FW: Brain Sex

http://www.cerebromente.org.br/n11/mente/eisntein/cerebro-homens.html

Are There Differences between the Brains of Males and Females?

Renato M.E. Sabbatini, PhD  
That men and women are different, everyone knows that.
But, aside from external anatomical and primary and secondary sexual differences, scientists know also that there are many other subtle differences in the way the brains from men and women process language, information, emotion, cognition, etc.
One of the most interesting differences appear in the way men and women estimate time, judge speed of things, carry out mental mathematical calculations, orient in space and visualize objects in three dimensions, etc. In all these tasks, women and men are strikingly different, as they are too in the way their brains process language. This may account, scientists say, for the fact that there are many more male mathematicians, airplane pilots, bush guides, mechanical engineers, architects and race car drivers than female ones.
On the other hand, women are better than men in human relations, recognizing emotional overtones in others and in language, emotional and artistic expressiveness, esthetic appreciation, verbal language and carrying out detailed and pre-planned tasks. For example, women generally can recall lists of words or paragraphs of text better than men (13).
The "father" of sociobiology, Edward O. Wilson, of Harvard University (10), said that human females tend to be higher than males in empathy, verbal skills, social skills and security-seeking, among other things, while men tend to be higher in independence, dominance, spatial and mathematical skills, rank-related aggression, and other characteristics.
When all these investigations began, scientists were skeptical about the role of genes and of biological differences, because cultural learning is very powerful and influential among humans. Are girls more prone to play with dolls and cooperate among themselves than boys, because they are taught to be so by parents, teachers and social peers, or is it the reverse order?
However, gender differences are already apparent from just a few months after birth, when social influence is still small. For example, Anne Moir and David Jessel, in their remarkable and controversial book "Brain Sex" (11), offer explanations for these very early differences in children:
"These discernible, measurable differences in behaviour have been imprinted long before external influences have had a chance to get to work. They reflect a basic difference in the newborn brain which we already know about -- the superior male efficiency in spatial ability, the greater female skill in speech."
But now, after many careful controlled studies where environment and social learning were ruled out, scientists learned that there may exist a great deal of neurophysiological and anatomical differences between the brains of males and females.

Studying Differences in the Brain

There are now a number of sophisticated neuroscientific methods which allow scientists to probe minute differences between any two groups of brains. There are several approaches, brought forth by advancements in computerized image processing, such as tomography (detailed imaging of the brain using "slices"): 

1. volumetric measurements of brain parts: a region is defined, and the computer, working with a pile of slices, calculates the areas of the brain region, and then integrates numerically several areas in order to calculate its approximate volume. Statistical analysis of samples containing several brains are able to discover (or not) any differences in volume, thickness, etc.
2. functional imaging: using advanced devices, such as PET (Positron Emission Tomography), fMRI (functional Magnetic Resonance Imaging) or Brain Topographic Electroencephalography, researchers are able to visualize in two and three dimensions what parts of brain are functionally activated when a given task is performed by the subjects.
3. post-mortem examinations. The brains of deceased individuals are excised and sliced. Modern image analysis techniques are used to detect quantitative differences, such as the number and form of neurons and other brain cells, the area, thickness and volumes of brain regions, etc.

