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Causal reasoning enables us to explain the past, predict the future, and intervene in the present. Does the brain allocate specialized cortical regions to causal reasoning? And if so, are they involved in reasoning about both physical and social causal relationships, or are they domain-specific? In a pre-registered experiment (Exp 1) we scanned adults using fMRI while they matched physical and social causes to effects (e.g., ‘The car swerved to avoid a crash' -> ‘Coffee spilled all over the car seat'; ‘He was late for work' -> ‘Tom was scolded by his boss') or physical and social descriptions of the same entity matched for difficulty and linguistic variables to the causal conditions (e.g., ‘The brightest object in the sky'-> ‘The closest star to earth'; ‘She works at a hotel' -> ‘She brings in guests' luggage'). A region in the left lateral prefrontal cortex (LPFC) responded significantly more strongly to causal than descriptive conditions in most subjects individually. Responses in this region in held-out data were high for both social and physical causal conditions, yet no greater than baseline for the two descriptive (non-causal) conditions. In a follow-up exploratory experiment (Exp 2), we tested a different task (answering causal versus non-causal questions about physical and social narratives, matched for linguistic variables). Again, we found that both the physical and social causal stimuli selectively engaged the LPFC region. Finally, in both experiments, we found that brain regions previously implicated in intuitive physical reasoning responded more to the physical causal than the physical non-causal stimuli. Collectively, these results suggest that a) a region in the LPFC is selectively engaged in causal reasoning independent of content domain and b) the hypothesized physics network (hPN) is selectively involved in physical causal reasoning across modalities (visual vs. linguistic).

Faces are an important source of perceptual and social information. Multiple cortical regions including the fusiform faces area (FFA), the superior temporal sulcus (STS), and medial prefrontal cortex (MPFC) respond more to dynamic faces than videos of toy objects, human bodies, and pastoral scenes. Do face-preferring regions in FFA, STS, and MPFC have different functions? To address this question, we re-analyzed functional magnetic resonance imaging (fMRI) data from seven different experiments that included a dynamic faces versus objects localizer. Each of the seven experiments tested different perceptual and social features using dynamic videos, point light displays, narratives, and animated cartoons. Using a functional region of interest approach, we observed a significant condition by region interaction in four of the seven experiments. Thus, although FFA, STS, and MPFC respond more to dynamic faces than objects, bodies, and scenes, these three regions differ from each other functionally.

Prior studies have observed selective neural responses in the adult human auditory cortex to music and speech that cannot be explained by the differing lower‐level acoustic properties of these stimuli. Does infant cortex exhibit similarly selective responses to music and speech shortly after birth? To answer this question, we attempted to collect functional magnetic resonance imaging (fMRI) data from 45 sleeping infants (2.0‐ to 11.9‐weeks‐old) while they listened to monophonic instrumental lullabies and infant‐directed speech produced by a mother. To match acoustic variation between music and speech sounds we (1) recorded music from instruments that had a similar spectral range as female infant‐directed speech, (2) used a novel excitation‐matching algorithm to match the cochleagrams of music and speech stimuli, and (3) synthesized "model‐matched" stimuli that were matched in spectrotemporal modulation statistics to (yet perceptually distinct from) music or speech. Of the 36 infants we collected usable data from, 19 had significant activations to sounds overall compared to scanner noise. From these infants, we observed a set of voxels in non‐primary auditory cortex (NPAC) but not in Heschl's Gyrus that responded significantly more to music than to each of the other three stimulus types (but not significantly more strongly than to the background scanner noise). In contrast, our planned analyses did not reveal voxels in NPAC that responded more to speech than to model‐matched speech, although other unplanned analyses did. These preliminary findings suggest that music selectivity arises within the first month of life. A video abstract of this article can be viewed at https://youtu.be/c8IGFvzxudk. Research Highlights: Responses to music, speech, and control sounds matched for the spectrotemporal modulation‐statistics of each sound were measured from 2‐ to 11‐week‐old sleeping infants using fMRI.Auditory cortex was significantly activated by these stimuli in 19 out of 36 sleeping infants.Selective responses to music compared to the three other stimulus classes were found in non‐primary auditory cortex but not in nearby Heschl's Gyrus.Selective responses to speech were not observed in planned analyses but were observed in unplanned, exploratory analyses. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

