg's
(1966) task. On each trial to-be-remembered yellow digits were presented one at a
time, for 1000 ms. All 10 digits had an equal chance of being selected, and no
repetition within trials was allowed. Then a dash was presented for 3000 ms, followed
by a single white digit. The participants' task was to decide whether the white digit
was a member of the previously presented set. Forty trials were presented in total, half
of which with three digits to remember and half with ®ve. For half of each of these set
sizes, the white digit did in fact come from the set (target present), and for half it did
not (target absent).
Face recognition
On each trial a face was presented in the middle of the screen. The participant's task
was to decide whether or not it was a famous face. Of the 42 faces in the experiment,
25 were famous and 17 were not. Each face was presented twice during the task, giving
a total of 84 trials for each participant on each test session. There were two sets of
faces, and about half the participants saw Set A in their ®rst test session and Set B on
their second, whereas the other participants saw Set B and then Set A.
Word memory
Words were presented for 3000 ms, one at a time in the middle of the screen. The
participant triggered the presentation of the following word by pressing the space bar.
Participants were told that their memory for these words would be tested later. In
every test session, 61 words were presented. The ®rst six and the last ®ve words were
held constant in order to reduce any e€ects of primacy and recency, and memory for
these items was not tested. This gave 50 target words for which memory was tested.
Memory for these items was tested approximately 10 minutes after this presentation phase, the time it took to perform the mapping and Sternberg tasks. The
technique employed was that used by Jacoby et al. (1993) for separating conscious
and unconscious in¯uences on memory. This consists of a stem-completion task
Copyright # 1999 John Wiley & Sons, Ltd.
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Arctic Cognition in Summer and Winter
569
where the instructions varied according to the colour of the stem: when the stem was
written in green, the participant had to complete it with a word from the previously
seen list. If the participant did not remember a word from the list, any other word
could be written. When the stem was written in red, the participant had to complete it
with a word NOT from the previously seen list. These instructions are known as the
inclusion and the exclusion tests, respectively. Each participant saw 25 stems in the
inclusion condition and 25 in the exclusion condition. In conjunction these two types
of test provide estimates of the contributions of recollection and automatic in¯uences
on memory performance.
There were two counterbalancing factors. First, there were two lists of 50 words and
half the participants saw List 1 in their ®rst test session and List 2 in their second,
while the other half had the reverse order. Second, each wordlist was divided into two,
so that across each test session any particular word was seen by equal numbers of
participants in the inclusion and the exclusion conditions.
The last task in each test session was a surprise-free recall test for the words in the
original list. Although we expected this test to be less of a surprise at the end of the
second session, the number, variety and intensity of tests meant that the participants
were surprised the second time too!
Fluency
This was a verbal ¯uency test. Participants were given a letter from the alphabet and
told to generate as many words as possible in one minute. Proper names and foreign
words were not allowed, and words with the same stem as a previously generated
word, e.g. plurals, did not count. The letters used were `F' and `S'. About half the
participants generated words from the letter `F' in the ®rst test session and `S' in the
second, while the others generated in the reverse order.
Order of tasks
The order of tests was identical for all participants in all test sessions:
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
Dot numerosity judgements
Fluency
Word memory±presentation phase
Sternberg
Mapping
Word memory ± stem completion
Time estimation
Speed: break
Face recognition
Stroop
Word memory ± free recall.
RESULTS
A separate analysis of variance was carried out for each test. The analysis for all tests
includes a season factor (with the levels of summer and winter) and a counterCopyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
570
T. Brennen et al.
Table 1. A summary for each task of the seasonal means (with standard deviation), the e€ect
of season, and e€ect size, ES
Task
Summer
Winter
Seasonal e€ect?
Speed
271 ms (46)
260 ms (38)
Dot numerosity
Stroop
1290 ms (454)
7.1 errors (3.6)
984 ms (326)
1180 ms (393)
6.8 errors (3.2)
935 ms (301)
Mapping
508 ms (124)
493 ms (97)
Time estimation
Sternberg
Face recognition
Word memory
0.212 (0.22)
1004 ms (244)
887 ms (162)
A: 0.12 (0.08)
R: 0.27 (0.16)
FR: 12.1 (6.6)
15.7 (4.6)
0.194 (0.17)
974 ms (226)
864 ms (170)
A: 0.10 (0.07)
R: 0.30 (0.17)
FR: 14.4 (8.7)
15.0 (5.0)
Yes: summer slower than winter,
ES ˆ 0.26
Yes: summer more error-prone
than winter, ES ˆ 0.08
No: no seasonal e€ect and no
season by consistency
interaction
Yes: increased mapping
confusion in summer (28 ms
versus 12 ms in winter)
No (see Table 2)
No
No
Yes: free recall better in winter,
ES ˆ 0.33
Fluency
Yes: summer better than winter,
ES ˆ 0.12
balancing factor of subgroup (with the levels of summer±winter and winter±summer).
