Emotive interference during cognitive processing in major depression: An investigation of lower alpha 1 activity

Journal of Affective Disorders 141 (2012) 185–193

Contents lists available at SciVerse ScienceDirect

Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad

Research report

Emotive interference during cognitive processing in major depression: An investigation of lower alpha 1 activity R.A. Segrave a,⁎, R.H. Thomson a, N.R. Cooper b, R.J. Croft c, D.M. Sheppard d, P.B. Fitzgerald a a b c d

Monash Alfred Psychiatry Research Centre, The Alfred and Monash University Central Clinical School, Victoria, Australia Centre for Brain Science, Department of Psychology, University of Essex, Colchester, United Kingdom Department of Psychology, University of Wollongong, New South Wales, Australia School of Psychology and Psychiatry, Monash University, Victoria, Australia

a r t i c l e

i n f o

Article history: Received 18 October 2011 Received in revised form 5 March 2012 Accepted 5 March 2012 Available online 24 April 2012 Keywords: EEG Major depression Lower alpha 1 Working memory Emotional-cognitive interaction Information processing bias

a b s t r a c t Background: Individuals with Major Depressive Disorder (MDD) tend to be more susceptible to distraction by negative emotional material than their non-depressed counterparts. This extends to an enhanced vulnerability to interference from mood-congruent stimuli during cognitive processing. The current study investigated the electrophysiological correlates of competing cognitive and emotional processing demands in MDD. Methods: Event-related alpha activity within the lower alpha 1 band was examined during the online information retention phase of a non-emotive WM task with extraneous emotional stimuli (positive, negative and neutral) presented as background images. EEG activity over posterior parietal cortex was compared between 15 acutely depressed and 16 never depressed righthanded women. Results: A valence specific dissociation in lower alpha 1 activity was observed between the two groups, consistent with greater attentional resource allocation to positive distracters in control participants and to negative distracters in MDD participants. No group differences were seen when neutral distracters were displayed. Conclusions: These results demonstrate that activity within the lower alpha 1 band is sensitive to competing emotional and cognitive processing demands and highlight the importance of posterior parietal regions in depression-related susceptibility to affective distractibility during cognitive processing. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Patients with Major Depressive Disorder (MDD) display an increased susceptibility to distraction by mood-congruent material (Leppanen, 2006). This increased affective distractibility contributes to numerous aspects of depressive psychopathology including inability to disengage from negative thought processes (i.e. depressive ruminations) and preferential recall of negative memories, and is thought to play a critical role in the

⁎ Corresponding author at: Monash Alfred Psychiatry Research Centre, First Floor, Old Baker Building, The Alfred, Commercial Rd Melbourne, Victoria, Australia, 3004. Tel.: +61 3 9076 8538; fax: +61 3 9076 6588. E-mail address: [email protected] (R.A. Segrave). 0165-0327/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jad.2012.03.004

maintenance of depressive episodes (Gotlib and Joormann, 2010). Interference from extraneous (i.e. non-task related) negative stimuli and thought processes can also impact upon the efficiency of cognitive processing (Joormann and Gotlib, 2008; Ladouceur et al., 2005). This can further impair already compromised cognitive functioning in MDD and interfere with the ability to maintain attention on goal-directed behaviours (Rogers et al., 2004). The impact of heightened emotional distractibility on cognitive processing in MDD has been the focus of a small number of recent fMRI investigations (Dichter et al., 2009; Fales et al., 2008; Wang et al., 2008) which have identified functional abnormalities in several brain areas. However, an understanding of the neural mechanisms through

186

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193

which brain activity related to the salience of emotive distracters interferes with cognition remains lacking. Electroencephalography (EEG) has previously been used to explore the psychophysiological correlates of cognitive processing of emotive stimuli in MDD (Deldin et al., 2001; Shestyuk et al., 2005; Siegle et al., 2010), but studies specifically focussed on the influence of emotive stimuli on otherwise non-emotive cognitive processing have not yet been conducted. Thus, the current study aimed to use EEG to investigate the neural correlates of interference from extraneous emotive material on cognitive processing in MDD. We chose to focus on working memory (WM), the limited capacity cognitive system that supports the temporary online retention and manipulation of goal-related information (D'Esposito et al., 2000). As WM is a limited capacity system, efficient WM processing relies upon intact cognitive control which supports the ability to maintain attentional focus on stimuli relevant to immediate cognitive or behavioural goals, while concurrently inhibiting any distracting extraneous processes or stimuli (Hasher and Zacks, 1988), (Hasher and Zacks, 1988). Attenuation of this cognitive control (i.e. the ability to appropriately direct attentional resources) has been proposed to underpin heightened affective distractibility in MDD (Fales et al., 2008). EEG studies in both healthy controls and patients with MDD have found that alpha activity is reliably modulated during WM processing (Jensen et al., 2002; Segrave et al., 2010). Much of this work has utilised the Sternberg WM task, a delayed match to sample paradigm which temporally separates various aspects of WM processing (i.e. encoding, online information retention, retrieval and response) allowing for their individual analyses. The retention period of the Sternberg WM task is specifically associated with active online maintenance of previously encoded material and concurrent inhibition of extraneous stimuli. Numerous investigations have documented a substantial increase in alpha activity during the retention period (Jensen et al., 2002; Klimesch et al., 2007) which is thought to reflect maintenance of focused attention on a previously presented memory set and simultaneous inhibition of competing/non-task related processes and stimuli. For the purposes of the current investigation we developed an emotionally contextualised version of the Sternberg WM paradigm by superimposing WM stimuli on images of varying valence from the International Affective Picture Scheme (Lang et al., 2005). This type of paradigm bears some relation to real-world functioning whereby MDD patients must perform cognitively demanding tasks (e.g. execution of activities of daily living) despite preoccupation with negative thought processes, internal mood state and environmental stimuli. We focused our exploration on the modulation of alpha activity during the retention period under the assumption that interference effects will likely occur when participants are attempting to maintain attention on previously encoded memory stimuli and are concurrently confronted with distracting emotive images. Moreover, we have focused analysis on the lower alpha 1 subband. 1 Activity with this subband has been found to desynchronise specifically in response to stimuli that are not directly relevant to the task at hand, such as a warning 1 Please refer to the Supplementary Results for analysis of activity within the upper alpha, lower alpha 2 and theta subbands.

