Brain Mapping seminar abstracts 2007-08
Andrew Maudsley, Ph.D.
Professor of Radiology, University of Miami
Wednesday, 09/12/07, noon, MGH bldg 149
Metabolic Mapping in Brain by Volumetric Proton MRSI
Distributions of magnetic-resonance observable metabolites in the brain
can be efficiently mapped using volumetric MR Spectroscopic Imaging
(MRSI) with echo-planar readout. The efficient processing of this data
can, however, represent a challenge in light of the large amounts of
data and the non-ideal characteristics of in vivo spectra. In this
presentation a MRSI data processing environment will be described that
integrates and automates multiple processing and analysis functions for
imaging of proton metabolite distributions in the normal human brain.
The image reconstruction methods make use of several sources of prior
information, including MRI-derived tissue segmentation, morphological
analysis, and spectral characteristics of the observed metabolites.
Additional capabilities include normalization of metabolite signal
intensities and transformation into a common spatial reference frame,
thereby enabling the formation of a database of MR-measured human
metabolite values as a function of acquisition, spatial, and subject
parameters. This development is carried out under the MIDAS project
(Metabolite Imaging and Data Analysis System). The analysis of multiple
normal subject data demonstrate considerable heterogeneity of metabolite
distributions in the brain, and preliminary results for clinical studies
indicate that considerable advantage can be gained by performing
voxel-based comparisons of individual subject data against normal
Penelope Kostopoulos, Ph.D.
Wednesday, 09/19/07, noon, MGH bldg 149
The Ventrolateral Prefrontal Cortex and Memory Disambiguation
Although it is widely known that the prefrontal cortex plays a role in
memory, the specific contribution of particular prefrontal regions in
mnemonic functions remains controversial. A series of fMRI experiments
were conducted to examine the specific role of the mid-ventrolateral
prefrontal cortex in memory retrieval. It was hypothesized that, when
stimuli in memory are related to each other with multiple associations and
familiarity, strong stimulus-stimulus links or contextual cues are not
sufficient for successful retrieval, control processing emanating from the
mid-ventrolateral prefrontal cortex is required to disambiguate and select
the appropriate information among memory traces. This type of retrieval is
referred to as active retrieval to contrast it to automatic retrieval that
depends on the simple re-activation of memory traces. Specific increases
in activity were reported within the mid-ventrolateral prefrontal areas 45
and 47/12 during the performance of active retrieval tasks using visual,
tactile, and auditory stimuli. These results indicate that the
mid-ventrolateral prefrontal cortex plays a specific role in the
disambiguation of information in memory for the active retrieval of
relevant mnemonic information.
Amit Anand, M.D.
Associate Professor of Psychiatry and Radiology,
Indiana University School of Medicine
Wednesday, 09/26/07, 4pm, MIT bldg 46
Novel Techniques for Imaging the Mood Regulating Circuit:
Implications for the Diagnosis and Treatment of Depression
Recent neuroscience research indicates that brain functions, particularly higher
brain functions such as emotion, which are implicated in psychiatric illnesses, are
represented in circuits and distributed networks rather than in localized brain
regions. In a series of studies, for which data will be presented, we have developed
fMRI methods to measure local activation and distributed connectivity within the
putative cortico-striatal-thalmaic-amygdalar mood regulating circuit (MRC). We have
shown, with open-labeled antidepressant treatment, that decreased cortico-limbic
connectivity and increased limbic activation is present in depression and that these
abnormalities are reversed with antidepressant treatment. These techniques could
potentially be used to predict and monitor the effects of both pharmacological and
non-pharmacological treatments for depression.
Robert Handa, Ph.D. & Stuart Tobet, Ph.D.
Professors of Biomedical Sciences, Colorado State University
Wednesday, 10/03/07, noon, MGH bldg 149
Brain Sexual Differentiation: Inside stories...
Steroid hormones dramatically influence the development of numerous sites in
the nervous system. Basic mechanisms in neural development provide foci for
understanding how factors related to sex can alter the ontogeny of these
regions. Sex differences in neurogenesis, cell migration, cell differentiation,
cell death, and synaptogenesis are being addressed. Any and all of these events
serve as likely targets for genetic or gonadal steroid-dependent mechanisms
throughout development. Sex differences in the positioning of cells in the
developing hypothalamus further suggest that cell migration may be one key
target for early gene actions that impact long-term susceptibility to brain
sexual differentiation. Estrogens have numerous effects on the brain, both in
adulthood and during development. These actions of estrogen are mediated by at
least two distinct estrogen receptor (ER) systems, ER alpha (ERα) and ER
beta (ERβ). In brain, ERα plays a critical role in regulating
reproductive neuroendocrine function and behavior, however, a definitive role
for ERβ in any neurobiological function has been slow in forthcoming.
