Seasonal photoperiod, gender, and P300

Seasonal photoperiod, gender, and P300

Phillip P. Shelton, Anita M. Hartmann *, James Allen

Department of Psychology, University of Alaska Fairbanks, P.O. Box 756480, Fairbanks, AK 99775-6480,

USA

Received 28 March 2000; accepted 12 June 2002

Abstract

The photoperiod model of seasonal affective disorder (SAD) suggests that SAD is caused by

abnormal responses to seasonal changes in day length. Clarifying the utility of event-related

brain potentials (ERPs) as diagnostic aids or measures of therapeutic efficacy in SAD requires

understanding the range of naturally occurring seasonal patterns of variation in human

responses. This investigation studied ERPs from non-patients (402 from men, 415 from

women) during the pronounced photoperiod variation of the Alaskan subarctic where light

availability ranges from 3.20 h in winter to 21.98 h in summer. ANOVA showed significant

(P�/0.03) main effect of photoperiod in the amplitude and latency of P300 responses, as well

as a main effect of sensory modality (P�/0.002). There was neither a main effect of gender,

nor any significant gender-interactive effect in ERP responses. In clients with SAD, the ERP

variability attributed to seasonal photoperiod remains to be clarified. # 2002 Elsevier Science

B.V. All rights reserved.

Keywords: Event-related brain potentials; P300; Season; Gender; Seasonal affective disorder

1. Introduction

The P300 component of event-related brain potentials (ERPs) was first reported in

the 1960s (Sutton et al., 1965). Since its discovery, P300 has become considered a

* Corresponding author. Tel.: �/1-907-474-1989; fax: �/1-907-474-5781

E-mail address: [email protected] (A.M. Hartmann).

Biological Psychology 60 (2002) 151�/171

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0301-0511/02/$ - see front matter # 2002 Elsevier Science B.V. All rights reserved.

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‘cognitive’ neuroelectric event because it is generated in psychological tasks that

require discrimination of sensory stimuli along a perceptual dimension (Loveless,

1983; Squires et al., 1977). The allocation capacity model of attention and

immediate memory explains the role of the P300 component during psychological

tasks, through the model’s basic information-processing mechanisms (cf. Polich and

Kok, 1995). Although P300 is usually viewed within a cognitive context, a growing

body of literature notes that a substantial portion of variability in P300characteristics appears related to the biological arousal state of the subject. These

state fluctuations can be induced by environmental factors, or ‘biological determi-

nants’, in that they affect the organism’s physiological state as a whole, and

therefore, affect its capability to engage in cognitive operations (Polich and Kok,

1995).

1.1. Background to the problem

Evaluation of P300 within a cognitive context requires consideration of whether

changes observed in P300 characteristics occur due to cognitive events, or are instead

related to biological determinants. Polich and Kok (1995) define some biological

determinants as general , meaning the effects are not restricted to the population of

neurons influenced by P300 task-specific variables. Other biological determinants are

defined as specific , meaning they effect the same population of neurons influenced

by P300-specific task variables. Biological determinants that influence P300

responses are also organized into natural or environmentally induced categories.Natural determinants that influence the P300 response include circadian and

ultradian rhythms, food ingestion, preferred time of activities, menstrual cycle,

and season. Environmental determinants, or stressors, include exercise, sleep

deprivation, and psychoactive substances (e.g. caffeine, nicotine, alcohol). The

present investigation contributes to a better understanding of how the general,

natural biological determinant of seasonality affects P300 responses in an extreme

northern population.

1.2. Relevant prior studies

Previous research on seasonality and P300 was prompted by initial findings that

visual, but not auditory P300 amplitude enhanced in patients receiving light therapy

for seasonal affective disorder (SAD) (Duncan and Rosenthal, 1986; Deldin,

1990Duncan et al., 1990Duncan et al., 1991). In one study, an increase in

visual P300 amplitude was observed in a clinical SAD group (n�/7) but not in a

non-clinical control group, and the increase in visual P300 amplitude was

directly proportional to the anti-depressant effects of light therapy (Duncan andRosenthal, 1986). Subsequent studies have explored the relationship between

season and P300 responses in healthy subjects, and are reviewed here in

chronological order.

Deldin et al. (1989a,b, 1994) and Deldin (1990) studied archival data from 88

normal subjects (48 women) in metropolitan Washington, DC. Each subject was

P.P. Shelton et al. / Biological Psychology 60 (2002) 151�/171152

tested one time, and testing occurred at different times of the year, using both an

auditory and a visual ERP oddball protocol. Season was defined on a solar-basis as

‘‘average amount of sunlight per month’’ (Deldin et al., 1994). Another natural

determinant, recent sunlight, was also included in an attempt to distinguish long-

term from short-term sunlight influences. The solar-based definition of sunlight was

‘‘minutes of sunlight, sunrise to sunset, minus minutes of cloud cover’’ (Deldin et al.,

1994). In a regression analysis, both gender and minutes of daylight predicted visual

P300 amplitude. The authors concluded that (1) visual P300 varied with light and

amplitude was larger in summer and winter, and (2) visual P300 amplitude was

larger in women compared to men. They found no interactive effects for sensory

modality with either gender or season, and no main effects for P300 latency. The

unanticipated finding of greater P300 amplitude in winter, the season of photoperiod

minima, led the authors to speculate that some characteristic of seasonality other

than simply the amount of sunlight had a mediating effect on the P300 response.

