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Articles & Tech Transfers


GUI4GUI user guide
Abstract Frequently, a computer program requires input parameters to define a specific application prior to running it. For codes that require few input parameters, the usual method to define these parameters is to store them in a ...

A psychophysiological theory of reinforcement, drive, motivation, and attention
Abstract NA ...

Enhanced neural network shell for application programs
Abstract An enhanced neural network shell for application programs is disclosed. The user is prompted to enter in non-technical information about the specific problem type that the user wants solved by a neural network. The user also ...

Application specific intelligent microsensors
Abstract An intelligent microsensor module (10, 100, 210, 300, 355, 410) is provided that can fuse data streams from a variety of sources and then locally determine the current state of the environment in which the intelligent ...

Some nonlinear networks capable of learning a spatial pattern of arbitrary complexity
Abstract Introduction: This note describes some nonlinear networks which caD learn a spatial pattern, in "black and white," of arbitrary size and complexity. These networks are a special case of a collection of learning machines ~ ...

Some physiological and biochemical consequences of psychological postulates
Abstract This note lists some psychological, physiological, and biochemical predictions that have been derived from simple psychological postu]ates. These psychological postulates have been used to derive a nev learning theory, 1-3 ...

Global ratio limit theorems for some nonlinear functional differential equations, I
Abstract 1. Introduction. We study some systems of nonlinear functional-differential equations of the form(1)X(t)= A X(1) + B(Xi)X(t - r) + CO), t' 0,where X=(xi,, x„) is nonnegative, B(Xj) =jjB;j(t)jj is a matrixof nonlinear ...

On learning and energy-entropy dependence in recurrent and nonrecurrent signed networks
Abstract Learning of patterns by neural networks obeying general rules of sensory transduction and of converting membrane potentials to spiking frequencies is considered. Any finite number of cellsA can sample a pattern playing on ...

On the variational systems of some nonlinear difference-differential equations
Abstract This paper studies the variational systems of two closely related systemsof nonlinear difference-differential equations which arise in prediction- andlearning-theoretical applications ([1], [2], [31). The first system is ...

Some networks that can learn, remember, and reproduce any number of complicated space-time patterns, I.
Abstract 1. Introduction. This paper describes some networks 9R that can learn,simultaneously remember, and individually reproduce on demand any numberof spatiotemporal patterns (e.g., "motor sequences") of essentially arbitrary ...

Learning and energy-entropy dependence in some nonlinear functional-differential systems
Abstract 1. Introduction. This note describes limiting and oscillatory fea-tures of some nonlinear functional-differential systems having appli-cations in learning and nonstationary prediction theory. The mainresults discuss systems ...

On learning, information, lateral inhibition, and transmitters
Abstract A mathematical model with both a psychological and neurophysiological interpretation is introduced to qualitatively explain data about serial learning of lists. Phenomenasuch as bowing, anchoring, chunking, backward ...

On the production and release of chemical transmitters and related topics in cellular control
Abstract This paper makes some neurophysiological and biochemical predictionsconcerning transmitter production and release which are suggested bypsychological postulates. A main theme is the joint comrol of presynapticexcitatory ...

On learning of spatiotemporal patterns by networks with ordered ordered sensory and motor components, I: Excitatory components of the cerebellum
Abstract Many of our sensory and motor organs have linearly ordered components, for example the fingers on a hand, the tonotopic organization of the auditory system, the successivjeo ints on arms and legs,t he spine,e tc. This paper ...

Global ratio limit theorems for some nonlinear functional differential equations, II
Abstract Introduction: A previous note [l] introduced some systems of nonlinear functional-differential equations of the form X(t) = AX(t) + B(Xt)X(t - r) + C(t) i £ 0, where X~(xi, • - * , xn) is nonnegative, B(Xt) is a ...

On the global limits and oscillations of a system of nonlinear differential equations describing a flow of a probabilistic network
Abstract 1. INTRODUCTION: This paper considers various aspects of the global limiting and oscillatorybehavior of the following system of nonlinear differential equations.sx;(t) ...

