Areas of Research
The MIT Department of Brain and Cognitive Sciences has an ambitious mission: to understand how the mechanisms of the brain give rise to the mind. To advance this vision, we bring together researchers, students, and faculty who study brain science at all levels.
Our researchers often cross the boundaries of established fields, or invent new disciplines entirely. Conceptually, however, we think of our research in four broad categories:
Research in cellular and molecular neuroscience strives to understand the brain at its most fundamental level by studying the mechanisms that control construction and maintenance of cellular and molecular circuits.
Work in this area creates a window into how neurons are born and migrate, and how they form synaptic connections. Understanding how synapses function and undergo plasticity also allows insights into the molecular underpinnings of memory formation in the brain. Studying the ways that neurons operate will move us closer to understanding how the brain develops and responds to outside stimuli. The interplay of the complex molecular machinery of the neuronal membrane with the dynamics of electrical potentials is critical to understanding the synaptic contacts where neurons communicate with each other. This leads to important questions at the systems level. The plasticity of these contacts, expressed by neuronal axons, allows robust behavioral modification to changing environmental stimuli and internal representations.
Disruptions of the molecular machines that underlie neuronal development and function are also at the heart of most neurological and psychiatric diseases. This provides strong motivation to define how these molecular and cellular pathways allow neurons to connect and communicate, and how they go awry in brain diseases.
Cellular and molecular neuroscience is a deep mystery, but it brings exciting and critical bridges to other facets of brain and cognitive science. Researchers at BCS are using the latest tools and technologies to unlock critical applications of molecular science, including the prospects of future genetic intervention that might one day lead to cures for brain diseases.
Our focus in these important areas will help bring about new treatments for both neurodevelopment diseases like autism, as well as late-onset neurodegenerative diseases like Alzheimer’s. These studies also promise new insights into how other brain-related disorders associated with aging alter the functional interplay of neuronal function and connectivity.
In systems neuroscience, researchers use animal models to emulate core cognitive processes. This allows for more detailed study of algorithms and neural circuits that produce the representations of the mind. Scientists examine how patterns of neuronal connections (circuits) give rise to patterns of neuronal activity, and how those patterns of neural activity give rise to overt behavioral and different internal neural states.
Systems neuroscience studies the processes that occur within our central nervous system. Animal models allow much more precise study and intervention in the neural circuits that underlie higher cognitive function. Although these models do not capture the full mental abilities of humans, they are selected such that they likely share evolutionarily conserved neuronal processing mechanisms that will generalize to human brain function.
This research is important to all aspects of our work. It provides detailed data that is used to build computational models of cognitive processes. It also allows us to test hypotheses about brain function by precisely intervening in the system in ways that are not possible in humans, such as neural or genetic manipulations.
These experiments are critical to building our understanding, as captured by computational models. They are also central to our exploration of possible ways to repair or augment broken neural circuits in diseased or disrupted states.
Because systems neuroscientists seek to understand the basis for cognitive, motivational, sensory, and motor processes, their work overlaps with that of our other research disciplines. These connections are critical in uncovering answers to basic questions about how we move, learn and feel.
Cognitive science is the scientific study of the human mind. It is a highly interdisciplinary field, combining ideas and methods from psychology, computer science, linguistics, philosophy, and neuroscience. The broad goal of cognitive science is to characterize the nature of human knowledge – its forms and content – and how that knowledge is used, processed, and acquired.
Active areas of cognitive research in the Department include language, memory, visual perception and cognition, thinking and reasoning, social cognition, decision making, and cognitive development.
The study of cognitive science within BCS illustrates the department’s philosophy that understanding the mind and understanding the brain are ultimately inseparable, even with the gaps that currently exist between the core questions of human cognition and the questions that can be productively addressed in molecular, cellular or systems neuroscience. To bridge these gaps, several cognitive labs maintain a primary or secondary focus on cognitive neuroscience research. There are many opportunities for interaction and collaboration between cognitive and neuroscience labs across BCS and its related centers.
Computational neuroscience uses the tools of mathematics and computers to develop theoretical models that test and expand our understanding of the workings of brain and behavioral processes. Unlike the related field of artificial intelligence, computation seeks not just to create intelligence out of machines, but to illuminate the processes that underlie sensation and perception, control of action, learning and memory, language, and other cognitive processes.
These theoretical studies offer the prospect of connecting diverse research constructs and paradigms, and of providing a new understanding of the algorithms that drive our “mental machinery.”
BCS scientists are focused on three key areas of computation:
- The study of the data representations and algorithms that autonomous systems might build to perform tasks that are important for human survival (closely related to artificial intelligence).
- The implementation and testing of circuits that are constrained by neuronal data but aim to accomplish the tasks above.
- The development of analysis and statistical tools for analyzing and visualizing neuroscience data.
Understanding something as complex as the human mind requires computational models that accurately translate the system’s internal workings. Models help us build formal bridges between any two levels of analysis. For example: from gene expression programs to regulation of neuronal connections (synapses), or from neuronal circuit connections to patterns of neuronal activity. Other examples include from patterns of neuronal activity to behavioral report and mental states, and last, from mental states to cognitive function.
As we work to build a complete picture of the neural mechanisms of the mind, it is necessary for us to link models of all levels. Models allow us to make predictions about behavior, to emulate key aspects of neural computations in other devices (brain inspired computing), and to consider the best ways to repair or augment key functions.