They speculated that ‘‘if P300 can respond to light exposure in normal subjects, it

apparently requires longer time length of season, suggesting that normal subjects

may be better protected against short-term light changes than patients’’ (Deldin et

al., 1994).

Polich and Geisler (1991) used archival data collected in San Diego using a cross-

sectional sample of subjects, not screened for psychiatric disorder, each of whom was

tested once, using only an auditory discrimination protocol. Auditory P300

amplitude was greater in spring, and in women; there was no effect on latency.

Average sunlight for seasons was not reported and the variable season was defined

differently, overlapping with season as defined by earlier researchers (Deldin et al.,

1989a,b).Bush (1993) tested a small non-clinical sample (n�/4 women, four men) living in

the Alaskan subarctic monthly for 12 months. Using an auditory and a visual

discrimination paradigm, a main effect for month emerged on both P300 amplitude

and latency in a repeated measures ANOVA. With season defined using 1-month

windows around equinoxes and solstices, an unrotated principal components

analysis suggested that photoperiod was not as heavily weighted as the geomagnetic

field characteristics.

Kosmidis et al. (1998) tested 32 normal people living in the metropolitan

Washington, DC area (n�/15 women), who were screened for psychiatric disorder

by a clinical psychologist. Each was tested in two seasons, using both auditory and

visual discrimination protocols. The solar-based definition of seasons used corre-

sponded to that of Deldin et al. (1994) and Bush (1993). Unfortunately, no fall

season data were included due to small sample sizes. Recent sunlight was analyzed as

a potential explanatory factor. Data were analyzed using a modality�/specificity

model employing a series of seasonal pairwise comparisons. P300 amplitude varied

with season, and seasonal variation was greater in women. The finding that P300

amplitude did not correlate with recent sunlight again suggests that factors other

than recent sunlight may account for the seasonal variation in amplitude. The

researchers speculated that the lack of a relationship between recent sunlight and

P.P. Shelton et al. / Biological Psychology 60 (2002) 151�/171 153

P300 responses might reflect a fundamental, autonomous built-in compensatory

mechanism to ensure constancy of behavioral competence in non-hibernating

species.

1.3. Present study

Studies of the relationship of event-related responses to biological determinants

are needed (Polich and Kok, 1995). The current study extends this line of

inquiry using general, natural biological determinants as independent variables. It

replicates studies (Deldin et al., 1994) on seasonality and P300 using a larger sampleand data spanning all four solar-based seasons (Kosmidis et al., 1998). Importantly,

the ERP recordings were obtained from a non-clinical sample in the Alaskan

subarctic, where extreme variation in seasonal photoperiod ranges from 3.20 h at

winter solstice to 21.98 h at summer solstice. This affords study of the impact of large

seasonal variation in light on P300 and of human adaptation in extreme

environments.

2. Methods

2.1. Subjects

Subjects were 442 university students, staff, and faculty residing in Fairbanks, AK,at 648 north latitude, during 1988�/1999. All subjects were recorded during their

normal workday. Earlier samples from this Alaskan subarctic population (Bush and

Emery, 1985, 1987) displayed no significant change in P300 amplitude or latency

after an 8-h or 12-h work shift.

Inclusion criteria for the study were age 18�/38, functionally normal vision and

hearing, and self-report of absence of psychiatric disorder, of good general physical

health, and of not currently using psychoactive substances. Handedness and

ethnicity were not reliably coded in the archives and could not be included asvariables.

The data analyzed were extracted from archived ERP recordings of individuals

who met the inclusion criteria. Archives contained 229 female auditory ERPs (age

M�/24.25, SD�/5.7), 213 male auditory ERPs (age M�/23.54, SD�/4.98), 186

female visual ERPs (age M�/24.19, SD�/6.16), and 189 male visual ERPs (age M�/

23.81, SD�/5.02).

Only ages 18�/38 years were selected for analysis, as the P300 latency-to-age

relationship appears to be a quadratic function, with shortest latency in early teensand marked increase in latency in older adults (Polich et al., 1985). Mean ages in this

sample were similar in mean age to the ‘younger group’ sample (22.8 years) in

previous research of age-related changes in event-related potentials (Ford et al.,

1979) and to subjects in previous studies of seasonality and P300 (e.g. Deldin et al.,

1994; Kosmidis et al., 1998).


Although subjects were sampled across all four seasons, sample size varied

significantly across the four photoperiods (x2�/33.277, df�/3, P B/0.05)1, ranging

from 143 records during photoperiod minima (Nov�/Dec�/Jan) to 258 records during

rising photoperiod (Feb�/Mar�/Apr)2.