Embedding fields: A theory of learning with physiological implications
Abstract A learning theory in continuous time is derived herein from simple psychologicalpostulates. The theory has an anatomical and neurophysiological interpretation interms of nerve cell bodies, axons, synaptic knobs, membrane ...

Neural dynamics of perceptual grouping: Textures, boundaries, and emergent segmentations
Abstract A real-time visual processing theory is used to analyze and explain a wide variety of perceptual grouping and segmentation phenomena, including the grouping of textured images, randomly defined images, and images built up ...

Some networks that can learn, remember, and reproduce any number of complicated space-time patterns, II.
Abstract 1. Introduction - This paper describes some networks ..lf that can learn, simultaneously remember,and perform individually upon demand any number of spatiotemporal patterns(e.g., "motor sequences" and "internal perceptual ...

Neural expectation: Cerebellar and retinal analogs of cells fired by learnable or unlearned pattern classes
Abstract Neural networks are introduced which can be taught by classical or instrumental conditioning to fire in response to arbitrary learned classes of patterns. The filters of output cells are biased by presetting cells whose ...

Neural dynamics of decision making under risk: Affective balance and cognitive-emotional interactions
Abstract A real-time neural network model, called affective balance theory, is developed to explain many properties of decision making under risk that heretofore have been analyzed using formal algebraic models, notably prospect ...

Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreading
Abstract A real-time visual processing theory is used to analyze real and illusory contour formation, contour and brightness interactions, neon color spreading, complementary color induction, and filling-in of discounted illuminants ...

Neural dynamics of attention switching and temporal order information in short-term memory
Abstract Reeves and Sperling (1986) have developed an experimental paradigm and a model to explain how attention switching influences the, storage oftemporal-order information in short-term memory (STM), or working memory. The ...

Neural dynamics of word recognition and recall: Attentional priming, learning, and resonance
Abstract Data and models about recognition and recall of words and non words are unified using a real-time network processing theory. Lexical decision and word frequency effect data are analyzed in terms of theoretical concepts that ...

Neural dynamics of attentionally-modulated Pavlovian conditioning: Conditioned reinforcement, inhib
Abstract A real-time neural network model is developed to explain data about the acquisition and extinction of conditioned excitors and inhibitors. Systematic computer simulations are described of a READ circuit, which joins together ...

Neural dynamics of speech and language coding: Developmental programs, perceptual grouping, and competition for short-term memory
Abstract Summary. A computational theory of how an observer parses a speech stream into context-sensitive language representations is described. It is shown how temporal lists of events can be chunked into unitized repre~ntations, ...

Spiking threshold and overarousal effects in serial learning
Abstract Possible dependencies of serial learning data on physiological parameters such as spiking thresholds, arousal level, and decay rate of potentials are considered in a rigorous learning model. Influence of these parameters on ...

Pattern formation, contrast control, and oscillations in the short-term memory of shunting on-center off-surround networks
Abstract The transformation of spatial patterns and their storage in short term memory by shunting neural networks are studied herein. Various mechanisms are described for real-time regulation of the amount of contrast with which a ...

On visual illusions in neural networks: Line neutralization, tilt aftereffect, and angle expansion
Abstract Certain visual illusion occur in neural networks that are capable of storing partially contrasted enhanced spatial patterns in short term memory (STM), and whose feature detectors are interconnected by nontrivial ...

On the dynamics of operant conditioning
Abstract Simple psychological postulates are presented which are used to derivepossible anatomical and physiological substrates of operant conditioning.These substrates are compatible with much psychological data aboutoperants. A ...

Pavlovian pattern learning by nonlinear neural networks
Abstract This note describes laws for the anatomy, potentials, spiking rules, and transmitters of some networks of formal neurons that enable them to learn spatial patterns by Pavlovian conditioning. Applications to spacetime pattern ...

The quantized geometry of visual space: The coherent computation of depth, form, and lightness
Abstract A theory is presented of how global visual interactions between depth, length, lightness, and form percepts can occur. The theory suggests how quantized activity patterns which reflect these visual properties can coherently ...

