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In human adults, multiple cortical regions respond robustly to faces, including the occipital face area (OFA) and fusiform face area (FFA), implicated in face perception, and the superior temporal sulcus (STS) and medial prefrontal cortex (MPFC), implicated in higher-level social functions. When in development, does face selectivity arise in each of these regions? Here, we combined two awake infant functional magnetic resonance imaging (fMRI) datasets to create a sample size twice the size of previous reports ( n  = 65 infants; 2.6-9.6 months). Infants watched movies of faces, bodies, objects, and scenes, while fMRI data were collected. Despite variable amounts of data from each infant, individual subject whole-brain activation maps revealed responses to faces compared to nonface visual categories in the approximate location of OFA, FFA, STS, and MPFC. To determine the strength and nature of face selectivity in these regions, we used cross-validated functional region of interest analyses. Across this larger sample size, face responses in OFA, FFA, STS, and MPFC were significantly greater than responses to bodies, objects, and scenes. Even the youngest infants (2-5 months) showed significantly face-selective responses in FFA, STS, and MPFC, but not OFA. These results demonstrate that face selectivity is present in multiple cortical regions within months of birth, providing powerful constraints on theories of cortical development., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Kosakowski et al.)

Prior work has identified cortical regions selectively responsive to specific categories of visual stimuli. However, this hypothesis-driven work cannot reveal how prominent these category selectivities are in the overall functional organization of the visual cortex, or what others might exist that scientists have not thought to look for. Furthermore, standard voxel-wise tests cannot detect distinct neural selectivities that coexist within voxels. To overcome these limitations, we used data-driven voxel decomposition methods to identify the main components underlying fMRI responses to thousands of complex photographic images. Our hypothesis-neutral analysis rediscovered components selective for faces, places, bodies, and words, validating our method and showing that these selectivities are dominant features of the ventral visual pathway. The analysis also revealed an unexpected component with a distinct anatomical distribution that responded highly selectively to images of food. Alternative accounts based on low- to mid-level visual features, such as color, shape, or texture, failed to account for the food selectivity of this component. High-throughput testing and control experiments with matched stimuli on a highly accurate computational model of this component confirm its selectivity for food. We registered our methods and hypotheses before replicating them on held-out participants and in a novel dataset. These findings demonstrate the power of data-driven methods and show that the dominant neural responses of the ventral visual pathway include not only selectivities for faces, scenes, bodies, and words but also the visually heterogeneous category of food, thus constraining accounts of when and why functional specialization arises in the cortex., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Scanning young children while they watch short, engaging, commercially-produced movies has emerged as a promising approach for increasing data retention and quality. Movie stimuli also evoke a richer variety of cognitive processes than traditional experiments, allowing the study of multiple aspects of brain development simultaneously. However, because these stimuli are uncontrolled, it is unclear how effectively distinct profiles of brain activity can be distinguished from the resulting data. Here we develop an approach for identifying multiple distinct subject-specific Regions of Interest (ssROIs) using fMRI data collected during movie-viewing. We focused on the test case of higher-level visual regions selective for faces, scenes, and objects. Adults (N = 13) were scanned while viewing a 5.6-min child-friendly movie, as well as a traditional localizer experiment with blocks of faces, scenes, and objects. We found that just 2.7 min of movie data could identify subject-specific face, scene, and object regions. While successful, movie-defined ssROIS still showed weaker domain selectivity than traditional ssROIs. Having validated our approach in adults, we then used the same methods on movie data collected from 3 to 12-year-old children (N = 122). Movie response timecourses in 3-year-old children's face, scene, and object regions were already significantly and specifically predicted by timecourses from the corresponding regions in adults. We also found evidence of continued developmental change, particularly in the face-selective posterior superior temporal sulcus. Taken together, our results reveal both early maturity and functional change in face, scene, and object regions, and more broadly highlight the promise of short, child-friendly movies for developmental cognitive neuroscience., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Successful engagement with the world requires the ability to predict what will happen next. Here, we investigate how the brain makes a fundamental prediction about the physical world: whether the situation in front of us is stable, and hence likely to stay the same, or unstable, and hence likely to change in the immediate future. Specifically, we ask if judgments of stability can be supported by the kinds of representations that have proven to be highly effective at visual object recognition in both machines and brains, or instead if the ability to determine the physical stability of natural scenes may require generative algorithms that simulate the physics of the world. To find out, we measured responses in both convolutional neural networks (CNNs) and the brain (using fMRI) to natural images of physically stable versus unstable scenarios. We find no evidence for generalizable representations of physical stability in either standard CNNs trained on visual object and scene classification (ImageNet), or in the human ventral visual pathway, which has long been implicated in the same process. However, in frontoparietal regions previously implicated in intuitive physical reasoning we find both scenario-invariant representations of physical stability, and higher univariate responses to unstable than stable scenes. These results demonstrate abstract representations of physical stability in the dorsal but not ventral pathway, consistent with the hypothesis that the computations underlying stability entail not just pattern classification but forward physical simulation., Competing Interests: RP, MC, JT, NK No competing interests declared, (© 2022, Pramod et al.)

