Effect of Negative Memory Bias and Autobiographical Memory Specificity on the Relationship between Social Decision Making and Depression

The Effect of Negative Memory Bias and Autobiographical Memory Specificity on the

Relationship Between Social Decision Making and Depression

Social decisions are critical for day-to-day functioning, building interpersonal relationships and determining the quality of social life (Rohde, 2016). Social decisions, affecting oneself and others, can range from simple choices of deciding work outfits to more complex decisions such as resolving conflicts in relationships. The ability to make effective social decisions is impaired when social functioning is disturbed, particularly in depression (Hinterbuchinger et al., 2018).

Alongside deficits in making decisions that benefit their social well-being, indivdiuals with depression or major depressive disorder (MDD) show strong autobiographical memory biases. Research indicates that we inform decisions by drawing on memories of past choices (Bornstein, Khaw, Shohamy, & Daw, 2017). In doing so, bias in autobiographical memory recall impacts decisions in social scenarios. Depressed individuals tend to remember more negative memoriesand information that reflect their mood better than neutral or positive information (Watkins, Vache, Verney, Muller & Mathews, 1996). In addition, individuals with depression lack autobiographical memory specificity(AMS; Matsumoto & Mochizuki, 2018). That is, they have more generalised memories of events lacking personal, specific details of time and place (Summer, 2012). The literature has yet to identify these memory tendencies as regulators of social decision making in depressed individuals, which could posit pertinent clinical implications (Kuyen & Dalgleish, 2011; Hitchcock et al., 2018). Thus, the present study investigates whether AMS or negative memory bias moderates the relationship between depressive symptoms and social decision making skills.

There is a robust association between decision making and memories of past events that guide our everyday decisions (Bornstein et al., 2017). Models in memory retrieval paths demonstrate how modulations to episodic or ‘event-specific’ memories can easily alter our decision making (Conway & Pleydell-Pearce, 2000). Our event-specific memories are either activated by cues and retrieved automatically or searched by relevance or similarity to the decision at hand. Cognitive bias present along the automatic retrieval path has implications for our memories, which could predict future decisions (Conway & Pleydell-Pearce, 2000). Individuals with biased sensitivity to social rejection might recall negative social events more than positive. For instance, they might remember the times they were rejected from clubs, more than when they were invited to parties. This bias could result in the person refraining from future invitations. A corroborative finding reported that reminding outcomes of past decisions influenced participants’ episodic memory (Bornstein et al., 2017). Presenting memory cues to remind previous outcomes increased the likelihood of retrieving particular memories and predicted participants’ future choices. Further, episodic memory search to make decisions is adaptive and produces stronger associative memory for choices with rewarding outcomes (Murty, FeldmanHall, Hunter, Phelps & Davachi, 2016).

Associations formed by episodic memory could generalise to complex choice behaviours, including social decision making. Past research showed this by distinguishing how participants use memories of past events to make decisions in a context-concordant manner (Duncan & Shohamy, 2016). That is, indivdiuals were most likely to retrieve episodic memories to make choices in familiar situations. In novel circumstances, participants drew memories from similar past choices to make generalised, optimal decisions. Experiencing novel situations expanded participants’ memories of choice environments to aid future decisions (Duncan & Shohamy, 2016). Using episodic memory for making decisions not only influence simple stimuli-based decisions but also complex problem-solving engagements in psychosocial contexts. As yet however, we have limited understanding of the direct impact of autobiographical memories on social decision making. We know from the current literature that our autobiographical memory tendencies are prone to influences such as mental disturbances that could impact this adaptive skill.

The autobiographical memories driving our daily decisions are susceptible to bias and this is particularly problematic for indivdiuals with depression, who show distinct disturbances in memory recall and maintenance (Dalgleish & Werner-Seidler, 2014). The depression-memory literature reveals that depressed indivdiuals have a systematic bias toward negative memories (Gotlib & Joorman, 2010). This bias can be observed in memory retrieval involving facial recognition (Ridout et al., 2003) and emotive word recall (Gotlib & Joormann, 2010). Further, individuals with MDD exhibit hypersensitive neural responses to social rejection or negative cues (Kumar et al., 2017). One study found that this hypersensitivity impairs both social functioning and decision making (Kumar et al., 2017). This impairment occurs by instigating the need to cope with aversive social signals and consequent symptoms of interpersonal stress and social withdrawal. In explanation, the Social Risk Hypothesis (Allen & Badcock, 2003) states that depression is an adaptive mechanism against social risks and negative or rejection outcomes. Frameworks such as the mood congruency bias (Watkins et al., 1996) also suggest that stimuli that reflect individuals’ current emotional states are more memorable. Perhaps as functions of these mechanisms, depressed individuals show heightened sensitivity and attention to negative memories and stimuli indicating social risk.

