Psychological correlates of nonspecific electrodermal responses

Electrodermal activity (EDA) refers to the fluctuations in the skin electrical properties in response to sweat secretion. The term EDA was first introduced in 1966 by Johnson & Lubin, describing all electrical phenomena in skin [1]. Sweat glands, particularly the palmar and plantar eccrine sweat glands responsible for the psychological responses, are innervated by the sympathetic nervous system, and changes in EDA are thought to reflect sympathetic nervous system arousal associated with emotion, cognition, and attention [1]. Sweating as a result of the sympathetic nervous system activation and consequently sweat glands, significantly influences the EDA responses [2], but with different characteristics.

Skin conductance responses (SCRs) increase with the sweat ducts filling and recover when sweat is reabsorbed. The same mechanisms govern the skin potential responses (SPRs), but the SPRs are more complex [3], as they change in both positive and negative directions and produce monophasic, biphasic or triphasic responses [1]. Finally skin susceptance responses (SSRs) changes are associated with the moisture content or hydration of the skin [4, 5].

The simplicity and non-invasiveness method of recordings has made EDA a common tool within various fields and attractive for several uses such as in the field of psychophysiology [6], in the field of neurology [7], measurement of arousal [8], sweating estimation [9], stress assessment [10, 11], assessment of psychiatric disorders [12, 13], pain assessment [14, 15], and skin moisture assessment [4].

Short-lasting variations in EDA are known as the electrodermal responses. Mainly there are two types of EDA responses, specific electrodermal responses (S.EDRs)

and nonspecific electrodermal responses (NS.EDRs). S.EDRs are phasic changes in EDA that are associated with externally applied arousal stimuli [16]. On the other hand, NS.EDRs are responses that cannot be traced to any specific stimulation. Hence, they are called “spontaneous” or “nonspecific” responses [1].

The frequency of occurrence of NS.EDRs reflects an important psychophysiological dimension of individual differences, such as individuals showing high NS.EDRs frequency are found to differ from individuals showing low NS.EDRs frequency in EEG and behavioral measures of vigilance and attention [17, 18]. Moreover, subjects who exhibit a high NS.EDRs frequency are referred to as EDA “labiles,” whereas those that exhibit low NS.EDRs frequency are considered EDA “stabiles” [19]. Furthermore, NS.EDRs are predominately common in investigations of individual differences variables such as personality [20, 21], health vulnerability [22, 23], and aggressive or antisocial behavior [24].

The NS.EDRs, particularly NS.SCRs are defined and discussed in Boucsein et al [16], where NS.EDRs are explained as phasic increases in EDA that have the same appearance as stimulus-elicited EDA responses. However, they are considered tonic measures because they occur in the absence of external stimuli and in the absence of artifacts such as movements and sighs. NS.EDRs are usually expressed as the number of responses per unit of time (minute) and can be computed as an average over several intervals. Although, the minimum amplitudes of nonspecific SCRs is defined as 0.01 for computerized scoring and 0.05 μS for hand scoring NS.EDRs records [16], the author could not find any literature, which defines the amplitude of nonspecific SPRs and nonspecific SSRs. Therefore, all the NS.EDRs (NS.SCRs, NS.SPRs and NS.SSRs) that occurred in the absence of external stimuli and in the absence of artifacts were simultaneously recorded, even NS.SCRs with amplitude larger than the defined values.

A feature of EDA, which to the author’s knowledge is not studied before, is the investigation in NS.EDRs (which occurs in the absence of external stimuli) at two different resting phases. The main aim of this study was to compare variations (in terms of amplitude, frequency and time components) in NS.EDRs at two different (pre and post of an external stimulus) resting periods through simultaneously recording the three EDA (skin conductance (SC), skin potential (SP) and skin susceptance (SS)) parameters at the same skin site.

