Three experiments tested whether spatial attention can be influenced by a predictive relation between incidental information and the location of target events. Subjects performed a simple dot detection task; 600 msec prior to each target a word was presented briefly 5 degrees to the left or right of fixation. There was a predictive relationship between the semantic category (living or non-living) of the words and target location. However, subjects were instructed to ignore the words, and a post-experiment questionnaire confirmed that they remained unaware of the word-target relationship. In all three experiments, given some practice on the task, response times were faster when target appeared at likely ( p = 0.8 ), compared to unlikely ( p = 0.2 ) locations, in relation to lateral word category. Experiments 2 and 3 confirmed that this effect was driven by semantic encoding of the irrelevant words, and not by repetition of individual stimuli. Theoretical implications of this finding are discussed.

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In the framework of “togetherness” as a psychophysiological experience of social presence, the current chapter highlights the importance of work environments to socializing. The absence of such physical collective spaces impacts group-dynamics and team performance in online meetings, which also tend to prioritize task-solving discussions and limit non-verbal exchanges. Interpersonal coordination (or “social glue”), characterized by a spontaneous mutual attunement, both in speech and gestures, is classically observed during collective events where social-bonding and affiliation are promoted. This chapter will review the cognitive, behavioral, and physiological consequences of togetherness and integrate those in the context of recent technological advancements in computer-mediated interaction which have culminated in the advent of virtual and augmented reality. Given the potential of such methods to increase embodied interactions, they have been coined as “empathy machines” and could be seen as a technological solution to restore the experience of togetherness in the workplace.

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Prospective memory (PM, the memory of future intentions) is one of the first complaints of those that develop dementia-related disease. Little is known about the neurophysiology of PM in ageing and those with mild cognitive impairment (MCI). By using a novel artificial neural network to investigate the spatial and temporal features of PM related brain activity, new insights can be uncovered. Young adults (n = 30), healthy older adults (n = 39) and older adults with MCI (n = 27) completed a working memory and two PM (perceptual, conceptual) tasks. Time-locked electroencephalographic potentials (ERPs) from 128-electrodes were analysed using a brain-inspired spiking neural network (SNN) architecture. Local and global connectivity from the SNNs was then evaluated. SNNs outperformed other machine learning methods in classification of brain activity between younger, older and older adults with MCI. SNNs trained using PM related brain activity had better classification accuracy than working memory related brain activity. In general, younger adults exhibited greater local cluster connectivity compared to both older adult groups. Older adults with MCI demonstrated decreased global connectivity in response to working memory and perceptual PM tasks but increased connectivity in the conceptual PM models relative to younger and healthy older adults. SNNs can provide a useful method for differentiating between those with and without MCI. Using brain activity related to PM in combination with SNNs may provide a sensitive biomarker for detecting cognitive decline. Cognitively demanding tasks may increase the amount connectivity in older adults with MCI as a means of compensation.