Research: Current Projects

Read about our current studies below.

Brain Imaging in Children with Autism

While significant advances have been made in identifying brain functional and structural difference between individuals with autism spectrum disorders (ASD) and typically developing (TD) individuals, little is known regarding differences in large-scale brain network interactions that underlie the social and communicative deficits and atypical behaviors in ASD. Our research aims to examine the structural and functional connectivity patterns of brain areas that participate in neural networks for social cognition, imitation, language, and other functions in children and adolescents with ASD. We theorize that abnormalities in connections within and between these neural networks can disrupt normative cognitive development in ASD.

We use a multimodal approach to this research, utilizing two complementary neuroimaging techniques (functional connectivity MRI and diffusion weighted MRI) to assess both functional and structural connectivity in children and adolescents ages 7-18 years. Establishing links between cognitive-behavioral impairment, local cortical compromise, functional connectivity, and anatomical connectivity promises to unite several currently separate lines of neurodevelopmental research in autism that may be the foundation for therapeutic advances. Research also provides an approach to characterizing neurofunctionally defined endophenotypes of autism, in support of identifying subtypes of genetic risk within the population.

Adults with Autism

The behavioral and neuroscientific literature on children and adolescents with autism spectrum disorder (ASD) has grown dramatically over the past decades. In contrast, almost nothing is known about ASD later in life. This is problematic in view of preliminary findings suggesting that some older people with ASD may experience accelerated cognitive and neurological decline, combined with extensive evidence of age-related complications and decline in other neurodevelopmental disorders.

This study is the first systematic investigation of brain anatomy and connectivity in mid to late adulthood in ASD. We use anatomical, functional connectivity, and diffusion MRI as well as a battery of sensorimotor and cognitive tests in a longitudinal design, with participants returning after 2.5 years for a second time point. The major goals of the study are to examine (1) brain anatomy (cortical thickness and volumes of gray matter structures, white matter, and CSF) and (2) anatomical and functional brain connectivity in adults with ASD compared to typically developing participants, (3) to characterize cognitive and behavioral abilities, and correlate these skills with brain structure and function, and (4) to create an extensive inventory of variables that may predict long- term neurocognitive success or decline in ASD. Analyses will be performed for a broad range of domains and networks, with some focus on executive, motor, and memory systems.

Results from this study will provide a systematic body of evidence on changes in brain and behavior during mid to late adulthood in ASD, and will have strong prospective translational relevance because identification of brain sites and behavioral measures most likely to predict age-related decline vs. successful aging in ASD will be crucial for the development of preventative interventions.

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Dynamic Changes in Brain Networks

In the context of increasing prevalence, the brain bases of autism spectrum disorder (ASD) remain incompletely understood. There is growing consensus that ASD is a disorder of brain connectivity, but functional connectivity findings are inconsistent. Resting state functional MRI (rs-fMRI) data, considered ideal for the study of intrinsic functional connectivity, are being collected by numerous groups and are now available in a large public database. However, differences in behavioral and cognitive traits may significantly affect fMRI data collected in the ‘resting state’ and little is known about potential confounds that may result from these differences. This lack of knowledge is troubling in view of the ill-defined nature of the ‘resting state’, which largely eludes experimental control.

Specifically, rs-fMRI connectivity has been solely examined using static approaches. This project uses dynamic fMRI sliding window analyses in combination with EEG (electroencephalography) to investigate the dynamic variability of functional connectivity during the resting state. Adolescents with ASD and matched typically developing (TD) participants will be scanned using both rs-fMRI and EEG concurrently. We will test dynamic changes in connectivity across time, using a sliding window rs-fMRI analysis, and use EEG data to examine dynamic changes in high temporal frequency bands and characterize temporal patterns with respect to electrophysiological changes. We hypothesize that ASD participants will show greater variability of connectivity across time in and between several brain networks (e.g., default mode, dorsal attention, saliency), accompanied by variability in electrophysiological states. A better understanding of potentially systematic differences between ASD and TD participants in response to the resting state will allow us to better interpret group differences detected in rs-fMRI functional connectivity studies.

We are currently seeking individuals aged 12-22 to participate in this study. To find out more, follow this link.

SCANgroup and Toddler MRI Project

Dr. Inna Fishman and her colleagues at BDIL/SDSU, UCSD, and Rady Children’s Hospital (Drs. Ralph-Axel Müller, Ruth Carper, Christina Corsello) are conducting a research study to identify early brain markers for Autism spectrum disorders. This project is funded by the National Institutes of Mental Health and aims at detecting unique “brain signature” in the first years of life in toddlers with ASD.

As a disorder of brain development, autism affects how the brain grows and works; yet, brain development trajectories accompanying the emergence of first symptoms of ASD, in the 2nd year of life, are almost completely unknown.  This research study aims to identify how brain networks are organized and change over time, during the most critical developmental window when ASD symptoms first emerge (at age 18-26 months) and reach their peak (at 4-5 years of age).  Identification of brain markers of risk will advance future discoveries of novel, effective diagnostics and treatments in ASD.  Experts agree that better and earlier detection of autism is critical for successful treatment.

If you have a 15-28 months old child with a diagnosis of ASD (or suspect she or he may have one), or if you have a typically developing toddler, please consider taking part in this important project.  If you are unsure about your child’s status, our experienced developmental psychologist will conduct a play-based diagnostic evaluation to assess whether your child may have ASD.  Should your child be eligible for the study, you will be asked to bring your child for an MRI scan around his or her bedtime.  Your child will be scanned while naturally asleep (no sedation will be involved).  To achieve the goals of the study, we would also like to see you again 2 more times before your child turns 5 years old (each time will be about 1.5 years apart).  You will be compensated for your time (you will earn $100 for the MRI visit and $50 for the evaluation / introductory visit).

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Word Reading in the Brain

Recent findings from functional connectivity MRI (fcMRI) and diffusion tensor imaging (DTI) suggest that cognitive, sociocommunicative, and sensorimotor impairments in autism spectrum disorders (ASD) are associated with impaired brain network connectivity. Few ASD studies, however, have combined measures of functional and anatomical connectivity. Even more importantly, there are no studies combining these with measures of dynamic processing, which are provided by magnetoencephalography (MEG).

This project uses fcMRI, DTI, and MEG for a comprehensive investigation of brain connectivity in ASD, using a work reading task to identify a visual, lexico-semantic, executive, and motor (VLSEM) circuit. In this project, we will first identify network nodes of a VLSEM brain circuit using fMRI during lexical-semantic decision making and examine the functional connectivity within this circuit and between nodes and the remaining brain. We will also examine the dynamic, spatiotemporal characteristics of the VLSEM circuit, using MEG in time-domain and time-frequency analyses. We will then examine the anatomical connections within the VLSEM circuit using probabilistic DTI tractography, and test for links between fcMRI, MEG, and DTI measures. Finally, we will examine the relation of functional and anatomical connectivity as well as dynamic processing with diagnostic and neuropsychological measures in the ASD group.

The project will contribute multimodal imaging evidence for an improved and comprehensive understanding of brain network abnormalities in ASD. Such evidence will be particularly important for the identification of biomarkers of ASD, including those that may distinguish different biological subtypes of the disorder.

We are currently seeking children aged 7-17 years to participate in this study. To find out more, follow this link.

Computational Projects