How much of the structure of the human mind and brain is already specified at birth, and how much arises from experience? In this article, we consider the test case of extrastriate visual cortex, ...where a highly systematic functional organization is present in virtually every normal adult, including regions preferring behaviourally significant stimulus categories, such as faces, bodies, and scenes. Novel methods were developed to scan awake infants with fMRI, while they viewed multiple categories of visual stimuli. Here we report that the visual cortex of 4-6-month-old infants contains regions that respond preferentially to abstract categories (faces and scenes), with a spatial organization similar to adults. However, precise response profiles and patterns of activity across multiple visual categories differ between infants and adults. These results demonstrate that the large-scale organization of category preferences in visual cortex is adult-like within a few months after birth, but is subsequently refined through development.
Abstract
A recent neuroimaging study in adults found that the occipital place area (OPA)—a cortical region involved in “visually guided navigation” (i.e. moving about the immediately visible ...environment, avoiding boundaries, and obstacles)—represents visual information about walking, not crawling, suggesting that OPA is late developing, emerging only when children are walking, not beforehand. But when precisely does this “walking selectivity” in OPA emerge—when children first begin to walk in early childhood, or perhaps counterintuitively, much later in childhood, around 8 years of age, when children are adult-like walking? To directly test these two hypotheses, using functional magnetic resonance imaging (fMRI) in two groups of children, 5- and 8-year-olds, we measured the responses in OPA to first-person perspective videos through scenes from a “walking” perspective, as well as three control perspectives (“crawling,” “flying,” and “scrambled”). We found that the OPA in 8-year-olds—like adults—exhibited walking selectivity (i.e. responding significantly more to the walking videos than to any of the others, and no significant differences across the crawling, flying, and scrambled videos), while the OPA in 5-year-olds exhibited no walking selectively. These findings reveal that OPA undergoes protracted development, with walking selectivity only emerging around 8 years of age.
Functional magnetic resonance imaging has revealed a set of regions selectively engaged in visual scene processing: the parahippocampal place area (PPA), the retrosplenial complex (RSC), and a region ...around the transverse occipital sulcus (previously known as "TOS"), here renamed the "occipital place area" (OPA). Are these regions not only preferentially activated by, but also causally involved in scene perception? Although past neuropsychological data imply a causal role in scene processing for PPA and RSC, no such evidence exists for OPA. Thus, to test the causal role of OPA in human adults, we delivered transcranial magnetic stimulation (TMS) to the right OPA (rOPA) or the nearby face-selective right occipital face area (rOFA) while participants performed fine-grained perceptual discrimination tasks on scenes or faces. TMS over rOPA impaired discrimination of scenes but not faces, while TMS over rOFA impaired discrimination of faces but not scenes. In a second experiment, we delivered TMS to rOPA, or the object-selective right lateral occipital complex (rLOC), while participants performed categorization tasks involving scenes and objects. TMS over rOPA impaired categorization accuracy of scenes but not objects, while TMS over rLOC impaired categorization accuracy of objects but not scenes. These findings provide the first evidence that OPA is causally involved in scene processing, and further show that this causal role is selective for scene perception. Our findings illuminate the functional architecture of the scene perception system, and also argue against the "distributed coding" view in which each category-selective region participates in the representation of all objects.
•Visual scene stimuli share a common vertical luminance gradient (VLG).•VLG is correlated with cortical scene selectivity in complex, naturalistic stimuli.•Tightly controlled stimuli of VLG drive ...cortical scene selectivity.•Humans behaviorally categorize tightly controlled stimuli of VLG as a “place”.•Visual scenes may be characterized by a set of common and unique features.
