Testimony of Richard L. McCormick
President of Rutgers (#28), The State University of New Jersey
Assembly Higher Education Committee
Monday, February 8, 2010
Chairwoman Lampitt and members of the Assembly Higher Education Committee: Good morning. I am Dick McCormick, President of Rutgers, The State University of New Jersey, and I am pleased to speak today on behalf of the New Jersey Presidents’ Council and as the representative of our state’s public research universities. First I want to congratulate you, Chairwoman Lampitt, on your appointment to chair this committee. I appreciate your passion for and commitment to higher education issues, and I look forward to working with you and this committee in the future.
Chairwoman Lampitt has asked me to speak about the Presidents’ Council’s economic impact study, entitled “Partners for Prosperity: New Jersey and Higher Education.” Each of you should have before you a copy of the report that came out of our collaborative process. All members of the Presidents’ Council participated in a broad-based and detailed survey, conducted by Appleseed to collect data demonstrating the financial impact of the sectors. All of the sectors—research universities, state colleges and universities, independent colleges and universities, county colleges, and proprietary colleges and universities—contributed to the study.
Not surprisingly, we found that our colleges and universities play a vital role in the economy in the Garden State. It starts with our core mission of teaching. Collectively, our institutions provide educational opportunities to more than a half million students, helping them to acquire the skills to succeed in an increasingly knowledge-driven economy. At the same time, colleges and universities are also a major industry in themselves. Our campuses are huge employers of New Jersey residents, buyers of goods and services from New Jersey companies, and sponsors of construction projects that help to shape the state’s future.
Based upon data from the fall of 2007, New Jersey’s colleges and universities collectively enrolled approximately 533,000 students. (Let me add that this figure has surely grown larger, having seen Rutgers set a new high for enrollment this year, and we are not alone.)
Systemwide, enrollment in credit-bearing programs totaled approximately 309,000, with 88 percent of the students being New Jersey residents. Between 2003 and 2007, more than 317,000 students received a degree or certificate from one of our institutions, including 75,000 who earned advanced degrees.
A number of national studies have confirmed that education has a significant impact on an individual’s earning power. Our findings in this study revealed the same. We found that in 2007 the median income of New Jersey residents with some college or an associate degree was $40,354, more than 25 percent higher than the median for residents with only a high school diploma. More impressive, the median income of New Jersey residents with a bachelor’s degree was $55,191, fully 72 percent higher than the median for high school graduates.
As we looked at the economic impact of higher education as a major New Jersey industry, the data revealed another facet of our colleges and universities’ value to our state. In fiscal year 2007–08, the revenues of our institutions totaled nearly $8.6 billion.
Let me highlight a few areas. Tuition and fees accounted for 29 percent of our revenues in contrast to the state and local appropriations of 22 percent. Also, worthy of note is that federal grants accounted for 10 percent of our revenues, and that earnings from investments and other enterprises made up 20 percent of the total.
Higher education is a huge employer. As you will see in the report, our employment numbers compare favorably to other industries in New Jersey. Out of 13 industries, higher education ranked sixth, with construction, hospitals, and food and beverage retailing leading the pack. Collectively we employ more than 80,000 people, not including student workers. About 63 percent of this number represents full-time employees, and 91 percent live in New Jersey.
As I noted earlier, colleges and universities also contribute to the state’s economy as they purchase goods and services from New Jersey companies and undertake construction projects. In 2007–08, our institutions purchased $1.3 billion in goods and services and spent $677 million on capital construction and major maintenance projects. In the same year, our members’ construction projects generated about 4,240 full-time-equivalent jobs in private-sector construction and related industries.
As president of the state’s leading public research university, I am especially pleased to say that the research carried on by our faculty also strengthens the state’s economy in many ways. About 70 percent of these dollars come from the federal government, 10 percent come from the state, and the remainder comes from corporations, foundations, foreign governments, and internal funding. New Jersey colleges and universities spent about $780 million in research projects in fiscal year 2007–08—and, again, I can say from Rutgers’ experience that this figure has increased significantly since this data was compiled.
Much of this research addresses critical challenges for our state—in areas such as alternative energy, autism, nutrition and obesity, transportation, cancer, environmental protection, early childhood education, and health care. The application of our research has profound benefits, both economic and social, far beyond the jobs and revenue the research itself may generate.
