Christof Koch - US grants

This effort deals with the use of concepts borrowed form recent developments in modelling of brain function. By issuing circuit elements with specified characteristics and interconnecting them in a dense manner (many elements - many interconnections among them) one is able to perform calculations in a parallel manner; such calculations being distributed throughout the interconnected elements. The properties of such circuits make them advantageous for such functions as pattern and motion recognition, generalization, and generally many calculational efforts which are difficult with conventional computers. Although the model can best be a primitive and crude representation of the complexities of biological neural systems, the concepts and approaches which have resulted from it have stimulated new and different approaches to many engineering problems.

The area of neuroengineering and parallel computing are closely related and their developments go hand in hand. Of the various ways in which a parallel computer can be implemented with individual computational processing elements, the hypercube is one. It is arrived at by taking the sequence of a point to a line, a line to a square, a square to a cube and subsequent generalizations to hypercube architectures. A processor is located at each vertex. Such a topology is not as tightly connected as others but is sufficient to allow significant speed-up in those calculations involving processors in relatively close neighborhoods. The neural architecture is connected much more densely. It is also analog and involves nonlinear summing of signals with subsequent thresholding (taking a large signal or nothing depending upon whether the sum is large or small). It is thus quite different, although it has parallelism in common. The hypercube is a good parallel computer on which to study the behavior of potential neuroengineering systems, for example an artificial vision system. Vice versa, the neuroengineering approaches in development are excellent tools by which to control the loading of the processors in a parallel machine such as the hypercube and to control the actual numerical procedure itself. The fields of endeavor are highly cross-disciplinary. The benefits to the engineering profession by support of such a parallel computing effort will be enormous in terms of speeds of processing and calculations which will be attained, as well as large problems which can ultimately be handled. The orientation of the specific cross-disciplinary team is that of neuroengineering. This is an effort which involves vision in particular and is directed towards its understanding and its operation as an engineering system. In addition, effort is being directed towards understanding of learning and memory processes. Learning in particular involves complex processing which for the moment is too complex and too little understood to be effectively, if at all, integrated into the hardware of a neuroengineered chip or optical system.

This action is to recommend a Presidential Young Investigator Award for Dr. Christof Koch. Dr. Koch is one of the most outstanding young investigators in the rapidly developing field of computational neuroscience. He combines a deep knowledge of neurobiology with excellent mathematical skills and real expertise in computer science. He has already created a classic work on the computational of motion in the dendritic tree of retinal ganglion cells. His work on image segmentation is very fundamental. Finally, his studies on the detailed biophysics of the electrical interactions in neural spines is bringing a highly quantitative approach to the study of learning in the nervous system.

Selective attention is the process whereby a subset of the incoming sensory stream is selected for further processing. In the case of visual attention, this process can be subdivided into two distinct types of selection. The first type entails the establishment of a spatial focus, for preferential processing of a single, circumscribed area of the visual field as needed for object analysis or recognition. The second type involves the establishment of a filter which selectively enhances one or more distinct visual channels across the visual field as a whole, such as to facilitate perception of all stimuli of a specific color, spatial frequency, or direction of motion. The principal investigators will study the neurobiological mechanism of selective visual attention, through computer modeling of the correlates of attention at the single cell level and the integration of visual processing and attentional control at the systems level.

9312224 Braun In prior work, we have studied concurrent visual task situations in which the observer directs visual attention at one part of a visual scene, thus leaving other parts unattended, but attempts to judge attributes of both the attended and unattended parts of the scene. These experiments have demonstrated that a significant amount of information, especially about salient objects, can be discriminated in unattended regions of the field of view. Here, we formulate a hypothesis which could explain these observations, and propose to test it psychophysically. This hypothesis is based on our earlier proposal that a "saliency map" guides visual attention. Our new hypothesis it states that the saliency map provides a rudimentary but functional alternative to visual attention, and that it can sometimes mediate nonattentive stimulus selection, nonattentive figure-ground segregation, and nonattentive access to awareness. To test this hypothesis, we propose to conduct experiments on unattended but salient objects, investigating feature discrimination, as well as feature conjunctions and other "binding" phenomena. Ongoing research in our laboratory, supported by the NSF grant "An integrated, neurally based model of selective, visual attention," (BIR 92-14238), aims to build a model of visual attention and the saliency map at the systems level, on the basis of neurally plausible elements. The psychophysical experiments proposed here will help to guide this effort and will help decide what perceptual phenomena (grouping, feature conjoining, apparent motion, tracking) should be our benchmarks in evaluating the model.***

