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PubMed1993

Neural organization of the locomotive oscillator.

We study the relation of neural development, organization, and activity to behavior. We provide a model of the locomotive oscillator, a neural system supplying alternating stimulation to extensor and flexor muscles creating an oscillatory motion. We propose a protocol by which this neural system starting from unstructured, unconnected neural populations develops structure and function. The protocol is studied by both computer simulation and mathematical analysis. Our main results are 1. The locomotive oscillator self-organizes and maintains its organization, assuming certain properties of the neural populations. 2. Imperfections disturbing the functional adequacy of the neural populations may lead to the deterioration and disappearance of the oscillatory behavior. 3. The locomotive oscillator may fail to organize if the development is not staged in time.

Animals↗
PubMed1993

A neural network model for kindling of focal epilepsy: basic mechanism.

A simple neural network model is proposed for kindling--the phenomenon of generating epilepsy by means of repeated electrical stimulation. The model satisfies Dale's hypothesis, incorporates a Hebb-like learning rule and has low periodic activity in absence of shocks. Many of the experimental observations are reproduced and some new experiments are suggested. It is proposed that the main reason for kindling is the formation of a large number of excitatory synaptic connections due to learning.

Animals↗
PubMed1993

Transient analysis of a chemical synaptic transmission.

The statistical dynamics of an impulse induced quanta turnover is studied by means of a nonstationary stochastic model--double barrier synapse--resulting from a previously developed mathematical theory of chemical synaptic transmission. An essential aspect of nonstationarities of the model is that the interpool quanta transfers follow binomial distribution at impulse arrival time, while in the absence of stimulation they obey Yule-Furry statistics. Under a variety of conditions, corresponding to those in actual experiments, the transient behaviour of the model is simulated and analysed in detail. As a result, the quantitative description of immediate and delayed components of synaptic action is introduced. If simulations of quantal fluctuations are performed numerically, then for the treatment of dynamic regularities, besides numerical procedures, an analytical method of envelopes is developed. It is supported by the theorems which reduce behaviour of the double-barrier synapse to the super-position of simpler solutions for single-barrier systems. With short-term facilitation quantitative analysis and simulations, the synaptic resonance phenomenon is theoretically predicted: different resonant frequencies are found at different levels of facilitation. The importance of this phenomenon treated as a clue to the information processing capabilities of a chemical synapse is discussed.

Animals↗
PubMed1993

A neural model for nonassociative learning in a prototypical sensory-motor scheme: the landing reaction in flies.

Nonassociative learning is an important property of neural organization in both vertebrate and invertebrate species. In this paper we propose a neural model for nonassociative learning in a well studied prototypical sensory-motor scheme: the landing reaction of flies. The general structure of the model consists of sensory processing stages, a sensory-motor gate network, and motor control circuits. The paper concentrates on the sensory-motor gate network which has an agonist-antagonist structure. Sensory inputs to this circuit are transduced by chemical messenger systems whose dynamics include depletion and replenishment terms. The resulting circuit is a gated dipole anatomy and we show that it gives a good account of nonassociative learning in the landing reaction of the fly.

Animals↗
PubMed1993

A biologically motivated and analytically soluble model of collective oscillations in the cortex. I. Theory of weak locking.

A model of an associative network of spiking neurons with stationary states, globally locked oscillations, and weakly locked oscillatory states is presented and analyzed. The network is close to biology in the following sense. First, the neurons spike and our model includes an absolute refractory period after each spike. Second, we consider a distribution of axonal delay times. Finally, we describe synaptic signal transmission by excitatory and inhibitory potentials (EPSP and IPSP) with a realistic shape, that is, through a response kernel. During retrieval of a pattern, all active neurons exhibit periodic spike bursts which may or may not be synchronized ('locked') into a coherent oscillation. We derive an analytical condition of locking and calculate the period of collective activity during oscillatory retrieval. In a stationary retrieval state, the overlap assumes a constant value proportional to the mean firing rate of the neurons. It is argued that in a biological network an intermediate scenario of 'weak locking' is most likely.

Animals↗
PubMed1993

The relationship between smoothness and performance during the practice of a lower limb obstacle avoidance task.

The relationship between performance (movement time) and smoothness was examined as subjects (n = 8) practiced a simple lower limb obstacle avoidance task. Smoothness was quantified by endpoint 3D jerk-cost, partitioned into magnitudinal and directional components. Data were collected with two WATSMART cameras at a sampling rate of 200 Hz for three sets of two trial blocks, including trials 1, 2, 13, 14, 25, and 26. Ten practice trials were performed between blocks of recorded trials. A DLT method was used to reconstruct 3D position coordinates of the fifth metatarsal of the subject's right (dominant) foot, considered to be the endpoint. After the data were smoothed with a fourth order, zero lag Butterworth filter, the time period was normalized so that a comparison of jerk-cost could be made between trials. Very rapid decreases in both movement time and jerk-cost measures were followed by gradual decreases, indicating that the movement became smoother as performance improved. Correlation coefficients between movement time and the various components of jerk-cost ranged from 0.70 to 0.78, supporting the hypothesis that moving more smoothly enables a person to move more rapidly during an obstacle avoidance task.