Some of the tests have additional counterbalancing factors, as described in the Tasks
section above. Where appropriate, tasks had one analysis for correct responses and
another for errors.
Tests had slightly di€erent numbers of participants due to causes such as
equipment failure and corrupted data ®les. The resultant number of participants per
task ranges from 93 to 99. An alpha level of 0.05 was used for all statistical tests. All
signi®cant sources of variance are mentioned below. Table 1 summarizes the main
results of each task by indicating whether a season e€ect was observed.
Speed
The mean reaction time was 271 ms (SD ˆ 46) for summer and 260 ms (SD ˆ 38) for
winter. A two-way ANOVA with the factors of season and subgroup showed that the
main e€ect of season was signi®cant, F(1,91) ˆ 4.46, MSE ˆ 822. The main e€ect of
subgroup was also signi®cant, F(1,91) ˆ 4.90, MSE ˆ 2538: the summer±winter
group had a mean of 272 ms (SD ˆ 44) and the winter±summer had a mean of 255
ms (SD ˆ 37). These main e€ects were modi®ed by an interaction between subgroup
and season, F(1,91) ˆ 6.19, MSE ˆ 822. The winter±summer group had a mean of
256 ms (SD ˆ 40) in winter and 255 ms (SD ˆ 34) in summer, whereas the summer±
winter group had a mean of 262 ms (SD ˆ 36) in winter and 282 ms (SD ˆ 49) in
summer. Therefore, for one subgroup there was an advantage in winter and for the
other there was no e€ect. These data are consistent with a model of simple reaction
time where performance is quicker in winter than summer, and where there is a
practice e€ect.
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
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Dot numerosity judgements
Wrong key presses and latencies in excess of 3000 ms were counted for each subject in
each test session. The mean number of errors was 7.07 (SD ˆ 3.6) for summer and 6.8
(SD ˆ 3.2) for winter. A two-way ANOVA showed that the main e€ect of season was
signi®cant, F(1,95) ˆ 4.3, MSE ˆ 6.2. The main e€ect of subgroup was not
signi®cant, F(1,95) ˆ 0.02, MSE ˆ 16.0, whereas the interaction was signi®cant,
F(1,95) ˆ 25.5, MSE ˆ 6.2. Inspection of the means showed that both subgroups
produced more errors on the second time of testing. This was con®rmed by separate
one-way ANOVAs on each subgroup. For the summer±winter group, the mean
number of errors per subject was 6.3 (SD ˆ 3.6) in summer and 7.4 (SD ˆ 3.2) in
winter, F(1,60) ˆ 6.6, MSE ˆ 0.56. For the winter±summer group, the mean
number of errors per subject was 8.3 (SD ˆ 3.2) in summer and 5.7 (SD ˆ 3.0) in
winter, F(1,35) ˆ 17.4, MSE ˆ 0.72.
The mean reaction time for correct responses in summer was 1290 ms (SD ˆ 454)
and in winter it was 1180 ms (SD ˆ 393). An ANOVA showed that the main e€ects of
season and subgroup were not signi®cant, F(1,95) ˆ 1.46, MSE ˆ 104,109, and
F(1,95) ˆ 2.57, MSE ˆ 234,797, respectively. The interaction was signi®cant,
F(1,95) ˆ 17.6, MSE ˆ 104,109. The mean reaction times for the summer±winter
group were 1408 ms (SD ˆ 462) in summer and 1149 ms (SD ˆ 367) in winter, and
for the winter±summer group were 1091 ms (SD ˆ 364) for summer and 1235 ms
(SD ˆ 433) for winter. Separate one-way ANOVAs for each subgroup showed that
for the summer±winter group a signi®cant practice e€ect was observed,
F(1,60) ˆ 27.9, MSE ˆ 73,622, whereas for the winter±summer group the trend
did not reach signi®cance, F(1,35) ˆ 2.36, MSE ˆ 156,373.
In summary, performance of the dot perception task in summer had a signi®cantly
higher error rate, as well as a trend for longer latencies. There was also a speed±
accuracy tradeo€ between participants' ®rst and second times of testing: their correct
reaction times were shorter in the second testing session, but their error rates were
higher.