This project will support five graduate research traineeships over a seven year period in the Computation and Neural Systems (CNS) Option at the California Institute of Technology. The CNS option brings together biologists, engineers, computer scientists, and physicists with an interest in learning how computation is done by the nervous system, and applying that knowledge to the design of computers. Work in this area is expected to lead to significant advances in many engineering applications as well as neurobiology.

9412426 Koch The goal of this study is to understand how the electrical signals (called spikes) generated by nerve cells encode information. Studying nerve cells that are part of the early visual or auditory pathways in the nervous system provides an opportunity to directly relate visual or auditory stimuli with the trains of spikes generated by these neurons. To understand how the nervous system works it is important to understand how time-varying signals such as the velocity of a moving target in the visual field of an animal is encoded in such spike trains. Another important issue is to understand how information encoded in neuronal spike trains depends on the biophysical properties of the nerve cells, the hardware of the nervous system. This group of investigators will apply methods of information theory, which up to now have been mainly used in the engineering sciences, to estimate the rate, in bits per second, at which nerve cells can transmit information and to understand better the nature of the encoding of time-varying signals in neuronal spike trains. The role of the biophysics of single cells in this information transmission will be investigated by performing realistic computer simulations of nerve cell activity.

DESCRIPTION (Adapted from applicant's abstract): The aim of this psychophysical project is to study the expression, and the neuronal mechanisms underlying this expression, of two forms of human visual attention: focal or serial attention and a saliency-based form of visual attention. This latter form of attention is believed to operate in parallel throughout the entire visual field and is based on center-surround type of neuronal operations. Preliminary psychophysical evidence supports two such forms of complementary attentional processes that can operate independently of each other. To further distinguish these two different attentional processes operating in the primate visual system, this study plans to carry out three sets of psychophysical experiments (using computer generated and controlled stimuli displayed on a monitor). The experiments address the question of whether there only exists a single form of focal attention, to what extent both forms of attention are influenced by prior visual experience on the subject and which of these two forms are necessary for conveying precise spatial relationships (e.g. the triangle is to the left of the circle). Computer modeling will be used to complement the experimental program. The scene will be represented in a large number of cortical maps, representing different features, such as intensity, color (red-green and blue-yellow), different orientations and motion. Neurons in these maps will have receptive fields operating at many different spatial scales and will interact with each other in accordance with the known physiology of the visual system of macaque monkeys and humans. The output of these neurons will feed into a single saliency map that expresses the conspicuity or saliency of particular features in images. This computer model will be used to replicate and predict psycho-physical performance.

