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PubMed2002

Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales.

We present further simulation results of the model of two reciprocally connected visual areas proposed in the first paper [Knoblauch and Palm (2002) Biol Cybern 87:151-167]. One area corresponds to the orientation-selective subsystem of the primary visual cortex, the other is modeled as an associative memory representing stimulus objects according to Hebbian learning. We examine the scene-segmentation capability of our model on larger time and space scales, and relate it to experimental findings. Scene segmentation is achieved by attention switching on a time-scale longer than the gamma range. We find that the time-scale can vary depending on habituation parameters in the range of tens to hundreds of milliseconds. The switching process can be related to findings concerning attention and biased competition, and we reproduce experimental poststimulus time histograms (PSTHs) of single neurons under different stimulus and attentional conditions. In a larger variant the model exhibits traveling waves of activity on both slow and fast time-scales, with properties similar to those found in experiments. An apparent weakness of our standard model is the tendency to produce anti-phase correlations for fast activity from the two areas. Increasing the inter-areal delays in our model produces alternations of in-phase and anti-phase oscillations. The experimentally observed in-phase correlations can most naturally be obtained by the involvement of both fast and slow inter-areal connections; e.g., by two axon populations corresponding to fast-conducting myelinated and slow-conducting unmyelinated axons.

Animals↗

PubMed2006

Comments on 'Is partial coherence a viable technique for identifying generators of neural oscillations?': Why the term 'Gersch Causality' is inappropriate: common neural structure inference pitfalls.

To aid prospective neural connectivity inference analysts and hoping to preclude misconception spread, we exploit the didatic value of some of the issues raised by Albo et al. (Biol Cybern 90: 318-326, 2004) who claim that signal-to-noise ratio (SNR) values can lead to mistakes in structural inference when using partial coherence in connection to Gersch's 1970 method for spotting signal sources (Gersch in Math Biosci 14: 177- 196, 1972). We show theoretically that Gersch's method is able only to spot which measurement of some common underlying factor has the least amount of additive noise and that this has nothing to do with any reasonable notion of 'causality' as suggested by Albo et al. (Biol Cybern 90: 318-326, 2004). We also show that despite the inherent structural ambiguity of the model used by Albo et al. (Biol Cybern 90: 318-326, 2004) to back their claim, its data can nonetheless furnish the correct time precedence hierarchy between the activities in its measured structures, both when simple (correlation) and more sophisticated methods are used (partial directed coherence) (Baccala and Sameshima in Biol Cybern 84:463-474, 2001a) in a true depiction of time series causality.

Animals↗

PubMedDate not supplied

Bursting as an effective relay mode in a minimal thalamic model.

In recent years, accumulating evidence indicates that thalamic bursts are present during wakefulness and participate in information transmission as an effective relay mode with distinctive properties from the tonic activity. Thalamic bursts originate from activation of the low threshold calcium cannels via a local feedback inhibition, exerted by the thalamic reticular neurons upon the relay neurons. This article, examines if this simple mechanism is sufficient to explain the distinctive properties of thalamic bursting as an effective relay mode. A minimal model of thalamic circuit composed of a retinal spike train, a relay neuron and a reticular neuron is simulated to generate the tonic and burst firing modes. The integrate-and-fire-or-burst model is used to simulate the neurons. After discriminating the burst events with criteria based on inter-spike-intervals, statistical indices show that the bursts of the minimal model are stereotypic events. The relation between the rate of bursts and the parameters of the input spike train demonstrates marked nonlinearities. Burst response is shown to be selective to spike-silence-spike sequences in the input spike train. Moreover, burst events represent the input more reliably than the tonic spike in a considerable range of the parameters of the model. In conclusion, many of the distinctive properties of thalamic bursts such as stereotypy, nonlinear dependence on the sensory stimulus, feature selectivity and reliability are reproducible in the minimal model. Furthermore, the minimal model predicts that while the bursts are more frequent in the spike train of the off-center X relay neurons (corresponding to off-center X retinal ganglion cells), they are more reliable when generated by the on-center ones (corresponding to on-center X ganglion cells).

Action Potentials↗

PubMed1993

An aggregation of pro and con evidence for medical decision support systems.

One promising way to increase the classification accuracy of medical decision support systems is to implement heuristic combinations of pattern recognition and artificial intelligence tools. A parallel between "cognition" model and differential diagnostic task is sketched accentuating the aggregation of activating and restraining inputs and corresponding PRO and CON evidence in medicine. On the basis of this paradigm a trainable model of a fuzzy neuron is proposed which resembles some elements from the physician's decision process. An example from aviation medicine is presented which demonstrates the enhanced performance.