Just as significant, although harder to calculate in dollars and cents, is the service that our colleges and universities contribute to New Jersey. Our students give time and energy in a variety of ways to extra-curricular service programs, and in courses that integrate service with classroom learning. New Jersey institutions reported that more than 32,500 students participated in some form of community service during the 2007–08 academic year.
Wherever New Jerseyans are grappling with challenges—whether protecting our shore line, increasing agricultural productivity, revitalizing our state’s industrial cities, finding better means of delivering health care, or improving our K–12 schools—the colleges and universities are there.
The impacts enumerated above are just some of the benefits our state receives from the higher education sector. As you peruse our study, I know you will find many, many more benefits not outlined in my remarks today.
As the representative of the public research universities, I would like to make some specific comments about those institutions.
In recent years, there has been growing concern—and rightfully so—about America’s competitiveness and preeminence in science and technology. We have led the world for decades, and we continue to do so in many research fields today. But the world is changing rapidly, and our advantages are no longer unique. China and other nations are making major investments in producing scientists and engineers.
Just two years ago, a national committee’s report entitled Gathering Storm warned that the United States was in danger of losing its position as an international leader in science and technology.
The report, commissioned by the National Academy of Sciences, National Academy of Engineering, and the Institute of Medicine, argued for increased public investment in math and science education and for the promotion of research activities in the public and private sectors.
Specifically, the report sought to make our nation “the most attractive setting in which to study and perform research so that we can develop, recruit, and retain the best and brightest students, scientists, and engineers from within the United States and throughout the world.”
As New Jersey’s largest and most comprehensive public university, with more than 10,000 faculty and staff and 54,000 students, Rutgers is uniquely positioned to be the type of research powerhouse and economic engine envisioned in the report. One of only 32 public universities nationally in the prestigious Association of American Universities, Rutgers is already recognized as one of the nation’s leading research institutions. Moreover, each year Rutgers returns to the New Jersey economy more than six times the state government’s annual investment in the university.
Of particular significance is our research. Last year Rutgers generated nearly $400 million in external research support, and we are on track to obtain nearly $500 million this year. This research is creating jobs, educational opportunities, and scientific and technological innovations that stimulate local industry.
It is a credit to the quality of our faculty and programs at our state university, but I know we could do even better. This amount could be increased substantially through strategic state investments in faculty recruitment, equipment, and student support in key areas of science, engineering, and technology.
And not just at Rutgers. Similar research examples, although to a lesser extent, exist at colleges and universities across New Jersey, and I urge the state’s investment for these vital purposes.
Honored members of the Assembly Higher Education Committee, please know that the proud achievements I have shared with you this morning are all at risk. Public funding for higher education, in actual dollars, has stagnated for more than a decade, while our enrollments, our educational and research achievements, and our payrolls have soared.
Unlike virtually every other state, New Jersey contributes practically nothing to the physical facilities of its four-year colleges and universities. There are no annual appropriations for this purpose, and there has been no higher education bond issue since 1988. This neglect of the state’s colleges and universities gravely imperils our ability to achieve what we can and what we must if New Jersey is to thrive and prosper.
Without better state support, our capacity to expand college opportunity for low- and middle-income students, to keep college affordable, and to contribute to the development of an educated, employable, economically stable, and engaged citizenry—is at risk.
Without better state support, our ability to ensure the quality of the state’s colleges and universities, to stem the brain drain of many of our best students who are leaving New Jersey, and to enhance New Jersey’s available workforce—is at risk.
Without better state support, our capacity to create new jobs, to stimulate and sustain economic growth, and to contribute to an attractive environment for business investment—is at risk.
Without better state support, our ability to expand research that creates new knowledge and technological innovation, provides opportunities for productive partnerships with business and industry, and garners greater federal and private support for research—is at risk.
Without better state support for colleges and universities, our capacity to maintain, let alone expand, what is already a major industry in our state, to employ thousands, to buy goods and services from New Jersey companies, and to put New Jerseyans to work through these purchases and through major construction projects—is at risk.
Members of the committee, as you refresh your work in a new legislature and with new leadership, please be our advocates so that the vital work of the colleges and universities is protected rather than imperiled. We recognize the difficulties that you face in helping New Jersey find answers to this recession. As you do, please remember that your colleges and universities have already demonstrated the capacity for enormously positive impacts on our economy. And we can do so much more. All of us look forward to working in partnership with you.
