Mapping the Mind: a conversation between LeDoux and Kandel Eric Kandel

22 08 2014

Here is a fascinating interview with Kandel, a Nobel laureate and professor of biochemistry and biophysics at Columbia University. In this conversation between LeDoux and Kandel you can learn how do our brains remember: http://vimeo.com/103749284

Enjoy!

 





GxExAge

23 05 2014

Here are fascinating findings regarding the Genes – Enviroment interaction and mental illness onset:

http://www.nimh.nih.gov/news/science-news/2014/genes-impact-suspect-cortex-areas-more-as-youth-mature.shtml





Are Neuropsychiatric Disorders caused by Autoimmune Sydndroms??

15 05 2014

Did you know that recent high quality, cutting edge research indicates that neuropsychiatric disorders may be caused by definable autoimmune syndromes?  The theoretical implications of this line of research may significantly impact the way we understand, diagnose and treat persons with neuropsychiatric disorders!

Here are two reviews in this issue that you may find interesting:

The Emerging Link Between Autoimmune Disorders and Neuropsychiatric Disease

Neuroinflammation and psychiatric illness

 

 

 





What we know, and mostly don’t know about ASD in 2014

28 03 2014

Autism Awareness: April 2014

By 

Autism Awareness Month arrives this year with a package of new, important research findings. Below I describe a few of these. The field is moving so rapidly that, by the end of April, there will likely be yet a new crop of findings—so this is, at best, a progress report for the beginning of Autism Awareness Month.

Today the Centers for Disease Control and Prevention (CDC) released new numbers on the prevalence of autism, based on the most recent results from their long running Autism and Developmental Disabilities Monitoring  (ADDM) network.  Looking at administrative data on 8-year-olds from 11 sites across the country, ADDM reported a prevalence of autism of 1 in 68 children in 2010 (based on children born in 2002), up from 1 in 88 in 2008 (based on children born in 2000).  There was considerable variation across the 11 sites: from 1 in 45 in New Jersey to 1 in 175 in Alabama. As in previous surveys, boys were almost 5 times more likely to have an autism label. The prevalence in boys was 1 in 42; in girls, 1 in 189.

One of the best things about the ADDM network is that it has provided surveillance using similar methods for over a decade. The prevalence of autism as estimated from administrative records has increased:  by 125 percent since 2002 and by 29 percent just between 2008 and 2010.  How much of this increase is “more detected” versus “more affected”? Is this increase a mark of better care, with more cases identified and treated, or is this a reflection of a continually growing public health care emergency due to more children affected? ADDM cannot answer these questions, but it does point to the need for a population-wide study, as currently planned by CDC and Autism Speaks in South Carolina. A previous total population study of all 7- to12-year-olds in a town in South Korea (more than 55,000 children) used standardized diagnostic instruments for children who screened positive and reported a prevalence of 1 in 38 children. Could that figure, which is in the range of the ADDM estimate of 1 In 45 for New Jersey, serve as a reasonable estimate for the actual prevalence once everyone with autism is detected? Perhaps the ADDM numbers will continue to rise, indicating better detection as awareness of the signs and symptoms increase.

Whatever the meaning of the new ADDM report, there is little doubt that more children and more adults on the autism spectrum will require more services. Ganz estimated the lifetime economic cost of autism to be $3.2 million per individual, back in 2006 when the prevalence was thought to be closer to 1 in 150.1 A new economic analysis looks at the cost, including education and indirect costs, based on three national data sets.2 The additional cost of having a child with autism was $17,081 per year in 2011. Only 18 percent of these costs were related to health care; half were attributed to school costs. Assuming 673,000 children ages 3 to 17 with a diagnosis of autism spectrum disorder, the total societal cost would be roughly $11.5 billion per year. Of course, with new estimates from the CDC about the increase in prevalence, these costs may need to be adjusted upward.

On the brain research front, a new report in the New England Journal of Medicine describes changes seen in the architecture of post-mortem brains in 10 of 11 children who had an autism diagnosis.3 Similar changes were found in  only 1 of 11 unaffected children. Dr. Eric Courchesne and his colleagues at the University of California, San Diego and Dr. Ed Lein and colleagues at the Allen Institute of Brain Science found patches of abnormal anatomy in parts of the brain associated with social and communication functions. Given that the pattern of cell layers in the cortex is laid down prenatally, these findings, if replicated, suggest that brain changes in autism are likely to have originated before birth, although the disorder is usually diagnosed behaviorally after age 4 years.

In 2014, the mystery of autism remains largely unsolved. We describe autism as a neurodevelopmental disorder, but even with the new report mentioned above, we do not know precisely how to define what the brain disorder is or when it occurs. We realize that as many as 30 percent of children with autism have spontaneous genetic mutations, but these large genetic changes have not yet been shown to cause the disorder, since other children with some of the same changes don’t have autism. We have treatments for autistic symptoms, helping many children to enter regular classrooms and ultimately function fully in society. But these behavioral treatments are expensive and intensive and often not available to children in need. Medical treatments have lagged behind.