2.2. Design

Two 2X4X2 (sensory modality X photoperiod X gender) between groups ANOVA’s

tested P300 amplitude (P300 Amp) and P300 latency (P300 Lat) as dependent

variables. Cell sizes were not equal.

2.3. Independent variables

Independent variables included one fixed factor, sensory modality, and tworandom factors, photoperiod and gender. At 648 north latitude, photoperiod

(defined as length of possible daylight between sunrise and sunset) varies from

3.20 h at winter solstice to 21.98 h at summer solstice. In this study, the four seasons

were defined using solar-based photoperiods:

1) Minima (winter solstice, 9/1 calendar month; U-shaped): 3.20�/8.13 h.

2) Rising (vernal equinox, 9/1 calendar month; /-shaped): 8.13�/17.78 h.

3) Maxima (summer solstice, 9/1 calendar month; þ-shaped): 17.78�/21.98 h.

4) Declining (autumnal equinox, 9/1 calendar month; \-shaped): 8.13�/17.78 h.

In prior work at this latitude with samples of individuals with SAD (Booker and

Hellekson, 1992; Hellekson, 1989; Hellekson and Rosenthal, 1987) the photoperiod

shape and direction of change were suspected to have a role in temporally relatedchanges in SAD symptomatology and in seasonal pattern of suicidal behavior

observed. Therefore, rising and declining photoperiods were considered separately.

Sensory modality refers to the type of discrimination task performed at the time of

ERP recording. The auditory modality required the subject to discriminate and

detect a sound, while the visual modality required the subject to discriminate and

detect a visual pattern.

1 Cell sizes varied for each of the two dependent variables, P3A and P3L (32 cells), with gender treated

as a within-factor. While the k-group MANOVA is preferred (Stevens, 1979, 1986), with unequal cell sizes

robustness is not guaranteed. The largest cell (declining photoperiod, auditory mode, female�/84)

compared to the smallest cell (declining photoperiod, visual mode, male�/28) yields a size ratio of 3.0.

However, such crossed intraphotoperiod contrasts (male visual to female auditory) are not part of the

analytical model.2 The intra-cell size ratios range from 1 (rising photoperiod, visual 64/64) to 1.61 (declining

photoperiod, auditory 84/52). The ratio of 1.61 is slightly greater than the ‘less than 1.5’ guideline

recommended by Stevens (1986) for the customary MANOVA. Based on the smallest n�/28 cell size, the

minimum detectable differences achievable, at 95% confidence, are: d�/2.85 mV P300 amplitude and d�/

24.94 ms P300 latency (Salkind, 1997).


2.4. Dependent variables

The dependent variables were two characteristics of the P300 component of the

ERP. The P300 component was defined as the largest, positive-going peak after the

N1-P2-N2 complex (N1�/1st negativity, P2�/2nd positivity, N2�/2nd negativity)

which was followed by a long-lasting slow wave and which was evident in both the

left and right channels during the signal-attended and -detected condition (see Fig.

1). Amplitude of the P300 response, measured in microvolts (mV), was defined as

maximal P300 voltage beyond the pre-stimulus baseline (Bush, 1993; Polich and

Kok, 1995). Latency of the P300 response, measured in milliseconds (ms), was

defined as the elapsed time from onset of sensory stimulus to maximal P300 response

(Bush, 1993; Polich and Kok, 1995).

Electrode impedances at Cz, left and right mastoid (A1 and A2), and forehead

ground were reduced to less than 5000 ohms. Electroencephalographic (EEG) signals

were amplified to 10 mV per division on-screen, filtered from 1 to 100 Hz (half-

amplitude settings) and digitized at 8 bits over 18 kHz. Waveforms were visually

inspected for gross artifacts, which were removed prior to averaging. Rare target

trials (15% probability) were averaged for left and right separately; frequent trials

were not analyzed further. For each channel (Cz-A1, Cz-A2), P300 amplitude and

latency were obtained as described below, to produce two measures of amplitude and

latency under both auditory and visual presentation conditions.

Fig. 1. Example of an event-related potential recording that is produced by the Quantun84, using the

recording parameters described. Grand means for this large sample size exceed the memory capacity of the

Quantum84 (limited to 8) and so are not presented.


2.5. Waveform analysis

One second of time-captured 4-channel EEG recording began 15 ms prior to the

onset of each sensory stimulus. The data were signal-averaged via average

summation method (Fujikake et al., 1989) over each sensory attention and signal

detection task. The task consisted of 350 sensory signal presentations of which 85%

were to be ignored and 15% were to be detected. This produces one signal-averagedwaveform for each of the four possible channels previously described. Using

unlinked mastoids permits treating left and right waveforms as replicates rather

than as split-halves, and avoids the error of pseudoreplication (Hurlburt, 1984) from

using interconnected units.

