Autism and the development of face processing

Autism is a pervasive developmental condition, characterized by impairments in non-verbal communication, social relationships and stereotypical patterns of behavior. A large body of evidence suggests that several aspects of face processing are impaired in autism, including anomalies in gaze processing, memory for facial identity and recognition of facial expressions of emotion. In search of neural markers of anomalous face processing in autism, much interest has focused on a network of brain regions that are implicated in social cognition and face processing. In this review, we will focus on three such regions, namely the STS for its role in processing gaze and facial movements, the FFA in face detection and identification and the amygdala in processing facial expressions of emotion. Much evidence suggests that a better understanding of the normal development of these specialized regions is essential for discovering the neural bases of face processing anomalies in autism. Thus, we will also examine the available literature on the normal development of face processing. Key unknowns in this research area are the neuro-developmental processes, the role of experience and the interactions among components of the face processing system in shaping each of the specialized regions for processing faces during normal development and in autism.     

High-resolution imaging reveals highly selective nonface clusters in the fusiform face area

A region in ventral human cortex (fusiform face area, FFA) thought to be important for face perception responds strongly to faces and less strongly to nonface objects. This pattern of response may reflect a uniform face-selective neural population or activity averaged across populations with heterogeneous selectivity. Using high-resolution functional magnetic resonance imaging (MRI), we found that the FFA has a reliable heterogeneous structure: localized subregions within the FFA highly selective to faces are spatially interdigitated with localized subregions highly selective to different object categories. We found a preponderance of face-selective responses in the FFA, but no difference in selectivity to faces compared to nonfaces. Thus, standard fMRI of the FFA reflects averaging of heterogeneous highly selective neural populations of differing sizes, rather than higher selectivity to faces. These results suggest that visual processing in this region is not exclusive to faces. Overall, our approach provides a framework for understanding the fine-scale structure of neural representations in the human brain.     

Representation of shapes, edges, and surfaces across multiple cues in the human visual cortex

The lateral occipital complex (LOC) responds preferentially to objects compared with random stimuli or textures independent of the visual cue. However, it is unknown whether the LOC (or other cortical regions) are involved in the processing of edges or global surfaces without shape information. Here, we examined processing of 1) global shape, 2) disconnected edges without a global shape, and 3) global surfaces without edges versus random stimuli across motion and stereo cues. The LOC responded more strongly to global shapes than to edges, surfaces, or random stimuli, for both motion and stereo cues. However, its responses to local edges or global surfaces were not different from random stimuli. This suggests that the LOC processes shapes, not edges or surfaces. LOC also responded more strongly to objects than to holes with the same shape, suggesting sensitivity to border ownership. V7 responded more strongly to edges than to surfaces or random stimuli for both motion and stereo cues, whereas V3a and V4 preferred motion edges. Finally, a region in the caudal intraparietal sulcus (cIPS) responded more strongly to both stereo versus motion and to stereo surfaces versus random stereo (but not to motion surfaces vs. random motion). Thus we found evidence for cue-specific responses to surfaces in the cIPS, both cue-specific and cue-independent responses to edges in intermediate visual areas, and shape-selective responses across multiple cues in the LOC. Overall, these data suggest that integration of visual information across multiple cues is mainly achieved at the level of shape and underscore LOC's role in shape computations.     

A sequence of object-processing stages revealed by fMRI in the human occipital lobe

Functional magnetic resonance imaging was used in combined functional selectivity and retinotopic mapping tests to reveal object-related visual areas in the human occpital lobe. Subjects were tested with right, left, up, or down hemivisual field stimuli which were composed of images of natural objects (faces, animals, man-made objects) or highly scrambled (1,024 elements) versions of the same images. In a similar fashion, the horizontal and vertical meridians were mapped to define the borders of these areas. Concurrently, the same cortical sites were tested for their sensitivity to image-scrambling by varying the number of scrambled picture fragments (from 16–1,024) while controlling for the Fourier power spectrum of the pictures and their order of presentation. Our results reveal a stagewise decrease in retinotopy and an increase in sensitivity to image-scrambling. Three main distinct foci were found in the human visual object recognition pathway (Ungerleider and Haxby [1994]: Curr Opin Neurobiol 4:157–165): 1) Retinotopic primary areas V1–3 did not exhibit significant reduction in activation to scrambled images. 2) Areas V4v (Sereno et al., [1995]: Science 268:889–893) and V3A (DeYoe et al., [1996]: Proc Natl Acad Sci USA 93:2382–2386; Tootell et al., [1997]: J Neurosci 71:7060–7078) manifested both retinotopy and decreased activation to highly scrambled images. 3) The essentially nonretinotopic lateral occipital complex (LO) (Malach et al., [1995]: Proc Natl Acad Sci USA 92:8135–8139; Tootell et al., [1996]: Trends Neurosci 19:481–489) exhibited the highest sensitivity to image scrambling, and appears to be homologous to macaque the infero-temporal (IT) cortex (Tanaka [1996]: Curr Opin Neurobiol 523–529). Breaking the images into 64, 256, or 1,024 randomly scrambled blocks reduced activation in LO voxels. However, many LO voxels remained significantly activated by mildly scrambled images (16 blocks). These results suggest the existence of object-fragment representation in LO. Hum. Brain Mapping 6:316–328, 1998. © 1998 Wiley-Liss, Inc.     