Scientists working at Johns Hopkins University, recently reporting in the "Cerebral Cortex" scholarly journal (1), have discovered that there is a brain region in the cortex, called inferior-parietal lobule (IPL) which is significantly larger in men than in women. This area is bilateral and is located just above the level of the ears (parietal cortex).
Furthermore, the left side IPL is larger in men than the right side. In women, this asymmetry is reversed, although the difference between left and right sides is not so large as in men, noted the JHU researchers. This is the same area which was shown to be larger in the brain of Albert Einstein, as well as in other physicists and mathematicians. So, it seems that IPL's size correlates highly with mental mathematical abilities. Morphological brain differences in intellectual skills were suspected to exist by neurologists since the times of phrenology (although this was proved to be a wrong approach), in the 19th century. The end of the 20th century has witnessed the first scientific proofs for that.
The study, led by Dr. Godfrey Pearlson, was performed by analyzing the MRI scans of 15 men and women. Volumes were calculated by a software package developed by Dr. Patrick Barta, a JHU psychiatrist. After allowing for the natural differences in overall brain volume which exist between the brains of men and women, there was still a difference of 5% between the IPL volumes (human male brains are, on average, approximately 10 % larger than female, but this is because of men's larger body size: more muscle cells  imply more neurons to control them).
In general, the IPL allows the brain to process information from senses and help in selective attention and perception (for example, women are more able to focus on specific stimuli, such as a baby crying in the night). Studies have linked the right IPL with the memory involved in understanding and manipulating spatial relationships and the ability to sense relationships between body parts. It is also related to the perception of our own affects or feelings. The left IPL is involved with perception of time and speed, and the ability of mentally rotate 3-D figures (as in the well-known Tetris game).
Another previous study by the same group led by Dr. Godfrey Pearlson (9) has shown that two areas in the frontal and temporal lobes related to language (the areas of Broca and Wernicke, named after their discoverers) were significantly larger in women, thus providing a biological reason for women's notorious superiority in language-associated thoughts. Using magnetic resonance imaging, the scientists measured gray matter volumes in several cortical regions in 17 women and 43 men. Women had 23% (in Broca's area, in the dorsolateral prefrontal cortex) and 13% (in Wernicke's area, in the superior temporal cortex) more volume than men.
These results were later corroborated by another research group from the School of Communication Disorders, University of Sydney, Australia, which  was able to prove these anatomical differences in the areas of Wernicke and of Broca (3). The volume of the Wernicke's area was 18% larger in females compared with males, and the cortical volume the Broca's area in females was 20% larger than in males.
On the other hand, additional evidence comes from research showing that the corpus callosum, a large tract of neural fibers which connect both brain hemispheres, is enlarged in women, compared to men (5), although this discovery has been challenged recently.
In another research, a group from the University of Cincinnati, USA, Canada, presented morphological evidence that while men have more neurons in the cerebral cortex, women have a more developed neuropil, or the space between cell bodies, which contains synapses, dendrites and axons, and allows for communication among neurons (8). According to Dr. Gabrielle de Courten-Myers, this research may explain why women are more prone to dementia (such as Alzheimer's disease) than  men, because although both may lose the same number of neurons due to the disease, "in males, the functional reserve may be greater as a larger number of nerve cells are present, which could prevent some of the functional losses."
The researchers made measurements on slices of brains of 17 deceased persons (10 males and seven females), such as the cortex thickness and number of neurons in several places of the cortex.
Other researchers, led by Dr. Bennett A. Shaywitz, a professor of Pediatrics at the Yale University School of Medicine, discovered that the brain of women processes verbal language simultaneously in the two sides (hemispheres) of the frontal brain, while men tend to process it in the left side only. They performed a functional planar magnetic resonance tomographic imaging of the brains of 38 right-handed subjects (19 males and 19 females). The difference was demonstrated in a test that asked subjects to read a list of nonsense words and determine if they rhyme (7). Curiously, oriental people which use pictographic (or ideographic) written languages tend also to use both sides of the brain, regardless of gender.
Although most of the anatomical and functional studies done so far have focused on the cerebral cortex, which is responsible for the higher intellectual and cognitive functions of the brain, other researchers, such as Dr. Simon LeVay, have shown that there are gender differences in more primitive parts of the brain, such as the hypothalamus, where most of the basic functions of life are controlled, including hormonal control via the pituitary gland. LeVay discovered that the volume of a specific nucleus in the hypothalamus (third cell group of the interstitial nuclei of the anterior hypothalamus) is twice as large in heterosexual men than in women and homosexual men, thus prompting a heated debate whether there is a biological basis for homosexuality (6). Dr. LeVay wrote an interesting book about the sex differences in the brain, titled "The Sexual Brain" (6).

Evolution versus Environment

What is the reason for these gender differences in structure and function?
According to the Society for Neuroscience, the largest professional organization in this area, evolution is what gives sense to it. "In ancient times, each sex had a very defined role that helped ensure the survival of the species. Cave men hunted. Cave women gathered food near the home and cared for the children. Brain areas may have been sharpened to enable each sex to carry out their jobs". Prof. David Geary, at the University of Missouri, USA, a researcher in the area of gender differences, thinks that "in evolutionary terms, developing superior navigation skills may have enabled men to become better suited to the role of hunter, while the development by females of a preference for landmarks may have enabled them to fulfill the task of gathering food closer to home." (2) The advantage of women regarding verbal skills also make evolutionary sense. While men have the bodily strength to compete with other men, women use language to gain social advantage, such as by argumentation and persuasion, says Geary.
Author Deborah Blum, who wrote "Sex on the Brain: The Biological Differences Between Men and Women" (12), has reported the current trend towards assigning evolutionary reasons for many of our behaviors. She says: "Morning sickness, for example, which steers some women away from strong tastes and smells, may once have protected babes in utero from toxic items. Infidelity is a way for men to ensure genetic immortality. Interestingly, when we deliberately change sex-role behavior -- say,  men become more nurturing or women more aggressive -- our hormones and even our brains respond by changing, too."
During the development of the embryo in the womb, circulating hormones have a very important role in the sexual differentiation of the brain. The presence of androgens in early life produces a "male" brain. In contrast, the female brain is thought to develop via a hormonal default mechanism, in the absence of androgen. However, recent findings have shows that ovarian hormones also play a significant role in sexual differentiation.
One of the most convincing evidences for the role of hormones, has been shown by studying girls who were exposed to high levels of testosterone because their pregnant mothers had congenital adrenal hyperplasia (4). These girls seem to have better spatial awareness than other girls and are more likely to show turbulent and aggressive behaviour as kids, very similar to boys'.

Fact and Prejudice

But do these differences mean a superiority/inferiority relationship between men and women?
"No", says Dr. Pearlson. "To say this means that men are automatically better at some things than women is a simplification. It's easy to find women who are fantastic at math and physics and men who excel in language skills. Only when we look at very large populations and look for slight but significant trends do we see the generalizations. There are plenty of exceptions, but there's also a grain of truth, revealed through the brain structure, that we think underlies some of the ways people characterize the sexes."
Dr. Courten-Myers concurs: "The recognition of gender-specific ways of thinking and feeling -- rendered more credible given these established differences -- could prove beneficial in enhancing interpersonal relationships. However, the interpretation of the data also has the potential for abuse and harm if either gender would seek to construct evidence for superiority of the male or female brain from these findings."
The conclusion is that neuroscience has made great strides in the 90s, regarding the discovery of concrete, scientifically proved anatomical and functional differences between the brains of males and females. While this knowledge could in theory be used to justify misogyny and prejudice against women, fortunately this has not happened. In fact, this new knowledge may help physicians and scientists to discover new ways to explore the brain differences in the benefit of the treatment of diseases, the personalized action of drugs, different procedures in surgeries, etc. After all, males and females differ only by one Y chromosome, but this makes a real impact upon the way we react to so many things, including pain, hormones, etc.