Stroop
For each participant and for each test session, the proportion of trials that were errors
in the consistent and inconsistent conditions were computed. Errors included wrong
key presses and latencies exceeding 3000 ms. The mean proportion of errors was 0.027
(SD ˆ 0.04) for the consistent condition and 0.082 (SD ˆ 0.08) for the inconsistent
condition. The mean error rate for summer was 0.053 (SD ˆ 0.08) and for winter it
was 0.056 (SD ˆ 0.07).
An ANOVA with the factors of season, subgroup and consistency was performed
on these data. There were no main e€ects of season, F(1,93) ˆ 0.50, MSE ˆ 0.004, or
of subgroup, F(1,93) ˆ 2.68, MSE ˆ 0.008. There was a main e€ect of consistency,
F(1,93) ˆ 90.2, MSE ˆ 0.003, and an interaction between consistency and subgroup,
F(1,93) ˆ 4.29, MSE ˆ 0.003 which was explored by separate two-way ANOVAs for
each subgroup. These showed that while both subgroups had signi®cantly higher
error rates on inconsistent trials than on consistent ones, the e€ect was larger in the
winter±summer subgroup (0.029 versus 0.099; F(1,35) ˆ 34.1, MSE ˆ 0.005) than in
the summer±winter subgroup (0.026 versus 0.072; F(1,58) ˆ 55.9, MSE ˆ 0.002). In
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both of these supplementary analyses the main e€ect of consistency was signi®cant
and the interaction was not.
The mean reaction time of correct responses on consistent trials was 896 ms
(SD ˆ 284), whereas for inconsistent trials it was 1024 ms (SD ˆ 331). The mean
reaction time of correct responses in summer was 984 ms (SD ˆ 326), and in winter it
was 935 ms (SD ˆ 301).
An ANOVA with the factors of season, subgroup and consistency showed that
season did not have a main e€ect, F(1,93) ˆ 0.63, MSE ˆ 34,274, and nor did
subgroup, F(1,93) ˆ 0.65, MSE ˆ 310,856. There was a main e€ect of consistency,
F(1,93) ˆ 126.6, MSE ˆ 11,736. The two-way interaction between season and
subgroup was also signi®cant, F(1,93) ˆ 47.0, MSE ˆ 34,274. Separate two-way
ANOVAs for each subgroup showed that this was due to participants in both
subgroups responding more rapidly in their second session. The summer±winter
group had a mean of 1052 ms (SD ˆ 332) in summer and 903 ms (SD ˆ 277) in
winter, F(1,59) ˆ 35.5, MSE ˆ 37,677, whereas the winter±summer group had a
mean of 990 ms (SD ˆ 333) in winter and 871 ms (SD ˆ 283) in summer,
F(1,35) ˆ 17.7, MSE ˆ 28,537. In both of these supplementary analyses the main
e€ect of consistency was signi®cant and the interaction was not.
There was no e€ect of season on performance of the Stroop task. Note also that in
all the above analyses, both for error rate and reaction time, there was a main e€ect of
consistency, and also that on none was the interaction between season and consistency signi®cant. Only on the reaction time data for the summer±winter group did
it approach signi®cance, F(1,59) ˆ 3.3, MSE ˆ 5678, p ˆ 0.07, and this was a
tendency to a reduced Stroop e€ect in winter.
Mapping
Errors were counted for each condition, subject and test session. They consisted either
of reaction times over 2000 ms or wrong key presses. The mean number of errors per
condition in summer was 0.83 (SD ˆ 1.2), and in winter was 0.82 (SD ˆ 1.1). The
mean number of errors on compatible trials was 0.59 (SD ˆ 1.0), and on
incompatible trials was 1.1 (SD ˆ 1.2). On a three-way ANOVA with the factors of
season, subgroup and compatibility, the only signi®cant source of variance was a
main e€ect of compatibility, F(1,97) ˆ 16.1, MSE ˆ 1.2.
The mean reaction time on correct trials in summer was 508 ms (SD ˆ 124), and
in winter was 493 ms (SD ˆ 97). The mean correct reaction time on compatible
trials was 491 ms (SD ˆ 107), and on incompatible trials was 511 ms (SD ˆ 115). A
three-way ANOVA with the factors of season, subgroup and compatibility was
carried out on the data. The main e€ect of season was not signi®cant, F(1,97) ˆ 0.77,
MSE ˆ 3740. A main e€ect of compatibility was observed, F(1,97) ˆ 24.0,
MSE ˆ 1510. There were signi®cant interactions between season and subgroup,
F(1,97) ˆ 33.0, MSE ˆ 3740, and between season and compatibility, F(1,97) ˆ 5.0,
MSE ˆ 1012. These interactions were explored below.