White matter microstructure on diffusion tensor imaging is associated with conventional magnetic resonance imaging findings and cognitive function in adolescents born preterm

Aim Diffusion tensor imaging (DTI) was used to evaluate white matter architecture after preterm birth. The goals were (1) to compare white matter microstructure in two cohorts of preterm‐ and term‐born children; and (2) within preterm groups, to determine if sex, gestational age, birthweight, white matter injury score from conventional magnetic resonance imaging (MRI), or IQ was associated with DTI measures. Method Participants (n=121; 66 females, 55 males) were aged 9 to 16 years. They comprised 58 preterm children (site 1, n=25; and site 2, n=33) born at less than 36 weeks’ gestation (mean 29.4wks; birthweight 1289g) and 63 term children (site 1, n=40; site 2, n=23) born at more than 37 weeks’ gestation. DTI was analyzed using tract‐based spatial statistics. Diffusion measures were fractional anisotropy, axial, radial, and mean diffusivity. Results In no region of the white matter skeleton was fractional anisotropy lower in the preterm group at either site. Within the preterm groups, fractional anisotropy was significantly associated with white matter injury score, but not sex, gestational age, or birthweight. At site 1, fractional anisotropy was associated with IQ. Interpretation DTI contributes to understanding individual differences after preterm birth but may not differentiate a relatively high‐functioning group of preterm children from a matched group of term‐born children.     

Face-likeness and image variability drive responses in human face-selective ventral regions

The human ventral visual stream contains regions that respond selectively to faces over objects. However, it is unknown whether responses in these regions correlate with how face-like stimuli appear. Here, we use parameterized face silhouettes to manipulate the perceived face-likeness of stimuli and measure responses in face- and object-selective ventral regions with high-resolution fMRI. We first use "concentric hyper-sphere" (CH) sampling to define face silhouettes at different distances from the prototype face. Observers rate the stimuli as progressively more face-like the closer they are to the prototype face. Paradoxically, responses in both face- and object-selective regions decrease as face-likeness ratings increase. Because CH sampling produces blocks of stimuli whose variability is negatively correlated with face-likeness, this effect may be driven by more adaptation during high face-likeness (low-variability) blocks than during low face-likeness (high-variability) blocks. We tested this hypothesis by measuring responses to matched-variability (MV) blocks of stimuli with similar face-likeness ratings as with CH sampling. Critically, under MV sampling, we find a face-specific effect: responses in face-selective regions gradually increase with perceived face-likeness, but responses in object-selective regions are unchanged. Our studies provide novel evidence that face-selective responses correlate with the perceived face-likeness of stimuli, but this effect is revealed only when image variability is controlled across conditions. Finally, our data show that variability is a powerful factor that drives responses across the ventral stream. This indicates that controlling variability across conditions should be a critical tool in future neuroimaging studies of face and object representation.     

