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Research Topics in Neuroscience >> Content Detail



Lecture Notes



Lecture Notes

These lecture summaries provide overviews of the topics covered by the professors, each of whom is a leader in their field.
Lecture 1: From Neurons to Neural Networks

The Liu Lab at MIT, where we are working to elucidate the biophysical mechanisms of plasticity in synapses, cells and networks. We are particularly interested in innovating new techologies that permit conclusive experiments - to understand the rules of plasticity in terms of their functional logic as well as their biological implementations. Ultimately we attempt to examine how rules at different functional levels (from synapse to network) interact. We believe that this integrative approach will eventually lead to a coherent general framework for neural plasticity.


A Culture System for Direct Neuronal Manipulation

We have perfected a culture system that allows us to grow dissociated neurons in a dish where they can be directly observed. The neurons form connections and self-assemble into functional networks, allowing us access to the same phenomena of plasticity that occur in vivo. The system is also amenable to genetic transfections, and provides a very short incubation period for studying the role of various genes. Best of all, the cultured cells can be viewed, measured and manipulated without dissection, providing what is perhaps the most convenient preparation for plasticity studies.


Synaptic Staining and Functional Visualization

The lab incorporates a wide variety of staining and dynamical imaging techniques for locating synapses and characterizing their functional capabilities. Functional dyes such as FM1-43 and FM4-64 are used in nearly all of our experiments to depict which synapses on a given cell or network are functional, as well as providing some index of the synapses’ strengths. We have also been experimenting with methods for using the exchange of these dyes to visualize synaptic activity, and have recently fostered collaborations to develop new staining molecules for better functional assays. These methods can combine with calcium-sensitive fluorescence and immunostaining to provide a visual description of the synapses along a cultured cell or neural network.


Stimulation and Recording of Single Synapses

A major challenge in studying the synapse is how to tell what observed effects are due to presynaptic factors and which to postsynaptic ones. A large proportion of the lab’s efforts have gone towards finding a technique to directly control the behavior of one side of the synapse – the presynaptic one – by replacing it with an artificial terminal under our control. By using a carefully optimized form of iontophoresis, we are able to deliver specified profiles of neurotransmitter directly to single synapses.

A slight holding potential can retain transmitter inside a quartz micropipette that can then be robotically positioned directly alongside a single synapse (located using dyes such as those described above). A specialized amplifier and software program then delivers an iontophoretic current to eject transmitter from the pipette, generating a time course that exactly mimics that observed during real synaptic transmission. A patch-clamped electrode on the receiving cell can then record any post-synaptic activity that results from this simulated presynaptic release. This method therefore allows the researcher to study the synapse one side at a time, by effectively replacing the presynaptic terminal with an artificial “terminal” capable of delivering arbitrary profiles of neurotransmitter.


Functional Mapping of Dendritic Trees

One of our recent techniques is to provide a complete functional description of a given neuron’s dendrites. After labeling functional synapses with FM1-43, automated computer software drives robotic manipulators to guide iontophoresis pipettes to synaptic sites. Applying iontophoretic pulses while patch clamping the postsynaptic cell then yields a functional description of each synapse’s strength. After approximately five minutes a dendritic tree of many synapses can be precisely mapped, giving information that can be useful for describing poly-synaptic interactions within a given neuron.


Confocal and Two-photon Microscopy

The use of cultured neurons permits direct visualization that we try to realize via the best optical equipment. The lab is equipped with three confocal microscopes, many with muiltiple lasers, that provide high-resolution imaging of cells and fluorscent markers during recording and stimulation. The lab has also recently gained access to a two-photon microscope setup, as well as acquired our own high-resolution digital video microcamera for rapid, real-time visualization of network activity.


Genetic Manipulations in Cultured Cells and Animal Models

We are also equipped with full facilities for transfecting our cell cultures with inserted genes, with up to 50% of all cells within a culture successfully transfected. Also, thanks to a collaboration with Prof. Susumu Tonegawa, we are able to probe questions of synaptic plasticity in vivo at the physiological and behavioral levels, by creating mice overexpressing or deficient in particular genes.


Computational Analysis and Biologically-inspired Modeling

The lab is unusual among groups working at a similar level of experimental biology in the number of students with computational backgrounds that we employ. Our group has numerous members with degrees in computer science and engineering, and we hope to continue to attract more. Modeling studies are currently underway to predict the transmitter release and binding kinetics at single synapses, while other models seek to discern equations governing the homeostasis of synaptic input. We especially hope to require computational analysis in the coming years as our cultured neural network technology matures. Towards this end, collaborations are currently underway with students in the Seung Lab for Theoretical Neurobiology.


