A size-adaptive 32-channel array coil for awake infant neuroimaging at 3 Tesla MRI

PURPOSE

Functional magnetic resonance imaging (fMRI) during infancy poses challenges due to practical, methodological, and analytical considerations. The aim of this study was to implement a hardware-related approach to increase subject compliance for fMRI involving awake infants. To accomplish this, we designed, constructed, and evaluated an adaptive 32-channel array coil.

METHODS

To allow imaging with a close-fitting head array coil for infants aged 1-18 months, an adjustable head coil concept was developed. The coil setup facilitates a half-seated scanning position to improve the infant's overall scan compliance. Earmuff compartments are integrated directly into the coil housing to enable the usage of sound protection without losing a snug fit of the coil around the infant's head. The constructed array coil was evaluated from phantom data using bench-level metrics, signal-to-noise ratio (SNR) performances, and accelerated imaging capabilities for both in-plane and simultaneous multislice (SMS) reconstruction methodologies. Furthermore, preliminary fMRI data were acquired to evaluate the in vivo coil performance.

RESULTS

Phantom data showed a 2.7-fold SNR increase on average when compared with a commercially available 32-channel head coil. At the center and periphery regions of the infant head phantom, the SNR gains were measured to be 1.25-fold and 3-fold, respectively. The infant coil further showed favorable encoding capabilities for undersampled k-space reconstruction methods and SMS techniques.

CONCLUSIONS

An infant-friendly head coil array was developed to improve sensitivity, spatial resolution, accelerated encoding, motion insensitivity, and subject tolerance in pediatric MRI. The adaptive 32-channel array coil is well-suited for fMRI acquisitions in awake infants.

Music-selective neural populations arise without musical training

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.

The Language Network Is Recruited but Not Required for Nonverbal Event Semantics

The ability to combine individual concepts of objects, properties, and actions into complex representations of the world is often associated with language. Yet combinatorial event-level representations can also be constructed from nonverbal input, such as visual scenes. Here, we test whether the language network in the human brain is involved in and necessary for semantic processing of events presented nonverbally. In Experiment 1, we scanned participants with fMRI while they performed a semantic plausibility judgment task versus a difficult perceptual control task on sentences and line drawings that describe/depict simple agent-patient interactions. We found that the language network responded robustly during the semantic task performed on both sentences and pictures (although its response to sentences was stronger). Thus, language regions in healthy adults are engaged during a semantic task performed on pictorial depictions of events. But is this engagement necessary? In Experiment 2, we tested two individuals with global aphasia, who have sustained massive damage to perisylvian language areas and display severe language difficulties, against a group of age-matched control participants. Individuals with aphasia were severely impaired on the task of matching sentences to pictures. However, they performed close to controls in assessing the plausibility of pictorial depictions of agent-patient interactions. Overall, our results indicate that the left frontotemporal language network is recruited but not necessary for semantic processing of nonverbally presented events.

Reduced Language Lateralization in Autism and the Broader Autism Phenotype as Assessed with Robust Individual-Subjects Analyses

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.

Visual experience is not necessary for the development of face-selectivity in the lateral fusiform gyrus

The fusiform face area responds selectively to faces and is causally involved in face perception. How does face-selectivity in the fusiform arise in development, and why does it develop so systematically in the same location across individuals? Preferential cortical responses to faces develop early in infancy, yet evidence is conflicting on the central question of whether visual experience with faces is necessary. Here, we revisit this question by scanning congenitally blind individuals with fMRI while they haptically explored 3D-printed faces and other stimuli. We found robust face-selective responses in the lateral fusiform gyrus of individual blind participants during haptic exploration of stimuli, indicating that neither visual experience with faces nor fovea-biased inputs is necessary for face-selectivity to arise in the lateral fusiform gyrus. Our results instead suggest a role for long-range connectivity in specifying the location of face-selectivity in the human brain.

Invariant representations of mass in the human brain

An intuitive understanding of physical objects and events is critical for successfully interacting with the world. Does the brain achieve this understanding by running simulations in a mental physics engine, which represents variables such as force and mass, or by analyzing patterns of motion without encoding underlying physical quantities? To investigate, we scanned participants with fMRI while they viewed videos of objects interacting in scenarios indicating their mass. Decoding analyses in brain regions previously implicated in intuitive physical inference revealed mass representations that generalized across variations in scenario, material, friction, and motion energy. These invariant representations were found during tasks without action planning, and tasks focusing on an orthogonal dimension (object color). Our results support an account of physical reasoning where abstract physical variables serve as inputs to a forward model of dynamics, akin to a physics engine, in parietal and frontal cortex.

