Archive for August, 2015

Manuel Casanova, PhD, University of South Carolina

Manuel Casanova, PhD, University of South Carolina

Steven Chance, PhD, University of Oxford

Steven Chance, PhD, University of Oxford

Studies using brain tissues have revealed brain cells in the area called the cerebral cortex are organized in a specific way called “minicolumns”. In people with autism, this organization is different than those without autism. This has led scientists to ask what these columns do and how is it related to autism symptoms?

We asked two of the worlds leading researchers, Steven Chance of Oxford University and Manny Casanova at the University of South Carolina, who have studied the brains of people with autism, to weigh in on this topic. Specifically, we interviewed them to explain how the minicolumnar findings have impacted the field of autism research and led to discoveries that are important for families.


So, what is a cortical minicolumn and what do they do?

Steven Chance:  There are cells in the cerebral cortex that are arranged in columns. These ‘mini’-columns of cells are typically about one third the width of a human hair. In the typically developed brain, wider minicolumns seem to be associated with processing more individual features of incoming information.

Manny Casanova:  Minicolumns are a basic template that is used by neurons to figure out where neurons should go and where they should connect. They also help process the connections of different brain cells. Some people think of minicolumns as the microprocessor of a computer. Indeed, Vernon Mountcastle thoughtof minicolumns as the basic unit of information processing in the brain. More recent experiments have proven that these minicolumns help people to think and to act.

How are they different in people with autism?

Steven Chance: In ASD these minicolumns are between 5% and 10% wider than in those without autism. . This difference may not sound like much, but multiplied over hundreds of thousands of minicolumns throughout the brain it may contribute to a significant difference in brain organization. In addition to cognition and thinking like Manny Casanova pointed out, our lab has recently found these minicolumns in brain areas involved in basic sound and word processing, as well as in areas involved in complex social behavior.

Manny Casanova: Yes, minicolumns affect different aspects of behaviour. We have also found variability in the size of mini columns according to brain area. These changes are consistent with other neuropathological findings and indicate that the minicolumnopathy of autism is part of a process called cortical dysplasia. The presence of cortical dysplasia provides an explanation for intractable seizures and sensory abnormalities commonly observed in ASD. The pathology may be selective as to whom it affects as, on occasion, involved individuals have either a specific genetic or immunological profile.

What does this mean for people with autism?

Steven Chance: The differences in width and spacing of the minicolumns means that they may become too independent and overly focused on individual features in the environment.  This may explain the altered cognitive style or focus in many people with autism, and possibly explain the strengths of some people with autism in certain situations.

Manny Casanova: The findings help explain many of the symptoms observed in ASD. We are using the findings to provide new ways for screening for diagnosis, to provide for severity dependent outcome measures that do not rely on behavioral screening, and to introduce a possible therapeutic intervention.

Larger or smaller, what is it?

Steven Chance: The findings depend on the age of the individual. In other words, when the data from studies are compared while accounting for subject age, they suggest that minicolumns are wider in youth in autism but then become narrower in later life. This is interesting because it is consistent across the studies and reinforces tha autism as a developmental condition which changes across the lifespan. It also makes sense in the light of other MRI studies which have shown larger brains in ASD in early life, followed by a loss of this enlargement later on.

Manny Casanova: It may be that the age-related changes in the minicolumnopathy of autism may constitute an adaptive response meant to correct early changes in the cortex; or or it could be the beginning of a neurodegenerative process whose manifestation may appear later on in life.  We don’t know, we need more research using brains of people with autism at all ages and abilities.

These questions can only be answered with more brain tissue from individuals across the lifespan. You can help with the discoveries. Register to donate your amazing brain when you don’t need it anymore by going to www.takesbrains.org.