Clues to the function of ERβ in the central nervous system can be gleaned
from the neuroanatomical distribution of ERβ and the phenotypes of neurons
that express ERβ. ERβ immunoreactivity has been found in populations
of GnRH, CRH, vasopressin, oxytocin and prolactin containing neurons in the
hypothalamus. Utilizing subtype-selective estrogen receptor agonists can help
determine the roles for ERβ in a number of sex-dependent behaviors in rat
Nicholas Ayache, Ph.D.
Research director, INRIA/ASCLEPIOS,
Wednesday, 10/10/07, noon, MGH bldg 149
Computational Models of the Human Body for Medical Image Analysis
Medical image analysis brings about a revolution to the medicine of
the 21st century, introducing a collection of powerful new tools
designed to better assist the clinical diagnosis and to model,
simulate, and guide more efficiently the patient's therapy. A new
discipline has emerged in computer science, closely related to others
like computer vision, computer graphics, artificial intelligence and
In this talk, I describe the increasing role of computational models
of anatomy and physiology to guide the interpretation of complex
series of medical images, and illustrate my presentation with three
applications: 1) statistical modeling and analysis of sulcal lines on
the brain cortex; 2) modeling and simulation of brain tumors
evolution; 3) electro-mechanical modeling of the heart function for
therapy planning and simulation. I conclude with some promising
trends, including the analysis of in vivo confocal microscopic images.
Scott Hoge, Ph.D.
Instructor of Radiology,
Brigham and Women's Hospital and Harvard Medical School
Wednesday, 10/17/07, noon, MGH bldg 149
Combining GRAPPA and SENSE to Improve Parallel MR Imaging
This talk will present a review of parallel MR imaging to illustrate
the similarities and differences between the two dominant
reconstruction algorithms: GRAPPA and SENSE. The inherent strengths
of these methods are complementary, which allows one to combine them
to great effect. We will demonstrate two such combinations: the use
of GRAPPA to enable self-referenced SENSE reconstructions using very
few auto-calibration lines, and the use of each algorithm in different
temporal-frequency bands associated with UNFOLD. These examples
demonstrate that, in certain cases, the combination of SENSE and
GRAPPA will produce higher image quality than either method can
Bruce Rosen, M.D., Ph.D.
Director, Martinos Center for Biomedical Imaging
Wednesday, 10/24/07, noon, MGH bldg 149
Functional Magnetic Resonance Imaging: An Historical Perspective
Paul M. Matthews, M.D., D.Phil.
Vice-President for Imaging, Genetics and Neurology, GlaxoSmithKline, UK
Wednesday, 10/31/07, noon, MGH bldg 149
Unravelling Single Gene Contributions to Brain Structure: Hope or Hype
The likely heritability of structure has been well-defined and is substantial. There has been hope that, as a "endophenotype", structural brain imaging could enhance the power of genetic association studies. Defining specific genes that contribute to brain structure should allow more detailed appreciation for mechanisms contributing to the heritability of intelligence and other quantitative traits, as well as providing insight into mechanisms of some brain disorders. In this lecture, the potential for integrated genetics and imaging to provide insight into genes that contribute to neurodegeneration is illustrated by a study of ApoE4 in Alzheimer’s disease. Evidence for novel genetic associations with brain structural variation in a population without neurological disease also is presented. Current problems with study power and validation will be highlighted.
Chun-yu Yip, Ph.D.
Electrical Engineering and Computer Science, University of Michigan
Monday, 11/12/07, 12:30pm, MGH bldg 149
RF Pulse Designs for Signal Recovery in T2*-Weighted Functional MRI
In blood-oxygenation-level-dependent (BOLD) functional magnetic resonance
imaging (fMRI) using T2* contrast, images suffer from loss of signals at
brain regions close to the air-filled cavities in the human head. The
artifact arises from magnetic field distortion caused by the magnetic
susceptibility difference between air and brain tissues, and hampers
functional studies of important brain regions such as the orbito-frontal
cortex. In this research project, I investigate two methods of designing
radio-frequency (RF) pulses that can recover the signal loss. In addition to
slice selective excitation, both pulse designs ``precompensate'' the
through-plane dephasing that occurs between excitation and data acquisition.
One method, which utilizes ``three-dimensional tailored RF pulses'',
achieves these goals via three-dimensional spatially selective excitation.
The other method uses spectral-spatial selective excitation, and relies on
the assumption that through-plane dephasing is correlated with resonance
frequency offset. All these sophisticated pulses are numerically designed
using the iterative conjugate gradient method. To facilitate those design
methods, I also propose new techniques applicable to general pulse designs,
such as frameworks for pulse computation acceleration and joint design of
excitation k-space trajectory and RF pulse. With phantom and human
experiments, I demonstrate that the methods are efficacious in signal
recovery, but not without costs and hurdles to overcome.
Peter Caravan, Ph.D.
Instructor in Radiology at Harvard Medical School
Wednesday, 11/14/07, noon, MGH bldg 149
Molecular MRI of Myocardial Collagen
Molecular MR imaging is attractive from a number of
standpoints. It combines biochemical information with the high
spatial resolution, deep tissue penetration, and excellent soft
tissue contrast inherent in MRI. The molecular information yielded
can be combined with anatomical and functional data acquired in the
same exam. Molecular MRI uses stable isotopes which means the probes
can be prepared in advance, used at any time, and exhibit no ionizing
radiation. The major drawback is sensitivity of the probe.
