Biological Learning

Papers focusing on how biological systems learn. Topics include laminar computing, cognitive emotional interaction, and sequence learning, etc.


Articles & Tech Transfers


View-invariant object category learning, recognition, and search: How spatial and object attention are coordinated using surface-based attentional shrouds
Abstract How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are ...

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

Modeling developmental transitions in adaptive resonance theory
Abstract Neural networks are applied to a theoretical subject in developmental psychology: modeling developmental transitions. Two issues that are involved will be discussed: discontinuities and acquiring qualitatively new knowledge. ...

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 ...

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 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 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 ...

Some normal and abnormal behavioral syndromes due to transmitter gating of opponent processes
Abstract Opponent processes have long been known to be a basic building block of neural circuits. This article describes properties of opponent processes in which phasic cues and tonic arousal are gated by slowly accumulating ...

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 ...

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 ...

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 ...

Unitization, automaticity, temporal order, and word recognition
Abstract Samuel, van Santen, and Johnston (1982,1983) reported a word length effect in a word superiority paradigm. A word length effect was predicted in Grossberg (1978a). This article describes the main concepts about the ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Predictive regulation of associative learning in a neural network by reinforcement and attentive feedback
Abstract A real time neural network model is described in which reinforcement helps to focus attention upon and organize learning of those environmental events and contingencies that have predicted behavioral success in the past. ...

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 ...

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 ...

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 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 ...

Neural control of interlimb oscillations, I: Human bimanual coordination
Abstract How do humans and other animals accomplish coordinated movements? How are novel combinations of limb joints rapidly assembled into new behavioral units that move together in in-phase or anti-phase movement patterns during ...

The hippocampus and cerebellum in adaptively timed learning, recognition, and movement
Abstract The concepts of declarative memory and procedural memory have been used to distinguish two basic types of learning. A neural network model suggests how such memory processes work together as recognition learning, ...

Neural dynamics of motion grouping: From aperture ambiguity to object speed and direction
Abstract A neural model is developed of how motion integration and segmentation processes compute global motion percepts. Figure-ground properties, such as occlusion, influence which motion signals determine the percept. For visible ...

Neural control of interlimb oscillations, II: Biped and quadruped gaits and bifurcations
Abstract Behavioral data concerning animal and human gaits and gait transitions are simulated as emergent properties of a central pattern generator (CPG) model. The CPG model is a version of the Ellias-Grossberg oscillator. Its ...

Neural dynamics of variable-rate speech categorization
Abstract What is the neural representation of a speech code as it evolves in time? A neural model simulates data concerning segregation and integration of phonetic percepts. Hearing two phonetically related stops in a VC-CV pair (V = ...

Metabotropic glutamate receptor activation in cerebellar Purkinje cells as substrate for adaptive timing of the classically conditioned eye blink response
Abstract To understand how the cerebellum adaptively times the classically conditioned nictitating membrane response (NMR), a model of the metabotropic glutamate receptor (mGluR) second messenger system in cerebellar Purkinje cells ...

Cortical synchronization and perceptual framing
Abstract How does the brain group together different parts of an object into a coherent visual object representation? Different parts of an object may be processed by the brain at different rates and may thus become desynchronized. ...

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 ...

A neural model of cerebellar learning for arm movement control: Cortico-spino-cerebellar dynamics
Abstract A neural network model of opponent cerebellar learning for arm movement control is proposed. The model illustrates how a central pattern generator in cortex and basal ganglia, a neuromuscular force controller in spinal cord, ...

Cortical networks for control of voluntary arm movements under variable force conditions
Abstract A neural model of voluntary movement and proprioception is developed that offers an integrated interpretation of the functional roles of diverse cell types in movement-related areas of primate cortex. The model circuit ...

Spatial facilitation by color and luminance edges: Boundary, surface, and attentional factors
Abstract The thresholds of human observers detecting line targets improve significantly when the targets are presented in a spatial context of collinear inducing stimuli. This phenomenon is referred to as spatial facilitation, 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 ...

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 ...

Kinematic coordinates in which motor cortical cells encode movement direction
Abstract During goal-directed reaching in primates, a sensorimotor transformation generates a dynamical pattern of muscle activation. Within the context of this sensorimotor transformation, a fundamental question concerns the ...

The imbalanced Brain: From normal behavior to schizophrenia
Abstract An outstanding problem in psychiatry concerns how to link discoveries about the pharmacological, neurophysiological, and neuroanatomical substrates of mental disorders to the abnormal behaviors that they control. A related ...

How the basal ganglia use parallel excitatory and inhibitory learning pathways to selectively respond to unexpected rewarding cues
Abstract After classically conditioned learning, dopaminergic cells in the substantia nigra pars compacta (SNc) respond immediately to unexpected conditioned stimuli (CS) but omit formerly seen responses to expected unconditioned ...

