Neuroskeptic - Is It Time To Redraw the Map of the Brain?

A new study published online ahead of print publication in Brain: A Journal of Neurology suggests that our current maps of human brain-lesion deficits are not accurate and need to be reconsidered. Neuroskeptic offered a nice overview of the study, accessible to non-PhD readers. The article is also open access and available online.

I have included the summary from Neuroskeptic and the beginning of the full article - follow the links below to see the original article.

Is It Time To Redraw the Map of the Brain?

By Neuroskeptic | July 1, 2014 

A provocative and important paper just out claims to have identified a pervasive flaw in many attempts to map the function of the human brain.

University College London (UCL) neuroscientists Yee-Haur Mah and colleagues say that in the light of their findings, “current inferences about human brain function and deficits based on lesion mapping must be re-evaluated.”

Lesion mapping is a fundamental tool of modern neuroscience. By observing the particular symptoms (deficits) people develop after suffering damage (lesions) to particular parts of the brain, we can work out what functions those various parts perform. If someone loses their hippocampus, say, and gets amnesia, you might infer that the function of the hippocampus is related to memory – as indeed it is.

However, there’s a problem with this approach, Mah et al say. Conventional lesion mapping treats each point in the brain (voxel) individually, as a possible correlate of a given deficit. This is called a mass univariate approach.

The problem is that the shape and location of brain lesions is not random – some areas are more likely to be affected than others, and the extent of the lesions varies in different places.

What this means is that the presence of damage in a certain voxel may be correlated with damage in other voxels. So damage in a voxel might be correlated with a given deficit, even though it has no role in causing the deficit, just because it tends to be damaged alongside another voxel that really is involved.

Mah et al call this problem ‘parasitic association’. In a large sample of diffusion-weighted MRI scans from 581 stroke patients, the authors show that the co-occurrence of damage across voxels leads to systematic, large biases in mass univariate deficit mapping.

The biases follow a complex geometry throughout the brain: as this lovely (but scary) image shows -

This shows the direction and magnitude of the error that would afflict a standard attempt to localize a hypothetical deficit that was truly associated with points throughout the brain. In some areas, the bias ‘points’ forward, so the deficit would be wrongly mapping as being further forward than it really was. In other places, it points in other direction.

The mean size of the expected error is 1.5 cm, but with a high degree of variability, so it is much worse in some areas.

Worse yet, Mah et al say that in cases where the same deficit can be caused by damage to two, non-adjacent areas, univariate lesion mapping might fail to pinpoint either of them. Instead, it could wrongly implicate a nearby, unrelated area.

The authors conclude that the only way to avoid this problem is by using multivariate statistics to explicitly model voxel interrelationships, e.g. a machine learning approach. This will require large datasets, but they caution that merely having a big sample, without multivariate statistics, would achieve nothing. They conclude on a somewhat downbeat note:

It is outside the scope if this study to determine the optimal multivariate approach: our focus here is on the evidence of the misleading picture the mass-univariate approach has created, and the need to review it wholesale. Taken together, our work demonstrates a way forward to place the study of focal brain lesions on a robust theoretical footing.

I’m not sure the outlook is quite so bleak. It’s a very nice paper, however, Mah et al’s dataset is purely based on stroke patients. Yet there are many other sources of brain lesions that are used for lesion mapping: tumours, infections, and head injuries to name a few.

These kinds of lesions probably throw up parasitic associations as well, however, they might be very different from the kind seen in strokes. This is because strokes, unlike other kinds of lesions, are always centered on blood vessels.

Mah et al note that the bias map they found is clustered around the major cerebral arteries and veins, but the obvious conclusion to draw from this is that it’s only applicable to strokes.

Whether other kinds of lesions produce substantial biases remains to be established. Until we know that, we shouldn’t be rushing to redraw any maps just yet.

Full Citation:
Mah, Y., Husain, M., Rees, G., & Nachev, P. (2014, Jun 28). Human brain lesion-deficit inference remapped. Brain; DOI: 10.1093/brain/awu164

Included here is the abstract and the introduction - follow the link in the title to download the PDF for yourself.

Human brain lesion-deficit inference remapped

Yee-Haur Mah, Masud Husain, Geraint Rees, and Parashkev Nachev

Author Affiliations

1. Institute of Neurology, UCL, London, WC1N 3BG, UK
2. Department of Clinical Neurology, University of Oxford, Oxford OX3 9DU, UK
3. Institute of Cognitive Neuroscience, UCL, London WC1N 3AR, UK
4. Wellcome Trust Centre for Neuroimaging, UCL, London WC1N 3BG, UK

Summary

Our knowledge of the anatomical organization of the human brain in health and disease draws heavily on the study of patients with focal brain lesions. Historically the first method of mapping brain function, it is still potentially the most powerful, establishing the necessity of any putative neural substrate for a given function or deficit. Great inferential power, however, carries a crucial vulnerability: without stronger alternatives any consistent error cannot be easily detected. A hitherto unexamined source of such error is the structure of the high-dimensional distribution of patterns of focal damage, especially in ischaemic injury—the commonest aetiology in lesion-deficit studies—where the anatomy is naturally shaped by the architecture of the vascular tree. This distribution is so complex that analysis of lesion data sets of conventional size cannot illuminate its structure, leaving us in the dark about the presence or absence of such error. To examine this crucial question we assembled the largest known set of focal brain lesions (n = 581), derived from unselected patients with acute ischaemic injury (mean age = 62.3 years, standard deviation = 17.8, male:female ratio = 0.547), visualized with diffusion-weighted magnetic resonance imaging, and processed with validated automated lesion segmentation routines. High-dimensional analysis of this data revealed a hidden bias within the multivariate patterns of damage that will consistently distort lesion-deficit maps, displacing inferred critical regions from their true locations, in a manner opaque to replication. Quantifying the size of this mislocalization demonstrates that past lesion-deficit relationships estimated with conventional inferential methodology are likely to be significantly displaced, by a magnitude dependent on the unknown underlying lesion-deficit relationship itself. Past studies therefore cannot be retrospectively corrected, except by new knowledge that would render them redundant. Positively, we show that novel machine learning techniques employing high-dimensional inference can nonetheless accurately converge on the true locus. We conclude that current inferences about human brain function and deficits based on lesion mapping must be re-evaluated with methodology that adequately captures the high-dimensional structure of lesion data.

Introduction

The study of patients with focal brain damage first revealed that the human brain has a functionally specialized architecture (Broca, 1861; Wernicke, 1874). Over the past century and a half such studies have been critical to identifying the distinctive neural substrates of language (Broca, 1861; Wernicke, 1874), memory (Scoville and Milner, 1957), emotion (Adolphs et al., 1995; Calder et al., 2000), perception (Goodale and Milner, 1992), decision-making (Bechara et al., 1994), attention (Egly et al., 1994; Mort et al., 2003), and intelligence (Gla¨ scher et al., 2009), casting light on the anatomical basis of deficits resulting from dysfunction of the brain. Though functional imaging has revolutionized the field of brain function mapping in the last 20 years, the necessity of a brain region for a putative function—arguably the strongest test—can only be established by showing a deficit when the function of the region is disrupted. Inactivating brain areas experimentally cannot easily be done in humans; the special cases of transcranial magnetic and direct current stimulation, though potentially powerful, are restricted temporally to days and anatomically to accessible regions of cortex.