Processing of expected and unexpected events during conditioning and attention: A psychophysiological theory
Abstract Some recent formal models of Pavlovian and instrumental conditioning contain internal paradoxes that restrict their predictive power. These paradoxes can be traced to an inadequate formulation of how mechanisms of ...

Some developmental and attentional biases in the contrast enhancement and short-term memory of recurrent neural networks
Abstract This paper studies the global dynamics of neurons, or neuron populations,in a recurrent on-center off-surround anatomy undergoing nonlinearshunting interactions. In such an anatomy, a given population excitesitself and ...

Neural pattern discrimination
Abstract Some possible neural mechanisms of pattern discrimination are discussed, leading to neural networks which can discriminate any number of essentially arbitrarily complicated space-time patterns and activate cells which can ...

Decisions, patterns, and oscillations in nonlinear competitive systems with applications to Volterra-Lotka systems
Abstract This paper describes new properties of competitive systems which arise in population biology, ecology, psychophysiology, and developmental biology. These properties yield a global method for analyzing the geometric design ...

Intracellular mechanisms of adaptation and self-regulation in self-organizing networks: The role of chemical transducers
Abstract This paper describes mechanisms of intracellular and intercellular adaptation that are due to spatial or temporal factors. The spatial mechanisms support self-regulating pattern formation that is capable of directing ...

Embedding fields: Underlying philosophy, mathematics, and applications to psychology, physiology, and anatomy
Abstract This article reviews results on a learning theory that can be derived from simple psychological postulates and given a suggestive neurophysiological, anatomical, and biochemical interpretation. The neural networks described ...

On the development of feature detectors in the visual cortex with applications to learning and reaction-diffusion systems
Abstract Developmental mechanisms for tuning of visual cortex are derived from adult learning mechanisms: an adaptational property of shunting on-center off-surround networks that prevents saturation of parallel processed patterns at ...

Contour enhancement, short-term memory, and constancies in reverberating neural networks
Abstract A model of the nonlinear dynamics of reverberating on-center off-surround networks of nerve cells, or of cell populations, is analysed. The on-center off-surround anatomy allows patterns to be processed across populations ...

Absolute stability of global pattern formation and parallel memory storage by competitive neural networks
Abstract The process whereby input patterns are transformed and stored by competitive cellular networks is considered. This process arises in such diverse subjects as the short-tenD storage of visual or language patterns by neural ...

Biological competition: Decision rules, pattern formation, and oscillations
Abstract Competition solves a universal problem about pattern processing by cellular systems. Competition allows cells to automatically retune their sensitivity to avoid noise and saturation effects. All competitive systems induce ...

Adaptation and gain normalization: A comment on Ullman and Schechtman (1982)
Abstract A well-known process for adaptation and gain normalization is compared with the process described by S. Ullman and G. Schechtman (Proc. R. Soc. Lond. B 216, 299-313 (1982)). A neural interpretation of this process in terms ...

Competition, decision, and consensus
Abstract The following problem, in one form or another, has intrigued philosophers and scientists for hundreds of years: How do arbitrarily many individuals, populations, or states, each obeying unique and personal laws, ever succeed ...

Bisensory stimulation: Inferring decision-related processes from the P300 component
Abstract Three experiments were conducted to evaluate the P300 component of the human evoked response as an index of bisensory information processing. On different blocks of trials, subjects were presented with auditory stimuli ...

Schizophrenia: Possible dependence of associational span, bowing, and primacy vs. recency on spiking threshold
Abstract The hypothesis has been advanced thatcertain schizophrenic patients are in acontinual state of overarousal, leading topoor attention, and perhaps to schizophrenicpunning (Kornetsky and Eliasson, 1969;Maher, 1968). ...

A neural theory of punishment and avoidance, I: Qualitative theory
Abstract Neural networks are derived from psychological postulates about punishment and avoidance. The classical notion that drive reduction is reinforcing is replaced by a precise physiological alternative akin to Miller s ""Go"" ...

Behavioral contrast in short-term memory: Serial binary memory models or parallel continuous memory models?
Abstract This paper develops a model wherein STM primacy as well as recency effects can occur. The STM primacy effects can be used to generate correct immediate recall of short lists that have not been coded in LTM. The properties of ...

