Brain Mapping seminar abstracts 2010-11

Tommi Raij, MD, PhD
TMS Core Director MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging Bldg 149, 13th St Charlestown, MA 02129 U.S.A.

Transcranial magnetic stimulation: From correlation to causality
Transcranial magnetic stimulation (TMS) is a safe research, diagnostic, and therapeutic tool that has been used for 25 years for non-invasive stimulation of the human brain. As a research tool it goes beyond brain imaging by allowing modulation of selected brain areas at chosen timepoints. Therefore, TMS allows validation of hypotheses based on MRI/fMRI and MEG/EEG results and determination of functional roles of specific regions. The clinical applications are also expanding as FDA has recently approved the use of TMS in treatment of depression and in pre-surgical mapping of motor areas. The Martinos Center TMS laboratory is now fully functional and is already attracting large-scale funding. Thus, this talk serves as a primer to TMS by reviewing its physics, instrumentation, applications, safety and IRB protocols, as well some of our recent results.

Georges El Fakhri, Ph.D., DABR
Director, Molecular Imaging Physics and Instrumentation Associate Director, PET Core Massachusetts General Hospital Associate Professor of Radiology Harvard Medical School

Novel Applications in Quantitative PET imaging
Positron Emission tomography (PET) has become a key molecular imaging modality and an essential approach in the diagnosis, follow-up and assessment of response to therapy for many diseases. In this talk, we will explore three developments in brain and thoracic imaging, using novel PET methods, that are being pursued in the Molecular Imaging Physics and Instrumentation Laboratory and discuss their clinical impact in oncology and cardiology. Specifically, we will investigate the role of simultaneous PET-MR in dramatically improving PET image quality and lesion detection accuracy, the role of quantitative PET in monitoring proton therapy and the expected improvement with time-of-flight (TOF) PET for lesion detection and activity quantitation.

Anna-Liisa Brownell, PhD
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging Experimental PET Laboratory 55 Fruit Street Bartlett Hall 504R Boston, MA 02114

Overview of PET Imaging at MGH; from man to mouse to man
Now, when we are ready to implement radiopharmaceutical production with PET as a new research modality to the Martinos Biomedical Imaging Center it might be good know that positron imaging has a long history at MGH. It started already in 1951, when Dr. Gordon Brownell designed an instrument for imaging brain tumors. For PET imaging both instrument and radioligand are needed. At that time radioligand production was available only in the government laboratories and the closest one was the Brookhaven National Laboratory, which provided radioligands, like arsenic-74 and 72, copper-64 and zinc-62. Also gallium-68 generator was developed. Using arsenic-74 the first positron imaging study was done in 1952 to diagnose a malignancy in a 8-yr old girl. After her successful surgery and recovery positron imaging was soon a method of choice to diagnose different type of malignancies and the number of studies per year was increased to 1500 per year by 1960. Brownell$.1Žňůs laboratory developed several more advanced systems for positron imaging - turning point being 1970 when Dr. David Chessler in BrownellŽňůs laboratory developed a reconstruction algorithm, which actually made tomographic imaging possible, and PC-I, which was constructed during 1968-1969 was turned to be the first tomographic positron imaging device. Development of PET accelerated the physiological modeling, since it was possible to obtain the real activity concentration from tissues. The first kinetic modeling of functional neuroimaging at MGH concerned blood flow and oxygen metabolism published in 1978 by Subramanyam et al and followed by glucose metabolism (Kearfott 1980). PET was purely a research tool almost for twenty years until the insurance companies started to re-reimburse diagnostic cancer studies. Meantime active research using PET imaging technology was focused on physiological functions using small animal models. The most important outcomes of these studies were results obtained from neurodegenerative disorders especially investigating dopaminergic system showing progressive decline of dopamine transporter function and its correlation to the locomotor activity. These studies awoke active radioligand development for the imaging of dopaminergic receptor system. The obtained results contributed also to the development of therapeutic approaches to repair defect in dopaminergic circuitry. Finally these experiments resulted to explore other receptor systems including metabotropic glutamate receptors (mGluR)s. To close the loop these new imaging ligands are on the way to be used in human studies - what is a little bit more challenging than sixty years ago.

Linda K. McEvoy, PhD
Assistant Adjunct Professor, Department of Radiology, UCSD

Quantitative Structural Magnetic Resonance Imaging for Individual Risk Prediction in Patients with Mild Cognitive Impairment.
Structural magnetic resonance imaging (MRI) measures are highly sensitive to the neurodegeneration that occurs in Alzheimers disease (AD), even in prodromal stages. Using individual-specific measures of regional atrophy from a baseline MRI scan we have identified a pattern of regional atrophy that is characteristic of mild AD. The presence of this atrophy pattern discriminates healthy control from Alzheimer cases with high cross-validated sensitivity (85%) and specificity (93%). Inclusion of 1-year follow-up measures significantly improved discrimination(sensitivity=90%, specificity=92%). The degree to which the regional atrophy pattern is present at baseline in individuals with amnestic mild cognitive impairment is predictive of risk of decline to AD: Relative to the risk associated with a diagnosis of MCI (~15-20% / year), quantitative structural MRI measures can identify individuals with a much lower risk (3%) of converting to AD within the next year and individuals with a much higher risk (40%). Inclusion of information on rate of atrophy from a 1-year follow-up MRI can identify individuals with even higher risk of imminent conversion (67%). Such risk estimates could have great practical prognostic utility for individualized patient risk assessment. They could also be useful for improving the efficiency of clinical trials: Constraining enrollment to MCI subjects who show the regional atrophy pattern characteristic of mild AD on a screening MRI could allow for reductions of sample sizes by up to 60%.

Eva-Maria Ratai, PhD
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging Bldg 149, 13th St Charlestown, MA 02129 U.S.A.

MR spectroscopy in the accelerated simian immunodeficiency virus macaque model of HIV-associated neurological disease: from mechanism to treatment.
Despite the success of antiretroviral therapy, the neurological complications of HIV-associated neurological disease (HAND) continue to be a significant problem among the HIV-infected population. Neuroimaging has become a useful tool for the study of HIV-infected patients with neurological and/or cognitive symptoms. In vivo magnetic resonance spectroscopy (MRS) has the unique ability to measure metabolite levels in a non-invasive manner. Quantification of these metabolites can be used to identify disease, measure the severity of injury and/or monitor response to treatment. Furthermore, spectroscopic imaging allows for the detection of region specific metabolic responses to SIV infection in the macaque brain. The simian immunodeficiency virus (SIV) macaque model is extremely informative as a model for CNS disease progression as it shares very similar pathology with HIV-infected human patients. Moreover, brain metabolite changes detected by in vivo MRS are confirmed by postmortem histopathological studies in the SIV macaque model which allow examination of the full chain of causality from viral infection to encephalitis/neuronal injury. Thus, the macaque model in combination with in vivo 1H MRS, immunology, virology and postmortem histopathology provides an exceptional opportunity to efficiently characterize HIV neuropathogenesis and explore drug therapies that impact neuronal injury.