Recent work has shown that human auditory cortex contains neural populations anterior and posterior to primary auditory cortex that respond selectively to music. However, it is unknown how this selectivity for music arises. To test whether musical training is necessary, we measured fMRI responses to 192 natural sounds in 10 people with almost no musical training. When voxel responses were decomposed into underlying components, this group exhibited a music-selective component that was very similar in response profile and anatomical distribution to that previously seen in individuals with moderate musical training. We also found that musical genres that were less familiar to our participants (e.g., Balinese gamelan ) produced strong responses within the music component, as did drum clips with rhythm but little melody, suggesting that these neural populations are broadly responsive to music as a whole. Our findings demonstrate that the signature properties of neural music selectivity do not require musical training to develop, showing that the music-selective neural populations are a fundamental and widespread property of the human brain. NEW & NOTEWORTHY We show that music-selective neural populations are clearly present in people without musical training, demonstrating that they are a fundamental and widespread property of the human brain. Additionally, we show music-selective neural populations respond strongly to music from unfamiliar genres as well as music with rhythm but little pitch information, suggesting that they are broadly responsive to music as a whole.

Facial and vocal cues provide critical social information about other humans, including their emotional and attentional states and the content of their speech. Recent work has shown that the face-responsive region of posterior superior temporal sulcus ("fSTS") also responds strongly to vocal sounds. Here, we investigate the functional role of this region and the broader STS by measuring responses to a range of face movements, vocal sounds, and hand movements using fMRI. We find that the fSTS responds broadly to different types of audio and visual face action, including both richly social communicative actions, as well as minimally social noncommunicative actions, ruling out hypotheses of specialization for processing speech signals, or communicative signals more generally. Strikingly, however, responses to hand movements were very low, whether communicative or not, indicating a specific role in the analysis of face actions (facial and vocal), not a general role in the perception of any human action. Furthermore, spatial patterns of response in this region were able to decode communicative from noncommunicative face actions, both within and across modality (facial/vocal cues), indicating sensitivity to an abstract social dimension. These functional properties of the fSTS contrast with a region of middle STS that has a selective, largely unimodal auditory response to speech sounds over both communicative and noncommunicative vocal nonspeech sounds, and nonvocal sounds. Region of interest analyses were corroborated by a data-driven independent component analysis, identifying face-voice and auditory speech responses as dominant sources of voxelwise variance across the STS. These results suggest that the STS contains separate processing streams for the audiovisual analysis of face actions and auditory speech processing., (Copyright © 2020. Published by Elsevier Inc.)

Prior work decoding linguistic meaning from imaging data has been largely limited to concrete nouns, using similar stimuli for training and testing, from a relatively small number of semantic categories. Here we present a new approach for building a brain decoding system in which words and sentences are represented as vectors in a semantic space constructed from massive text corpora. By efficiently sampling this space to select training stimuli shown to subjects, we maximize the ability to generalize to new meanings from limited imaging data. To validate this approach, we train the system on imaging data of individual concepts, and show it can decode semantic vector representations from imaging data of sentences about a wide variety of both concrete and abstract topics from two separate datasets. These decoded representations are sufficiently detailed to distinguish even semantically similar sentences, and to capture the similarity structure of meaning relationships between sentences.

