One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that—despite some variability in CF estimates between RS scans—neural properties such as CF maps and CF size can be derived from resting state data.

Responsiveness to hypnotic procedures has been related to unusual eye behaviors for centuries. Kallio and collaborators claimed recently that they had found a reliable index for "the hypnotic state" through eye-tracking methods. Whether or not hypnotic responding involves a special state of consciousness has been part of a contentious debate in the field, so the potential validity of their claim would constitute a landmark. However, their conclusion was based on 1 highly hypnotizable individual compared with 14 controls who were not measured on hypnotizability. We sought to replicate their results with a sample screened for High (n = 16) or Low (n = 13) hypnotizability. We used a factorial 2 (high vs. low hypnotizability) x 2 (hypnosis vs. resting conditions) counterbalanced order design with these eye-tracking tasks: Fixation, Saccade, Optokinetic nystagmus (OKN), Smooth pursuit, and Antisaccade (the first three tasks has been used in Kallio et al.'s experiment). Highs reported being more deeply in hypnosis than Lows but only in the hypnotic condition, as expected. There were no significant main or interaction effects for the Fixation, OKN, or Smooth pursuit tasks. For the Saccade task both Highs and Lows had smaller saccades during hypnosis, and in the Antisaccade task both groups had slower Antisaccades during hypnosis. Although a couple of results suggest that a hypnotic condition may produce reduced eye motility, the lack of significant interactions (e.g., showing only Highs expressing a particular eye behavior during hypnosis) does not support the claim that eye behaviors (at least as measured with the techniques used) are an indicator of a "hypnotic state.” Our results do not preclude the possibility that in a more spontaneous or different setting the experience of being hypnotized might relate to specific eye behaviors.

Visual object recognition occurs at the intersection of visual perception and visual cognition. It typically occurs very fast and it has therefore been difficult to disentangle its constituent processes. Recognition time can be extended when using images with emergent properties, suggesting they may help examining how visual recognition unfolds over time. Until now, their use has been constrained by limited availability. We used a set of stimuli with emergent properties-akin to the famous Gestalt image of a Dalmatian-in combination with eye tracking to examine the processes underlying object recognition. To test whether cognitive processes influenced eye movement behavior during recognition, an unprimed and three primed groups were included. Recognition times were relatively long (median ∼ 5s for the unprimed group), confirming the object's emergent properties. Surprisingly, within the first 500 ms, the majority of fixations were already aimed at the object. Computational models of saliency could not explain these initial fixations. This suggests that observers relied on image statistics not captured by saliency models. For the primed groups, recognition times were reduced. However, threshold-free cluster enhancement-based analysis of the time courses indicated that viewing behavior did not differ between the groups, neither during the initial viewing nor around the moment of recognition. This implies that eye movements are mainly driven by perceptual processes and not affected by cognition. It further suggests that priming mainly boosts the observer's confidence in the decision reached. We conclude that emerging images can be a useful tool to dissociate the perceptual and cognitive contributions to visual object recognition.