9720353 Niebur The ability to learn and to adapt to a changing environment is one of the fundamental characteristics of life itself. The purpose of the proposed work is to develop, implement and test adaptation mechanisms which are modeled after their biological counterparts. The centerpoint of the project is the development of adaptive "neuromorphic" VLSI (Very-Large-Scale-Integrated) devices. Neuromorphic devices are similar to common computer chips but they are designed and operated in somewhat different regimes (analog variables instead of digital, subthreshold voltages instead of suprathreshold, and parallel processing instead of serial) which gives them properties much more similar to those of nerve cells than can be claimed of standard computer chips. While neuromorphic circuits have been designed and fabricated for about a decade, this work is one of the first to systematically incorporate learning and adaptation into that technology. This is accomplished by making use of recently developed design techniques (''floating gates'') which for the first time allow storage of learned values for periods of time (years) similar to the lifetimes of retention mechanisms encountered in animals and humans. Furthermore, while most of the previous work was concerned with the processing of sensory information (good examples being the "silicon retina" and "silicon cochlea"), this project also includes motor control and thus closes the behavioral loop, from sensory input to motor output which then again influences sensory input. The adaptive neuromorphic devices are integrated in a realistic model of the eye-movement control of primates (monkeys and humans), which is one of the best understood biological sensorimotor systems. Different mechanisms of adaptation and learning have been studied in monkeys and humans and the performance of the adaptive control system is evaluated by comparing with experimental data. The development of a hardware model for eye movements promises significant insights into the function of an important sensorimotor control system. Understanding human (and primate) eye control in the real world and how it adapts to changing situations may lead to the development of practical tools, for instance, for target detection and pursuit. More importantly, however, synthesizing a complex behavior will help us understand this and other behavioral patterns to a degree which is impossible to achieve with analytical methods alone.

This program will provide predoctoral training of graduate students preparing for research careers in "Computation and Neural Systems". It involves a total of 18 faculty members, 8 from the Division of Biology, 8 from the Division of Engineering and Applied Science, one from Physics and one with a joint appointment in Biology and in Engineering and Applied Science. This program is a continuation of a previous training grant supported by NIMH. The CNS program, established in 1986, is jointly organized by the Divisions of Biology, Engineering and Applied Science, and Physics, Mathematics and Astronomy. The program's objective is to provide trainees with a broad knowledge of an inherently multidisciplinary field, while at the same time requiring an appropriate depth of knowledge in the particular field of thesis research. Research is loosely structured around three strands: 1) to elucidate the biochemical, biophysical, anatomical and physiological basis of how computations are carried out within the nervous system; 2) to understand the neuroronal basis of attention, perception, memory and other cognitive tasks in humans and animals; and 3) to mimic the architectures and processing strategies used by nervous systems in engineered systems (both software and hardware). Since 1989, 41 graduate students have been awarded a PhD in CNS. Currently, 43 graduate students are enrolled. The major components of our training activities are: 1) Each student's individual research program under one or more faculty sponsors; 2) an organized curriculum of mandatory graduate courses; 3) preparations for two qualifying examinations; and 4) an extensive seminar program. Support is requested in each year for ten predoctoral CNS trainees. Criteria for admissions to the training program will be applicants who have given early and sustained interest in Neuroscience. All but one training faculty and students are housed in three adjacent buildings clustered adjacent to one other on the North-West corner of the campus. One entire floor in the Beckman Institute is given over to the CNS program and faculty, including both the Director's and the Co-Director's lab, a computer laboratory, a wet efectrophysiology classroom and a seminar room. The CNS program is searching for one or more new faculty members. A major brain FMRI facility for both human and non-human primates is being added to the program.

Much effort has focused in recent years on the temporal precision with which neurons respond to synaptic input or to direct current injection. This precision relates to the crucial issue of the nature of the neuronal code used to represent and transmit information. We propose to quantify the fundamental limits that noise places on temporal precision by measuring and analyzing the various noise sources, including (i) noise due to the stochastic nature of voltage-dependent ionic channels, (ii) the effect of "spontaneous" synaptic background firing and (iii) the noise introduced by the unreliable, probabilistic nature of synaptic transmission. 1. We intend to experimentally characterize these noise sources in neocortical neurons using pharmacological manipulations which allow us to isolate the contribution of individual noise sources like Na+, K+ or Ca2+ channels. We will use whole-cell patch recordings at the soma and dendrites of single neurons, and in pairs of connected neurons of an in vitro preparation, visualized using infrared optics. 2. We will repeatedly inject frozen current noise into the soma, the dendrite and the presynaptic neuron (using dual electrodes), and record the noise in the post-synaptic potential (sub-threshold PSPs) as well as the fitter in timing of the resulting spike train. This will allow us to compute the mutual information between the injected current and the output spike train. 3. We will compare these measurements with analytical and numerical models of thermal, channel and synaptic noise in weakly- active linear cables, obtained by incorporating the detailed morphology (that we will reconstruct following infra-cellular injection of biocytin) and the electrophysiological properties of these cells. 4. We will use theoretical techniques to derive measures of spike fitter and similarity between spike trains in terms of the noise sources and compare them against the experimental data obtained in step 2. Our research plan will lead to a quantitative picture of the properties of neuronal noise sources and their effect on the information capacity of individual cortical neurons.