Neural dynamics of attentionally modulated Pavlovian conditioning: Blocking, inter-stimulus interval, and secondary reinforcement
Abstract Selective information processing in neural networks is studied through computer simulations of Pavlovian conditioning data. The model reproduces properties of blocking, inverted-U in learning as a function of interstimulus ...

A neural theory of punishment and avoidance, II: Quantitative theory
Abstract Quantitative neural networks are derived from psychological postulates about punishment and avoidance. The classical notion that drive reduction is reinforcing is replaced by a precise physiological altetAative akin to ...

Probing cognitive processes through the structure of event-related potentials during learning: An experimental and theoretical analysis
Abstract Data reporting correlated changes, due to learning, in the amplitudes and chronometry of several eventrelated potentials (ERPs) are compared to neural explanations and predictions of the adaptive resonance theory. The ERP ...

Cortical dynamics of three-dimensional form, color, and brightness perception, II: Binocular theory
Abstract A real-time visual processing theory is developed to explain how three-dimensional form, color, and brightness perceptsa re coherently synthesized. The theory describeEhJo w several undamental uncertainty principles which ...

Cortical dynamics of three-dimensional form, color, and brightness perception, I: Monocular theory
Abstract A real-time visual processing theory is developed to explain how three-dimensional form, color, and brightness percept. aJ re coherently synthesized. The theory describesh ow several fundamental uncertainty principles which ...

Competitive learning: From interactive activation to adaptive resonance
Abstract Functional and mechanistic comparisons are made between several network models of cognitive processing: competitive learning, interactive activation, adaptive resonance, and back propagation. The starting point of this ...

Masking fields: A massively parallel neural architecture for learning, recognizing, and predicting
Abstract A massively parallel neural network architecture, called a masking field, is characterized through systematic computer simulations. A masking field is a multiple-scale self-similar automatically gain-controlled ...

Computer simulation of neural networks for perceptual psychology
Abstract Computer simulations of neural network processes fill an important methodological niche, permitting the investigation of questions not resolvable by physiological, behavioral, or formal approaches alone. Two types of network ...

Neural dynamics of adaptive timing and temporal discrimination during associative learning
Abstract A neural network model that controls behavioral timing is described and simulated. This model, called the Spectral Timing Model, controls a type of timing whereby an animal or robot can learn to wait for an expectedg oal by ...

A neural architecture for visual motion perception: Group and element apparent motion
Abstract neural network model ormotion segmentation by visual cortex is described. The model s properties are illustrated by simulating on the computer data concerning group and element apparent motion, including the tendency for ...

Neural FACADES: Visual representations of static and moving form-and-color-and-depth
Abstract 1. Introduction: The Inadequacy of Visual Modules
This article discusses some implications for understanding vision of recent theoretical results concerning the neural architectures that subserve visual perception in humans ...

Neural dynamics of planned arm movements: Emergent invariants and speed-accuracy properties during trajectory formation
Abstract A real-time neural network model. called the vector-integration-to-endpoint( VITE) model is developed and used to simulate quantitatively behavioral and neural data about planned and passive arm movements.I nvariants of arm ...

A neural network architecture for preattentive vision
Abstract Recent results towards development of a neural network architecture for general-purpose preattentive vision are summarized. The architecture contains two parallel subsystems, the boundary contour system (BCS) and the feature ...

Cortical dynamics of visual motion perception: Short-range and long-range apparent motion
Abstract A large body of data is reviewed to support a new theory of motion perception described by S. Grossberg and M. E. Rudd (1989). The Motion Boundary Contour System is used to explain classical and recent data about motion ...

Adaptive vector integration to endpoint: Self-organizing neural circuits for control of planned movement trajectories
Abstract A neural network model is described for adaptive control of arm movement trajectories during visually guided reaching. The model clarifies how a child, or infant robot, can learn to reach for objects that it sees. Piaget has ...

Working memory networks for learning temporal order with application to 3-D visual object recognition
Abstract Working memory neural networks, called Sustained Temporal Order REcurrent (STORE) models, encode the invariant temporal order of sequential events in short-term memory (STM). Inputs to the networks may be presented with ...