Aerospace Medicine↗

PubMed1995

Mapping clause of Arden Syntax with HL7 and ASTM E 1238-88 standard.

The Arden Syntax is a standard description syntax for modular medical knowledge. The purpose of the Arden Syntax is to allow the construction of medical knowledge bases out of elementary medical logic modules (MLMs) that may be contributed and shared by different institutions. The format of the input data is not defined in the Arden Syntax, but left to the user. Every input and output must be rewritten for the local data access definition before an MLM can be used. It is suggested that by using the Health Level Seven (HL7) interface definition to define the communication and data transfer between the MLMs and the medical data base the shareability of MLMs can be enhanced.

Artificial Intelligence↗

PubMed1995

Practical approach to implementation of neural nets at the molecular level.

Potentialities for implementing simple neural net information processing devices based on chemical and biochemical dynamic media are discussed. This approach gives an opportunity to construct efficient systems capable of performing some primitive operations important for imaging processing.

Image Processing, Computer-Assisted↗

PubMedDate not supplied

Visualization and interactive exploration of multidimensional confocal images.

A confocal image analysis system is developed for automatic extraction of surface representation of biological structures. A visualization system is also developed to manipulate these surface representations and to obtain morphometrical parameters and provides a powerful tool for biomedical research such as microstructural characterization, morphogenesis, cell differentiation, tissue organization, and embryo development.

3T3 Cells↗

PubMedDate not supplied

Image analysis and computer vision in medicine.

Multimedia lives with images; medical images are born from digital imaging. A physician's multimedia workstation cannot exist without tools for manipulating images, performing measurements and, generally speaking, extracting and collecting pieces of information from the available data. Image analysis and computer vision constitute a wide and rapidly evolving field. This paper is intended as an introductory document for medical imaging researchers and practitioners wishing an overview of recent developments and trends. The major lines of activities in the domain are presented, under the common framework of a processing pipeline. After a presentation of the various stages of this pipeline, current subjects of research are indicated.

Computer Graphics↗

PubMed2005

Support vector machines committee classification method for computer-aided polyp detection in CT colonography.

RATIONALE AND OBJECTIVES: A new classification scheme for the computer-aided detection of colonic polyps in computed tomographic colonography is proposed. MATERIALS AND METHODS: The scheme involves an ensemble of support vector machines (SVMs) for classification, a smoothed leave-one-out (SLOO) cross-validation method for obtaining error estimates, and use of a bootstrap aggregation method for training and model selection. Our use of an ensemble of SVM classifiers with bagging (bootstrap aggregation), built on different feature subsets, is intended to improve classification performance compared with single SVMs and reduce the number of false-positive detections. The bootstrap-based model-selection technique is used for tuning SVM parameters. In our first experiment, two independent data sets were used: the first, for feature and model selection, and the second, for testing to evaluate the generalizability of our model. In the second experiment, the test set that contained higher resolution data was used for training and testing (using the SLOO method) to compare SVM committee and single SVM performance. RESULTS: The overall sensitivity on independent test set was 75%, with 1.5 false-positive detections/study, compared with 76%-78% sensitivity and 4.5 false-positive detections/study estimated using the SLOO method on the training set. The sensitivity of the SVM ensemble retrained on the former test set estimated using the SLOO method was 81%, which is 7%-10% greater than the sensitivity of a single SVM. The number of false-positive detections per study was 2.6, a 1.5 times reduction compared with a single SVM. CONCLUSION: Training an SVM ensemble on one data set and testing it on the independent data has shown that the SVM committee classification method has good generalizability and achieves high sensitivity and a low false-positive rate. The model selection and improved error estimation method are effective for computer-aided polyp detection.

Algorithms↗

PubMed2005

Classifying free-text triage chief complaints into syndromic categories with natural language processing.