Madam Chairwoman, I would be pleased to answer any questions that you or your committee members may have. Thank you.
Sunday, March 15, 2009
Wednesday, March 11, 2009
Ph.D. in Neuroscience for the 21st Century
Course of Study
During the first year of their Ph.D., all students take the Neuroscience Core Course. The goal of this course is to provide a common foundation, so that all students have a strong knowledge base and a common language across the breadth of Neuroscience, a highly diverse and multidisciplinary field. To the extent possible, the course aims to teach an overview of all topics through a mix of hands-on laboratory experience, lecture, and computational modeling.
Ph.D. students must also choose and take two elective courses from those listed below. Rotate, during the first year, in up to three laboratories, participating in research projects during each rotation. Pass their general exam, which will include both a breadth component and a thesis proposal depth component, by the end of their second year. Most importantly students must carry out original research leading to a Ph.D. thesis.
QCN Track
Across the board, from molecular biology to physics to psychology, Princeton's world-class faculty is particularly strong in quantitative and theoretical investigations. The same is true in Neuroscience. In recognition of this, a Quantitative and Computational Neuroscience track exists within the Neuroscience Ph.D. Students in this track must fulfill all the requirements of the Neuroscience Ph.D. In addition, their electives should be in quantitative courses, and their Ph.D. research should be in quantitative and/or computational neuroscience.
List of Courses for all Neuroscience PhD. Students (Further information on the courses below can be found on the Princeton Registrar's web site.)
Neuroscience Core Course. This is the foundation for coursework in the Neuroscience Ph.D. In terms of time and effort, this course counts as two regular courses for each of the two semesters. Lectures, laboratory work, and computational studies are intertwined throughout the course.
Module 1: Neural Development and Plasticity (Wet Lab and Lecture)
Module 2: Cellular Neurophysiology (Wet Lab, Lecture, and Computational lab)
Module 3: Neural Coding (Wet Lab, Lecture, and Computational lab)
Module 4: Visual Neuroscience (fMRI and behavior lab, Lecture, and Computational lab)
Module 5: Executive Function (fMRI and EEG lab, Lecture, and Computational lab)
Module 6: Genetics and Imaging (Wet Lab, Lecture, and Computational lab)
Module 7: Evolution and Brain Structure (Lecture)
Module 8: Motor Control and Sequential Action (fMRI and TMS lab, Lecture, and Computational lab)
Module 9: Long-term memory (Lecture and Computational lab)
Neuroscience Electives
APC/MAT 351Topics in Mathematical Modeling - Mathematical Neuroscience This course combines modeling with applied math methods including PDE, probability, stochastic ODE, dynamical systems, cells as electrical circuits, Hodgkin-Huxely equation describing spikes in single neurons & bursting neurons (e.g., breathing, heartbeat, other rhythms), propagation of action potentials, reaction-diffusion equations, Hopfield-Grossberg neural nets, leaky accumulator models, drift-diffusion models, information theoretic approaches to analysis of neural spike trains.
MOL 408/PSY404 Cellular and Systems Neuroscience A survey of fundamental principles in neurobiology at the biophysical, cellular, and system levels. Lectures will address the basis of the action potential, synaptic transmission, sensory physiology and motor control, development of the central nervous system, synaptic plasticity, and disease states. A central theme will be the understanding of systems phenomena in terms of cellular mechanisms. (can be used as a first course in neuroscience for entering graduate students in Neuroscience who are coming from a different field and are not yet ready for the core curriculum)
MOL 431 Advanced Topics in Developmental Neurobiology Contemporary approaches to the study of neural development, emphasizing genetic and molecular techniques. Topics include generation, patterning, differentiation, migration and survival of neurons and glia, axon growth and guidance, target selection, synapse formation/elimination, activity-dependent remodeling of connectivity, and the relationship between neural development and behavior. Reading will be mainly from the primary literature with textbook reading provided for background. Classroom participation is required.
MOL 437/537 Computational Neuroscience Introduction to the biophysics of nerve cells and synapses, and the mathematical descriptions of neurons and neural networks. How do networks of neurons represent information, and how do they compute with it? The course will survey computational modeling and data analysis methods for neuroscience. Representation of visual information, navigation through space, short-term memory and decision-making will be some of the issues considered from a mathematical/computational viewpoint.