The mean reaction times for the summer±winter group were 533 ms (SD ˆ 132) in
summer and 491 ms (SD ˆ 107) in winter, and for the winter±summer group were
465 ms (SD ˆ 92) for summer and 496 ms (SD ˆ 80) for winter. Separate one-way
ANOVAs for each subgroup showed that for each subgroup a signi®cant practice
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Arctic Cognition in Summer and Winter
573
e€ect was observed; for the summer±winter group, F(1,62) ˆ 24.6, MSE ˆ 4580,
and for the winter±summer group, F(1,35) ˆ 15.5, MSE ˆ 2251.
The interaction between season and compatibility was due to a reduced e€ect of
compatibility in winter compared to summer. The compatibility e€ect in winter was
12 ms and in summer was 28 ms. Both were signi®cant e€ects, t(99) ˆ 2.6, p 5 0.01
and t(99) ˆ 5.8, p 5 0.0001. Compatible trials in summer were only 8 ms longer than
compatible trials in winter and this di€erence was not signi®cant, t(99) ˆ 0.39.
However, incompatible trials in summer were 24 ms longer than incompatible trials in
winter and this di€erence was signi®cant, t(99) ˆ 2.6, p 5 0.01.
There were no main e€ects of season in this task. Both a signi®cant practice e€ect
and the classic Simon e€ect were observed. The Simon e€ect on reaction times was
modi®ed by season: there was a reduced e€ect in winter.
Time estimation
While the raw data gives one indication of the accuracy of performance, a more
informative way of presenting and processing the data is to use the absolute proportion deviation from the target time period. This avoids two problems: measuring
absolute deviation ensures that over- and underestimates do not cancel each other
out, and measuring proportion deviation makes a comparison between the three trial
lengths fairer. The mean estimates for the three time periods in summer and winter
and the absolute proportion deviations are shown in Table 2.
An ANOVA on the absolute proportion deviation data revealed no main e€ect of
season, F(1,97) ˆ 0.1, MSE ˆ 0.05. There was a main e€ect of subgroup,
F(1,97) ˆ 7.31, MSE ˆ 0.125, due to the fact that participants in the winter±
summer subgroup were more accurate than those in the summer±winter subgroup
(mean absolute proportion deviation for summer±winter group ˆ 0.234
(SD ˆ 0.217); for the winter±summer group ˆ 0.153 (SD ˆ 0.147)). There was
also a main e€ect of time period, F(1,97) ˆ 10.72, MSE ˆ 0.012. Contrasts showed
that estimates of 15 seconds were the least precise, and that those for 30 and 60
seconds did not di€er from each other in accuracy: for 60 versus 30, F ˆ 2.25,
MSE ˆ 0.028; for 30 versus 15, F ˆ 9.3, MSE ˆ 0.114; for 60 versus 15, F ˆ 20.7,
MSE ˆ 0.254.
There was also a two-way interaction between season and season order, F(1,
97) ˆ 5.6, MSE ˆ 0.05. Separate one-way ANOVAs on each subgroup showed that
Table 2. Mean time estimates in ms (standard deviation) and mean proportion of absolute
deviation on time estimates (standard deviation) in summer and winter for three time periods
60 seconds
Summer
Winter
Mean
30 seconds
15 seconds
Mean
Deviation deviation
Time
Deviation
Time
Deviation
Time
61322
(16006)
61079
(14501)
0.177
(0.20)
0.179
(0.16)
33383
(8775)
32675
(6711)
0.215
(0.23)
0.183
(0.16)
17548
(4499)
17301
(3578)
0.245
(0.24)
0.221
(0.18)
61200
(15234)
0.178
(0.18)
33029
(7799)
0.199
(0.20)
17424
(4056)
0.233
(0.21)
Copyright # 1999 John Wiley & Sons, Ltd.
0.212
(0.22)
0.194
(0.17)
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T. Brennen et al.
this interaction was due to a tendency for each subgroup to be more accurate at the
second time of testing: For the summer±winter subgroup the mean absolute proportion deviation for summer was 0.26 (SD ˆ 0.25) and for winter was 0.21
(SD ˆ 0.17), F(1,61) ˆ 3.8, MSE ˆ 0.07, p ˆ 0.055, whereas for the winter±
summer group the mean absolute proportion deviation for summer was 0.13
(SD ˆ 0.13) and for winter was 0.17 (SD ˆ 0.16), F(1,36) ˆ 3.1, MSE ˆ 0.03,
p ˆ 0.087. There was no seasonal e€ect on this task.