OBJECTIVE: Develop and evaluate a natural language processing application for classifying chief complaints into syndromic categories for syndromic surveillance. INTRODUCTION: Much of the input data for artificial intelligence applications in the medical field are free-text patient medical records, including dictated medical reports and triage chief complaints. To be useful for automated systems, the free-text must be translated into encoded form. METHODS: We implemented a biosurveillance detection system from Pennsylvania to monitor the 2002 Winter Olympic Games. Because input data was in free-text format, we used a natural language processing text classifier to automatically classify free-text triage chief complaints into syndromic categories used by the biosurveillance system. The classifier was trained on 4700 chief complaints from Pennsylvania. We evaluated the ability of the classifier to classify free-text chief complaints into syndromic categories with a test set of 800 chief complaints from Utah. RESULTS: The classifier produced the following areas under the ROC curve: Constitutional = 0.95; Gastrointestinal = 0.97; Hemorrhagic = 0.99; Neurological = 0.96; Rash = 1.0; Respiratory = 0.99; Other = 0.96. Using information stored in the system's semantic model, we extracted from the Respiratory classifications lower respiratory complaints and lower respiratory complaints with fever with a precision of 0.97 and 0.96, respectively. CONCLUSION: Results suggest that a trainable natural language processing text classifier can accurately extract data from free-text chief complaints for biosurveillance.

Bayes Theorem↗

PubMed2006

Towards a computer-aided diagnosis system for vocal cord diseases.

OBJECTIVE: The objective of this work is to investigate a possibility of creating a computer-aided decision support system for an automated analysis of vocal cord images aiming to categorize diseases of vocal cords. METHODOLOGY: The problem is treated as a pattern recognition task. To obtain a concise and informative representation of a vocal cord image, colour, texture, and geometrical features are used. The representation is further analyzed by a pattern classifier categorizing the image into healthy, diffuse, and nodular classes. RESULTS: The approach developed was tested on 785 vocal cord images collected at the Department of Otolaryngology, Kaunas University of Medicine, Lithuania. A correct classification rate of over 87% was obtained when categorizing a set of unseen images into the aforementioned three classes. CONCLUSION: Bearing in mind the high similarity of the decision classes, the results obtained are rather encouraging and the developed tools could be very helpful for assuring objective analysis of the images of laryngeal diseases.

Cluster Analysis↗

PubMedDate not supplied

A model of motor control of the nematode C. elegans with neuronal circuits.

OBJECTIVE: Living organisms have mechanisms to adapt to various conditions of external environments. If we can realize these mechanisms on the computer, it may be possible to apply methods of biological and biomimetic adaptation to the engineering of artificial machines. This paper focuses on the nematode Caenorhabditis elegans (C. elegans), which has a relatively simple structure and is one of the most studied multicellular organisms. We aim to develop its computer model, artificial C. elegans, to analyze control mechanisms with respect to motion. Although C. elegans processes many kinds of external stimuli, we focused on gentle touch stimulation. METHODS: The proposed model consists of a neuronal circuit model for motor control that responds to gentle touch stimuli and a kinematic model of the body for movement. All parameters included in the neuronal circuit model are adjusted by using the real-coded genetic algorithm. Also, the neuronal oscillator model is employed in the body model to generate the sinusoidal movement. The motion velocity of the body model is controlled by the neuronal circuit model so as to correspond to the touch stimuli that are received in sensory neurons. CONCLUSION: The computer simulations confirmed that the proposed model is capable of realizing motor control similar to that of the actual organism qualitatively. By using the artificial organism it may be possible to clarify or predict some characteristics that cannot be measured in actual experiments. With the recent development of computer technology, such a computational analysis becomes a real possibility. The artificial C. elegans will contribute for studies in experimental biology in future, although it is still developing at present.

Algorithms↗

PubMed2006

Invariant visual object recognition: a model, with lighting invariance.

How are invariant representations of objects formed in the visual cortex? We describe a neurophysiological and computational approach which focusses on a feature hierarchy model in which invariant representations can be built by self-organizing learning based on the statistics of the visual input. The model can use temporal continuity in an associative synaptic learning rule with a short term memory trace, and/or it can use spatial continuity in Continuous Transformation learning. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and in this paper we show also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in for example spatial and object search tasks. The model has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene.

Animals↗

PubMed2003

Comparison of simulated annealing and mean field annealing as applied to the generation of block designs.

This paper describes an experimental comparison between a discrete stochastic optimization procedure (Simulated Annealing, SA) and a continuous deterministic one (Mean Field Annealing), as applied to the generation of Balanced Incomplete Block Designs (BIBDs). A neural cost function for BIBD generation is proposed with connections of arity four, and its continuous counterpart is derived, as required by the mean field formulation. Both strategies are optimized with regard to the critical temperature, and the expected cost to the first solution is used as a performance measure for the comparison. The results show that SA performs slightly better, but the most important observation is that the pattern of difficulty across the 25 problem instances tried is very similar for both strategies, implying that the main factor to success is the energy landscape, rather than the exploration procedure used.

