Faculty Bibliography

Here analytical and simulation results are presented characterizing the recoding arising when overlapping patterns of sensor input impinge on an array of model neurons with branched thresholded dendritic trees. Thus, the neural units employed are intended to capture the integrative behavior of pyramidal cells that sustain isolated Na(+) or NMDA spikes in their branches. Given a defined set of sensor vectors, equations were derived for the probability of firing of both branches and neurons and for the expected overlap between the neural firing patterns triggered by two afferent patterns of given overlap. Thus, both the sparseness of the neural representation and the orthogonalization of overlapping vectors were computed. Simulations were then performed with an array of 1000 neurons comprising 30,000 branches to verify the analytical results and confirm their applicability to systems (which include any practicable artificial system) in which the combinatorically possible branches and neurons are severely subsampled. A means of readout and a measure of discrimination performance were provided so that the accuracy of discrimination among overlapping sensor vectors could be optimized as a function of neuron structure parameters. Good performance required both orthogonalization of the afferent patterns, so that discrimination was accurate and free of interference, and maintenance of a minimum level of neural activity, so that some neurons fired in response to each sensor pattern. It is shown that the discrimination performance achieved by arrays of neurons with branched dendritic trees could not be reached with single-compartment units, regardless of how many of the latter are used. The analytical results furnish a benchmark against which to measure further enhancements in the performance of subsequent simulated systems incorporating local neural mechanisms which, while often less amenable to closed-form analysis, are ubiquitous in biological neural circuitry

The predominance of dopamine (DA) receptors at extrasynaptic vs. synaptic sites implies that DA signaling is by diffusion-based volume transmission. In this review, we compare characteristics that regulate extracellular DA behavior in substantia nigra pars compacta (SNc) and striatum, including regional differences in structure (a 40% greater extracellular volume fraction in SNc vs. striatum) and in dynamic DA uptake (a 200-fold greater DA uptake rate in striatum vs. SNc). Furthermore, we test the assumption of diffusion-based volume transmission for SNc and striatum by modeling dynamic DA behavior after quantal release using region-specific parameters for diffusion and uptake at 37 degrees C. Our model shows that DA uptake does not affect peak DA concentration within 1 mum of a release site in either SNc or striatum because of the slow kinetics of DATs vs. diffusion. Rather, diffusion and dilution are the dominant factors governing DA concentration after quantal release. In SNc, limited DAT efficacy is reflected in a lack of influence of uptake on either amplitude or time course of DA transients after quantal release up to 10 mum from a release site. In striatum, the lack of effect of the DAT within 1 mum of a release site means that perisynaptic DATs do not 'gate' synaptic spillover. This contrasts with the conventional view of DA synapses, in which DATs efficiently recycle DA by re-uptake into the releasing axon terminal. However, the model also shows that a primary effect of striatal uptake is to curtail DA lifetime after release. In both SNc and striatum, effective DA radius after quantal release is ~2 mum for activation of low-affinity DA receptors and 7-8 mum for high-affinity receptors; the corresponding spheres of influence would encompass tens to thousands of synapses. Thus, the primary mode of intercellular communication by DA, regardless of region, is volume transmission

Abnormal protein deposits are a common feature of many human diseases including Alzheimer's disease. In Alzheimer's disease, the appearance of tangles, composed of the microtubule associated protein tau, correlates with both cell death and symptom severity. However, are tau filaments simply markers of disease progression, or are they directly responsible for cell death? Due to conflicting findings from cell and animal models, it remains controversial whether tau polymers or smaller pre-fibrillar aggregates or tau monomers are the toxic species. Indeed, if monomeric or oligomeric species are mediators of disease, formation of larger tau filaments may prove beneficial to affected cells. This review will examine the findings regarding the toxicity of various tau species