Eye movements and retinotopic tuning in developmental prosopagnosia

Despite extensive investigation, the causes and nature of developmental prosopagnosia (DP)-a severe face identification impairment in the absence of acquired brain injury-remain poorly understood. Drawing on previous work showing that individuals identified as being neurotypical (NT) show robust individual differences in where they fixate on faces, and recognize faces best when the faces are presented at this location, we defined and tested four novel hypotheses for how atypical face-looking behavior and/or retinotopic face encoding could impair face recognition in DP: (a) fixating regions of poor information, (b) inconsistent saccadic targeting, (c) weak retinotopic tuning, and (d) fixating locations not matched to the individual's own face tuning. We found no support for the first three hypotheses, with NTs and DPs consistently fixating similar locations and showing similar retinotopic tuning of their face perception performance. However, in testing the fourth hypothesis, we found preliminary evidence for two distinct phenotypes of DP: (a) Subjects characterized by impaired face memory, typical face perception, and a preference to look high on the face, and (b) Subjects characterized by profound impairments to both face memory and perception and a preference to look very low on the face. Further, while all NTs and upper-looking DPs performed best when faces were presented near their preferred fixation location, this was not true for lower-looking DPs. These results suggest that face recognition deficits in a substantial proportion of people with DP may arise not from aberrant face gaze or compromised retinotopic tuning, but from the suboptimal matching of gaze to tuning.

Divergence in the functional organization of human and macaque auditory cortex revealed by fMRI responses to harmonic tones

We report a difference between humans and macaque monkeys in the functional organization of cortical regions implicated in pitch perception: humans but not macaques showed regions with a strong preference for harmonic sounds compared to noise, measured with both synthetic tones and macaque vocalizations. In contrast, frequency-selective tonotopic maps were similar between the two species. This species difference may be driven by the unique demands of speech and music perception in humans.

An integrative computational architecture for object-driven cortex

Computational architecture for object-driven cortex Objects in motion activate multiple cortical regions in every lobe of the human brain. Do these regions represent a collection of independent systems, or is there an overarching functional architecture spanning all of object-driven cortex? Inspired by recent work in artificial intelligence (AI), machine learning, and cognitive science, we consider the hypothesis that these regions can be understood as a coherent network implementing an integrative computational system that unifies the functions needed to perceive, predict, reason about, and plan with physical objects-as in the paradigmatic case of using or making tools. Our proposal draws on a modeling framework that combines multiple AI methods, including causal generative models, hybrid symbolic-continuous planning algorithms, and neural recognition networks, with object-centric, physics-based representations. We review evidence relating specific components of our proposal to the specific regions that comprise object-driven cortex, and lay out future research directions with the goal of building a complete functional and mechanistic account of this system.

How face perception unfolds over time

Within a fraction of a second of viewing a face, we have already determined its gender, age and identity. A full understanding of this remarkable feat will require a characterization of the computational steps it entails, along with the representations extracted at each. Here, we used magnetoencephalography (MEG) to measure the time course of neural responses to faces, thereby addressing two fundamental questions about how face processing unfolds over time. First, using representational similarity analysis, we found that facial gender and age information emerged before identity information, suggesting a coarse-to-fine processing of face dimensions. Second, identity and gender representations of familiar faces were enhanced very early on, suggesting that the behavioral benefit for familiar faces results from tuning of early feed-forward processing mechanisms. These findings start to reveal the time course of face processing in humans, and provide powerful new constraints on computational theories of face perception.

Toward a universal decoder of linguistic meaning from brain activation

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.

Dissociating intuitive physics from intuitive psychology: Evidence from Williams syndrome

Prior work suggests that our understanding of how things work ("intuitive physics") and how people work ("intuitive psychology") are distinct domains of human cognition. Here we directly test the dissociability of these two domains by investigating knowledge of intuitive physics and intuitive psychology in adults with Williams syndrome (WS) - a genetic developmental disorder characterized by severely impaired spatial cognition, but relatively spared social cognition. WS adults and mental-age matched (MA) controls completed an intuitive physics task and an intuitive psychology task. If intuitive physics is a distinct domain (from intuitive psychology), then we should observe differential impairment on the physics task for individuals with WS compared to MA controls. Indeed, adults with WS performed significantly worse on the intuitive physics than the intuitive psychology task, relative to controls. These results support the hypothesis that knowledge of the physical world can be disrupted independently from knowledge of the social world.