The only comprehensive means of establishing functional necessity thus remains the study of patients with naturally occurring focal brain lesions (Rorden and Karnath, 2004). Though single patients may sometimes be suggestive, robust, population-level inferences about lesion-deficit relationships require aggregation of data from many patients (Karnath et al., 2004). Analogously to functional brain imaging, a statistical test comparing groups of patients with and without a deficit is iteratively applied point-bypoint to brain lesion images parcellated into many volume units (voxels) (Bates et al., 2003; Karnath et al., 2004). Voxels that cross the significance threshold are then taken to identify the functionally critical brain areas whose damage leads to the deficit.

Crucially, this ‘mass-univariate’ approach assumes that the resultant structure-deficit localization is not distorted by co-incidental damage of other, non-critical loci in each patient: in other words, that damage to each voxel is independent of damage to any other. This cannot be assumed in the human brain. Collaterally damaged but functionally irrelevant voxels might be associated with voxels critical for a deficit through an idiosyncrasy of the pathological process—the distribution of the vascular tree, for example—while having no relation to the function of interest. Such associations would lead to a distortion of the inferred anatomical locus.

Importantly, these ‘parasitic’ voxel-voxel associations can be detected only by examining the multivariate pattern of damage across the entire brain, and across the entire group. Studying large numbers of patients with the standard approach simply exacerbates the problem, because such consistent error will also consistently displace inferred critical brain regions from their true locations. Equally, replicating a study with the same number of patients will replicate the error too: observing the same result across different research groups and epochs offers no reassurance. Instead, the pattern of damage must be captured by a high dimensional multivariate distribution that describes how the presence or absence of damage at every voxel within each brain image is related to damage to all other voxels. The presence of ‘parasitic’ voxel-voxel associations would then manifest as a
hidden bias within the multivariate distribution, a complex correlation between individual patterns of damage apparent only in a high-dimensional space and opaque to inspection with simple univariate tools.

To illustrate the problem, consider the 2D synthetic example in Fig. 1, where damage to any part of area ‘A’ alone may disrupt a putative function of interest, but ‘B’ plays no role in this function of interest. If the lesions used to map the functional dependence on A follow a stereotyped pattern where damage to any part of A is systematically associated with collateral damage to the non-critical area B, both areas might appear to be significantly associated even if B is irrelevant to the function of interest. Crucially, if the pattern of the lesions within each patient is such (for reasons to do with factors unconnected to function) that the spatial variability of damage to B is less than to A, B will not only be erroneously determined to be critical but will have a higher significance value for such an association than A. The apparent locus of a lesion function deficit will therefore be displaced from A (the true locus) to B. Thus a hidden bias in the pattern of damage—hidden because it is apparent only when examining the pattern as a whole, in a multivariate way—distorts the spatial inference. 

Whether or not such a hidden bias exists has not been previously investigated. Here we analyse the largest reported series of focal brain lesions (n = 581) to show that it does exist, and that it compels a revision of previous lesion-deficit relationships within a wholly different inferential framework.

Mapping the Brain - Christof Koch and John Donoghue

This is a nice (but short) discussion on progress being made in mapping the brain in order to understand neurological trauma.

Mapping the Brain

Trailblazers in neuroscience, Dr. Christof Koch and Dr. John Donoghue, reveal mind-blowing insights on how the brain turns thought into voluntary behaviors and how that knowledge is empowering victims of neurological trauma with regained physical abilities.


Mapping the Brain from National Geographic Live on FORA.tv
John Donoghue is Henry Merritt Wriston Professor in the Department of Neuroscience at Brown University, Director of the Brown Institute for Brain Science, VA Senior Career Research Scientist, and Director of the Center of Excellence for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI. From 1991 to 2006, Dr. Donoghue was the founding Chairman of the Department of Neuroscience at Brown. For more than 20 years, Dr. Donoghue has conducted research on brain computer interfaces and his laboratory is internationally recognized as a leader in this field. Dr. Donoghue has published over 80 scientific articles in leading journals such as Nature and Science, and has served on advisory panels for the National Institutes of Health, the National Science Foundation and NASA. Dr. Donoghue has won awards for his work from Discover, Popular Mechanics, and Reader's Digest magazines. In 2007, he won the K. J. Zulch Prize, Germany's highest honor for neurological research. Dr. Donoghue is a fellow in the American Institute for Medical and Biomedical Engineering and the American Association for the Advancement of Science as well as a member of the board of directors for the MIT Media Lab. Dr. Donoghue received an A.B. from Boston University in 1971, an M.S. in anatomy from the University of Vermont in 1976, and a Ph.D. in neuroscience from Brown University in 1979.

Christof Koch joined the Allen Institute as Chief Scientific Officer in 2011. For the past 25 years, Koch has served on the faculty at the California Institute of Technology (Caltech), from his initial appointment as Assistant Professor, Division of Biology and Division of Engineering and Applied Sciences in 1986, to his most recent position as Lois and Victor Troendle Professor of Cognitive & Behavioral Biology. Previously, he spent four years as a postdoctoral fellow in the Artificial Intelligence Laboratory and the Brain and Cognitive Sciences Department at the Massachusetts Institute of Technology. He received his baccalaureate from the Lycée Descartes in Rabat, Morocco, his M.S. in physics from the University of Tübingen in Germany and his Ph.D. from the Max-Planck-Institut für Biologische Kybernetik, Tübingen. Koch has published extensively, and his writings and interests integrate theoretical, computational and experimental neuroscience. Stemming in part from a long-standing collaboration with the late Nobel Laureate Francis Crick, Koch authored the book The Quest for Consciousness: A Neurobiological Approach. He has also authored the technical books Biophysics of Computation: Information Processing in Single Neurons and Methods in Neuronal Modeling: From Ions to Networks, and served as editor for several books on neural modeling and information processing. Koch's research addresses scientific questions using a widely multidisciplinary approach. His research interests include elucidating the biophysical mechanisms underlying neural computation, understanding the mechanisms and purpose of visual attention, and uncovering the neural basis of consciousness and the subjective mind. Koch maintains a part-time appointment and laboratory at Caltech.

Map Of The Developing Human Brain Shows Where Problems Begin (NPR)

Our ability to image the brain is becoming quite extraordinary. How we use those images and the agenda of which they are a piece are, however, somewhat concerning. It's wonderful to see how the brain can go wrong in development, but it's FAR more important to understand WHY the brain goes wrong - and the single greatest factor, far more important than genetics, is adverse childhood experience, especially neglect, abuse, and incest.

If we could put an end to those three experiences, the rates of mental illness would be a fraction of the current numbers.