Jaakko Kauram.AŽäki
Aalto University, Department of Biomedical Engineering and Computational Science (BECS) Helsinki, Finland

Measures and models of top-down influences in the human auditory cortex
Our senses rapidly adapt to the sensory information. These short-term, plastic changes especially in the central nervous system are necessary for goal-directed and active behavior. Nevertheless, partly due to methodological limitations, the neural mechanisms underlying improved perception during selective attention are not well understood. For instance, human auditory cortex activity is enhanced while engaging in an auditory task, but whether such enhancement involves a larger-extend or a more specific response from a sharply tuned neuronal population remains vague. In addition to unimodal attention effects, our senses can influence each others' processing. Seeing a person articulate can both enhance and modify the perception of acoustic speech and even induce activation in the auditory areas. In this talk I will shortly present a series of four studies using EEG and MEG, where the neural basis of these auditory cortex modulations due to 1) selective attention and 2) cross-modal interactions were studied. The results show that 1) evoked responses mainly from secondary auditory areas were rapidly enhanced by feature-specific manner during a discrimination task, where bottom-up and top-down processing were modified by stimulus and task design, and 2) lipreading and covert speech production tasks dynamically suppress auditory cortex reactivity, possibly via an efference copy signal from the speech-production system.

Diego A. Pizzagalli, PhD
Associate Professor of Psychiatry, Harvard Medical School Director, Neuroimaging Center Director, Center For Depression, Anxiety and Stress Research McLean Hospital

Toward an Objective Characterization of Depressive Phenotypes:Clues from Affective Neuroscience
Anhedonia - loss of pleasure or lack of reactivity to pleasurable stimuli - is a core symptom of depression and a potential risk factor for various forms of psychopathology. Few studies to date have employed laboratory-based measures to objectively characterize this important depressive phenotype. Further, although preclinical data have emphasized stress-mediated disturbances of mesocorticolimbic dopaminergic functions in the pathophysiology of depression, the mechanisms and substrates underlying these processes are largely unknown in humans. Findings from recent studies in my laboratory combining behavioral, functional neuroimaging, molecular genetics, and pharmacological challenge approaches to study the neurobiology of anhedonia will be reviewed. Collectively, these findings indicate that depression is characterized by an impaired tendency to modulate behavior as a function of prior reinforcements and dysfunction in brain reward pathways. The potential role of stressors, dopamine, and genetic vulnerability on reduced hedonic capacity in depression will be discussed.

Phoebe Suk-tak Chan, PhD
Tara N. Sporko, BS

Center for Acupuncture Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129

Acupuncture, the Limbic System, and the Default Mode Network of the Brain
The study of the mechanism of acupuncture action was revolutionized by the use of functional magnetic resonance imaging (fMRI). Over the past decade, we have elucidated the central effect of acupuncture through fMRI studies of healthy subjects. These studies have shown that acupuncture stimulation, when associated with sensations comprising deqi, evokes deactivation of a limbic-paralimbic-neocortical network, which encompasses the limbic system, as well as activation of somatosensory brain regions. These networks closely match the default mode network and the anti-correlated task-positive network described in the literature. We have also shown that the effect of acupuncture on the brain is integrated at multiple levels, down to the brainstem and cerebellum. Our studies support the hypothesis that the effect of acupuncture on the brain goes beyond the effect of attention on the default mode network or the somatosensory stimulation of acupuncture needling. The amygdala and hypothalamus, in particular, show decreased activation during acupuncture stimulation that is not commonly associated with default mode network activity.

Sava Sakadzic, PhD
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129

Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue
Measurements of oxygen partial pressure (pO2) with high temporal and spatial resolution in three dimensions are crucial for understanding oxygen delivery and consumption in normal and diseased brain. Among existing pO2 measurement methods, phosphorescence quenching is optimally suited for the task. However, previous attempts to couple phosphorescence with two-photon laser scanning microscopy have faced substantial difficulties because of extremely low two-photon absorption cross-sections of conventional phosphorescent probes. Here we report the first practical in vivo two- photon high-resolution pO2 measurements in small rodents' cortical microvasculature and tissue, made possible by combining an optimized imaging system with a two- photon enhanced phosphorescent nanoprobe. The method features a measurement of pO2 in all cortical microvessels including capillaries, 0.2-second temporal resolution, measurement depth of several hundreds microns, and requires low probe concentration. The properties of the probe allowed for the first direct 2-photon measurement of cortical tissue pO2. The application of the new technology to investigation of pO2 distribution in microvasculature, development of a novel methodology for measurement of CMRO2, and changes of tissue pO2 during functional stimulation and hypoxia will be presented.

Marco Loggia, PhD
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129

Neural Correlates of Ongoing Chronic Low Back Pain as Measured by Arterial Spin Labeling (ASL)
Over the last two decades, functional imaging studies of experimentally-induced pain have provided considerable insight into the neural underpinnings of different components of the pain experience, as well as into the mechanisms underlying its modulation (e.g., placebo-induced analgesia). While the central processing of experimental pain has been intensively investigated, several obstacles have hindered the understanding of the brain correlates of chronic pain (CP) conditions. Most notably, chronic pain, unlike experimental pain, cannot be switched on and off at will, and thus eludes study with block or event-related experimental paradigms and BOLD imaging. Arterial spin labeling (ASL) is a perfusion-based fMRI technique which allows the absolute quantification of regional cerebral blood flow (rCBF), through the use of magnetically labeled water in blood acting as a diffusible tracer. As ASL is more sensitive than BOLD to low frequency signals, it has the potential to be a better tool for the study of certain CP conditions. In this talk I will present an experiment in which ASL was applied to the study of chronic low back pain (cLBP). A 6-minute resting state pulsed ASL scan was acquired before and after the exacerbation of clinical pain in 16 cLBP patients (achieved using clinical maneuvers, such as straight leg raising or pelvic tilt). In response to these maneuvers, we were able to observe significant rCBF increases within the 'evoked pain matrix' (S1, S2, insula and prefrontal cortex) and in other structures less frequently observed in experimental pain studies, such as the superior parietal lobule. This effect appears to have specificity to changes in ongoing pain, as it was not observed after the application of exogenous heat pain to the affected leg dermatome in the same CLBP subjects, nor in matched, pain-free healthy controls undergoing identical clinical maneuvers. These findings reveal the potential of ASL as a tool to investigate the neural processing of CP, and provide a step forward in the quest for objective biomarkers of CP.