At archiving, the amplitude and latency characteristics of each signal-averaged

P300 component obtained during the sensory discrimination trials were recorded.

The P300 component was identified via visual inspection, applying P300 defining

criteria to the recordings from the signal-detected condition.P300 amplitude was measured with two on-screen cursors: the first cursor

identified the pre-stimulus baseline as time-zero; the second cursor applied the first

derivative test for relative extrema (Kohlman and Denlinger, 1988). Earlier research

with extreme northern samples found measuring amplitude from a defined pre-

stimulus baseline to the relative maxima of the averaged waveform maximized

analytical power and reduced probability of type I error (Bush, 1993). The 15 ms of

recording prior to stimulus onset was the designated pre-stimulus baseline, and on-

screen baseline offset correction was achieved through individual visual inspection ofwaveform. The baseline used in the current recordings is comparable to the 20 ms

pre-stimulus baseline used by Giard et al. (1988) in topographic analysis of auditory

attention-related waveforms.

P300 latency was measured via two on-screen cursors: the first cursor identified

the sensory signal onset as time-zero; the second cursor measured elapsed time to

P300 peak amplitude. This approach has been judged well suited for evaluating

waveforms from normal, non-patient subjects (Bush, 1993; Picton et al., 1984a). The

definition of the P300 component used for these recordings uses a wide latencywindow since P300 latencies of B/250 ms have been reported for this age-group of

subjects (Picton et al., 1984b; Polich, 1989), and early latency windows, beginning at

B/250 ms, have previously been used (Giedke et al., 1981; Kutas et al., 1977).

Grand averages are not presented because the Quantum84 cannot export data to

ASCII files for analysis, and the Quantum84’s internal grand average procedure is

limited to eight waveforms (Cadwell Laboratories, 1988). This data set exceeds this

capacity.

2.6. Sensory signal detection tasks

The auditory oddball detection paradigm used required a subject to listen

binaurally, via balanced audiometric headphones (Amplivox† Audiocups), to a

sequence of 350 randomly generated tones presented at a rate of one per second, and

to maintain a silent running count of the number of target tones (2000 Hz, 15% of


trials) detected amid the tones to be ignored (1000 Hz, 85% of trials). Each tone had

duration of 0.3 s and was cosine-ramped with equal rise, plateau and decay times of

0.1 s. Tones were presented binaurally at 80 dB, which is slightly louder than a

normal conversational tone of 65 dB. All subjects received the same number of trials.

During a two-tone pre-test trial, all subjects reported being able to hear the tones

equally well in both ears, and could distinguish the target tone. All subjects

performed the auditory signal detection task accurately 9/1 target.The visual oddball detection paradigm required a subject to watch (via eye-level 49

cm monitor at a distance of 0.6 m) a series of 350 pattern-reversing black and white

checkerboard patterns, and to maintain a silent running count of the number of

target patterns detected. Using the trigonometric functions of right triangles (Smith,

1986) and the method described by Hubel (1988), the entire visual screen subtended

30.518 of visual arc. The pattern to be ignored (‘large’, 5-cm squares, 85% of trials)

subtended 6.58 of visual arc, and the target pattern (‘small’, 2.5-cm squares, 15% of

trials) subtended 2.68 of visual arc. During a two-screen pre-test trial all subjectsreported being able to easily see the difference in the two screen patterns and

affirmed that the screen of ‘small squares’ was the target. All subjects received the

same number of trials, and all subjects performed the task accurately 9/1 target.

The auditory and visual oddball detection tasks produce similar ERP responses

(see Fig. 2). However, Bush (1993) found sensory modality effects in an extreme

northern sample. On the basis of these findings greater visual than auditory P300

amplitude was anticipated and greater visual than auditory P300 latency was

anticipated. Therefore, P300 responses are analyzed separately for each sensorymodality.

2.7. Procedures

All recordings followed IRB approved protocols, and were obtained from

volunteers solicited from university faculty, staff and students. Students were

recruited from psychology courses, including upper division courses as well as

introductory courses, and some received modest course credit for participating.

None received monetary compensation. Original recruitment purposes varied (Bush,1993; Bush et al., 1991; Grubb et al., 1998; Zamora et al., 1992) and included

unpublished undergraduate Experimental Psychology course projects. All were

investigations of non-clinical populations. Each subject gave fully informed consent.

The experimenter greeted subjects in the psychology laboratory. The purposes and

procedures were explained, and the subjects had opportunity to have all questions

fully answered prior to signing consent. A registered nurse with board certification in

clinical neuroscience then interviewed subjects, for functionally normal hearing and

vision, and for subjective wakefulness, quality of last sleep epoch, or other factorsthat might warrant exclusion from normative investigation. Subjects were then taken

to the neuroelectrophysiological cubicle where all jewelry was removed, electrodes

were placed and impedances verified. The subject remained comfortably seated on an

anti-static chair, in the recording cubicle, along with all the recording equipment and

the recording technician. Overhead fluorescent lights were extinguished and a single


100 W incandescent bulb in a shielded table lamp located away from the subject and

equipment lighted the room. The auditory detection task preceded the visual

detection task, and both recordings occurred within 10 min of each other (cf. Bush,

1993). Live recordings were stored electronically for post hoc waveform analysis.