The existence of color-processing regions in the human ventral visual pathway (VVP) has long been known from patient and imaging studies, but their location in the cortex relative to other regions, their selectivity for color compared with other properties (shape and object category), and their relationship to color-processing regions found in nonhuman primates remain unclear. We addressed these questions by scanning 13 subjects with fMRI while they viewed two versions of movie clips (colored, achromatic) of five different object classes (faces, scenes, bodies, objects, scrambled objects). We identified regions in each subject that were selective for color, faces, places, and object shape, and measured responses within these regions to the 10 conditions in independently acquired data. We report two key findings. First, the three previously reported color-biased regions (located within a band running posterior-anterior along the VVP, present in most of our subjects) were sandwiched between face-selective cortex and place-selective cortex, forming parallel bands of face, color, and place selectivity that tracked the fusiform gyrus/collateral sulcus. Second, the posterior color-biased regions showed little or no selectivity for object shape or for particular stimulus categories and showed no interaction of color preference with stimulus category, suggesting that they code color independently of shape or stimulus category; moreover, the shape-biased lateral occipital region showed no significant color bias. These observations mirror results in macaque inferior temporal cortex (Lafer-Sousa and Conway, 2013), and taken together, these results suggest a homology in which the entire tripartite face/color/place system of primates migrated onto the ventral surface in humans over the course of evolution., Significance Statement: Here we report that color-biased cortex is sandwiched between face-selective and place-selective cortex on the bottom surface of the brain in humans. This face/color/place organization mirrors that seen on the lateral surface of the temporal lobe in macaques, suggesting that the entire tripartite system is homologous between species. This result validates the use of macaques as a model for human vision, making possible more powerful investigations into the connectivity, precise neural codes, and development of this part of the brain. In addition, we find substantial segregation of color from shape selectivity in posterior regions, as observed in macaques, indicating a considerable dissociation of the processing of shape and color in both species., (Copyright © 2016 Lafer-Sousa et al.)

The Fourth International Workshop on Advances in Electrocorticography (ECoG) convened in New Orleans, LA, on October 11-12, 2012. The proceedings of the workshop serves as an accurate record of the most contemporary clinical and experimental work on brain surface recording and represents the insights of a unique multidisciplinary ensemble of expert clinicians and scientists. Presentations covered a broad range of topics, including innovations in passive functional mapping, increased understanding of pathologic high-frequency oscillations, evolving sensor technologies, a human trial of ECoG-driven brain-machine interface, as well as fresh insights into brain electrical stimulation., (© 2013.)

Unlike brain regions that respond selectively to specific kinds of information content, a number of frontal and parietal regions are thought to be domain- and process-general: that is, active during a wide variety of demanding cognitive tasks. However, most previous evidence for this functional generality in humans comes from methods that overestimate activation overlap across tasks. Here we present functional MRI evidence from single-subject analyses for broad functional generality of a specific set of brain regions: the same sets of voxels are engaged across tasks ranging from arithmetic to storing information in working memory, to inhibiting irrelevant information. These regions have a specific topography, often lying directly adjacent to domain-specific regions. Thus, in addition to domain-specific brain regions tailored to solve particular problems of longstanding importance to our species, the human brain also contains a set of functionally general regions that plausibly endow us with the cognitive flexibility necessary to solve novel problems.

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.

The crux of vision is to identify objects and determine their locations in the environment. Although initial visual representations are necessarily retinotopic (eye centered), interaction with the real world requires spatiotopic (absolute) location information. We asked whether higher level human visual cortex-important for stable object recognition and action-contains information about retinotopic and/or spatiotopic object position. Using functional magnetic resonance imaging multivariate pattern analysis techniques, we found information about both object category and object location in each of the ventral, dorsal, and early visual regions tested, replicating previous reports. By manipulating fixation position and stimulus position, we then tested whether these location representations were retinotopic or spatiotopic. Crucially, all location information was purely retinotopic. This pattern persisted when location information was irrelevant to the task, and even when spatiotopic (not retinotopic) stimulus position was explicitly emphasized. We also conducted a "searchlight" analysis across our entire scanned volume to explore additional cortex but again found predominantly retinotopic representations. The lack of explicit spatiotopic representations suggests that spatiotopic object position may instead be computed indirectly and continually reconstructed with each eye movement. Thus, despite our subjective impression that visual information is spatiotopic, even in higher level visual cortex, object location continues to be represented in retinotopic coordinates.