Alvaro Pascual-Leone, MD, PhD
Beth Israel Deaconess Medical Center, Boston, MA

Assessing cortical plasticity and brain network dynamics with TMS across the lifespan
The human brain is intrinsically plastic, changing across the lifespan. Such changes may proof adaptive and lead to functional benefits, or may be the very cause ofdisease and disability. The challenge is to learn enough about the mechanisms of brain plasticity to guide them, enhancing some and suppressing others, to promote the best functional outcome for a given individual. This requires insights about causal relations between brain activity and behavior. Functional brain imaging provides correlational information about brain activity and behavior. Establishing causal links requires intervention and brain stimulation techniques enable this, thus offering the potential of adding another dimension to functional brain imaging. Multimodal brain imaging, combining brain imaging and neurophysiologic measuring and noninvasive stimulation methodologies, allows the establishment of a causal relationship and a precise chronometrybetween regional brain activation and behavior. Application of similar methods in animal models enables true translational mourse-to-human approaches, bridging mechanistic and clinical investigation. Noninvasive brain stimulation with Transcranial Magnetic Stimulation (TMS) or Transcranial Direct Current Stimulation (tDCS) can interfere with activity in a specificcortical brain region and modulate brain network dynamics. Both of these technique can be combined with brain mapping methods. For example, PET or fMRI can identify information about brain areas associated with behavior and TMS can transiently deactivate a region of the brain, thus creating a $(B!F(Bvirtual patient$(B!G(B and explore causal relations. EEG, MEG and ERPs can provide further chronometric information. Repetitive TMS or tDCS allows the non-invasive modulation of activity in a specified cortical target in the brain convexity and its functionally connected cortico-subcortical neural network. MRI and EEG can guide such application of rTMS. Depending on stimulation parameters cortical excitability of the directly targeted brain region can be increased or decreased beyond the duration of the rTMS train. Network effects can result in behavioral benefits through paradoxical functional facilitation, induction of desirable plastic changes, or release of specific neurotransmitters. Such combinations of noninvasive brain stimulation and brain mapping methods can lead to clinically relevant therapeutic effects in neuropsychiatry and neurorehabilitation and provide unique insights into brain plasticity mechanisms in health and disease across the lifespan. The focus of my presentation will be on the mechanisms that control brain plasticity across the lifespan and how increased understanding may enable to prevent age-related cognitive decline, the impact of developmental disorders such as autism, and the risk of dementia. The work combines various brain imaging and brain stimulation methodologies to establish a casual relationship and a precise chronometry between regional brain activation and behavior, and uses noninvasive brain stimulation techniques and behavioral interventions to modulate brain plasticity, suppressing some changes and enhancing others to gain a clinical benefit and functional advantage for each individual

Claudine Gauthier, MS
CRIUGM, Universite de Montreal, Canada

A generalized procedure for calibrated MRI incorporating hyperoxia and hypercapnia
Calibrated MRI techniques estimate changes in cerebral metabolic rate of O2 consumption (CMRO2) from BOLD task measurements. Different calibration techniques involve estimation of M, equivalent to the maximum possible BOLD signal change, by extrapolating from smaller changes obtained during hypercapnia or hyperoxia. We present a generalization of previous BOLD signal models which can be applied to data acquired during hypercapnia, hyperoxia, or both hypercapnia and hyperoxia simultaneously. We demonstrate the application of this generalized model during all three manipulations. While comparable group average results were achieved, the combined hyperoxia and hypercapnia method yielded more robust individual estimates of M and CMRO2.

David Sosnovik, MD
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129

Imaging Motion, Microstructure and Cell Death: Common Challenges in the Heart and Brain.
The heart and brain have several important similarities. Both are highly susceptible to hypoxic injury (heart attack and stroke). Both organs have a highly organized microstructure (myofiber tracts and nerve tracts), and both present the need for more rapid and/or realtime imaging. In this seminar I will review recent advances in molecular MRI of acute ischemic injury, diffusion MRI and tractography of the heart, and highly accelerated (128 channel) cardiac MR imaging. The focus of our work has been principally in ischemic heart disease, but the tools and techniques we have developed are of broad relevance to the molecular imaging, neuroimaging and physics/engineering communities.

Maximilien Chaumon, PhD
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129

Multiple scales of contextual processing in the brain: from sensory encoding to large-scale network effects.
Every event occurs within a certain set of circumstances that we call its context. The context can be defined at multiple scales. For instance, at the sensory level, context deeply affects how we perceive visual objects, but this effect is itself contingent on higher-order context, such as the affective state of the observer. In this talk, I will take ascending steps across scales of contextual effects. First, I will present data showing how sensory contextual regularities are unconsciously learned. I will then focus on the mechanisms subtending the reactivation of learned regularities with a special emphasis on the orbitofrontal cortex. To finish, I will present an original analysis showing how activity in the default mode network during task performance constitutes a brain context that radically changes the response function of the orbitofrontal cortex.