MOL 508 Advanced Topics in Neurobiology This course will focus on original scientific literature and class discussion with readings that center on major problems and current research in neuroscience.
MOL 510 Introduction to Biological Dynamics Designed for students in the biological sciences, this course focuses on the application of mathematical methods to biological problems. Intended to provide a basic grounding in mathematical modeling and data analysis for students who might not have pursued further study in mathematics. Topics include differential equations, linear algebra, difference equations, and probability. Each topic will have a lecture component and computer laboratory component. Students will work extensively with the computing package Matlab. No previous computing experience necessary.
MOL 549 Laboratory in Neuroscience The biophysics of neurons and synapses will be explored using electrophysiological and optical recording methods.
PSY 330 Introduction to Connectionist Models: Bridging Between Brain and Mind
A fundamental goal of cognitive neuroscience is to understand how psychological functions such as attention, memory, language, and decision-making arise from computations performed by assemblies of neurons in the brain. This course will provide an introduction to the use of connectionist models (also known as neural network or parallel distributed processing models) as a tool for exploring how psychological functions are implemented in the brain, and how they go awry in patients with brain damage.
PSY 336 The Diversity of Brains The premise of this seminar is that an understanding of the neural basis of behavior can be gained by examining species-typical behaviors. Each animal species has evolved neural solutions to specific problems posed to them by their environment. The course will focus primarily on forebrain mechanisms in mammals, highlighting the unique environmental problems that a species must solve and the ways in which the brains of these animals implement their solutions. Some example model systems include prey capture by bats, monogamy and aggression in voles, and eye gaze processing by primates.
PSY338/NEU338 Animal learning and decision making – psychological, computational and neural perspectives Seminar designed to expose students to a modern, integrative view of animal learning phenomena from experimental psychology, through the lens of computational models and current neuroscientific knowledge. At the psychological level we will concentrate on classical and instrumental conditioning. Computationally, we will view these as exemplars of prediction learning and action selection, the pillars of reinforcement learning. Neurally, we will focus on the roles of dopamine and the basal ganglia at the systems level. Students will see how the study of animal decision making can inform us about the computations that take place in the brain.
PSY 407 Developmental Neuroscience An analysis of cellular processes and regulatory factors that underlie vertebrate brain development and the development of behavior. Topics include: neurogenesis, neuronal migration, cell death, synapse formation, dendritic differentiation, as well as the influences of neurotransmitters, hormones, trophic factors and experience on developmental processes and behavior. In addition, conditions that induce abnormal brain development, and potentially result in the development of psychopathology, will be considered.
PSY 410 Depression: From Neuron to Clinic This course focuses on clinical depression, utilizing it as a model topic for scientific discourse. This topic is ideal for this purpose because it intersects a broad range of issues. The course focuses on a neurobiological approach to this personally and societally important subject. Topics range from the molecular to the clinical.
PSY 415 / MOL 415 Advanced Topics in Learning & Memory: Cellular and Molecular Mechanisms Seminar designed to expose students to current research on the cellular and molecular basis of learning and memory, providing an up-to-date analysis of what is, and is not known about the neurobiology of learning and memory. We begin with a review of the model systems used to study learning and memory, including an analysis of the translational validity of certain model systems. We then deal with different forms of plasticity (synaptic and structural) as they pertain to learning and memory during development and adulthood. Finally, we apply some of these findings to evaluate the current status of research on aging and Alzheimer's.
PSY 416 Brain Imaging in Cognitive Neuroscience Research This course will provide an introduction for advanced students on the use of functional brain imaging in cognitive neuroscience research. The first third of the course will cover the foundations of brain imaging in neurophysiology, imaging physics, experimental design, and image analysis. The rest of the course will be an examination of innovations in experimental design and methods of analysis that have opened new areas of cognitive neuroscience to inquiry using functional brain imaging.
PSY511 Neuroscience seminar series: Current Issues in Neuroscience and Behavior Advanced seminar that reflects current research on brain and behavior.