After debriefing, subjects were assisted in removal of the EEG paste and gel, given a

final opportunity to have questions answered, then thanked for their participation.

Fig. 2. The auditory and visual oddball detection tasks produce similar event-related potential recordings.

Within individuals, the visual P300 component is normally of greater amplitude and longer latency than

the similar auditory P300 component. In each modality, P300 latency was measured from stimulus onset,

and P300 amplitude was measured from a defined pre-stimulus baseline.


3. Results

3.1. Data analysis

Based on the smallest cell size, n�/28, the minimum detectable differences at 95%

confidence level are d�/2.85 mV for P300 amplitude and d�/24.94 ms for P300latency (Salkind, 1997). The option to equalize cell sizes by random deletion of cases

(Tabachnick and Fidell, 1996) was not exercised in order to maximally utilize the

available data. The distribution of P300 amplitude data was best normalized with

Kirk square root transform (SQRT (X�/1)) (Kirk, 1968), and the conventional

square root transform best normalized the distribution of P300 latency data. The

transformed data were used in the parametric analyses and the raw, untransformed

data, are presented in the graphs.

A general linear model k-group MANOVA using Pillai’s criterion and pooledeffect variances3 (Olson, 1974, 1976, 1979) was performed on normalized data using

SYSTAT 6.0 GLM (Tabachnick and Fidell, 1996). Post hoc univariate ANOVA

followed for the three main effects: photoperiod, sensory modality, gender. Each

ANOVA was followed by pairwise comparisons, with pairwise comparison probabil-

ities, using Tukey’s Honestly Significant Difference multiple comparison procedure.

3.2. P300 amplitude

A significant main effect of photoperiod was noted in P300 amplitudes for pooled

genders across modalities (F3, 813�/51.19, P B/0.01); HSD pairwise comparison by

least square means using model MSE of 3.103 noted that photoperiod maxima

(‘summer’) differed significantly (a�/�/0.523, P�/0.01) from declining photoperiod

(‘fall’). No significant main effect of gender was observed in pooled modalities

(F1, 815�/0.154, P�/0.69). The expected significant main effect of sensory modality

(F1, 815�/18.263, P B/0.01) was observed in ERP amplitude, and so are profiledseparately. A descriptive profile of auditory P300 amplitude by gender across

photoperiods is presented in Fig. 3; a descriptive profile of visual P300 amplitude by

gender across photoperiods is presented in Fig. 4.

As can be seen in Fig. 3, for the auditory modality alone, P300 amplitude showed

a significant main effect of photoperiod (F3, 434�/57.39, P B/0.01), a significant main

3 Since parametric analyses assume normally distributed data (Stevens, 1986; Tabachnick & Fidell,

1996), raw data distribution was assessed at the cell level using gamma statistics for skewness (G1) and

kurtosis (G2), following the criteria that if the interval of G1 or G29/2 standard errors does not include

zero, then the measure is considered extreme. If jG1j or jG2j�/1.0, then it is extreme enough for rejection

of normality assumption (Hurlburt, 1994). Of the 32 data cells, five P300 amplitude cells (15.6%) were

extreme, and four P300 latency cells (12.5%) were extreme. In all but one cell (rising photoperiod, auditory

modality, male subjects) the extreme cells differed in season and gender. Standard data transformations

were explored (Tabachnick & Fidell, 1996) for amplitude and latency responses separately and the final

transforms selected were those that minimized the number of non-normal cells.


Fig. 3. Seasonal profile of auditory P300 amplitudes, by gender across photoperiods using mean9/1

standard error of the mean, S.E.M.

Fig. 4. Seasonal profile of visual P300 amplitudes, by gender across photoperiods using mean9/1 standard

error of the mean, S.E.M.


effect of gender (F1, 434�/4.154, P B/0.05), and a significant interactive effect of

photoperiod and gender (F3, 434�/3.800, P�/0.01). For both males and females, the

mean auditory P300 amplitude was lowest during rising photoperiod (‘spring’) and

highest during photoperiod maxima (‘summer’). Within the auditory modality, the

differences in mean P300 amplitude between females and males were greatest during

photoperiod maxima (‘summer’, d�/2.93 mV) and photoperiod minima (‘winter’,

d�/2.00 mV); in both seasons, the mean auditory P300 amplitude was greater in

males.

As can be seen in Fig. 4, for visual modality alone, the P300 amplitude

demonstrated a significant main effect of photoperiod (F3, 367�/7.522, P B/0.01)

but no significant effect of gender (F1, 367�/2.429, P�/0.12), and no significant

interactive effect of photoperiod with gender (F3, 367�/1.417, P�/0.24). For both

males and females, the mean visual P300 amplitude was lowest during rising

photoperiod (‘spring’) and highest during photoperiod maxima (‘summer’). Within

the visual modality, the difference in mean P300 amplitude between females and

males was greatest during declining photoperiod (‘fall’, d�/2.55 mV); the mean P300

amplitude of females was greater than that of males.