Typically micromolar (~nmol per gram tissue) concentrations are
required to elicit contrast. To overcome this sensitivity issue,
large assemblies of metal ions have been used, e.g. MION, polymeric
agents, but the large size of these agents impacts their
pharmacokinetics and tissue penetration. An alternate approach is to
identify high concentration molecular targets of relevance. In this
presentation myocardial collagen is targeted in order to assess
First-pass contrast enhanced MRI for the study of myocardial
perfusion and the assessment of coronary artery disease is a powerful
technique, but the imaging tradeoffs necessitated by ultrafast
imaging limit the degree of resolution and spatial coverage that can
be obtained. Moreover the patient must be stressed while inside the
magnet, two injections of contrast are required, and a time consuming
data analysis is required. We sought an MR contrast agent that could
be administered during stress and that provided persistent high
resolution images reflective of blood flow at stress, i.e. combine
the ease of nuclear cardiology with the much higher resolution of
steady-state MRI. We hypothesized that interstitial myocardial
collagen, present at levels compatible with detection by gadolinium
enhanced MR, could act as a reservoir for a targeted MR contrast
agent that distributed as a function of perfusion.
This presentation describes design, synthesis, and characterization
of a gadolinium-based, type I collagen-targeted molecular MR
contrast agent and reports its proof of concept in a porcine model of
critical coronary stenosis.
Richard Leahy, Ph.D.
Professor of Electrical Engineering, Biomedical Engineering and Radiology,
University of Southern California
Wednesday, 11/28/07, noon, MGH bldg 149
Combining Cortical and Volumetric Analysis of the Human Brain
Intersubject registration of anatomical MR images is a necessary step in group analysis of structural and functional neuroimaging studies. Statistical power for detecting cortical effects can be enhanced by ensuring alignment of sulcal features, either through the use of explicit landmarks or through curvature matching. I will describe the approach we have taken to registration of cortical surfaces based on a set of sulcal curves, and the interactive computational tools we have developed for this purpose. I will also describe an extension of this approach to volumetric registration in which we use an initial surface alignment to ensure a one-to-one mapping between cortices while aligning subcortical structures through a combination of harmonic mapping and elastic energy minimization.
Ona Wu, Ph.D.
Instructor in Radiology at Harvard Medical School
Wednesday, 12/05/07, 4pm, MIT bldg 46
MRI-Based Imaging Models of Infarction after Acute Stroke
Stroke is a leading cause of death and morbidity in the US. Currently, the only FDA approved pharmaceutical intervention for the treatment of acute human ischemic stroke is thrombolysis with intravenous recombinant tissue plasminogen activator (rt-PA) administered within 3 h of stoke onset. Beyond this time frame, reduced clinical efficacy along with an increased risk of worsened outcome has been observed, and therefore rt-PA has been used cautiously. On the other hand, this 3h time window has been argued to be too narrow, unnecessarily excluding patients. An imaging tissue signature that can identify patients who will maximally benefit from treatment, or alternatively, who are at high risk of developing intracerebral hemorrhage, would provide a tremendous advance in patient management. Towards this goal, using supervised learning algorithms and acute MRI, we (1) developed tissue signature algorithms to predict infarction under natural history conditions, e.g. no rt-PA, (2) assessed efficacy of these natural history models for identifying treatment-induced changes in patients given rt-PA, and (3) developed treatment models to predict response to different therapies prior to administration. Using a generalized linear model (GLM), we combined multiple acute MRI data, such as diffusion-weighted and perfusion-weighted MRI. We were able to predict tissue outcome for natural history acute stroke patients and for experimental rat stroke models with high accuracy. Demonstrating the sensitivity of the algorithms for detecting an alteration in the natural progression of the ischemic cascade, the performance of the models was significantly reduced for the rt-PA group compared with the non-thrombolysed group. Using the GLM to predict outcome for different therapies, e.g. rt-PA or normobaric hyperoxia, the treatment models were fond to perform more accurately in patients who received treatment, with the estimated risk of infarction reduced compared to the risk maps produced by the natural history model. These results show that tissue signature maps generated with MRI-based statistical algorithms are promising metrics for diagnosis, prognosis and therapeutic evaluation after acute stroke that can translate readily from preclinical to clinical settings and a key step towards personalized medicine.
Mike Fox, Ph.D.
Department of Radiology, Washington University
Wednesday, 12/12/07, noon, MGH bldg 149
Spontaneous brain activity and variability in human behavior
The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. Spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging are a potentially important and revealing manifestation of spontaneous neuronal activity. These studies have provided insight into the intrinsic functional architecture of the brain, variability in measured brain responses, and most recently variability in human behavior.
Chris Cocosco, M.Eng.