Skin complex admittance (SY) and SP were simultaneously recorded at the same electrode on the same skin site by using a PC-based EDA system. It was similar to the system presented in Tronstad et al [9] and Bari et al [25], consisting of a small front-end electronic box connected by means of a National Instruments DAQ card-NI USB-6211 to a PC laptop running custom-written software in LabVIEW, version 14. A three-electrode measurement setup was employed, which was composed from one measuring electrode (M), one reference electrode (R), and a current-sink electrode (C). The current sink electrode, together with the reference electrode, served to provide a unipolar AC SC measurement below the measuring electrode.

Simultaneously, the DC voltage between the measuring electrode and the reference electrode is utilized for SP measurement. Also a Howland current source was utilized as in Tronstad et al [9]. A 200 mV digital sine wave was produced via the PC, under control of LabVIEW software, converted to analog, and then fed to the Howland circuit (front-end electronic box) by the DAQ card. The Howland circuit in turn delivered a 20 Hz AC current of about 20 μA, through the measuring electrode to the skin. The DAQ card received the analog signals back from the skin through the front-end electronic box and converted it to the digital form. Then the digitized signals were processed by differentiation in the PC LabVIEW program, and separated into a DC component for SP and an AC component for SC from the real part of the SY signal and SS from the imaginary part by means of phase-sensitive rectification.

Three electrodes were placed on one arm of the test subjects at three different skin sites. The M electrode was placed on the hypothenar site of the palm, the R electrode on the apex of the elbow, which is an electrodermally inactive area as recommended in [26], and finally the C electrode on the underarm between M and R. Although abrasion [27] and skin drilling [28] were recommended as a pretreatment for the inactive site, no pretreatment of the skin was used in this study to avoid any risk of contamination.

The employed electrodes were Kendall Kittycat 1050NPSM Ag/AgCl solid gel ECG neonatal electrodes with an active electrode area of 5.05 cm². These electrodes were chosen because they cause no or minimal wetting of the skin [29]. In addition, they are better suited than wet gel electrodes for EDA measurements [30, 31], and hence are crucial for obtaining accurate EDA results.

Test subjects and study protocol

A total of 50 apparently healthy volunteers (25 female and 25 male) ranging in age from 18 to 66 years (mean 24.96 years) were enrolled in this study. All participants were recruited from the University of Zakho and all of them gave written informed consent before taking part in the study.

All the participants were requested to sit quietly in a chair during the experiments in a soundproof room. The room temperature was maintained (22–23 °C), as recommended by Boucsein [1]. After a general introduction about the purpose of the experiment, the electrodes for the aim of EDA recordings were appropriately placed on one of the subjects’ hand. Before recording, 5 min were allowed for EDA electrodes stabilization after electrode application on the participants’ hands, and then NS.EDRs (NS.SCRs, NS.SPRs, and NS.SSRs) were simultaneously recorded at two different resting periods for 2 minutes (1 minute pre and 1 minute post a specific stimulus) as illustrated in Figure 1. In order to produce S.EDRs between the two resting periods, the participants were asked to answer a mathematical task (subtract seventeen successively from a starting number of 100) during 5 seconds. The purpose of using the external stimulus was only to separate the two resting periods and to show the pattern of NS.EDRs in pre and post of S.EDRs; therefore, all the recorded S.EDRs were ignored. Any speaking was not allowed for participants, and they were asked to relax and to avoid bodily movement, during the whole session of EDA recordings.

Fig.1

The purpose of the present study was to examine nonspecific electrodermal responses (NS.EDRs) at two different relaxation periods (pre and post of a specific stimulus) and find out whether there are any difference (in terms of amplitude, frequency and time components) between NS.EDRs that were recorded post of the stimulus compared to those measured pre of the stimulus, through simultaneously recording the three EDA (SC, SP and SS) parameters.

The study results suggest the possibility of changes in frequency of responses, time components and amplitude of NS.EDRs measured in the second resting period (post of the math task (stimulus)) in contrast to NS.EDRs recorded in the first period. However, there was great disparity among the test subjects according to the data seen in Tables 2, which is due to individual differences (labiles and stabiles).