Cybernetics↗
PubMed1991

A self-organizing multiple-view representation of 3D objects.

We explore representation of 3D objects in which several distinct 2D views are stored for each object. We demonstrate the ability of a two-layer network of thresholded summation units to support such representations. Using unsupervised Hebbian relaxation, the network learned to recognize ten objects from different viewpoints. The training process led to the emergence of compact representations of the specific input views. When tested on novel views of the same objects, the network exhibited a substantial generalization capability. In simulated psychophysical experiments, the network's behavior was qualitatively similar to that of human subjects.

Cybernetics↗
PubMed1991

Speech recognition by an artificial neural network using findings on the afferent auditory system.

An artificial neural network which uses anatomical and physiological findings on the afferent pathway from the ear to the cortex is presented and the roles of the constituent functions in recognition of continuous speech are examined. The network deals with successive spectra of speech sounds by a cascade of several neural layers: lateral excitation layer (LEL), lateral inhibition layer (LIL), and a pile of feature detection layers (FDL's). These layers are shown to be effective for recognizing spoken words. Namely, first, LEL reduces the distortion of sound spectrum caused by the pitch of speech sounds. Next, LIL emphasizes the major energy peaks of sound spectrum, the formants. Last, FDL's detect syllables and words in successive formants, where two functions, time-delay and strong adaptation, play important roles: time-delay makes it possible to retain the pattern of formant changes for a period to detect spoken words successively; strong adaptation contributes to removing the time-warp of formant changes. Digital computer simulations show that the network detect isolated syllables, isolated words, and connected words in continuous speech, while reproducing the fundamental responses found in the auditory system such as ON, OFF, ON-OFF, and SUSTAINED patterns.

Acoustic Stimulation↗
PubMed1993

Pattern recognition in the neocognitron is improved by neuronal adaptation.

We demonstrate that equipping the neurons of Fukushima's neocognitron with the phenomenon that a neuron decreases its activity when repeatedly stimulated (adaptation) markedly improves the pattern discriminatory power of the network. By means of adaptation, circuits for extracting discriminating features develop preferentially. In the original neocognitron, in contrast, features shared by different patterns are preferentially learned, as connections required for extracting them are more frequently reinforced.

Adaptation, Physiological↗
PubMed1993

Characteristics of hand tremor time series.

Tremor is classified into physiological, essential, and parkinsonian tremor by means of clinical criteria. The aim of our work was to extract quantitative features from the measurements of the acceleration of human postural hand tremor. Different mathematical methods were adopted and modified in order to separate these three types of tremor. Best discrimination between physiological and pathological tremors has been achieved by methods distinguishing nonlinear from linear behavior. On the other hand, methods separating different forms of nonlinear behavior have been found to be superior in discriminating parkinsonian and essential tremor. By these methods physiological and pathological tremors can be separated with an error rate below 20% and essential and parkinsonian tremor with an error rate below 10%. This may help to classify tremor time series by objective mathematical criteria and may increase the understanding of the pathophysiological differences underlying these kinds of tremor.

Cybernetics↗
PubMed1993

Adaptive synaptogenesis constructs networks that maintain information and reduce statistical dependence.

This report demonstrates the effectiveness of two processes in constructing simple feedforward networks which perform good transformations on their inputs. Good transformations are characterized by the minimization of two information measures: the information loss incurred with the transformation and the statistical dependency of the output. The two processes build appropriate synaptic connections in initially unconnected networks. The first process, synaptogenesis, creates new synaptic connections; the second process, associative synaptic modification, adjusts the connection strength of existing synapses. Synaptogenesis produces additional innervation for each output neuron until each output neuron achieves a firing rate of approximately 0.50. Associative modification of existing synaptic connections lends robustness to network construction by adjusting suboptimal choices of initial synaptic weights. Networks constructed using synaptogenesis and synaptic modification successfully preserve the information content of a variety of inputs. By recording a high-dimensional input into an output of much smaller dimension, these networks drastically reduce the statistical dependence of neuronal representations. Networks constructed with synaptogenesis and associative modification perform good transformations over a wide range of neuron firing thresholds.

Adaptation, Physiological↗
PubMed1993

Examining the volume efficiency of the cortical architecture in a multi-processor network model.

The convoluted form of the sheet-like mammalian cortex naturally raises the question whether there is a simple geometrical reason for the prevalence of cortical architecture in the brains of higher vertebrates. Addressing this question, we present a formal analysis of the volume occupied by a massively connected network or processors (neurons) and then consider the pertaining cortical data. Three gross macroscopic features of cortical organization are examined: the segregation of white and gray matter, the circumferential organization of the gray matter around the white matter, and the folded cortical structure. Our results testify to the efficiency of cortical architecture.

Animals↗
PubMed1991

A learning network model of the neural integrator of the oculomotor system.