Sternberg
The raw data were checked for errors, which were counted up for each subject,
condition and test session. There was a mean of 0.42 (SD ˆ 0.78) errors per condition
in summer and 0.36 (SD ˆ 0.68) in winter. A four-way ANOVA with the factors of
season, subgroup, target presence and set size was carried out on these data. There
was no main e€ect of season, F(1,96) ˆ 0.30, MSE ˆ 0.52. The main e€ect of target
presence was signi®cant, F(1,96) ˆ 31.4, MSE ˆ 0.39, with a mean of 0.52
(SD ˆ 0.84) errors in the present condition and 0.26 (SD ˆ 0.58) in the absent
condition. There were fewer errors on the trials with three digits than those with ®ve;
the mean error rates were 0.24 (SD ˆ 0.54) and 0.54 (SD ˆ 0.54) respectively,
F(1,96) ˆ 39.9, MSE ˆ 0.402.
There was a signi®cant interaction between set size and target presence,
F(1,96) ˆ 4.6, MSE ˆ 0.47. This was due to a larger e€ect of target presence on
set sizes of ®ve compared to set sizes of three, t(98) ˆ 5.1, p 5 0.0001 versus
t(98) ˆ 2.1, p 5 0.05.
The interaction between season and subgroup was also signi®cant, F(1,96) ˆ 6.9,
MSE ˆ 0.52. Inspection of the means showed that both subgroups produced fewer
errors at the second time of testing. For the summer±winter group, the mean number
of errors per subject per condition was 0.42 (SD ˆ 0.8) in summer and 0.28
(SD ˆ 0.6) in winter. For the winter±summer group, the mean number of errors per
subject was 0.38 (SD ˆ 0.7) in summer and 0.49 (SD ˆ 0.8) in winter. Separate oneway ANOVAs on each subgroup showed that this practice e€ect was signi®cant for
the summer±winter subgroup, F(1,61) ˆ 6.6, MSE ˆ 0.54, but not for the winter±
summer subgroup, F(1,35) ˆ 1.8, MSE ˆ 0.48, p ˆ 0.18.
The mean correct reaction times were 1004 ms (SD ˆ 244) in summer and 974 ms
(SD ˆ 226) in winter. A four-way ANOVA was carried out on these data, and showed
no main e€ect of season, F(1,96) ˆ 0.18, MSE ˆ 53,334. There was a main e€ect of
set size, F(1,96) ˆ 149.0, MSE ˆ 9837, trials with ®ve digits taking longer than trials
with three, 1035 ms (SD ˆ 236) and 944 ms (SD ˆ 226).
There was an interaction between season and subgroup, F(1,96) ˆ 26.2,
MSE ˆ 53,334. This was due to a practice e€ect, both subgroups being quicker in
their second test session; for the summer±winter subgroup the mean in summer was
1058 ms (SD ˆ 250) and in winter 963 ms (SD ˆ 242); for the winter±summer
subgroup the mean in summer was 913 ms (SD ˆ 203) and in winter 994 ms
(SD ˆ 195). This was con®rmed by separate three-way ANOVAs, where the main
e€ect of season was signi®cant for both subgroups, F(1,61) ˆ 17.9, MSE ˆ 62,088,
and F(1,35) ˆ 12.2, MSE ˆ 38,078, respectively. There was no e€ect of season on
this task, just an e€ect of practice.
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Face recognition
For each participant, the number of errors on trials with famous and unfamiliar faces
was computed, for summer and winter. Error arose in two ways: the incorrect key was
pressed, or the latency exceeded 2000 ms. The mean number of errors for summer was
6.32 (SD ˆ 6.95) and the mean for winter was 6.36 (SD ˆ 6.91). The mean number
of errors on famous faces was 10.18 (SD ˆ 7.45) and for unfamiliar faces was 2.50
(SD ˆ 3.29).