Neural representations for sensory-motor control, I: Head-centered 3-D target positions from opponent eye commands
Abstract This article describes how corollary discharges from outflow eye movement commands can be transformed by two stages of opponent neural processing into a head-centered representation of 3-D target position. This ...

Neural representations for sensory-motor control, II: Learning a head-centered visuomotor representation of 3-D target position
Abstract A neural network model is described for how an invariant head-centered representation of 3-D target position can be autonomously learned by the brain in real time. Once learned, such a target representation may be used to ...

Neural dynamics of motion perception: Direction fields, apertures, and resonant grouping
Abstract A neural network model of global motion segmentation by visual cortex is described. Called the motion boundary contour system (BCS), the model clarifies how ambiguous local movements on a complex moving shape are actively ...

Vector associative maps: Unsupervised real-time error-based learning and control of movement trajectories
Abstract This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models ...

Why do parallel cortical systems exist for the perception of static form and moving form?
Abstract This article analyzes computational properties that clarify why the parallel cortical systems V1----V2, V1----MT, and V1----V2----MT exist for the perceptual processing of static visual forms and moving visual forms. The ...

Emergence of tri-phasic muscle activation from the nonlinear interactions of central and spinal neural network circuits
Abstract The origin of the tri-phasic burst pattern, observed in the EMGs of opponent muscles during rapid self-terminated movements, has benn controversial. Here we show by computer simulation that the pattern emerges from ...

A solution of the figure-ground problem for biological vision
Abstract A neural network model of 3-D visual perception and figure-ground separation by visual cortex is intro¬duced. The theory provides a unified explanation of how a 2-D image may generate a 3-D percept; how figures pop-out from ...

Adaptive neural networks for control of movement trajectories invariant under speed and force rescaling
Abstract This article describes two neural network modules that form part of an emerging theory of how adaptive control of goal-directed sensory-motor skills is achieved by humans and other animals. The Vector-1ntegration-To-Endpoint ...

A neural network model of adaptively timed reinforcement learning and hippocampal dynamics
Abstract A neural model is described of how adaptively timed reinforcement learning occurs. The adaptive timing circuit is suggested to exist in the hippocampus, and to involve convergence of dentate granule cells on CA3 pyramidal ...

A neural network model for cursive script production
Abstract This article describes a neural network model, called the VITEWRITE model, for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to ...

A self-organizing neural model of motor equivalent reaching and tool use by a multijoint arm
Abstract This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other ...

Synchronized oscillations during cooperative feature linking in a cortical model of visual perception
Abstract A neural network model of synchronized oscillations in visual cortex is presented to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these ...

A spectral network model of pitch perception
Abstract A model of pitch perception, called the spatial pitch network or SPINET model, is developed and analyzed. The model neurally instantiates ideas from the spectral pitch modeling literature and joins them to basic neural ...

Rules for the cortical map of ocular dominance and orientation columns
Abstract Three computational rules are sufficient to generate model cortical maps that simulate the interrelated structure of cortical ocular dominance and orientation columns: a noise input. a spatial band passfilter. and ...

A neural model of the saccade generator in the reticular formation
Abstract A neural model is developed of the neural circuitry in the reticular formation that is used to generate saccadic eye movements. The model simulates the behavior of identified cell types - such as long-lead burst neurons, ...

Neural representations for sensory-motor control, III: Learning a body-centered representation of 3-D target position
Abstract This article describes how corollary discharges from outflow eye movement commands can be transformed by two stages of opponent neural processing into a head-centered representation of 3-D target position. This ...

Self-organization of binocular disparity tuning by reciprocal corticogeniculate interactions
Abstract This article develops a neural model of how sharp disparity tuning can arise through experience-dependent development of cortical complex cells. This learning process clarifies how complex cells can binocularly match left ...

Cortical computation of stereo disparity
Abstract Our ability to see the world in depth is a major accomplishment of the brain. Previous models of how positionally disparate cues to the two eyes are binocularly matched limit possible matches by invoking uniqueness and ...