One of the few replicated functional brain differences between individuals with autism spectrum disorders (ASD) and neurotypical (NT) controls is reduced language lateralization. However, most prior reports relied on comparisons of group‐level activation maps or functional markers that had not been validated at the individual‐subject level, and/or used tasks that do not isolate language processing from other cognitive processes, complicating interpretation. Furthermore, few prior studies have examined functional responses in other brain networks, as needed to determine the spatial selectivity of the effect. Using functional magnetic resonance imaging (fMRI), we compared language lateralization between 28 adult ASD participants and carefully pairwise‐matched controls, with the language regions defined individually using a well‐validated language "localizer" task. Across two language comprehension paradigms, ASD participants showed less lateralized responses due to stronger right hemisphere activity. Furthermore, this effect did not stem from a ubiquitous reduction in lateralization of function across the brain: ASD participants did not differ from controls in the lateralization of two other large‐scale networks—the Theory of Mind network and the Multiple Demand network. Finally, in an exploratory study, we tested whether reduced language lateralization may also be present in NT individuals with high autism‐like traits. Indeed, autistic trait load in a large set of NT participants (n = 189) was associated with less lateralized language responses. These results suggest that reduced language lateralization is robustly associated with autism and, to some extent, with autism‐like traits in the general population, and this lateralization reduction appears to be restricted to the language system. Lay Summary How do brains of individuals with autism spectrum disorders (ASD) differ from those of neurotypical (NT) controls? One of the most consistently reported differences is the reduction of lateralization during language processing in individuals with ASD. However, most prior studies have used methods that made this finding difficult to interpret, and perhaps even artifactual. Using robust individual‐level markers of lateralization, we found that indeed, ASD individuals show reduced lateralization for language due to stronger right‐hemisphere activity. We further show that this reduction is not due to a general reduction of lateralization of function across the brain. Finally, we show that greater autistic trait load is associated with less lateralized language responses in the NT population. These results suggest that reduced language lateralization is robustly associated with autism and, to some extent, with autism‐like traits in the general population. Autism Res 2020, 13: 1746–1761. © 2020 International Society for Autism Research and Wiley Periodicals LLC [ABSTRACT FROM AUTHOR]

The input to our visual system shifts every time we move our eyes. To maintain a stable percept of the world, visual representations must be updated with each saccade. Near the time of a saccade, neurons in several visual areas become sensitive to the regions of visual space that their receptive fields occupy after the saccade. This process, known as remapping, transfers information from one set of neurons to another, and may provide a mechanism for visual stability. However, it is not clear whether remapping transfers information about stimulus features in addition to information about stimulus location. To investigate this issue, we recorded blood-oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI) responses while human subjects viewed images of faces and houses (two visual categories with many feature differences). Immediately after some image presentations, subjects made a saccade that moved the previously stimulated location to the opposite side of the visual field. We then used a combination of univariate analyses and multivariate pattern analyses to test whether information about stimulus location and stimulus features were remapped to the ipsilateral hemisphere after the saccades. We found no reliable indication of stimulus feature remapping in any region. However, we also found no reliable indication of stimulus location remapping, despite the fact that our paradigm was highly similar to previous fMRI studies of remapping. The absence of location remapping in our study precludes strong conclusions regarding feature remapping. However, these results also suggest that measurement of location remapping with fMRI depends strongly on the details of the experimental paradigm used. We highlight differences in our approach from the original fMRI studies of remapping, discuss potential reasons for the failure to generalize prior location remapping results, and suggest directions for future research. [ABSTRACT FROM AUTHOR]