Certain premotor neurons of the oculomotor system fire at a rate proportional to desired eye velocity. Their output is integrated by a network of neurons to supply an eye position command to the motoneurons of the extraocular muscles. This network, known as the neural integrator, is calibrated during infancy and then maintained through development and trauma with remarkable precision. We have modeled this system with a self-organizing neural network that learns to integrate vestibular velocity commands to generate appropriate eye movements. It learns by using current eye movement on any given trial to calculate the amount of retinal image slip and this is used as the error signal. The synaptic weights are then changed using a straight-forward algorithm that is independent of the network configuration and does not necessitate backwards propagation of information. Minimization of the error in this fashion causes the network to develop multiple positive feedback loops that enable it to integrate a push-pull signal without integrating the background rate on which it rides. The network is also capable of recovering from various lesions and of generating more complicated signals to simulate induced post-saccadic drift and compensation for eye muscle mechanics.

Algorithms↗
PubMed1991

Comparison between single signed integral pulse frequency and sine wave crossing modulation techniques.

The single signed integral pulse frequency modulation (SS-IPFM) is used in modeling neural communication processes. The reference signal crossing and in particular sine wave crossings (SWC) are used to describe physiological processes like vision. Under some restrictions upon the input signal it is possible to define SS-IPFM and SWC systems with identical output for the same modulation input. These restrictions and the exact compositions of the encoders are examined by comparison of both SS-IPFM and SWC to general form of Pulse Position Modulation (PPM) technique.

Cybernetics↗
PubMed1991

Local and global principles of striate cortical organization: an advanced model.

A model of the functional architecture in monkey striate cortex is proposed, based on recent data, in which the global structure is a result of the local structure. The local structure itself is organized around the cytochrome oxidase blobs. It is characterized by different anisotropic distributions of preferred orientations in upper and lower layers. In particular, the upper layers show a bias for "radial" orientations and the lower layers show a bias for "concentric" orientations (Bauer and Dow 1989). This organization may derive from the symmetry of the visual field and visual system which tends to be radial or concentric rather than cartesian. Functionally, the increased sensitivities of the different radial and concentric maps of orientation and movement detectors seem to be an adaptive fit to optic flow fields on the retina during complex movements of the subject in its environment.

Animals↗
PubMed1991

Multifrequency behavioral patterns and the phase attractive circle map.

With relative phase as a collective variable or order parameter, phase attractive dynamics can capture the temporally coherent behavior of a large number of different experimental systems. We present results from multifrequency coordination experiments in humans showing: a) that phase attraction persists especially for low order frequency ratios; b) that short-term jumps from one phase relation to another occur within a frequency ratio; c) that the most stable frequency-ratios are low order; and d) that transitions frequently occur from higher order (e.g. 5:2, 4:3) to lower order (2:1, 1:1) frequency ratios. We study a modified sine circle map with built-in phase attractive dynamics that qualitatively accounts for these results. In this phase-attractive map, patterns arise from competition between external driving and intrinsic phase attractive dynamics. The relative strength of extrinsic and intrinsic parameters determines the width of Arnol'd tongues, thereby influencing the delay or acceleration of irregular behavior. Behavioral complexity is inversely proportional to tongue width, thus accounting for the relative difficulty of performing different multifrequency behaviors and why "errors" in such behavior are often seen to occur.

Behavior↗
PubMed1991

Simulated bipolar cells in fovea of human retina. I. Computer simulation.

This static bipolar cell (BC) model of the human fovea is based on a number of reasonable assumptions. The human fovea is directly responsible for visual acuity and color vision. The fovea can be considered as having two parts; a central fovea with only red- and green-sensitive cones and a parafovea with blue-sensitive cones added to the other two. A cone mosaic can be precisely organized spatially into unit hexagons that specify inputs to horizontal cells (HC) and BCs. The retina up to and including BCs is piece-wise linear, i.e. at a given steady-state adapting light intensity BC outputs are linear functions of the physical image. BC centers receive inputs directly from weighted cones, while antagonistic surrounds receive inverted inputs from HCs. Appropriate optical and chromatic filtering due to the eye that are taken from human data are incorporated into the model. Chromatic aberrations are simulated by three separate point spread functions that also are taken from human data. Automatic gain control of cones is a function of intensity and wavelength of the steady adapting light.

Color Perception↗
PubMed1991

Simulated bipolar cells in fovea of human retina. II. Spectral responses of bipolar cells.

The static model developed in Part I is used to study spectral responses of C-type bipolar cells (BC). Once unique loci are adjusted to their proper wavelengths, and with a specified set of absorption spectra for cones, spectral responses of C-type BCs are dependent on only the balance between BC receptive field center and surround responses. This is true regardless of cone mosaic or BC receptive field organization. The unique yellow loci for the r-g channel is set at 576.7 nm while the unique green locus for the blue-center BC is set at 517.7 nm. A unique orange locus for a combined r-g and bl-y channels is set at 600 nm by multiplying the blue-center BC response spectra by a factor of six before adding to the r-g channel.

Adaptation, Ocular↗