Master of Science
Pattern separation is a neural computation thought to underlie our ability to form distinct memories of similar events. It involves transforming overlapping inputs into less overlapping outputs. In the ventral visual stream (VVS) there is considerable evidence for hierarchical transformation from feature-based visual representations to conjunctive whole-object representations, with the latter allowing for distinct coding even when objects have significant feature overlap. In the current study, we asked whether this transformation can be understood as pattern separation, and whether pattern separation can be observed even outside the context of classic recognition-memory tasks. To investigate pattern separation in the VVS, we combined fMRI in humans (N=23) with multivariate pattern analyses techniques and compared representations of visual objects in a mid-level visual region, Lateral Occipital (LO) region, with those in the region proposed to be at the top of the VVS object processing hierarchy, Perirhinal Cortex (PRC). During scanning we presented images of objects from multiple categories, with differing degrees of visual similarity among exemplars during performance of an N-Back task. Imaging results obtained using classification revealed patterns in LO could be distinguished successfully for all categories and at the lowest level of visual similarity within category exemplars. In contrast, patterns in PRC could be distinguished at all levels of similarity within a category, but no successful category differentiations were found. Because patterns at higher levels of visual similarity are overlapping in LO, but can be differentiated in PRC, these results provide evidence for pattern separation in the VVS. More broadly, this suggests that the engagement of pattern separation may not be restricted to the hippocampus during declarative-memory tasks.
Summary for Lay Audience
The ability to distinguish two similar ‘things’ is important in everyday life. These ‘things’ can be memories, for example, finding your car in the parking garage every day. Although the environment is very similar we are able to differentiate one day from the next. The neural process involved here is pattern separation. Pattern separation functions by transferring similar neural signals in one region to completely distinct neural signals in another region. Therefore, researchers can investigate this phenomenon by measuring how similar brain patterns are in different regions when participants complete a memory task. Previous animal and human research has provided evidence that the hippocampus plays an important role in separating similar signals from its input region, entorhinal cortex. But does pattern separation occur before the hippocampus and not solely during memory tasks?
The goal of this study was to investigate whether or not pattern separation exists upstream from the hippocampus in the ventral visual stream during object perception. To address this goal 23 human participants were scanned in a functional MR scanner to obtain pictures of their brain as they viewed images of objects on a screen. We presented images of objects from multiple categories, with differing degrees of visual similarity within a category.
Imaging results obtained by analyzing the neural patterns elicited by the stimuli revealed differences in mid-level visual region, lateral occipital (LO) region and the region thought to be at the top of the visual processing hierarchy, perirhinal cortex (PRC). In LO, patterns could be distinguished successfully when they represented different categories or within-category objects at the lowest level of visual similarity. In contrast, while all levels of visual similarity within a category could be distinguished successfully in PRC; no categories could be distinguished here. Because patterns at higher levels of visual similarity are non-distinguishable in LO, but can be differentiated in PRC, these results provide evidence for pattern separation in the ventral visual stream.
Ferko, Kayla, "Pattern Separation in the Ventral Visual Stream" (2019). Electronic Thesis and Dissertation Repository. 6485.