Map Of The Developing Human Brain Shows Where Problems Begin

by Jon Hamilton
April 02, 2014
3 min 53 sec

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Images of the developing fetal brain show connections among brain regions. Allen Institute for Brain Science
A high-resolution map of the human brain in utero is providing hints about the origins of brain disorders including schizophrenia and autism.

The map shows where genes are turned on and off throughout the entire brain at about the midpoint of pregnancy, a time when critical structures are taking shape, researchers reported Wednesday in the journal Nature.

"It's a pretty big leap," says Ed Lein, an investigator at the Allen Institute for Brain Science in Seattle who played a central role in creating the map. "Basically, there was no information of this sort prior to this project."

Having a map like this is important because many psychiatric and behavioral problems appear to begin before birth, "even though they may not manifest until teenage years or even the early 20s," says Dr. Thomas Insel, director of the National Institutes of Mental Health.

The human brain is often called the most complex object in the universe. Yet its basic architecture is created in just nine months, when it grows from a single cell to more than 80 billion cells organized in a way that will eventually let us think and feel and remember.

"We're talking about a remarkable process," a process controlled by our genes, Lein says. So he and a large team of researchers decided to use genetic techniques to create a map that would help reveal this process. Funding came from the 2009 federal stimulus package. The project is part of the BrainSpan Atlas of the Developing Brain.

The massive effort required tens of thousands of brain tissue samples so small that they had to be cut out with a laser. Researchers used brain tissue from aborted fetuses, which the Obama administration has authorized over the objections of abortion opponents.

Researchers tested each sample to see which genes were turned on and off in each tiny bit of brain. This helped the team figure out which types cells were present at specific points in the brain and what those cells were doing, Lein says.

The resulting map, which is available to anyone who wants to use it, has already led to at least two important findings, Lein says. "The first is that many genes that are associated with brain disorders are turned on early in development, which suggests that these disorders may have their origin from these very early time points."

And the map tells researchers who study these disorders where in the brain they should be looking for signs of trouble, Lein says.

For example, the map shows that genes associated with autism appear to be acting on a specific type of brain cell in a part of the brain called the neocortex. That suggests "we should be looking at this particular type of cell in the neocortex, and furthermore that we should probably be looking very early in the prenatal stages for the origin of autism," Lein says.

The second important finding from the mapping project, Lein says, is that the human brain is different from a mouse brain in ways researchers didn't know before. These differences could explain why a number of brain drugs that work well in mice have failed badly in people.

The map also reveals just how little scientists had known about the brain of a fetus.

"It's an enormous surprise to us that the genes that get expressed in the fetal brain don't look anything like what we would have expected from the adult brain," Insel says. "It's almost as if the fetal brain is a different organ altogether."

That realization is already helping to explain the complex role that genes often play in brain disorders, Insel says.

For example, researchers have been puzzled by some of the genes that appear to be involved in autism and schizophrenia because their function in the adult brain didn't seem to have anything to do with the disorders.

"But when you look at these new maps we have of what's happening in the fetal brain," Insel says, suddenly much of this begins to make sense."

From UCTV, Arthur W. Toga, PhD, joins William Mobley, MD, PhD to discuss scientific approaches to mapping the brain and its functions.

The Informatics of Brain Mapping - On Our Mind

Published on Jan 20, 2014
University of California Television


Can the secrets of the brain be decoded? Learn how finding meaningful patterns using big data is leading the way to big discoveries. Arthur W. Toga, PhD, joins William Mobley, MD, PhD to discuss scientific approaches to mapping the brain and its functions. Series: "The Brain Channel"

This is an interesting talk from the UC San Diego "Atlantic Meets the Pacific" series of conversations. This one focuses on the new efforts at brain mapping in neuroscience.

Brain Mapping: Pushing the Frontiers of Neurology -- Atlantic Meets the Pacific 2013

Published on Oct 17, 2013

(Visit: http://www.uctv.tv/)

UC San Diego neuroscientists Ralph Greenspan and Nicholas Spitzer join Kris Famm of GlaxoSmithKline and James Fallows of The Atlantic for a look into the future of brain research. This program is part of The Atlantic Meets the Pacific 2013 conference presented by The Atlantic and UC San Diego. Series: "The Atlantic Meets The Pacific" [11/2013]

This new study from The University of Western Australia maps the epigenome of the human brain.  While the ‘genome' acts as the instruction manual that contains the blueprints (genes) for all of the components of our cells and our body, the ‘epigenome' acts as an additional layer of information on top of our genes that change the way they are used.

This is huge breakthrough in brain imaging.

Brain Epigenomics Mapped

THE UNIVERSITY OF WESTERN AUSTRALIA
MONDAY, 08 JULY 2013

The new research will allow scientists to investigate the role the epigenome plays in learning, memory formation, brain structure and mental illness.                            Image: Jezper/Shutterstock

Comprehensive mapping of the human brain epigenome by UWA and US scientists uncovers large-scale changes that take place during the formation of brain circuitry.

Ground-breaking research by scientists from The University of Western Australia and the US, published in Science, has provided an unprecedented view of the epigenome during brain development.

High-resolution mapping of the epigenome has discovered unique patterns that emerge during the generation of brain circuitry in childhood.

While the ‘genome' can be thought of as the instruction manual that contains the blueprints (genes) for all of the components of our cells and our body, the ‘epigenome' can be thought of as an additional layer of information on top of our genes that change the way they are used.

"These new insights will provide the foundation for investigating the role the epigenome plays in learning, memory formation, brain structure and mental illness," says UWA Professor Ryan Lister, a genome biologist in the ARC Centre for Excellence in Plant Energy Biology, and a corresponding author in this new study.

Joseph R. Ecker, senior author of this study, and professor and director of the Genomic Analysis Laboratory at California's Salk Institute for Biological Studies in California, said the research shows that the period during which the neural circuits of the brain mature is accompanied by a parallel process of large-scale reconfiguration of the neural epigenome.

A healthy brain is the product of a long period of developmental processes, Professor Ecker said. These periods of development forge complex structures and connections within our brains. The front part of our brain, called the frontal cortex, is critical for our abilities to think, decide and act.

The frontal cortex is made up of distinct types of cells, such as neurons and glia, which each perform very different functions. However, we know that these distinct types of cells in the brain all contain the same genome sequence; the A, C, G and T ‘letters' of the DNA code that provides the instructions to build the cell; so how can they each have such different identities?

The answer lies in a secondary layer of information that is written on top of the DNA of the genome, referred to as the ‘epigenome'. One component of the epigenome, called DNA methylation, consists of small chemical tags that are placed upon some of the C letters in the genome. These tags alert the cell to treat the tagged DNA differently and change the way it is read, for example causing a nearby gene to be turned off. DNA methylation plays an essential role in our development and in our bodies's ability to make and distinguish different cell types.

To better understand the role of the epigenome in brain development, the scientists used advanced DNA sequencing technologies to produce comprehensive maps of precisely which C's in the genome have these chemical tags, in brains from infants through to adults. The study delivers the first comprehensive maps of DNA methylation and its dynamics in the brain throughout the lifespan of both humans and mice.