This project aims to extend an existing simple saliency-based visual attention system to animated color video sequences so as to enable it to cue the object recognition module towards interesting locations in live video streams, and simultaneously to extend an existing model for object recognition to on-line adaptability through top-down signals and task- and object-dependent learning of features. The PIs will then integrate these attention and recognition models, by developing feedforward and feedback interactions between localization of regions of interest and object recognition in those regions. This will require substantial elaboration of both models, as well as specific work on their integration. The result will be a complete model of object localization and recognition in primates, with direct applicability to computer vision challenges. The PIs will next implement and deploy the combined model on a cluster of CPUs linked by very fast interconnect (just installed at USC) to allow for real-time processing, and will demonstrate its utility in a prototype video-conferencing application in which the on-line adaptive attentional component of the integrated system will quickly locate regions in the monitored environment where something interesting is happening (e.g., a user raising her hand in a conference room). The recognition part of the system will then be trained and refined on-line to recognize relatively simple hand signs (e.g., a finger pointing up, meaning that the user wishes to become the center of interest in a video-conference). This work will demonstrate two points: that a biologically-inspired approach to traditionally hard computer vision problems can yield unusually robust and versatile vision systems (which work with color video streams and quickly adapt to various environmental conditions, users, and tasks); and that computational neuroscience models of vision can be extended to yield real, useful and widely applicable computer vision systems, and are not restricted to testing neuroscience hypotheses under simple laboratory stimuli.

EIA-0218693
Poggio, Tomaso
MIT

Collaborative Research: CRCNS: Detection and Recognition of Objects in Visual Cortex

A three way collaboration between the laboratories of Profs. T. Poggio at MIT, D. Ferster at Northwestern University and C. Koch at Caltech is exploring and evaluating the hypotheses that the cortical organization and the neural mechanisms of visual recognition can be explained by a coherent theoretical framework built on two existing computational models for recognition and attention and, secondly, that a combination of physiological work on monkeys and cats, together with visual psychophysics can be used to test and refine the theory. The research is organized into three main projects. The work at MIT is guided by a quantitative hierarchical model of recognition, probing the relations between identification and categorization and the properties of selectivity and invariance of the neural mechanisms in IT cortex. The work at Northwestern University is testing a key prediction of the model about the nature of the pooling operation (a max operation vs. a linear sum) performed by complex cells in V1. The experiments are done in the anesthetized cat, intracellularly, to allow for a characterization of the underlying circuit and biophysical mechanisms. Finally, work at Caltech is extending the basic model of recognition by integrating it with a saliency-based attentional model. The computational component of this work, centered around the development of a quantitative model of visual recognition, constitutes the primary tool to enforce interactions between the investigators: the model suggests experiments and guides planning and interpreting new experiments.