Depressed indivdiuals, particularly adolescents, are also biased toward over-general memory and have reduced access to specific details of past memories. Over-general memories are broad or vague summaries of events that lack time or place details and extend longer than a day (Summer, 2012). The AMS literature shows strong evidence of bias toward categoric negative cue words and over-generalised memories in at-risk and MDD-diagnosed adolescents (Park, Goodyer, & Teasdale, 2002; Kuyken & Dalgleish, 2011). Recent studies reported that positive and specific memory styles relate to lower depressive symptoms for at-risk adolescents with early life stress (Askelund, Schweizer, Goodyer & Harmelen, 2019). These styles also predicted fewer negative perceptions of the self over a one-year period. Thus, current literature reveals negative, over-generalised autobiographical memory as a vulnerability marker and positive memory specificity as a resilience factor for depression in adolescents (Gutenbrunner, Salmon, & Jose, 2018). Identifying the above memory presentation patterns has led to the implementation of memory training interventions that focus on encouraging more positive and specific memories (Hitchcock et al., 2018).

Although the direct effect of these memory biases on the association between depression and social decision making remains uncertain, interventions that target the memory biases show promising outcomes in clinical populations. Previous randomised controlled trials have tested Memory Specificity Training (MEST) and positive elaboration for adolescents (Neshat-Doost et al., 2013). These interventions significantly reduced depressive traits including cognitive avoidance, rumination and improved problem-solving skills (Dalgleish & Werner-Seidler, 2014). Also, clinical trials of cognitive behavioural therapy showed that over-general memory in depressed patients can be targeted by brief treatments (McBride, Segal, Kennedy, & Gemar, 2007). Despite the known benefits of targeting negative memories and lack of AMS in interventions, their moderating influences on the association between depression and social decision making remain unclear.

Aims & Hypotheses

The current study aims to investigate whether AMS moderates the relationship between performance on a social decision making task (SDMT) and levels of depressive symptoms. We also aim to observe whether the extent of bias toward negative memories reflect levels of depression and social decision making skills. To do so, we will compare the performance of low and high depression groups on a SDMT. The current study will employ a modified version of the decision making task by Bornstein et al. (2017), which will include a social decision component.

In light of the above literature, we hypothesise that:

1. Autobiographical memory specificity will decrease as a function of depressive symptoms, in particular for positive cues.
2. Participants with high depressive symptoms will show more bias toward negative (rejection) memory cues compared with positive (acceptance) memory cues at the recall test of the social decision making task. That is, they will be more likely to remember seeing memory cues that were followed by a negative compared to a positive outcome.
3. Choice trials on the social decision making task following memory cues will be more likely to be influenced by the memory cue (i.e., selecting positive reward) when the outcome associated with the cue was negative.
4. Autobiographical memory specificity will partially account for this association.

Method

Participants

  A total of 96 participants aged 17-30 will be recruited from the University of New South Wales psychology first-year student cohort through the online research participation platform, SONA. Participants will be allocated into low and high depressive symptom groups through pre-screening questionnaires. Participants will receive 1 course credit incentive for their contribution.

Design

 The current study is an experimental study that compares social decision making performance of individuals who have high versus low depressive symptoms. We employ two 2x(2) mixed designs where the between-subject factors are levels of participant depressive symptoms (low and high). The within-subject factors are outcome types (positive and negative) on the SDMT recall test, and outcome associations (positive and negative) to memory cues influencing choice trials in the SDMT. The dependent variables are percentage of optimal choice made on the SDMT recall test and trials following memory cues and percentage of specific memories on the AMT.

Materials & Stimuli

Depressive symptoms. To assess depressive symptoms, participants will complete the short version (8 self-report questionnaire) of the Depression Anxiety Stress Scale (DASS). The DASS measures depressive symptoms based on responses to symptom experience on a 4- point scale ranging from: 0 = did not apply to me at all to 3 = applied to me very much or most of the time. Examples of items include “I felt down-hearted and blue” and “I found it hard to wind down”. Final scores will be calculated by adding the scores for each item, which could range from 0 to 24.

Autobiographical memory specificity. Participants will also take a written autobiographical memory test (AMT) as a measure of their AMS prior to the experiment. They will be asked to write about a specific memory in response to 10 cue words. There are 5 of each positive and negative cue words, such as: ‘happy’, ‘sad’ and ‘surprised’. AMS rate will be measured based on the word count and tense of each participant response, using a linguistic coding scheme by Takano et al. (2017).

Social decision-making. In the SDMT, or the modified version of the decision task by Bornstein et al. (2017; see Experiment 2 bandit task), participants will be asked to imagine that they are to organise a large social event with as many attendees as possible. In each trial, they are to imagine going around the university campus to recruit attendees and to knock on either blue or yellow doors that could lead to either a positive (person behind the door attends the party) or a negative (person behind the door rejects party invitation) outcome. After choosing a door, participants will be shown unrelated neutral object stimuli as memory cue ‘posters’ on the door (such as a blender), which is then followed by either a smiling face indicating an attendee, or a neutral face, indicating that the person will not be attending the event (see Figure 1).