Image Sciences Institute, Utrecht University
Monday, 12/17/07, 10am, MGH bldg 149, research affairs room A
Automatic Image-Driven Segmentation of Medical Magnetic
Resonance Images Without Prior Appearance Models
The focus of the presentation will be on original
contributions in methods for the automatic segmentation of
Magnetic Resonance Images (MRI) of the human head and
heart. These methods achieve the segmentation without using
previously trained image appearance or object shape models,
and employ imperfectly supervised non-parametric classifiers
and graph algorithms. The presentation will also include a
brief overview of other past research.
Daniel C. Javitt, M.D., Ph.D.
Professor of Psychiatry and Neuroscience,
New York University School of Medicine and
Nathan Kline Institute for Psychiatric Research
Wednesday, 01/16/08, noon, MGH bldg 149
Bottom up contributions to cognitive dysfunction in schizophrenia
Schizophrenia is associated with cognitive deficits that represent a core component of the disorder. Deficits have been extensively documented in domains such as executive processing, working memory, and learning/declarative memory formation, which localize to high-level cortical regions such as frontal cortex or hippocampus. In contrast, integrity of sensory processing in schizophrenia is less well appreciated. This presentation will present recent work demonstrating impairments in early stage visual and auditory processing in schizophrenia, and will highlight contributions of low level sensory processing deficits to more holistic processes such as perceptual closure, reading and voice emotion recognition. Overall patterns of neurocognitive dysfunctions will be discussed relative to predictions of the PCP/NMDA model and other glutamatergic conceptualizations of schizophrenia.
Diego Contreras, M.D., Ph.D.
Associate Professor of Neuroscience, University of Pennsylvania
Wednesday, 01/16/08, 3pm, MGH bldg 149
Input Integration in Different Network States Studied with
Intracellular and Optical Recordings in Vivo
Intracellular recordings from thalamus and cortex in the rat
whisker-barrel system reveal that synaptic inputs originating from
separate whiskers may add sublinearly or suppress each other depending on
the stimulation interval. The suppression is due to lateral inhibition in
thalamus and not in cortex. Current source density analysis reveals that
the rules of summation do not change after cortical inactivation but the
time course of suppression is reduced when anesthesia level is reduced.
Voltage sensitive dyes provide support to the integration rules revealed
with intracellular recordings and compare the differences between the
depolarizing and hyperpolarizing phases of the slow oscillation.
Sylvain Baillet, Ph.D.
Head, Neuroimaging Group, Centre National de la Recherche Scientifique
Wednesday, 01/23/08, noon, MGH bldg 149
Mapping and Tracking the Flow of Brain Activity using MEG/EEG: Hypothesis
The exquisite temporal resolution of electromagnetic measurements using MEG
and EEG combined with anatomical MRI leads to high-density sequences of
images of brain activity. The analysis and appraisal of such data are
high-dimensional and not deprived of subjectivity.
We develop the concept of 'cortical flow' as a methodological extension to
the empirical description of fast activity that unfolds onto the cortical
surface, as revealed by MRI-constrained electromagnetic brain imaging. The
methods involved include the computation of the optical flow of 3D manifolds
and the detection of metastable episodes in the large-scale dynamics of
We show how this concept relates to empirical investigations on
'microstates' and computational models of neural ensembles.
Time permitting, we would also like to discuss our recent developments on
anatomical coregistration based on the diffeomorphic matching of brain
surfaces based on their respective sulcal imprint.
David Salat, Ph.D.
Assistant Professor in Radiology at Harvard Medical School
Wednesday, 01/30/08, 4pm, MIT bldg 46
A Review of Diffusion Tensor Imaging Studies of Aging and Alzheimer's Disease
There is strong interest in the use of diffusion tensor imaging (DTI) for
the study of brain anatomy and pathology. DTI has been particularly
important in the characterization of changes in brain tissue integrity with
aging and age associated neurological disease. Recent data demonstrate the
potential for DTI to provide useful metrics in the basic and clinical
aspects of a variety of aspects of these conditions; however, controversies
exist about the biological significance of diffusion measures as well as the
technical aspects of DTI analysis. Thus, a variety of questions remain about
how DTI can best be utilized to understand age associated neural change.
This Brainmap will review the current literature utilizing DTI in the study
of aging and Alzheimer's disease, and will present some recent data on this
topic. Specifically, we utilized DTI to examine tissue changes in
individuals with Alzheimer.s Disease and find a network of tissue pathology
in that exceeds and complements more commonly employed prior imaging
methods. Overall, although limitations remain, this review demonstrates that
a wide range of information can be obtained from current DTI procedures, and
that these various metrics could provide important information about disease
Mary Phillips, M.D.
