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At least 145 records · Page 8Linked to original sources
PubMed2007

Detecting functional nodes in large-scale cortical networks with functional magnetic resonance imaging: a principal component analysis of the human visual system.

This study aimed to demonstrate how a regional variant of principal component analysis (PCA) can be used to delineate the known functional subdivisions of the human visual system. Unlike conventional eigenimage analysis, PCA was carried out as a second-level analysis subsequent to model-based General Linear Model (GLM)-type functional activation mapping. Functional homogeneity of the functional magnetic resonance imaging (fMRI) time series within and between clusters was examined on several levels of the visual network, starting from the level of individual clusters up to the network level comprising two or more distinct visual regions. On each level, the number of significant components was identified and compared with the number of clusters in the data set. Eigenimages were used to examine the regional distribution of the extracted components. It was shown that voxels within individual clusters and voxels located in bilateral homologue visual regions can be represented by a single component, constituting the characteristic functional specialization of the cluster(s). If, however, PCA was applied to time series of voxels located in functionally distinct visual regions, more than one component was observed with each component being dominated by voxels in one of the investigated regions. The model of functional connections derived by PCA was in accordance with the well-known functional anatomy and anatomical connectivity of the visual system. PCA in combination with conventional activation mapping might therefore be used to identify the number of functionally distinct nodes in an fMRI data set in order to generate a model of functional connectivity within a neuroanatomical network.

Adult↗
PubMed2006

From grid cells to place cells: a mathematical model.

Anatomical connectivity and recent neurophysiological results imply that grid cells in the medial entorhinal cortex are the principal cortical inputs to place cells in the hippocampus. The authors propose a model in which place fields of hippocampal pyramidal cells are formed by linear summation of appropriately weighted inputs from entorhinal grid cells. Single confined place fields could be formed by summing input from a modest number (10-50) of grid cells with relatively similar grid phases, diverse grid orientations, and a biologically plausible range of grid spacings. When the spatial phase variation in the grid-cell input was higher, multiple, and irregularly spaced firing fields were formed. These observations point to a number of possible constraints in the organization of functional connections between grid cells and place cells.

Animals↗
PubMed1992

Navigation by fragment fitting: a theory of hippocampal function.

This paper describes a computational theory of spatial learning and navigation and its possible realization in the hippocampus. In the theory, mammals store memories of their geographical environment as a large number of independent fragments. A typical fragment denotes a few prominent landmarks in some region, their geometric relations, and their nongeometric properties, such as smells and visual cues. Navigation involves piecing together current sense data and relevant fragments to form a local map of the animal's surroundings; this is like solving a jigsaw puzzle. This computational model has been implemented in a computer program, whose performance is broadly consistent with observed levels of animal performance, and laboratory results, in spatial learning. Possible realizations of the model in animal brains are discussed. Unlike some neural net models of spatial learning, the model is strongly geometric, and uses special neural structures to store and manipulate two-dimensional vectors and bearings. A possible neural architecture is described in which the hippocampus performs the geometric operations; this has a long-term memory for fragments (somewhere in the neocortex), which can associatively recall fragments into a number of parallel fragment fitters, in the dentate gyrus and CA3 regions. These vary the positions and orientations of their fragments, to optimize the fit of the fragments to each other and to the animal's recent sense data. A local map of the animal's surroundings is stored in CA1 and subicular regions, where matching of fragment positions and attributes takes place. Mismatches are passed back via the entorhinal cortex to improve the fit during the next hippocampal theta cycle. The model offers the potential for understanding current data on spatial learning, on the neuroanatomy of the hippocampus and on place cells in a coherent framework, as well as understanding the role of the hippocampus in nonpositional memory tasks. Comparisons with experimental data are given.

Animals↗
PubMed2005

Measurement of fiber orientation distributions using high angular resolution diffusion imaging.

