Adaptive shape coding for perceptual decisions in the human brain

Circadian Responses to Light-Flash Exposure: Conceptualization and New Data Guiding Future Directions

A growing number of studies document circadian phase-shifting after exposure to millisecond light flashes. When strung together by intervening periods of darkness, these stimuli evoke pacemaker responses rivaling or outmatching those created by steady luminance, suggesting that the circadian system's relationship to light can be contextualized outside the principle of simple dose-dependence. In the current review, we present a brief chronology of this work. We then develop a conceptual model around it that attempts to relate the circadian effects of flashes to a natural integrative process the pacemaker uses to intermittently sample the photic information available at dawn and dusk. Presumably, these snapshots are employed as building blocks in the construction of a coherent representation of twilight the pacemaker consults to orient the next day's physiology (in that way, flash-resetting of pacemaker rhythms might be less an example of a circadian visual illusion and more an example of the kinds of gestalt inferences that the image-forming system routinely makes when identifying objects within the visual field; i.e., closure). We conclude our review with a discussion on the role of cones in the pacemaker's twilight predictions, providing new electrophysiological data suggesting that classical photoreceptors—but not melanopsin—are necessary for millisecond, intermediate-intensity flash responses in ipRGCs (intrinsically photosensitive retinal ganglion cells). Future investigations are necessary to confirm this “Cone Sentinel Model” of circadian flash-integration and twilight-prediction, and to further define the contribution of cones vs. rods in transducing pacemaker flash signals.

Differences in selectivity to natural images in early visual areas (V1-V3)

High-level regions of the ventral visual pathway respond more to intact objects compared to scrambled objects. The aim of this study was to determine if this selectivity for objects emerges at an earlier stage of processing. Visual areas (V1–V3) were defined for each participant using retinotopic mapping. Participants then viewed intact and scrambled images from different object categories (bottle, chair, face, house, shoe) while neural responses were measured using fMRI. Our rationale for using scrambled images is that they contain the same low-level properties as the intact objects, but lack the higher-order combinations of features that are characteristic of natural images. Neural responses were higher for scrambled than intact images in all regions. However, the difference between intact and scrambled images was smaller in V3 compared to V1 and V2. Next, we measured the spatial patterns of response to intact and scrambled images from different object categories. We found higher within-category compared to between category correlations for both intact and scrambled images demonstrating distinct patterns of response. Spatial patterns of response were more distinct for intact compared to scrambled images in V3, but not in V1 or V2. These findings demonstrate the emergence of selectivity to natural images in V3.

Low-level properties of natural images predict topographic patterns of neural response in the ventral visual pathway

Neuroimaging research over the past 20 years has begun to reveal a picture of how the human visual system is organized. A key distinction that has arisen from these studies is the difference in the organization of low-level and high-level visual regions. Low-level regions contain topographic maps that are tightly linked to properties of the image. In contrast, high-level visual areas are thought to be arranged in modules that are tightly linked to categorical or semantic information in the image. To date, an unresolved question has been how the strong functional selectivity for object categories in high-level visual regions might arise from the image-based representations found in low-level visual regions. Here, we review recent evidence suggesting that patterns of response in high-level visual areas may be better explained by response to image properties that are characteristic of different object categories.

Understanding mid-level representations in visual processing

It is clear that early visual processing provides an image-based representation of the visual scene: Neurons in Striate cortex (V1) encode nothing about the meaning of a scene, but they do provide a great deal of information about the image features within it. The mechanisms of these "low-level" visual processes are relatively well understood. We can construct plausible models for how neurons, up to and including those in V1, build their representations from preceding inputs down to the level of photoreceptors. It is also clear that at some point we have a semantic, "high-level" representation of the visual scene because we can describe verbally the objects that we are viewing and their meaning to us. A huge number of studies are examining these "high-level" visual processes each year. Less well studied are the processes of "mid-level" vision, which presumably provide the bridge between these "low-level" representations of edges, colors, and lights and the "high-level" semantic representations of objects, faces, and scenes. This article and the special issue of papers in which it is published consider the nature of "mid-level" visual processing and some of the reasons why we might not have made as much progress in this domain as we would like.