Multi-target visual search organisation across the lifespan: cancellation task performance in a large and demographically stratified sample of healthy adults

Accurate tests of cognition are vital in (neuro)psychology. Cancellation tasks are popular tests of attention and executive function, in which participants find and ‘cancel’ targets among distractors. Despite extensive use in neurological patients, it remains unclear whether demographic variables (that vary among patients) affect cancellation performance. Here, we describe performance in 523 healthy participants of a web-based cancellation task. Age, sex, and level of education did not affect cancellation performance in this sample. We provide norm scores for indices of spatial bias, perseverations, revisits, processing speed, and search organisation. Furthermore, a cluster analysis identified four cognitive profiles among participants, characterised by many omissions (N=18), many revisits (N=18), relatively poor search organisation (N=125), and relatively good search organisation (N=362). Thus, patient scores pertaining to search organisation should be interpreted cautiously: Given the large proportion of healthy individuals with poor search organisation, disorganised search in patients might be pre-existing rather than disorder-related.     

Automatic behavioural responses to valence: Evidence that facial action is facilitated by evaluative processing

Are motor schemata of facial action spontaneously activated upon the processing of evaluative information? In this case, the processing of positive evaluative information should immediately trigger the motor schema of smiling, and the processing of negative information should trigger frowning. This hypothesis was tested in two experiments in which participants were required to respond to positive and negative words by either smiling or frowning. Electromyogram (EMG) activity was recorded over the brow muscle region (corrugator supercilii) and over the cheek muscle region (zygomaticus major) in order to quantify the latency of muscular response as a dependent measure. In Experiment 1 we found that participants were faster at contracting their zygomaticus muscle (which is involved in smiling) when evaluating positive words, and faster at contracting their corrugator muscle (which is involved in frowning) when evaluating negative words. In Experiment 2, participants were required to respond with the contraction of one of the two muscles whenever a word appeared on the computer screen. Again, we found that responses were faster to congruent response valence combinations than to incongruent response valence combinations. These findings support the hypothesis that evaluative processing is directly linked to motor schemata of facial muscles.     

A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial

Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological markers related to suicide, computer science provides opportunities to understand suicide thought markers. In this novel prospective, multimodal, multicenter, mixed demographic study, we used machine learning to measure and fuse two classes of suicidal thought markers: verbal and nonverbal. Machine learning algorithms were used with the subjects’ words and vocal characteristics to classify 379 subjects recruited from two academic medical centers and a rural community hospital into one of three groups: suicidal, mentally ill but not suicidal, or controls. By combining linguistic and acoustic characteristics, subjects could be classified into one of the three groups with up to 85% accuracy. The results provide insight into how advanced technology can be used for suicide assessment and prevention.