Ai-Ling Lin, PhD
Texas Health Science Center

Flow-Metabolism Coupling- PET vs. fMRI- Debate, Modeling and Application
The relationship between task-induced changes in cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2) and glucose (CMRGlc) have been extensively investigated using positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) over the past two decades. However, controversies were raised between the two imaging methods as regards the flow-metabolism (CBF:CMRO2) coupling relationship (linear vs. non-linear) and the metabolic pathways (oxidative vs. non-oxidative) for meeting the energy demand and driving the increases in CBF during brain activation. The inconsistencies have been speculated due to the modeling strategy employed by a fMRI blood oxygenation-level dependent (BOLD) biophysical model, in which the accuracy of the BOLD relaxation rate (the M value) and cerebral blood volumes (CBV) determinations, in addition to CBF and BOLD, are critical for CMRO2 determination. Specifically, misestimated M and CBV values have been demonstrated as causing the apparent CBF:CMRO2 coupling relationship shifts from non-linear to linear during multi-frequency visual stimulation. Currently, nonetheless, the strategies for determining the accurate M value (e.g., hypercapnia, hypoxia, and CBF/venous oxygenation approaches) and the CBV compartmental contributions (arterial vs. venous) to the CMRO2 computation during brain activation are still under debate. As a result, future studies are needed to investigate these issues and to verify the fMRI BOLD modeling by comparison with other well-validated imaging methods. The validation of the fMRI CMRO2 measurement is important because it will have profound implications in future neurometabolic research in both healthy and disease states due to its entirely noninvasive nature, particular with small animal models. Although PET is an outstanding method for acquiring quantitative CMRGlc in rodents, it is poor suited for the quantitative CBF and CMRO2 (due to the difficulty of obtaining arterial input functions). On the contrary, fMRI is an excellent method for measuring quantitative CBF, but not CMRGlc. In one of our studies, the concurrent fMRI and PET measurements of basal CBF and CMRGlc showed the promise for investigating the relationship between the mitochondrial mutation and the metabolic alteration (shifted from oxidative to non-oxidative metabolism) in a transgenic mice model with extended longevity. With additional fMRI CMRO2 measurement (both quantitative and task-induced relative changes), the complementarity of fMRI (CBF and CMRO2) and PET (CMRGlc) will have wide applications in future neurometabolic and translational research.

Bruce Rosen, MD, PhD
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129

Lessons learned the hard way

Peter Savadjiev, PhD
LMI, Brigham and Women's Hospital, Boston, MA
Peter got his PhD in the computer science at McGill University in Montreal, under the supervision of Kalim Siddiqi. Thesis was about the organization of fiber tracts in diffusion MRI, with the study of shape and curvature. He is now working at the Brigham and Women's Hospital, in two laboratories: the Psychiatry Neuroimaging Laboratory with Martha Shenton and the Laboratory for Mathematics in Imaging with Carl-Fredrick Westin. Peter is developing methods for probabilistic tractography in HARDI. He is particularly interested in developing biomarkers based on the shape and curvature of fiber tracts. He notably applied these new metrics in the context of schizophrenia, which will be the topic of his talk today.

DTI-based measures of white matter fibre geometry, and applications to schizophrenia research
Measures of white matter fibre geometry and its variation along tracts can be useful in the study of normal white matter development, and of diseases that may affect it, e.g. as indicators of neurodegenerative processes. We present a set of scalar measures that describe the geometrical properties of white matter, such as its degree of "curving" and "fanning", directly from diffusion tensor data and without requiring prior tractography. We then apply these measures to investigate changes in local geometry in the left uncinate fasciculus and in the genu of the corpus callosum in schizophrenia patients as compared to matched healthy controls. Although changes such as fractional anisotropy (FA) reductions have been previously reported in these tracts in schizophrenia, to our knowledge this is the first investigation of geometry changes. Our results reveal structural differences and suggest avenues for future research.

Rob Brown, PhD
Montreal Neurological Institute
Rob has a BSc in computer science from Athabasca University, and a PhD in biomedical engineering from the University of Calgary. He is currently a post doctoral fellow in Dr. Douglas Arnold's lab, at the Montreal Neurological Institute. His PhD research focused on novel time-frequency transforms for signal and image processing of MRI, and their application to noninvasively identifying a particular genetic abnormality in brain tumors. His current research is focused on longitudinal measurement of demyelination and remyelination in multiple sclerosis using magnetization transfer ratio MRI, both in adults and children.

Imaging Remyelination by Lesional MTR Recovery in Adults and Children With Multiple Sclerosis and Fast Magnetic Resonance Imaging Using Compressed Sensing
Multiple sclerosis (MS) is a chronic, progressive disease characterized by the development of demyelinating lesions in the central nervous system. A standard clinical magnetic resonance (MR) imaging exam for MS looks primarily for T2 hyperintense, T1 hypointense and gadolinium (Gd) enhancing lesions. These three contrasts are very sensitive to disease activity and T2 lesion volume is frequently used as an imaging measure of disease burden while Gd lesion volume is used as a measure of ongoing disease activity. For example, the efficacy of treatments designed to slow disease progression is often assessed by identifying a decrease in the number of Gd lesions after treatment. However, none of these contrasts contains specific information about the underlying demyelination and remyelination process. Magnetization transfer ratio (MTR) is an MR contrast that is reasonably specific for myelin in the brain. Using this contrast, we have developed a technique for identifying demyelinating lesions and quantifying MTR recovery, or remyelination. As an example, data will be presented from the Canadian Multiple Sclerosis Bone Marrow Transplant (BMT) trial, which treats aggressive MS with immunoablation and autologous stem cell transplant. The second part of the presentation will introduce compressed sensing (CS) a new technique for reconstructing images from partially acquired data. In MR, virtually perfect image reconstruction can be achieved based on 1/4th to 1/20th of the k-space data, allowing acceleration factors of 4 to 20 times. CS promises to not only speed up existing MR acquisitions, but also allow clinical use of imaging techniques that are currently too time consuming, including quantitative imaging.

Tom Brady, MD
MGH Radiology Research, Boston, MA
Dr. Brady received his MD from Loyola University before completing his internship and residency at the University of Michigan, Ann Arbor. At Massachusetts General Hospital, he was the inaugural Director of Clinical MRI and established the Massachusetts General NMR Center. He is the Director of Cardiovascular Imaging and Intervention at Massachusetts General Hospital with active research and clinical programs in MRI and mult-detector CT. He is Director of Radiology Research at Massachusetts General Hospital and LL Robbins Professor of Radiology at Harvard Medical School, as well as a visiting professor at the MIT Sloan School. Dr. Brady has published more than 200 peer-reviewed articles.

Firdaus Janoos
Ohio State University
Firdaus is a PhD Candidate in the Computer Science and Engineering Dept at OSU. He is currently an Presidential Fellow at OSU and a Visiting Research Fellow at Harvard Medical School and the Brigham and Women Hospital. He has also worked at the Dept. of Radiology at OSU, the Dorthy Davis Heart and Lung Center at OSU, and has interned at GE Global Research. Before joining OSU, He was a field applications engineer at Texas Instruments. As part of his PhD thesis, he has been building models for the spatio-temporal analysis of functional neuro-imaging data, specifically fMRI. Apart from this, he is also interested in statistical machine learning, computational neuroscience, computer vision and mathematical statistics.