3.3. P300 latency

No significant main effect of photoperiod was observed in latency of P300

component in pooled modalities and genders (F3, 813�/1.946, P�/0.12). However, a

significant main effect for gender was noted (F1, 815�/4.735, P B/0.05) as well as a

significant main effect of sensory modality (F1, 815�/492.01, P B/0.01). A descriptive

profile of auditory P300 latency by gender across photoperiods is presented in Fig. 5.

A descriptive profile of visual P300 latency by gender across photoperiods is

presented in Fig. 6.

As can be seen in Fig. 5 for auditory P300 latency alone, a significant main effect

of photoperiod was observed (F3, 424�/4.20, P B/0.05). For both males and females,

mean auditory P300 latency was shortest during photoperiod maxima (‘summer’).

There was no significant gender effect (F1, 434�/0.042, P�/0.83) nor was there a

significant interactive effect of photoperiod with gender (P�/0.30). The greatest

difference in mean auditory P300 latency between females and males was during

photoperiod minima (‘winter’, d�/11.20 ms); mean auditory P300 latency for

females was shorter than that of males.

As seen in Fig. 6 for visual P300 latency alone, a significant main effect of

photoperiod was observed (F3, 367�/3.868, P B/0.01) as well as a significant main

effect of gender (F1, 367�/14.587, P B/0.01) and also a significant interactive effect of

photoperiod with gender (F3, 367�/4.100, P B/0.01). For both females and males, the

mean visual P300 latency was longest during photoperiod minima (‘winter’). The

greatest difference in mean visual P300 latency responses between females and males

occurred during rising photoperiod (‘spring’, d�/31.60 ms).


4. Discussion

This research investigated the effects of photoperiod, gender, and sensory

modality on the P300 component of ERPs in a sample living in the extreme north,

which is an area of pronounced seasonal natural light variation. The major finding

of this study was that photoperiod functioned as a potent general, natural biological

determinant of characteristics of the P300 wave induced through environmental

variation. This finding replicates previous research with smaller samples at lower

latitudes, and extends this research by exploring more fully the interaction of

photoperiod with gender and sensory modality. The current findings have implica-

tions for the study of P300, of human adaptation to environments marked by

extreme seasonal variation in photoperiod, and of our understanding of mechanisms

that accompany seasonal behavior variation at extreme latitudes, including SAD. In

addition, the current findings replicate and extend the findings of gender effects

observed in previous research with P300. We interpret these results below beginning

with main effects, first discussing photoperiod effects, then gender effects, and then

sensory modality effects. We then speculate on the meaning of selected interaction

effects, and conclude with a discussion of theoretical and methodological implica-

Fig. 5. Seasonal profile of auditory P300 latency, by gender across photoperiods using mean9/1 standard



tions of the research, including limitations of the current study and implications for

the study of seasonal variation in behavior in extreme environments.

4.1. Photoperiod

Photoperiod effected P300 responses across gender and sensory modality, andphotoperiod interacted with gender and modality. For both women and men,

auditory and visual P300 amplitude displayed a similar general profile: higher

amplitudes during either extreme of photoperiod (minima or ‘winter’ and maxima or

‘summer’), and lower amplitudes in the other two seasons. This finding replicates the

findings of Deldin et al. (1994), who also reported higher amplitudes in summer and

winter, and lower amplitudes in fall and spring. However, Deldin et al. averaged

amplitude across sensory modalities. In the current investigation, sensory modalities

were also considered separately. The current results discovered sensory modality tointeract with photoperiod, across gender. For amplitude, both auditory and visual

modalities displayed higher amplitudes during either extreme of photoperiod, and

lower amplitudes in the other two seasons, however in the visual modality, the mean

amplitude during spring was significantly less than that of auditory modality. Only

fall displayed an overall seasonal pattern remained similar for both. Kosmidis et al.

Fig. 6. Seasonal profile of visual P300 latency, by gender across photoperiods using mean9/1 standard



(1998) lacked fall data needed to present an annualized seasonal profile, and Polich

and Geisler (1991) used different seasonal cut points in their research. Nonetheless,

Polich and Kok’s (1995) results also indicated a summer peak in P300 amplitude.

Previous research (Deldin et al., 1994; Polich and Geisler, 1991; Polich and Kok,

1995) has not identified a photoperiod effect on P300 latency, although Kosmidis et

al. (1998) did find some seasonal latency changes in the pairwise comparisons they

reported. The present investigation found that photoperiod had a significant maineffect for both auditory and visual P300 latency. One explanation for the current

finding regarding latency may relate to larger sample sizes and enhanced analytic

power. Alternatively, this finding may be due to the impact of extreme photoperiod

variation found at high latitudes. Further research is needed.