signal preceding target stimuli (Klimesch et al., 1998), and is thought to be functionally related to attentional processing (Klimesch, 1999). As posterior parietal cortex is a critical node within attentional control circuitry (Culham and Kanwisher, 2001), is highly sensitive to distraction (Colby and Goldberg, 1999) and the emotional salience of visual images (Colby and Goldberg, 1999; Culham and Kanwisher, 2001; Junghofer et al., 2001) and previous investigations have reported greatest modulation of alpha activity during the information retention phase of WM over parieto-occipital scalp sites (Jensen et al., 2002; Michels et al., 2008) we focused our analysis on scalp sites across this region. Finally, while the majority of previous studies in this area have explored the comparative effects of negative and neutral distracters, we also included a positive condition to more fully explore the role of emotional valence on susceptibility to affective interference. In keeping with the results of previous behavioural studies (Ladouceur et al., 2005; Williams et al., 1996) it was hypothesised that, relative to non-depressed controls, MDD participants would experience greater interference during cognitive processing when WM stimuli were superimposed on negative images (compared with positive and neutral images), and that this would be reflected in reduced accuracy and increased response times. With respect to EEG activity, we hypothesised that MDD participants would show greater modulation of lower alpha 1 activity than controls in the presence of negative distracters, consistent with maximal affective distractibility in this condition. 2. Method 2.1. Participants Participants were 34 right-handed women aged between 21 and 59 years old. All reported no history of traumatic brain injury or neurological illness and had normal or corrected-tonormal vision. Eighteen were control participants with no history of mental illness. Sixteen had a pre-existing diagnosis of MDD, currently met criteria for a major depressive episode according to DSM-IV TR and had a ≥ 20 score on both the Montgomery–Asberg Depression Rating Scale (MADRS) (Montgomery and Asberg, 1979) and the Beck Depression Inventory — II (BDI-II) (Beck and Steer, 1984), consistent with a moderate to severe depressive episode. None of the MDD participants had a co-morbid anxiety disorder or history of mania, hypomania, psychotic symptoms, post traumatic stress disorder or obsessive compulsive disorder. None met criteria for substance dependence within the preceding 6-months. Data from three participants were later excluded due to excessive artefact within the EEG trace (one MDD) and technical error (two controls). This resulted in a final sample of 31 participants (16 controls and 15 MDD). The two groups did not differ in age (controls: 42.00 ± 13.27; MDD: 39.67± 10.91). Eight MDD participants were taking a stable dose of an antidepressant medication (three = venlafaxine; two = escitalopram; one = citalapram; one = fluoxetine; one = paroxetine). All other participants were free from psychoactive medications. The study received approval from the Alfred Human Research Ethics Committee. Participants provided written confirmation of informed consent prior to engaging the study protocol.

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193

2.2. Procedure During the first experimental session, all participants underwent a clinical interview to either confirm (MDD group) or exclude (controls) a diagnosis of MDD, to screen for additional Axis 1 disorders (Mini-International Neuropsychiatric Interview for DSM-IV; Sheehan et al., 1998) and to assess current levels of depressive psychopathology (MADRS and BDI-II). The Wechsler Test of Adult Reading (Wechsler Test of Adult Reading: WTAR; Wechsler, 2001) was used to estimate general intellectual functioning. The Edinburgh Handedness Inventory was used to confirm strong right-handed preference in all participants (Oldfield, 1971). All clinical scales, diagnostic questionnaires and cognitive tasks were administered by a single trained rater with extensive experience in their use. At a second experimental session, usually completed within 10 days of the first, EEG recordings were obtained at rest (three minutes eyes open and three minutes eyes closed) and during execution of a computerised version of the modified Sternberg WM task. All participants completed 10 trials of a neutral practice version of the WM task prior to EEG collection. They were additionally given the opportunity to repeat this sequence as many times as they felt was necessary to be able to comfortably execute the task. 2.3. WM task The WM task was a modified version of the Sternberg WM paradigm (Sternberg, 1966). Each memory set consisted of eight letters which were pseudo-randomly selected from a fixed pool of 15 consonants (B, C, D, F, H, J, K, L, N, R, S, T, Y, W, and Z). The number of stimuli in each memory set was based on unpublished pilot data and specifically chosen in order to induce effortful cognitive processing in both groups without overloading the WM capacity of MDD participants. Each trial of the WM task was superimposed upon a different picture from the International Affective Picture System (Lang et al., 2005). Forty images were chosen within each of three valence categories: positive, negative and neutral. Pictures within each valence category were balanced for arousal and female specific valence and arousal rating were used to guide image selection (see Supplementary methods). Each trial began with a fixation cross (800 ms) and immediately afterwards the background picture was presented for one second. At the end of this second, the memory set was superimposed upon the image for four seconds in a simultaneous horizontal arrangement. The memory set was then removed and the same background image remained visible throughout a three second retention period. At the end of the retention period a probe appeared and participants were asked to indicate via a ‘yes’ or ‘no’ button press with their dominant hand whether the probe had been present in the preceding memory set. Maximum response time (RT) was set at two seconds and responses outside of this time frame were eliminated from subsequent analysis. At the end of the response period the background image was replaced with a brief visual mask (116.67 ms) which was followed by a short break (1883.33 ms; blank screen) before the onset of the next trial (see Fig. 1 for task design). For each of the three valence categories two blocks of 20 trials were completed. The order in which blocks were presented was counter-balanced across