Spatio-temporal Models for Mental Processes from fMRI
Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Classically, the analysis of functional Magnetic Resonance Imaging (fMRI) has focused either on the creation of static maps localizing the metabolic fingerprints of neural processes or on studying their temporal evolution in a few pre-selected regions in the human brain. However, cognition recruits the entire brain and the underlying mental processes are fundamentally spatio-temporal in nature. By neglecting either the temporal dimension or the spatial entirety of brain function, such methods must necessarily compromise on extracting and representing all the information contained in the data. In this work, I present a new paradigm to facilitate a multivariate spatio-temporal model that allows a time-resolved exploration of mental processes as captured by fMRI. Using a state-space formalism that models the brain transitioning through a sequence of cognitive states as it solves a mental task, we are able to study the spatial distribution of activity along with its temporal structure. In addition to revealing the mental patterns of an individual subject, such a generative model enables group-level inferences in terms of information-theoretic properties such as complexity and mutual information. Efficient algorithms for estimating the parameters, state-sequence and the hemodynamic behavior of the brain have been developed. This method was applied to a multi-subject fMRI study for developmental disorders such as dyslexia and dyscalculia (i.e. math learning disability). I shall show the kind of inferences possible with this method in analyzing and differentiating the groups and the neuro-scientific conclusions that it provides.

Mert Rory Sabuncu, PhD
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129
Mert is a faculty member at the Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School and a research affiliate at MIT's Computer Science and Artificial Intelligence Lab (CSAIL). He completed my post-doctoral training with Polina Golland in the medical vision group at MIT's CSAIL. He received my PhD degree from the Department of Electrical Engineering at Princeton University in 2006.

Cortical thickness as a dynamic and early marker of Alzheimer risk
Alzheimer's disease (AD), the most common form of dementia, is an incurable and terminal disease, with heritability estimates of up to 70%. The prevailing model of AD predicts a cascade of events, where abnormal processing of $(B&B(B-amyloid (A$(B&B(B) and tau peptide in genetically susceptible yet cognitively normal (CN) individuals is followed by neuronal injury and neurodegeneration, which in turn leads to clinical decline and dementia. The preclinical period may last more than a decade, which provides a window of opportunity for therapeutic intervention. Correlates of A$(B&B(B and tau, such as CSF and PET measurements, therefore provide an important capability as antecedent biomarkers of AD. Classical MRI-derived measures such as hippocampal volume are also robust markers of AD, yet they seem to be more strongly correlated with clinical decline and thus less useful during the long preclinical period. Recent emerging data however have started to demonstrate that MRI-derived cortical thickness measurements may be detectably abnormal before clinical symptoms begin. In this talk, I will go over the relevant literature and present data from our own on-going work that examines cortical thinning in early AD. I will present a theoretical model that will be useful for studying the dynamics of longitudinal markers. We use this model to demonstrate and characterize the sigmoidal pattern in AD-associated brain atrophy. Finally, I will talk about a sophisticated genetic modeling strategy that enables us to study AD-related variation in healthy individuals. This approach enables us to demonstrate AD-associated cortical thickness variation in cognitively normal individuals with no detectable indications of AD pathology.

Charles R. G. Guttmann, MD
Director, Center for Neurological Imaging Assistant Professor un Radiology Brigham and Women's Hospital, Harvard Medical School Boston, USA
Dr. Guttmann is the Director of the Center for Neurological Imaging at Brigham and Women's Hospital and an Assistant Professor in Radiology at Harvard Medical School. He graduated from the University of Zurich with a Doctorate in Medicine and completed the Post-Graduate Course in Experimental Medicine and Biology at the same Institution. His M.D. thesis on the invasivity of human glioma cell lines in the central nervous system was done under the direction of Dr. Martin E. Schwab at the Brain Research Institute of the University of Zurich. Following his Post-Doctoral training under Dr. Ferenc A. Jolesz at Brigham and Women's Hospital (Harvard Medical School) he went on to found the CNI in 2000. His main interest is the quantitative evaluation of normal and pathological states of the brain using MRI. Among Dr. Guttmann's specific goals are the understanding of the natural course of MS and of white matter disorders in the elderly. Using MRI findings as phenotypic descriptors and elucidating the relationship between brain morphological changes and functional deficits is particularly emphasized.

Ibis redibis non morietur in bello: imaging and predicting the course of syndromes affecting central nervous system white matter
Syndromes such as multiple sclerosis (MS) are very heterogeneous with respect to prognosis, disease course, and response to treatment. Underlying pathogenesis is likely to involve multiple, genetically predisposing factors and their interaction with exogenous conditions, such as infectious, nutritional, toxic, and environmental elements. This talk will analyze the role of imaging and quantitative image analysis in understanding pathogenesis and searching for clinically and pathologically predictive factors. A pathogenic model of diseases affecting CNS white matter will be illustrated with examples from MS and age-related syndromes.

Simona Temereanca, PhD
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129
Simona is a faculty member at the Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School. She completed her Ph.D. in Neurobiology, at the University of Pittsburgh School of Medicine, and subsequently did her post-doctoral training at the Martinos Center. Her research focuses on understanding the impact of action on perceptual and cognitive function in the human brain. In natural vision and reading, we constantly move our eyes from one target to another for detailed image analysis onto the fovea, the retinal area with highest visual acuity. In doing so, we perceive the world as staying "still", while our brain ignores the abrupt retinal motion and compensates for the repositioning of gaze. Yet, the neuroscience of active vision and reading remains a mystery. Simona’s research looks into this mystery with the long-term objective of understanding the complex interactions between visual, language, memory, attentional and motor systems during reading and active vision.

Active Reading: The Challenge of Word Processing after Eye Movements
Reading is an active process that requires coordination between frequent eye movements (saccades) and short fixations on the visual target. This complex behavior challenges our brain to ignore the abrupt image motion and compensate for the repositioning of gaze in order to maintain spatial and perceptual constancy, a prerequisite of fluent reading. Yet, the impact of saccades on word processing remains unknown, as previous data were collected typically during constant eye fixation. In active vision, perceptual and cognitive processes are known to be modified before, during and after an eye movement, suggesting that similar neural pathways and mechanisms may be crucial during reading. This talk will analyze effects of saccades on word recognition processes employing anatomically-constrained magnetoencephalography (MEG), psychophysical measurements and saccade detection in real time. Word recognition is slower and brain responses are reduced to words presented early vs. late after saccades, suggesting an overall transient impairment of word processing after an eye movement. Response reductions in various degrees occur in occipital pole and downstream visual and language-specific regions, where they are co-localized with repetition priming effects implicated in semantic processing. Similar effects occur when words are presented early vs. late after background motion that mimics saccades, suggesting a pronounced contribution to postsaccadic suppression from the visual effect associated with retinal image motion. At the same time, significant differences in the degree of postsaccadic and background movement modulation are consistent with additional influences of extraretinal origin after saccades, possibly mediated by brain regions that control eye movements and attention. This study provides a framework for testing a neurobiological model of the consequences of eye movements in reading based on hypotheses emerging from basic vision research. Together, our results suggest complex visual and extraretinal postsaccadic influences on word processing that alter perception and reading performance.