Moreover, Nikula et al [32], indicated that the observed NS.EDRs during resting conditions are connected with conscious rumination on motivationally relevant but unrealized goals and intentions. Since such rumination could be considered an effortful process, NS.EDRs may reflect arousal in the service of increased cognitive capacity during rumination. Therefore, stable and consistent individual differences in resting NS.EDRs lability may index differential propensities toward effortful ideation [33]. NS.EDRs lability is certainly associated with self-reports of emotional ideation during relaxation conditions [34] and with observer ratings of active suppression of negative thoughts while anticipating an aversive stimulus [35].

It should furthermore be noted that the frequency of NS.EDRs (both NS.SCRs and NS.SPRs) was changed in the second resting period, following the math task as indicated by Figures 2 and 3. This means that there should be a psychological reason, which causes these changes; although, such changes were statistically insignificant (p>0.05). In addition, the analysis with ICC (Table 3) showed that the level of reliability, which reflects both degree of correlation and agreement between measurements of both NS.SCRs and NS.SPRs obtained from the two resting periods is from "good" to "excellent". According to Bernstein [37] the status of a subject in terms of NS.EDRs frequency depends on the conditions or occasion under which the frequency is obtained, then the interaction of subjects and conditions or subjects and sessions can be major contributors to changes in NS.EDRs frequency, and this frequency may reflects a trait-like characteristic of subjects.

The results for mean NS.SCRs amplitude, which allows for determining the total amount of nonspecific changes in EDA [1], presented in Figure 4, indicate that there is a significant (p<0.001) difference between mean amplitude of NS.SCRs measured in the first and second resting periods. In addition, the median values of NS.SCRs amplitudes were decreased in the second relaxation period after the math task. This reduction trend may be due to habituation in the individuals’ reactions to external stimuli, leading to a decrease in the amplitude of the NS.SCRs. Furthermore, this also may be due to change or decrease in the level of stress response of individuals with the passage of time, since EDA responses are strongly associated with mental stress [37]. The same results was also found with simultaneously measured NS.SPRs (Figure 5), in which the amplitude of NS.SPRs is significantly (p<0.005) decreased in the second resting period.

Data of the present study also point to changes in time dependent EDA scores. Figure 6 shows rise time of NS.SCRs. It can be seen that, rise time of the responses is decreased in the second resting time following the math task. This suggests that, the shorter rise time is associated with the weaker NS.SCRs [25]. Figure 7 indicates a significant (p<0.001) reduction in mean SPRET value in the second period, although more negative SPRET values are obtained in the first period. This means that in the first period, some of the NS.SPRs peak at a later time than the NS.SCRs peak (negative SPRET) [29], whereas the negative SPRET values is reduced in the second period, which mean that the NS.SPRs peaked earlier than the NS.SCRs peak.

The study results (see Figure 8 for example) show that SS is a more robust parameter than SC and SP in response to nonspecific stimuli, since no NS.SSRs greater than 0.02 μS were detected in any participant, neither in the first nor second resting periods. This means that SSRs are not influenced by nonspecific stimuli. Moreover, the nonspecific stimuli may not lead to changes in skin hydration as a result of sweat secretion and then cause changes in SS (as noted in this paper, SSRs changes are associated with the moisture content or hydration of the skin), because these stimuli are very fast and short and perhaps there is not enough time for skin to undergo such changes.

The subjects’ NS.EDRs were rated to be significantly more intense at the first resting period (pre of the specific stimulus) of the experiment compared to the NS.EDRs recorded in the second resting periods (post of the specific stimulus) as indicated by NS.SCRs and NS.SPRs. Moreover, the NS.EDRs that were measured at the second resting period, were different in frequency of responses and time components and of smaller amplitude compared to those detected at the first resting period. NS.SSRs recorded from all the participants were very small or even not detectable, and found to be robust with respect to nonspecific stimuli. This suggests that, the role of SS is less important in analysis of NS.EDRs with respect to the SC and SP at low frequency (20 Hz AC current). This is important to consider in the recording or analysis of NS.EDRs.

The computed NS.EDRs, in particular NS.SCRs and NS.SPRs could be of physiological interest and be used to study the electrodermal responses in detail. In addition, such responses may be used as a useful measure of arousal and in assessing individual differences in feelings of excitement or stress under various conditions due to their fast response and sensitivity.