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PubMed1994

Modeling human motion perception. I. Classical stimuli.

Motion perception is one of the most prominent tasks of the visual system and therefore has been extensively investigated both experimentally and theoretically. A classical model describing the mechanism of motion detection originally developed in the context of insect orientation behavior, the elementary motion detector (EMD) of the correlation type, turned out to be very powerful in explaining many basic aspects of human motion perception. For more complex visual tasks, like the discrimination of a figure from its background by relative motion, on the other hand, further processing of motion information is required. In the first part of this review it will be illustrated by means of a few examples, what kind of motion information can be derived from the mere correlation-type model, and what perceptual phenomena can be accounted for by the EMD. In the second part, more recently developed stimuli will be introduced to answer the question what further processing steps, or more sophisticated mechanisms than the EMD, have to be assumed in order to understand "higher" aspects of human motion perception.

Cybernetics↗
PubMed1994

Modelling human motion perception. II. Beyond Fourier motion stimuli.

In the first part of this review a basic mechanism of motion perception was illustrated. The elementary motion detector (EMD) of the correlation type can account for the detection of "Fourier" motion stimuli in which the spatial intensity distribution on the retina is shifted over time. In recent years, novel classes of stimuli such as "drift-balanced" or "theta" motion (in which the picture elements carrying luminance contrast do not move, or move in the opposite direction to the traveling object defined by such element motion) were introduced into psychophysics. Such stimuli may play an important role in the understanding of "higher" visual processing which goes beyond the pure detection of motion. Thus, in the second part of the review, the question will be addressed as to what further processing steps, or more sophisticated mechanisms than the EMD, have to be assumed in order to understand more complex aspects of human motion perception.

Fourier Analysis↗
PubMed1993

Cortical regulation of subcortical dopamine systems and its possible relevance to schizophrenia.

A unique model of DA system regulation is presented, in which tonic steady-state DA levels in the ECF act to down-regulate the response of the system to pulsatile DA released by DA cell action potential generation. This type of regulation is similar in many respects to the phenomenon proposed to mediate the action of norepinephrine on target neurons; i.e., an increase in the "signal-to-noise" ratio as measured by postsynaptic cell firing (Freedman et al., 1977; Woodward et al., 1979). However, in this model the signal and the noise are neurochemical rather than electrophysiological. Furthermore, the "noise" (tonic DA in the ECF) actually down-regulates the "signal" (phasic DA release) directly, and thereby provides a "signal" of its own that affects the system over a longer time-course. Therefore, the difference between signal and noise may also depend on the time frame under which such determinations are made.

Afferent Pathways↗
PubMed1992

The hyperaemic response to a transient reduction in cerebral perfusion pressure. A modelling study.

A mathematical model of cerebral blood flow and the cerebrospinal fluid circulation is described which permits the study of phenomena caused by dynamic changes in cerebrovascular autoregulatory or cerebrospinal fluid compensatory reserves. A transient decrease in cerebral perfusion pressure was produced by carotid artery compression. Comparison of the computer simulations with clinical and experimental data, reported elsewhere, suggests that the transient hyperaemic response (THR) is proportional to the strength of the autoregulatory response. The relationships between the magnitude and time course of the THR, and the period and level of reduction in CPP were studied. This model suggests that simple clinical tests based on the examination of THR using transcranial Doppler velocity measurements are of potential value for the non-invasive assessment of the autoregulatory reserve.

Blood Flow Velocity↗
PubMed1981

Infantile autism and the temporal lobe of the brain.

Studies are reviewed that support the hypothesis that infantile autism results from a neuropathology of the temporal lobes of the brain. First, there are parallels between symptoms noted in autism and those found in the Kluver-Bucy and amnesic syndromes. Second, there is a similarity between developmental dysphasia and autism. Third, the formation of cross-modal associations may be deficient in autistic children, a symptom resembling aspects of Geschwind's disconnection syndromes. Finally, a large number of organic factors have been associated with the development of autism, some of these having specific implications for temporal lobe involvement. It is concluded that the main autistic symptoms are most consistent with a neurological model involving bilateral dysfunction of the temporal lobes. Individual differences in the extent of bilateral involvement and/or other coexistent neuropathologies could contribute to the heterogeneity of the autistic population.

Amnesia↗
PubMed1995

Ion channel hypothesis for Alzheimer amyloid peptide neurotoxicity.

1. Alzheimer's disease (AD) is a chronic dementia and neurodegenerative disorder affecting the oldest portions of the population. Brains of AD patients accumulate large amount of the A beta P peptide in amyloid plaques. 2. The A beta P[1-40] peptide is derived by proteolytic processing from a much larger amyloid precursor protein (APP), and has been circumstantially identified as the toxic principle causing cell damage in the disease. 4. The A beta P[1-40] peptide is able to form quite characteristic calcium channels in planar lipid bilayers. These channels have conductances in the nS range, and can dissipate ion gradients quickly. The peptide can also cause equivalent cation conductances in cells. 5. We suggest that amyloid channel blocking agents might be therapeutically useful in Alzheimer's Disease, and have constructed molecular models of the channels to aid in the design of such compounds.

Alzheimer Disease↗
PubMed1987

A self-organizing neural network sharing features of the mammalian visual system.

This paper describes a neural network model whose structure is designed to closely fit neuroanatomical and -physiological data, and not to be most suitable for rigorous mathematical analysis. It is shown by computer simulation that a process of self-organization that departs from a fixed retinotopic order at peripheral layers and includes Hebbian modifications of synaptic connectivity at higher processing levels leads to a system that is capable of mimicking various functions of visual systems: In the initial state the overall structure of the network is preset, individual connections at higher levels are randomly selected and their strength is initialized with random numbers. For this model the outcome of the self-organization process is determined by the stimulation during the developmental phase. Depending on the type of stimuli used the model can either develop towards a feature-selective "preprocessor" stage in a complex vision system or towards a subsystem for associative recall of abstract patterns. This flexibility supports the hypothesis that the principles embodied are rather universal and can account for the development of various nervous system structures.