4.2. Gender effects

P300 amplitude and latency differed by gender in the current sample. The current

findings of greater auditory P300 latency in men replicated previous findings ofGolgeli et al. (1999) and Polich et al. (1988). In the current study, P300 visual latency

was also greater for men. These latency findings are also consistent with Deldin et al.

(1994) and Taylor et al. (1990), who reported greater latency among men across

modalities. The current findings that visual P300 amplitude in women was also larger

is consistent with the findings of Hoffman and Polich (1999), Osterhout et al. (1997)

and Taylor et al. (1990) who reported smaller P300 components in men.

The findings regarding amplitude are more complex. Consistent with the findings

of Golgeli et al. (1999) and Polich et al. (1988), the current data found visual P300amplitude larger for women. Deldin et al. (1994), Polich and Geisler (1991) also

reported greater P300 amplitude for women across sensory modalities. However, the

current study found greater auditory P300 amplitude for men. Further research is

needed to explore this gender by modality interaction effect.

With respect to the three other seasonal investigations being compared, Deldin et

al. (1994) did not observe an interaction of gender with photoperiod for P300

amplitude however, in the present investigation, gender was a significant interactive

effect with photoperiod for both auditory and visual P300 amplitude, and visualP300 latency but not for auditory P300 latency. This provides general support for the

Sex�/X�/Season interactions reported by Kosmidis et al. (1998) and Polich and

Geisler (1991). It should be noted however that the Kosmidis et al. study lacked fall

season data and the Polich and Geisler study used different seasonal cut points than

this study or that of Deldin et al. (1994). However, in this investigation and in

contrast to the findings of Kosmidis et al. (1998) gender was not a significant

interactive factor with photoperiod for the auditory P300 latencies. Further research

is needed for this complex interaction.Hormonal levels, menstrual cycling, and contraceptives are all potential con-

founds with the variable of gender in this study, which could potentially effect P300.

The current study included no measurement of hormone levels, or inquiry regarding

menstrual phase or contraceptive use of female subjects. However, no effects of

menstruation on P300 amplitude or latency have been found (Fleck and Polich,


1988). In a recent integrative review (Polich and Kok, 1995) of data from both

spontaneously cycling women as well as oral contraceptive users, P300 values from

an oddball task were consistent during bodily changes due to menstruation.

Kosmidis et al. (1998) also concluded that gender effects in ERP data are likely

due to factors other than gonadal hormones, and speculate on a relationship of ERP

to other gender-specific hormones or circannual biological processes that remain as

yet unidentified. These gender effects in the seasonal patterns of P300 responses mayhave implications for an understanding of gender differences in vulnerability to

SAD.

4.3. Sensory modality effects

This study replicated a consistent finding in the literature of greater visual than

auditory P300 amplitude (Bush, 1993; Clifford and Willison, 1992; Hillyard and

Kutas, 1983; Luo and Wei, 1999; Picton et al., 1984b; Roth et al., 1984; Teder-Salajearvi et al., 1999). The study also replicated earlier findings of longer visual than

auditory P300 latency (Deldin et al., 1994; Roth et al., 1984). This visual�/auditory

latency difference has been explained as due to volume�/conductor effects (Picton et

al., 1984b).

4.4. Limitations

This study explored the effect of photoperiod on auditory and visual P300

responses in a general university community sample living in the extreme north. Allfour photoperiod seasons were represented in the data, and gender and two sensory

modalities were evaluated separately. However, a number of significant limitations

exist.

Major technical limitations were associated with ERP recording methodology

used in this study, rendering these archival data severely limited by contemporary

recording standards (Picton et al., 2000). The Quantum84 system used in the study

had significant technological limitations. A limited number of recording channels

eliminated the possibility of monitoring extra-ocular movements. Eye blink artifactscan augment the P300 amplitude at Cz, and the degree to which these data are

contaminated by ocular artifact is unknown. Although a seasonal pattern in normal,

spontaneous eye blink rates has not been reported, Barbato et al. (1993) found that

spontaneous eye blink rates did not change in response to light therapy for either a

winter SAD clinical sample or normal controls. Additionally, the recording system’s

limited capabilities in real time common mode rejection may have yielded

artifactually shorter P300 latencies and/or higher amplitudes. Finally, the equip-

ment’s broader bandpass may have clipped P300 waveforms, yielding earlier andsmaller components. In addition, the use of Cz as a common referent, and the use of

gold-plated electrodes may have reduced P300 amplitudes. Finally, the short pre-

stimulus baseline used in this study may have been inadequate. Though subjects self-

reported absence of medical or psychiatric conditions, there was no structured

screening for medical or psychiatric disorder, therefore it is possible that some


individuals in the current sample were experiencing medical or psychiatric condi-

tions, including SAD or subsyndromal-SAD conditions. In addition, data on

ethnicity or handedness was not available in this archival sample. Finally, inquiries

about food ingestion or activity pattern were not made, nor measurement of core

temperature or other physiological variables that may have introduced extraneous

variance in the P300 measures (Polich and Kok, 1995).