To Know More

Sabbatini, R.M.E.: The PET Scan: A New Window Into the Brain 
Gattass, R.: Thoughts: Image Mapping by Functional Nuclear Magnetic Resonance 
Cardoso, S.H.: Why Einstein Was a Genius? 
Sabbatini, R.M.E.: Paul Broca: Brief Biography 
Sabbatini, R.M.E.: Mapping the Brain

References

1. Frederikse, M.E., Lu, A., Aylward, E., Barta, P., Pearlson, G. Sex differences in the inferior parietal lobule. Cerebral Cortex vol 9 (8) p896 - 901, 1999 [MEDLINE].
2. Geary, D.C. Chapter 8: Sex differences in brain and cognition. In "Male, Female: the Evolution of Human Sex Differences". American Psychological Association Books. ISBN: 1-55798-527-8 [AMAZON].
3. Harasty J., Double K.L., Halliday, G.M., Kril, J.J., and McRitchie, D.A. Language-associated cortical regions are proportionally larger in the female brain. Archives in Neurology vol 54 (2) 171-6, 1997 [MEDLINE].
4. Collaer, M.L. and Hines, M. Human behavioural sex differences: a role for gonadal hormones during early development? Psychological Bulletin vol 118 (1): 55-77, 1995 [MEDLINE].
5. Bishop K.M. and Wahlsten, D. Sex differences in the human corpus callosum: myth or reality? Neuroscience and Biobehavioural Reviews vol 21 (5) 581 - 601, 1997.
6. LeVay S. A difference in hypothalamic structure between heterosexual and homosexual men Science. 253(5023):1034-7, 1991 [MEDLINE].

See also: LeVay, S.: "The Sexual Brain". MIT Press, 1994 [AMAZON]
7. Shaywitz, B.A., et al. Sex differences in the functional organisation of the brain for language. Nature vol 373 (6515) 607 - 9, 1995 [MEDLINE].
8. Rabinowicz T., Dean D.E., Petetot J.M., de Courten-Myers G.M. Gender differences in the human cerebral cortex: more neurons in males; more processes in females. J Child Neurol. 1999 Feb;14(2):98-107. [MEDLINE]
9. Schlaepfer T.E., Harris G.J., Tien A.Y., Peng L., Lee S., Pearlson G.D. Structural differences in the cerebral cortex of healthy female and male subjects: a magnetic resonance imaging study. Psychiatry Res. 1995 Sep 29;61(3):129-35 [MEDLINE].
10. Wilson, E.O. - "Sociobiology". Harvard University Press, 1992 [AMAZON].
11. Moir A. and Jessel D. - "Brain Sex". 1993 [AMAZON] See also: Excerpts from the book
12. Blum, D. - "Sex on the Brain: The Biological Differences Between Men and Women". Penguin, 1998 [AMAZON]
13. Kimura, D. - "Sex and Cognition". MIT Press, 1999 [AMAZON]

Classic post about Empirical Bayesian application in MEG source reconstruction.

Dear Yuri,

Yury Petrov wrote:
> Hi Will,
> 
> I attached the paper. 

Thx, its a top paper.

My concern is that the EM algorithm cannot be
> used to estimate two parameters when one of them is used to define a
> prior for the other. 

It can.

One parameter defining a prior over another results in a hierarchical 
model. Bayesian estimation of linear Gaussian hierarchical models was 
solved in the 70's by the stats community. More recently the machine 
learning community have been using various approximate inference 
algorithms for hierarchical nonlinear/nonGaussian models. See 
Jordan/Bishop/Ghahramani etc.

Irrespectively of how the MSP algorithm has been
> derived, the ReML learning part explicitly described in the Appendix
> of the Phillips et al 2002 paper is violating the Bayes rule. It
> first calculates the source covariance matrix given the solution of
> the previous iteration, then uses its scale (trace) to rescale the
> original source covariance, etc. Yes, it uses the 'lost degrees of
> freedom' trick 

This isn't a trick. It falls naturally out of the mathematics.

to prevent a nonsensically localized solution, but
> this trick does not address the main problem. The algorithm still
> changes the prior based on posterior, then posterior based on the new
> prior, etc. iteratively.
> 

All of what i've said corresponds to the framework of Empirical Bayes - 
where you estimate the parameters of priors from data.

Pure Bayesians do not allow this. They see it, as you say, as a 
violation of what a prior is.

But then pure Bayesians have'nt solved many interesting problems. The 
Empirical Bayesian claims to know only the form of prior densities. Not 
their parameters.

Best,

Will.