Image denoising methods are often designed to minimize mean-squared error (MSE) within the subbands of a multiscale decomposition. However, most high-quality denoising results have been obtained with overcomplete representations, for which minimization of MSE in the subband domain does not guarantee optimal MSE performance in the image domain. We prove that, despite this suboptimality, the expected image-domain MSE resulting from applying estimators to subbands that are made redundant through spatial replication of basis functions (e.g., cycle spinning) is always less than or equal to that resulting from applying the same estimators to the original nonredundant representation. In addition, we show that it is possible to further exploit overcompleteness by jointly optimizing the subband estimators for image-domain MSE. We develop an extended version of Stein's unbiased risk estimate (SURE) that allows us to perform this optimization adaptively, for each observed noisy image. We demonstrate this methodology using a new class of estimator formed from linear combinations of localized 'bump' functions that are applied either pointwise or on local neighborhoods of subband coefficients. We show through simulations that the performance of these estimators applied to overcomplete subbands and optimized for image-domain MSE is substantially better than that obtained when they are optimized within each subband. This performance is, in turn, substantially better than that obtained when they are optimized for use on a nonredundant representation

Anatomical knowledge of the structures to be targeted and of the circuitry involved is crucial in stereotactic functional neurosurgery. The present study was undertaken in the context of surgical treatment of motor disorders such as essential tremor (ET) and Parkinson's disease (PD) to precisely determine the course and three-dimensional stereotactic localisation of the cerebellothalamic and pallidothalamic tracts in the human brain. The course of the fibre tracts to the thalamus was traced in the subthalamic region using multiple staining procedures and their entrance into the thalamus determined according to our atlas of the human thalamus and basal ganglia [Morel (2007) Stereotactic atlas of the human thalamus and basal ganglia. Informa Healthcare Inc., New York]. Stereotactic three-dimensional coordinates were determined by sectioning thalamic and basal ganglia blocks parallel to stereotactic planes and, in two cases, by correlation with magnetic resonance images (MRI) from the same brains prior to sectioning. The major contributions of this study are to provide: (1) evidence that the bulks of the cerebellothalamic and pallidothalamic tracts are clearly separated up to their thalamic entrance, (2) stereotactic maps of the two tracts in the subthalamic region, (3) the possibility to discriminate between different subthalamic fibre tracts on the basis of immunohistochemical stainings, (4) correlations of histologically identified fibre tracts with high-resolution MRI, and (5) evaluation of the interindividual variability of the fibre systems in the subthalamic region. This study should provide an important basis for accurate stereotactic neurosurgical targeting of the subthalamic region in motor disorders such as PD and ET

We present a mathematical model and provide an analysis of optical beam director systems composed of adaptive arrays of fiber collimators (subapertures), referred to here as conformal optical systems. Performances of the following two system architectures are compared: A conformal-beam director with mutually incoherent output laser beams transmitted through fiber collimators (beamlets), and a corresponding coherent system whose beamlets can be coherently combined (phase locked) at a remote target plane. The effect of the major characteristics of the conformal systems on the efficiency of laser beam projection is evaluated both analytically and through numerical simulations. The characteristics considered here are the number of fiber collimators and the subaperture and conformal aperture fill factors, as well as the accuracy of beamlet pointing

We analyze the potential efficiency of laser beam projection onto a remote object in atmosphere with incoherent and coherent phase-locked conformal-beam director systems composed of an adaptive array of fiber collimators. Adaptive optics compensation of turbulence-induced phase aberrations in these systems is performed at each fiber collimator. Our analysis is based on a derived expression for the atmospheric-averaged value of the mean square residual phase error as well as direct numerical simulations. Operation of both conformal-beam projection systems is compared for various adaptive system configurations characterized by the number of fiber collimators, the adaptive compensation resolution, and atmospheric turbulence conditions

Determining how a particular neuron, or population of neurons, encodes information in their spike trains is not a trivial problem, because multiple coding schemes exist and are not necessarily mutually exclusive. Coding schemes generally fall into one of two broad categories, which we refer to as rate and temporal coding. In rate coding schemes, information is encoded in the variations of the average firing rate of the spike train. In contrast, in temporal coding schemes, information is encoded in the specific timing of the individual spikes that comprise the train. Here, we describe a method for testing the presence of temporal encoding of information. Suppose that a set of original spike trains is given. First, surrogate spike trains are generated by randomizing each of the original spike trains subject to the following constraints: the local average firing rate is approximately preserved, while the overall average firing rate and the distribution of primary interspike intervals are perfectly preserved. These constraints ensure that any rate coding of information present in the original spike trains is preserved in the members of the surrogate population. The null-hypothesis is rejected when additional information is found to be present in the original spike trains, implying that temporal coding is present. The method is validated using artificial data, and then demonstrated using real neuronal data.