Robert J. Ogg, PhD
Chief, Division of Translational Imaging Research Department of Radiological Sciences St. Jude Children's Research Hospital
Robert is an associate member of Radiological Sciences at St. Jude Children’s Research Hospital and an affiliated associate professor in the department of anatomy and neurobiology at the University of Tennessee Health Science Center. Rob is interested in Diagnostic Imaging in Pediatric Oncology and Brain Function in Survivors of Catastrophic Diseases of Childhood.

Functional Neuroimaging in Children with Catastrophic Diseases: Neural Systems for Reading in Survivors of Medulloblastoma
Survival for childhood cancer has increased dramatically over the past 40 years with five-year survival rates now approaching 80%. Rapid increases in survival began in the 1970s with the broader introduction of multi-modality therapy. With this increase in rates of survivorship has come the recognition that survivors are at risk for adverse health outcomes, including cognitive deficits. We use functional neuroimaging to investigate the effects of disease and treatment on brain function in children with cancer and other catastrophic diseases. This presentation will focus on our work to characterize the development of neural systems for reading in patients treated for medulloblastoma, the most common pediatric brain tumor.

Carl-Fredrik Westin, PhD
Director, Laboratory of Mathematics in Imaging (LMI) Associate Professor of Radiology, Harvard Medical School Brigham and Women's Hospital, 75 Francis St., Boston, MA 02115
Dr. Westin got his PhD degree in Computer Vision at Linkšping University in Sweden, then he joined the BWH in Boston in 1996 for a Postdoctoral training. Over the past 14 years Dr. Westin has developed considerable expertise in all aspects of diffusion-weighted MRI. The main direction of research is the development of novel methods for image analysis. He has (co)-authored over 180 publications, in the fields of computer vision, medical image analysis and image guided surgery. Dr. Westin is the founding director of the Laboratory of Mathematics in Imaging (LMI,, and he is Associate Professor of Radiology at Harvard Medical School, Boston. Additionally, he has a joint appointment with the CSAIL at MIT. The LMI is focused on the application of mathematical theory, analysis, modeling, and signal processing to medical imaging applications.

Diffusion MRI: The next generation
The diffusion MRI (dMRI) technique has raised hopes in the neuroscience community for a better understanding of the white matter anatomy of the human brain. The hope is that the extension of available technology will aid in the diagnosis and subsequent treatment of disorders of the central nervous system and is likely to have a major impact on assessment of white matter pathologies (e.g., schizophrenia, multiple sclerosis), quantification of abnormal white matter development, detection of stroke and trauma including traumatic brain swelling, diffuse axonal injury, and spinal trauma, as well as a large variety of brain tumors. In this talk I will review recent developments in dMRI analysis, and discuss where the field is heading.

Anastasia Yendiki, PhD
Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital and Harvard Medical School
Anastasia received a Ph.D. in Electrical Engineering: Systems from the University of Michigan at Ann Arbor, where she worked on statistical image reconstruction for nuclear imaging. Her thesis addressed accurate detector modeling and analytical optimization of reconstruction methods with respect to lesion detectability. Upon graduation she came to the Martinos Center to learn about functional MRI but quickly got distracted by the pretty, colorful strands of diffusion tractography. Her research interests have since been in image analysis and reconstruction methods for diffusion MRI.

TRACULA: A new tool in FreeSurfer for looking beneath the surface
Diffusion MRI can be used to extract measures of anisotropy and diffusivity that describe the coherence and density of white-matter axon bundles at a macroscopic level. Although it is possible to compare these measures between populations on a voxel-by-voxel basis, more specific hypotheses can be tested if aggregate measures can be computed for specific pathways that are known or assumed to serve different brain networks. Reconstruction of these pathways is the objective of tractography, a field that has experienced great development over the past decade. Most existing tractography methods are geared towards exploring all possible connections from one brain region, which is used as the seed, to any other region. However, if the goal is to isolate specific pathways, e.g., the corticospinal tract or the uncinate fasciculus, manual interaction with the data by a user with substantial neuroanatomical expertise is required. For example, regions that a pathway does or does not intersect need to be delineated and thresholds on anisotropy or pathway curvature need to be adjusted by trial-and-error. This has to be repeated for each subject and pathway, making tractography studies time-consuming and compromising their robustness and reliability. We have developed a fully automated tool for probabilistic tractography that utilizes prior information on the anatomy of 18 major white-matter pathways from a set of training subjects. By incorporating this prior knowledge in the tractography procedure, our method obviates the need for manual interaction with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The new tool is called TRACULA (TRActs Constrained by UnderLying Anatomy) and is included in the upcoming release of FreeSurfer 5.1. This talk will discuss how our method relates to alternative approaches and will present results from validation on healthy subjects, as well as an application to a study of schizophrenia.

Alexandre Gramfort, PhD
Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA
Alexandre graduated from the Ecole Polytechnique in 2006. He obtained his PhD in 2009 from Telecom ParisTech under the supervision of Maureen Clerc and Olivier Faugeras. He did his PhD jointly at INRIA in Sophia Antipolis and the Computer Science Department at the Ecole normale superieure in Paris. He is currently a research fellow at the Martinos Center for Biomedical Imaging in Boston working with Matti Hamalainen. His research interests are on brain functional imaging (MEG, EEG, fMRI) and in particular on problems involving signal and image processing, scientific computing, numerical methods, data mining and machine learning.

Brain mapping with sparse structured priors: MEG and EEG analysis concepts applied to fMRI
Due to the fundamental laws of electromagnetism and limited number of sensors, solution of an ill-posed inverse problem is necessary in brain mapping with MEG/EEG. In particular, to render the solution unique, suitable a priori assumptions about the current generators are needed. In this talk I will give an overview of my recent work which aims to improve the localization in space but also in time of brain activations with M/EEG data and convex sparse priors. I will discuss how structured priors build with mixed-norm can be designed to take into account some physiological knowledge on neural sources such as spatial focality and temporal non-stationarity. I will very briefly address the mathematical challenges of this approach and the numerical aspects of the ensuing optimization procedure. Based on the concepts behind structured priors, I will explain how these very same ideas have been successfully applied on fMRI data in the context of decoding and for identifying resting state networks at a population level.