187

participants. The frequency of presentation, position within the memory set and use as a probe of each consonant was pseudo-randomised across trials and balanced between blocks. The probability that the probe was a member of the preceding memory set was 50%. A brief distracter task was presented between each block in order to minimise emotional flow-over effects between blocks of differing valence (Dichter et al., 2009; Wang et al., 2008); participants were shown a neutral image (landscape) with numbers superimposed upon it and given 20 s to determine how many numbers were on the image and how many of those were even numbers. A brief break was taken between each block, after completion of the distracter task. 2.4. EEG recording EEG's were recorded using a 64 channel stretch lycra Ag/Ag Cl electrode cap (Compumedics Quick-Cap). EOG was recorded from four facial electrodes positioned above and below the left orbit and adjacent to the left and right outer canthus of each eye. NeuroScan Acquire Software and a SynAmps 2 amplifier (Compumedics, Melbourne Australia) were used for all EEG acquisition. Impedances were below 5 kΩ at the beginning of each recording and were checked again at a mid-task break. Electrodes were referenced to a central in-cap reference (located between Cz and CPz). Data were digitised at 250 Hz with a bandpass of 0.1–100 Hz (24 dB/octave roll-off). 2.5. Data preparation Offline EEG analysis was performed using Scan 4.3 (Compumedics, Melbourne, Australia) and Matlab (The Mathworks, Natick, MA). Ocular artefact reduction was applied according to the method described in Croft and Barry (2000). Data were visually inspected and areas contaminated by non-cerebral artefact were rejected. EEGs were re-referenced offline to a common average reference. Only correct trials were included in the analysis. These were epoched into 10.8 s segments extending from the onset of the fixation cross to the end of the response period. In order to minimise filtering artefact, lower alpha 1 power (induced and evoked) was firstly calculated for each participant across the entire epoch and then the intervals of interest were extracted. This was performed using Scan 4.3 (Compumedics), an implementation that employs complex demodulation to calculate power, allowing simultaneous zerophase bandpass filtering (48 dB/oct) and signal envelope computation (Andrew, 1999; Otnes and Enochson, 1978). Power within a 600 ms reference interval (onset 200 ms following offset of the fixation cross and offset 200 ms prior to onset of the memory set) and sequential 1000 ms intervals throughout the retention period were used to calculate event-related alpha activity during each of the three seconds in the retention period. The terms event-related synchronisation (ERS) and event-related desynchronisation (ERD) refer to the percentage increase or decrease (respectively) in band power during a test interval compared to a reference interval. ERS/ERD%=(A−R) / R⁎100, where A is power within the specified frequency band during the epoch of interest and R denotes power within the same frequency band during a baseline/reference interval (Pfurtscheller and Aranibar, 1977). Using this formular, positive values represent synchronization (i.e. ERS) and negative values represent desynchronisation (i.e. ERD).

188

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193

Fig. 1. WM task design. A fixation cross (800 ms) was followed by a 1000 ms presentation of the background stimulus. The memory set was then superimposed on this image for 400 ms and was followed by a 300 ms retention period. The probe appeared for 2000 ms during which time participants responded via ‘yes’ or ‘no’ button press whether it was present in the preceding memory set. A brief visual mask (116.67 ms) was followed by a pause (1883.33 ms; blank screen) before onset of the next trial. Please note that the background image above is not contained within the IAPS library; it is an image held within the public domain and is depicted here in order to adhere to IAPS EULA restrictions.

2.6. Individualised lower alpha 1 delineation The boundaries of each participant's lower alpha 1 subband were delineated in Matlab (The Mathworks, Natick, MA) using Individual Alpha Frequency (IAF) as an anchor point and according to the method described in Klimesch (1999). For each participant resting data were collapsed across all electrodes and the beginning of the ascent (f1) and end of the descent (f2) of the alpha curve identified via visual inspection. Using a spline interpolated frequency band between f1 and f2, the mean of the product of frequency and amplitude was calculated. This weighted mean was then divided by the sum of the amplitudes to yield IAF. The lower alpha 1 band was then defined as: (IAF — 4 Hz) to (IAF — 2 Hz). Of note, mean IAF (and by extension the lower alpha 1 range) did not differ between the groups (controls= 9.31 Hz+ 1.03; MDD= 9.82 Hz+ 1.17).

distributed, non-parametric Mann U Whitney tests were employed for these analyses. In order to test for group by valence interactions lower alpha 1 activity during the positive condition was subtracted from activity during the negative condition and difference scores were compared between groups (i.e. MDD: pos-neg versus controls: pos-neg). As antidepressant medications have been shown to influence information processing of affective material (Harmer et al., 2009) an exploratory secondary-analysis was conducted to examine whether medicated and un-medicated MDD participants differed in their ERD/ERS. Finally, Spearman's rank correlations were used to explore relationships between lower alpha 1 activity, depression severity, reaction time and task accuracy across the whole sample. Correlations were restricted to those valence conditions and portions of the retention period where significant group differences were observed.

2.7. Statistical analysis 3. Results Two-tailed Student's t-tests were used to assess group differences in WTAR estimated general intelligence, accuracy and RT on the WM task and number of responses made outside of the two second response window. Group differences in lower alpha 1 ERD/ERS was assessed at the following electrodes: P0Z, P03, P04, P05, P06, P07 and P08. In order to explore the temporal consistency of any group differences, lower alpha 1 activity in each three seconds of the retention period were analysed separately. As electrophysiological data were not normally

3.1. Behavioural data MDD and control participants did not differ in the number of responses made outside of the specified two second RT (t(29)= 0.93, p = 0.36). There were no group differences in estimated general intellect as measured by the WTAR, or in RT or accuracy on the WM task in any of the three valence conditions (Table 1).