High angular resolution measurements of diffusion are used to estimate the angular distribution and diffusion anisotropy of fibers in a voxel. A simple, axially symmetric model of diffusion in white matter fibers is used to relate diffusion measurements to fiber properties. The new technique is called fiber orientation estimated using continuous axially symmetric tensors (FORECAST). It is tested using both numerical simulation and in vivo measurements. The new method agrees with other methods in voxels containing single fibers, but resolves crossing fibers better, at least at the level of diffusion weighting used in this study (tr(b) = 1480 s/mm2). The simplifying assumptions of the model are tested by comparison with the "model-free" q-ball analysis of in vivo data and the results are shown to be in good agreement. The new method addresses the problem of partial volume averaging in diffusion tensor imaging and provides a basis for more reliable estimates of fiber orientation and fractional anisotropy.

Algorithms↗
PubMed1992

Far-field potentials in circular volumes: the effect of different volume sizes and intercompartmental openings.

Preliminary investigations of circular volume conductors suggested that far-field potential magnitude declines progressively slower with increasing radial distance from a current source and follows a cosine function with angular displacement of the recording electrode from the electrical generator's axis. Using circular volumes of 6 differing radii, the mathematical relationship between angle, radii, and far-field potential amplitude is determined. Previous theoretical relationships of amplitude versus dipolar spacing, current, and distance from a dipole generator in a bounded volume conducting medium are verified for the near-field. Far-field potentials in circular volumes are found to become constant at radii greater than 75% of the bounded volume's radius. Additionally, an adjoining volume conductor acts simply as a passive fluid-filled electrode (wick electrode) to the circular volume containing the generator until the intercompartmental opening to the circular volume exceeds 20% of its circumference. This finding was clinically supported by recording similar P9 somatosensory-evoked far-field potentials generated caudal to the foramen magnum from various portions of the cranium, whose connections to the torso, foramen magnum, and neck, average 6.2% and 17.8%, respectively. Finally, 3 circular volume conductors were connected in series by channels less than 20% of the volume conductor's circumference. Both adjoining circular volumes were equipotential to the far-field potential present at the boundary of the first circular volume containing the dipole generator. This observation supports the clinical finding of far-field potential transmission through multiple human bodies in conductive contact.

Action Potentials↗
PubMedDate not supplied

Diffusion tensor fiber tracking of human brain connectivity: aquisition methods, reliability analysis and biological results.

We present a description, biological results and a reliability analysis for the method of diffusion tensor tracking (DTT) of white matter fiber pathways. In DTT, diffusion-tensor MRI (DT-MRI) data are collected and processed to visualize the line trajectories of fiber bundles within white matter (WM) pathways of living humans. A detailed description of the data acquisition is given. Technical aspects and experimental results are illustrated for the geniculo-calcarine tract with broad projections to visual cortex, occipital and parietal U-fibers, and the temporo-calcarine ventral pathway. To better understand sources of error and to optimize the method, accuracy and precision were analyzed by computer simulations. In the simulations, noisy DT-MRI data were computed that would be obtained for a WM pathway having a helical trajectory passing through gray matter. The error vector between the real and ideal track was computed, and random errors accumulated with the square root of track length consistent with a random-walk process. Random error was most dependent on signal-to-noise ratio, followed by number of averages, pathway anisotropy and voxel size, in decreasing order. Systematic error only occurred for a few conditions, and was most dependent on the stepping algorithm, anisotropy of the surrounding tissue, and non-equal voxel dimensions. Both random and systematic errors were typically below the voxel dimension. Other effects such as track rebound and track recovery also depended on experimental conditions. The methods, biological results and error analysis herein may improve the understanding and optimization of DTT for use in various applications in neuroscience and medicine.

Adult↗
PubMed2005

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain.

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

Adult↗
PubMed1995

Synapse elimination, the size principle, and Hebbian synapses.