 (A)            (B)                 (C)                 (D)

Figure 1. Sample trial showing stimuli sequence. (A) shows the initial door choice, followed by a neutral stimulus in (B). (C) and (D) correspondingly show the positive or acceptance and negative or rejection outcomes.

The SDMT has a total of 162 trials consisting of 130 social decision making trials followed by 32 memory recall trials. At the recall trials, which will occur sometimes during the SDMT for practice and be measured at a final test after the task, participants will be asked to recall the presence of an object memory cue and whether participants living behind the corresponding door were coming to the party or not.

Procedure

 Participants will first complete a demographic questionnaire followed by a pre-experiment questionnaire battery on the laboratory computer. After, participants will be given verbal instructions of the imagined scenario for the SDMT, followed by written instructions on how to complete the task. Before commencing the actual SDMT, participants will complete two sample trials of the choice tasks. After completing the SDMT and related recall tasks, participants will be debriefed on the present study and recompensed with course credit.

Statistical Analyses

 Linear regression analyses will be used to test our first hypothesis that AMS will decrease as a function of depressive symptoms (high vs. low). We will also look at the association between AMS and depressive symptoms continuously. The association (Pearson’s r) between DASS scores and AMS rate to all memory cues, positive memory cues and negative memory cues will be entered into a Hotelling-Williams test. The test will be performed to compare whether there are significant differences in the magnitude of these associations.

A 2x(2) mixed model analysis will be used to test our second hypothesis that participants with high depression will show greater bias toward negative compared to positive memory outcome cues in the recall test. The 2x(2) general linear model will also be used to test whether choices in trials following memory outcome cue presentations are affected more by the cues if the outcome associated with it is negative. To test our fourth hypothesis that this difference is moderated by AMS, we will run a moderation analysis on SPSS using the Hayes-PROCESS package. No temporal mediation is implied, only statistical. That is, we expect the association between depressive symptoms and social decision-making to be partially accounted for by levels of AMS.

Expected Results

Consistent with existing literature, we firstly expect to see that AMS will decrease with greater presentations of depressive symptoms. This difference will be more pronounced for positive cues in the AMT (see Figure 2). We also expect an overall diagnosis main effect (high vs. low symptom groups) where participants with higher DASS scores will choose the optimal outcome significantly less on average than those with low symptoms (see Figure 3). We also expect those with higher depression to choose more optimal outcomes on average in trials with negative compared with positive memory cues. That is, we should observe a significant interaction effect between memory cue type and diagnosis main effects (see Figure 3). Further, we anticipate this negative outcome bias to affect choices made in SDMT trials following memory outcome cue presentations. If the outcome associated with the memory cue is negative, choices made after the cue is shown (later in the SDMT) should be influenced more than if the association is positive.

Figure 2. Expected negative linear correlations between depressive symptoms (DASS scores) and AMS on average, AMS for positive cues and AMS for negative cues.

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Figure 3. Sample data displaying rate of optimal outcome choice across different level groups of depressive symptoms for memory cue types and expected significance in relation to one another.

Overall, the results should show that the high depressive symptom group, or those with low specificity scores on the AMT, have lower rates of optimal outcome choice on the SDMT than those with high AMS. Thus, we expect to see a moderating effect of AMS on the association between optimal choice rate on the SDMT and DASS scores.

Significance & Innovation

 Uncertainty remains in the literature about what moderates or underlies the characteristics of memory biases and decision making skill deficits in depression (Okwumabua, Duryea, & Wong, 2013). Targeting these associations has already proven effective as positive and specific memory training interventions show promising evidence for improving depressive symptoms (Dalgleish & Werner-Seidler, 2014). Ascertaining whether AMS and negative memory bias in social decision making moderate or predict risk of depressive symptoms could also identify avenues of enhancement in diagnosing depression (Gotlib & Joorman, 2010; Dalgleish & Werner-Seidler, 2014). This may further influence early prevention methods to specifically target these distinct memory patterns prior to the presentation of high or full-blown depressive symptoms. Thus, the present study has both practical and theoretical implications for future research to investigate towards a causative factor of depressive symptoms.

The present study focuses on the association between memory biases and the social aspect of decision making in depression that the literature has not yet addressed. Previous research indicates predictive connections between depressive symptoms and social skill deficits in clinical and developmental samples (Segrin, 2000; Wang et al., 2014; Hinterbuchinger et al., 2018). However, the literature has yet to test the underlying influence of memory presentation and maintenance patterns distinct to depression on this association. Currently, depression is the most common mental health condition with 11% lifetime prevalence worldwide (Lim et al., 2018). This makes abnormal memory and social decision making behaviour in those with MDD a critical area of research for examining predictors and risk factors of depression (Wang et al., 2014). Thus, the current study will add to existing findings by exploring the gap between the social decision making, memory bias and depression literature in the search for causal and diagnostic markers of depressive symptoms.

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