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193

3.2. Group by valence interactions Significant lower alpha 1 group by valence interactions were observed at all electrodes throughout the first second of the retention period (z's≤ −3.28, p's = 0.001–0.02). During the middle second of the retention period, group by valence interactions achieved significance at P04, P06, P08 and P0Z (z's≤ −2.65, p's = 0.02–0.04) and were at trend level at P03 and P07 (z's ≤ −1.97, p's = 0.05). No group by valence interactions were observed during the third second of the retention period. 3.3. Within valence group comparisons 3.3.1. Positive condition Both controls and MDD participants displayed lower alpha 1 ERD throughout the retention period. When positive images were used as emotional distracters, controls showed greater ERD than MDD participants during the first second of the retention interval at P03, P04 and P0Z (z's ≤ −2.25, p's = 0.02–0.04). There was a trend in the same direction at P05 and P06 (z's≤ −1.98, p's = 0.05) (Fig. 2, Table 2 and Supplementary figures). No significant differences were observed between the groups during the latter two seconds of the retention period. 3.3.2. Neutral condition Lower alpha 1 activity did not differ between MDD and control participants when WM task was superimposed on neutral stimuli. 3.3.3. Negative condition When negative images were used as emotional distracters, a trend towards MDD participants showing greater ERD than controls was observed during the first second of the retention period at P07 (z= −1.90, p = 0.06). A significant group difference in the same direction was observed during the middle second of the retention period at P08 (z= −2.21, p = 0.03) (Fig. 2, Table 3 and Supplementary figures).

Table 1 Mean Depression Rating Scale scores, estimated general intellect, accuracy and response time for the WM task for MDD and control participants. Controls

MDD

M ± SD

M ± SD

t

p

MADRS BDI-II WTAR Pred IQ

1.81 ± 1.68 1.94 ± 2.35 110.56 ± 5.84

30.27 ± 5.12 37.67 ± 10.71 107.00 ± 5.34

− 21.07 − 20.51 1.68

b 0.00 b 0.00 0.10

Response time Positive Neutral Negative

1030.17 ± 162.86 1067.44 ± 156.60 1060.51 ± 151.89

1109.29 ± 163.09 1132.33 ± 143.47 1153.57 ± 188.97

− 1.35 − 1.20 − 1.52

0.19 0.24 0.14

Accuracy (%) Positive Neutral Negative N

77.83 ± 10.53 75.33 ± 11.00 73.28 ± 12.80 16

75.18 ± 15.45 72.00 ± 10.35 69.68 ± 14.35 15

0.56 0.55 0.86

0.58 0.58 0.40

Note: degrees of freedom = 29 for all comparisons; response times shown in milliseconds; MADRS = Montgomery–Asberg Depression Rating Scale; BDI-II = Beck Depression Inventory — II; WTAR Pred IQ = Wechsler Test of Adult Reading Predicted Intelligence Quotient.

189

Table 2 Mean lower alpha 1 ERD/ERS values for controls and MDD participants during the first second of the retention period. Controls

MDD

Lower alpha 1

M ± SD

M ± SD

z

p

P08 Positive Neutral Negative

− 17.59 ± 20.64 − 14.94 ± 20.96 − 5.36 ± 23.37

− 9.05 ± 15.86 − 14.60 ± 20.31 − 18.02 ± 26.28

− 1.46 − 0.16 − 1.46

0.15 0.89 0.15

P06 Positive Neutral Negative

− 20.50 ± 21.08 − 17.08 ± 5.76 − 6.88 ± 26.29

− 7.25 ± 21.34 − 14.41 ± 7.27 − 21.24 ± 20.55

− 1.98 − 0.16 − 1.46

0.05 0.87 0.14

P04 Positive Neutral Negative

− 27.58 ± 20.01 − 17.64 ± 27.49 − 9.13 ± 30.88

− 7.10 ± 28.51 − 14.48 ± 34.19 − 19.67 ± 17.84

− 2.10 0.00 − 0.40

0.04 1.00 0.69

P0Z Positive Neutral Negative

− 28.59 ± 21.38 − 13.51 ± 25.35 − 10.27 ± 22.10

− 7.29 ± 26.15 − 8.36 ± 39.36 − 14.54 ± 15.39

− 2.17 − 0.55 − 0.63

0.03 0.58 0.53

P03 Positive Neutral Negative

− 26.80 ± 20.50 − 14.92 ± 21.40 − 10.10 ± 21.99

− 2.89 ± 35.58 − 4.39 ± 36.32 − 14.83 ± 5.77

− 2.25 − 0.47 − 0.75

0.02 0.64 0.45

P05 Positive Neutral Negative

− 20.90 ± 20.85 − 10.53 ± 21.01 − 0.93 ± 23.39

− 0.22 ± 34.15 0.42 ± 29.57 − 11.89 ± 29.84

− 1.94 − 0.83 − 1.71

0.05 0.41 0.08

P07 Positive Neutral Negative N

− 18.37 ± 21.27 − 8.78 ± 18.85 1.92 ± 24.51 16

1.27 ± 33.45 0.82 ± 26.41 − 10.81 ± 37.56 15

− 1.82 − 0.91 − 1.90

0.07 0.38 0.06

3.3.4. Medication effects There was no difference in lower alpha 1 activity between medicated and unmediated MDD participants across any of the three valence conditions. 3.4. Relationship between lower alpha 1 activity and depression severity 3.4.1. Positive condition During the first second of the retention period, participants with more severe depressive symptoms, as indexed by both BDI-II and MADRS, showed reduced lower alpha 1 ERD in the presence of positive distracters at P03, P04, P0Z and P06 (ρ's = 0.35–0.45, p's = 0.01–0.05). At P08 only BDI-II score achieved significance (ρ = 0.39, p = 0.03). During the middle second of the retention period a moderate positive correlation was observed between lower alpha 1 activity and BDI-II score at P0Z (ρ = 0.37, p = 0.04). 3.4.2. Negative condition No significant correlations between lower alpha 1 activity and depression severity as measured by either rating scale were observed during the first second of the retention period. During the middle second of the retention period moderate negative correlations between both BDI-II and MADRS scores

190

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193

Fig. 2. Mean and standard error lower alpha 1 ERD at selected representative electrodes.