[unreadable] DESCRIPTION (provided by applicant): The CMS program provides predoctoral training for graduate students preparing for research careers in Computation and Neural Systems at Caltech. Established in 1968, the 20 faculty are from three Divisions (Biology, Engineering, and Humanities). This application is a continuation of a previous NIMH training grant. The CMS program's objective is to provide trainees with a broad knowledge of a multidisciplinary field-spanning physics, engineering, applied mathematics, molecular biology, neuroscience, psychology, cognitive science and computer science-while at the same time requiring an appropriate depth of knowledge in one particular field. Research is structured around elucidating the molecular, biophysical, anatomical and physiological basis of how computations are carried out within biological systems; in understanding the neuronal basis of attention, perception, memory and other cognitive tasks in humans and animals in health and disease; and in mimicking the architectures and processing strategies used by nervous systems in engineered systems. Since 1990, 68 graduate students have been awarded a PhD in CNS. Currently, 45 graduate students are enrolled. Of these, 23 are assistant, associate or full professors and 17 are post-doctoral scholars. [unreadable] The major components of our training activities are: (i) each student's individual research program under one or two professors; (ii) an organized curriculum of mandatory graduate courses; (iii) preparations for two qualifying examinations; (iv) mandatory laboratory rotations; and (v) an extensive seminar program. Training faculty and students are housed in four adjacent campus buildings. Students have access to a range of facilities, including 3 new animal and human fMRI magnetic scanners combined with Caltech's small size, all of this makes for an intensive learning experience. [unreadable] [unreadable] Support is requested in each year for ten predoctoral CNS trainees. [unreadable] [unreadable] [unreadable]

Neurons communicate by both slow chemical and fast electrical signaling. The membranes of neurons are excitable, and the coordinated voltage fluctuation through the neuronal membrane is a fundamental function. By collectively changing their membrane potentials in a synchronous manner neurons can generate large electrical fields in their extraneuronal milieu. This project asks whether these collectively generated electrical fields can influence the activity of individual neurons. The proposed work impacts the understanding of how individual nerve cells are influenced by their electrical environment. Since neurons are not surrounded by a constant extracellular potential, it is critical to understand the effect of an inhomogeneous local field on a neuron's excitability. These inferred field effects could be relevant in any excitable, neuronal tissue.

Current understanding of the dynamics of the membrane potential in individual neurons and in small networks is based on the theories of linear and nonlinear electrical phenomena. A key assumption is that the extracellular potential does not vary significantly in space and its effect on the membrane potential along neuronal processes can be neglected. However, spatial inhomogeneities in the local electrical field at the sub-millimeter scale, challenge the assumption. Experimentally observed fluctuations in the local field potential can be as large as 1 to 3 mV and are large enough to potentially shift spike timing. Thus local electrical fields might entrain synchronization among the embedded neurons, both under normal and pathological conditions. Given the physics of hippocampal and neocortical tissue, such effects might therefore play an important role in information processing in health and disease.

The experimental part of this proposal will be carried out at Rutgers University, while the modeling will be done at Caltech. The broader impact of the proposal is to promote training of minority and female undergraduate students via a summer intern program. Also, the project has a strong interdisciplinary nature through the blend of experimental and computational components in the research. Understanding the effects of spatially varying external potential is also important for public safety. People are increasingly surrounded by devices that emit low- and high-frequency electro-magnetic fields. Devices such as electric power distribution systems, cell phones, and wireless WiFi nodes can create electrical fields with the potential to modify nerve funciton. There is also risk from the growing use of deep-brain, transcranial magnetic stimulators and other neuroprosthetic devices. These devices introduce external current sources into the nervous system, demanding a better understanding of the induced extracellular voltages on neuronal activity.

This Integrative Graduate Education and Research Traineeship (IGERT) award supports the development of a multidisciplinary graduate training program in Brain, Mind, and Society. Its purpose is to provide students with the analytical foundations and the experimental skills needed to pursue scientific careers at the intersection of neuroscience and the social sciences, who are capable of integrating neural, psychological, and economic approaches to attack basic and applied problems related to valuation, human decision making, and social exchange. Trainees will take a rigorously designed, largely team-taught course sequence, spanning from nervous system organization and function to mathematical models of decision making and social exchange. This coursework will be complemented by equal balance in cross-disciplinary laboratory research, thereby tightly integrating research training with scholarship to create true intellectual hybrids across both disciplines.
The Brain, Mind, and Society program emphasizes the inclusion of highly qualified underrepresented students through a four-tiered outreach program, Science Matters, involving a team-based mentorship program bringing together students from the this program, underrepresented undergraduate students at Cal State University, Los Angeles and underrepresented high school students in Los Angeles' Belmont Schools. The resulting diversity of the program's collaborative teams will reflect the program's broader impact in five key social application areas, which may ultimately provide a new scientifically-enriched discourse to help us understand critical social problems, in economic, therapeutic, educational, philosophical, and business and political applications. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries.

