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Project
Openings 
Research
Profiles
Supervisor
Index
Other
Research
|
Undergraduate
research opportunities
are offered
in this department
under subject
9.UR, Undergraduate
Research (graded
on a P/D/F
basis), 9.URG
Undergraduate
Research (letter
grade), or
for pay. Another
research opportunity
is 9.50, Research
in Brain and
Cognitive
Sciences.
This subject
is offered
for a letter
grade, and
counts for
Institute
General Laboratory
credit. Students
must get either
Prof. Nedivi's
or Prof. Schiller's
approval before
registering
for 9.50.
A written
presentation
of results,
due the last
day of classes,
must be submitted
to the faculty
supervisor
and to either
Prof. Nedivi
or Prof. Schiller.
Prof.
Edward
Adelson, 46-4115,
x3-0645, adelson@mit.edu
Visual
perception
by humans
and machines,
including
motion perception,
texture
perception,
and brightness
perception.
Image processing
and image
coding.
Prof.
Mark Bear, 46-3301,
x4-7002, mbear@mit.edu
Studies of synaptic plasticity in cerebral cortex and hippocampus.
Prof. Emilio Bizzi, 46-6189A, x3-5769
or x3-0771, ebizzi@mit.edu
Neural
mechanisms
subserving
motor control
and motor
learning
in vertebrates.
Techniques
used in
my laboratory
involve
electrophysiological
recordings
from the
cortex and
subcortical
structures,
modeling,
and studies
with patients
with neurological
motor disorders.
Prof. Ed Boyden, E15-430, x4-3085, edboyden@mit.edu
Our brains and nervous systems mediate everything we perceive, feel, decide, and do- and act as our ultimate interface to the world. An outstanding challenge for humanity is to understand the brain at a level of abstraction that enables us to engineer its function-repairing pathology, augmenting cognition, and revealing insights into the human condition. We are inventing and applying novel tools for the analysis and engineering of brain circuits in both humans and model systems, with a current focus on devising technologies for interfacing to specific circuit targets, and controlling the processing within those circuits.
Prof.
Suzanne Corkin, 3-5726, x3-5762, corkin@mit.edu
Behavioral
neuroscience;
studies
of the neural
basis of
perception,
attention,
memory,
problem-solving,
and emotions
in normal
subjects,
using functional
magnetic
resonance
imaging.
Subjects
are typically
normal young
or older
adults.
Prof. James DiCarlo, 46-6161,
x2-2045, dicarlo@mit.edu
The DiCarlo lab studies high-level neuronal object representations that underlie our remarkable ability for rapid visual recognition. The primary methods used in the laboratory are neurophysiology in awake, behaving monkeys, functional magnetic resonance imaging (fMRI) and x-ray in monkeys, and computational modeling. The lab typically has open UROP projects that involve a range of topics, including human testing, help with animal experiments, computational modeling, and hardware/software device construction and testing. Students that are very comfortable with computers and software (e.g. Matlab) are especially encouraged to contact us.
Prof.
Michale
Fee, 46-5133,
x4-0173, fee@mit.edu
The research in the Fee Lab has two main themes:
1). To understand the neural and biophysical mechanisms underlying the generation and learning of complex sequences
2). To develop advanced optical and electrical techniques for measurement of brain activity in behaving animals.
Prof. John Gabrieli, 46-4033B, x3-8946, gabrieli@mit.edu
Brain basis of memory, thought, and emotion in humans as studied by brain imaging (fMRI). We study both normal brain function, and diseases of brain function such as Alzheimer’s disease, dyslexia, ADHD, and autism.
Prof.
Edward
Gibson, 46-3035,
x3-8609, gibson@mit.edu
Human
language
comprehension:
behavioral
measurements
(e.g. self-paced
reading),
computational
analyses
of large
texts, and
computational
modeling
Prof.
Ann Graybiel, 46-6133B, x3-5785, graybiel@mit.edu
Functional
organization
of forebrain;
neurotransmitter
immunohistochemistry,
electrophysiology
and anatomy
of central
nervous
system,
focusing
on organization
of the basal
ganglia
and in basal
ganglia
disease
states.
Prof. Alan Jasanoff, NW14-2213, x-2-2538, jasanoff@mit.eduMagnetic resonance imaging of reward-related behavior in animals; development of new MRI contrast agents for neuroimaging; molecular imaging applied to study neural function in single cells and circuits.
Prof.