In 1861, Paul Broca stood up before the Anthropological Society of Paris and announced that the left frontal lobe was the seat of speech. Ever since, Broca's eponymous brain region has served as a primary battleground for one of the central debates in the science of the mind and brain: Is human cognition produced by highly specialized brain regions, each conducting a specific mental process, or instead by more general-purpose brain mechanisms, each broadly engaged in a wide range of cognitive tasks? For Broca's area, the debate focuses on specialization for language versus domain-general functions such as hierarchical structure building (e.g., [1, 2]), aspects of action processing (e.g., [3]), working memory (e.g., [4]), or cognitive control (e.g., [5-7]). Here, using single-subject fMRI, we find that both ideas are right: Broca's area contains two sets of subregions lying side by side, one quite specifically engaged in language processing, surrounded by another that is broadly engaged across a wide variety of tasks and content domains., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

In a widely used functional magnetic resonance imaging (fMRI) data analysis method, functional regions of interest (fROIs) are handpicked in each participant using macroanatomic landmarks as guides, and the response of these regions to new conditions is then measured. A key limitation of this standard handpicked fROI method is the subjectivity of decisions about which clusters of activated voxels should be treated as the particular fROI in question in each subject. Here we apply the Group-Constrained Subject-Specific (GSS) method for defining fROIs, recently developed for identifying language fROIs (Fedorenko et al., 2010), to algorithmically identify fourteen well-studied category-selective regions of the ventral visual pathway (Kanwisher, 2010). We show that this method retains the benefit of defining fROIs in individual subjects without the subjectivity inherent in the traditional handpicked fROI approach. The tools necessary for using this method are available on our website (http://web.mit.edu/bcs/nklab/GSS.shtml)., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Work in theoretical linguistics and psycholinguistics suggests that human linguistic knowledge forms a continuum between individual lexical items and abstract syntactic representations, with most linguistic representations falling between the two extremes and taking the form of lexical items stored together with the syntactic/semantic contexts in which they frequently occur. Neuroimaging evidence further suggests that no brain region is selectively sensitive to only lexical information or only syntactic information. Instead, all the key brain regions that support high-level linguistic processing have been implicated in both lexical and syntactic processing, suggesting that our linguistic knowledge is plausibly represented in a distributed fashion in these brain regions. Given this distributed nature of linguistic representations, multi-voxel pattern analyses (MVPAs) can help uncover important functional properties of the language system. In the current study we use MVPAs to ask two questions: (1) Do language brain regions differ in how robustly they represent lexical vs. syntactic information? and (2) Do any of the language bran regions distinguish between "pure" lexical information (lists of words) and "pure" abstract syntactic information (jabberwocky sentences) in the pattern of activity? We show that lexical information is represented more robustly than syntactic information across many language regions (with no language region showing the opposite pattern), as evidenced by a better discrimination between conditions that differ along the lexical dimension (sentences vs. jabberwocky, and word lists vs. nonword lists) than between conditions that differ along the syntactic dimension (sentences vs. word lists, and jabberwocky vs. nonword lists). This result suggests that lexical information may play a more critical role than syntax in the representation of linguistic meaning. We also show that several language regions reliably discriminate between "pure" lexical information and "pure" abstract syntactic information in their patterns of neural activity., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