Human neuroimaging studies have revealed a dedicated cortical system for visual scene processing. But what is a “scene”? Here, we use a stimulus-driven approach to identify a stimulus feature that selectively drives cortical scene processing. Specifically, using fMRI data from BOLD5000, we examined the images that elicited the greatest response in the cortical scene processing system, and found that there is a common “vertical luminance gradient” (VLG), with the top half of a scene image brighter than the bottom half; moreover, across the entire set of images, VLG systematically increases with the neural response in the scene-selective regions (Study 1). Thus, we hypothesized that VLG is a stimulus feature that selectively engages cortical scene processing, and directly tested the role of VLG in driving cortical scene selectivity using tightly controlled VLG stimuli (Study 2). Consistent with our hypothesis, we found that the scene-selective cortical regions—but not an object-selective region or early visual cortex—responded significantly more to images of VLG over control stimuli with minimal VLG. Interestingly, such selectivity was also found for images with an “inverted” VLG, resembling the luminance gradient in night scenes. Finally, we also tested the behavioral relevance of VLG for visual scene recognition (Study 3); we found that participants even categorized tightly controlled stimuli of both upright and inverted VLG to be a place more than an object, indicating that VLG is also used for behavioral scene recognition. Taken together, these results reveal that VLG is a stimulus feature that selectively engages cortical scene processing, and provide evidence for a recent proposal that visual scenes can be characterized by a set of common and unique visual features.
Neuroimaging studies have identified multiple face-selective regions in human cortex but the functional division of labor between these regions is not yet clear. A central hypothesis, with some ...empirical support, is that face-selective regions in the superior temporal sulcus (STS) are particularly responsive to dynamic information in faces, whereas the fusiform face area (FFA) computes the static or invariant properties of faces. Here we directly tested this hypothesis by measuring the magnitude of response in each region to both dynamic and static stimuli. Consistent with the hypothesis, we found that the response to movies of faces was not significantly different from the response to static images of faces from these same movies in the right FFA and right occipital face area (OFA). By contrast the face-selective region in the right posterior STS (pSTS) responded nearly three times as strongly to dynamic faces as to static faces, and a face-selective region in the right anterior STS (aSTS) responded to dynamic faces only. Both of these regions also responded more strongly to moving faces than to moving bodies, indicating that they are preferentially engaged in processing dynamic information from faces, not in more general processing of any dynamic social stimuli. The response to dynamic and static faces was not significantly different in a third face-selective region in the posterior continuation of the STS (pcSTS). The strong selectivity of face-selective regions in the pSTS and aSTS, but not the FFA, OFA or pcSTS, for dynamic face information demonstrates a clear functional dissociation between different face-selective regions, and provides further clues into their function.
► The face-selective rpSTS region shows a strong preference for dynamic faces. ► The face-selective raSTS region responds to dynamic faces only. ► The rFFA and rOFA do not distinguish between dynamic and static faces.
Despite over two decades of research on the neural mechanisms underlying human visual scene, or place, processing, it remains unknown what exactly a “scene” is. Intuitively, we are always inside a ...scene, while interacting with the outside of objects. Hence, we hypothesize that one diagnostic feature of a scene may be concavity, portraying “inside”, and predict that if concavity is a scene-diagnostic feature, then: 1) images that depict concavity, even non-scene images (e.g., the “inside” of an object – or concave object), will be behaviorally categorized as scenes more often than those that depict convexity, and 2) the cortical scene-processing system will respond more to concave images than to convex images. As predicted, participants categorized concave objects as scenes more often than convex objects, and, using functional magnetic resonance imaging (fMRI), two scene-selective cortical regions (the parahippocampal place area, PPA, and the occipital place area, OPA) responded significantly more to concave than convex objects. Surprisingly, we found no behavioral or neural differences between images of concave versus convex buildings. However, in a follow-up experiment, using tightly-controlled images, we unmasked a selective sensitivity to concavity over convexity of scene boundaries (i.e., walls) in PPA and OPA. Furthermore, we found that even highly impoverished line drawings of concave shapes are behaviorally categorized as scenes more often than convex shapes. Together, these results provide converging behavioral and neural evidence that concavity is a diagnostic feature of visual scenes.
A long-standing question in neuroscience is how perceptual processes select stimuli for encoding and later retrieval by memory processes. Using a functional magnetic resonance imaging study with ...human participants, we report the discovery of a global, stimulus-driven processing stream that we call memorability. Memorability automatically tags the statistical distinctiveness of stimuli for later encoding, and shows separate neural signatures from both low-level perception (memorability shows no signal in early visual cortex) and classical subsequent memory based on individual memory. Memorability and individual subsequent memory show dissociable neural substrates: first, memorability effects consistently emerge in the medial temporal lobe (MTL), whereas individual subsequent memory effects emerge in the prefrontal cortex (PFC). Second, memorability effects remain consistent even in the absence of memory (i.e., for forgotten images). Third, the MTL shows higher correlations with memorability-based patterns, while the PFC shows higher correlations with individual memory voxels patterns. Taken together, these results support a reformulated framework of the interplay between perception and memory, with the MTL determining stimulus statistics and distinctiveness to support later memory encoding, and the PFC comparing stimuli to specific individual memories. As stimulus memorability is a confound present in many previous memory studies, these findings should stimulate a revisitation of the neural streams dedicated to perception and memory.