All of this reminds us that for both children and adults with autism we need more science as well as more services. Indeed, the best way to better services will be through better science. As we understand what happens in the developing brain that renders a child unable to communicate or unable to engage the social world, we will be better able to provide earlier detection and better interventions. As we identify the many forms of autism, some more genetic, some more environmental, we can expect better tools for prevention and treatment. And as we understand better the evolution of autism in adults, we should be able to provide better care and offer better outcomes. Autism awareness reminds us of the vital importance of committing to both science and service for an increasing number of our fellow citizens.

References

1 Ganz ML. The lifetime distribution of the incremental societal costs of autism.  Arch Pediatr Adolesc Med. 2007 Apr;161(4):343-9.

2 Lavelle TA et al. Economic burden of childhood autism spectrum disorders.  Pediatrics. 2014 Mar;133(3):e520-9. doi: 10.1542/peds.2013-0763. Epub 2014 Feb 10.

3 Stoner R et al. Patches of disorganization in the neocortex of children with autism. N Engl J Med. 2014;370:1209-19. DOI:10.1056/NEJMoa1307491.





THE UNCONSCIOUS: A bridge between psychoanalysis and cognitive science – Researchers and clinicians in dialogue

23 03 2014

This year the Joseph Sandler Research Conference was devoted to a central topic of the interdisciplinary dialogue between contemporary psychoanalysis and other scientific disciplines: the unconscious. In order to see the lectures of the leading researchers and practitioners that participated in this interesting conference click HERE.

I would like to thanks Ms. Irith Raveh, Founder and Chairperson at Israel Forum of Neuropsychoanalysis, that sent me the links to these great lectures.





Brain Awareness Month – What do we know and don’t know about the brain

12 03 2014

Brain Awareness

By Thomas Insel

This is the time of March Madness, Daylight Savings Time, and what Emily Dickinson famously called the “month of expectation.” March is also Brain Awareness Month, an annual celebration with school visits, community lectures, and lab tours to introduce the public to the mind-blowing world of neuroscience. A list of Brain Awareness events can be found at http://www.dana.org/brainweek/ , where you will also find that March 10 -16 is the peak for related public events around the world.

Since NIMH began focusing on mental disorders as brain disorders nearly two decades ago, educating people about the brain has been a priority for us. We often say that with the powerful tools of neuroscience, we can now use the brain to understand the mind, fulfilling the original vision that Freud had for a scientific psychology. But we have to remain humble about our understanding of the brain, because even our most powerful tools remain pretty blunt instruments for decoding the brain. In fact, we still do not know how to decipher the basic language of how the brain works.

A few numbers can help to define the challenge. The human brain is thought to have close to 86 billion neurons, each making on average about 10,000 connections. In contrast to most animals, our brains are largely made up of a heavily folded cortex, accounting for 80 percent of brain mass and about 100,000 miles of axons that provide the highways between neurons.1

How many different kinds of neurons are there in the brain? We really don’t know.  Unlike the heart or kidney, which have a small, defined set of cell types, we still do not have a taxonomy of neurons, and neuroscientists still argue whether specific types of neurons are unique to humans. But there is no disputing that neurons are only about 10 percent of the cells in the human brain. Most of our brain cells are glial cells, once thought to be mere support cells, but now understood as having a critical role in brain function. Glial cells in the human brain are markedly different from glial cells in other brains, suggesting that they may be important in the evolution of brain function. As one hint to their function, astrocytes, which are one form of glial cell, have been reported recently to “eat” synapses in the brain, providing a critical new mechanism for brain plasticity.2

How does the brain work? Again, we really don’t know. We have a very detailed understanding of how the heart pumps and the kidney filters, but how the brain encodes, stores, and retrieves information is still largely a mystery. We have known for over a century that most of the cortex is organized horizontally into six precise layers, and much of the cortex has vertical mini-columns, but how this matrix of horizontal and vertical structures computes information is not really clear.

Neuroscientists talk a lot about brain circuits. In fact, the word “circuit” is probably misleading. We do not know where most circuits begin and end. And unlike an electrical circuit, brain connections are heavily reciprocal and recursive, so that a direction of information flow can be inferred but sometimes not proven. We believe there are “emergent properties” of the brain that convert electrical signals into memories or dreams, but how this happens is still a mystery. Recent studies have shown that diffuse waves of synchronization across the brain may be critical for attention or learning, but we are just learning about these slow waves of activity, and whether they occur at the “speed of thought” is still debated.3

Of course, the spectacular images from MRI and PET scans have already given us maps for perception and fear and language and many other functions. As scanners have improved their resolution from 1.5T (tesla) to 3T to recent 7T magnets, and the protocols and analytic approaches have evolved, we now can map the cortical real estate associated with complex tasks like decision-making and face recognition. But these approaches, even with the best current technology, are still a 30,000-foot view of the action. Jay Giedd here at NIMH estimates that each gray matter voxel—the individual 3D pixels of 1 cubic mm that make up the scan—contains about 90,000 neurons, 400 meters of dendrites, and 4.5 million synapses. Each scan has over 650,000 voxels. And the actual measure is not neural activity per se but local blood flow, which changes slowly relative to the speed of thought.