For every claim in the neuroimaging literature about a particular brain region supporting syntactic processing, there exist other claims implicating the target region in different linguistic processes, and, in many cases, in non-linguistic cognitive processes (e.g., Blumstein, 2009). We argue that traditional group analysis methods in neuroimaging may obscure functional specificity because of inter-subject anatomical variability (Fedorenko & Kanwisher, 2009). In Fedorenko, Hsieh, Nieto-Castanon, Whitfield-Gabrieli, and Kanwisher (2010) we presented a functional localizer that allows quick and reliable identification of key language-sensitive regions in each individual brain. This approach enables pooling data from corresponding functional regions across subjects rather than from the same locations in stereotaxic space that may differ functionally due to inter-subject anatomical variability. In the current paper we demonstrate that the individual-subjects functional localization approach is superior to the traditional methods in its ability to distinguish among conditions in a brain region's response. This ability is at the core of all neuroimaging research and is critical for answering questions of functional specialization (e.g., does a brain region specialize for processing syntactic aspects of the linguistic signal), which is in turn essential for making inferences about the precise computations conducted in each brain region. Based on our results, we argue that supplementing existing methods with an individual-subjects functional localization approach may lead to a clearer picture of the neural basis of syntactic processing, as it has in some other domains, such as high-level vision (e.g., Kanwisher, 2010) and social cognition (e.g., Saxe & Kanwisher, 2003)., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Stimulus inversion impairs face discrimination to a greater extent than discrimination of other non-face object categories. This finding has led to suggestions that upright faces are represented by mechanisms specialized for upright faces whereas inverted face representation depends on more general object recognition mechanisms. In the present study we tested the causal role of face-selective and object-selective cortical areas for upright and inverted face discrimination by transiently disrupting neural processing using transcranial magnetic stimulation (TMS). Participants matched upright and inverted faces while TMS was delivered over each participant's functionally localized right occipital face area (rOFA) or right lateral occipital area (rLO). TMS delivered over rOFA disrupted the discrimination of upright and inverted faces while TMS delivered over rLO impaired inverted face discrimination only. These results provide causal evidence that upright faces are represented by face-specific mechanisms whereas inverted faces are represented by both face-specific and object-specific mechanisms. The similar sensitivity of the OFA to upright and inverted faces is consistent with the hypothesis that the OFA processes facial features at an early stage of face processing., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Electrophysiological and behavioral studies in many species have demonstrated mirror-image confusion for objects, perhaps because many objects are vertically symmetric (e.g., a cup is the same cup when seen in left or right profile). In contrast, the navigability of a scene changes when it is mirror reversed, and behavioral studies reveal high sensitivity to this change. Thus, we predicted that representations in object-selective cortex will be unaffected by mirror reversals, whereas representations in scene-selective cortex will be sensitive to such reversals. To test this hypothesis, we ran an event-related functional magnetic resonance imaging adaptation experiment in human adults. Consistent with our prediction, we found tolerance to mirror reversals in one object-selective region, the posterior fusiform sulcus, and a strong sensitivity to these reversals in two scene-selective regions, the transverse occipital sulcus and the retrosplenial complex. However, a more posterior object-selective region, the lateral occipital sulcus, showed sensitivity to mirror reversals, suggesting that the sense information that distinguishes mirror images is represented at earlier stages in the object-processing hierarchy. Moreover, one scene-selective region (the parahippocampal place area or PPA) was tolerant to mirror reversals. This last finding challenges the hypothesis that the PPA is involved in navigation and reorientation and suggests instead that scenes, like objects, are processed by distinct pathways guiding recognition and action.

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., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Previous neuroimaging research has identified a number of brain regions sensitive to different aspects of linguistic processing, but precise functional characterization of these regions has proven challenging. We hypothesize that clearer functional specificity may emerge if candidate language-sensitive regions are identified functionally within each subject individually, a method that has revealed striking functional specificity in visual cortex but that has rarely been applied to neuroimaging studies of language. This method enables pooling of data from corresponding functional regions across subjects rather than from corresponding locations in stereotaxic space (which may differ functionally because of the anatomical variability across subjects). However, it is far from obvious a priori that this method will work as it requires that multiple stringent conditions be met. Specifically, candidate language-sensitive brain regions must be identifiable functionally within individual subjects in a short scan, must be replicable within subjects and have clear correspondence across subjects, and must manifest key signatures of language processing (e.g., a higher response to sentences than nonword strings, whether visual or auditory). We show here that this method does indeed work: we identify 13 candidate language-sensitive regions that meet these criteria, each present in >or=80% of subjects individually. The selectivity of these regions is stronger using our method than when standard group analyses are conducted on the same data, suggesting that the future application of this method may reveal clearer functional specificity than has been evident in prior neuroimaging research on language.