Synapse elimination at the vertebrate neuromuscular junction reduces a polyinnervated population of muscle fibers to a monoinnervated state. The function of this developmental phenomenon (if any) is unproven. A theoretical analysis of Hebbian (correlation) rules connecting presynaptic and postsynaptic activity and synaptic strength at the neuromuscular junction is presented. The following points are demonstrated: (1) Correlational competition leads to the reduction of polyinnervation to a stable monoinnervated state; (2) the competition gives rise to the size principle over a wide range of the plausible parameter space; (3) over a significant subrange, the competition selectively eliminates topographically incorrect synapses; and (4) in cases in which topographic projection errors overwhelm the system, both error correction and the development of the size principle are disrupted. Correlational competition may explain contradictory experimental results concerning the effects of stimulating or silencing subpopulations of motor neurons. It may also explain an otherwise puzzling instance of a breakdown in the size principle seen in humans undergoing neural regeneration. Taken together, these findings suggest a novel hypothesis for the function of synapse elimination at the neuromuscular junction: the establishment of the size principle.

Models, Neurological↗
PubMed2004

Modelling neuromotor ratings with floor-effects.

Associated movements (AMs) are a classical diagnostic tool to assess differences between normal children and children with some motor dysfunction. This paper presents a methodology to produce age- and gender-dependent reference-curves for AMs of normal children, for various tasks of a test battery. Data available consist of separate ratings of duration and extent of AMs, which are ordinal quantities with few levels. Other problems are severe age- and gender-dependent floor-effects (as well as some ceiling-effects), leaving little information for analysis at older ages. To get a better scale, we combined the two ordinal ratings into one meaningful and quasi-continuous quantity referred to as intensity of AMs. In order to solve problems due to floor-effects, ceiling-effects and discreteness, we assumed left- , right- and interval-censored values, respectively. We considered a censored regression problem and postulated a truncated normal distribution for the non-censored values (after an appropriate transformation of the data). Using Wei and Tanner's poor man's data augmentation algorithm, together with the technique of linear mixed effects modelling, useful reference-curves could be produced. In contrast to the cumulative probabilities approach for ordinal data, our methodology allows the calculation of individual age- and gender-standardized values, which puts us in a position to investigate numerous scientific questions.

Adolescent↗
PubMed2006

Bootstrap-based methods for testing factor-by-curve interactions in generalized additive models: assessing prefrontal cortex neural activity related to decision-making.

In many situations the effect of a continuous covariate on response varies across groups defined by levels of a categorical variable. This paper addresses generalized additive models incorporating the so-called factor-by-curve interaction. A local scoring algorithm based on local linear kernel smoothers was used to estimate the model. Two different types of bootstrap-based procedures are proposed for testing interaction terms, namely, the likelihood ratio test, and a procedure based on an estimate of the interaction terms. Given the high computational cost involved, binning techniques were used to speed up computation in the estimation and testing processes. A simulation study was conducted to assess the validity of these bootstrap-based tests. This methodology was applied to studying prefrontal cortex neural activity associated with decision-making in monkeys. The proposed statistical procedure proved very useful in revealing the neural activity correlates of decision-making strategies adopted by monkeys in accordance with different behavioural tasks.

Action Potentials↗
PubMed1988

A reevaluation of the mathematical models for simulating single-channel and whole-cell ionic currents.

We have developed a technique that allows for the simulation of both single-channel and whole-cell ionic currents given any arbitrary first-order kinetic scheme for the conformational states of an ion channel. The procedure is based on the solution of the master equation, which, in turn, is a general expression for a Markov process. The solution is expressed in terms of the eigenvalues and eigenvectors of the kinetic system and the system's deviation from equilibrium. Our derived expression provides a general recipe for the calculation of whole-cell currents. By further manipulation of this expression, we show how conditional probabilities are derived that can be used for the simulation of single-channel currents. We discuss computer implementation of the results so that complicated kinetic schemes can be solved numerically. Finally, we demonstrate the procedure by providing a worked example of a simple model of activation followed by inactivation.

Computer Simulation↗
PubMed1991

Where is the self? A neuroanatomical theory of consciousness.