Unequal subject cell sizes in the design resulted from the university academiccalendar and subject recruitment strategies. However, the smallest cell size, n�/28, is

sufficiently large under Central Limit Theorem (Hurlburt, 1998; Tabachnick and

Fidell, 1996) to estimate the population mean. Moreover, the most appropriate

analytical approaches to unbalanced designs were used. Nonetheless, the possibility

of selection bias remains.

Despite these many technical and methodological limitations, the current findings

converge with similar patterns of seasonal P300 responses reported in the existing

literature. Future studies using longitudinal within-subject designs are needed toaddress these methodological and technical limitations.

4.5. Relation of seasonal P300 variation to seasonal behavioral variation

SAD is an extreme form of seasonal behavior variation characterized by

depression with an onset and recovery that is temporally related to change in season

that is more prevalent among women than men (American Psychiatric Association,

1994; Lee et al., 1998). SAD symptoms have been investigated for their relationship

to the duration and intensity of light (Rosenthal et al., 1984, 1987). The P300 iswidely used to study human information processing and clinical conditions such as

schizophrenia and major depression, and one clinical study (Duncan et al., 1990)

suggested that the P300 response is sensitive to light. Duncan et al. (1990) recorded

the ERPs of SAD patients being treated with brief light therapy. They reported a

positive relationship between increased amplitude in visual P300 and degree of

clinical improvement, while auditory P300 amplitude is unaffected by light therapy.

This suggests sensory modality�/specificity in the underlying psychophysiological

responses. Similarly, the gender differences found in P300 responses to photoperiodand modality in the current study may have implications in our understanding of the

differential gender prevalence rates for SAD.

Although Duncan et al. (1990), Deldin et al. (1989a) observed P300 to vary with

light therapy in individuals with SAD, the research findings on the pattern of P300

response to natural light variation among non-clinical samples have been less clear.

Deldin et al. (1994) evaluated the impact on P300 for normal subjects of recent

sunlight (minutes of available sunlight minus minutes of cloud cover) separately

from photoperiod. They could not determine from this data what seasonalcharacteristic was responsible for seasonal P300 variation, concluding that some

correlate of season other than recent sunlight varied with P300. An earlier (Bush,

1993) 12 month longitudinal study of eight normal subjects in the Alaskan subactiv

concluded that month-by-month changes in the P300 could not be reasonably

explained by photoperiod.


Other studies have also suggested that recent sunlight alone is not the important

factor in seasonal variation. Kosmidis et al. (1998) also failed to support their

hypothesis that sunlight determined seasonal P300 variation. They draw from Polich

and Kok’s (1995) suggestion regarding seasons with increased light, activity level,

and arousal, and suggest that the seasonal effects on P300 may reflect fundamental,

autonomous built-in compensatory mechanisms that ensure constancy of behavioral

competence in non-hibernating species. Alternatively, Deldin et al. (1994) suggesteda yet unidentified factor, and Bush (1993) found that two measures of ambient

geomagnetic field were more heavily weighted factors than photoperiod in a

principal components analysis of ERP responses.

The current data suggests that the relationship of P300 responses to seasonality is

complex and mediated by both interactive sensory modality and gender effects. The

inconsistent findings for P300 and photoperiod in the existing research may reflect

the lack of control for these variables in the designs of previous studies.

Finally, the connection between the P300 component and its underlyingneurophysiological mechanisms is not yet clearly understood. One explanation for

seasonal behavior variation explores arousal level. Demonstration of such a direct

relationship between arousal and ERPs may prove difficult as arousal reflects tonic

changes while ERPs are phasic in origin (Polich and Kok, 1995).

4.6. Conclusion

The current research raises a number of important questions, most prominentlywhether cognitive processes related to P300 might also be sensitive to seasonal

variation (Deldin et al., 1994; Picton and Cohen, 1984; Polich and Kok, 1995). If this

is the case, P300 may function as a marker variable for the study of various aspects

of seasonal behavior variation. P300 may also have relevance in clinical research, in

that it may function as a marker for cognitive processes associated with SAD. The

current research can also provide preliminary baseline data with which to compare

the P300 seasonal profiles of a SAD clinical sample. Finally, in applied and clinical

research using between subjects designs, measurement of important biologicalvariables such as P300 may serve to reduce artifactual inter-group variability that

affects hypothesis-testing error rates (Hurlburt, 1998; Polich and Kok, 1995).

Despite the apparent complexity, clarifying the relationship of P300 to photoperiod

and other biological determinants remains an important challenge.

Acknowledgements

Portions of this work were the basis for a thesis submitted by Phillip Shelton inpartial fulfillment of the requirements of the M.A. degree in Community Psychology

from the University of Alaska, Fairbanks. Preliminary report of a portion of the

thesis work was presented via poster at the annual meeting of the American

Association for the Advancement of Science-Arctic Division, Fairbanks, AK

(September, 1998).


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