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Biomedical subjects

E Ruppin

Publications and source records attributed to E Ruppin.

At least 19 recordsLinked to original sources
PubMed2000

NMDA receptor delayed maturation and schizophrenia.

This paper presents the hypothesis that NMDA receptor delayed maturation (NRDM) may lead to the pathogenesis of schizophrenic psychotic symptoms. This hypothesis is further analyzed in the language of a neural modeling formulation. This formulation points to a possible chain of pathological events, leading from molecular-level NRDM to over-increased synaptic plasticity, and to the formation of pathological attractors, a putative macroscopic-level correlate of schizophrenic positive symptoms. The relations of the NRDM hypothesis to other alterations which are assumed to take place in schizophrenia are discussed, together with possible ways to test this hypothesis.

Humans↗
PubMed1999

Neuronal regulation: A mechanism for synaptic pruning during brain maturation.

Human and animal studies show that mammalian brains undergo massive synaptic pruning during childhood, losing about half of the synapses by puberty. We have previously shown that maintaining the network performance while synapses are deleted requires that synapses be properly modified and pruned, with the weaker synapses removed. We now show that neuronal regulation, a mechanism recently observed to maintain the average neuronal input field of a postsynaptic neuron, results in a weight-dependent synaptic modification. Under the correct range of the degradation dimension and synaptic upper bound, neuronal regulation removes the weaker synapses and judiciously modifies the remaining synapses. By deriving optimal synaptic modification functions in an excitatory-inhibitory network, we prove that neuronal regulation implements near-optimal synaptic modification and maintains the performance of a network undergoing massive synaptic pruning. These findings support the possibility that neural regulation complements the action of Hebbian synaptic changes in the self-organization of the developing brain.

Aging↗
PubMed1999

Associative memory in a multi-modular network.

Recent imaging studies suggest that object knowledge is stored in the brain as a distributed network of many cortical areas. Motivated by these observations, we study a multimodular associative memory network, whose functional goal is to store patterns with different coding levels--patterns that vary in the number of modules in which they are encoded. We show that in order to accomplish this task, synaptic inputs should be segregated into intramodular projections and intermodular projections, with the latter undergoing additional nonlinear dendritic processing. This segregation makes sense anatomically if the intermodular projections represent distal synaptic connections on apical dendrites. It is then straightforward to show that memories encoded in more modules are more resilient to focal afferent damage. Further hierarchical segregation of intermodular connections on the dendritic tree improves this resilience, allowing memory retrieval from input to just one of the modules in which it is encoded.

Algorithms↗
PubMed1999

Pathogenic mechanisms in ischemic damage: a computational study.

The pathogenesis of penumbral tissue infarction during acute ischemic stroke is controversial. This peri-infarct tissue may subsequently die, or survive and recuperate, and its preservation has been a prime goal of recent therapeutic trials in acute stroke. Two major hypotheses currently under consideration are that penumbral tissue is recruited into an infarct by cortical spreading depression (CSD) waves, or by a non-wave self-propagating process such as glutamate excitotoxicity (GE). Careful experimental attempts to discriminate between these two hypotheses have so far been quite ambiguous. Using a computational metabolic model of acute focal stroke we show here that the spatial patterns of tissue damage arising from artificially induced foci of infarction having specific geometric shapes are inherently different. This is due to the distinct propagation characteristics underlying self-regenerating waves and non-wave diffusional processes. The experimental testing of these predicted spatial patterns of damage may help determine the relative contributions of the two pathological mechanisms hypothesized for ischemic tissue damage.

Acute Disease↗
PubMed1999

From parallel to serial processing: a computational study of visual search.

A novel computational model of a preattentive system performing visual search is presented. The model processes displays of lines, reproduced from Wolfe, Friedman-Hill, Stewart, and O'Connell's (1992) and Treisman and Sato's (1990) visual-search experiments. The response times measured in these experiments suggest that some of the displays are searched serially, whereas others are scanned in parallel. Our neural network model operates in two phases. First, the visual displays are compressed via standard methods (principal component analysis), to overcome assumed biological capacity limitations. Second, the compressed representations are further processed to identify a target in the display. The model succeeds in fast detection of targets in experimentally labeled parallel displays, but fails with serial ones. Analysis of the compressed internal representations reveals that compressed parallel displays contain global information that enables instantaneous target detection. However, in representations of serial displays, this global information is obscure, and hence, a target detection system should resort to a serial, attentional scan of local features across the display. Our analysis provides a numerical criterion that is strongly correlated with the experimental response time slopes and enables us to reformulate Duncan and Humphreys's (1989) search surface, using precise quantitative measures. Our findings provide further insight into the important debate concerning the dichotomous versus continuous views of parallel/serial visual search.