Co-Director, Brain Imaging Research Center, Carnegie Mellon University and University of Pittsburgh
Professor of Clinical Affective Neuroscience, Department of Psychological Medicine, Cardiff University
Wednesday, 02/06/08, noon, MGH bldg 149
Imaging Emotion in the Brain: from Normal Emotion to Abnormal Mood States
My long-term research goal is to identify specific functional abnormalities in neural systems underlying the different subprocesses important for emotion perception and emotion regulation that may be present as biomarkers of major psychiatric disorders, including bipolar disorder, unipolar depression, schizophrenia and anxiety disorders. The identification of these neural markers of psychiatric disorder is, I believe, a crucially important step toward the long-term goal of improving diagnostic accuracy with the use of reliable biomarkers in individuals presenting in the early stages of psychiatric illness. In the presentation, I will describe data from my research groups in Pittsburgh and the UK indicating functional and structural abnormalities in neural systems underlying different component processes of emotion perception that may distinguish individuals with different mood disorders, such as bipolar disorder and unipolar depression. I will also present data from my research group in Pittsburgh, where we have begun to examine the extent to which these neuroimaging markers may be present in individuals at high genetic risk of subsequently developing bipolar disorder and unipolar depression to aid the identification of potential risk markers of disorder development. I will finally present data from a provisional, naturalistic treatment study of unipolar depression, where the focus has been examination of the extent to which neuroimaging markers of dysfunction in neural systems underlying the different component processes of emotion processing may act as predictors of response to specific treatments.
Lisa Feldman Barrett, Ph.D.
Professor of Psychology, Boston College
Wednesday, 02/13/07, noon, MGH bldg 149
What is an emotion?
Hesheng Liu, Ph.D.
Research Fellow in Radiology at Harvard Medical School
Wednesday, 02/20/08, noon, MGH bldg 149
Functional Mapping Using fMRI, fcMRI, iEEG, and MEG/EEG -- Preliminary
Findings with Motor Mapping, Visual Selectivity and Memory Retrieval
Several functional mapping techniques were employed on
surgical patients and normal subjects. In the first part of this talk,
I evaluate the feasibility of resting state fMRI (fcMRI) for task-free
pre-surgical functional mapping. This new approach may be
useful for the patients who are unable to perform tasks in the scanner, or
who require several functional maps in one session. In the second part,
I will show preliminary results from a visual object recognition study using
intracranial EEG (iEEG). Our findings indicate that the temporal lobe shows
selectivity to multiple object categories. The selectivity is invariant when
the size and orientation of the objects change. The selectivity also remains
when patients are viewing dynamic pictures. In the final part, I will
discuss a fMRI, MEG, EEG study of episodic memory retrieval.
Carl Schwartz, M.D.
Director, Developmental Neuroimaging and Psychopathology Research
Laboratory, Harvard Medical School Department of Psychiatry at MGH/Martinos
Wednesday, 02/27/08, noon, MGH bldg 149
Infant temperament, Adolescent psychiatric disorder, and Neuroimaging:
Pitfalls and Possibilities
Temperament refers to the individual differences in emotions, cognitions, and behaviors based on biology that are first observed in infancy or early childhood.
Temperament is important because of its role in both normative development and as a risk factor for psychiatric disorder. We review our earlier studies of the relationship between childhood temperament and adolescent anxiety disorder. We then discuss fMRI studies from our lab that offer insights into the neural bases of differences in temperament. We will discuss inhibited temperament as a putative endophenotype for anxiety disorder, and the potential benefit of such an approach to other psychiatric illnesses including depression and autism. Possible pathways from temperament to disorder will be discussed. Limitations and potential fallacies in common experimental designs for fMRI, and as well as implications for psychiatric diagnosis and treatment will be discussed.
Chris B. Schaffer, Ph.D.
Assistant Professor of Biomedical Engineering, Cornell University
Wednesday, 03/05/08, noon, MGH bldg 149
All-Optical Animal Models of Small-Scale Stroke
Clinical evidence shows that ischemic and hemorrhagic
microvascular lesions in the brain play an important role in elderly
dementia, but few effective treatment or preventative strategies exist.
This deficit is due, in part, to a lack of good animal models of these
small-scale strokes that would allow the progression of disease to be
studied and would provide a platform for the evaluation of therapeutics.
Here, we use advanced optical techniques to induce single-vessel
occlusions and hemorrhages in the cortex of live, anesthetized rodents,
as a means to provide a comprehensive animal model of small-scale
stroke. A tightly-focused femtosecond laser pulse is used to deposit
laser energy into the endothelial cells that line a specifically
targeted vessel causing an injury that triggers clotting or causes
hemorrhage, but only in the targeted vessel. This technique allows any
blood vessel, including individual arterioles, capillaries, and venules,
in the top 0.5 mm of the cortex of a rodent to be selectively lesioned.
We also use optical techniques, such as two-photon excited fluorescence
microscopy, to study the physiological consequences of these occlusions.
To date, we have investigated how blood flow reroutes after the
occlusion of a single vessel for clots located at different positions in
the vascular hierarchy. This study has pointed to the extreme
vulnerability of cortical perfusion to occlusions in penetrating
arterioles and to the remarkable robustness of the cortical surface
arteriole network. Ongoing work aims at determining the effect of
microvascular lesions on the health and functionality of nearby brain
Earl Miller, Ph.D.