A three-way ANOVA was carried out on these error data with the within-subjects
factors of season and fame (with the levels of Famous and Unfamiliar faces) and the
between-subjects factor of subgroup. There was no signi®cant e€ect of season,
F(1,97) ˆ 0.34, MSE ˆ 7.1. The only signi®cant main e€ect was of fame,
F(1,97) ˆ 95.6, MSE ˆ 56.0. There was a signi®cant interaction between season
and subgroup, F(1,97) ˆ 8.3, MSE ˆ 7.1. This was explored by separate two-way
ANOVAs for each subgroup, revealing that participants made signi®cantly more
errors when tested the second time, regardless of whether that fell in summer or
winter. For the winter±summer group the mean number of errors in winter was 5.4
(SD ˆ 5.9) and in summer was 6.3 (SD ˆ 6.6), F(1,36) ˆ 4.3, MSE ˆ 7.9. For the
summer±winter group the mean number of errors in winter was 7.0 (SD ˆ 7.3) and in
summer was 6.3 (SD ˆ 7.2) which approached signi®cance, F(1,61) ˆ 3.8,
MSE ˆ 6.6, p ˆ 0.056. In both supplementary ANOVAs there was a main e€ect of
fame and no signi®cant interaction.
The mean reaction time on correct responses in summer was 887 ms (SD ˆ 162),
and in winter was 864 ms (SD ˆ 170). The mean reaction time to recognize a famous
face was 833 ms (SD ˆ 137) whereas the mean to correctly reject unfamiliar faces was
918 ms (SD ˆ 182).
A three-way ANOVA with the factors of season, subgroup and fame was carried
out on reaction times to correct trials, revealing no main e€ect of season,
F(1,97) ˆ 0.47, MSE ˆ 10,037. There was a main e€ect of fame, F(1,97) ˆ 50.97,
MSE ˆ 13,698, and a signi®cant interaction between season and subgroup, F(1,
97) ˆ 33.20, MSE ˆ 10,037. The three-way interaction was also signi®cant, F(1,
97) ˆ 11.22, MSE ˆ 5367.
The two-way interaction between season and subgroup was explored by means of
separate two-way ANOVAs for each subgroup. They showed that both subgroups
were quicker when tested the second time. For the winter±summer group the mean
reaction time in summer was 852 ms (SD ˆ 165), and in winter it was 905 ms
(SD ˆ 165), F(1,36) ˆ 9.0, MSE ˆ 11,456. The means for the summer±winter group
were 907 ms (SD ˆ 158) in summer and 840 ms (SD ˆ 154) in winter,
F(1,61) ˆ 30.3, MSE ˆ 9199. Taken in conjunction with the error analysis of the
same interaction, a speed-accuracy trade-o€ is observed: at the second time of testing
participants were both quicker and made more errors.
The three-way interaction is due to a reduction of the advantage of famous faces
over unfamiliar faces in the second test session for both groups. The di€erence in
latency between famous and unfamiliar faces for the summer±winter group went
from 103 ms in the ®rst test session to 61 ms in the second. For the winter±summer
group it went from 121 ms to 62 ms.
In summary, in the face-recognition task there was no seasonal e€ect, either on
error rates or on reaction times.
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T. Brennen et al.
Word memory
For each participant, and for each season, the proportion of old words produced in
the inclusion and exclusion conditions was computed. The means for exclusion were
0.09 (SD ˆ 0.07) in summer and 0.07 (SD ˆ 0.06) in winter. The means for inclusion
were 0.36 (SD ˆ 0.07) for summer and 0.37 (SD ˆ 0.14) for winter.
Estimates of recollection and automatic processing were obtained using Jacoby
et al.'s (1993) equations: Recollection ˆ Inclusion ÿ Exclusion, and Automatic ˆ
Exclusion/(1 ÿ Recollection). The means for recollection in summer and winter were
0.270 (SD ˆ 0.16) and 0.298 (SD ˆ 0.17) respectively. The means for the automatic
in¯uences were 0.12 (SD ˆ 0.08) in summer and 0.10 (SD ˆ 0.07) in winter. A
separate two-way ANOVA was carried out for each of these scores, with the factors of
Season and Subgroup. For recollection there were no signi®cant e€ects. For the
automatic in¯uence, the interaction between season and subgroup was signi®cant,
F(1,95) ˆ 9.8, MSE ˆ 0.004. Inspection of the means for each subgroup showed that
there was a reduced automatic in¯uence upon the second time of testing. For the
summer±winter group the mean in summer was 0.12 (SD ˆ 0.09) and in winter was
0.09 (SD ˆ 0.07), whereas for the winter±summer group the mean in summer was
0.09 (SD ˆ 0.08) and in winter was 0.11 (SD ˆ 0.07). Separate one-way ANOVAs
were carried out on the automaticity scores for each subgroup. The summer±winter
group scored higher in summer than winter, F(1,62) ˆ 10.8, MSE ˆ 0.004, whereas
there was no signi®cant di€erence for the winter±summer group, F(1,34) ˆ 2.1,
MSE ˆ 0.003.
