As the father of a 15 year old son with severe autism deficits AND "profound developmental delays" I have found the insistence in some quarters of the alleged world autism community that there is no such thing as low functioning and high functioning autism, or severe and mild autism, to be both irrational and offensive. It is irrational and offensive to suggest that a very high functioning individual with high intelligence and excellent communication skills, capable of sitting on IACC committees and moving from one high profile media interview to the next, has the the same, or even similar, challenges as my 15 year old Dr. Seuss reading son who does occasionally suffer serious meltdowns in public settings or when frustrated or overwhelmed generally. It is offensive to see my son's challenges hidden in a media closet while those barely affected, if they are affected at all, by autism portray autism as a difference not a disability.
The media obsession with, and public perception of, high functioning autism and Asperger's success stories as being representative of autism, will not go away soon if at all. Public understanding of the challenges facing the severely autistic will probably remain limited for many years to come. The just reported Stanford/Packard autism brain imaging study though may be an important step forward for the family members and professionals who understand and face the realities of trying to help severely autistic loved ones or patients.
The study involved subjects with autism excluding Asperger's and related disorders. The authors claim to have mapped a topography of the autistic brain so clearly that they have been able to identify a relationship between severity of autism symptoms and severity of brain-structure differences. As with any small initial study replication studies involving more participants will need to be done to confirm the original findings. Given the promise of this initial study I would be shocked if such confirming studies are not undertaken promptly. Perhaps if the mainstream media can actually, finally see images of differences in autism brain structures they will stop ignoring differences in severity levels of those affected by autism disorders. Perhaps.
While autism diagnoses are now based entirely on clinical observations and a battery of psychiatric and educational tests, researchers have been making advances toward identifying anatomical features in the brain that would help to determine whether a person is autistic.
"The new findings give a uniquely comprehensive view of brain organization in children with autism and uncover a relationship between the severity of brain-structure differences and the severity of autism symptoms," said Vinod Menon, PhD, a professor of psychiatry and behavioral sciences and of neurology and neurological sciences, who led the research.
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"We could discriminate between typically developing and autistic children with 92 percent accuracy on the basis of gray matter volume in the posterior cingulate cortex," said Lucina Uddin, PhD, the study's first author. Uddin is an instructor in psychiatry and behavioral sciences at Stanford.
In addition, the children with the most severe communication deficits, as measured on a standard behavioral scale for diagnosing individuals with autism, had the biggest brain structure differences. Severe impairments in social behavior and repetitive behavior also showed a trend toward association with more severe brain differences.
The above quotes are from the press release, posted in full below, for the Stanford/Packard MRI brain scan study published September 2 2011 in Biological Psychiatry, the official journal of the Society of Biological Psychiatry.
The above quotes are from the press release, posted in full below, for the Stanford/Packard MRI brain scan study published September 2 2011 in Biological Psychiatry, the official journal of the Society of Biological Psychiatry.
Public release date: 2-Sep-2011
Contact: Jonathan Rabinovitz
jrabin@stanford.edu
650-724-2459
Stanford University Medical Center
Distinct features of autistic brain revealed in novel Stanford/Packard analysis of MRI scans
STANFORD, Calif. - Researchers at the Stanford University School of Medicine and Lucile Packard Children's Hospital have used a novel method for analyzing brain-scan data to distinguish children with autism from typically developing children. Their discovery reveals that the gray matter in a network of brain regions known to affect social communication and self-related thoughts has a distinct organization in people with autism. The findings will be published online Sept. 2 in Biological Psychiatry.
While autism diagnoses are now based entirely on clinical observations and a battery of psychiatric and educational tests, researchers have been making advances toward identifying anatomical features in the brain that would help to determine whether a person is autistic.
"The new findings give a uniquely comprehensive view of brain organization in children with autism and uncover a relationship between the severity of brain-structure differences and the severity of autism symptoms," said Vinod Menon, PhD, a professor of psychiatry and behavioral sciences and of neurology and neurological sciences, who led the research.
"We are getting closer to being able to use brain-imaging technology to help in the diagnosis and treatment of individuals with autism," said child psychiatrist Antonio Hardan, MD, who is the study's other senior author and an associate professor of psychiatry and behavioral sciences at Stanford. Hardan treats patients with autism at Packard Children's.
Brain scans are not likely to completely replace traditional methods of autism diagnosis, which rely on behavioral assessments, Hardan added, but they may eventually aid diagnosis in toddlers.
Autism occurs in about one in every 110 children. It is a disabling developmental disorder that impairs a child's language skills, social interactions and the ability to sense how one is perceived by others.
The study compared MRI data from 24 autistic children aged 8 to 18 with scan data from 24 age-matched, typically developing children. The data was collected at the University of Pittsburgh.