Electronic Data Processing↗
PubMed1998

Synaptic pruning in development: a computational account.

Research with humans and primates shows that the developmental course of the brain involves synaptic overgrowth followed by marked selective pruning. Previous explanations have suggested that this intriguing, seemingly wasteful phenomenon is utilized to remove, "erroneous" synapses. We prove that this interpretation is wrong if synapses are Hebbian. Under limited metabolic energy resources restricting the amount and strength of synapses, we show that memory performance is maximized if synapses are first overgrown and then pruned following optimal "minimal-value" deletion. This optimal strategy leads to interesting insights concerning childhood amnesia.

Animals↗
PubMed1998

Synaptic runaway in associative networks and the pathogenesis of schizophrenia.

Synaptic runaway denotes the formation of erroneous synapses and premature functional decline accompanying activity-dependent learning in neural networks. This work studies synaptic runaway both analytically and numerically in binary-firing associative memory networks. It turns out that synaptic runaway is of fairly moderate magnitude in these networks under normal, baseline conditions. However, it may become extensive if the threshold for Hebbian learning is reduced. These findings are combined with recent evidence for arrested N-methyl-D-aspartate (NMDA) maturation in schizophrenics, to formulate a new hypothesis concerning the pathogenesis of schizophrenic psychotic symptoms in neural terms.

Association Learning↗
PubMed1998

Memory maintenance via neuronal regulation.

Since their conception half a century ago, Hebbian cell assemblies have become a basic term in the neurosciences, and the idea that learning takes place through synaptic modifications has been accepted as a fundamental paradigm. As synapses undergo continuous metabolic turnover, adopting the stance that memories are engraved in the synaptic matrix raises a fundamental problem: How can memories be maintained for very long time periods? We present a novel solution to this long-standing question, based on biological evidence of neuronal regulation mechanisms that act to maintain neuronal activity. Our mechanism is developed within the framework of a neural model of associative memory. It is operative in conjunction with random activation of the memory system and is able to counterbalance degradation of synaptic weights and normalize the basins of attraction of all memories. Over long time periods, when the variance of the degradation process becomes important, the memory system stabilizes if its synapses are appropriately bounded. Thus, the remnant memory system is obtained by a dynamic process of synaptic selection and growth driven by neuronal regulatory mechanisms. Our model is a specific realization of dynamic stabilization of neural circuitry, which is often assumed to take place during sleep.

Animals↗
PubMed1998

Spreading depression in focal ischemia: a computational study.

When a cerebral infarction occurs, surrounding the core of dying tissue there usually is an ischemic penumbra of nonfunctional but still viable tissue. One current but controversial hypothesis is that this penumbra tissue often eventually dies because of the metabolic stress imposed by multiple cortical spreading depression (CSD) waves, that is, by ischemic depolarizations. We describe here a computational model of CSD developed to study the implications of this hypothesis. After simulated infarction, the model displays the linear relation between final infarct size and the number of CSD waves traversing the penumbra that has been reported experimentally, although damage with each individual wave progresses nonlinearly with time. It successfully reproduces the experimental dependency of final infarct size on midpenumbra cerebral blood flow and potassium reuptake rates, and predicts a critical penumbra blood flow rate beyond which damage does not occur. The model reproduces the dependency of CSD wave propagation on N-methyl-D-aspartate activation. It also makes testable predictions about the number, velocity, and duration of ischemic CSD waves and predicts a positive correlation between the duration of elevated potassium in the infarct core and the number of CSD waves. These findings support the hypothesis that CSD waves play an important causal role in the death of ischemic penumbra tissue.

Cerebral Infarction↗
PubMed1998

Neuronal regulation versus synaptic unlearning in memory maintenance mechanisms.

Hebbian learning, the paradigm of memory formation, needs further mechanisms to guarantee creation and maintenance of a viable memory system. One such proposed mechanism is Hebbian unlearning, a process hypothesized to occur during sleep. It can remove spurious states and eliminate global correlations in the memory system. However, the problem of spurious states is unimportant in the biologically interesting case of memories that are sparsely coded on excitatory neurons. Moreover, if some memories are anomalously strong and have to be weakened to guarantee proper functioning of the network, we show that it is advantageous to do that by neuronal regulation (NR) rather than synaptic unlearning. Neuronal regulation can account for dynamical maintenance of memory systems that undergo continuous synaptic turnover. This neuronal-based mechanism, regulating all excitatory synapses according to neuronal average activity, has recently gained strong experimental support. NR achieves synaptic maintenance over short time scales by preserving the average neuronal input field. On longer time scales it acts to maintain memories by letting the stronger synapses grow to their upper bounds. In ageing, these bounds are increased to allow stronger values of remaining synapses to overcome the loss of synapses that have perished.