In a sense, functional MRI (fMRI) is providing an image of something like the power grid of a city. fMRI slowly maps where and when different parts of the brain wake up, based on blood oxygen metabolism. By contrast, the street map of the brain is being mapped by the Human Connectome Project. Supported by the NIH Blueprint for Neuroscience Research , over 100 neuroscientists at ten sites in the United States and Europe are building something like a Google map for the human brain.  Scientists at Massachusetts General Hospital have created new MRI scanners with greatly enhanced resolution for looking at the geometric structure of the human brain.4 One remarkable claim from that work (still controversial) is that the fiber connections which heretofore looked like a bowl of spaghetti might actually have a relatively simple grid structure, allowing comparisons of connectomes between people. This kind of comparison is already underway at Washington University and the University of Minnesota where the Human Connectome Project  is obtaining the wiring diagrams of 1200 healthy adults, including 300 twin pairs. Thus far, data from the first 226 volunteers have been released on the Connectome website, with 10 gigabytes of data available for each subject. That’s right, this project is releasing the data as it becomes available to scientists everywhere—over 700 users are already mining the Connectome data to see how a Google map of the human brain might answer their questions.

Whether March for you means basketball, changing clocks, or expectations, I hope you will check out some of the Brain Awareness events. Brain science has become one of the most exciting frontiers of science. When I was a kid, the scientific frontier was “outer space.” Today it seems to be “inner space” that fascinates the boldest and brightest young minds (or should we say young brains). We are still at the beginning of what could be an era of brain exploration, with great promise for understanding more about how each of us thinks and dreams and loves, but perhaps even greater promise for helping people with mental disorders.

References

1 Lent R, Azevedo FA, Andrade-Moraes CH, Pinto AV. How many neurons do you have? Some dogmas of quantitative neuroscience under revision.  Eur J Neurosci. 2012 Jan;35(1):1-9. doi: 10.1111/j.1460-9568.2011.07923.x.

2 Chung WS et al. Astrocytes mediate synapse elimination through MEGF10 and MERTK pathways . Nature. 2013 Dec 19;504(7480):394-400. doi: 10.1038/nature12776. Epub 2013 Nov 24.

3 Salazar RF, Dotson NM, Bressler SL, Gray CM. Content-specific fronto-parietal synchronization during visual working memory Science 2012 Nov 23;338(6110):109-100. doi: 10.1126/science.1224000.

4 Wedeen VJ et al. The geometric structure of the brain fiber pathways .Science. 2012 Mar 30;335(6076):1628-34. doi: 10.1126/science. 1215280.





How the anatomical structure of the brain impacts its functional networks?

20 01 2014

Today I want to offer an interesting paper by Andreas et al (2013) that sought to  determine how the anatomical structure of the brain impacts its functional networks. I think that their interesting findings (see abstract below) may contribute to a better understanding of brain functioning in healthy people and people with neurodegenerative disorders such as Alzheimer’s disease and psychiatric disorders such as schizophrenia and bipolar disorder. Enjoy!

Andreas Horn, et al., “The structural–functional connectome and the default mode network of the human brain,” NeuroImage, 2013; DOI: 10.1016/j.neuroimage.2013.09.069

Abstract

An emerging field of human brain imaging deals with the characterization of the connectome, a comprehensive global description of structural and functional connectivity within the human brain. However, the question of how functional and structural connectivity are related has not been fully answered yet. Here, we used different methods to estimate the connectivity between each voxel of the cerebral cortex based on functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data in order to obtain observer-independent functional–structural connectomes of the human brain. Probabilistic fiber-tracking and a novel global fiber-tracking technique were used to measure structural connectivity whereas for functional connectivity, full and partial correlations between each voxel pair’s fMRI-timecourses were calculated. For every voxel, two vectors consisting of functional and structural connectivity estimates to all other voxels in the cortex were correlated with each other. In this way, voxels structurally and functionally connected to similar regions within the rest of the brain could be identified. Areas forming parts of the ‘default mode network’ (DMN) showed the highest agreement of structure–function connectivity. Bilateral precuneal and inferior parietal regions were found using all applied techniques, whereas the global tracking algorithm additionally revealed bilateral medial prefrontal cortices and early visual areas. There were no significant differences between the results obtained from full and partial correlations. Our data suggests that the DMN is the functional brain network, which uses the most direct structural connections. Thus, the anatomical profile of the brain seems to shape its functional repertoire and the computation of the whole-brain functional–structural connectome appears to be a valuable method to characterize global brain connectivity within and between populations.