Picower Professor of Neuroscience,
The Picower Institute for Learning and Memory and Department of Brain and
Cognitive Sciences, Massachusetts Institute of Technology
Wednesday, 03/12/08, noon, MGH bldg 149
Rules, Concepts, and Executive Brain Functions
What controls your thoughts? How do you focus attention? How do you know
how to act while dining in a restaurant? This is cognitive control, the
ability to organize thought and action around goals. I will present
theories and evidence on how this arises from interactions between cortical
areas (especially the prefrontal cortex) and the basal ganglia. Results
from our laboratory have in these areas have properties commensurate with a
role in "executive" brain function. They are involved in directing
attention, in recalling stored memories, predicting reward value, and they
integrate the diverse information needed for a given goal. Perhaps most
importantly, they transmit acquired knowledge. Their activity reflects
learned task contingencies, concepts and rules. In short, they seem to
underlie our internal representations of the "rules of the game" needed for
Leonid Perlovsky, Ph.D.
Harvard University and Air Force Research Lab
Wednesday, 03/19/08, noon, MGH bldg 149
Language, Cognition, and Cultural Evolution
What are the mechanisms of interaction between language and
cognition? The talk briefly reviews past mathematical difficulties of
modeling the mind and new mathematical techniques of dynamic logic
and neural modeling fields, which overcome these difficulties.
Mechanisms of concepts, emotions, instincts, imaginations, intuitions
are described; they are inseparable from perception and cognition.
Engineering applications illustrate orders of magnitude improvement
in pattern recognition, data mining, fusion, financial predictions.
Dynamic logic is extended to language and mechanisms of joint
operations of language and cognition. It turned out those human
abilities could only evolve jointly.
The last part of the talk moves to future research directions: roles
of beautiful, music, sublime in the mind, cognition, and evolution. I
relate dynamic logic to the knowledge instinct, which drives the mind
to understand the world, and argue that instinct is even more
important than sex or food. Two mechanisms of the knowledge instinct,
differentiation and synthesis determine evolution of cultures, and
explain two types of cultural evolutions. The knowledge-acquiring
cultures leading to science and technology, but doubting their
values, and stagnating cultures investing their limited amount of
knowledge with ever increasing emotional value. English language
leads to the first type of culture, and Arabic language leads to the
second type. The Nobel Prize in Economics, 2003 is related to the
Biblical story of the fall. Mathematical models of the mind and
cultures bear on contemporary world, and may be used to improve
mutual understanding among peoples around the globe and reduce
tensions between cultures.
James Gee, Ph.D.
Associate Professor of Radiologic Science and Computer and Information Science,
University of Pennsylvania
Wednesday, 03/26/08, 4pm, MIT bldg 46
Structure-Specific Normalization and Analysis for Multi-Modality
In multi-subject structural, functional or diffusion-weighted MRI studies,
it is common to analyze the imaging data using whole-brain approaches, such
as voxel-based or deformation-based morphometry. Whole-brain analysis is a
powerful tool for exploratory research, but in studies where there are a
priori hypotheses about individual anatomical structures, a more
structure-centric approach to image analysis may be appropriate. This is
especially true for complex structures such as the hippocampus, which tend
to not be adequately normalized by whole-brain techniques. This talk will
focus on recent work at Penn that uses deformable geometrical models as a
framework for shape-based normalization, smoothing and analysis of
individual anatomical structures. Several applications will be discussed,
including a new detailed atlas of the hippocampus derived from high-field
postmortem MRI; hippocampus-specific analysis of fMRI activation in memory
tasks, as applied to predicting memory outcome in epilepsy surgery; and a
new surface-based framework for DTI analysis.
Anna Devor, Ph.D.
Assistant Adjunct Professor,
Department of Neurosciences and Department of Radiology,
University of California San Diego
Friday, 04/04/08, noon, MGH bldg 149 (conf. room A, 1st floor)
Evidence that Neuronal Signaling and not Energy Consumption Controls the
We examined bilateral neuronal and hemodynamic changes, and glucose uptake
in response to a unilateral somatosensory stimulus in rat primary
somatosensory cortex (SI). In contrast to the contralateral forepaw area
where neuronal activity, blood oxygenation/flow and glucose uptake increased
in unison, we observed blood oxygenation/flow decrease and arteriolar
vasoconstriction in presence of increased glucose uptake in the ipsilateral
SI. Voltage-sensitive dyes measurements revealed sequential de- and
hyperpolarization with a comparable amplitude bilaterally. Ipsilateral
hyperpolarization was stronger, suggesting stronger recruitment of
inhibitory interneurons in ensemble response. Laminar electrophysiological
recordings revealed an increase in ipsilateral spiking consistent with the
observed increase in glucose uptake. The vasoconstriction and decrease in
blood flow in presence of an increase in both neuronal spiking and glucose
uptake in ipsilateral SI argues against feed back signaling by energy
metabolites. Rather, our results are consistent with feed forward neuronal
control of vasodilation and vasoconstriction.