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ASF accelerator grant awardee, Jennifer Foss-Feig, PhD

2015 ASF accelerator grant awardee, Jennifer Foss-Feig, PhD

“If you’ve met one person with autism, then you’ve met one person with autism.” This adage has become often-repeated in the autism community. It speaks to the uniqueness of each individual with autism and to the fact that no individual can be captured or fully described by his or her diagnosis. At the same time, it reflects what has become one of the greatest challenges facing autism science: variability in symptoms across people diagnosed with autism, otherwise known as heterogeneity. No one feature is reliably seen in every individual with autism, and any research sample can reflect only a subset of the diverse individuals who fall along the autism spectrum. In the latest diagnostic manual of the APA, a new, broader diagnostic category – Autism Spectrum Disorder (ASD) – replaced the categories we had all become familiar with: Autistic Disorder, Asperger’s, and PDD-NOS. For my colleagues at the Yale Child Study Center and I, the new DSM-5 umbrella “ASD” category opened the door for developing novel ways of conceptualizing and clustering heterogeneity among ASD features.


In a commentary published in the Journal of Autism and Developmental Disorders1 this month, we suggest a new way to consider autism symptoms. Borrowing concepts from the schizophrenia literature, we propose a new framework within which ASD-related features can be categorized. We introduce the idea of positive, negative, and cognitive feature clusters as a novel way to conceptualize ASD symptoms. Positive features include behaviors not present in typical development, but present in ASD, such as circumscribed interests or stereotyped motor movements. The negative feature dimension captures behaviors that are present in typical development, but delayed, deficient, or absent in some individuals with ASD, such as eye contact, social engagement, and spoken language. Finally, the cognitive dimension reflects patterns of thinking, behavior, and relating that are cognitively-driven and common among individuals with ASD, such as rigidity of thinking and difficulty with switching between tasks. These categories cut across social-communication and repetitive behavior domains that are currently the primary means of clustering symptoms in the DSM-5, which translates to how ASD is thought of and its features are grouped in both clinic and research settings. It may be easier to conceptualize this by looking at the table below.


DSM-5 Social Communication


DSM-5 Restricted/Repetitive Behaviors
Positive Features Intrusive social initiatives; Exaggerated prosody or intonation of speech; Pronoun reversal Echolalia and stereotyped speech; Repetitive use of objects;

Repetitive hand mannerisms

Negative Features Difficulty with conversation; Lack of pointing; Reduced eye contact and range of facial expressions Non-functional play with toys; Narrowed range of interests;

Lack of imagination

Cognitive Features Difficulties with theory of mind and taking another’s perspective; Difficulty with non-literal language Insistence on sameness;

Rigid adherence to routines;

Black-and-white thinking


In this way, we offer new ways to conceptualize and organize hallmark symptoms of ASD. In addition, this way of thinking offers an opportunity to describe specific characteristics with new precision. For example, instead of indicating a child has “atypical facial expressions,” the new dimensions would allow separating of children who have exaggerated affect from others who show limited range of facial expressions.


In schizophrenia, the notion of positive, negative, and cognitive feature clusters has been quite useful to both clinical and research communities. In the clinic, assessing and labeling symptoms along these dimensions has been useful for deciding which medications to prescribe, predicting which patients will continue to struggle versus which will have quick remittance of symptoms, and identifying individuals in a “prodromal” phase before the onset of more acute symptoms. In the lab, this framework has been useful for clustering symptom dimensions in ways that correspond with experimental task performance and underlying brain differences. In other words, positive, negative, and cognitive symptom dimensions help researchers understand which underlying brain differences or cognitive and social processes are most affected in patients showing more positive versus more negative symptoms. This, in turn, provides clues to genetic underpinnings of different symptoms as well as new leads from which to develop treatments.


In the future, with further research, we hope to use what has been learned in schizophrenia and apply it to autism. It is our hope that the dimensions we propose offer new ways to capture and organize the heterogeneity that makes each individual with ASD unique in a way that makes us better able to talk about what we see, provide good clinical care, and solve the remaining puzzles of autism.


