- Variability in anticipatory attentional bias for alcohol was predicted and confirmed to be associated with conflicting automatic associations. A previously developed variant of the dot-probe task, the cued Visual Probe Task, was used in order to remove sources of noise that could affect variability. In this task, trials are randomly selected to be a Picture or a Probe trial: on Picture trials, predictive cues are followed by salient and control stimuli, and no response is required. On Probe trials, the predictive cues are followed by a probe stimulus, but no pictures occur. Thus, if a bias occurs this is due to the anticipated picture categories but not to an actually presented stimulus. Good reliability of the anticipatory bias was found for alcohol, and individual differences in bias were associated with risky drinking. Anticipatory spatial attentional bias to threat was also found to exist in a first test. The outcome-based response selection model (R3) that originally motivated the anticipatory attentional bias was supported in a predictive ABM training study, in which training towards or away from threat generalized to post-training stimulus-evoked bias; i.e., it's not just about the visual features of the cues becoming salient themselves. This approach may also address a potential issue with usual Attention Bias Modification paradigms, in that even when training attention away from certain stimulus categories, those categories are still task-relevant and therefore being made or kept salient, termed the salience side-effect.
- These results suggest that the well-known psychometric problems with measuring attentional bias using traditional task variants should not lead to premature dismissal of such behavioural measures in general: there may be ways to improve reliability. Further, the noise may actually carry information, as suggested by Attentional Bias Variability studies. One potential cause of such within-subject variability consists of trial-to-trial carryover effects on attentional bias (Gladwin & Figner, 2019), i.e., does the attentional bias on trial N depend on the proble location on trial N - 1? This appeared to be the case in a Visual Probe Task. Carryover effects may be related to trauma symptoms.
- Landscape-based cluster analysis can be used to define clusters (e.g., in fMRI data). Recognizing a "blob" intuitively involves looking at their shape, formalized as their second derivative of activation over space in this method. A recursive clustering function defined 3D blobs of arbitrary shapes, searching for edges, i.e., inflection points, in a spreading search pattern from a local maximum. To each blob defined this way an activation score combining blob size and statistical significance of effects in voxels contained in the blob could be assigned. The set over the whole brain of activation scores was tested using permutation tests. The main goal was to avoid an arbitrary threshold for the initial definition of clusters. The method also scales up with better spatial resolution (i.e., more and smaller voxels), unlike traditional familywise correction in which statistical power would suffer from a larger number of voxels.
- Freezing (operationalized as body sway reduction and bradycardia in a threatening context) may be a preparatory, rather than "helpless", state. We used a virtual Shooting task to manipulate the ability to prepare to respond to avoid a threat by either making participants armed or unarmed. Freezing was very strongly related to being armed, and within the armed-condition additionally to the degree of threat. The scientific concept of freezing has to be separated from the idea of "being frozen in fear." The task has been used to study neural effects related to freezing and the freeze-fight transition (Hashemi et al., 2019). Anticipatory effects of threat were further explored behaviourally in a subsequent study in which effects were explored of freeze-terminating stimuli. We looked at the effect of anticipated versus actual virtual attacks as distractors in an emotional Sternberg task. While an attack was impending, reaction times were slowed; but this appeared to be due to a reversible inhibited state that was released after the attack actually occurred. A stop-signal version of the Shooting task was used in a study of effects of sleep deprivation and threat on impulsive responding. This showed that threat affected impulsivity while sleep deprivation caused a general reduction of accuracy.
- Deconstructing dual-process models: see section 5 of the linked article and this chapter for an argument why we should talk about impulsive and reflective processing, defined parametrically in terms of response selection search time, rather than processes and separable systems. This is the R3 model of automaticity versus reflectivity that generated the anticipatory attentional bias / predictive ABM line of research. In the figure below, the R3 model is visualized with S(timulus), predicted O(utcomes) for responses and for delaying, R(esponses), an inhibitory D(elay) mechanism and Lateral Inhibition between responses. The activation of the processes represented by these abstractions are generally time-dependent, and so simply delaying the final selection of a response to execute may change the preferred response and the available information. The principle illustrated by this model is that impulsive versus reflective behavior can be generated by a continuous underlying parameter - how much will you delay? - rather than different types of processes. However, faster processes (e.g., more strongly reinforced associations, or simpler computations) will naturally dominate response selection more after shorter than longer delays.