Dmitriy Yablonskiy, Ph.D.
Professor of Radiology and Physics, Washington University in St. Louis
Wednesday, 04/09/08, noon, MGH bldg 149
Quantitative BOLD: Mapping of Human Cerebral Deoxyhemoglobin-Containing Blood
Volume and Oxygen Extraction Fraction
Since fundamental discovery by Ogawa and co-workers of BOLD contrast in MRI substantial progress has been achieved in understanding the nature and mechanisms underlying the BOLD signal. However, most work has been directed at the study of dynamic BOLD temporal changes in the MRI signal during functional activation. At the same time, very little attention has been paid to studying the nature and mechanisms of BOLD contrast in the resting (baseline) state of brain activity which can be described as a default mode of the brain activity.
Quantitative evaluation of brain hemodynamics in the baseline state is important for understanding normal human brain functioning as well as understanding the pathophysiology of disorders such as stroke, Alzheimers disease, Huntingtons disease, Parkinsons disease and other neurological disorders. It can also be of great importance for evaluation of hypoxia within tumors of the brain and other organs. Currently, clinically accepted methods for measuring cerebral blood flow (CBF) and oxygen extraction fraction (OEF) main parameters characterizing brain hemodynamics rely on PET techniques.
In my presentation I will describe a technique for in vivo quantitative evaluation of brain hemodynamic parameters that has been under development in our laboratory. The technique quantitative BOLD (qBOLD) is based on BOLD phenomena and allows quantitative measurements of OEF and deoxyhemoglobin containing blood volume (DBV).
Phillip Zhe Sun, Ph.D.
Assistant Professor in Radiology at Harvard Medical School
Wednesday, 04/16/08, noon, MGH bldg 149
Imaging pH Using Chemical Exchange-Dependent Saturation Transfer (CEST) MRI
Chemical exchange saturation transfer (CEST) MRI, first proposed by
Ward and Balaban, offers a remarkably sensitive detection mechanism that
allows characterization of dilute proteins/peptides and microenvironment
properties. For instance, CEST agents that are sensitive to tissue energy
metabolites/byproducts including glucose, glycogen and lactate as well as pH
and temperature have been reported. Given that CEST imaging is capable of
capturing cellular and molecular events that are often inaccessible by
conventional MRI, it may significantly enhance our understanding of tissue
pathophysiology and thus, holds great promise for developing therapeutics
and guiding treatments. In fact, in vivo amide proton transfer (APT) MRI, a
variant of CEST MRI, has been shown sensitive to ischemic tissue acidosis
and tumor proteins/peptides content change, and thus, complementing the
conventional MRI approach. While on the other hand, it is also known that
CEST MRI is susceptible to concomitant RF irradiation and field
inhomogeneity artifacts and varies with experimental conditions, and
consequently, the sensitivity and specificity of CEST MRI is not optimal. To
overcome these limitations, we have developed analytical and numerical
models to quantitatively describe the CEST contrast, proposed concise
correction algorithms for minimizing measurement errors, and ultimately
demonstrated absolute pH imaging using CEST MRI. Recently, we have further
exploited in vivo CEST MRI and showed that tissue acidosis, assessed by APT
MRI, serves as a metabolic imaging marker for disrupted oxygen/glucose
metabolism and can help predict final tissue infarction, augmenting the
commonly used perfusion and diffusion MRI methods. Principles of CEST MRI
and its in vivo applications will be presented.
Douglas C. Noll
Ann and Robert H. Lurie Professor and Chair of Biomedical Engineering,
Co-Director, Functional MRI Laboratory,
University of Michigan at Ann Arbor
Wednesday, 04/23/08, noon, MGH bldg 149
Better Images of the Thinking Brain:
Advances in Image Reconstruction and Motion Correction
Magnetic susceptibility, the material property of becoming magnetized in response to an applied magnetic field, plays a fundamental role in the generation of the desired signal in the most common form of using magnetic resonance imaging (MRI) to image human brain function (functional MRI or fMRI). Unfortunately, magnetic susceptibility is also a major source of static image distortions as well as dynamic signal variations the limit functional MRI. In this talk, I will describe how susceptibility leads to both spatially distorted images, signal losses in certain regions of the brain, and increased image variability due to head motion. We have developed MRI acquisition and image reconstruction approaches that individually and together can reduce these effects. The image reconstruction approaches follow a general framework of modeling the physical processes and iteratively estimating the object as well as the distorting processes. This provides dynamic estimates that qualitatively improve overall image appearance and quantitatively more robust corrections for head motion.
Martin Styner, Ph.D.
Research assistant professor of Computer Science, University of North Carolina
Wednesday, 04/30/08, 4pm, MIT bldg 46
DTI Analysis in the Developing Brain of Humans and Non-Human Primates
Diffusion tensor imaging (DTI) has become increasingly important as a means
of investigating the structure and properties of neural white matter, with
many applications in our own research in the developing brain of humans and
macaque monkeys. Several analysis frameworks have been proposed, such as
region based, voxel-based as well as fiber tract based framework.