How laminar frontal cortex and basal ganglia circuits interact to control planned and reactive saccades
Abstract How does the brain learn to balance between reactive and planned behaviors? The basal ganglia (BG) and frontal cortex together allow animals to learn planned behaviors that acquire rewards when prepotent reactive behaviors ...

Laminar cortical dynamics of 3D surface perception: Stratification, transparency, and neon color spreading
Abstract The 3D LAMINART neural model is developed to explain how the visual cortex gives rise to 3D percepts of stratification, transparency, and neon color spreading in response to 2D pictures and 3D scenes. Such percepts are ...

Linking attention to learning, expectation, competition, and consciousness
Abstract The concept of attention has been used in many senses, often without clarifying how or why attention works as it does. Attention, like consciousness, is often described in a disembodied way. The present article summarizes ...

Neural dynamics of autistic behaviors: Cognitive, emotional, and timing substrates
Abstract What brain mechanisms underlie autism, and how do they give rise to autistic behavioral symptoms? This article describes a neural model, called the Imbalanced Spectrally Timed Adaptive Resonance Theory (iSTART) model, that ...

Space, time, and learning in the hippocampus: How fine spatial and temporal scales are expanded into population codes for behavioral control
Abstract The hippocampus participates in multiple functions, including spatial navigation, adaptive timing and declarative (notably, episodic) memory. How does it carry out these particular functions? The present article proposes ...

Consciousness CLEARS the mind
Abstract A full understanding of consciousness requires that we identify the brain processes from which conscious experiences emerge. What are these processes, and what is their utility in supporting successful adaptive behaviors? ...

Spatial pattern learning, catastrophic forgetting, and optimal rules of synaptic transmission
Abstract It is a neural network truth universally acknowledged, that the signal transmitted to a target node must be equal to the product of the path signal times a weight. Analysis of catastrophic forgetting by distributed codes ...

The attentive brain
Abstract Myriad signals relentlessly bombard our senses. These signals may arrive in disconnected pieces, yet we can integrate them as unified moments of conscious experience. the apparent singularity and coherence of an experience ...

Normal and amnesic learning, recognition, and memory by a neural model of cortico hippocampal interactions
Abstract The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation and novelty detection work ...

Distributed hypothesis testing, attention shifts, and transmitter dynamics during the self-organization of brain recognition codes
Abstract How the mammalian brain can rapidly but stably learn about a changing world filled with unexpected events is one of the most challenging scientific problems of our time. The brain?s ability to autonomously discover and ...

Self organizing neural network architectures for adaptive pattern recognition and robotics
Abstract In this chapter, we discuss some recent results in neural networks relevant to adaptive pattern recognition and sensory-motor control problems. IN biologically-oriented neural networks, whose fast dynamics are governed by ...

Neural dynamics of category learning and recognition: Attention, memory consolidation, and amnesia
Abstract A theory is developed of how recognition categories can be learned in response to a temporal stream of input patterns. Interactions between an attentional subsystem and an orienting subsystem enable the network to ...

Nonlinear neural networks: Principles, mechanisms, and architectures
Abstract An historical discussion is provided of the intellectual trends that caused nineteenth century interdisciplinary studies of physics and psychobiology by leading scientists such as Helmholtz, Maxwell, and Mach to splinter ...

The ART of adaptive pattern recognition by a self organizing neural network
Abstract The adaptive resonance theory (ART) suggests a solution to the stability-plasticity dilemma facing designers of learning systems, namely how to design a learning system that will remain plastic, or adaptive, in response to ...

A massively parallel architecture for a self organizing neural pattern recognition machine
Abstract A neural network architecture for the learning of recognition categories is derived. Real-time network dynamics are completely characterized through mathematical analysis and computer simulations. The architecture ...

A neural theory of circadian rhythms: Split rhythms, after effects, and motivational interactions
Abstract A neural theory of the circadian pacemaker within the hypothalamic suprachiasmatic nuclei (SCN) is used to explain parametric data about mammalian operant behavior. The intensity, duration, and patterning of ultradian ...

Category learning and adaptive pattern recognition: A neural network model
Abstract A theory is presented of how recognition categories can be learned in response to a temporal stream of input patterns. Interactions between an attentional subsystem and an orienting subsystem enable the network to ...

A neural theory of circadian rhythms: The gated pacemaker
Abstract This article describes a behaviorally, physiologically, and anatomically predictive model of how circadian rhythms are generated by each suprachiasmatic nucleus (SCN) of the mammalian hypothalamus. This gated pacemaker model ...