> 
> 
> ------------------------------------------------------------------------
> 
> 
> 
> 
> On Sep 22, 2010, at Sep 22, 2010 | 1:14 PM, Will Penny wrote:
> 
>> Dear Yury,
>> 
>>>> ---------------------------------- Dear All,
>>>> 
>>>> I have a conceptual concern regarding the MSP algorithm used by
>>>>  SPM8 to localize sources of EEG/MEG activity. The algorithm is
>>>>  based, in part, on EM iterative scheme used to estimate source
>>>>  priors (source covariance matrix) from the measurements. The
>>>> way this scheme is described in the Phillips et al. 2002 paper,
>>>> it works as an iterative Bayesian estimator: first it estimates
>>>> the sources, then calculates the resulting source covariance
>>>> from the estimate, next it (effectively) uses it as the new
>>>> prior for the sources, estimates the sources again, etc.
>>>> However, applying Bayesian learning iteratively is a common
>>>> pitfall and should not be used, because each such iteration
>>>> amounts to introducing new fictitious data. I attached a nice
>>>> introductory paper illustrating the pitfall on page 1426.
>> 
>> I don't believe that this is a pitfall.
>> 
>> The parameters of the prior (specifically the variance components)
>> are estimated iteratively along with the variance components of the
>> likelihood.
>> 
>> Importantly, each is estimated using degrees of freedom which are 
>> effectively partitioned into those used to estimate prior variance
>> and those used to estimate noise variance. This is a standard
>> Empirical Bayesian approach and produces unbiased results.
>> 
>> See papers by David Mackay on this topic and eg. page 6-8 of the
>> chapter on 'Hierarchical Models' in the SPM book (this is available
>> under publications/book chapters on my web page 
>> http://www.fil.ion.ucl.ac.uk/~wpenny/ - note gamma and (k-gamma)
>> terms in denominator of eqs 32 and 35 denoting the partitioning of
>> the degrees of freedom).
>> 
>> Nevertheless, I'd like to read page 1426 of your introductory
>> paper. Can you send it to me ?
>> 
>> Best wishes,
>> 
>> Will.
>> 
>> In particular, the outcome of the
>>>> iterations may become biased toward the original source
>>>> covariance used. In my test application of the described EM
>>>> algorithm I found that scaling the original source covariance
>>>> matrix changes the resulting sources estimate, which, in
>>>> principle, should not happen. For comparison, this problem does
>>>> not occur, when the source covariance parameters are learned
>>>> using ordinary or general cross-validation (OCV or GCV).
>>>> 
>>>> Best, Yury
>>>> 
>>>> 
>>>> 
>>>> 
>>>> 
>>>> 
>>> 
>> -- William D. Penny Wellcome Trust Centre for Neuroimaging 
>> University College London 12 Queen Square London WC1N 3BG
>> 
>> Tel: 020 7833 7475 FAX: 020 7813 1420 Email:
>> [log in to unmask] URL: http://www.fil.ion.ucl.ac.uk/~wpenny/
>> 
>> 
> 

-- 
William D. Penny
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG

Tel: 020 7833 7475
FAX: 020 7813 1420
Email: [log in to unmask]
URL: http://www.fil.ion.ucl.ac.uk/~wpenny/

GIFT Group ICA for FMRI data

Before using GIFT to do ICA analysis on your fMRI data, you need to do several pre-processing steps:

(1) slice timing correction (before realignment if your data were collected interleave fashion, otherwise after realignment) - This step is sometime neglected in the block design.  For event-related design, it is important.

(2) realignment: get your motion parameters (x,y,z, roll, pitch, yaw)

(3) coregistration - T1-template, then apply transformation matrix to EPI.

(4) segmentation - skull stripping

(5) normalization - normalize to template

(6) smooth - blur the data

You can use spm_jobman('run',jobs) to do batch scripting.  Save you time for group analysis.

Human Brain Mapping 2012, Beijing, China, Itinerary Draft

HUMAN BRAIN MAPPING 2012 ITINERARY

Day 1:  June 10^th, Sunday, 2012    Educational Courses - The Connectome

Details: The Connectome

http://www.humanbrainmapping.org/files/2012MeetingFiles/Sessions/Connectome.pdf

  Organizers: Heidi Johansen-Berg, University of Oxford, UK

                                                         Ed Bullmore, University of Cambridge, UK

Learning Objectives: Having completed this course, participants will be able to:

1.       Understand methods for acquisition and analysis of diffusion MRI, resting state FMRI, EEG and MEG data

2.       Understand network modelling methods for connectomics

3.       Give examples of approaches to visualising connectomes; and

4.       Give examples of applications of connectomics to understanding brain function and dysfunction.

Course Schedule

I. Building Connectomes

8:00-8:30 Introduction to Connectomics and Overview of the Course Heidi Johansen-Berg, University of Oxford, UK

8:30-9:00 MRI Acquisition and Analysis Strategies for Connectomics  Larry Wald, Harvard Medical School, USA

9:00-9:30 Diffusion Tractography and Structural Measures Donald Tournier, Brain Research Institute, Melbourne, Australia

9:30-10:00 Overview of Intrinsic Connectivity Networks Vince Calhoun, University of New Mexico, USA

10:00-10:30 Break

10:30- 11:00 EEG/MEG and Brain Networks  Johanna Zumer, Radboud University Nijmegen, Netherlands

11:00-11:30 Overview of FMRI Network Modelling Methods in Task and Rest Ed Bullmore, University of Cambridge, UK

11:30-12:00 Discussion and Q+A

12:00-13:00 Lunch

II. Modeling and Mining Connectomes

13:00-13:30 Advanced Network Modelling I: Dynamic Models; Multimodal Integration Mark Woolrich, University of Oxford, UK

13:30-14:00 Advanced Network Modelling II Gael Varoquaux, INSERM, Neurospin, France

14:00-14:30 Neuroinformatics for Connectomics David Van Essen, Washington University, St Louis, USA

14:30-15:00 Brain Networks in Health and Disease Ed Bullmore, University of Cambridge, UK

15:00-15:30 Break

15:30-16:00 Data Mining and Visualisation Angie Laird, University of Texas, San Antonio, USA

16:00-16:30 State-Dependent and Disease-Related Variations in Functional Networks Silvina Horovitz, NINDS, NIH, USA

16:30-17:00 Discussion and Q+A

17:30-19:00 Opening Ceremonies and Talairach Lecture

Speech and Auditory Memory: How Deep is Their Connection? Mortimer Mishkin, PhD, Bethesda, MD, USA

Lecture Abstract: This talk revolves around two seemingly unrelated findings. The first is the momentous discovery of the FOXP2 gene, essential for oromotor articulation, an ability that likely evolved within the hominid line in just the last 300,000 years. The second finding, less momentous but more puzzling, is that, unlike humans, monkeys seem unable to store long-term memories in audition, even though they are easily able to do so in vision and touch. Together, these two pieces of evidence suggest that speech and long-term auditory memory may be indissolubly linked. An initial test provides this suggestion with some preliminary support.