"Surprisingly, we discovered that a unique type of DNA methylation emerges precisely when the neurons in a child's developing brain are forming new connections with each other; essentially when critical brain circuitry is being formed." says co-first author Eran Mukamel from Salk's Computational Neurobiology Laboratory.

Conventionally, DNA methylation in humans had been thought to occur almost exclusively at C's that are followed by a G in the genome sequence, so-called ‘CG methylation'. However, in a surprise discovery in 2009, the researchers found that a distinct form of DNA methylation, called ‘non-CG methylation' constitutes a large fraction of DNA methylation in the human embryonic stem cell genome.

The researchers had previously observed both forms of DNA methylation in plant genomes when conducting earlier research that pioneered many of the techniques required for this brain study.

"Because of our earlier plant epigenome research we approached our human investigations from a distinct angle," Professor Lister said. "We were actively looking for these non-CG methylation sites that were not widely thought to exist. Our new study adds to this picture by showing that abundant non-CG methylation also exists in the human brain."

Surprisingly, this unique form of DNA methylation is almost exclusively found in neurons, and in patterns that are very similar between individuals. "Our research shows that a highly-ordered system of DNA tagging operates in our brain cells and that this system is unique to the brain," says co-author Dr Julian Tonti-Filippini, a computational biologist of the ARC Centre for Excellence in Plant Energy Biology and the WA Centre of Excellence for Computational Systems Biology.

This finding is very important, as previous studies have suggested that DNA methylation may play an important role in learning, memory formation, and flexibility of human brain circuitry. "These results extended our knowledge of the unique role of DNA methylation in brain development and function," Professor Ecker said. "They offer a new framework for testing the role of the epigenome in healthy function and in pathological disruptions of neural circuits."

"We found that patterns of methylation are dynamic during brain development, in particular for non-CG methylation during early childhood and adolescence, which changes the way that we think about normal brain function and dysfunction." says study co-author Terrence J. Sejnowski, head of Salk's Computational Neurobiology Laboratory. Recent studies have suggested that DNA methylation may be involved in mental illnesses, including bipolar disorder, depression, and schizophrenia. 

Environmental or experience-dependent alteration of these unique patterns of DNA methylation in neurons could lead to changes gene expression, adds co-corresponding author M. Margarita Behrens, a scientist in Salk's Computational Neurobiology Laboratory, "the alterations of these methylation patterns will change the way in which networks are formed, which could, in turn, lead to the appearance of mental disorders later in life."

This study is the culmination of more than two years' hard work from an international, interdisciplinary team involving science superstars from The Salk Institute for Biological Studies in La Jolla, California, UWA and several other institutes internationally.

Professor Lister and Dr Tonti-Filippini are now focussing their new research at UWA on how to control these epigenetic patterns within plant and animal genomes, which they hope will translate into breakthrough applications benefitting both human health and agriculture.

The work was supported by the Australian Research Council, the Western Australian State Government, the National Institute of Mental Health, the Howard Hughes Medical Institute, the Gordon and Betty Moore Foundation, the California Institute for Regenerative Medicine, the Leukemia and Lymphoma Society, and the Centre for Theoretical Biological Physics at the University of California, San Diego.

Editor's Note: Original news release can be found here.

An Overview of Critical Neuroscience

Via Somatosphere, these two videos offer a useful introduction to "Critical Neuroscience," an emergent field that seeks to examine (with a critical eye) the ways in which the new brain technologies influence our lives, from the personal, social, ethical, clinical, commercial, and policy debates to the methods and tools used to acquire new findings.

Critical Neuroscience probes the extent to which discussion of neuroscience—in ethical debates, policy texts, commercial, and clinical projects—matches the achievements and potential of neuroscience itself. It examines the ways in which the new sciences and technologies of the brain lead to classifying people in new ways, and the effects this can have on social and personal life. It studies both the methods used to gain new knowledge, and the ways in which the knowledge is interpreted and used. The project aims at finding or creating a shared vocabulary for neuroscientists and social scientists in which they can talk about the potential of the tools, the analytical methods, the interpretations of the data. We also need a shared way in which to think about the barrage of media reports of all this work. Critical Neuroscience aims, more over, at drawing attention to any social or political imperatives that make certain research programs in neuroscience more attractive and better funded than others. We hope to introduce our observations into brain research itself, and to integrate them into new experimental and interpretive directions.

The incredibly overpriced handbook to this field is Critical Neuroscience: A Handbook of the Social and Cultural Contexts of Neuroscience (2011), but two of the articles/chapters are available at Suparna Choudhury's Academia.edu page.

This is an interesting new field and these videos offer a nice introduction.

Videos from “Critical Neuroscience” Course

By Eugene Raikhel

I’ve written in the past (here and here) about the Critical Neuroscience project – an effort led by a group of social and biological scientists and philosophers to develop “a reflexive scientific practice that responds to the social, cultural and political challenges posed by the advances in the behavioural and brain sciences,” (Choudhury, Nagel and Slaby 2009). Suparna Choudhury, Jan Slaby and others have been very active in developing this project through a series of workshops, conferences, publications and ultimately, research projects. A short course on Critical Neuroscience has now been included in McGill’s Summer Program in Social and Cultural Psychiatry and you can view videos of two lectures from the course online. I’ve embedded them below.

If you’re interested in learning more about Critical Neuroscience, a good place to start is the Introduction and “Proposal for a Critical Neuroscience” from Choudhury and Slaby’s edited volume Critical Neuroscience. I was very excited to also have a chapter included in that volume; the only problem has been that the book has only been released in hardcover at a prohibitive price. Luckily Suparna has been kind enough to post both of these chapters on her Academia.edu site.

1: Critical Neuroscience and the Cultural Brain: An Outlook

How do we make sense of what is going on in the field of neuroscience? How can we make sense of the many discourses about neuroscience? Lecture given by Suparna Choudhury of McGill University, Montreal and Jan Slaby of Freie Universitat, Berlin.

2: Critical Neuroscience: An Overview

Critical Neuroscience and the Cultural Brain: an outlook. How do we make sense of what is going on in the field of neuroscience? How can we make sense of the many discourses about neuroscience? Lecture given by Suparna Choudhury of McGill University, Montreal and Jan Slaby of Freie Universitat, Berlin. 

In part two, Laurence Kirmayer gives an overview on the field of Critical Neuroscience, covering varieties of critical neuroscience, cultural constructions of the brain, the social brain, cultural neuroscience and neurodiversity.

The Brain - A User's Guide to Emotions and Emotional Styles

This is a cool graphic that Pamela Brooke (from bestpsychologydegrees.com) who emailed the link to me because she thought those of you who read this blog might find it interesting - and it is pretty cool.

Below the graphic, I have included the text from the section on emotional styles and how to change (retrain) your brain.

Image source: www.bestpsychologydegrees.com

The Brain: A User's Guide to Emotions

Emotional Styles - How to Retrain Your Brain

Six emotional dimensions that shape our lives and determine how we respond to our environment and the people around us, based on activity in the brain.

Resilience

- Definition: The ability to recover from adversity.
- Originates: Signals between the prefrontal cortex and the amygdala.
- How to retrain: Engage regularly in mindfulness meditation, focusing on your breathing and the sensations in your body.