Is the human mind/brain composed of a set of highly specialized components, each carrying out a specific aspect of human cognition, or is it more of a general-purpose device, in which each component participates in a wide variety of cognitive processes? For nearly two centuries, proponents of specialized organs or modules of the mind and brain--from the phrenologists to Broca to Chomsky and Fodor--have jousted with the proponents of distributed cognitive and neural processing--from Flourens to Lashley to McClelland and Rumelhart. I argue here that research using functional MRI is beginning to answer this long-standing question with new clarity and precision by indicating that at least a few specific aspects of cognition are implemented in brain regions that are highly specialized for that process alone. Cortical regions have been identified that are specialized not only for basic sensory and motor processes but also for the high-level perceptual analysis of faces, places, bodies, visually presented words, and even for the very abstract cognitive function of thinking about another person's thoughts. I further consider the as-yet unanswered questions of how much of the mind and brain are made up of these functionally specialized components and how they arise developmentally.

The mammalian visual system contains an extensive web of feedback connections projecting from higher cortical areas to lower areas, including primary visual cortex. Although multiple theories have been proposed, the role of these connections in perceptual processing is not understood. We found that the pattern of functional magnetic resonance imaging response in human foveal retinotopic cortex contained information about objects presented in the periphery, far away from the fovea, which has not been predicted by prior theories of feedback. This information was position invariant, correlated with perceptual discrimination accuracy and was found only in foveal, but not peripheral, retinotopic cortex. Our data cannot be explained by differential eye movements, activation from the fixation cross, or spillover activation from peripheral retinotopic cortex or from lateral occipital complex. Instead, our findings indicate that position-invariant object information from higher cortical areas is fed back to foveal retinotopic cortex, enhancing task performance.

What is the neural code for object shape? Despite intensive research, the precise nature of object representations in high-level visual cortex remains elusive. Here we use functional magnetic resonance imaging (fMRI) to show that convex shapes are encoded in a privileged fashion by human lateral occipital complex (LOC), a region that has been implicated in object recognition. On each trial, two convex or two concave shapes that were either identical or different were presented sequentially. Critically, the convex and concave stimuli were the same except for a binocular disparity change that reversed the figure-ground assignment. The fMRI response in LOC for convex stimuli was higher for different than that for identical shape pairs, indicating sensitivity to differences in convex shape. However, when the same stimuli were seen as concave, the response for different and identical pairs was the same, indicating lower sensitivity to changes in concave shape than convex shape. This pattern was more pronounced in the anterior than that in the posterior portion of LOC. These results suggest that convex contours could be important elements in cortical object representations.

Neuroimaging research over the past decade has revealed a detailed picture of the functional organization of the human brain. Here we focus on two fundamental questions that are raised by the detailed mapping of sensory and cognitive functions and illustrate these questions with findings from the object-vision pathway. First, are functionally specific regions that are located close together best understood as distinct cortical modules or as parts of a larger-scale cortical map? Second, what functional properties define each cortical map or module? We propose a model in which overlapping continuous maps of simple features give rise to discrete modules that are selective for complex stimuli.

We present a method for discovering patterns of activation observed through fMIRI in experiments with multiple stimuli/tasks. We introduce an explicit parameterization for the profiles of activation and represent fMRI time courses as such profiles using linear regression estimates. Working in the space of activation profiles, we design a mixture model that finds the major activation patterns along with their localization maps and derive an algorithm for fitting the model to the fMRI data. The method enables functional group analysis independent of spatial correspondence among subjects. We validate this model in the context of category selectivity in the visual cortex, demonstrating good agreement with prior findings based on hypothesis-driven methods.

Numerous functionally distinct regions of cortex (e.g., V1, MT, the fusiform face area) can be easily identified in any normal human subject in just a few minutes of fMRI scanning. However, the locations of these regions vary across subjects. Investigations of these regions have therefore often used a functional region of interest (fROI) approach in which the region is first identified functionally in each subject individually, before subsequent scans in the same subjects test specific hypotheses concerning that region. This fROI method, which resembled long-established practice in visual neurophysiology, has methodological, statistical, and theoretical advantages over standard alternatives (such as whole-brain analyses of group data): (i) because functional properties are more consistently and robustly associated with fROIs than with locations in stereotaxic space, functional hypotheses concerning fROIs are often the most straightforward to frame, motivate, and test, (ii) because hypotheses are tested in only a handful of fROIs (instead of in tens of thousands of voxels), advance specification of fROIs provides a massive increase in statistical power over whole-brain analyses, and (iii) some fROIs may serve as candidate distinct components of the mind/brain worth investigation as such. Of course fROIs can be productively used in conjunction with other complementary methods. Here, we explain the motivation for and advantages of the fROI approach, and we rebut the criticism of this method offered by Friston et al. (Friston, K., Rotshtein, P., Geng, J., Sterzer, P., Henson, R., in press. A critique of functional localizers. NeuroImage).