Multi-electrode Arrays for Observing Cultured Neural Networks

One of our recent acquisitions is a 64-channel multi-electrode array, which supports recording and inducing the electrical activity of many cultured neurons. The system can be used in conjunction with patch clamp and iontophoresis, as well as our visualization protocols. Commercial software allows for in-depth analysis of network activity in real time, and stimulation protocols that automatically respond to the system's observations. We have been working on ways to deploy this system in an incubator to extend our interface with the cells from hours to days.


Lecture 2: Prefrontal Cortex and the Neural Basis of Cognitive Control

Our research interests center around the neural mechanisms for voluntary, goal-directed, behavior. Much effort is directed at the prefrontal cortex, a brain region associated with the highest levels of cognitive function.  We combine a sophisticated behavioral methodology with techniques for examining the activity of groups of neurons.

The prefrontal cortex (PFC), a cortical region at the anterior end of the brain, has long been known play a central role in orchestrating complex thoughts and actions.  Its damage or dysfunction seems to result in a loss of the brain's "executive".  It disrupts our ability to ignore distractions, hold important information "in mind", plan behavior, and control impulses.

Results from our laboratory suggests that the PFC provides an infrastructure for the rapid synthesis of the diverse information.  Its major function may be to acquire and implement our internal representations of the "rules of the game" needed to achieve a given goal in a given situation.  This could lay the foundation for the complex and elaborate forms of behavior observed in primates, in whom this structure is most elaborate.


Lecture 3: Hippocampal Memory Formation and the Role of Sleep

Research in the Wilson laboratory focuses on the study of information representation across large populations of neurons in the mammalian nervous system, as well as on the mechanisms that underlie formation and maintenance of distributed memories in freely behaving animals. To study the basis of these processes, the lab employs a combination of molecular genetic, electrophysiological, pharmacological, behavioral, and computational approaches. Using techniques that allow the simultaneous activity of ensembles of hundreds of single neurons to be examined in freely behaving animals, the lab examines how memories of places and events are encoded across networks of cells within the hippocampus ­ a region of the brain long implicated in the processes underlying learning and memory.

These studies of learning and memory in awake, behaving animals have led to the exploration of the nature of sleep and its role in memory. Previous theories have suggested that sleep states may be involved in the process of memory consolidation, in which memories are transferred from short to longer-term stores and possibly reorganized into more efficient forms. Recent evidence has shown that ensembles of neurons within the hippocampus, which had been activated during behavior are reactivated during periods of dreaming. By reconstructing the content of these states, specific memories can be tracked during the course of the consolidation process.


Lecture 4: The Formation of Internal Modes for Learning Motor Skills

In this talk, I will discuss a new perspective on how the central nervous system (CNS) represents and solves some of the most fundamental computational problems of motor control. In particular, I will discuss the task of transforming a planned limb movement into an adequate set of motor commands. To carry out this task the CNS must solve a complex inverse dynamic problem. This problem involves the trans-formation from a desired motion to the forces that are needed to drive the limb. The inverse dynamic problem is a hard computational challenge because of the need to coordinate multiple limb segments and because of the continuous changes in the mechanical properties of the limbs and of the environment with which they come in contact. A number of studies of motor learning have provided support for the idea that the CNS creates, updates and exploits internal representations of limb dynamics in order to deal with the complexity of inverse dynamics. In the talk I will discuss how such internal representations are likely to be built by combining the modular primitives in the spinal cord as well as other building blocks found in higher brain structures. Experimental studies on spinalized frogs and rats have led to the conclusion that the premotor circuits within the spinal cord are organized into a set of discrete modules. Each module, when activated, induces a specific force field and the simultaneous activation of multiple modules leads to the vectorial combination of the corresponding fields. I regard these force fields as computational primitives that are used by the CNS for generating a rich grammar of motor behaviors.


Lecture 5: Look and See: How the Brain Selects Objects and Directs the Eyes

Purpose of the Research

To determine how visual perception is processed by the brain and how visually guided eye movements are generated.

Methods

The methods used in the Schiller lab are:
  1. Physiological studies in non-human primates that utilize single-cell recordings, microstimulation, pharmacological manipulation, tissue inactivation and ablation.
  2. Behavioral studies in normal human subjects, in patients with brain infarcts, and in non-human primates that examine visual and oculomotor capacities.

Lecture 6: How the Brain Wires Itself

Plasticity and Dynamics in the Developing and Adult Cerebral Cortex

Plasticity, or the adaptive response of the brain to changes in inputs, is essential to brain development and function. The developing brain requires a genetic blueprint but is also acutely sensitive to the environment. The adult brain constantly adapts to changes in stimuli, and this plasticity is manifest not only as learning and memory but also as dynamic changes in information transmission and processing. The goal is to understand long-term plasticity and short-term dynamics in networks of the developing and adult cortex.



 



 








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