Outlook

- Definition: The ability to sustain a positive emotional viewpoint.
- Originates: Ventral straitum
- How to retrain: Fill your workstation and home with positive reminders of happy times, such as vacations or photos of friends and family; change those photos every few weeks. Express gratitude frequently by thanking people and keeping a gratitude journal.

Self-awareness

- Definition: The ability to determine the physical signals that reflect emotions
- Originates: Signals between visceral organs and the insula
- How to retrain: For the overly self-aware and critical, practice non-judgmentally observing thoughts and feelings; for those who want to develop more self-awareness, tune in frequently to your body and determine how you feel and where those feelings originate.

Social interactions

- Definition: The ability to interpret social cues
- Originates: Interplay between the amygdala and fusiform
- How to retrain: Watch the body language of strangers and try to guess what emotions they are expressing. Work up to doing the same with family, friends and colleagues, monitoring how their body language matches with their tone of voice.

Sensitivity to context

- Definition: The ability to regulate responses based on the context of a situation
- Originates: Activity levels in the hippocampus
- How to retrain: List behaviors or events that trigger responses and consider why they did so. Think about your behaviors in those situations, meditating and breathing deeply until you feel more relaxed.

Attention

- Definition: The sharpness and clarity of focus
- Originates: Regulated by the prefrontal cortex
- How to retrain: Spend 10 minutes a day sitting in a quiet room and focusing on one object, refocusing when your attention wanders. 

SOURCES

• http://www.salon.com/2012/02/25/the_scientific_argument_for_being_emotional 
• http://www.thedailybeast.com/newsweek/2012/02/19/tired-of-feeling-bad-the-new-science-of-feelings-can-help.html 
• http://www.forbes.com/sites/jennagoudreau/2012/04/26/the-emotional-life-of-the-brain/ 
• http://www.forbes.com/pictures/lmj45jefj/change-your-brain-change-your-life/ 
• http://www.brainwaves.com/brain_diagram.html 
• http://science.nationalgeographic.com/science/health-and-human-body/human-body/brain-article.html 
• http://thebrain.mcgill.ca/flash/d/d_04/d_04_cr/d_04_cr_peu/d_04_cr_peu.html 
• http://thebrain.mcgill.ca/flash/i/i_04/i_04_cr/i_04_cr_peu/i_04_cr_peu.html 
• http://biology.about.com/od/anatomy/p/temporal-lobes.htm 
• http://homepage.ntlworld.com/teversal/myweb/CNS/thalamus.htm 
• http://biology.about.com/od/anatomy/p/Hypothalamus.htm 
• http://biology.about.com/od/anatomy/a/aa042205a.htm 
• http://www.nytimes.com/2007/02/06/health/psychology/06brain.html?_r=0&pagewanted=print 
• http://www.hhs.gov/opa/familylife/tech_assistance/etraining/adolescent_brain/Development/prefrontal_cortex/ 
• http://thebrain.mcgill.ca/flash/i/i_12/i_12_cr/i_12_cr_con/i_12_cr_con.html 
• http://www.huffingtonpost.com/2012/10/24/facial-recognition-brain-fusiform-gyrus_n_2010192.html 
• http://www.richarddavidson.com

David Brooks - Beyond the Brain

Every once in a while, David Brooks (at the New York Times) makes excellent points in his columns - this is one of the those times. What this column boils down to is that the mind is not the brain.

But then we knew that.

Beyond the Brain

By DAVID BROOKS
Published: June 17, 2013

It’s a pattern as old as time. Somebody makes an important scientific breakthrough, which explains a piece of the world. But then people get caught up in the excitement of this breakthrough and try to use it to explain everything.

David Brooks

This is what’s happening right now with neuroscience. The field is obviously incredibly important and exciting. From personal experience, I can tell you that you get captivated by it and sometimes go off to extremes, as if understanding the brain is the solution to understanding all thought and behavior.

This is happening at two levels. At the lowbrow level, there are the conference circuit neuro-mappers. These are people who take pretty brain-scan images and claim they can use them to predict what product somebody will buy, what party they will vote for, whether they are lying or not or whether a criminal should be held responsible for his crime.

At the highbrow end, there are scholars and theorists that some have called the “nothing buttists.” Human beings are nothing but neurons, they assert. Once we understand the brain well enough, we will be able to understand behavior. We will see the chain of physical causations that determine actions. We will see that many behaviors like addiction are nothing more than brain diseases. We will see that people don’t really possess free will; their actions are caused by material processes emerging directly out of nature. Neuroscience will replace psychology and other fields as the way to understand action.

These two forms of extremism are refuted by the same reality. The brain is not the mind. It is probably impossible to look at a map of brain activity and predict or even understand the emotions, reactions, hopes and desires of the mind.

The first basic problem is that regions of the brain handle a wide variety of different tasks. As Sally Satel and Scott O. Lilienfeld explained in their compelling and highly readable book, Brainwashed: The Seductive Appeal of Mindless Neuroscience, you put somebody in an fMRI machine and see that the amygdala or the insula lights up during certain activities. But the amygdala lights up during fear, happiness, novelty, anger or sexual arousal (at least in women). The insula plays a role in processing trust, insight, empathy, aversion and disbelief. So what are you really looking at?

Then there is the problem that one activity is usually distributed over many different places in the brain. In his book, Brain Imaging, the Yale biophysicist Robert Shulman notes that we have this useful concept, “working memory,” but the activity described by this concept is widely distributed across at least 30 regions of the brain. 

Furthermore, there appears to be no dispersed pattern of activation that we can look at and say, “That person is experiencing hatred.”

Then there is the problem that one action can arise out of many different brain states and the same event can trigger many different brain reactions. As the eminent psychologist Jerome Kagan has argued, you may order the same salad, but your brain activity will look different, depending on whether you are drunk or sober, alert or tired.

Then, as Kagan also notes, there is the problem of meaning. A glass of water may be more meaningful to you when you are dying of thirst than when you are not. Your lover means more than your friend. It’s as hard to study neurons and understand the flavors of meaning as it is to study Shakespeare’s spelling and understand the passions aroused by Macbeth.

Finally, there is the problem of agency, the problem that bedevils all methods that mimic physics to predict human behavior. People are smokers one day but quit the next. People can change their brains in unique and unpredictable ways by shifting the patterns of their attention.

What Satel and Lilienfeld call “neurocentrism” is an effort to take the indeterminacy of life and reduce it to measurable, scientific categories.

Right now we are compelled to rely on different disciplines to try to understand behavior on multiple levels, with inherent tensions between them. Some people want to reduce that ambiguity by making one discipline all-explaining. They want to eliminate the confusing ambiguity of human freedom by reducing everything to material determinism.

But that is the form of intellectual utopianism that always leads to error. An important task these days is to harvest the exciting gains made by science and data while understanding the limits of science and data. The next time somebody tells you what a brain scan says, be a little skeptical. The brain is not the mind.