Adult↗
PubMed1997

A computational model of acute focal cortical lesions.

BACKGROUND AND PURPOSE: Determining how cerebral cortex adapts to sudden focal damage is important for gaining a better understanding of stroke. In this study we used a computational model to examine the hypothesis that cortical map reorganization after a simulated infarct is critically dependent on perilesion excitability and to identify factors that influence the extent of poststroke reorganization. METHODS: A previously reported artificial neural network model of primary sensorimotor cortex, controlling a simulated arm, was subjected to acute focal damage. The perilesion excitability and cortical map reorganization were measured over time and compared. RESULTS: Simulated lesions to cortical regions with increased perilesion excitability were associated with a remapping of the lesioned area into the immediate perilesion cortex, where responsiveness increased with time. In contrast, when lesions caused a perilesion zone of decreased activity to appear, this zone enlarged and intensified with time, with loss of the perilesion map. Increasing the assumed extent of intracortical connections produced a wider perilesion zone of inactivity. These effects were independent of lesion size. CONCLUSIONS: These simulation results suggest that functional cortical reorganization after an ischemic stroke is a two-phase process in which perilesion excitability plays a critical role.

Animals↗
PubMed1996

Neuronal-based synaptic compensation: a computational study in Alzheimer's disease.

In the framework of an associative memory model, we study the interplay between synaptic deletion and compensation, and memory deterioration, a clinical hallmark of Alzheimer's disease. Our study is motivated by experimental evidence that there are regulatory mechanisms that take part in the homeostasis of neuronal activity and act on the neuronal level. We show that following synaptic deletion, synaptic compensation can be carried out efficiently by a local, dynamic mechanism, where each neuron maintains the profile of its incoming post-synaptic current. Our results open up the possibility that the primary factor in the pathogenesis of cognitive deficiencies in Alzheimer's disease (AD) is the failure of local neuronal regulatory mechanisms. Allowing for neuronal death, we observe two pathological routes in AD, leading to different correlations between the levels of structural damage and functional decline.

Alzheimer Disease↗
PubMed1996

Pathogenesis of schizophrenic delusions and hallucinations: a neural model.

We implement and study a computational model of Stevens' theory of the pathogenesis of schizophrenia. This theory hypothesizes that the onset of schizophrenia is associated with reactive synaptic regeneration in brain regions that receive degenerating temporal lobe projections. Concentrating on one such area, the frontal cortex, we model a frontal module as an associative memory neural network whose input synapses represent incoming temporal projections. Modeling Stevens' hypothesized pathological synaptic changes in this framework results in adverse side effects similar to hallucinations and delusions seen in schizophrenia: spontaneous, stimulus-independent retrieval of stored memories focused on just a few of the stored patterns. These could account for the delusions and hallucinations that occur in schizophrenia without any apparent external trigger and for their tendency to concentrate on a few central cognitive and perceptual themes. The model explains why the positive symptoms of schizophrenia tend to wane as the disease progresses, why delayed therapeutic intervention leads to a much slower response, and why delusions and hallucinations may persist for a long time when they do occur.

Brain↗
PubMed1996

Frequency-spatial transformation: a proposal for parsimonious intra-cortical communication.

This work examines a neural network model of a cortical module, where neurons are organized on a 2-dimensional sheet and are connected with higher probability to their spatial neighbors. Motivated by recent findings that cortical neurons have a resonant peak in their impedance magnitude function, we present a frequency-spatial transformation scheme that is schematically described as follows: An external input signal, applied to a small input subset of the neurons, spreads along the network. Due to a stochastic component in the dynamics of the neurons, the frequency of the spreading signal decreases as it propagates through the network. Depending on the input signal frequency, different neural assemblies will hence fire at their specific resonance frequency. We show analytically that the resulting frequency-spatial transformation is well-formed; an injective, fixed, mapping is obtained. Extensive numerical simulations demonstrate that a homogeneous, well-formed transformation may also be obtained in neural networks with cortical-like "Mexican-hat" connectivity. We hypothesize that a frequency-spatial transformation may serve as a basis for parsimonious cortical communication.

Cell Communication↗