•Memorability is an intrinsic perceptual property with dedicated neural signals.•Ventral visual stream, medial temporal lobe sensitive to face, scene memorability.•Early visual cortex and attention regions show no memorability sensitivity.•Memorability effects exist even in the absence of memory (i.e., forgotten images).•Dissociation of neural patterns and loci between memorability and memory.
Historically, it has been argued that face individuation develops very slowly, not reaching adult levels until adolescence, with experience being the driving force behind this protracted improvement. ...Here, we challenge this view based on extensive review of behavioural and neural findings. Results demonstrate qualitative presence of all key phenomena related to face individuation (encoding of novel faces, holistic processing effects, face-space effects, face-selective responses in neuroimaging) at the earliest ages tested, typically 3-5 years of age and in many cases even infancy. Results further argue for quantitative maturity by early childhood, based on an increasing number of behavioural studies that have avoided the common methodological problem of restriction of range, as well as event-related potential (ERP), but not functional magnetic resonance imaging (fMRI) studies. We raise a new possibility that could account for the discrepant fMRI findings-namely, the use of adult-sized head coils on child-sized heads. We review genetic and innate contributions to face individuation (twin studies, neonates, visually deprived monkeys, critical periods, perceptual narrowing). We conclude that the role of experience in the development of the mechanisms of face identification has been overestimated. The emerging picture is that the mechanisms supporting face individuation are mature early, consistent with the social needs of children for reliable person identification in everyday life, and are also driven to an important extent by our evolutionary history.
We represent the locations of places (e.g., the coffee shop on 10th Street vs. the coffee shop on Peachtree Street) so that we can use them as landmarks to orient ourselves while navigating ...large-scale environments. While several neuroimaging studies have argued that the parahippocampal place area (PPA) represents such navigationally relevant information, evidence from other studies suggests otherwise, leaving this issue unresolved. Here we hypothesize that the PPA is, in fact, not well suited to recognize specific landmarks in the environment (e.g., the coffee shop on 10th Street), but rather is involved in recognizing the general category membership of places (e.g., a coffee shop, regardless of its location). Using fMRI multivoxel pattern analysis, we directly test this hypothesis. If the PPA represents landmark information, then it must be able to discriminate between 2 places of the same category, but in different locations. Instead, if the PPA represents general category information (as hypothesized here), then it will not represent the location of a particular place, but only the category of the place. As predicted, we found that the PPA represents 2 buildings from the same category, but in different locations, as more similar than 2 buildings from different categories, but in the same location. In contrast, another scene-selective region of cortex, the retrosplenial complex (RSC), showed the exact opposite pattern of results. Such a double dissociation suggests distinct neural systems involved in categorizing and navigating our environment, including the PPA and RSC, respectively.
Abstract
Recent work has shown that the occipital place area (OPA)—a scene-selective region in adult humans—supports “visually guided navigation” (i.e. moving about the local visual environment and ...avoiding boundaries/obstacles). But what is the precise role of OPA in visually guided navigation? Considering humans move about their local environments beginning with crawling followed by walking, 1 possibility is that OPA is involved in both modes of locomotion. Another possibility is that OPA is specialized for walking only, since walking and crawling are different kinds of locomotion. To test these possibilities, we measured the responses in OPA to first-person perspective videos from both “walking” and “crawling” perspectives as well as for 2 conditions by which humans do not navigate (“flying” and “scrambled”). We found that OPA responded more to walking videos than to any of the others, including crawling, and did not respond more to crawling videos than to flying or scrambled ones. These results (i) reveal that OPA represents visual information only from a walking (not crawling) perspective, (ii) suggest crawling is processed by a different neural system, and (iii) raise questions for how OPA develops; namely, OPA may have never supported crawling, which is consistent with the hypothesis that OPA undergoes protracted development.
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