~ A version of this op-ed appeared in print on June 18, 2013, on page A25 of the New York edition with the headline: Beyond The Brain.

In this interesting Perspectives paper from the open access Frontiers in Human Neuroscience, the authors analyzed current poster abstracts from the 18th Annual Meeting of the Organization for Human Brain Mapping (OHBM) in Beijing and scientific research published in peer-reviewed journals that addressed the neural foundations of culturally-shaped ways of defining or understanding the self. Their framework consisted of four biases - essentialism, binarity, Eurocentrism, and postcolonial and Orientalist views of the Self.

Both at the level of hypotheses generation and at the level of data interpretation, all research is influenced by specific socio-political and historical contexts. In this respect we argue that all quoted CN studies referring to the self are rooted in a specific context which defines the relevant research questions and topics and the way of interpretation. This context is traversed by social circumstances, political interests, and imbalances of power (Martínez Mateo et al., 2012).

Seems that social constructionist models are also gaining ground in the realm of brain mapping, brain imaging, and cognitive neuroscience more widely.


Full Citation: 

Martínez Mateo M, Cabanis M, Stenmanns J and Krach S. (2013). Essentializing the binary self: individualism and collectivism in cultural neuroscience. Frontiers in Human Neuroscience; 7:289. doi: 10.3389/fnhum.2013.00289

Essentializing the binary self: individualism and collectivism in cultural neuroscience

M. Martínez Mateo, M. Cabanis, J. Stenmanns, and S. Krach

Within the emerging field of cultural neuroscience (CN) one branch of research focuses on the neural underpinnings of “individualistic/Western” vs. “collectivistic/Eastern” self-views. These studies uncritically adopt essentialist assumptions from classic cross-cultural research, mainly following the tradition of Markus and Kitayama (1991), into the domain of functional neuroimaging. In this perspective article we analyze recent publications and conference proceedings of the 18th Annual Meeting of the Organization for Human Brain Mapping (2012) and problematize the essentialist and simplistic understanding of “culture” in these studies. Further, we argue against the binary structure of the drawn “cultural” comparisons and their underlying Eurocentrism. Finally we scrutinize whether valuations within the constructed binarities bear the risk of constructing and reproducing a postcolonial, orientalist argumentation pattern.

Introduction

At the 18th Annual Meeting of the Organization for Human Brain Mapping which was held in Beijing (June 10–14, 2012) the official program was amended by the philosophical supplement “Entering the Mind's I: Some reflections on the Chinese notion of self.” The supplement begins by explaining that the “concept of the individual as outlined by Western philosophy finds its most successful and most immediate conceptual and visual transposition in the work The Vitruvian Man by Leonardo [da Vinci].” The authors of this supplement pursue by stating that “No iconographic representation could be more antithetical to the concept of an individual characterized by the entirety of Chinese philosophy and culture (…)” (Lietti, 2012). 

During the conference various other contributions, symposia [e.g., “Imaging the sociocultural human brain” by Gao (2012)], i-poster presentations, or posters addressed “culturally” tuned ways of understanding the self. In these presentations the neural basis of “individualistic/Western” and “collectivistic/Eastern” “cultures” and their way of treating the self were discussed in comparison based on new insights from functional neuroimaging. 

But what does it mean to presume a “culturally” imprinted self? And what are the implications of considering two seemingly complementary groups with putatively opposed world- and self-views? The classic review of “cross-cultural” research by Markus and Kitayama (1991) represents the primary inspiration for actual neuroimaging work on “East/West” comparisons. We argue that, by doing so, assumptions implied in classic cross-cultural research are adopted to the functional neuroimaging community without being scrutinized. “Psychological” findings about “cultural differences” are thereby translated onto a “biological” level treating “culture” as a characteristic which can be read out from the body. By means of neuroimaging technology the simplifications of “culture” inherent to many cross-cultural psychological studies receive additional support as cultural differences can now be fostered by biological “evidence.” 

Here we elaborate why such neuroscientific findings bear the risk of constructing and reproducing essentialist (1), binarized (2), and Eurocentric (3) ways of thinking and acting which follow a postcolonial and orientalist tradition (4). These four dimensions build the frame for the current analysis. They all refer to specific traditions of critique which originate from philosophy and social science and which will be introduced in more detail in the respective sections of this manuscript. 

The endeavor to studying “cultural” phenomena by using functional MRI started only in the last decade (Chiao, 2009; Han and Northoff, 2009;Vogeley and Roepstorff, 2009; Kitayama and Park, 2010; Losin et al., 2010; Bao and Pöppel, 2012; Han et al., 2013; Rule et al., 2013). Since the year 2000 the number of publications in the cultural neurosciences (CN) has increased tremendously. Although particular concepts of “culture” are implied, these are only rarely explicitly addressed (Martínez Mateo et al., 2012, 2013). Within the field of CN, however, a particular branch has focused on “culturally” tuned ways of understanding the self [see Martínez Mateo et al. (2012) for a review on different branches in CN]. For the purpose of the present article we searched (i) peer-reviewed English language manuscripts of original functional MRI studies indexed in large databases (e.g., Google Scholar; PubMed) and (ii) abstracts published in the this year's Organization for Human Brain Mapping (OHBM) abstract book [pdf] which addressed the neural correlates of the self or self-concepts such as individualism and collectivism in a “cultural” context using cerebral blood flow imaging techniques such as fMRI or fNIRS. Overall, 10 manuscripts and 10 conference abstracts fulfilled these criteria and thus, formed the data pool for the present analysis. 

From these publications we extracted the aforementioned four fundamental dimensions which we problematize by briefly discussing their immanent assumptions, their implications and consequences.

Read the whole article.

Harvard’s George Whitesides Gives Brilliant Critique of Mammoth U.S. Brain Project

Not everyone in the neuroscience and psychology worlds are excited by President Obama's $100 million Brain Activity Map Project—or the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. George Whitesides (Harvard chemist and veteran of big government ventures in support of nanotechnology) recently gave a very good critique of the BRAIN Initiative.

Harvard’s Whitesides Gives Brilliant Critique of Mammoth U.S. Brain Project

By Gary Stix | May 29, 2013

George Whitesides

The Obama administration’s Big Brain project—$100 million for a map of some sort of what lies beneath the skull—has captured the attention of the entire field of neuroscience. The magnitude of the cash infusion can’t help but draw notice, eliciting both huzzahs mixed with gripes that the whole effort might sap support for other perhaps equally worthy neuro-related endeavors.

The Brain Activity Map Project—or the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative—is intended to give researchers tools to elicit the real-time functioning of neural circuits, providing a better picture of what happens in the brain when immersed in thought or when brain cells are beset by a degenerative condition like Parkinson’s or Alzheimer’s. Current technologies are either too slow or lack the resolution to achieve these goals.

One strength of the organizers—perhaps a portent of good things to come—is that they don’t seem to mind opening themselves to public critiques. At a planning meeting earlier this month, George Whitesides, the eminent Harvard chemist and veteran of big government ventures in support of nanotechnology, weighed in on how the project appeared to an informed outsider. Edited excerpting of some of his comments follows. This posting is a bit long, but Whitesides is eloquent and it’s worth reading what he has to say because his views apply to any large-scale sci-tech foray.