PSY 516: The Neural Basis of Goal-Directed Behavior A fundamental property of human action is its orientation toward specific desired outcomes or goals. Understanding the computations & neural mechanisms underlying this goal-directedness is a central challenge for both psychology and neuroscience. We'll review major theories characterizing the role of goals in behavior, from cognitive, social & developmental psychology, animal behavior research and artificial intelligence. Having established this conceptual context, we'll review a wide range of neuroscientific data to sketch out the neural substrates of goal-directed behavior, considering the neural basis of goal evaluation, selection, representation & pursuit.
PSY 591A Ethical Issues in Scientific Research Examination of issues in the responsible conduct of scientific research, including the definition of scientific misconduct, mentoring, authorship, peer review, grant practices, use of humans and of animals as subjects, ownership of data, and conflict of interest. Class will consist primarily of the discussion of cases. Required of all first and second year graduate students in the Department of Psychology. Open to other graduate students.
Other Courses of Interest to Neuroscience Graduate Students
APC 503 Analytical Techniques/Differential Equations
APC 514 Biological Dynamics
CHE 514 Molecular and Biomolecular Imaging
CHM 545/MOL512 Magnetic Resonance in Chemical Biology and Neuroscience
COS 402 Artificial Intelligence
COS 429 Computer Vision
COS 487 Theory of Computation
EEB 502/3 Fundamental Concepts in Ecology, Evolution, and Behavior
NEU 593 Magnetic Resonance Imaging
MAE 541/APC541 Applied Dynamical Systems
MAE 546 Optimal Control and Estimation
MOL 504 Cellular Biochemistry
MOL 506 Molecular Biology of Eukaryotes
MOL 507 Developmental Biology
MOL 510 Introduction to Biological Dynamics
MOL 515 Methods and Logic in Quantitative Biology
MOL 561 Scientific Integrity
PHY 561/2 Biophysics
PSY 543 Research Seminar in Cognitive Psychology
Silicea
Silicea is used in epilepsy that presents mainly in children
and young adults. The silicea type of patient is usually
distressed, especially at night or early in the morning,
often has frightful dreams, and presents with spasm of
limbs. The agitation, which increases with sleep deprivation,
can lead to a generalized tonic-clonic seizure. The
patient often describes the seizure spreading from the
solar plexus (the abdomen) to the brain. Attacks could be
preceded by coldness of left side, shaking, and twisting of
left arm. Patients could suffer from vertigo and tinnitus,
pressing bursting headaches over the eyes and the occiput,
and profuse night sweats and fever [14].
See Also Geoffrey E. Hinton
During the first year of their Ph.D., all students take the Neuroscience Core Course. The goal of this course is to provide a common foundation, so that all students have a strong knowledge base and a common language across the breadth of Neuroscience, a highly diverse and multidisciplinary field. To the extent possible, the course aims to teach an overview of all topics through a mix of hands-on laboratory experience, lecture, and computational modeling.
Ph.D. students must also choose and take two elective courses from those listed below. Rotate, during the first year, in up to three laboratories, participating in research projects during each rotation. Pass their general exam, which will include both a breadth component and a thesis proposal depth component, by the end of their second year. Most importantly students must carry out original research leading to a Ph.D. thesis.
QCN Track
Across the board, from molecular biology to physics to psychology, Princeton's world-class faculty is particularly strong in quantitative and theoretical investigations. The same is true in Neuroscience. In recognition of this, a Quantitative and Computational Neuroscience track exists within the Neuroscience Ph.D. Students in this track must fulfill all the requirements of the Neuroscience Ph.D. In addition, their electives should be in quantitative courses, and their Ph.D. research should be in quantitative and/or computational neuroscience.
List of Courses for all Neuroscience PhD. Students (Further information on the courses below can be found on the Princeton Registrar's web site.)
Neuroscience Core Course. This is the foundation for coursework in the Neuroscience Ph.D. In terms of time and effort, this course counts as two regular courses for each of the two semesters. Lectures, laboratory work, and computational studies are intertwined throughout the course.
