Maladaptive Laterality in Cortical Networks Related to Social Communication in Autism Spectrum Disorder.

Neuroimaging studies of individuals with autism spectrum disorders (ASDs) consistently find an aberrant pattern of reduced laterality in brain networks that support functions related to social communication and language. However, it is unclear how the underlying functional organization of these brain networks is altered in ASD individuals. We tested four models of reduced laterality in a social communication network in 70 ASD individuals (14 females) and a control group of the same number of tightly matched typically developing (TD) individuals (19 females) using high-quality resting-state fMRI data and a method of measuring patterns of functional laterality across the brain. We found that a functionally defined social communication network exhibited the typical pattern of left laterality in both groups, whereas there was a significant increase in within- relative to across-hemisphere connectivity of homotopic regions in the right hemisphere in ASD individuals. Furthermore, greater within- relative to across-hemisphere connectivity in the left hemisphere was positively correlated with a measure of verbal ability in both groups, whereas greater within- relative to across-hemisphere connectivity in the right hemisphere in ASD, but not TD, individuals was negatively correlated with the same verbal measure. Crucially, these differences in patterns of laterality were not found in two other functional networks and were specifically correlated to a measure of verbal ability but not metrics of other core components of the ASD phenotype. These results suggest that previous reports of reduced laterality in social communication regions in ASD is because of the two hemispheres functioning more independently than seen in TD individuals, with the atypical right-hemisphere network component being maladaptive.SIGNIFICANCE STATEMENT A consistent neuroimaging finding in individuals with ASD is an aberrant pattern of reduced laterality of the brain networks that support functions related to social communication and language. We tested four models of reduced laterality in a social communication network in ASD individuals and a TD control group using high-quality resting-state fMRI data. Our results suggest that reduced laterality of social communication regions in ASD may be because of the two hemispheres functioning more independently than seen in TD individuals, with atypically greater within- than across-hemisphere connectivity in the right hemisphere being maladaptive.

A data-driven functional mapping of the anterior temporal lobes.

Even though the anterior temporal lobe (ATL) comprises several anatomical and functional subdivisions, it is often reduced to a homogeneous theoretical entity, such as a domain-general convergence zone, or "hub", for semantic information. Methodological limitations are largely to blame for the imprecise mapping of function to structure in the ATL. There are two major obstacles to using fMRI to identify the precise functional organization of the ATL: the difficult choice of stimuli and tasks to activate, and dissociate, specific regions within the ATL and poor signal quality due to magnetic field distortions near the sinuses. To circumvent these difficulties, we developed a data-driven parcellation routine using resting-state fMRI data (24 females, 64 males) acquired using a sequence that was optimized to enhance signal in the ATL. Focusing on patterns of functional connectivity between each ATL voxel and the rest of the brain, we found that the ATL comprises at least 34 distinct functional parcels that are arranged into bands along the lateral and ventral cortical surfaces, extending from the posterior temporal lobes into the temporal poles. In addition, the anterior region of the fusiform gyrus, most often cited as the location of the semantic hub, was found to be part of a domain-specific network associated with face and social processing, rather than a domain-general semantic hub. These findings offer a fine-grained functional map of the ATL and offer an initial step towards using more precise language to describe the locations of functional responses in this heterogeneous region of human cortex.SIGNIFICANCE STATEMENTThe functional role of the anterior aspects of the temporal lobes (ATL) is a contentious issue. While it is likely that different regions within the ATL subserve unique cognitive functions, most studies revert to vaguely referring to particular functional regions as "the ATL" and, thus, the mapping of function to anatomy remains unclear. We used resting-state fMRI connectivity patterns between the ATL and the rest of the brain to reveal that the ATL comprises at least 34 distinct functional parcels that are organized into a three-level functional hierarchy. These results provide a detailed functional map of the anterior temporal lobes that can guide future research on how distinct regions within the ATL support diverse cognitive functions.

Distinct representations of spatial and categorical relationships across human scene-selective cortex.

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.

Dissociable Neural Systems for Recognizing Places and Navigating through Them.