Whitesides began his talk after listening to a steady cavalcade of big-name neuroscientists furnish their personal wish lists for the program: ultrasound to induce focal lesions, more fruit fly studies to find computational nervous system primitives, more studies on zebra fish, studies on wholly new types of model organisms, avoiding too much emphasis on practical applications and so on.

“Listening to you this morning has been intensely interesting for me,” Whitesides began. “It has very much the flavor of a thousand flowers blooming. That is to say a problem which we all agree is intensely important: what is the brain how does it think, what is mind. It fits right there with issues such as what is life and where does life come from. It fits with the great problems of the next century.” 

“The question of whether people outside understand what is going on and where it leads is more complicated,” he continued. “I’ll just make a point to set a starting point. When I first heard about…the brain map I checked with a bunch of people who are good scientists and neurobiologists and everybody’s opposed, almost universally…There’s very deep skepticism that this approach, physical mapping at that scale, is going to work and lead to something.”

To promote the program, Whitesides emphasized the critical need to get non-neuroscientists to understand the problem being addressed—and to think carefully about something as simple as what the project should be called. Would the name “brain map” convey anything intelligible to someone not conversant with technical papers that bear titles like “Climbing Fiber Input Shapes Reciprocity of Purkinje Cell Firing”?

Whitesides suggested reverting to first principles in trying to describe to the world at large the importance of spending $100 million to gain better insight into the minutiae of neural circuitry. He recommended a cross-disciplinary collaboration by drawing upon knowledge, not from geneticists or bioengineers, but by borrowing across the divide of C.P. Snow’s Two Cultures: In other words, bringing in the English teachers. Going as basic as it gets, Whitesides told a room packed with full professors from elite universities that they should craft the story of the Big Brain project with the structural elements of a murder mystery.

“You have to have a puzzle or problem: Who killed lady of house? Was it the butler or somebody else? There has to be a puzzle or conflict or problem you want to resolve. The second element, a journey or trek, how you get there. You’ve spent much time talking here about that: what technical methods to get data or to formulate experiments. 

“The third component: There has to be a surprise. If you don’t have a surprise nobody’s interested. You have to catch the attention of people. To say [you want to come up with] a theory of mind is too far off. You want something shorter term that people can get a grip on. Finally, you need a resolution. The cat killed the lady of house, not the butler…But you need a resolution. Often in science you call it an application. 

“If you don’t have those components, you don’t have much to work with when talking to people who are not neuroscientists. Everybody’s fascinated by the particular tack they take to a particular piece of research. Outside it’s a different story. People want to know what you’re all doing and it has to be simple enough for people to understand that. It’s very difficult to do. 

“It’s very, very difficult to do and one of the issues here is to start hammering out that story. In genomics, it was: ‘we’re going to understand genomics, and based on the genome we’re going to understand cancer, and based on that understanding we’re going to cure cancer; and based on that your mother is going to live for a longer period of time.’ 

“Now it’s turned out to be more complicated than that as everything is in biology is. But here you’ve got an even more complicated problem. So how do you simplify this very complicated problem with top and bottom-level stories in such a fashion that I as an outsider can understand what the field is going to be doing, what it’s deliverables are going to be? … 

“Now in that context there are just a couple of things to remember. One of them is the question of ‘Why now?’ This problem has been around for a long time. And this is hardly the first group that’s thought about the nature of the brain. So why is now the time where we expect something astonishing to happen? With genomics, it happened because the technology of sequencing became so good that virtually anyone could generate floods of data and then begin to think about what could be done with that. What’s the corresponding thing here? I don’t know the answer to that. 

“The second issue which is in the same general issue of ‘why now’ is ‘Who cares?’” Obviously you care because you care about problems. But outside of this room with people who are not neuroscientists, what do they care about? What is the problem that you say you’re going to solve that they care about and I don’t think there are any shortage of these problems, all the way from alleviating tremor in Parkinson’s to beginning to think about depression, which is one of the great problems in public health.”

Whitesides then went on to talk about other considerations for structuring the project so that it retains some relevance beyond the neuroscience community. “I think that it’s really important to have deliverables and outcomes.” he said. “They don’t have to be the things that have the characteristic that they have to be the ultimate goal, but you need milestones along the way so you can go to the outside world and say we have done this. It’s not a compelling case to say that we’re here and in 100 years we’ll have a theory of mind and there’s nothing to show you in between because it’s all too complicated to understand. So what are they going to be and what do they look like?

“Second there’s a question of reductionism vs. higher-level stuff. If you think that a theory of mind is going to come by understanding the function of individual synapses and then building up from there, that tends not to work too well with really complicated systems. It works well with engineered systems like transistors or integrated circuits or devices or the Internet or Facebook. Those systems are engineered systems. Picking really complicated systems apart is hard to do. So what often one does is go from the end and look at higher-level behaviors in terms of black boxes and if you have good working models, you can pick those black boxes apart. 

“Just to give you an example of how the fully reductionist approach can run into difficulties, again we can go to genomics. If you talk now to the people in the pharmaceutical industry, what they will say is they’re moving massively away from target-based medicine to phenotypic assays. That is to say, if you want to find out whether a mouse gets better, you give a mouse stuff and see what happens, you don’t ask too many detailed questions. The detailed questions haven’t worked out very well. Here I don’t have a sense where the dividing line is between things that are best done at high-level and things that are best done by going reductionist. But there’s probably a place for everything.” 

“Zebra fish are a nice transparent model, but they’re probably not going to tell us very much about depression. People are probably more interested in depression than they are in zebra fish outside the room. That’s an interesting question. 

“The third point is about balance and inclusion. We are at the tail end of a pretty successful program in the United States on nanoscience or nanotechnology. And the question of why was this successful is complicated. But one of the reasons is that when this program emerged, it was phrased in such a way that virtually every area of science saw there was something in it for them; that is, the chemists, the biologists, the physicists, the device guys; everybody saw that there was some value in nanoscience for them. 

“And there was a supporting enormously important technology which is the technology of integrated circuits. And what’s happened over the course of time is what the engineers at Intel have done which is almost beyond belief in terms of its sophistication. Two generations or maybe one generation from now, microprocessors will have minimum feature sizes that are on the order of maybe 8 nanometers. I still can’t believe this and that’s using 190 nanometer light. 

So they provided an enormous practical push for this area and then everybody had something interesting to do at the nanoscale. The question is how to does one open this community in such a fashion that everyone thinks there’s something interesting and important…[For the brain project], it has to include engineering, it has to include clinical medicine it has to include the molecular it has to include cells and animals. The whole story has to be there somehow but making the story inclusive will make a much stronger case for building a strong community. 

