Motion and form coherence processing in individuals with cerebral visual impairment

Visuospatial processing in early brain-based visual impairment is associated with differential recruitment of dorsal and ventral visual streams

Visuospatial processing impairments are prevalent in individuals with cerebral visual impairment (CVI) and are typically ascribed to "dorsal stream dysfunction" (DSD). However, the contribution of other cortical regions, including early visual cortex (EVC), frontal cortex, or the ventral visual stream, to such impairments remains unknown. Thus, here, we examined fMRI activity in these regions, while individuals with CVI (and neurotypicals) performed a visual search task within a dynamic naturalistic scene. First, behavioral performance was measured with eye tracking. Participants were instructed to search and follow a walking human target. CVI participants took significantly longer to find the target, and their eye gaze patterns were less accurate and less precise. Second, we used the same task in the MRI scanner. Along the dorsal stream, activation was reduced in CVI participants, consistent with the proposed DSD in CVI. Intriguingly, however, visual areas along the ventral stream showed the complete opposite pattern, with greater activation in CVI participants. In contrast, we found no differences in either EVC or frontal cortex between groups. These results suggest that the impaired visuospatial processing abilities in CVI are associated with differential recruitment of the dorsal and ventral visual streams, likely resulting from impaired selective attention.

Visual search patterns during exploration of naturalistic scenes are driven by saliency cues in individuals with cerebral visual impairment

We investigated the relative influence of image salience and image semantics during the visual search of naturalistic scenes, comparing performance in individuals with cerebral visual impairment (CVI) and controls with neurotypical development. Participants searched for a prompted target presented as either an image or text cue. Success rate and reaction time were collected, and gaze behavior was recorded with an eye tracker. A receiver operating characteristic (ROC) analysis compared the distribution of individual gaze landings based on predictions of image salience (using Graph-Based Visual Saliency) and image semantics (using Global Vectors for Word Representations combined with Linguistic Analysis of Semantic Salience) models. CVI participants were less likely and were slower in finding the target. Their visual search behavior was also associated with a larger visual search area and greater number of fixations. ROC scores were also lower in CVI compared to controls for both model predictions. Furthermore, search strategies in the CVI group were not affected by cue type, although search times and accuracy showed a significant correlation with verbal IQ scores for text-cued searches. These results suggest that visual search patterns in CVI are driven mainly by image salience and provide further characterization of higher-order processing deficits observed in this population.

Rapid measurement and machine learning classification of colour vision deficiency

Colour vision deficiencies (CVDs) indicate potential genetic variations and can be important biomarkers of acquired impairment in many neuro-ophthalmic diseases. However, CVDs are typically measured with tests which possess high sensitivity for detecting the presence of a CVD but do not quantify its type or severity. In this study, we introduce Foraging Interactive D-prime (FInD), a novel computer-based, generalisable, rapid, self-administered vision assessment tool and apply it to colour vision testing. This signal detection theory-based adaptive paradigm computed test stimulus intensity from d-prime analysis. Stimuli were chromatic Gaussian blobs in dynamic luminance noise, and participants clicked on cells that contained chromatic blobs (detection) or blob pairs of differing colours (discrimination). Sensitivity and repeatability of FInD colour tasks were compared against the Hardy-Rand-Rittler and the Farnsworth-Munsell 100 hue tests in 19 colour-normal and 18 inherited colour-atypical, age-matched observers. Rayleigh colour match was also completed. Detection and discrimination thresholds were higher for atypical than for typical observers, with selective threshold elevations corresponding to unique CVD types. Classifications of CVD type and severity via unsupervised machine learning confirmed functional subtypes. FInD tasks reliably detect inherited CVDs, and may serve as valuable tools in basic and clinical colour vision science.