Animals↗
PubMed1990

Forming sparse representations by local anti-Hebbian learning.

How does the brain form a useful representation of its environment? It is shown here that a layer of simple Hebbian units connected by modifiable anti-Hebbian feed-back connections can learn to code a set of patterns in such a way that statistical dependency between the elements of the representation is reduced, while information is preserved. The resulting code is sparse, which is favourable if it is to be used as input to a subsequent supervised associative layer. The operation of the network is demonstrated on two simple problems.

Brain↗
PubMed1990

Anti-Hebbian learning in a non-linear neural network.

The Hebbian rule (Hebb 1949), coupled with an appropriate mechanism to limit the growth of synaptic weights, allows a neuron to learn to respond to the first principal component of the distribution of its input signals (Oja 1982). Rubner and Schulten (1990) have recently suggested the use of an "anti-Hebbian" rule in a network with hierarchical lateral connections. When applied to neurons with linear response functions, this model allows additional neurons to learn to respond to additional principal components (Rubner and Tavan 1989). Here we apply the model to neurons with non-linear response functions characterized by a threshold and a transition width. We propose local, unsupervised learning rules for the threshold and the transition width, and illustrate the operation of these rules with some simple examples. A network using these rules sorts the input patterns into classes, which it identifies by a binary code, with the coarser structure coded by the earlier neurons in the hierarchy.

Brain↗
PubMed1993

Cortico-cortical connections, non-linear multicolumnar parallel distributed networks and memory processes in humans. A review.

This review outlines the knowledge gained in the last 50 years concerning the neuroanatomy and neuro-psychophysiology of memory processes in humans. The first part traces the history of the most important findings from ablations of specific cerebral structures and/or stimulations performed on numerous patients using different surgical and neurophysiological methodologies. The interpretation of these findings is discussed. The most recent hypotheses on the neuronal substrates likely to be involved in memory and recall processes are then presented. In particular the concept of parallel distributed non-linear multicolumnar cortical networks is described as well as the recent hypothesis concerning the chaotic oscillatory properties of these complex non-linear neuronal systems which are said to behave as chaotic deterministic attractors.

Cerebral Cortex↗
PubMed1995

Hypnosis modelling in neural networks.

In the framework of the neural network theory effects similar to hypnotic displays are constructed. They are based on the associative paradigm involving non-linear interaction of excitatory and inhibitory channels with synaptic memory. The non-linearity of long-term memorizing processes may cause effects exhibited by blind spots, which are interpreted as the first stage of hypnosis. More complicated phenomena are discussed in terms of a two-layer network.

Humans↗
PubMed1989

Context-dependent associations in linear distributed memories.

In this article we present a method that allows conditioning of the response of a linear distributed memory to a variable context. This method requires a system of two neural networks. The first net constructs the Kronecker product between the vector input and the vector context, and the second net supports a linear associative memory. This system is easily adaptable for different goals. We analyse here its capacity for the conditional extraction of features from a complex perceptual input, its capacity to perform quasi-logical operations (for instance, of the kind of "exclusive-or"), and its capacity to structurate a memory for temporal sequences which access is conditioned by the context. Finally, we evaluate the potential importance of the capacity to establish arbitrary contexts, for the evolution of biological cognitive systems.

Artificial Intelligence↗
PubMed1991

Evaluation of the time course of neurotransmitter release from the measured PSC and MPSC.

A method for obtaining delay histograms for the time course of neurotransmitter release is presented. The delay histogram is derived from the measured psc (or the sum of several psc's) and the mpsc (obtained experimentally or otherwise) by means of a simple, quick, mathematical procedure. The procedure may be automated for the greater part. No approximation of the mpsc shape is performed, and the method is applicable to all quantal contents. For low and medium quantal contents, the delay histograms obtained by the method are compared to those obtained by direct analysis. A reasonable agreement is achieved. An experiment of high quantal content, for which direct analysis is impossible, is then analysed using the new method. Difficulties which may arise when applying the procedure and methods to overcome them are discussed at length. Other methods are set forth in the Discussion.

Animals↗
PubMed1991

Statistical evaluation of dendritic growth models.

A mathematical model (Kliemann, W. 1987. Bull. math. Biol. 49, 135-152.) that predicts the quantitative branching pattern of dendritic tree was evaluated using the apical and basal dendrites of rat hippocampal neurons. The Wald statistic for chi 2-test was developed for the branching pattern of dendritic trees and for the distribution of the maximal order of the tree. Using this statistic, we obtained a reasonable, but not excellent, fit of the mathematical model for the dendritic data. The model's predictability of branching pattern was greatly enhanced by replacing one of the assumptions used for the original method "splitting of branches for all dendritic orders is stochastically independent", with a new assumption "branches are more likely to split in areas where there is already a high density of branches". The modified model delivered an excellent fit for basal dendrites and for the apical dendrites of hippocampal neurons from young rats (30-34 days postpartum). This indicates that for these cells the development of dendritic patterns is the result of a purely random and a systematic component, where the latter one depends on the density of dendritic branches in the brain area considered. For apical dendrites there is a trend towards decreasing pattern predictability with increasing age. This appears to reflect the late arrival of afferents and subsequent synaptogenesis proximal on the apical dendritic tree of hippocampal neurons.

Animals↗