The enigmatic nature of the experience of self-awareness is examined in the light of recent discoveries and, on this basis, combined with inferences derived introspectively from the experience of the phenomenon itself; a specific physical locus of this experience within the human brains is deduced-proposed. The fundamental premise in this work is that whereever conscious self-awareness is generated, the neuronal structure(s) involved must continually have access to an extremely precise representation of information derived from the sense of vision plus a great variety of other kinds of information so as to permit it to make decisions regarding actions (movements and their implementation) that promote the survival and perpetuation of the biological system in which the self is generated. First, a definitve set of criteria that define most of the inputs to and operations carried out by the self-awareness entity were assembled. This ensemble of functions was then compared with the connections and possible roles of specific neuroanatomical structures described in published literature, particularly the recent literature and particularly that concerned with the sense of vision. It was discovered that only one brain structure receives the prerequisite information from the sense of vision plus information derived from cortical memory stores plus a variety of other relevant sources needed to generate a coherent sense of selfness. This structure is the superior colliculus of the tectum. The superior colliculi not only receive a highly precise retinotopic representation of inputs to the eyes, but also receive inputs from a great variety of other structures, including many areas of the cerebral cortex, vestibular inputs, auditory inputs, "affective" inputs, and inputs that putatively define the positions of the eyes and of the head. This information, it is deduced, not only allows this structure to generate a continuing synthesis of representations of the self-vs.-environment, but also allows a part of it to assess the significance (probable meaning) of these integrated inputs with respect to the selection of an implementation of actions that serve the interests of the physical structure in which the self-experience is generated. The function of memory in this system not only involves the continually updated representation of where the self is with respect to items and objects in its environment, but also provides means through which the relevance of recorded experiences representing the past may be caused to affect the decision-making process.(ABSTRACT TRUNCATED AT 400 WORDS)

Awareness↗
PubMed1999

Toward a cultural neuropsychology: An alternative view and a preliminary model.

Any integrated theory of mind and behavior must address the dynamic interaction between neurobiological and sociocultural systems as possible causes for human action. Newer findings within the behavioral neurosciences have pointed to the brain's exceptional plasticity and flexibility and suggest that one's surroundings, including one's cultural environment, may directly influence the way the human nervous system becomes organized. In this paper, a preliminary connectionist model of culture-brain interaction is proposed in an effort to illustrate the possible contribution of cultural factors to the development of the individual human brain.

Behavior↗
PubMed2000

Statistical analysis and parsimonious modelling of dendrograms of in vitro neurones.

The processes whereby developing neurones acquire morphological features that are common to entire populations (thereby allowing the definition of neuronal types) are still poorly understood. A mathematical model of neuronal arborizations may be useful to extract basic parameters or organization rules, hence helping to achieve a better understanding of the underlying growth processes. We present a parsimonious statistical model, intended to describe the topological organization of neuritic arborizations with a minimal number of parameters. It is based on a probability of splitting which depends only on the centrifugal order of segments. We compare the predictions made by the model of several topological properties of neurones with the corresponding actual values measured on a sample of honeybee (olfactory) antennal lobe neurones grown in primary culture, described in a previous study. The comparison is performed for three populations of segments corresponding to three neuronal morphological types previously identified and described in this sample. We show that simple assumptions together with the knowledge of a very small number of parameters allow the topological reconstruction of representative (bi-dimensional) biological neurones. We discuss the biological significance (in terms of possible factors involved in the determinism of neuronal types) of both common properties and cell-type specific features, observed on the neurones and predicted by the model.

Animals↗
PubMed1999

A parallel distributed processing model of stimulus-stimulus and stimulus-response compatibility.

A parallel distributed processing (PDP) model is proposed to account for choice reaction time (RT) performance in diverse cognitive and perceptual tasks such as the Stroop task, the Simon task, the Eriksen flanker task, and the stimulus-response compatibility task that are interrelated in terms of stimulus-stimulus and stimulus-response overlap (Kornblum, 1992). In multilayered (input-intermediate-output) networks, neuron-like nodes that represent stimulus and response features are grouped into mutually inhibitory modules that represent stimulus and response dimensions. The stimulus-stimulus overlap is implemented by a convergence of two input modules onto a common intermediate module, and the stimulus-response overlap by direct pathways representing automatic priming of outputs. Mean RTs are simulated in various simple tasks and, furthermore, predictions are generated for complex tasks based on performance in simpler tasks. The match between simulated and experimental results lends strong support for our PDP model of compatibility.

Computer Simulation↗