At the end of the test session there was a surprise-free recall test. The mean number
of words recalled in summer was 12.1 (SD ˆ 6.6), and in winter was 14.4 (SD ˆ 8.7).
On a two-way ANOVA the e€ect of season was signi®cant, F(1,95) ˆ 6.2,
MSE ˆ 22.9. The interaction between season and subgroup was also signi®cant,
F(1,95) ˆ 8.6, MSE ˆ 22.9. The mean number of words recalled by the summer±
winter group was 11.5 (SD ˆ 6.3) in summer and 15.4 (SD ˆ 9.1) in winter. The
mean number of words recalled by the winter±summer group was 13.1 (SD ˆ 7.2) in
summer and 12.8 (SD ˆ 7.7) in winter. Separate one-way ANOVAs for the two
subgroups showed that only for the summer±winter group was there a signi®cant
e€ect of season, F(1,61) ˆ 18.0, MSE ˆ 25.8. The data from the free recall test are
thus consistent with a model where there are advantages of winter over summer, and
of second-time performance over ®rst-time performance.
There was no e€ect of season or practice on recollection. The automatic in¯uence
was reduced at a second time of testing (a reliable e€ect for one subgroup) and was
not a€ected by the seasonal manipulation. In free recall there was evidence of a winter
advantage.
Fluency
The mean number of words generated in summer was 15.74 (SD ˆ 4.57), and for
winter was 15.03 (SD ˆ 4.96). The scores for each participant in each test session
were analysed by an ANOVA with the factors of season and subgroup. There was no
e€ect of subgroup, F(1,95) ˆ 0.646, MSE ˆ 28.4, whereas the e€ect of season was
marginal, F(1,95) ˆ 3.34, MSE ˆ 16.3, p ˆ 0.07. This was modi®ed by a signi®cant
two-way interaction, F(1,95) ˆ 6.17, MSE ˆ 16.3. Separate one-way ANOVAs for
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577
each subgroup revealed that whereas for the summer±winter subgroup there was no
di€erence between summer and winter (mean in summer ˆ 15.4 (SD ˆ 4.4), mean in
winter ˆ 15.8 (SD ˆ 5.1); F(1,60) ˆ 0.35, MSE ˆ 13.6), for the winter±summer
subgroup there was a signi®cant advantage for summer over winter (mean in
summer ˆ 16.3 (SD ˆ 4.9), mean in winter ˆ 13.7 (SD ˆ 4.4); F(1,35) ˆ 5.8,
MSE ˆ 20.8).
The pattern of performance on the verbal ¯uency task is consistent with a twoprocess model where the e€ect of practice tends to increase a participant's score on the
second testing, and where summer has an advantage over winter.
DISCUSSION
There is a growing literature on the e€ects of the annual ¯uctuations in day length on
humans. Mood swings through the seasons are now well documented, with winter
being a time of worse moods than summer. The hypothesized causative agent is
shortage of daylight in winter, thus leading to the idea that swings will be larger, the
further from the equator. Circannual cognitive swings have not been previously
studied on a large scale. In this study, a group of 100 people living at 698N were tested
on a battery of cognitive tests in both summer and winter. One dependent variable
used was reaction time, in order to detect even subtle disadvantages in winter
performance.
Summarizing across tests, this large database does not provide evidence of cognitive impairment in winter. Indeed, on the tests showing summer±winter di€erences,
four showed winter advantages, whereas only one showed a winter disadvantage. Of
all the cognitive capacities covered in the battery of tasks, the only one to show the
predicted disadvantage in winter was verbal ¯uency: on average, participants
generated 0.7 more words in summer than in winter.
On the purest measure of simple reaction time, where subjects responded to a visual
stimulus with a key press as quickly as possible, there was a signi®cant advantage for
winter. Bearing in mind that the participants in this study experience extreme seasonal
swings in the amount of natural daily light to which they are exposed, this result rules
out any notion of a pure low-level cognitive de®cit in winter, and sets limits on
accounts of seasonal processing in humans. Performance on another simple speeded
reaction time task, the dot numerosity task, was more error-prone in summer, again
irreconcilable with a winter disadvantage.
Another possibility was that even if reaction time did not increase in winter,
attention would be less focused and participants would be more easily confused. By
looking at the di€erence between consistent and inconsistent trials on the Stroop and
mapping tasks, we have measures of confusability. There was a signi®cant reduction in
confusability in winter, as measured in the mapping task, and no seasonal di€erence
in the Stroop task. Again, claims that humans are more confused in winter can be
rejected because if Tromsù participants are not impaired in winter then there is no
reason to expect more southerly humans to be so.
