Ehud Kaplan - US grants

Our long-range objective is to understand the functional organization and dynamical activity of the cortex. The discovery of the columnar organization of the cortex has led to the notion that the columns are fundamental building blocks, from which larger functional units are constructed. The cortex is thus viewed as a crystal (a more or less regular array of repeating, similar modules. Our proposal will test and refine this modular hypothesis. We shall use optical imaging of the primary visual cortex of monkeys and cats, and simultaneously record electrical responses from small neuronal clusters and local field potentials. We shall thus obtain a spatio- temporal picture of the activity in the neural ensembles which encode various stimulus parameters. The data will be analyzed with extensions of Principal Component Analysis that we have developed. We address three major aims: 1) To test the modularity hypothesis we shall measure, in a large piece of cortical tissue, the full range of functional maps ( for orientation, color, spatial frequency etc.) together with the retinotopic map. We shall measure the periodicity of, and correlations among, the functional maps, to determine if they are commensurate. This will lead to a refined framework that could include possibly incommensurate cortical scales and interactions among cortical elements. 2) We shall investigate how the Principal Components (eigenfunctions) obtained from the optical images depend on the extent of the visual stimulus, to determine how the dynamical dimension of the primary visual cortex (viewed as a dynamical system) scales with size. 3) We shall study the concerted electrical responses of neuronal clusters, to clarify the link between optical signals and neuronal activity, and to deepen our understanding of the neuronal dynamics. Our study is aimed at an intermediate architectural level, and deals with the way in which the fundamental modalities of the visual world (orientation, size, color and so on) are analyzed in the primary visual cortex. Such knowledge is crucial for the construction of cortical models, which are essential for any quantitative understanding of critical function and dysfunction.

DESCRIPTION: (Adapted from the Investigator's Abstract) The purpose of the proposed research is to determine the quantitative relationship between neural activity in the cortex and intrinsic optical signals (signals that do not require the application of dyes). Optical imaging of the cortex, especially of intrinsic optical signals, has been used extensively in the past decade to explore the functional organization in the brain, especially in the visual cortex. Some of the reported results have been surprising and some remain controversial. Despite the natural appeal of the technique and the wide attention that its results have attracted, very little is known in quantitative detail about the coupling between the neural activity and the intrinsic optical signal, which has several components. Such knowledge is crucial for the proper interpretation of the activity and selectivity selectivity maps obtained with optical imaging. An investigation of the following questions is proposed: 1) What is the quantitative relationship between the neural activity and the optical signal? 2) Is the neural-optical relationship uniform across the cortex (isotropic)? 3) What aspects of neural activity (spikes, synaptic activity) are represented by the optical signal? 4) What is the contribution to the optical signal of the various functional or anatomical cell types in the cortex? The results of these studies will allow a quantitative interpretation of activity maps obtained not only by optical imaging, but also by other important imaging technologies that rely on the hemodynamic filter, such as fMRI and PET, which are now used not only in research but also as diagnostic tools in clinical practice.

[unreadable] DESCRIPTION (provided by applicant): How do thalamic neurons integrate their various feedforward and feedback inputs? Most of the inputs and synapses in the mammalian lateral geniculate nucleus (LGN) are extra-retinal, but the way in which these diverse inputs are integrated to control the flow of visual information from retina to cortex is not understood. In particular, the influence of the descending inputs from the cortex and the perigeniculate nucleus (PGN) on the spatiotemporal properties of receptive fields of LGN relay neurons is unknown, although the size and complexity of these inputs strongly suggest their importance, without them, the LGN might arguably be unnecessary. To address this knowledge gap, we shall combine physiological experiments with computational modeling to achieve the following aims: 1) Measure the spatiotemporal structure of receptive fields in the cat LGN before and during (reversible) inactivation of the descending feedback pathway from V1; 2) Compare spatial summation in the retina with that of LGN neurons with and without V1 feedback; 3) Measure the temporal transfer function of neurons in layer 6 of V1; 4) Construct computational models of LGN relay neurons that incorporate the descending pathway from V1 and the PGN, and 5) Validate the models' predictions against physiological measurements. The proposed modeling, which builds on our initial (static) feedback model, will employ the innovative simulation approach of population kinetics, and will be one of the first attempts to model the corticothalamic feedback and its dynamics. It will use parallel computation on a scale not commonly found in neuroscience: two clusters of powerful computers, and a very large IBM supercomputer, which can accommodate larger, more complex models than could have been attempted in the past. The results will advance our understanding of the role that the descending inputs to the LGN play in establishing its sensitivity, dynamics, receptive field structure and discharge pattern, and will provide a necessary stepping stone for future expansions of our evolving model of the early visual system. HEALTH RELEVANCE: A more complete knowledge of how the LGN combines its diverse inputs, and especially how its temporal behavior depends on the cortex, should lead to insights into its role in dynamical brain diseases, such as epilepsy. More generally, an understanding of the role of feedback circuits will help us understand other dynamical pathologies, such as Parkinson's disease. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Emotional stress affects millions of people, and is a major health-related expense in the US. Despite great advances in our knowledge of the molecular, cellular and genetic factors that are involved, precious little is known about the effects of emotional stress on the neuronal circuits and ensembles that are the mediators between the cellular pathologies and the dysfunctional behavior. Recent advances have made it possible, for the first time, to record simultaneously from many neurons in one (or several) brain areas, and to apply new analysis methods to such data. These advances are now poised to produce new insights into the network's dynamical behavior. We propose to record simultaneously from many neurons in those parts of the mammalian brain that have been shown to be involved in emotional stress and drug addiction, which include the Ventral Tegmental Area (VTA), Prefrontal Cortex (PFC) and Nucleus Accumbens (NAc). The recordings will be carried out in mice that have been subjected to the behavioral protocol of social defeat (SD), which is used as an animal model for emotional stress, and which results in two distinct behavioral phenotypes, called resilient and susceptible. We shall compare the effect of SD on the dynamical behavior and interactions among the neural populations in these two behavioral phenotypes, to test the hypothesis that SD induces (or is at least correlated with) changes in the dynamical network properties of the mesolimbic system. This research differs from most of the previous work in this area in combining 3 crucial features: 1) It focuses not on individual neurons, but on the dynamical behavior and interactions within the relevant brain networks;2) It is related to the behavioral state of the animal, and 3) It will be carried out in vivo, rather than in vitro. It will therefore provide new information, not currently available, about the neuronal ensembles that occupy a critical intermediate brain level, between single neurons and whole animal behavior. It will thus shed new light on the brain mechanisms that are involved in emotional stress, and will provide new ways to assess the effectiveness of drugs. PUBLIC HEALTH RELEVANCE: We plan to use modern methods of network analysis to investigate the hypothesis that emotional stress is caused by changes in the dynamical behavior of neuronal groups in specific parts of the brain. After being exposed to aggressive behavior from other mice, some mice show signs of emotional stress, while others remain resilient. We shall compare the network properties of the stressed and resilient mice to discover how the emotional stress changes the group behavior of their neuronal ensembles.