Automatic analysis (aa): efficient neuroimaging workflows and parallel processing using Matlab and XML.

Recent years have seen neuroimaging data sets becoming richer, with larger cohorts of participants, a greater variety of acquisition techniques, and increasingly complex analyses. These advances have made data analysis pipelines complicated to set up and run (increasing the risk of human error) and time consuming to execute (restricting what analyses are attempted). Here we present an open-source framework, automatic analysis (aa), to address these concerns. Human efficiency is increased by making code modular and reusable, and managing its execution with a processing engine that tracks what has been completed and what needs to be (re)done. Analysis is accelerated by optional parallel processing of independent tasks on cluster or cloud computing resources. A pipeline comprises a series of modules that each perform a specific task. The processing engine keeps track of the data, calculating a map of upstream and downstream dependencies for each module. Existing modules are available for many analysis tasks, such as SPM-based fMRI preprocessing, individual and group level statistics, voxel-based morphometry, tractography, and multi-voxel pattern analyses (MVPA). However, aa also allows for full customization, and encourages efficient management of code: new modules may be written with only a small code overhead. aa has been used by more than 50 researchers in hundreds of neuroimaging studies comprising thousands of subjects. It has been found to be robust, fast, and efficient, for simple-single subject studies up to multimodal pipelines on hundreds of subjects. It is attractive to both novice and experienced users. aa can reduce the amount of time neuroimaging laboratories spend performing analyses and reduce errors, expanding the range of scientific questions it is practical to address

The Brain Imaging Data Structure, a Format for Organizing and Describing Outputs of Neuroimaging Experiments

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations

Laminar fMRI in Auditory Cortex at 7T

Auditory cortex is involved in the perception, attention, memory and imagery of sounds. Neuroimaging has been a rich source of information on which cortical areas are recruited for different tasks. However, a more detailed understanding has been confined to animal studies using invasive imaging modalities, and high-resolution functional descriptions of auditory cortex, including columnar/laminar specific activity, topographical organization within layers, and the way these representations transfer between processing structures remain poorly understood in humans. We present 7T fMRI as a non-invasive tool for high-resolution functional imaging of human auditory cortex on the laminar scale. We describe MATLAB tools for optimizing a segmentation pipeline in BrainVoyager, and an analysis pipeline using an SPM to examine functional differences between cortical layers of auditory cortex. These differences are measured within the context of auditory memory maintenance, imagery, and tonotopy

Assessing awareness in severe Alzheimer's disease

There is an urgent need to understand the nature of awareness in people with severe Alzheimer's disease (AD) to ensure effective person-centered care. Objective biomarkers of awareness validated in other clinical groups (e.g., anesthesia, minimally conscious states) offer an opportunity to investigate awareness in people with severe AD. In this article we demonstrate the feasibility of using Transcranial magnetic stimulation (TMS) combined with EEG, event related potentials (ERPs) and fMRI to assess awareness in severe AD. TMS-EEG was performed in six healthy older controls and three people with severe AD. The perturbational complexity index (PCIST) was calculated as a measure of capacity for conscious awareness. People with severe AD demonstrated a PCIST around or below the threshold for consciousness, suggesting reduced capacity for consciousness. ERPs were recorded during a visual perception paradigm. In response to viewing faces, two patients with severe AD provisionally demonstrated similar visual awareness negativity to healthy controls. Using a validated fMRI movie-viewing task, independent component analysis in two healthy controls and one patient with severe AD revealed activation in auditory, visual and fronto-parietal networks. Activation patterns in fronto-parietal networks did not significantly correlate between the patient and controls, suggesting potential differences in conscious awareness and engagement with the movie. Although methodological issues remain, these results demonstrate the feasibility of using objective measures of awareness in severe AD. We raise a number of challenges and research questions that should be addressed using these biomarkers of awareness in future studies to improve understanding and care for people with severe AD

While you were sleeping: Evidence for high-level executive processing of an auditory narrative during sleep

During sleep we lack conscious awareness of the external environment. Yet, our internal mental state suggests that high-level cognitive processes persist. The nature and extent to which the external environment is processed during sleep remain largely unexplored. Here, we used an fMRI synchronization-based approach to examine responses to a narrative during wakefulness and sleep. The stimulus elicited the auditory network and a frontoparietal pattern of activity, consistent with high-level narrative plot-following. During REM sleep, the same frontoparietal pattern was observed in one of three participants, and partially in one other, confirming that it is possible to track and follow the moment-to-moment complexities of a narrative during REM sleep. Auditory network recruitment was observed in both non-REM and REM sleep, demonstrating preservation of low-level auditory processing, even in deep sleep. This novel approach investigating cognitive processing at different levels of awareness demonstrates that the brain can meaningfully process the external environment during REM sleep

Multimodal Integration and Vividness in the Angular Gyrus During Episodic Encoding and Retrieval.