Object-selective cortex exhibits performance-independent repetition suppression

Object-selective cortical regions exhibit a decreased response when an object stimulus is repeated [repetition suppression (RS)]. RS is often associated with priming: reduced response times and increased accuracy for repeated stimuli. It is unknown whether RS reflects stimulus-specific repetition, the associated changes in response time, or the combination of the two. To address this question, we performed a rapid event-related functional MRI (fMRI) study in which we measured BOLD signal in object-selective cortex, as well as object recognition performance, while we manipulated stimulus repetition. Our design allowed us to examine separately the roles of response time and repetition in explaining RS. We found that repetition played a robust role in explaining RS: repeated trials produced weaker BOLD responses than nonrepeated trials, even when comparing trials with matched response times. In contrast, response time played a weak role in explaining RS when repetition was controlled for: it explained BOLD responses only for one region of interest (ROI) and one experimental condition. Thus repetition suppression seems to be mostly driven by repetition rather than performance changes. We further examined whether RS reflects processes occurring at the same time as recognition or after recognition by manipulating stimulus presentation duration. In one experiment, durations were longer than required for recognition (2 s), whereas in a second experiment, durations were close to the minimum time required for recognition (85-101 ms). We found significant RS for brief presentations (albeit with a reduced magnitude), which again persisted when controlling for performance. This suggests a substantial amount of RS occurs during recognition.     

Relating retinotopic and object-selective responses in human lateral occipital cortex

What is the relationship between retinotopy and object selectivity in human lateral occipital (LO) cortex? We used functional magnetic resonance imaging (fMRI) to examine sensitivity to retinal position and category in LO, an object-selective region positioned posterior to MT along the lateral cortical surface. Six subjects participated in phase-encoded retinotopic mapping experiments as well as block-design experiments in which objects from six different categories were presented at six distinct positions in the visual field. We found substantial position modulation in LO using standard nonobject retinotopic mapping stimuli; this modulation extended beyond the boundaries of visual field maps LO-1 and LO-2. Further, LO showed a pronounced lower visual field bias: more LO voxels represented the lower contralateral visual field, and the mean LO response was higher to objects presented below fixation than above fixation. However, eccentricity effects produced by retinotopic mapping stimuli and objects differed. Whereas LO voxels preferred a range of eccentricities lying mostly outside the fovea in the retinotopic mapping experiment, LO responses were strongest to foveally presented objects. Finally, we found a stronger effect of position than category on both the mean LO response, as well as the distributed response across voxels. Overall these results demonstrate that retinal position exhibits strong effects on neural response in LO and indicates that these position effects may be explained by retinotopic organization.     

The lateral occipital complex and its role in object recognition

Here we review recent findings that reveal the functional properties of extra-striate regions in the human visual cortex that are involved in the representation and perception of objects. We characterize both the invariant and non-invariant properties of these regions and we discuss the correlation between activation of these regions and recognition. Overall, these results indicate that the lateral occipital complex plays an important role in human object recognition.     

Not one extrastriate body area: using anatomical landmarks, hMT+, and visual field maps to parcellate limb-selective activations in human lateral occipitotemporal cortex

The prevailing view of human lateral occipitotemporal cortex (LOTC) organization suggests a single area selective for images of the human body (extrastriate body area, EBA) that highly overlaps with the human motion-selective complex (hMT+). Using functional magnetic resonance imaging with higher resolution (1.5mm voxels) than past studies (3-4mm voxels), we examined the fine-scale spatial organization of these activations relative to each other, as well as to visual field maps in LOTC. Rather than one contiguous EBA highly overlapping hMT+, results indicate three limb-selective activations organized in a crescent surrounding hMT+: (1) an activation posterior to hMT+ on the lateral occipital sulcus/middle occipital gyrus (LOS/MOG) overlapping the lower vertical meridian shared between visual field maps LO-2 and TO-1, (2) an activation anterior to hMT+ on the middle temporal gyrus (MTG) consistently overlapping the lower vertical meridian of TO-2 and extending outside presently defined visual field maps, and (3) an activation inferior to hMT+ on the inferotemporal gyrus (ITG) overlapping the parafoveal representation of the TO cluster. This crescent organization of limb-selective activations surrounding hMT+ is reproducible over a span of three years and is consistent across different image types used for localization. Further, these regions exhibit differential position properties: preference for contralateral image presentation decreases and preference for foveal presentation increases from the limb-selective LOS to the MTG. Finally, the relationship between limb-selective activations and visual field maps extends to the dorsal stream where a posterior IPS activation overlaps V7. Overall, our measurements demonstrate a series of LOTC limb-selective activations that 1) have separate anatomical and functional boundaries, 2) overlap distinct visual field maps, and 3) illustrate differential position properties. These findings indicate that category selectivity alone is an insufficient organization principle for defining brain areas. Instead, multiple properties are necessary in order to parcellate and understand the functional organization of high-level visual cortex.