Dimitrios Pantazis, PhD
Research Scientist, MEG lab, Martinos Imainging Center at MIT
Dimitrios Pantazis, who joined the McGovern Institute in 2010, oversees the operation of the recently established Magnetoencephalography (MEG) Laboratory within the Martinos Imaging Center at MIT. Before moving to MIT, he was a Research Assistant Professor at the University of Southern California. His research interest is in the application of signal processing theory to the analysis of neuroimaging data, including MEG, EEG and MRI. He has collaborated with many neuroscience researchers and has published over 70 articles in scientific journals and conference proceedings.

Novel Interaction Measures for Statistical Functional Connectivity Using MEG
Whole head Magnetoencephalography (MEG) arrays provide dynamic images of human brain function at a millisecond scale, enabling us to study the rapid communication of neuronal populations between different cortical areas. This talk introduces several novel methods to identify cortical networks in MEG distributed images. We begin with canonical correlation networks, which allow us to detect functional interactions across different frequencies when combined with proper statistical inference. We further introduce new graph theory methods to partition undirected and directed graphs, measure information flow, and detect the statistical significance of a partition. We conclude with a new interaction measure, the partial phase locking value, which resolves the ambiguity of whether neuronal synchronization results from direct or indirect relationships between signals.

G. Bruce Pike, PhD
Brain Imaging Center, MNI, McGill University, Montreal, Canada
Dr. Bruce Pike is the Killam Professor of Neurology & Neurosurgery and James McGill Professor of Biomedical Engineering at McGill University. He is also Director of the McConnell Brain Imaging Centre at the Montreal Neurological Institute and is a Chercheur Nationaux (National Researcher) of the FRSQ.

Outstanding issues for calibrated fMRI: Are assumptions about CMRO2 and CBV correct?
The effect of carbon dioxide on cerebral metabolism is of tremendous interest to functional neuroimaging. In particular, mild-to-moderate hypercapnia is routinely used in calibrated BOLD fMRI-based quantification of cerebral oxidative metabolism changes, and relies on the assumption of a stable oxygen metabolism during CO2 challenges. However, this assumption has been challenged by some animal studies, necessitating its evaluation in humans under conditions customary to fMRI. I will present whole brain oxygen consumption measurements made noninvasively in humans during graded hypercapnia and hypocapnia. Computerized end-tidal gas modulation was employed to achieve stable CO2 and O2 conditions. Hyperoxic calibration results will also be presented and results compared to hypercapnia. Finally, the relationship between these calibration methods, BOLD signal modeling and changes in specific blood volume compartments will be considered.

Yogesh Rathi, PhD
Assistant Professor of Radiology, Harvard Medical School Brigham and Women's Hospital, 75 Francis St., Boston, MA 02115

Compressive sampling for diffusion MRI
Diffusion MRI has become a tool of choice for investigating the neural architecture of the brain. Typical neuroimging studies involve using a simple Diffusion tensor model for analysis, where 7-30 gradient directions are used to estimate a Gaussian diffusion profile. However, this has been shown to be inadequate due to crossing and branching fibers. High angular resolution scans (HARDI) can instead be used to recover proper orientation of the fibers. However, such scans take a long time to acquire, due to the large number of gradient directions required. Recent advances in computational harmonic analysis have shown techniques for signal recovery from far few measurements than what is required by Nyquist criteria. In this talk, I will motivate the construction of a basis specifically designed to represent HARDI signals, which are functions defined in a sphere. In particular, we show that the representation of HARDI signals in this basis is sparse and as such allows us to use the concept of compressive sampling to faithfully recover the diffusion signal from as little as 16-20 gradient directions. I will also discuss extensions of this work to multiple b-value diffusion data and discuss schemes for spatially smooth reconstruction of the signal.

Riitta Hari, MD PhD
Director of the Brain Research Unit, Aalto University School of Science, Finland

Time scales of human brain function: Insights from behavioral measures and neuromagnetic recordings
Human percepts, cognition, and actions are coordinated in a temporally accurate manner, with the relevant timescales ranging from milliseconds to several seconds. Multiple time scales typically govern the same behavior. During social interaction, such as free conversation, the speaker's articulation movements and other expressions change at time scales from tens to hundreds of milliseconds, and the prediction of and the reaction to the other speaker's talking can vary rapidly. — I will discuss the role of magnetoencephalography (MEG), both evoked responses and the reactivity of brain rhythms, in assessing the dynamics of the rapidly changing human percepts and actions. My dream would be to move towards “2-person neuroscience”, to study—in not too distant future—the brain basis of social interaction in real time.

Ashley Harris, PhD
Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK.

Examinations into the cerebral response to hypoxia in healthy subjects.
Cerebral hypoxia occurs in many neurological conditions and the use of MR imaging provides several tools to investigate these changes. However, the response to hypoxia in the absence of disease is not well understood, let alone in the presence of pathology, neurological or psychiatric conditions. During this talk, Ashley Harris will discuss some of her recent work using MR to examine the cerebral response to hypoxia in a young, healthy, human population, using well-controlled respiratory challenges. She will compare some preliminary findings comparing the cerebral blood flow response and the lactate response to acute hypoxia. These preliminary findings have motivated more in-depth analysis of the dynamics of cerebral lactate, which will be presented. Finally, she will consider these findings in context of more recent findings of the cerebral metabolic rate of oxygen consumption during hypoxia.

Thomas Yeo, PhD
Department of Psychology, Harvard University, Cambridge, MA.
B.T. Thomas Yeo received the B.S. and M.S. in Electrical Engineering from Stanford University in 2002, and the Ph.D. in Electrical Engineering and Computer Science from MIT in 2010. He is currently a post-doctoral fellow in the Psychology department at Harvard University. Dr. Yeo is interested in the analysis of brain images to provide insights into the organization of the human brain. More specifically, he has been developing algorithms to register, segment and analyze the human brain using functional, diffusion and structural magnetic resonance images. Dr. Yeo is a recipient of the MICCAI Young Scientist Award and the A*STAR National Science Scholarship.