Several real-life decisions involve combining sensory and reward information, yet most previous research in human and animal literature has focused on either economic or sensory decision making in isolation. The proposed research bridges this gap by developing a behavioral and computational understanding of how sensory information about an object's visual attractiveness (salience) and economic information about its reward value combine to guide visual attention and decisions such as whether a search target is present or not in a cluttered, distracting background; and where to look next to find the target. In particular, the research will investigate the optimality of such sensory-economic decision making - do humans behave as reward-maximizing agents?

A potential application of this study is in designing reward incentives to detect rare, life-critical targets that are otherwise missed (e.g., bombs in airline passenger bags, cancers in medical images, and scud missiles in satellite images). The impact of this study extends to everyday decisions as well: when people go shopping and see multiple items on a display, where do they look - is attention guided to visually attractive items or rewarding items in the display or a combination of both? What people see influences what they buy (they cannot buy what they cannot see). A quantitative understanding of how salience and reward combine to influence where people look will lead to better designed user interfaces and displays for education and instruction material (e.g., in books, other visual media), that will draw the viewer's attention to important information by increasing its visual salience and reward value.

This three-year grant will purchase two pieces of equipment for magnetic resonance imaging of the brain at the California Institute of Technology. One equipment piece provides the best resolution in a horizontal orientation; the second provides imaging of behaving monkeys in vertical position. This will provide state-of-the-art tools for investigating brain structure and function in monkeys with noninvasive methods, and also provide opportunities for imaging post-mortem human brains. The technology will make possible a set of research studies on how the brain processes information, including how it sees faces, how it weighs different choices, and how it makes decisions and guides action. These are important questions in neuroscience, and the new equipment will greatly enhance science at the Caltech Brain Imaging Center. The grant will also provide opportunities for training of students and post-docs on the new equipment. This will include classes taught at Caltech as well as participation in individual research projects. The development of these new scientific tools will lead to a better understanding of how the brain works, and how it is "wired up." That knowledge, in turn, will contribute to efforts to build artificially intelligent systems. Taken together, the cutting-edge science enabled by the new equipment, and the training of the next generation of young scientists on it, will contribute substantially to cognitive neuroscience in America and worldwide.

We often make choices without knowing why or in some cases even without being aware that we made a choice at all. Moreover, we sometimes find ourselves having made choices that, with hindsight, we do not believe we should have made. For example, we might find ourselves with a cookie in our mouth despite firm intentions to diet; or we might find ourselves strongly liking or disliking a person without any knowledge of why.

These examples are puzzling because we tend to think that all choices are deliberate and based on information of which we are fully aware. Clearly, this is not the case. In fact, it may be the exception. Yet there must always be some signature of our choice, and of the ingredients that went into it, in our brains. In this research project, the Principal Investigators will conduct a series of studies that systematically explore what happens our brains when we make various kinds of decisions, some conscious, some non-conscious, using state-of-the-art tools from cognitive neuroscience: high resolution magnetic resonance imaging, and rare electrical recordings of the brain from neurosurgical patients. These studies will result in an unprecedented dissection of the different components that contribute to how we make decisions and provide novel insights into the role of consciousness in human behavior.