When entering an environment, we can use the present visual information from the scene to either recognize the kind of place it is (e.g., a kitchen or a bedroom) or navigate through it. Here we directly test the hypothesis that these two processes, what we call "scene categorization" and "visually-guided navigation", are supported by dissociable neural systems. Specifically, we manipulated task demands by asking human participants (male and female) to perform a scene categorization, visually-guided navigation, and baseline task on images of scenes, and measured both the average univariate responses and multivariate spatial pattern of responses within two scene-selective cortical regions, the parahippocampal place area (PPA) and occipital place area (OPA), hypothesized to be separably involved in scene categorization and visually-guided navigation, respectively. As predicted, in the univariate analysis, PPA responded significantly more during the categorization task than during both the navigation and baseline tasks, whereas OPA showed the complete opposite pattern. Similarly, in the multivariate analysis, a linear support vector machine achieved above-chance classification for the categorization task, but not the navigation task in PPA. By contrast, above-chance classification was achieved for both the navigation and categorization tasks in OPA. However, above-chance classification for both tasks was also found in early visual cortex and hence not specific to OPA, suggesting that the spatial patterns of responses in OPA are merely inherited from early vision, and thus may be epiphenomenal to behavior. Together, these results are evidence for dissociable neural systems involved in recognizing places and navigating through them.SIGNIFICANCE STATEMENT It has been nearly three decades since Goodale and Milner demonstrated that recognizing objects and manipulating them involve distinct neural processes. Today we show the same is true of our interactions with our environment: recognizing places and navigating through them are neurally dissociable. More specifically, we found that a scene-selective region, the parahippocampal place area, is active when participants are asked to categorize a scene, but not when asked to imagine navigating through it, whereas another scene-selective region, the occipital place area, shows the exact opposite pattern. This double dissociation is evidence for dissociable neural systems within scene processing, similar to the bifurcation of object processing described by Goodale and Milner (1992).

Places in the Brain: Bridging Layout and Object Geometry in Scene-Selective Cortex.

Diverse animal species primarily rely on sense (left-right) and egocentric distance (proximal-distal) when navigating the environment. Recent neuroimaging studies with human adults show that this information is represented in 2 scene-selective cortical regions-the occipital place area (OPA) and retrosplenial complex (RSC)-but not in a third scene-selective region-the parahippocampal place area (PPA). What geometric properties, then, does the PPA represent, and what is its role in scene processing? Here we hypothesize that the PPA represents relative length and angle, the geometric properties classically associated with object recognition, but only in the context of large extended surfaces that compose the layout of a scene. Using functional magnetic resonance imaging adaptation, we found that the PPA is indeed sensitive to relative length and angle changes in pictures of scenes, but not pictures of objects that reliably elicited responses to the same geometric changes in object-selective cortical regions. Moreover, we found that the OPA is also sensitive to such changes, while the RSC is tolerant to such changes. Thus, the geometric information typically associated with object recognition is also used during some aspects of scene processing. These findings provide evidence that scene-selective cortex differentially represents the geometric properties guiding navigation versus scene categorization.

Value is in the eye of the beholder: early visual cortex codes monetary value of objects during a diverted attention task.

A central concern in the study of learning and decision-making is the identification of neural signals associated with the values of choice alternatives. An important factor in understanding the neural correlates of value is the representation of the object itself, separate from the act of choosing. Is it the case that the representation of an object within visual areas will change if it is associated with a particular value? We used fMRI adaptation to measure the neural similarity of a set of novel objects before and after participants learned to associate monetary values with the objects. We used a range of both positive and negative values to allow us to distinguish effects of behavioral salience (i.e., large vs. small values) from effects of valence (i.e., positive vs. negative values). During the scanning session, participants made a perceptual judgment unrelated to value. Crucially, the similarity of the visual features of any pair of objects did not predict the similarity of their value, so we could distinguish adaptation effects due to each dimension of similarity. Within early visual areas, we found that value similarity modulated the neural response to the objects after training. These results show that an abstract dimension, in this case, monetary value, modulates neural response to an object in visual areas of the brain even when attention is diverted.

Functional magnetic resonance imaging adaptation reveals a noncategorical representation of hue in early visual cortex.

Color names divide the fine-grained gamut of color percepts into discrete categories. A categorical transition must occur somewhere between the initial encoding of the continuous spectrum of light by the cones and the verbal report of the name of a color stimulus. Here, we used a functional magnetic resonance imaging (fMRI) adaptation experiment to examine the representation of hue in the early visual cortex. Our stimuli varied in hue between blue and green. We found in the early visual areas (V1, V2/3, and hV4) a smoothly increasing recovery from adaptation with increasing hue distance between adjacent stimuli during both passive viewing (Experiment 1) and active categorization (Experiment 2). We examined the form of the adaptation effect and found no evidence that a categorical representation mediates the release from adaptation for stimuli that cross the blue-green color boundary. Examination of the direct effect of stimulus hue on the fMRI response did, however, reveal an enhanced response to stimuli near the blue-green category border. This was largest in hV4 and when subjects were engaged in active categorization of the stimulus hue. In contrast with a recent report from another laboratory (Bird, Berens, Horner, & Franklin, 2014), we found no evidence for a categorical representation of color in the middle frontal gyrus. A post hoc whole-brain analysis, however, revealed several regions in the frontal cortex with a categorical effect in the adaptation response. Overall, our results support the idea that the representation of color in the early visual cortex is primarily fine grained and does not reflect color categories.