Module 1: Neural Development and Plasticity (Wet Lab and Lecture)
Module 2: Cellular Neurophysiology (Wet Lab, Lecture, and Computational lab)
Module 3: Neural Coding (Wet Lab, Lecture, and Computational lab)
Module 4: Visual Neuroscience (fMRI and behavior lab, Lecture, and Computational lab)
Module 5: Executive Function (fMRI and EEG lab, Lecture, and Computational lab)
Module 6: Genetics and Imaging (Wet Lab, Lecture, and Computational lab)
Module 7: Evolution and Brain Structure (Lecture)
Module 8: Motor Control and Sequential Action (fMRI and TMS lab, Lecture, and Computational lab)
Module 9: Long-term memory (Lecture and Computational lab)
Neuroscience Electives
APC/MAT 351Topics in Mathematical Modeling - Mathematical Neuroscience This course combines modeling with applied math methods including PDE, probability, stochastic ODE, dynamical systems, cells as electrical circuits, Hodgkin-Huxely equation describing spikes in single neurons & bursting neurons (e.g., breathing, heartbeat, other rhythms), propagation of action potentials, reaction-diffusion equations, Hopfield-Grossberg neural nets, leaky accumulator models, drift-diffusion models, information theoretic approaches to analysis of neural spike trains.
MOL 408/PSY404 Cellular and Systems Neuroscience A survey of fundamental principles in neurobiology at the biophysical, cellular, and system levels. Lectures will address the basis of the action potential, synaptic transmission, sensory physiology and motor control, development of the central nervous system, synaptic plasticity, and disease states. A central theme will be the understanding of systems phenomena in terms of cellular mechanisms. (can be used as a first course in neuroscience for entering graduate students in Neuroscience who are coming from a different field and are not yet ready for the core curriculum)
MOL 431 Advanced Topics in Developmental Neurobiology Contemporary approaches to the study of neural development, emphasizing genetic and molecular techniques. Topics include generation, patterning, differentiation, migration and survival of neurons and glia, axon growth and guidance, target selection, synapse formation/elimination, activity-dependent remodeling of connectivity, and the relationship between neural development and behavior. Reading will be mainly from the primary literature with textbook reading provided for background. Classroom participation is required.
MOL 437/537 Computational Neuroscience Introduction to the biophysics of nerve cells and synapses, and the mathematical descriptions of neurons and neural networks. How do networks of neurons represent information, and how do they compute with it? The course will survey computational modeling and data analysis methods for neuroscience. Representation of visual information, navigation through space, short-term memory and decision-making will be some of the issues considered from a mathematical/computational viewpoint.
MOL 508 Advanced Topics in Neurobiology This course will focus on original scientific literature and class discussion with readings that center on major problems and current research in neuroscience.
MOL 510 Introduction to Biological Dynamics Designed for students in the biological sciences, this course focuses on the application of mathematical methods to biological problems. Intended to provide a basic grounding in mathematical modeling and data analysis for students who might not have pursued further study in mathematics. Topics include differential equations, linear algebra, difference equations, and probability. Each topic will have a lecture component and computer laboratory component. Students will work extensively with the computing package Matlab. No previous computing experience necessary.
MOL 549 Laboratory in Neuroscience The biophysics of neurons and synapses will be explored using electrophysiological and optical recording methods.
PSY 330 Introduction to Connectionist Models: Bridging Between Brain and Mind
A fundamental goal of cognitive neuroscience is to understand how psychological functions such as attention, memory, language, and decision-making arise from computations performed by assemblies of neurons in the brain. This course will provide an introduction to the use of connectionist models (also known as neural network or parallel distributed processing models) as a tool for exploring how psychological functions are implemented in the brain, and how they go awry in patients with brain damage.
PSY 336 The Diversity of Brains The premise of this seminar is that an understanding of the neural basis of behavior can be gained by examining species-typical behaviors. Each animal species has evolved neural solutions to specific problems posed to them by their environment. The course will focus primarily on forebrain mechanisms in mammals, highlighting the unique environmental problems that a species must solve and the ways in which the brains of these animals implement their solutions. Some example model systems include prey capture by bats, monogamy and aggression in voles, and eye gaze processing by primates.
PSY338/NEU338 Animal learning and decision making – psychological, computational and neural perspectives Seminar designed to expose students to a modern, integrative view of animal learning phenomena from experimental psychology, through the lens of computational models and current neuroscientific knowledge. At the psychological level we will concentrate on classical and instrumental conditioning. Computationally, we will view these as exemplars of prediction learning and action selection, the pillars of reinforcement learning. Neurally, we will focus on the roles of dopamine and the basal ganglia at the systems level. Students will see how the study of animal decision making can inform us about the computations that take place in the brain.