Congenital amusia is a lifelong deficit in music perception thought to reflect an underlying impairment in the perception and memory of pitch. The neural basis of amusic impairments is actively debated. Some prior studies have suggested that amusia stems from impaired connectivity between auditory and frontal cortex. However, it remains possible that impairments in pitch coding within auditory cortex also contribute to the disorder, in part because prior studies have not measured responses from the cortical regions most implicated in pitch perception in normal individuals. We addressed this question by measuring fMRI responses in 11 subjects with amusia and 11 ageand education-matched controls to a stimulus contrast that reliably identifies pitch-responsive regions in normal individuals: harmonic tones versus frequency-matched noise. Our findings demonstrate that amusic individuals with a substantial pitch perception deficit exhibit clusters of pitch-responsive voxels that are comparable in extent, selectivity, and anatomical location to those of control participants. Wediscuss possible explanations for why amusics might be impaired at perceiving pitch relations despite exhibiting normal fMRI responses to pitch in their auditory cortex: (1) individual neurons within the pitch-responsive region might exhibit abnormal tuning or temporal coding not detectable with fMRI, (2) anatomical tracts that link pitch-responsive regions to other brain areas (e.g., frontal cortex) might be altered, and (3) cortical regions outside of pitch-responsive cortex might be abnormal. The ability to identify pitch-responsive regions in individual amusic subjects will make it possible to ask more precise questions about their role in amusia in future work. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Pitch is a defining perceptual property of many real-world sounds, including music and speech. Classically, theories of pitch perception have differentiated between temporal and spectral cues. These cues are rendered distinct by the frequency resolution of the ear, such that some frequencies produce "resolved" peaks of excitation in the cochlea, whereas others are "unresolved," providing a pitch cue only via their temporal fluctuations. Despite longstanding interest, the neural structures that process pitch, and their relationship to these cues, have remained controversial. Here, using fMRI in humans, we report the following: (1) consistent with previous reports, all subjects exhibited pitch-sensitive cortical regions that responded substantially more to harmonic tones than frequency-matched noise; (2) the response of these regions was mainly driven by spectrally resolved harmonics, although they also exhibited a weak but consistent response to unresolved harmonics relative to noise; (3) the response of pitch-sensitive regions to a parametric manipulation of resolv-ability tracked psychophysical discrimination thresholds for the same stimuli; and (4) pitch-sensitive regions were localized to specific tonotopic regions of anterior auditory cortex, extending from a low-frequency region of primary auditory cortex into a more anterior and less frequency-selective region of nonprimary auditory cortex. These results demonstrate that cortical pitch responses are located in a stereotyped region of anterior auditory cortex and are predominantly driven by resolved frequency components in a way that mirrors behavior. [ABSTRACT FROM AUTHOR]

Visual object recognition relies critically on learning. However, little is known about the effect of object learning in human visual cortex, and in particular how the spatial distribution of training effects relates to the distribution of object and face selectivity across the cortex before training. We scanned human subjects with high-resolution functional magnetic resonance imaging (fMRI) while they viewed novel object classes, both before and after extensive training to discriminate between exemplars within one of these object classes. Training increased the strength of the response in visual cortex to trained objects compared with untrained objects. However, training did not simply induce a uniform increase in the response to trained objects: the magnitude of this training effect varied substantially across subregions of extrastriate cortex, with some showing a twofold increase in response to trained objects and others (including the right fusiform face area) showing no significant effect of training. Furthermore, the spatial distribution of training effects could not be predicted from the spatial distribution of either pretrained responses or face selectivity. Instead, training changed the spatial distribution of activity across the cortex. These findings support a dynamic view of the ventral visual pathway in which the cortical representation of an object category is continuously modulated by experience. [ABSTRACT FROM AUTHOR]

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 4.0mm)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*). [ABSTRACT FROM AUTHOR]

Macular degeneration (MD), the leading cause of visual impairment in the developed world, damages the central retina, often obliterating foveal vision and severely disrupting everyday tasks such as reading, driving, and face recognition. In such cases, the macular damage eliminates the normal retinal input to a large region of visual cortex, comprising tens of square centimeters of surface area in each hemisphere, which is normally responsive only to foveal stimuli. Using functional magnetic resonance imaging, we asked whether this deprived cortex simply becomes inactive in subjects with MD, or whether it takes on new functional properties. In two adult MD subjects with extensive bilateral central retinal lesions, we found that parts of visual cortex (including primary visual cortex) that normally respond only to central visual stimuli are strongly activated by peripheral stimuli. Such activation was not observed (1) with visual stimuli presented to the position of the former fovea and (2) in control subjects with visual stimuli presented to corresponding parts of peripheral retina. These results demonstrate large-scale reorganization of visual processing in MD and will likely prove important in any effort to develop new strategies for rehabilitation of MD subjects. [ABSTRACT FROM AUTHOR]

How can functional magnetic resonance imaging (fMRI) advance cognitive theory? Some have argued that fMRI can do little beyond localizing brain regions that carry out certain cognitive functions (and may not even be able to do that). However, in this article, we argue that fMRI can inform theories of cognition by helping to answer at least four distinct kinds of questions. Which mental functions are performed in brain regions specialized for just that function (and which are performed in more general-purpose brain machinery)? When fMRI markers of a particular Mental Process X are found, is Mental Process X engaged when people perform Task Y? How distinct are the representations of different stimulus classes? Do specific pairs of tasks engage common or distinct processing mechanisms? Thus, fMRI data can be used to address theoretical debates that have nothing to do with where in the brain a particular process is carried out. [ABSTRACT FROM AUTHOR]