A neural theory of circadian rhythms: Aschoffs rule in diurnal and nocturnal mammals
Abstract A neural model of the suprachiasmatic nuclei suggests how behavioral activity, rest, and circadian period depend on light intensity in diurnal and nocturnal mammals. these properties are traced to the action of light input ...

Which behavior does the lamprey central motor program mediate?
Abstract The lamprey occupies a strategic evolutionary position in terms of the organization of its nervous system (1), and serves as an important cellular model for recovery from spinal cord lesions (2) and for the analysis of motor ...

Adaptation and transmitter gating in vertebrate photoreceptors
Abstract A quantitative model for the transduction dynamics whereby intracellular transmitter in a vertebrate cone mediates between light input and voltage output is analyzed. a basic postulate is that the transmitter acts to ...

How does a brain build a cognitive code?
Abstract This article indicates how competition between afferent data and learned feed-back expectancies can stabilize a developing code by buffering committed populations of detectors against continual erosion by new environmental ...

A theory of human memory: Self-organization and performance of sensory-motor codes, maps, and plans
Abstract A psychophysiological theory of the self-organization and performance of sensory-motor codes, maps, and plans is derived herein. this general topic includes a variety of phenomena in many species, ranging from the ...

Classical and instrumental learning by neural networks
Abstract This article reviews results chosen from the theory of embedding fields. Embedding field theory discusses mechanisms of pattern discrimination and learning in a psychophysiological setting. It is derived from psychological ...

Brain categorization:  learning, attention, and consciousness
Abstract How do humans and animals learn to recognize objects and events? Two classical views are that exemplars or prototypes are learned. A hybrid view is that a mixture, called rule-plus-exceptions, is learned. None of these ...

Spikes, synchrony, and attentive learning by laminar thalamocortical circuits
Abstract This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and ...

Neural-network models of learning and memory: leading questions and an emerging framework
Abstract Real-time neural-network models provide a conceptual framework for formulating questions about the nature of cognition, an architectural framework for mapping cognitive functions to brain regions, a semantic framework for ...

Adaptive Resonance Theory
Abstract Principles derived from an analysis of experimental literatures in vision, speech, cortical development, and reinforcement learning, including attentional blocking and cognitive-emotional interactions, led to the ...

Mammalian circadian rhythms: A neural network model
Abstract A neural network model provides behavioral, physiological, and anatomical predictions of how circadian rhythms are generated by the suprachiasmatic nuclei (SCN) of the mammalian hypothalamus. The 4-dimensional basic gated ...

A neural model of corticocerebellar interactions during attentive imitation and predictive learning
Abstract Much sensory-motor behavior develops through imitation, as during the learning of handwriting by children. Such complex sequential acts are broken down into distinct motor control synergies, or muscle groups, whose ...

A neural model of how horizontal and interlaminar connections of visual cortex develop into adult circuits that carry out perceptual groupings and learning
Abstract A neural model suggests how horizontal and interlaminar connections in visual cortical areas V1 and V2 develop within a laminar cortical architecture and give rise to adult visual percepts. The model suggests how mechanisms ...

A neural model of how the brain represents and compares multi-digit numbers
Abstract Both animals and humans represent and compare numerical quantities, but only humans have evolved multi-digit place-value number systems. This article develops a Spatial Number Network, or SpaN, model to explain how these ...

Towards a theory of the laminar architecture of cerebral cortex
Abstract One of the most exciting and open research frontiers in neuroscience is that of seeking to understand the functional roles of the layers of cerebral cortex. New experimental techniques for probing the laminar circuitry of ...

How does the cerebral cortex work?
Abstract A key goal of behavioral and cognitive neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how the visual cortex sees. Visual cortex, like many ...

From normal brain and behavior to schizophrenia
Abstract This article introduces neural models as a link between neuroscience discoveries of brain mechanisms controlling behavior and psychiatric imbalances leading to behavioral ...


Software


EPSP IPSP
Description A model to demonstrate the effect of Excitatory Postsynaptic Potentials (EPSP) and Inhibitory Postsynaptic Potentials (IPSP) on a neuron. The model is based on synaptic conductance equations from (Kohn and Worgotter 1998) ...

Outstar learning law
Description Outstar learning law (Grossberg, 1976) governs the dynamics of feedback connection weights in a standard competitive neural network in an unsupervised manner. This learning models how a neuron can learn a top-down template ...

Instar learning law
Description Instar learning law (Grossberg, 1976) governs the dynamics of feedforward connection weights in a standard competitive neural network in an unsupervised manner. This learning models how a neuron can become selectively ...

SMART network
Description This entry contains the software, implemented in the KDE Integrated NeuroSimulation Software (KInNeSS ) that simulates the Synchronous Matching Adaptive Resonance Theory. SMART was first described in Grossberg and Versace ...