Simon Fraser University. University of Alberta. University of Toronto. McGill University. New York University. University of Southern California. Overview Students and faculty in the USC Neuroscience Graduate Program study questions spanning the entire spectrum of modern neuroscience research. Key questions include: how do molecules work together in time and space to build functioning nerve cells? How do individual neurons and their interconnections lead to the emergent properties of neural circuits? How do the information processing functions of neural circuits lead to complex behaviors, memories, emotions, and thought? Departing from the traditional focus on individual disciplines, USC Neuroscience is characterized by collaborative interactions between faculty and students working at many different levels of analysis, including research on cell-molecular neurobiology, systems-level analysis of neural circuits, neural engineering, and cognitive and computational neuroscience.
Brown University. Harvard University. The HILS academic areas shown represent the depth and breadth of current thinking in the life sciences. Prospective students can learn more about our programs and connect to them by clicking the links below. Academic Benefits Full access to faculty throughout the University – approximately 500 life sciences faculty – and to training resources of the entire University. abundant opportunities to participate in new interdisciplinary areas of study asthey developfreedom to move among programs, subject to specific program requirementsand lab availabilityintegrated research opportunities, including seminars with top facultyand workshops Degrees Offered The PhD The PhD degree signifies mastery of a broad discipline of scientific learning together with demonstrated competence in a specialized life sciences field within that discipline (the discipline is specified on the diploma).
The MD/PhD For more information about the MD/PhD program, go to www.hms.harvard.edu/md_phd. Biophysics Chemical Biology. Yale University. The scientific interests of the Neuroscience Track faculty at Yale represent the full range of the broad and rapidly growing field of neuroscience. Leaders in areas ranging from the genetic and structural analysis of single-membrane channels to the functional characterization of the neocortex are represented in a diverse group of outstanding scientists. In many research areas groups of faculty with different backgrounds apply complementary technologies to similar problems. The long and productive history of multidisciplinary collaboration between basic and applied sciences has also made Yale a leader in clinically relevant neuroscience. The neuroscience faculty members command more than half the university’s biomedical research budget and occupy more than 60,000 square feet of well-equipped laboratory space. The Faculty The interdisciplinary research programs of Yale neuroscience faculty are central to the Neuroscience Track in the Biological and Biomedical Sciences program.
The Ph.D. Stanford Institute for Neuro-Innovation & Translational Neurosciences - Stanford University School of Medicine. Research. In particular, we are interested in the mechanisms that underlie signal and information propagation in biological cellular neural networks, and the computational potential of such networks in the brain. There are some key things a network of cells must be able to do: Store different pieces of information, morph or modify stored information, and manipulate stored information. These must occur in some logical and physically constrained way that results in a meaningful outcome for the organism.
A broad objective of this work aims to understand how given a network of a certain size with a specific set of operational parameters (i.e. a defined amount of degrees of freedom), one can tell what kinds of structures (i.e. classes of objects) such a network can represent, how much information it can store (i.e. the size of the objects it can hold), and how a network can manipulate such objects. Another specific interest in our lab are glial neurobiology and neuron-astrocyte interactions. Dalhousie University. Undergraduate Neuroscience Society. MIT : Brain and Cognitive Sciences. Meditation-0505. Studies have shown that meditating regularly can help relieve symptoms in people who suffer from chronic pain, but the neural mechanisms underlying the relief were unclear.
Now, MIT and Harvard researchers have found a possible explanation for this phenomenon. In a study published online April 21 in the journal Brain Research Bulletin, the researchers found that people trained to meditate over an eight-week period were better able to control a specific type of brain waves called alpha rhythms. “These activity patterns are thought to minimize distractions, to diminish the likelihood stimuli will grab your attention,” says Christopher Moore, an MIT neuroscientist and senior author of the paper.
“Our data indicate that meditation training makes you better at focusing, in part by allowing you to better regulate how things that arise will impact you.” A 1966 study showed that a group of Buddhist monks who meditated regularly had elevated alpha rhythms across their brains. Network-control-0512. At first glance, a diagram of the complex network of genes that regulate cellular metabolism might seem hopelessly complex, and efforts to control such a system futile. However, an MIT researcher has come up with a new computational model that can analyze any type of complex network — biological, social or electronic — and reveal the critical points that can be used to control the entire system.
Potential applications of this work, which appears as the cover story in the May 12 issue of Nature, include reprogramming adult cells and identifying new drug targets, says study author Jean-Jacques Slotine, an MIT professor of mechanical engineering and brain and cognitive sciences. MIT and Northeastern University researchers devised a computer algorithm that can generate a controllability structure for any complex network. The red points are 'driver nodes,' which can control the rest of the nodes (green).Image: Mauro Martino Jean-Jacques SlotinePhoto: Patrick Gillooly. 150-brain-ai-symposium. In the 1950s and ’60s — when MIT’s Warren McCulloch and Walter Pitts were building networks of artificial neurons, John McCarthy and Marvin Minsky were helping to create the discipline of artificial intelligence and Noam Chomsky was revolutionizing the study of linguistics — hopes were high that tools emerging from the new science of computation would soon unravel the mysteries of human thought.
As the computational complexity of even the most common human cognitive tasks became clear, however, researchers trimmed their sails. Today, “artificial intelligence,” or AI, generally refers to the type of technology that helps focus point-and-shoot cameras or lets people verbally navigate airline reservation systems. The central theme of “Brains, Minds and Machines” — the last of a series of symposia celebrating MIT’s 150th anniversary — is that it’s time for artificial-intelligence research, cognitive science and neuroscience to get ambitious again. Revisiting robotics The 25-year itch.