Bio: Mortimer Mishkin received an AB from Dartmouth College (1946) and an MA (1949) and PhD (1951) from McGill University (MA with D.O. Hebb; PhD with H.E. Rosvold and K.H. Pribram).  In 1955, after completing postdoctoral research with both Pribram at the Institute of Living, Hartford, CT, and H.L. Teuber at Bellevue Medical Center, New York University, he joined Rosvold at NIMH, where, in 1980, he became chief of the Laboratory of Neuropsychology (LN), and, in 1994, associate director for basic research at NIMH.  He relinquished both titles in 1997, remaining chief of LN’s Section on Cognitive Neuroscience, acting chief of LN, and visiting professor at University College London Institute of Child Health.

19:00-21:00 Welcome Reception

Day 2:  June 11^th, Monday, 2012    http://www.humanbrainmapping.org/i4a/pages/index.cfm?pageid=3459

8:30-9:45      Morning workshop: Assessing Network (dys-) Function in Development, At-Risk States and Psychiatric Disorders, Chair: Simon B. Eickhoff, Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany

                              1. The Maturation of Top-Down Frontal Cognitive Control Through Adolescence Beatriz Luna, Laboratory of Neurocognitive Development, University of Pittsburgh Medical Center, Pittsburgh, PA, USA

                              2. Genetic Control Over Brain Connectivity: Implications for Affective Disorders David C. Glahn, Department of Psychiatry, Yale University, Hartford, CT, USA

                              3. Networks at Risk: Dynamic Causal Modeling Reveals Mechanisms of Dysfunction in Adolescents Vulnerable to Psychiatric Illness Vaibhav A. Diwadkar, Dept of Psychiatry & Behavioral Neuroscience, Wayne State University School of Medicine, Detroit, MI, USA

                              4. Imaging Brain Networks in the "Grey-Zone" Between Health and Disease Simon B. Eickhoff, Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany

10:00-11:30 Symposia: LOC Symposium: Imaging the Sociocultural Human Brain

        Chair: Jia-Hong Gao, Peking University, China; University of Chicago, USA

                        1. Neural Processing Underlying Emotion Recognition and Regulation

        Tatia Lee, The University of Hong Kong, China

2. Unconscious Processing of Facial Expressions-Cortical Sites, Dynamics, and Individual Differences

Sheng He, Institute of Biophysics, Chinese Academy of Sciences, China; University of Minnesota, USA

3. Unconscious Processing of Facial Expressions-Cortical Sites, Dynamics, and Individual Differences

Sheng He, Institute of Biophysics, Chinese Academy of Sciences, China; University of Minnesota, USA

4. Neural Representation of the Self in Sociocultural Contexts

Shihui Han, Peking University, China

11:45-12:30 Keynote lectures (approximately 30 minutes long and cover a wide variety of topics)

                         Functional Architecture of Face Processing in the Primate Brain

Leslie Ungerleider, Laboratory of Brain & Cognition, NIMH, Bethesda, MD, USA

Lecture Abstract:

Face recognition is a remarkable ability, given the tens of thousands of different faces we can recognize, sometimes even many years later after a single encounter.  This unique ability likely depends on specialized neural machinery dedicated to face processing.  This talk will focus on the network dynamics among regions mediating the recognition of both face identity and facial expression in the primate brain.

Biography:

Dr. Ungerleider is Chief of the Laboratory of Brain and Cognition at the National Institute of Mental Health and an NIH Distinguished Investigator. She hs been elected to the National Academy of Sciences, the American Academy of Arts and Sciences, and the Institute of Medicine.

13:30-15:30  Poster Session

15:45-17:00  Symposia: What Can Brain Imaging Tell Us About Motor Learning?

                           Chair: Joern Diedrichsen, Motor Control Group, Institute of Cognitive Neuroscience, University College London, London, UK

                          1. Dynamic Brain Correlates of Dexterity and Motor Skill Acquisition Traced with Structural Magnetic Resonance Imaging, Hartwig Roman Siebner, Danish Research Center for Magnetic Resonance, Department of MR (DRCMR), Copenhagen University, Hospital Hvidovre, Hvidovre, Denmark

                          2. Dynamic Changes in Neurochemistry and Brain Structure with Learning and Brain Stimulation, Heidi Johansen-Berg, Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Oxford, UK

                          3. Predicting Learning Based on Large-Scale Network Dynamics in fMRI, Scott T. Grafton, UCSB Brain Imaging Center and the Department of Psychological & Brain Sciences, University of California, Santa Barbara, CA, USA

                          4. Motor Learning: A Change in Neuronal Representation, Rather than in Activation, Joern Diedrichsen, Motor Control Group, Institute of Cognitive Neuroscience, University College London, London, UK

17:15-18:00  Keynote lectures: Spectral Fingerprints of Cognitive Processing, Andreas Engel, Dept. of Neurophysiology and Pathophysiology University Medical Center Hamburg-Eppendorf, Hamburg, Germany

Lecture Abstract:

Cognition results from large-scale interactions among functionally specialized but widely distributed brain regions. The talk will focus on recent studies that exploit correlated neuronal oscillations to characterize such large-scale cortical interactions in the human brain. It will be argued that large-scale oscillatory coupling provides a level of description that is particularly fruitful for identifying unifying principles underlying cognitive processing.