The last point I’ll make is inclusion of industry…Let me tell you another short story which comes from a component of genomics that was Illumina, the sequencer that has been as important as many other things in genomics. The inventor of the technology at the very beginning was David Walt of Tufts…I was at a seminar with David in which one of the people in the audience at the end asked the following question: [which was] ‘how do you handle the conflict of interest problem in an academic lab. when you’re working on this and a company is working on the same thing’ and he [Walt] said ‘there’s never a problem and the reason there’s never a problem is that once industry takes up an idea; and good engineers, mature engineers, begin to work on it, an academic laboratory can never compete.’ 

“Now the relevance to this [the brain project] if you think about what Illumina and other sequencers made possible in genomics you can ask the question: are there corresponding things in this area where really good, skilled industrial engineers can make a capability available to the community in a way that makes it possible to collect all the data, all the structure, function, the measurements that you want to collect because it’s going to be vastly, vastly easier if it’s done as a centralized function, with real people paying real dollars to get it done really, really well. 

“And it may be premature to do it at this point. I don’t know the answer to that but it’s something for you to think about. And I think the earlier you get people who are professional engineers and, on the other end, clinicians actively involved in the work that you’re doing; the more likely you are to find components that you can use and motivations for using them that will help keep the field strong. 

“So it’s a fantastic area, unbelievably complicated. Outside it looks less straightforward than it looks to you inside and inside it looks pretty chaotic, so you can imagine what it looks like from outside.”

~ About the Author: Gary Stix, a senior editor, commissions, writes, and edits features, news articles and Web blogs for SCIENTIFIC AMERICAN. His area of coverage is neuroscience. He also has frequently been the issue or section editor for special issues or reports on topics ranging from nanotechnology to obesity. He has worked for more than 20 years at SCIENTIFIC AMERICAN, following three years as a science journalist at IEEE Spectrum, the flagship publication for the Institute of Electrical and Electronics Engineers. He has an undergraduate degree in journalism from New York University. With his wife, Miriam Lacob, he wrote a general primer on technology called Who Gives a Gigabyte? Follow on Twitter @gstix1.


The views expressed are those of the author and are not necessarily those of Scientific American.

Diane Rehm Show - Mapping The Human Brain (NPR)

From NPR's The Diane Rehm Show, a discussion with National Institutes of Health Director, Francis Collins, on President Obama's BRAIN proposal (Brain Research through Advancing Innovative Neurotechnologies).

Mapping The Human Brain

LISTEN
TRANSCRIPT

Wednesday, April 3, 2013 

President Barack Obama leaves the stage in the East Room of the White House in Washington, Tuesday, April 2, 2013, after he announces the BRAIN, Brain Research through Advancing Innovative Neurotechnologies, proposal. The president is asking Congress to spend $100 million next year to start a new project to map the human brain in hopes of eventually finding cures for diseases like Alzheimer's. (AP Photo/Charles Dharapak)


President Barack Obama announced a new multi-year research initiative to map the human brain. He compared its potential to that of the Human Genome Project. Scientists hope the brain project will eventually lead to solutions to diseases like Alzheimer's and Parkinson's and better treatments for a range of mental illnesses. The National Institutes of Health will coordinate the project. The president wants Congress to approve $100 million in initial funding. Some critics argue the money could be better spent on smaller grants to a number of brain research projects with specific goals. But many scientists are enthusiastic. Join Diane and NIH Director Francis Collins for a discussion on mapping the human brain.

Guests
Dr. Francis Collins, Director, National Institutes of Health.

Related Links

• What is the NIH BRAIN initiative?
• Research!America Public Opinion on Science Research

Related Images 

 

Related Video 

 

On The Clock: The BRAIN Initiative April 02, 2013 | Public Domain 

Dr. Francis Collins, the Director of the National Institutes of Health, highlights the BRAIN Initiative. The BRAIN (Brain Research through Advancing Innovative Neurotechnologies) initiative is a new proposal by President Obama for a new, bold research effort to revolutionize our understanding of the human mind and advance the President's vision for creating jobs and building a thriving middle class by investing in research and development.  

Learn more at http://WH.gov

Tom Hartsfield - Attention Ray Kurzweil: We Can't Even Build an Artificial Worm Brain

In this cool piece from Real Clear Science, Tom Hartsfield pokes some serious holes in Ray Kurzweil's project to build a human-like artificial intelligence. Part of Kurzweil's agenda is based on his belief that we understand enough about the human brain now to make this happen, and if we don't, we will soon.

The problem with theory, pointed out in this article, is that we have completely mapped the C. elegans (a small worm) neural network, and have had this map for years, but we remain perplexed in our efforts to predict its behavior based on its brain activity.

If we can't simulate 302 neurons and 5,000 synapses, how can we hope to conquer 100,000,000,000 and 100,000,000,000,000? Let's not even get started on the 100,000,000,000,000,000 electrical signals per second that form the traffic on that neural road network.

This is a good read.

Attention Ray Kurzweil: We Can't Even Build an Artificial Worm Brain

Posted by Tom Hartsfield at Tue, 05 Mar 2013

In the human brain, 100 billion neurons are connected by 100 trillion synapses. And, really, this staggeringly complex structure is only the beginning. (Consider that there may be roughly one hundred thousand trillion electrical signals traversing the brain in one second.)

Can we build a working model of our brain, or is it still too formidable for complete scientific study? The key insight to answer this question comes from looking at something far, far simpler.

Transparent and only one millimeter long, C. elegans worms are used in thousands of biology experiments as a ubiquitous invertebrate "lab rat." Each worm has exactly 302 neurons (connected by roughly 5,000-7,000 synapses). We know this because many scientists have counted the number of cells; each worm always contains 959 cells (hermaphrodite) or 1031 cells (male- which also contains 81 extra neurons in its tail).

C. elegans was the first animal to have its genome sequenced. We can freeze it in liquid nitrogen and revive it. We can track it in 3-D. You can browse a library of its complete genome, its proteome (like the genome, but proteins) and even its whole nervous system on the internet. Science has studied this organism more thoroughly than any other -- with the possible exception of the fruit fly and the laboratory mouse -- in the entire animal kingdom.

If we can get inside any mind in nature, this would be the one. We've had a map of every neuron and every neural connection in the brain of the worm for more than 20 years. Here is a complete picture:

Plenty of high quality, useful research has been produced using this knowledge of C. elegans' brain. Scientists can tie reflexes and simple behaviors of the worm to individual neural pathways or circuits in the brain.

Further, we've been working on simulations of the C. elegans brain for at least 10 years. Can we use this to model or predict the actions of the worm? No. We're not even close. In fact, it takes a computer with a billion transistors to make a weak, incorrect guess at what a worm with 302 brain cells will do.

If we can't simulate 302 neurons and 5,000 synapses, how can we hope to conquer 100,000,000,000 and 100,000,000,000,000? Let's not even get started on the 100,000,000,000,000,000 electrical signals per second that form the traffic on that neural road network.

Science always has to start at the very simplest level and work its way up. We build on our previous knowledge and eventually arrive at enormous achievements. Further research on this topic is absolutely important; some day we may very well be able to model the brain of a worm and even a human. However, at the present, there is simply no way that a comprehensive human brain simulation will be feasible in the near future.

So, no mind uploading yet. Sorry, Ray Kurzweil.