and lower alpha 1 activity in the presence of negatively valenced distracters were observed at P08 (BDI-II: ρ= −0.36, p= 0.05; MADRS: ρ= −0.40, p =0.03). At P06 only MADRS score achieved significance (ρ=−0.35, p =0.05). 3.5. Relationships between lower alpha 1 activity and WM task performance 3.5.1. Positive condition During the first second of the retention period, participants who exhibited faster performance in the presence of positive distracters showed greater lower alpha 1 activity at P03, P05 and P07 (ρ's = 0.45–0.49, p's = 0.01–0.05). The same relationship was observed during the middle second of the retention period at P05, P07 and P0Z (ρ's= 0.37–0.47, p's = 0.008–0.04). No significant correlations were observed between lower alpha 1 activity and WM task accuracy during the positive condition. 3.5.2. Negative condition During the first second of the retention period, participants who were less accurate in the presence of negative distracters showed greater lower alpha 1 activity at P04 (ρ = 0.36, p = 0.05). No significant correlations were observed between lower alpha 1 activity and RT during the negative condition. 4. Discussion The introduction of extraneous affective images to an otherwise non-emotive WM task resulted in a differential pattern of electrophysiological activity for acutely depressed and psychologically healthy participants. During the information retention

phase of WM, controls showed greater neural desynchronisation (i.e. greater ERD) within the lower alpha 1 band when positive distracters were depicted, whereas depressed participants displayed increased desynchronisation during presentation of negative distracters. Importantly, differentiation between the groups was restricted to interference from positive and negative stimuli, with no differences seen when WM stimuli were superimposed on neutral images. These results do not appear to be related to group differences in estimated general intelligence. The current findings are in keeping with prior electrophysiological studies that have found lower alpha 1 activity to respond primarily to extrinsic non-task specific factors and stimuli (Klimesch, 1999; Klimesch et al., 1998; Onoda et al., 2007). Within valence examinations of lower alpha 1 activity revealed a consistent pattern of greater desynchronisation in the control compared to MDD group in the presence of positive distracters. As activity within this alpha subband is thought to reflect attentional processing (see Klimesch, 1999 for review), and greater desynchronisation denotes increased cortical activation and mental activity (Pfurtscheller, 2001), this pattern is consistent with an attentional bias for positive stimuli in healthy controls which is substantially attenuated in depressed individuals. Reduced preferential processing of positive material in MDD has been previously reported (Fu et al., 2007; Keedwell et al., 2005; Surguladze et al., 2005) but has been less consistently demonstrated than negative information processing biases in MDD (Deveney and Deldin, 2004; Goeleven et al., 2006; Joormann and Gotlib, 2008; Siegle et al., 2010). A pattern of lower alpha 1 activity indicative of enhanced attention to extraneous negative material in MDD (i.e. greater desynchronisation during presentation of negative distracters in MDD participants) was also observed. However, the

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193 Table 3 Mean lower alpha 1 ERD/ERS values for controls and MDD participants during the middle second of the retention period. Controls

MDD

Lower alpha 1

M ± SD

M ± SD

z

p

P08 Positive Neutral Negative

− 18.48 ± 23.90 − 21.88 ± 20.99 − 11.82 ± 20.63

− 13.64 ± 19.89 − 17.65 ± 16.68 − 27.73 ± 13.03

− 0.71 − 1.34 − 2.21

0.48 0.18 0.03

P06 Positive Neutral Negative

− 20.88 ± 22.02 − 23.17 ± 22.53 − 15.65 ± 21.13

− 14.31 ± 20.45 − 20.21 ± 12.87 − 27.56 ± 12.09

− 0.91 − 1.62 − 1.66

0.38 0.11 0.10

P04 Positive Neutral Negative

− 28.97 ± 19.34 − 26.01 ± 24.60 − 19.31 ± 24.78

− 17.38 ± 20.18 − 26.47 ± 16.55 − 27.01 ± 14.86

− 1.54 − 0.51 − 0.83

0.13 0.63 0.42

P0Z Positive Neutral Negative

− 33.75 ± 15.74 − 25.51 ± 16.94 − 21.05 ± 19.66

− 21.03 ± 22.13 − 25.92 ± 20.85 − 28.88 ± 14.66

− 1.54 − 1.54 − 0.95

0.13 0.13 0.36

P03 Positive Neutral Negative

− 29.49 ± 18.53 − 21.40 ± 19.99 − 22.22 ± 19.35

− 17.77 ± 26.09 − 20.04 ± 34.29 − 20.94 ± 18.46

− 1.46 − 0.36 − 0.27

0.15 0.74 0.80

P05 Positive Neutral Negative

− 22.38 ± 19.03 − 14.70 ± 20.22 − 14.37 ± 21.38

− 10.39 ± 30.19 − 12.46 ± 42.70 − 17.20 ± 19.36

− 1.50 − 0.95 − 0.47

0.14 0.36 0.65

P07 Positive Neutral Negative N

− 20.39 ± 20.78 − 14.06 ± 17.45 − 13.99 ± 21.28 16

− 4.77 ± 33.04 − 10.71 ± 43.10 − 17. 63 ± 23.65 15

− 1.34 − 0.75 − 0.95

0.19 0.47 0.36

magnitude and consistency of group differences in the negative condition were not as prominent as those in the positive condition. It may be that the moderate sample size resulted in insufficient statistical power to detect a more widespread pattern of group differences in the negative condition. Although considered a tentative explanation, this possibility is supported by the group means which document a consistent pattern of greater desynchronisation in the MDD than control group in the presence of extraneous negative images. Overall, the current results suggest that under conditions of conflicting cognitive and emotional processing demands, extraneous positive material has greater capacity to capture attention in controls while, to a somewhat lesser degree, extraneous negative material has greater capacity to capture attention in depressed individuals. The positive correlations between depression severity and lower alpha 1 activity during exposure to extraneous positive distracters, and negative correlations observed between depression severity and lower alpha 1 activity during exposure to extraneous negative images further support these relationships. The strength of interactions between group differences in lower alpha 1 activity and the valence of distracting images lessened with each sequential second of the retention period. While not formally assessed, this pattern is suggestive of a

