Selective attention to threat versus reward: Meta-analysis and neural-network modeling of the dot-probe task

Abstract

Two decades of research conducted to date has examined selective visual attention to threat and reward stimuli as a function of individual differences in anxiety using the dot-probe task. The present study tests a connectionist neural-network model of meta-analytic and key individual study results derived from this literature. Attentional bias for threatening and reward-related stimuli is accounted for by connectionist model implementation of the following clinical psychology and affective neuroscience principles: 1) affective learning and temperament, 2) state and trait anxiety, 3) intensity appraisal, 4) affective chronometry, 5) attentional control, and 6) selective attention training. Theoretical implications for the study of mood and anxiety disorders are discussed.Key Words: Dot-Probe Task, Selective Attention, Threat, Reward, Anxiety, Depression, Connectionism, Neural Network, Amygdala. A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPTSelective Attention for Reward & Threat 3 Selective Attention to Threat versus Reward: Meta-analysis and Neural-Network Modeling of the Dot-Probe TaskTheoretical constructs and research methodologies derived from cognitive psychology figure prominently in current emotion research, including investigations into the nature and function of anxiety. For example, cognitive researchers have been studying how individuals visually attend to threatening stimuli, and how between-subject variability in the functioning of attentional systems may correlate with individual differences in anxiety-related traits and disorders (e.g., Williams, Watts, MacLeod, & Matthews, 1997).Evolutionary models of emotion and attention hypothesize that nature may have programmed the visual-attention system to attend selectively to stimuli of biological significance, including both to cues of possible impending threat (e.g., predators), on the one hand, and to cues of potential reinforcement-reward value (e.g., food, mates), on the other (e.g., LeDoux, 1996;Panksepp, 1998;Rolls, 1999). Attentional mechanisms procuring the rapid detection of sources of potential environmental threat are therefore presumed to afford an obvious survival-facilitating mechanism (A. Mathews & Mackintosh, 1998;A. Mathews, Mackintosh, & Fulcher, 1997;. However, an equally integral attentional function to the biological fitness of organisms is to orient toward stimuli of potential reward-value in their environments (Panksepp, 1998;Rolls, 1999).It may be that reward-and threat-detection are performed by distinct attentional systems 1 . Specifically, threat detection attentional mechanisms may represent secondary interrupt programs that continuously perform a background analysis of stimuli regarding their likelihood of representing a source of danger, attaining foreground and conscious significance only to the extent that this analysis results in the detection of relatively significant sources of danger (e.g., LeDoux, 1996). Otherwise, the default and primary orientation of attention may be toward reward-relevant stimuli...

The impact of an unpredictable context and intolerance of uncertainty on the electrocortical response to monetary gains and losses

“…Therefore, in the present study it is possible that the unpredictable context primed defense system activation, which in turn interfered with reward processing. This is consistent with previous research demonstrating that threat processing trumps reward processing (Frewen, Dozois, Joanisse, & Neufeld, 2008), and research indicating that stress can alter dopaminergic functioning (Lemos et al, 2012) and diminish both neural sensitivity to reward (Porcelli, Lewis, & Delgado, 2012) and reward learning (Bogdan & Pizzagalli, 2006). Overall, the present study suggests that a task-irrelevant unpredictable context has the capacity to alter a neural measure of reward system functioning.…”

Negative emotional photographs are identified more slowly than positive photographs

“…For instance, in the previous experiments, participants may have covertly shifted attention away from the negative image (e.g., to the side of the computer monitor), thereby interrupting the initial encoding of the negative images. Although this explanation may be at odds with claims that attention rapidly and reflexively shifts toward potentially negative images (Bradley et al, 1997;Eastwood, Smilek, & Merikle, 2001;Koster, Crombez, Van Damme, Verschuere, & De Houwer, 2004;Öhman et al, 2001), there is some evidence that an attentional bias toward negative images is robust only when one tests populations that have been selected for high anxiety; among nonselect and populations selected for low-anxiety, there is some evidence for a bias away from negative information (Bar-Haim, Lamy, Lee, Bakermans-Kranenburg, & van Ijzendoorn, 2007;Becker & Detweiler-Bedell, 2009;Frewen et al, 2008). Thus, it is possible that a reflexive attentional shift away from the negative images impeded their identification and storage.…”

“…If so, the poor performance with negative images may have reflected a rapid shift of resources away from the negative images toward the positive images. This shift of resources could be accounted for by an attentional bias toward positive stimuli (Frewen, Dozois, Joanisse, & Neufeld, 2008) or by a tendency to rapidly deploy resources to negative stimuli but to quickly remove them (Rinck & Becker, 2006).…”

The dot-probe task to measure emotional attention: A suitable measure in comparative studies?

“…The large variability in the experimental procedure and the populations used for testing make it difficult to compare the results and conduct a reliable meta-analysis. To date, analyses indicated that the intensity of the threatening stimuli determines the magnitude of the attentional bias (Frewen, Dozois, Joanisse, & Neufeld, 2008) and that the attentional bias seems to be dependent on stimulus presentation time (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007). Because many research articles had to be left out of the previous meta-analyses due to the large methodological variability in the literature, we will here provide a full review of the literature on dot-probe tasks and will discuss related methodological issues.…”