Subjects were scanned in a single functional MRI (fMRI) experiment that enabled us to localize cortical regions in each subject in the occipital and temporal lobes that responded significantly in a variety of contrasts: faces>objects, body parts>objects, scenes>objects, objects>scrambled objects, and moving>stationary stimuli. The resulting activation maps were co-registered across subjects using spherical surface coordinates [Fischl et al., Hum Brain Mapp 1999;8:272-284] to produce a "percentage overlap map" indicating the percentage of subjects who showed a significant response for each contrast at each point on the surface. Prominent among the overlapping activations in these contrasts were the fusiform face area (FFA), extrastriate body area (EBA), parahippocampal place area (PPA), lateral occipital complex (LOC), and MT+/V5; only a few other areas responded consistently across subjects in these contrasts. Another analysis showed that the spatial profile of the selective response drops off quite sharply outside the standard borders of the FFA and PPA (less so for the EBA and MT+/V5), indicating that these regions are not simply peaks of very broad selectivities spanning centimeters of cortex, but fairly discrete regions of cortex with distinctive functional profiles. The data also yielded a surprise that challenges our understanding of the function of area MT+: a higher response to body parts than to objects. The anatomical consistency of each of our functionally defined regions across subjects and the spatial sharpness of their activation profiles within subjects highlight the fact that these regions constitute replicable and distinctive landmarks in the functional organization of the human brain., (Hum Brain Mapp, 2005. (c) 2005 Wiley-Liss, Inc.)

Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that the FFA is exclusively selective for face stimuli. We examined this claim by conducting a functional magnetic resonance imaging experiment at both standard (3.125 x 3.125 x 4.0 mm) and high resolution (1.4 x 1.4 x 2.0 mm). In both experiments, regions of interest (ROIs) were defined using data from blocked localizer runs. Within each ROI, we measured the mean peak response to a variety of stimulus types in independent data from a subsequent event-related experiment. Our localizer scans identified a fusiform body area (FBA), a body-selective region reported recently by Peelen and Downing (2005) that is anatomically distinct from the extrastriate body area. The FBA overlapped with and was adjacent to the FFA in all but two participants. Selectivity of the FFA to faces and FBA to bodies was stronger for the high-resolution scans, as expected from the reduction in partial volume effects. When new ROIs were constructed for the high-resolution experiment by omitting the voxels showing overlapping selectivity for both bodies and faces in the localizer scans, the resulting FFA* ROI showed no response above control objects for body stimuli, and the FBA* ROI showed no response above control objects for face stimuli. These results demonstrate strong selectivities in distinct but adjacent regions in the fusiform gyrus for only faces in one region (the FFA*) and only bodies in the other (the FBA*).

In many situations, people can only compute one stimulus-to-response mapping at a time, suggesting that response selection constitutes a "central processing bottleneck" in human information processing. Using fMRI, we tested whether common or distinct brain regions were involved in response selection across visual and auditory inputs, and across spatial and nonspatial mapping rules. We isolated brain regions involved in response selection by comparing two conditions that were identical in perceptual input and motor output, but differed in the complexity of the mapping rule. In the visual-manual task of Experiment 1, four vertical lines were positioned from left to right, and subjects pressed one of four keys to report which line was unique in length. In the auditory-manual task of Experiment 2, four tones were presented in succession, and subjects pressed one of four keys to report which tone was unique in duration. For both visual and auditory tasks, the mapping between target position and key position was either spatially compatible or incompatible. In the verbal task of Experiment 3, subjects used nonspatial mappings that were either compatible ("same" if colors matched; "different" if they mismatched) or incompatible (the opposite). Extensive activation overlap was observed across all three experiments for incompatible versus compatible mapping in bilateral parietal and frontal regions. Our results indicate that common neural substrates are involved in response selection across input modalities and across spatial and nonspatial domains of stimulus-to-response mapping, consistent with behavioral evidence that response selection is a central process. [ABSTRACT FROM AUTHOR]