1 Foss-Feig, J. H., McPartland, J. C., Anticevic, A., & Wolf, J. (2015). Re-conceptualizing ASD Within a Dimensional Framework: Positive, Negative, and Cognitive Feature Clusters. Journal of Autism and Developmental Disorders, 1-10. http://link.springer.com/article/10.1007/s10803-015-2539-x



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At a time when 1 in 68 children is diagnosed with autism, early identification, diagnosis and treatment is crucial to give children the best opportunity to reach their full potential. The ambiguity of the statement offered by the US Preventative Services Task Force (USPSTF) on autism screening is troubling and unfortunately, may be easily misinterpreted. While the task force does not explicitly recommend against screening for autism, they state there is insufficient evidence to support autism-specific screening in clinical settings. Instead, they have called for more research in this area.

As a result, the task force has failed to fully endorse screening despite an abundance of research that demonstrates it is effective in a variety of settings1-3, leads to earlier identification of autism4, and that this earlier identification provides opportunities for early intervention which improves the lives of children with autism5. Research has demonstrated that formal screening is more effective than relying on clinician judgement alone1,6. This is especially important in reducing racial and ethnic disparities in access to care7,8 Moreover, screening is quick, affordable and has no substantial risk. We intend to review the USPSTF report and its methodology to understand why it differs from other evidence-based recommendations from the American Academy of Pediatrics and from experts in the field of autism spectrum disorders. Every child deserves an early, accurate diagnosis and we are hopeful that after the review period the USPSTF reconsider their conclusions.  You can read more about the recommendations and response here.

There are a number of world renowned autism researchers who agree with this position.  They include:

The High Risk Baby Siblings Research Consortium (https://www.autismspeaks.org/science/science-news/bsrc-response-uspstf-call-more-research-universal-autism-screening)

Jill Harris, Children’s Specialized Hospital of NJ

Bryan King, Seattle Childrens Hospital

Ami Klin, Emory University

David Mandell, University of Pennsylvania

James McPartland, Yale University

Diana Robins, Drexel University

Celine Saulnier, Emory University

Amy Wetherby, Florida State University

  1. Robins DL. Screening for autism spectrum disorders in primary care settings. Autism : the international journal of research and practice. 2008;12(5):537-556.
  2. Miller JS, Gabrielsen T, Villalobos M, et al. The each child study: systematic screening for autism spectrum disorders in a pediatric setting. Pediatrics. 2011;127(5):866-871.
  3. Robins DL, Casagrande K, Barton M, Chen CM, Dumont-Mathieu T, Fein D. Validation of the modified checklist for Autism in toddlers, revised with follow-up (M-CHAT-R/F). Pediatrics. 2014;133(1):37-45.
  4. Herlihy LE, Brooks B, Dumont-Mathieu T, et al. Standardized screening facilitates timely diagnosis of autism spectrum disorders in a diverse sample of low-risk toddlers. Journal of developmental and behavioral pediatrics : JDBP. 2014;35(2):85-92.
  5. Pierce K, Carter C, Weinfeld M, et al. Detecting, studying, and treating autism early: the one-year well-baby check-up approach. The Journal of pediatrics. 2011;159(3):458-465 e451-456.
  6. Wetherby AM, Brosnan-Maddox S, Peace V, Newton L. Validation of the Infant-Toddler Checklist as a broadband screener for autism spectrum disorders from 9 to 24 months of age. Autism : the international journal of research and practice. 2008;12(5):487-511.
  7. Khowaja MK, Hazzard AP, Robins DL. Sociodemographic Barriers to Early Detection of Autism: Screening and Evaluation Using the M-CHAT, M-CHAT-R, and Follow-Up. Journal of autism and developmental disorders. 2015;45(6):1797-1808.
  8. Daniels AM, Halladay AK, Shih A, Elder LM, Dawson G. Approaches to enhancing the early detection of autism spectrum disorders: a systematic review of the literature. Journal of the American Academy of Child and Adolescent Psychiatry. 2014;53(2):141-152.

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