PSY 407 Developmental Neuroscience An analysis of cellular processes and regulatory factors that underlie vertebrate brain development and the development of behavior. Topics include: neurogenesis, neuronal migration, cell death, synapse formation, dendritic differentiation, as well as the influences of neurotransmitters, hormones, trophic factors and experience on developmental processes and behavior. In addition, conditions that induce abnormal brain development, and potentially result in the development of psychopathology, will be considered.
PSY 410 Depression: From Neuron to Clinic This course focuses on clinical depression, utilizing it as a model topic for scientific discourse. This topic is ideal for this purpose because it intersects a broad range of issues. The course focuses on a neurobiological approach to this personally and societally important subject. Topics range from the molecular to the clinical.
PSY 415 / MOL 415 Advanced Topics in Learning & Memory: Cellular and Molecular Mechanisms Seminar designed to expose students to current research on the cellular and molecular basis of learning and memory, providing an up-to-date analysis of what is, and is not known about the neurobiology of learning and memory. We begin with a review of the model systems used to study learning and memory, including an analysis of the translational validity of certain model systems. We then deal with different forms of plasticity (synaptic and structural) as they pertain to learning and memory during development and adulthood. Finally, we apply some of these findings to evaluate the current status of research on aging and Alzheimer's.
PSY 416 Brain Imaging in Cognitive Neuroscience Research This course will provide an introduction for advanced students on the use of functional brain imaging in cognitive neuroscience research. The first third of the course will cover the foundations of brain imaging in neurophysiology, imaging physics, experimental design, and image analysis. The rest of the course will be an examination of innovations in experimental design and methods of analysis that have opened new areas of cognitive neuroscience to inquiry using functional brain imaging.
PSY511 Neuroscience seminar series: Current Issues in Neuroscience and Behavior Advanced seminar that reflects current research on brain and behavior.
PSY 516: The Neural Basis of Goal-Directed Behavior A fundamental property of human action is its orientation toward specific desired outcomes or goals. Understanding the computations & neural mechanisms underlying this goal-directedness is a central challenge for both psychology and neuroscience. We'll review major theories characterizing the role of goals in behavior, from cognitive, social & developmental psychology, animal behavior research and artificial intelligence. Having established this conceptual context, we'll review a wide range of neuroscientific data to sketch out the neural substrates of goal-directed behavior, considering the neural basis of goal evaluation, selection, representation & pursuit.
PSY 591A Ethical Issues in Scientific Research Examination of issues in the responsible conduct of scientific research, including the definition of scientific misconduct, mentoring, authorship, peer review, grant practices, use of humans and of animals as subjects, ownership of data, and conflict of interest. Class will consist primarily of the discussion of cases. Required of all first and second year graduate students in the Department of Psychology. Open to other graduate students.
Other Courses of Interest to Neuroscience Graduate Students
APC 503 Analytical Techniques/Differential Equations
APC 514 Biological Dynamics
CHE 514 Molecular and Biomolecular Imaging
CHM 545/MOL512 Magnetic Resonance in Chemical Biology and Neuroscience
COS 402 Artificial Intelligence
COS 429 Computer Vision
COS 487 Theory of Computation
EEB 502/3 Fundamental Concepts in Ecology, Evolution, and Behavior
NEU 593 Magnetic Resonance Imaging
MAE 541/APC541 Applied Dynamical Systems
MAE 546 Optimal Control and Estimation
MOL 504 Cellular Biochemistry
MOL 506 Molecular Biology of Eukaryotes
MOL 507 Developmental Biology
MOL 510 Introduction to Biological Dynamics
MOL 515 Methods and Logic in Quantitative Biology
MOL 561 Scientific Integrity
PHY 561/2 Biophysics
PSY 543 Research Seminar in Cognitive Psychology
Silicea
Silicea is used in epilepsy that presents mainly in children
and young adults. The silicea type of patient is usually
distressed, especially at night or early in the morning,
often has frightful dreams, and presents with spasm of
limbs. The agitation, which increases with sleep deprivation,
can lead to a generalized tonic-clonic seizure. The
patient often describes the seizure spreading from the
solar plexus (the abdomen) to the brain. Attacks could be
preceded by coldness of left side, shaking, and twisting of
left arm. Patients could suffer from vertigo and tinnitus,
pressing bursting headaches over the eyes and the occiput,
and profuse night sweats and fever [14].
See Also Geoffrey E. Hinton
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