A functional parcellation of the whole brain in individuals with autism spectrum disorder reveals atypical patterns of network organization.

BACKGROUND: Researchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy individuals with ASD and a group of seventy typically developing (TD) individuals. METHODS: The rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates stability and replicability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ. RESULTS: We compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: 1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, 2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and 3) subcortical structures and the hippocampus are atypically integrated with the neocortex. CONCLUSIONS: These results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.

Taxonomic structure in a set of abstract concepts.

A large portion of human knowledge comprises "abstract" concepts that lack readily perceivable properties (e.g., "love" and "justice"). Since abstract concepts lack such properties, they have historically been treated as an undifferentiated category of knowledge in the psychology and neuropsychology literatures. More recently, the categorical structure of abstract concepts is often explored using paradigms that ask participants to make explicit judgments about a set of concepts along dimensions that are predetermined by the experimenter. Such methods require the experimenter to select dimensions that are relevant to the concepts and further that people make explicit judgments that accurately reflect their mental representations. We bypassed these requirements by collecting two large sets of non-verbal and implicit judgments about which dimensions are relevant to the similarity between pairs of 50 abstract nouns to determine the representational space of the concepts. We then identified categories within the representational space using a clustering procedure that required categories to replicate across two independent data sets. In a separate experiment, we used automatic semantic priming to further validate the categories and to show that they are an improvement over categories that were defined within the same set of abstract concepts using explicit ratings along predetermined dimensions. These results demonstrate that abstract concepts can be characterized beyond their negative relation to concrete concepts and that categories of abstract concepts can be defined without using a priori dimensions for the concepts or explicit judgments from participants.

Three cortical scene systems and their development.

Since the discovery of three scene-selective regions in the human brain, a central assumption has been that all three regions directly support navigation. We propose instead that cortical scene processing regions support three distinct computational goals (and one not for navigation at all): (i) The parahippocampal place area supports scene categorization, which involves recognizing the kind of place we are in; (ii) the occipital place area supports visually guided navigation, which involves finding our way through the immediately visible environment, avoiding boundaries and obstacles; and (iii) the retrosplenial complex supports map-based navigation, which involves finding our way from a specific place to some distant, out-of-sight place. We further hypothesize that these systems develop along different timelines, with both navigation systems developing slower than the scene categorization system.

Layer-Specific Contributions to Imagined and Executed Hand Movements in Human Primary Motor Cortex.

The human ability to imagine motor actions without executing them (i.e., motor imagery) is crucial to a number of cognitive functions, including motor planning and learning, and has been shown to improve response times and accuracy of subsequent motor actions [1, 2]. Although these behavioral findings suggest the possibility that imagined movements directly influence primary motor cortex (M1), how this might occur remains unknown [3]. Here, we use a non-blood-oxygen-level-dependent (BOLD) method for collecting fMRI data, called vascular space occupancy (VASO) [4, 5], to measure neural activations across cortical laminae in M1 while participants either tapped their thumb and forefinger together or simply imagined doing so. We report that, whereas executed movements (i.e., finger tapping) evoked neural responses in both the superficial layers of M1 that receive cortical input and the deep layers of M1 that send output to the spinal cord to support movement, imagined movements evoked responses in superficial cortical layers only. Furthermore, we found that finger tapping preceded by both imagined and executed movements showed a reduced response in the superficial layers (repetition suppression) coupled with a heightened response in the deep layers (repetition enhancement). Taken together, our results provide evidence for a mechanism whereby imagined movements can directly affect motor performance and might explain how neural repetition effects lead to improvements in behavior (e.g., repetition priming).

Perceived egocentric distance sensitivity and invariance across scene-selective cortex.

Behavioral studies in many species and studies in robotics have demonstrated two sources of information critical for visually-guided navigation: sense (left-right) information and egocentric distance (proximal-distal) information. A recent fMRI study found sensitivity to sense information in two scene-selective cortical regions, the retrosplenial complex (RSC) and the occipital place area (OPA), consistent with hypotheses that these regions play a role in human navigation. Surprisingly, however, another scene-selective region, the parahippocampal place area (PPA), was not sensitive to sense information, challenging hypotheses that this region is directly involved in navigation. Here we examined how these regions encode egocentric distance information (e.g., a house seen from close up versus far away), another type of information crucial for navigation. Using fMRI adaptation and a regions-of-interest analysis approach in human adults, we found sensitivity to egocentric distance information in RSC and OPA, while PPA was not sensitive to such information. These findings further support that RSC and OPA are directly involved in navigation, while PPA is not, consistent with the hypothesis that scenes may be processed by distinct systems guiding navigation and recognition.