Abstract: 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., ). We argue that traditional group analysis methods in neuroimaging may obscure functional specificity because of inter-subject anatomical variability (). In 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., ) and social cognition (e.g., ). [Copyright &y& Elsevier]

Abstract: We present a method for discovering patterns of selectivity in fMRI data for experiments with multiple stimuli/tasks. We introduce a representation of the data as profiles of selectivity using linear regression estimates, and employ mixture model density estimation to identify functional systems with distinct types of selectivity. The method characterizes these systems by their selectivity patterns and spatial maps, both estimated simultaneously via the EM algorithm. We demonstrate a corresponding method for group analysis that avoids the need for spatial correspondence among subjects. Consistency of the selectivity profiles across subjects provides a way to assess the validity of the discovered systems. We validate this model in the context of category selectivity in visual cortex, demonstrating good agreement with the findings based on prior hypothesis-driven methods. [Copyright &y& Elsevier]

Neuroimaging studies have identified three scene-selective regions in human cortex: parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA). However, precisely what scene information each region represents is not clear, especially for the least studied, more posterior OPA. Here we hypothesized that OPA represents local elements of scenes within two independent, yet complementary scene descriptors: spatial boundary (i.e., the layout of external surfaces) and scene content (e.g., internal objects). If OPA processes the local elements of spatial boundary information, then it should respond to these local elements (e.g., walls) themselves, regardless of their spatial arrangement. Indeed, we found that OPA, but not PPA or RSC, responded similarly to images of intact rooms and these same rooms in which the surfaces were fractured and rearranged, disrupting the spatial boundary. Next, if OPA represents the local elements of scene content information, then it should respond more when more such local elements (e.g., furniture) are present. Indeed, we found that OPA, but not PPA or RSC, responded more to multiple than single pieces of furniture. Taken together, these findings reveal that OPA analyzes local scene elements – both in spatial boundary and scene content representation – while PPA and RSC represent global scene properties. [ABSTRACT FROM AUTHOR]

How is music represented in the brain? While neuroimaging has revealed some spatial segregation between responses to music versus other sounds, little is known about the neural code for music itself. To address this question, we developed a method to infer canonical response components of human auditory cortex using intracranial responses to natural sounds, and further used the superior coverage of fMRI to map their spatial distribution. The inferred components replicated many prior findings, including distinct neural selectivity for speech and music, but also revealed a novel component that responded nearly exclusively to music with singing. Song selectivity was not explainable by standard acoustic features, was located near speech- and music-selective responses, and was also evident in individual electrodes. These results suggest that representations of music are fractionated into subpopulations selective for different types of music, one of which is specialized for the analysis of song. • Neural population responsive to singing, but not instrumental music or speech • New statistical method infers neural populations from human intracranial responses • fMRI used to map the spatial distribution of intracranial responses • Intracranial responses replicate distinct music- and speech-selective populations Using human intracranial recordings, Norman-Haignere et al. reveal a neural population that responds to singing, but not instrumental music or speech. This neural population was uncovered by modeling electrode responses as a weighted sum of canonical response components. The spatial distribution of each intracranial component was mapped using fMRI. [ABSTRACT FROM AUTHOR]

Abstract: 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 (). 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 &y& Elsevier]

Abstract: Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with previously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli. [Copyright &y& Elsevier]

Abstract: 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 &y& Elsevier]

Abstract: We previously reported large-scale reorganization of visual processing (i.e., activation of “foveal” cortex by peripheral stimuli) in two individuals with loss of foveal input from macular degeneration [Baker, C.I., Peli, E., Knouf, N., & Kanwisher, N. G. (2005). Reorganization of visual processing in macular degeneration. Journal of Neuroscience, 25(3), 614–618]. Here, we replicate this result in three new individuals. Further, we test the hypothesis that this reorganization is dependent on complete loss of foveal input. In two other individuals with extensive retinal lesions but some foveal sparing we found no evidence for reorganization. We conclude that large-scale reorganization of visual processing in MD occurs only in the complete absence of functional foveal vision. [Copyright &y& Elsevier]