191

progressive reduction in group differences in the attentional salience of emotive distracters throughout the retention period. One potential explanation for this pattern is that during cognitive processing, mood-congruent distracters may have a more immediate impact than mood-incongruent distracters, with the latter becoming progressively more conspicuous over time. Therefore, negative images would influence processing in the depressed group during early stages of the retention period and positive images would have a similar effect in the control group. This would then be reflected in reduced group differences over time. While considered speculative, the direction of progressive changes in group differences in lower alpha 1 activity is consistent with this explanation. Previous studies of alpha activity have reported an increase in alpha activity during the retention period of the Sternberg WM task (Jensen et al., 2002; Klimesch, 1999), whereas in the current study a decrease in alpha was observed. Examination of activity within the other two alpha subbands (see Supplementary methods and Supplementary results) indicates that this discrepancy is a product of the subdivision of the alpha bandwidth. While there were no valence specific group differences, activity within the upper alpha band did show the expected pattern of increased synchronous activity throughout the retention period. The lower alpha 2 band showed a more variable pattern, with ERD or ERS observed depending on the time point, electrode or affective condition examined. Only the lower alpha 1 band showed a relatively consistent pattern of ERD during WM retention. These observations provide further support for the existence of functionally distinct subbands within the broad alpha range. Somewhat surprising is the lack of statistically significant group differences in response speed and accuracy on the WM task. WM impairments are commonly reported in MDD and the current task used a memory set consistent with the upper end of a typical WM span (Schweickert and Boruff, 1986). Despite the lack of significant group differences in behavioural measures, valence specific correlations were observed between task performance and lower alpha 1 activity. This indicates that relationships between lower alpha 1 activity, affective distracters and WM performance do exist. Specifically, in the presence of positive distracters greater lower alpha 1 desynchronisation was associated with faster reaction times. When negative distracters were depicted, greater lower alpha 1 desynchronisation was associated with reduced accuracy. Although the group means for measures of task performance were not statistically different, controls were consistently faster to respond in the positive condition and MDD participants were less accurate in the negative condition. Thus, one potential interpretation may be that greater engagement with extraneous positive images subsequently facilitated performance (i.e. response latencies) for controls, while greater engagement with extraneous negative material had a deleterious impact on performance (i.e. task accuracy) for depressed participants. However, as the differences in RT and accuracy between the groups did not reach statistical significance in the current sample we are limited in the conclusions that we can draw about the neural correlates of affective interference on WM performance. Clarification of the functional significance of the current electrophysiological findings awaits further research in larger samples. Our results do, however, demonstrate that emotional distracters elicit an effect on neural activity during WM

192

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193

processing, which is reflected in neural oscillations even in an absence of overt behavioural impairment. Enhanced susceptibility to distraction from extraneous mood-congruent material in MDD is thought to reflect a loss of cognitive control (i.e. the ability to appropriately direct attentional resources) which arises from disruptions in the normal interactions between the dorsal (i.e. executive) and ventral (i.e. emotive) brain systems that subsume cognitive and emotional processing (Dolcos and McCarthy, 2006; Drevets and Raichle, 1998; Mayberg, 1997). The majority of previous investigations in this area have focused on interactions between activity within the ventral system and the more anterior constituents of the dorsal system (i.e. discrete regions within the prefrontal cortex and the anterior cingulate). The posterior parietal cortex is also part of the dorsal system; as previously noted it is a critical node within attentional control circuitry and is highly sensitive to distraction (Colby and Goldberg, 1999; Culham and Kanwisher, 2001). However, this region has been less often investigated in relation to cognitive control over emotional distraction and its contribution remains poorly understood. In one of the few studies to consider the influence of more posterior regions, using fMRI, Dolcos and McCarthy (2006) found that negative emotional distracters evoked deactivation in lateral parietal cortex in healthy controls. In addition, while it was not the focus of their investigation, Wang et al. (2008) observed greater posterior parietal deactivation in response to sad distracters in depressed participants relative to controls, and suggested this may reflect allocation of attentional resources to mood-congruent distracters. The current results are consistent with this interpretation and extend upon those findings by demonstrating that a) attentional resource allocation is reflected in neural oscillations within the lower alpha 1 band, that b) this pattern of activity extends to both neural responses to positive distracters in healthy individuals, and c) to attenuated neural response to mood-incongruent distracters in MDD. There are a number of methodological caveats worth considering. The first concerns the selection of emotive stimuli. As, by definition, neutral images tend to elicit smaller emotional responses than positive or negative images, they also tend to have lower arousal ratings. In order to control for the influence of arousal, (i.e. balance average IAPS arousal ratings across the three valence conditions) the images selected for use in the positive and negative conditions also had relatively low arousal ratings. Intuitively this calls into question the emotive power of the selected images. The decision to present blocks of sequential trials of the same valence, rather than interspersing single trials of differing valences, was made to limit this and maximise the impact of each of the three valance conditions. That group differences were restricted to the positive and negative conditions and are within the existing theoretical framework of information processing biases in MDD suggests that this approach was successful. Moreover, although not formally assessed, informal verbal feedback from participants in both groups indicated that the perception of emotional content was consistent with the valence that images were intended to depict. A related issue is the inclusion of images likely to induce a variety of aversive responses, i.e. sadness, anxiety and disgust, within a single broad ‘negative’ condition. Exposure to sadness-related, threatrelated and anger-related stimuli are associated with differing patterns of behavioural and neurobiological response and are not processed via uniform neurocircuits (Murphy et al., 2003).