Algorithms↗

PubMed2004

A via-point time optimization algorithm for complex sequential trajectory formation.

In our previous research, we proposed a method for the reproduction of complex movement trajectories and robot arm control that could mimic fast, skilled human movements. That method is based on bi-directional theory and uses a representation of a set of via-points as boundary conditions or control variables to perform robot arm trajectory control. The via-points are extracted from human movement data and the resultant via-point representation is able to regenerate handwritten characters, control a Kendama toy, and perform a tennis serve. The via-point information contains both spatial and temporal information, that is, the position on the trajectory and the time of passing through the via-point position, respectively. Trajectory generation is performed using the trajectory formation model based on the optimal criterion, namely, the smoothness criterion, for which the boundary conditions are both the position and the timing of the via-point information. However, generating a smooth trajectory at different movement speeds is quite difficult if the time of passing through the via-point position is unknown or different from the extracted via-point time. In this paper, we therefore propose a new algorithm which can determine temporal via-point information. Our proposed algorithm can generate roughly the same trajectory as the measured human trajectory from only the spatial information of via-point locations. The optimality and the convergence of the new algorithm are investigated theoretically, and the trajectory generated by the algorithm is shown in numerical experiments. It is shown that starting from arbitrary temporal information the proposed algorithm can produce an appropriate trajectory.

Algorithms↗

PubMed2006

TreeSOM: Cluster analysis in the self-organizing map.

Clustering problems arise in various domains of science and engineering. A large number of methods have been developed to date. The Kohonen self-organizing map (SOM) is a popular tool that maps a high-dimensional space onto a small number of dimensions by placing similar elements close together, forming clusters. Cluster analysis is often left to the user. In this paper we present the method TreeSOM and a set of tools to perform unsupervised SOM cluster analysis, determine cluster confidence and visualize the result as a tree facilitating comparison with existing hierarchical classifiers. We also introduce a distance measure for cluster trees that allows one to select a SOM with the most confident clusters.

Age Factors↗

PubMed2006

Activity and effective connectivity of parietal and occipital cortical regions during haptic shape perception.

It is now widely accepted that visual cortical areas are active during normal tactile perception, but the underlying mechanisms are still not clear. The goal of the present study was to use functional magnetic resonance imaging (fMRI) to investigate the activity and effective connectivity of parietal and occipital cortical areas during haptic shape perception, with a view to potentially clarifying the role of top-down and bottom-up inputs into visual areas. Subjects underwent fMRI scanning while engaging in discrimination of haptic shape or texture, and in separate runs, visual shape or texture. Accuracy did not differ significantly between tasks. Haptic shape-selective regions, identified on a contrast between the haptic shape and texture conditions in individual subjects, were found bilaterally in the postcentral sulcus (PCS), multiple parts of the intraparietal sulcus (IPS) and the lateral occipital complex (LOC). The IPS and LOC foci tended to be shape-selective in the visual modality as well. Structural equation modelling was used to study the effective connectivity among the haptic shape-selective regions in the left hemisphere, contralateral to the stimulated hand. All possible models were tested for their fit to the correlations among the observed time-courses of activity. Two equivalent models emerged as the winners. These models, which were quite similar, were characterized by both bottom-up paths from the PCS to parts of the IPS, and top-down paths from the LOC and parts of the IPS to the PCS. We conclude that interactions between unisensory and multisensory cortical areas involve bidirectional information flow.

Adult↗

PubMed2004

A silicon early visual system as a model animal.

Examples that show the transfer of our basic knowledge of brain function into practical electronic models are rare. Here we present a user-friendly silicon model of the early visual system that contributes to animal welfare. The silicon chip emulates the neurons in the visual system by using analog Very Large Scale Integration (aVLSI) circuits. It substitutes for a live animal in experiment design and lecture demonstrations. The neurons on this chip display properties that are central to biological vision: receptive fields, spike coding, adaptation, band-pass filtering, and complementary signaling. Unlike previous laboratory devices whose complexity was limited by the use of discrete components on printed circuit boards, this battery-powered chip is a self-contained patch of the visual system. The realistic responses of the chip's cells and the self-contained adjustment-free correct operation of the chip suggest the possibility of implementation of similar circuits for visual prosthetics.

Animals↗