Biography:

Andreas K. Engel is Professor of Physiology and Director of the Dept. of Neurophysiology and Pathophysiology at the University Medical Center Hamburg-Eppendorf, Hamburg, Germany. He is also coordinator of Collaborative Research Centre SFB 936 at Hamburg, Germany. His research interests are: role of synchronization and oscillations for cognitive processing; neural mechanisms of intermodal and sensorimotor integration, emotion, working memory, decision making, attention and consciousness; changes of large-scale network dynamics in neurological and psychiatric disorders; brain-computer interfaces; bioinspired robot architectures.

18:15-19:45  Oral Sessions: O-M4: Resting State Networks, Chair: Michael Greicius

18:15 - 18:30

665 MT: Edge selection preserving the topological features of brain network

Hyekyoung Lee, SNUH, Seoul, Korea, Republic of

18:30 - 18:45

80 WTh: The Autism Brain Imaging Data Exchange (ABIDE) consortium: open sharing of autism resting state fMRI

Adriana Di Martino, NYU Child Study Center

18:45 - 19:00

554 MT: Network Analysis Could Reveal Local And Global Intelligence Fingerprint In Resting State fMRI Data

Emiliano Santarnecchi, Department of Neurological and Sensorial Sciences, Siena, Italy

19:00 - 19:15

739 MT: Resting state networks are characterized by high frequency BOLD fluctuations

Erik van Oort, MIRA Institute, University of Twente, Donders Institute, Radboud University Nijmegen, Nijmegen, Netherlands

19:15 - 19:30

476 MT: Tracking whole-brain connectivity dynamics in the resting-state

Elena Allen, Mind Research Network, Albuquerque, United States

19:30 - 19:45

795 WTh: Establishing homotopic inter-hemispheric regional correspondences via rest functional connectivity

Marc Joliot, UMR5296, Université Bordeaux Segalen, CNRS, CEA, Bordeaux, France

Day 3:  June 12^th, Tuesday, 2012

http://www.humanbrainmapping.org/i4a/pages/index.cfm?pageid=3459

8:30-9:45      Morning workshop: From Static to Dynamic Descriptions: Non-Stationarity in Functional and Effective Brain Connectivity, Chair: Christian F. Beckmann, MIRA Institute for Biomedical Engineering and Technical Medicine University of Twente, Enschede, NL Donders Institute for Brain, Congnition and Behavior Radboud University Nijmegen,, Nijmegen, Netherlands

1.       Measuring Electrodynamic Connectivity: Observations Using Magnetoencephalography Mark Woolrich, Univ Of Oxford, FMRIB Centre, John Radcliffe Hospital, Oxford , United Kingdom

2.       Functionally-Distinct Spatially-Overlapping Brain Modes Stephen M. Smith, Oxford University Centre for Functional MRI of the Brain (FMRIB), John Radcliffe Hospital, Oxford, UK

3.       Dynamics of Resting-State BOLD Signal Connectivity Catie Chang, Advanced MRI section, NINDS, NIH, Bethesda, MD, USA

4.       Temporal and Spatial Non-Stationarity in Effective Connectivity Networks Using Switching Linear Dynamic Systems Jason F. Smith, Brain Imaging and Modeling Section, NIDCD, National Institutes of Health, Bethesda, MD, USA

10:00-10:45 Keynote lectures: The Topological Definition of Perceptual Objects: Theory, Behavioral Evidence, and Neural Representation, Lin Chen, State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
Lecture Abstract:
What is a perceptual object? Intuitively, it is the holistic identity preserved over shape-changing transformations. According to the global-first topological approach, this core intuitive notion of an object can be characterized as topological invariants, such as holes. Behavioral experiments demonstrated that changes in topological properties disturbed object continuity, leading to the perception of an emergence of a new object; and fMRI experiments showed that the topological changes activated the anterior temporal lobe and amygdale.
Biography:
Prof. Lin Chen is Director of State Key Laboratory of Brain and Cognitive Science, and Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences. He is an elected member of Chinese academy of Sciences, and the Academy of Sciences for the Developing World.

11:00-12:30  Oral Sessions: O-T1: Modeling and Analysis Methods, Chair: Niko Kriegeskorte & O-T2: Motor Behavior, Learning & Disorders, Chair: Genevieve Albouy

11:00 - 11:15

786 MT: Neuronal network coherent with the kinematics of observed hand movement

Xavier De Tiège, Université Libre de Bruxelles, Brussels, Belgium

11:15 - 11:30

784 MT: Estimation of three-dimensional movement trajectory from MEG signals

Hong Gi Yeom, Seoul National University, Seoul, Korea, Republic of

11:45 - 12:00

760 MT: Fast and accurate modelling of longitudinal neuroimaging data

Bryan Guillaume, University of Warwick, Coventry, United Kingdom

12:00 - 12:15

499 MT: Estimating BOLD Signals of Deep Brain Networks From EEG using Canonical correlation Analysis

Lavi Shpigelman, IBM, Haifa, Israel

12:15 - 12:30

632 MT: Capturing high-order interactions in neuroimaging data

Sergey Plis, The Mind Research Network

13:30-15:30  Poster Session

15:45-17:00  Symposia: Relationships Between Functional Networks Assessed by fMRI and EEG/MEG/ECoG, Chairs: Todd S. Woodward, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada Jennifer C. Whitman, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada

1.       Spatial Correspondence Between Networks of Oscillatory Activity Identified in MEG Data and the Dorsal Attention and Default Mode Networks Identified in fMRI Data, Jennifer C. Whitman, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada

2.       Investigating the Spatial-Temporal Dynamics of Functional Networks with Simultaneous EEG-fMRI, Rene Scheeringa, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, Netherlands

3.       Investigating the Electrophysiological Origin of Brain Networks Using Magnetoencephalography Matthew Brookes, Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom

4.       A Frequency-Specific Mechanism that Links Human Brain Networks During Task Performance Maurizio Corbetta, Departments of Neurology, Radiology, Anatomy & Neurobiology, Washington University School of Medicine, St. Louis, Missouri, USA

17:15-18:00  Keynotes: Structural and Functional Architecture of the Human Cerebral Cortex: Multiscale and Multimodal Maps, Karl Zilles, Institute of Neuroscience and Medicine, Research Centre Jülich, and C. & O. Vogt Institute, University Düsseldorf, Germany

Lecture Abstract: The contribution of “tedious anatomy” for understanding brain structures underlying various types of neuroimaging data will be demonstrated. Localization beyond the common misuse of so-called “Brodmann maps”, multiscale (from molecules to circuits) and multimodal (cyto- and receptorarchitecture) mapping strategies, as well as an ultra-high resolution approach to structural connectivity will be discussed.

Biography: Karl Zilles is Professor of Brain Research at the Cécile & Oskar Vogt-Institute, University of Düsseldorf and Director at the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. His research topics are molecular organization, architectonic mapping and connectivity of the cerebral cortex, and transmitter receptors in brain diseases.

Day 4:  June 13^th, Wednesday, 2012

http://www.humanbrainmapping.org/i4a/pages/index.cfm?pageid=3459  

8:30-9:45      Morning workshop: Neural Repair as Changes in Network Connectivity: Using Computational Models of Brain Connectivity to Characterize Recovery from Injury and the Effects of Specific Interventions, Chair: Steven L. Small, University of California, Irvine, Departments of Neurology, Neurobiology & Behavior, and Cognitive Sciences Biological Sciences III, Irvine, CA, USA

1.       Network Recovery after Stroke: Dynamic Functional Reorganization of the Motor Execution Network after Stroke, Chaozhe Zhu, National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China

2.       Effects of Prenatal Focal Brain Injury on Reading-Related Functional Connectivity and Modular Organization, Anjali Raja Beharelle, Rotman Research Institute, University of Toronto, Toronto, ON, Canada

3.       New Insights into the Pathophysiology Underlying Motor Deficits and Recovery Thereof Using Models of Effective Connectivity, Christian Grefkes, Department of Neurology, University of Cologne, Köln, Germany

4.       Network Recovery after Stroke: Building Hand Motor and Aphasia Therapy on Physiological Data and Anatomical Connectivity, Ana Solodkin, Departments of Anatomy & Neurobiology and Neurology, University of California, Irvine, Irvine, CA, USA

10:00-10:45  Keynote lectures: Brain Plasticity-Based Therapeutics, Michael Merzenich, University of California, San Francisco, San Francisco, CA, USA

Lecture Abstract:

Neuroplasticity-based therapeutics strongly rely on the neurophysiological and brain imaging-based descriptions of neurological abnormalcy as it applies to specific clinical indications.  It also provides us with a powerful basis for confirming that a specific therapeutic approach is driving appropriate neurological 'corrections'.  A consideration of some of the basic principles guiding this therapeutic approach shall be a lead-in to a specific example (schizophrenia) for which this approach is being applied.

Biography:

Dr. Michael Merzenich is Professor Emeritus from the Keck Center for Integrative Neurosciences at the University of California at San Francisco, and the co-founder of three brain plasticity-based educational and medical software companies (Scientific Learning Corporation; Posit Science Corporation; Brain Plasticity Institute).  His research has focused on understanding the functional organization of sensory-perceptual-cognitive systems in mammalian brains, on brain plasticity phenomenology and mechanisms, on the contribution of brain plasticity to the expressions of neurological and psychiatric illness, and on the brain plasticity-based treatments of developmental and acquired impairments in children and adults.

11:00-12:30  Oral Sessions: O-W1: Disorders 2, Chair: Mirella Dapretto

11:00 - 11:15

90 WTh: Widespread brain hyper-connectivity in children with autism

Kaustubh Supekar, Stanford University School of Medicine, Stanford, United States

11:15 - 11:30

78 WTh: Robust prediction of autism diagnosis from brain responses to biological motion

Malin Bjornsdotter, Yale Child Study Center, New Haven, United States

11:30 - 11:45

342 WTh: The neural bases of reversal learning deficits in unmedicated schizophrenia patients

Florian Schlagenhauf, Charité Universitätsmedizin Berlin, Berlin, Germany

11:45 - 12:00

76 WTh: Underconnectivity of STS predicts socio-cognitive deficits in Autism

Kaat Alaerts, Katholieke Universiteit Leuven, ,

12:00 - 12:15

334 WTh: Aberrant inter-network connectivity reflects anterior insula activity and psychosis in schizophrenia

Andrei Manoliu, Klinikum Rechts der Isar, TU Munich, Munich, Germany

12:15 - 12:30

133 WTh: Altered Resting State Functional Connectivity in the Limbic System in Social Anxiety Disorder

Sheeba Anteraper, MIT

13:30-15:30  Poster Session (I’ll stand in front of the poster during this session)