Another limitation is the lack of correction for multiple comparisons. The issue of multiple comparisons is particularly difficult within electrophysiological research as EEG investigations typically involve numerous sources of measurement (i.e. electrodes) and examination of multiple data components within each source (see Hale et al., 2009 for discussion). The decision not to correct for multiple comparisons has been made in previous EEG studies when authors were concerned that truncated significance thresholds increased the probability of Type II error (e.g. Hale et al., 2009; Loo et al., 2003). In the current study, we restricted our comparisons to a set of hypothesis specific electrodes and experimental manipulations, and the direction and spectral specificity2 of electrophysiological changes were in keeping with the results of past research as well as our a-priori predictions. We feel that this suggests that the results are not the result of random type I error. However, the lack of consistency of group differences across individual scalp sites in the negative condition (compared to the positive) indicates that these findings should be interpreted with a degree of caution, and their confirmation awaits replication in larger experimental cohorts. In summary, the current investigation has demonstrated that, in comparison with controls, individuals with MDD differ in their electrophysiological responsiveness to emotional distraction during WM processing. Depression-related abnormalities in EEG activity were observed within the lower alpha 1 band and, from an electrophysiological perspective, the pattern of activity appears to reflect a loss of preferential processing of positive stimuli in MDD that is accompanied by enhanced attentional engagement with negative material. The results of the current study indicate that lower alpha 1 activity is sensitive to competing emotional and cognitive processing demands, even in the absence of explicit cognitive impairment, and highlight the importance of posterior parietal regions in susceptibility to affective distractibility during cognitive processing. Conflict of interest There are no actual or potential relationships between the authors that could constitute a conflict of interest.

Role of funding source Funding for this study was provided by Monash University postgraduate funding, Melbourne Australia. Purchase of EEG equipment was partially funded by the Neurosciences Victoria Clinical Neurobiology of Psychiatry Platform (CNV CNPP). Prof Paul Fitzgerald is supported by a National Health and Medical Research Council (NHMRC) Practitioner Fellowship. Neither Monash University, the NSV CNPP, nor NHMRC had any further role in study design, in the collection, analysis and interpretation of data, in the writing of the manuscript, or the decision to submit the paper for publication.

Acknowledgements Funding for this study was provided by Monash University. Equipment funding was provided in part by Neurosciences Victoria (Clinical Neurobiology of Psychiatry Platform). PBF is supported by a National Health and Medical Research Council Practitioner Fellowship.

Appendix A. Supplementary data and methods Supplementary data to this article can be found online at doi:10.1016/j.jad.2012.03.004.

2

See Supplementary materials.

R.A. Segrave et al. / Journal of Affective Disorders 141 (2012) 185–193

References Andrew, C., 1999. Quantification of event-related coherence (ERCoh). In: Pfurtsceller, G., Lopes De Silver, F.H. (Eds.), Handbook of Electroencephalography and Clinical Neurophysiology, Event Related Desynchronisation, Vol. 6. Elsevier, Amsterdam, pp. 119–137. Beck, A.T., Steer, R.A., 1984. Internal consistencies of the original and revised Beck Depression Inventory. Journal of Clinical Psychology 40, 1365–1367. Colby, C.L., Goldberg, M.E., 1999. Space and attention in parietal cortex. Annual review of neuroscience 22, 319–349. Croft, R.J., Barry, R.J., 2000. EOG correction of blinks with saccade coefficients: a test and revision of the aligned-artefact average solution. Clinical Neurophysiology 111, 444–451. Culham, J.C., Kanwisher, N.G., 2001. Neuroimaging of cognitive functions in human parietal cortex. Current opinion in neurobiology 11, 157–163. D'esposito, M., Postle, B.R., Rypma, B., 2000. Prefrontal cortical contributions to working memory: evidence from event-related fMRI studies. Experimental Brain Research 133, 3–11. Deldin, P.J., Deveney, C.M., Kim, A.S., Casas, B.R., Best, J.L., 2001. A slow wave investigation of working memory biases in mood disorders. Journal of abnormal psychology 110, 267–281. Deveney, C.M., Deldin, P.J., 2004. Memory of faces: a slow wave ERP study of major depression. Emotion 4, 295–304. Dichter, G.S., Felder, J.N., Smoski, M.J., 2009. Affective context interferes with cognitive control in unipolar depression: an fMRI investigation. Journal of Affective Disorders 114, 131–142. Dolcos, F., Mccarthy, G., 2006. Brain systems mediating cognitive interference by emotional distraction. The Journal of Neuroscience 26, 2072–2079. Drevets, W.C., Raichle, M.E., 1998. Reciprocal suppression of regional cerebral blood flow during emotional versus higher cognitive processes: implications for interactions between emotion and cognition. Cognition & Emotion 12, 353–385. Fales, C.L., Barch, D.M., Rundle, M.M., Mintun, M.A., Snyder, A.Z., Cohen, J.D., Mathews, J., Sheline, Y.I., 2008. Altered emotional interference processing in affective and cognitive-control brain circuitry in major depression. Biological Psychiatry 63, 377–384. Fu, C.H., Williams, S.C., Brammer, M.J., Suckling, J., Kim, J., Cleare, A.J., Walsh, N.D., Mitterschiffthaler, M.T., Andrew, C.M., Pich, E.M., Bullmore, E.T., 2007. Neural responses to happy facial expressions in major depression following antidepressant treatment. The American Journal of Psychiatry 164, 599–607. Goeleven, E., De Raedt, R., Baert, S., Koster, E.H., 2006. Deficient inhibition of emotional information in depression. Journal of affective disorders 93, 149–157. Gotlib, I.H., Joormann, J., 2010. Cognition and depression: current status and future directions. Annual review of clinical psychology 6, 285–312. Hale, T.S., Smalley, S.L., Hanada, G., Macion, J., Mccracken, J.T., Mcgough, J.J., Loo, S.K., 2009. Atypical alpha asymmetry in adults with ADHD. Neuropsychologia 47, 2082–2088. Harmer, C.J., Goodwin, G.M., Cowen, P.J., 2009. Why do antidepressants take so long to work? A cognitive neuropsychological model of antidepressant drug action. The British Journal of Psychiatry 195, 102–108. Hasher, L., Zacks, R.T., 1988. Working memory, comprehension, and aging: a review and a new view. The Psychology of Learning and Motivation 22, 193–225. Jensen, O., Gelfand, J., Kounios, J., Lisman, J.E., 2002. Oscillations in the alpha band (9–12 Hz) increase with memory load during retention in a shortterm memory task. Cerebral Cortex 12, 877–882. Joormann, J., Gotlib, I.H., 2008. Updating the contents of working memory in depression: interference from irrelevant negative material. Journal of abnormal psychology 117, 182–192. Junghofer, M., Bradley, M.M., Elbert, T.R., Lang, P.J., 2001. Fleeting images: a new look at early emotion discrimination. Psychophysiology 38, 175–178. Keedwell, P.A., Andrew, C., Williams, S.C., Brammer, M.J., Phillips, M.L., 2005. A double dissociation of ventromedial prefrontal cortical responses to sad and happy stimuli in depressed and healthy individuals. Biological Psychiatry 58, 495–503. Klimesch, W., 1999. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research Reviews 29, 169–195. Klimesch, W., Doppelmayr, M., Russegger, H., Pachinger, T., Schwaiger, J., 1998. Induced alpha band power changes in the human EEG and attention. Neuroscience letters 244, 73–76.