Nancy Kanwisher, 46-4133, x8-0721, ngk@mit.edu
Visual
cognition
especially
visual attention
and the
recognition
of objects
and faces,
using both
behavioral
and functional
brain imaging
(fMRI) measures.http://mit.edu/bcs/nklab/index.shtml
Prof. Yingxi Lin, 46-3121A, x4-6552, yingxi@mit.edu
Our lab studies the development and function of inhibitory (GABAergic) circuits in the brain, with the ultimate goal of understanding the etiology of neurological disorders that have been linked to deficits in the GABAergic system. Currently, we are focused on addressing the following questions:
1. How does neuronal activity modulate GABAergic synapses?
2. How does the regulation of GABAergic synapses contribute to the homeostasis of neural circuits?
3. How does the function of GABAergic synapses contribute to animal
Prof. Troy Littleton, 46-3243, x2-2605, troy@MIT.EDU
The focus of the work in the Littleton lab is to understand the mechanisms by which neurons form synaptic connections, how synapses transmit information, and how synapses change during learning and memory. To complement this basic research in neuroscience, the lab also studies how alterations in neuronal signaling underlie several neurological diseases, including epilepsy, autism and Huntington's Disease. They combine molecular biology, protein biochemistry, electrophysiology, and imaging approaches with Drosophila genetics to address these questions.
Prof.
Carlos Lois, 46-5235, x2-2263, loisc@mit.edu
Our laboratory is interested in the assembly of neuronal circuits, and the genetic control of brain development and function. We focus on the process of neuron replacement in the brain of adult vertebrates, and seek to understand how new neurons incorporate into the circuits of the adult brain, and their possible role in memory storage. To address these questions our laboratory is actively involved in the development of new technologies to genetically manipulate the development and function of neurons.
Prof.
Earl Miller, 46-6241, x2-1584, ekmiller@mit.edu
Neural
basis of
visual memory
and cognition.
Prof.
Christopher Moore, 46-2171C, x2-3526, cim@mit.edu
We investigate the neural mechanisms of tactile perception and how rapid changes in brain organization, on the millisecond to second timescale, lead to rapid changes in neural organization. To conduct these studies, we use both human imaging (fMRI) and animal studies.
Prof.
Elly Nedivi, 46-3239, x3-2344, nedivi@mit.edu
The Nedivi lab studies the cellular mechanisms that underlie activity-dependent plasticity in the developing and adult brain. Our approach is to identify and characterize.
Prof.
Aude Oliva, 46-4065, oliva@mit.edu
Research in the Computational Visual Cognition Laboratory concerns the investigation of high-level human cognition and more particularly scene and space understanding. Scenes are 3-dimensional structures composed of a variety of objects, textures, colors, materials and spatial layouts. Yet, we understand novel scenes quickly and effortlessly. In the laboratory, we approach the scene understanding problem from a computational stance, a brain imaging approach and a behavioral viewpoint. We also study the limits of human perception and cognition, as well as how to use our understanding of the pros and cons of human mechanisms for designing artificial vision systems and visual displays for human use. Our research topics bring together disciplines such as perceptual science, cognitive neuroscience, image processing, computational vision, computer graphics and clinical neuroscience.
Prof.
Tomaso Poggio, 46-5177B, x3-5230, tp@mit.edu
Learning and Networks, models of visual cortex, function approximation, machine and human vision, in particular object recognition and object detection in image sequences and speech recognition.
Prof.
Mary Potter, 46-4125, x3-5526,
mpotter@mit.edu
Human
cognitive
psychology:
reading,
memory,
sentence
comprehension,
picture
processing,
attention,
word perception.
Prof. Drazen Prelec, E40-161, x3-2833,dprelec@mit.edu
Individual decision making (especially apparent irrationalities), choices, preferences, risk, impatience, consumer misbehavior.
Prof.
William Quinn, 46-5009, x3-6307, cquinn@mit.edu
Genetic
and molecular
analysis
of the mechanisms
underlying
learning
and memory
in drosophila.
Prof.
Whitman Richards, 32-G364, x3-5776, wrichards@mit.edu
High level
vision and
perception;
Intentionalit;
aesthetics;
knowledge-structures.
Dr. Ruth Rosenholtz, 46-4115, x4-0269, rruth@mit.edu
Experiments and computational modeling of visual perception, particularly visual search, texture perception, and effect of visual clutter on perception. Application of visual perception to design of user interfaces and information visualizations, and image coding/image quality.
Prof. Rebecca Saxe, 46-4019, x4-2885, saxe@mit.edu
Development and neural basis or social cognition ad Theory of Mind. Approaches include functional neuroimaging (fMRI) and behavioral experiments infants, children, and adults.
Prof.
Gerald Schneider, 46-6021, x3-5795, jerry@mit.edu
Axon regeneration
and plasticity
after brain
injury;
vision and
natural
behavior
patterns
in small
animals.