Cortical dynamics of feature binding and reset: Control of visual persistence
Abstract An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset ...

Fast learning VIEWNET architectures for recognizing 3-D objects from multiple 2-D views
Abstract The recognition of three-dimensional (3-D) objects from sequences of their two-dimensional (2-D) views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With ...

A cortico-spinal model of reaching and proprioception under multiple task constraints
Abstract A model of cortico-spinal trajectory generation for voluntary reaching movements is developed to functionally interpret a broad range of behavioral, physiological, and anatomical data. The model simulates how arm movements ...

A neural network model for the development of simple and complex cell receptive fields within cortical maps of orientation and ocular dominance
Abstract Prenatal development of the primary visual cortex leads to simple cells with spatially distinct and oriented ON and OFF subregions. These simple cells are organized into spatial maps of orientation and ocular dominance that ...

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition
Abstract Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and ...

Neural dynamics of motion processing and speed discrimination
Abstract A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the ...

A self-organizing neural network architecture for navigation using optic flow
Abstract This article describes a self-organizing neural network architecture that transforms optic flow and eye position information into representations of heading, scene depth, and moving object locations. These representations ...

A neural model of motion processing and visual navigation by cortical area MST
Abstract Cells in the dorsal medial superior temporal cortex (MSTd) process optic flow generated by self-motion during visually guided navigation. A neural model shows how interactions between well-known neural mechanisms (log polar ...

Figure-ground separation by visual cortex
Abstract Figure-ground perception enables us to perceive objects that are distinct from one another and from their scenic background. The remarkable nature of figure-ground perception may be better appreciated when we reflect that ...

A neural model of the saccadic eye movement control explains task-specific adaptation
Abstract Multiple brain learning sites are needed to calibrate the accuracy of saccadic eye movements. This is true because saccades can be made reactively to visual cues, attentively to visual or auditory cues, or planned in ...

Neural dynamics of binocular brightness perception
Abstract How does the visual cortex combine information from both eyes to generate perceptual representations of object surfaces? Important clues about this process may be derived from data about the perceived brightness of surface ...

A neural model of first-order and second-order motion perception and magnocellular dynamics
Abstract A neural model of motion perception simulates psychophysical data concerning first-order and second-order motion stimuli, including the reversal of perceived motion direction with distance from the stimulus (Γ display), and ...

A neural model of smooth pursuit control and motion perception by cortical area MST
Abstract Smooth pursuit eye movements (SPEMs) are eye rotations that are used to maintain fixation on a moving target. Such rotations complicate the interpretation of the retinal image, because they nullify the retinal motion of the ...

Frequency-dependent synaptic potentiation, depression, and spike timing induced by Hebbian pairing
Abstract Experiments by Markram and Tsodyks (Nature, 382 (1996) 807?810) have suggested that Hebbian pairing in cortical pyramidal neurons potentiates or depresses the transmission of a subsequent pre-synaptic spike train at ...

A model of movement coordinates in the motor cortex: Posture-dependent changes in the gain and direction of single cell tuning curves
Abstract This article outlines a methodology for investigating the coordinate systems by which movement variables are encoded in the firing rates of individual motor cortical neurons. Recent neurophysiological experiments have probed ...

How hallucinations may arise from brain mechanisms of learning, attention, and volition
Abstract This article suggests how brain mechanisms of learning, attention, and volition may give rise to hallucinations during schizophrenia and other mental disorders. The article suggests that normal learning and memory are ...

Context-sensitive bindings by the laminar circuits of V1 and V2: A unified model of perceptual grouping, attention, and orientation contrast
Abstract A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific ...

The complementary brain: Unifying brain dynamics and modularity
Abstract How are our brains functionally organized to achieve adaptive behavior in a changing world? This article presents one alternative to the computer analogy that suggests brains are organized into independent modules. Evidence ...


Software


KInNeSS - the KDE Integrated NeuroSimulation Software
Description KInNeSS is an open source neural simulation software package that allows to design, simulate and analyze the behavior of networks of hundreds to thousands of branched multi-compartmental neurons with biophysical properties ...