193

Klimesch, W., Sauseng, P., Hanslmayr, S., 2007. EEG alpha oscillations: the inhibition-timing hypothesis. Brain Research Reviews 53, 63–88. Ladouceur, C.D., Dahl, R.E., Williamson, D.E., Birmaher, B., Ryan, N.D., Casey, B.J., 2005. Altered emotional processing in pediatric anxiety, depression, and comorbid anxiety-depression. Journal of Abnormal Child Psychology 33, 165–177. Lang, P.J., Bradley, M.M., Cuthbert, B.N., 2005. International affective picture system (IAPS): affective ratings of pictures and instruction manual. Technical Report A-6. University of Florida, Gainesville. Leppanen, J.M., 2006. Emotional information processing in mood disorders: a review of behavioral and neuroimaging findings. Current opinion in psychiatry 19, 34–39. Loo, S.K., Specter, E., Smolen, A., Hopfer, C., Teale, P.D., Reite, M.L., 2003. Functional effects of the DAT1 polymorphism on EEG measures in ADHD. Journal of the American Academy of Child and Adolescent Psychiatry 42, 986–993. Mayberg, H.S., 1997. Limbic-cortical dysregulation: a proposed model of depression. The Journal of neuropsychiatry and clinical neurosciences 9, 471–481. Michels, L., Moazami-Goudarzi, M., Jeanmonod, D., Sarnthein, J., 2008. EEG alpha distinguishes between cuneal and precuneal activation in working memory. NeuroImage 40, 1296–1310. Montgomery, S.A., Asberg, M., 1979. A new depression scale designed to be sensitive to change. The British Journal of Psychiatry 134, 382–389. Murphy, F.C., Nimmo-Smith, I., Lawrence, A.D., 2003. Functional neuroanatomy of emotions: a meta-analysis. Cognitive, affective, & behavioral neuroscience 3, 207–233. Oldfield, R.C., 1971. The assessment and analysis of handedness: the Edinburgh Inventory. Neuropsychologia 9, 97–113. Onoda, K., Okamoto, Y., Shishida, K., Hashizume, A., Ueda, K., Yamashita, H., Yamawaki, S., 2007. Anticipation of affective images and event-related desynchronization (ERD) of alpha activity: an MEG study. Brain Research 1151, 134–141. Otnes, R.K., Enochson, L., 1978. Applied Timer Series. Wiley, New York. Pfurtscheller, G., 2001. Functional brain imaging based on ERD/ERS. Vision Research 41, 1257–1260. Pfurtscheller, G., Aranibar, A., 1977. Event-related cortical desynchronization detected by power measurements of scalp EEG. Electroencephalography and clinical neurophysiology 42, 817–826. Rogers, M.A., Kasai, K., Koji, M., Fukuda, R., Iwanami, A., Nakagome, K., Fukuda, M., Kato, N., 2004. Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neuroscience Research 50, 1–11. Schweickert, R., Boruff, B., 1986. Short-term memory capacity: magic number or magic spell? Journal of Experimental Psychology. Learning, Memory, and Cognition 12, 419–425. Segrave, R.A., Thomson, R.H., Cooper, N.R., Croft, R.J., Sheppard, D.M., Fitzgerald, P.B., 2010. Upper alpha activity during working memory processing reflects abnormal inhibition in major depression. Journal of Affective Disorders 127, 191–198. Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., Amorim, P., Janavs, J., Weiller, E., Hergueta, T., Baker, R., Dunbar, G.C., 1998. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. The Journal of Clinical Psychiatry 59 (Suppl. 20), 22–33 quiz 34–57. Shestyuk, A.Y., Deldin, P.J., Brand, J.E., Deveney, C.M., 2005. Reduced sustained brain activity during processing of positive emotional stimuli in major depression. Biological Psychiatry 57, 1089–1096. Siegle, G.J., Condray, R., Thase, M.E., Keshavan, M., Steinhauer, S.R., 2010. Sustained gamma-band EEG following negative words in depression and schizophrenia. International Journal of Psychophysiology 75, 107–118. Sternberg, S., 1966. High-speed scanning in human memory. Science 153, 652–654. Surguladze, S., Brammer, M.J., Keedwell, P., Giampietro, V., Young, A.W., Travis, M.J., Williams, S.C., Phillips, M.L., 2005. A differential pattern of neural response toward sad versus happy facial expressions in major depressive disorder. Biological Psychiatry 57, 201–209. Wang, L., Labar, K.S., Smoski, M., Rosenthal, M.Z., Dolcos, F., Lynch, T.R., Krishnan, R.R., Mccarthy, G., 2008. Prefrontal mechanisms for executive control over emotional distraction are altered in major depression. Psychological research 163, 143–155. Wechsler, D., 2001. Wechsler Test Of Adult Reading. The Psychological Corporation, San Antonio, TX. Williams, J.M., Mathews, A., Macleod, C., 1996. The emotional Stroop task and psychopathology. Psychological bulletin 120, 3–24.