The influence of attentional load on population receptive field properties

Spatial attention enhances perception by attracting population receptive fields (pRFs) towards the attended locus. Our recent work has shown the degree of this attraction can be altered by precision of attention. In addition to spatial features of attention, understanding how qualitative aspects of attention, such as attentional load, influence pRF properties requires further investigation. The Gaussian attention field model is often used to summarize the locus and precision of attention by a Gaussian. In this context, attentional load is the amplitude of the attention field. Notably, this model predicts no effect of altering the amplitude of the attention field. Based on previous results, we added an offset of 1 to the attention field (AF+1 model), this better captured the effects of precision of attention while maintaining the core prediction of attraction towards the attended locus. In contrast, the AF+1 model predicts the amplitude of the attention field does influence resulting pRFs. Here, we compared these model predictions and investigated the effect of attentional load on pRF properties. We used 7T MRI to map pRFs while participants carried out an RSVP detection task at fixation. A stream of symbols which varied in color and orientation was presented at a rate of 5.3 Hz. Two attention conditions with identical stimuli were compared: low load where participants detected only a target symbol regardless of color and orientation and high load where participants detected two targets symbols each of a specific color and orientation combination. Additionally, separate pRF-mapping sessions were carried out to obtain pRF parameters independent of the two conditions. Behavioral results showed that the difficulty of the two conditions varied, with higher D’ values for the low-load condition compared to the high-load condition. Preliminary data shows some pRF property differences between conditions, indicating that attentional load alters visual representations of space.