Much evidence suggests that the angular gyrus (AnG) is involved in episodic memory, but its precise role has yet to be determined. We examined two possible accounts within the same experimental paradigm: the "cortical binding of relational activity" (CoBRA) account (Shimamura, 2011), which suggests that the AnG acts as a convergence zone that binds multimodal episodic features, and the subjectivity account (Yazar et al., 2012), which implicates AnG involvement in subjective mnemonic experience (such as vividness or confidence). fMRI was used during both encoding and retrieval of paired associates. During study, female and male human participants memorized picture-pairs of common objects (in the unimodal task) or of an object-picture and an environmental sound (in the crossmodal task). At test, they performed a cued-recall task and further indicated the vividness of their memory. During retrieval, BOLD activation in the AnG was greatest for vividly remembered associates, consistent with the subjectivity account. During encoding, the same effect of vividness was found, but this was further modulated by task: greater activations were associated with subsequent recall in the crossmodal than the unimodal task. Therefore, encoding data suggest an additional role to the AnG in crossmodal integration, consistent with its role at retrieval proposed by CoBRA. These results resolve some of the puzzles in the literature and indicate that the AnG can play different roles during encoding and retrieval as determined by the cognitive demands posed by different mnemonic tasks.SIGNIFICANCE STATEMENT We offer new insights into the multiplicity of processes that are associated with angular gyrus (AnG) activation during encoding and retrieval of newly formed memories. We used fMRI while human participants learned and subsequently recalled pairs of objects presented to the same sensory modality or to different modalities. We were able to show that the AnG is involved when vivid memories are created and retrieved, as well as when encoded information is integrated across different sensory modalities. These findings provide novel evidence for the contribution of the AnG to our subjective experience of remembering alongside its role in integrative processes that promote subsequent memory

Resting State fcMRI in the Social Cognition Network as a Predictive Measure for Scores of Socialization of Preterm Neonates

Many resting state networks have been detected in newborn infants using functional connectivity Magnetic Resonance Imaging (fcMRI). Few studies have looked at a social cognition network in adults and none have looked at this network in infants. Social cognition plays an important role in social competence at school age and beyond, and infants born prematurely tend to have difficulties with peer relationships and lower academic performance by school-age. This study had two purposes: to find a social cognition network in our preterm and neurologically diagnosed sample, and to find a relationship to social interaction scores from the Vineland Adaptive Behavior Scales-II (VABS-II). Results showed a positive correlation between an adult fcMRI and neonate fcMRI social cognition network, r(64) = .59, p \u3c .05, however, no correlation was found between fcMRI similarity (to adults) scores in the first six months, r(30) = .17, p \u3e .05, or the second six months, r(30) = .09, p \u3e .05 of life using the VABS-II social interaction category. Results also show no correlation between fcMRI scores of neonates and gestational age, r(30) = .20, p \u3e .05, nor birth weight, r(30) = .22, p \u3e .05). There are important implications for government spending, educational support, and child outcomes if we can predict which children need intervention, and implement them sooner than school-age. More research is needed to further assess and confirm the social cognition network in infants and find connections to later social adeptness in children so we can benefit this population sooner

Examining the relationship between measures of autistic traits and neural synchrony during movies in children with and without autism

Children who have been diagnosed with autism spectrum disorder (ASD) often show a marked deficit in measures of social cognition. In autistic adults, measures of social cognition have been shown to relate to differences in brain synchronization (as measured by fMRI) when individuals are processing naturalistic stimuli, such as movies. However, whether children who differ in their degree of autistic traits, with or without a diagnosis of ASD, differ in their neural responses to movies has not yet been investigated. In the current study, neural synchrony, measured using fMRI, was examined in three groups of children aged 7 to 12, who differed with respect to scores on a measure of autistic traits associated with social impairment and whether or not they had been diagnosed with ASD. While watching the movie ‘Despicable Me’, those diagnosed with ASD had significantly less neural synchrony in areas that have been previously shown to be associated with social cognition (e.g. areas related to ‘theory of mind’), and plot following (e.g. the lateral prefrontal cortex), than those who did not have an ASD diagnosis. In contrast, two groups who differed in their degree of autistic traits, but did not have a diagnosis of ASD, showed no significant differences in neural synchrony across the whole brain. These results shed some light on how autistic traits may contribute to an individual\u27s conscious experience of the world, and how, for children with ASD, that experience may differ markedly from that of those without ASD

Functional diversity of brain networks supports consciousness and verbal intelligence

© 2018, The Author(s). How are the myriad stimuli arriving at our senses transformed into conscious thought? To address this question, in a series of studies, we asked whether a common mechanism underlies loss of information processing in unconscious states across different conditions, which could shed light on the brain mechanisms of conscious cognition. With a novel approach, we brought together for the first time, data from the same paradigm—a highly engaging auditory-only narrative—in three independent domains: anesthesia-induced unconsciousness, unconsciousness after brain injury, and individual differences in intellectual abilities during conscious cognition. During external stimulation in the unconscious state, the functional differentiation between the auditory and fronto-parietal systems decreased significantly relatively to the conscious state. Conversely, we found that stronger functional differentiation between these systems in response to external stimulation predicted higher intellectual abilities during conscious cognition, in particular higher verbal acuity scores in independent cognitive testing battery. These convergent findings suggest that the responsivity of sensory and higher-order brain systems to external stimulation, especially through the diversification of their functional responses is an essential feature of conscious cognition and verbal intelligence