The studies will help to answer some important outstanding questions in neuroscience, psychology, and economics. How quickly do we make decisions? Are consciously made choices slower than ones made in the absence of consciousness? Do animals make conscious choices? How conscious are the choices made by people who are addicted to drugs, to shopping, or to gambling? Can we consciously override strong preferences of which we are not aware? Answering these questions will allow us to understand the mechanisms behind decision-making. It will also give us a deeper understanding of the nature of consciousness and what it contributes to human behavior. Finally, the insights obtained from our studies will lay the groundwork for engineering intelligent decision-making in computers, robots, and distributed systems.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

This NSF Major Research Instrumentation (MRI-R2) Award will enable a three-year grant to purchase an upgrade for a single piece of equipment for imaging the human brain at the California Institute of Technology. The upgrade, a 32-channel Total Imaging Matrix upgrade of a Siemens 3.0 Tesla MRI scanner, will substantially improve the resolution, the speed with which experiments can be done, and the kinds of imaging sequences that can be programmed. Taken together, these major enhancements will enable a range of questions about the structure, connectivity, and functioning of the human brain. Researchers at Caltech, in collaboration with a national and international consortium of scientists, will use the equipment to investigate how the brain makes financial decisions, how social information such as faces are processed, and how brain-machine interfaces can be built to decipher information from the brain to guide robotic prostheses. These are important, big open questions in neuroscience, and the new equipment will greatly enhance science at the Caltech Brain Imaging Center.

The grant will also provide opportunities for training of students and post-docs on the new equipment. This will include classes taught at Caltech as well as participation in individual research projects. The development of these new scientific tools will lead to a better understanding of how the brain works, how it is wired up, and how it may dysfunction in disease. That knowledge, in turn, will contribute to efforts to build artificially intelligent systems. Taken together, the cutting-edge science enabled by the new equipment, and the training of the next generation of young scientists on it, will contribute substantially to cognitive neuroscience in America and worldwide.

DESCRIPTION (provided by applicant): Project Summary/Abstract Neuroscientists monitor extracellular brain signals to infer the underlying neural mechanisms of computation and cognition. While intracellular and transmembrane processes have monopolized the interest of researchers, much less attention has been paid to extracellular eld eects. Yet, the quality and quantity of information retrieved from extracellular recording sessions critically depends on our understanding of the transfer function between intracellular activity and the ex- tracellular space. Moreover, it has been shown that endogenous extracellular elds do aect the state and function of individual neurons through ephaptic coupling. This provides a continuous non-synaptic feedback mechanism between the eld and individual neurons. In a collaborative eort, the laboratories of C. Koch and G. Buzsaki propose to unravel the origin and functionality of extracellular eld eects in the hippocampal CA1 region during theta and sharp waves activity by using a modeling/experimental approach. Computationally, by modeling a large number of biophysical realistic pyramidal and inhibitory interneurons making up the rat CA1 hippocampus subeld. These, in conjunction with glia cells, will be arranged in a 3-D resistive cytoplasm, and their extracellular contributions will be summed to yield the nal extracellular electrical potential associated with electrical activity in individual neurons. Patch-clamp experiments from individ- ual hippocampal neurons will shed light onto the intracellular and extracellular correlates of CA1 pattern activity. Recordings from anesthetized rats will be used to constrain these models and to test their accuracy. Simultaneous optical stimulation (in CA3 using ChR2 and related optogenetic techniques) and extracellular recording experiments in CA1 will be performed to manipulate ex- tracellular brain activity to answer a series of questions: (i) what is the detailed makeup of the extracellular eld in the hippocampus, (ii) what are its contributors (pre- versus post-synaptic ac- tivity, spiking currents, glia), and (iii) how does the eld serve to synchronize the underlying sub- and suprathreshold activity of CA1 neurons - even in the absence of direct synaptic coupling. This research will also bear on our understanding of a number of pathologies and their treatment, in particular on the initiation and spread of pathological hypersynchronziation, such as in epilepsy, and the short- and long-range eect of direct brain stimulation via electrical current, as in deep brain stimulation. Here, therapy ecacy crucially depends on a solid understanding of the eect of extracellular elds on neurons and neural circuits.