Prof.
Laura Schulz, 46-4011B, x3-7957, lschulz@mit.edu
My lab studies cognitive development, with a particular focus on causal learning. Since babies and children have limited prior knowledge and no formal training, understanding how children reason about the world can give us insight into the origins of knowledge and fundamental principles of learning. Using a variety of approaches (toys, storybooks,
computational models, and infant reaching and looking-time paradigms), we are currently looking at how evidence and prior knowledge interact to promote curiosity and affect exploratory play and at how exploratory play generates evidence to support new causal learning.
Prof.
Sebastian Seung, 46-5065, x2-1693, seung@mit.edu
Neuroanatomy (involves imaging, computational image analysis, and neurotropic viruses)
Prof.
Morgan Sheng, 46-4303A, 2-3716, msheng@mit.edu
The Molecular Basis of Synaptic Plasticity. We seek to understand the molecular and cellular mechanisms underlying the ability of the brain to change in response to experience and to store information over long time periods, such as occur during development and for learning and memory. Our research is focused on the molecular regulation of synaptic structure and function, using genetic, biochemical, imaging and behavioral approaches in vitro and in vivo.
Prof
Pawan Sinha, 46-4077, x3-1434, psinha@mit.edu
Experimental and computational studies of how the human brain interprets the visual world. Projects include:
1. testing visual recognition skills of children adults and some patient populations (some testing involves brain imaging).
2. development of computer programs that can intelligently analyze images
3. creation of practical devices for helping the blind interact with the environment.
Prof. Mriganka Sur, 46-6237,
x3-8784, x3-8785, msur@mit.edu
Development and plasticity of the cerebral cortex; mechanisms of learning and memory in the adult brain; activity-dependent mechanisms of synaptic change in visual cortex.
Prof.
Josh Tenenbaum, 46-4015, 2-2010, jbt@mit.edu
We study the computational basis of human learning and inference. Through a combination of mathematical modeling, computer simulation, and behavioral experiments, we try to uncover the logic behind our everyday inductive leaps: constructing perceptual representations, separating “style” and “content” in perception, learning concepts and words, judging similarity or representativeness, inferring casual connections, noticing coincidences, predicting the future. We approach these topics with a range of empirical methods—primarily, behavioral testing of adults, children and machines—and formal tools – drawn chiefly from Bayesian statistics and probability theory, but also from geometry, graph theory, and linear algebra. Our work is driven by the complementary goals of trying to achieve a better understanding of human learning in computational terms and trying to build computational systems that come closer to the capacities of human learners.
Prof. Li-Huei Tsai, 46-4235A, x4-1660, lhtsai@mit.edu
My laboratory is interested in elucidating the pathogenic mechanisms underlying neurological disorders affecting learning and memory. The major research areas include neuropsychiatric disorders, autism, and Alzheimer’s disease. Our findings have led to the hypothesis that deregulation of Cdk5, through conversion of p35 to p25, plays an important role in the pathogenesis of Alzheimer’s. Recently, we found that chromatin remodeling via increased histone acetylation is beneficial for learning impairment and memory loss caused by severe neurodegenreation in the inducible p25 mouse model.
Prof.
Kenneth Wexler, 46-3029, x3-5797, wexler@mit.edu
Language acquisition in children: linguistic development, especially the development of syntax, semantics, pragmatics, and morphology. Research on language impairment in people with specific language impairment, Williams syndrome, Down syndrome, and autism spectrum disorders. Research on identifying genetics underlying language impairments. Relation between language development and brain structures, especially using imaging.
Prof.
Matthew Wilson, 46-5223, x3-2046, wilson@mit.edu
Hippocampal
learning
and memory.
Prof. Richard J. Wurtman, 46-5023, x3-6731, dick@mit.edu
Control of glandular functions and bodily metabolism; effects of light, food, and other environmental factors on mammalian regulatory systems; melatonin, stroke, obesity, Alzheimer's Disease.
Prof. Weifeng Xu, 46-4239A, x5-5392, weifeng@mit.edu
We are interested in elucidating the molecular mechanisms that mediate activity-dependent modifications of neuronal properties (neural plasticity), and the implications of those mechanisms in neurodegenerative and psychiatric diseases. To achieve this end we will apply state-of-the-art methods combining molecular biology and electrophysiology and, when necessary, incorporate new methods to overcome the limitations of current technologies used in molecular manipulations in neurons. The advanced method of immediate applicability is the lentivirus-mediated molecular replacement system for spatiotemporal-controlled manipulation of neuronal proteins, combined with functional analysis using dual-whole-cell patch clamping techniques. |
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