"We jumped at the results," Menon said. "Our approach allows us to examine the structure of the autistic brain in a more meaningful manner." The new findings expand scientists' basic knowledge of the core brain deficits in autism, he added.
The analysis method, called "multivariate searchlight classification," divided the brain with a three-dimensional grid, then examined one cube of the brain at a time, and identified regions in which the pattern of gray matter volume could be used to discriminate between children with autism and typically developing children.
Instead of comparing the sizes of individual brain structures, as prior studies have done, the new analysis generated something akin to a topographical map of the entire brain. The scientists essentially mapped the autistic brain's distinct cliffs and valleys, uncovering subtle differences in the physical organization of the gray matter.
Such analysis may be a more useful approach than previous tacks. Earlier studies, for instance, suggested that people with autism may have larger brains in toddlerhood or have a large defect in one brain structure. This study took a different approach and discovered several autism-associated differences in the Default Mode Network, a set of brain structures important for social communication and self-related thoughts. Specific structures that differed included the posterior cingulate cortex, the medial prefrontal cortex and the medial temporal lobes. These findings align well with recent theoretical and functional MRI studies of the autistic brain, which also point to differences in the Default Mode Network, Menon said.
Once Menon and his team had found where the differences in autistic brains were located, they were able to use their analysis to classify whether individual children in the study had autism. They used a subset of their data to "train" the mathematical algorithm, then ran the remaining brain scans through the algorithm to classify the children.
"We could discriminate between typically developing and autistic children with 92 percent accuracy on the basis of gray matter volume in the posterior cingulate cortex," said Lucina Uddin, PhD, the study's first author. Uddin is an instructor in psychiatry and behavioral sciences at Stanford.
In addition, the children with the most severe communication deficits, as measured on a standard behavioral scale for diagnosing individuals with autism, had the biggest brain structure differences. Severe impairments in social behavior and repetitive behavior also showed a trend toward association with more severe brain differences.
Menon and his team plan to repeat the study in younger children and to extend it to larger groups of subjects. If the results are upheld, the new method offers the possibility of several applications in autism diagnosis and treatment. For instance, brain scans might eventually help distinguish autism from other behavioral disorders such as attention deficit hyperactivity disorder, or might predict whether high-risk children, such as those with autistic siblings, will go on to develop autism themselves. Brain scanning might also be able to predict what type of deficits will occur in a child with a new autism diagnosis, allowing clinicians to target their treatments to a child's predicted deficits.
"Scans would likely be used alongside clinical expertise, giving that extra hint from the brain data," Uddin said.
When such integrated assessments are possible, the researchers hope they will allow clinicians to build detailed profiles of each patient. "We hope we'll eventually be able to tell parents, 'Your child will probably respond to this treatment, or your child is unlikely to respond to that treatment,'" Hardan said. "In my mind, that's the future."
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Other Stanford scientists who collaborated on the project were research scientist Srikanth Ryali, PhD; postdoctoral scholar Tianwen Chen, PhD; and research assistants Christina Young and Amirah Khouzam. Nancy Minshew, MD, from the University of Pittsburgh, also contributed to the project.
The research was supported by funding from the Singer Foundation, the Stanford Institute for Neuro-Innovation & Translational Neurosciences, the National Institute of Child Health & Human Development, the National Institute of Deafness & Other Communication Disorders, the National Institute of Mental Health, the National Institute of Neurological Disorders & Stroke and the National Science Foundation. Uddin was also supported by a postdoctoral fellowship from the Stanford University Autism Working Group. Additional information about the Department of Psychiatry and Behavioral Sciences, which also supported this work, is available at http://psychiatry.stanford.edu/
The Stanford University School of Medicine consistently ranks among the nation's top medical schools, integrating research, medical education, patient care and community service. For more news about the school, please visit http://mednews.stanford.edu. The medical school is part of Stanford Medicine, which includes Stanford Hospital & Clinics and Lucile Packard Children's Hospital. For information about all three, please visit http://stanfordmedicine.org/about/news.html.
Celebrating its 20th anniversary in 2011, Lucile Packard Children's Hospital is annually ranked as one of the nation's best pediatric hospitals by U.S. News & World Report, and is the only San Francisco Bay Area children's hospital with programs ranked in the U.S. News Top Ten. The 311-bed hospital is devoted to the care of children and expectant mothers, and provides pediatric and obstetric medical and surgical services in association with the Stanford University School of Medicine. Packard Children's offers patients locally, regionally and nationally a full range of health-care programs and services, from preventive and routine care to the diagnosis and treatment of serious illness and injury. For more information, visit www.lpch.org.