I will present our current work in this field using both fiber tract and
region based analysis. These methods will be illustrated in applications of
normal brain development in rhesus macaques, as well as neonatal white
matter pathology in Krabbe's disease. I will further describe two ongoing
development efforts: a) towards an automated analysis of atlas based,
parametrized DTI fiber tracts and b) the use of DTI based connectivity
information as the basis for a novel, population based cortical
David Poeppel, Ph.D.
Professor of Biology and Linguistics,
Neuroscience and Cognitive Science Program,
University of Maryland College Park
Friday, 05/02/08, noon, MGH bldg 149
Temporal Primitives in Auditory Cognition and Speech Perception
Generating usable internal representations of speech input, or
an auditory scene more generally, requires, among other
operations, fractionating the signals into temporal units/chunks
of the appropriate granularity. Adopting (and adapting) Marr's
approach to vision, a perspective is outlined that formulates
linking hypotheses between specific neurobiological mechanisms
(for example cortical oscillations and phase-locking) and the
representations that underlie auditory cognition (for example
syllables). Focusing on the implementational and algorithmic
levels of description, I argue that the perception of sound
patterns requires a multi-time resolution analysis. In
particular, recent experimental data from psychophysics, MEG
(Luo & Poeppel, 2007), and concurrent EEG/fMRI (Giraud et al.,
2007) suggest that there exist two privileged time scales that
form the basis for constructing elementary auditory percepts.
These "temporal primitives" permit the construction of the
internal representations that mediate the analysis of speech and
other acoustic signals.
Helen Mayberg, M.D.
Professor of Psychiatry, Emory University
Wednesday, 05/14/08, noon, MGH bldg 149
Modulating Putative Depression Circuits Using Deep Brain Stimulation
Critical to development of deep brain stimulation (DBS) as a novel therapy
for intractable depression, has been the evolving understanding of brain
systems mediating normal and abnormal mood states and the ongoing,
systematic characterization of neural substrates mediating successful and
unsuccessful response to other antidepressant interventions. Based on
previous work implicating the subcallosal cingulate (Brodmann Area 25) and
its functional connections to specific paralimbic, cortical and subcortical
regions in the pathophysiology of depression and antidepressant response
mechanisms, we have piloted the use of chronic high frequency DBS to
modulate BA25 connectivity in patients with treatment resistant depression.
The theoretical and data-driven foundation for developing this new procedure
as well as long-term clinical, neuropsychological and imaging findings from
two ongoing experimental studies will be presented.
Wolf-Dieter Heiss, M.D.
Professor of Neurology
University of Cologne
Wednesday, 05/21/08, noon, MGH bldg 149
Multimodal Functional Imaging by PET in Gliomas: Pathophysiology and
Imaging in patients with brain tumors aims toward the determination of the
localization, extend, type, and malignancy of the tumor. Imaging is being
used for primary diagnosis, planning of treatment including placement of
stereotaxic biopsy, resection, radiation, guided application of
experimental therapeutics, and delineation of tumor from functionally
important neuronal tissue. After treatment, imaging is being used to
quantify the treatment response and the extent of residual tumor. At
follow-up, imaging helps to determine tumor progression and to
differentiate recurrent tumor growth from treatment-induced tissue
changes, such as radiation necrosis. A variety of complementary imaging
methods are currently being used to obtain all the information necessary
to achieve the abovementioned goals. Computed tomography and magnetic
resonance imaging (MRI) reveal mostly anatomical information on the tumor,
whereas magnetic resonance spectroscopy and positron emission tomography
(PET) give important information on the metabolic state and molecular
events within the tumor. Functional MRI and functional PET, in combination
with electrophysiological methods like transcranial magnetic stimulation,
are being used to delineate functionally important neuronal tissue, which
has to be preserved from treatment-induced damage, as well as to gather
information on tumor-induced brain plasticity. In summary, imaging in
patients with brain tumors plays a central role in the management of the
disease and in the development of improved imaging-guided therapies.
John Ashburner, Ph.D.
University College London
Wednesday, 05/28/08, noon, MGH bldg 149
Multivariate Analysis of Anatomical MRI
This talk will describe the methods used in the Functional Imaging Lab
(London, UK) for multivariate analysis of grey matter maps. The procedure
begins by segmenting the anatomical images into their different tissue
classes, using a generative modelling approach similar to that of Fischl or
van Leemput. The model combines tissue classification, bias correction and
nonlinear registration of pre-generated tissue probability maps. The
segmentation results are used to generate approximately rigidly aligned gray
and white matter images for each subject. More precise inter-subject
registration is then performed by repeatedly aligning the grey and white
matter images to their own mean, using a high-dimensional warping approach
that preserves the one-to-one mapping among brains. Warped versions of the
gray matter images are generated, which are locally scaled in order to
compensate for expansion/contraction during warping. These pre-processed
data are then used as features for multivariate kernel classification or