15:45-17:00  Symposia: Cracking the Columnar-Level Code in the Visual Cortex with Ultra-High Field fMRI, Chair: Rainer Goebel, Maastricht Brain Imaging Center, Maastricht University, Maastricht, Limburg, Netherlands

1.    Columnar Organization of Object Features in Monkey Inferior Temporal Cortex Keiji Tanaka, Riken, Cognitive Brain Mapping Laboratory, Saitama, Japan

2.    Sub-Millimeter Functional MRI at 7 Tesla: Possibilities and Challenges David Norris, Donders Centre for Cognitive Neuroimaging, Nijmegen, Netherlands

3.    Mapping Columnar-Level Organizations in Human early Visual Areas with Ultra-High Field fMRI

4.    Essa Yacoub, Center for Magnetic Resonance Research, Department of Radiology University of Minnesota Medical School, Minneapolis, Minnesota, MN, USA

5.   Strategies for Mapping Unknown Feature Representations in Specialized Mid-Level Areas of the Human Visual Cortex Rainer Goebel, Maastricht Brain Imaging Center, Maastricht University, Maastricht, Limburg, Netherlands

17:15-18:00  Keynote lectures: Networks of Anatomical Covariance, Alan Evans, McGill University, Montreal, QC, Canada

Lecture Abstract:

The investigation of brain connectivity using either functional  (fMRI,PET) or white matter (DTI, DSI) metrics is now widespread. This talk will explore the potential for revealing brain connectivity via covariance of grey matter metrics (cortical thickness, cortical volume, grey matter density) in human development, disease and in rodent models.

Biography:

Alan Evans is James McGill Professor of Neurology, Psychiatry and Biomedical Engineering at McGill University.  Based at the Montreal Neurological Institute since 1984, he has extensive background in neuroimaging methodology with 400+ peer-reviewed publications.  His recent work has focused on structural connectivity, high-performance computing and multimodal databasing.

21:00-1:00  Club Night, LAN Club

Day 5:  June 14^th, Thursday, 2012

http://www.humanbrainmapping.org/i4a/pages/index.cfm?pageid=3459   

8:30-9:45    Morning workshop:  Where’s Your Signal? Explicit Spatial Models to Improve Interpretability and Sensitivity of Neuroimaging Results, Chair: Thomas E. Nichols, Dept of  Statistics, Warwick Manufacturing Group, Warwick University, Coventry, UK

1.       What the Mass Univariate Model Doesn't Tell You Thomas E. Nichols, Dept of Statistics, Warwick Manufacturing Group, Warwick University, Coventry, UK

2.       Bayesian Model Selection Under Spatial Uncertainty for Functional Imaging Studies Alexis Roche, CIBM-Siemens, Ecole Polytechnique Fédérale (EPFL), Lausanne, Switzerland

3.       Bayesian Spatial Point Process Modeling of Neuroimaging Data Timothy D. Johnson, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA

4.       New Tools for Tracking the Dynamics of Mental Representations Sam Gershman, Department of Psychology, Princeton University, Princeton, NJ, USA

10:00-10:45  Keynote lectures: Meta-Analytic Modeling of Human Neural Systems: Data-Driven Hypothesis Generation, Peter Fox, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA

Lecture Abstract:

Stereotactic coordinates provide a standard framework for reporting structural and functional neuroimaging results. Widespread adoption of this standard has created an extensive, diverse literature uniquely well-suited for large-scale data mining. In response, a family of statistical methods for coordinate-based meta-analysis (CBMA) have been developed. Collectively, CBMA methods provide data-driven hypothesis generation and neural system modeling, including emergent properties (e.g., meta-analytic connectivity maps). A particularly powerful application of CMBA is creation of models for constrained exploration of new primary data sets.

Biography:

Dr. Peter Fox is Director of the Research Imaging Institute and Professor of Radiology, Neurology, Psychiatry and Physiology at the University of Texas Health Science Center in San Antonio. After a residency in Neurology, Dr. Fox trained in functional brain imaging under Dr. Marcus Raichle at Washington University. Dr. Fox is the originator of the BrainMap project (www.brainmap.org), which includes the BrainMap database and a suite of tools for coordinate-based meta-analysis and neural-system modeling.

10:45-12:45  Poster Session (I’ll stand in front of the poster during this session)

14:00-15:30  Oral Session: O-Th2: Imaging Methods, Chair: Timothy Q. Duong

14:00 - 14:15

706 WTh: 'Investigating the temporal dynamics of resting state connectivity with MEG'

Adam Baker, University of Oxford, Oxford, United Kingdom

14:15 - 14:30

534 WTh: Human cortical layers detected with high resolution diffusion MRI at 9.4T

Alard Roebroeck, Maastricht University, Maastricht, Netherlands

14:30 - 14:45

665 WTh: In Vivo Human Brain Measurements of Axon Diameter Using 300 mT/m Maximum Gradient Strengths

Jennifer McNab, A.A. Martinos Center for Biomedical Imaging,

14:45 - 15:00

792 WTh: Quantification of dopamine in the human striatum in anatomical and connectivity derived subdivisions

Andri Tziortzi, University of Oxford

15:00 - 15:15

653 WTh: Automatic HARDI White Matter Tract Labeling with Multiple Atlas Fusion

Yan Jin, University of California, Los Angeles, Los Angeles, United States

15:15 - 15:30

595 WTh: Resting State fMRI Predicts Task Activation of Individual Subjects

Prantik Kundu, NIMH