Memory for a word list was tested in three di€erent ways. On the measures of
recollection and automatic in¯uences there were no seasonal e€ects whereas on the
free recall task, there was an advantage for winter performance. On the remaining
tests ± face recognition, short-term memory scanning and time estimation ± there were
Copyright # 1999 John Wiley & Sons, Ltd.
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T. Brennen et al.
no seasonal e€ects. Overall, this study has found that there is very little in¯uence of
the seasons on cognitive performance. Furthermore, the majority of the circannual
variations found in this study are winter advantages, rather than disadvantages.
Note that the age of participants in this study (M ˆ 31, SD ˆ 10) is in the right
range for them to be susceptible to SAD. In all the investigations of SAD and
cognition described above, the patients' mean age was between 30 and 40. The participants in this study were thus at peak sensitivity to seasonal changes on mood.
Although there is no data on SAD incidence in our sample for the period of the study,
the size and the heterogeneity of the sample puts the burden of proof on anyone
wishing to claim that cognition performance is subject to circannual rhythms, in SAD
or non-SAD populations.
The battery of tests took over 90 minutes to complete, so that it demanded
considerable e€ort and concentration. It would be most unconvincing to argue, for
instance, that participants were able to compensate for a winter impairment by
making an extra e€ort ± this would absolutely not be a trivial feat.
Any concerns about the power of this study to detect cognitive disadvantages in
winter become irrelevant when four of ®ve signi®cant circannual e€ects are in the
unexpected direction. It should also be pointed out that the size of the e€ect on the
verbal ¯uency task was just less than SD 0.12, and so this study was powerful enough
to detect even small e€ects.
Above, we have listed many reasons why this study was suited to detecting any
rhythms in cognition. Despite the subjective feeling one may have that one is mentally
sluggish in winter, our data do not lend empirical support to the intuitive claim. This
result is similar to that reported in the literature on menstruation and cognition.
While women's self-report is that they are intellectually impaired in the premenstrual
and menstrual phases compared to the preluteal phase, there is converging evidence
for a total absence of such impairment, both in cognitive tasks and in real
examination performance (Richardson, 1991a, b). It has also been found that neither
women with, nor women without, premenstrual dysphoric disorder show cognitive
rhythms over the menstrual cycle: those with premenstrual dysphoric disorder may
show a marginal de®cit that is constant over the cycle (Keenan et al., 1995; Resnick
et al., 1998). It will be interesting to see if future investigations show more similarities
between the menstrual and the circannual cycles. It is tempting to extrapolate from
the literature on the menstrual cycle and predict, for instance, that SAD patients will
fail to show a cyclical cognitive pattern, just a general non-cyclical de®cit when
compared to normals. Another parallel between menstrual and circannual cycles
is that, just as Richardson (1991b) argued that the counterintuitive absence of
menstrual cognitive rhythms could be used to remove psychological barriers to
women in places of study, we would argue that the absence of a winter disadvantage
on cognitive tasks should act as a counterbalance to one's intuitions that intellectual
performance at high latitudes must be worse in winter.
Interestingly, the intuition of cognitive impairment during menstruation and the
intuition of cognitive impairment in winter are both relatively recent in origin.
Richardson (1991b) shows that the idea that menstruating women are less e€ective
mentally originates from the ®rst half of the twentieth century. The link between
annual rhythms and human performance is even more recent. Rosenthal et al. (1984)
®rst reported the circannual mood disorder SAD, and it has been widely assumed
since that time that cognition is also a€ected. The idea that the lack of daylight in
Copyright # 1999 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 13: 561±580 (1999)
Arctic Cognition in Summer and Winter
579
winter at 698N will have a debilitating e€ect on human cognition apparently has great
plausibility, to both academics and non-academics, north and south of the Arctic
Circle, but is simply not supported by this study.
Although the ideas in the SAD literature and anecdotal evidence and the extreme
latitude were all reasons to expect a winter de®cit in cognition in this study there was
little evidence for one: there was more support for a summer de®cit. This study, which
was carried out at 698N and which was designed to detect any circannual cognitive
rhythms, provides no support for the idea that cognitive performance is impaired in
winter.
ACKNOWLEDGEMENTS
This study was supported by grant 114162/330 from the Norwegian Research Council
and also by grant 211/97 from Nansenfondet, Den Norske Videnskaps-Akademi.
Thanks are due to Kristin Johannessen, Charlotte Kristiansen, Serge BreÂdart and
Ragnhild Dybdahl for assistance.
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