Large-Scale Organization of the Human Cerebral Cortex
Information processing within the cerebral cortex arises from local circuits as well as from large-scale circuits that span distributed areas. The details of wiring and regulation between systems is likely to be critical for normal brain function and relevant to disruptions in neuropsychiatric illness. Here the organization of networks in the human cerebrum was explored by applying resting-state functional connectivity MRI (fcMRI) to a group of 1000 subjects. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving V1, putative MT+, LIP and FEF was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. I will conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential expansion in humans to support cognition.

Demian Wassermann, PhD
LMI/PNL/SPL, Brigham and Women's Hospital
Demian graduated from the University of Buenos Aires, Argentina, where he obtained his B.Sc in computer science. He obtained his PhD at the Athena (formerly Odyssee) research team at the INRIA Sophia Antipolis-Mediterranee under the supervision of Professor Rachid Deriche. In his PhD he focused on the analysis of white matter fibers traced from Diffusion MRI, aiming at providing a sound mathematical framework for automatic dissection and statistical analysis of the structures of the human brain's white matter. Since May 2010, Demian is working under the joint supervision of Professor Shenton at the PNL, Professor Westin at the LMI and Professor Kikinis at the SPL, all three laboratories at the Harvard Medical School and the Brigham and Women's Hospital.

Automated In Vivo Dissection of White Matter Structures from Diffusion Magnetic Resonance Imaging and Their Subsequent Statistical Analysis
The motivation of this talk is the in vivo dissection of the human brain's white matter from diffusion magnetic resonance imaging. This procedure isolates the human brain's white matter tracts that play a role in a particular function or disorder of the brain so they can be analyzed. Manually performing this task requires a great knowledge of brain anatomy and several hours of work. Hence, the development of a technique to automatically perform the identification of white matter structures is of utmost importance. The brain is organized in networks that are made up of tracts connecting different regions. These networks are important for the development of brain functions such as language or vision. Moreover, lesions and cognitive disorders are sometimes better explained by disconnection mechanisms between cerebral regions than by damage of those regions. Despite several decades of tracing these networks in the brain, our knowledge of cerebral connections has progressed very little since the beginning of the las century. Recently, we have seen a spectacular development of magnetic resonance imaging (MRI) techniques for the study of the living human brain. One technique for exploring white matter tissue characteristics and pathways in vivo is Diffusion MRI (dMRI). Particularly, dMRI-based tractography facilitates tracing the white matter tracts in vivo. Overall, dMRI is a promising technique to explore the anatomical basis of human cognition and its disorders. In this talk, I develop the means for the automatic dissection of WM tracts from dMRI, this is based on a mathematical framework for the WM and its tracts based on the Gaussian process formalism. Using this framework, we develop techniques to dissect the white matter, register fiber bundles and find group differences in the white matter, particularly between healthy and schizophrenic subjects.

Marina Bedny, PhD
Saxe Lab, MIT, Cambridge, MA
Marina graduated from Johns Hopkins University with a B.A. in Cognitive Science. She obtained her MA and PhD in Experimental Psychology from the University of Pennsylvania.Currently she is a postdoctoral fellow at the department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology as well as at the Berenson-Allen entere for Noninvasive Brain Stimulation Beth Israel Deaconess Medical Center, Havard Medical School. Her research interest is on the effect of experience on the Theory of Mind and the relationship between sensory and conceptual representations.

Developmental experience drives functional specialization in the human brain: insights from blind individuals.
How does developmental experience structures the human mind and brain? I will discuss insights into this longstanding question from studies that compare the minds and brains of congenitally blind, late blind and sighted individuals. The talk will focus on a striking case of blindness enabling occipital brain regions that evolved for vision to process language. I will present data which suggest that in congenitally blind individuals, early visual areas respond to high-level linguistic information such as sentence structure and word meanings. This language response has a sensitive period: we find occipital language sensitivity in congenitally blind but not late blind individuals. Furthermore, the occipital response to language develops early in blind children (as early as 5 years of age). Together these data suggest that brain regions that evolved for vision can develop language functions as a result of early experience. These findings have broad implications. They suggest that: 1) Innate biological properties are not necessary for a brain regions to become involved in language processing. 2) The typical neural architecture of language emerges as a result of an experience sensitive processes of self-organization. 3) Experience can alter the function of brain regions not only across sensory-modalities (from vision to touch), but also across cognitive domains (from vision to language).

Bruce Jenkins, PhD
Instructor in Radiology at Harvard Medical School
Assistant in Physics at Massachusetts General Hospital
Director of Neurochemical Imaging at Martinos Center

Bruce Jenkins obtained his PhD in biophysics from State University of New York in Buffalo. He is now the director of the Neurochemical Imaging Lab at the Martinos Center.

Interpreting Brain Hemodynamic Changes due to Dopamine Receptor Stimulation with Applications to Drug Abuse and Neurodegenerative Disorders
Functional MRI is a rich and versatile tool for examining many aspects of brain function. Unfortunately, the interpretation of the data is not as straight-forward as one might hope. From the lack of a means to verify maps of functional connectivity to the inability to reliably ascribe signal changes to neuronal activity or inhibition much fMRI data must be interpreted as the output of a [non-linear] black-box filter. Correlations of fMRI data and electrophysiologic data have been used to help interpret the neural bases of fMRI signal changes, however in the absence of any yet-discovered voltage gated vascular receptors such correlations remain just that. There are myriad vasoactive molecules that act to regulate cerebral blood flow and many common neurotransmitters such as serotonin, acetylcholine and dopamine have direct effects upon vascular receptors. In this talk we will provide a unified framework for interpretation of MRI hemodynamic signals related to stimulation of dopamine receptors. We will show that negative or positive signal changes can be detected and these cannot easily be interpreted as "activation" or "inhibition" but rather can be ascribed to selective agonism or antagonism at specific dopamine receptor sub-types. We will show how the interpretational framework can be used to determine specific information about dopamine release and reuptake, dopamine cell loss and recovery, ontogeny of dopamine receptors, alterations in dopamine function related to upregulation of D3 receptors in Parkinson's disease (dyskinesia) and downregulation of D2 receptors in amyotrophic lateral sclerosis and alterations of dopamine receptor function in models of substance abuse. We will also present data showing how pharmacologic MRI (or phMRI) can be used to assay the in vivo dopamine receptor sub-type selectivity of novel ligands targeting dopamine receptor sub-types in cases where radio-labeled ligands might not exist. After all this we will admit that we still know very little about how to interpret fMRI signal changes!