Differential Deployment of Visual Attention During Interactive Approach and Avoidance Behavior

Abstract

The ability to coordinate approach and avoidance actions in dynamic environments represents the boundary between extinction and the continued survival of many animal species. It is therefore crucial that sensory systems allocate limited attentional resources to the most relevant information to facilitate planning and execution of appropriate actions. Prominent theories of how attention regulates visual processing focus on the distinction between behaviorally relevant and irrelevant visual inputs. To date, however, no study has directly compared the deployment of attention to visual inputs relevant for approach and avoidance behaviors, which naturally occur in dynamic, interactive environments. In two experiments, we combined electroencephalography, frequency tagging, and eye gaze measures to investigate whether the deployment of visual selective attention differs for items relevant for approach and avoidance actions. Participants maneuvered a cursor to approach and avoid contact with moving items in a continuous interactive task. The results indicated that while the approach and avoidance tasks recruited equivalent attentional resources overall, attentional biases were directed toward task-relevant items during approach, and away from task-relevant items during avoidance. We conclude that the deployment of visual attention is guided not only by relevance to a behavioral goal, but also by the nature of that goal.

Optimising non-invasive brain-computer interface systems for free communication between naïve human participants

“…SSVEP amplitudes were larger for the high compared with low accuracy group, especially for the first three harmonics. The grand mean SSVEP amplitude topographies of the first harmonics revealed maximal amplitudes at occipitoparietal sites, consistent with previous frequency tagging studies of attention 49–51 , with larger amplitudes for the high compared with low accuracy group (Fig. 4c).…”

Optimising the classification of feature-based attention in frequency-tagged electroencephalography data

“…This relatively long trial period was chosen to allow for sliding window decoding of the current target of feature selective attention over prolonged periods of constant stimulation, a desirable feature for BCI control. Participants should be able to switch their feature-selective attention between two stable targets indefinitely, and previous work suggests that the effects of feature selective attention on SSVEP amplitudes remain discriminable for at least the duration of 15 s trials 6 . Each 15 s period of dot motion contained five 500 ms bursts of coherent motion (targets).…”

“…BCI systems apply real-time decoding algorithms to human neuroimaging data, with the goal of extracting reliable patterns of neural activity to operate external devices or provide neurofeedback training 1 – 4 . Visual selective attention, the brain’s ability to selectively allocate its limited processing resources to a behaviourally relevant subset of visual inputs, is a common target for BCI control 5 , 6 . By deliberately shifting attentional focus across visual elements in a display, human participants are able to enhance their neural response to some display elements while suppressing their response to others 7 , 8 .…”

“…To track how attention is distributed across multiple concurrent visual stimuli, neuroscientists often use frequency tagging methods 6 , 8 , 23 – 25 . Frequency tagging involves flickering visual stimuli at specific frequencies, thus eliciting time-locked frequency-specific responses from visual system neural populations, termed steady-state visual evoked potentials (SSVEPs) 25 , 26 .…”

In pursuit of visual attention: SSVEP frequency-tagging moving targets

“…In addition, it is likely that some tasks and conditions might involve differences in target-tracking accuracy, where specific conditions or contexts are more likely to elicit saccades that are difficult to inhibit (or in populations where such inhibition might be impaired). An analysis of trial rejection may therefore provide an index of this, as well as more in-depth analysis of gaze-behaviour in the trials as a means of relating such behavior with visual attention during periods of target pursuit [51]. However, experimental conditions with significantly different numbers of accepted trials might further complicate the interpretation of the comparison of SSVEP responses in these conditions as the signal-to-noise ratios in the EEG averages is strongly affected by this factor.…”