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J Chover

Publications and source records attributed to J Chover.

7 recordsLinked to original sources

Alternating dominance of NMDA and AMPA for learning and recall: a computer model.

Physiological studies reveal a dichotomy in biological Hebbian learning: NMDA receptors are utilized for induction of long term potentiation (LTP) whereas AMPA is used for LTP expression. We propose that this dichotomy would have functional value: preventing previously stored memories from interfering with the storage of new memories. A previous hypothesis reduces this interference by temporarily reducing associative weights during learning. Complementary to this model, we propose a dual transmission algorithm in which one set of synaptic weights are used primarily for learning and another primarily for recall. This algorithm shows good performance in a simple neural network model. Biologically, the model could be mediated by a cholinergic switch from dominance of learning-insensitive NMDA receptors to dominance of learning-modifiable AMPA receptors.

Acetylcholine↗

Neural correlation via random connections.

A simple neural network is studied, which has sparse, random, plastic, excitatory connections and also feedback loops between sensory cells and correlator cells. Time is limited to several discrete instants, where firing is synchronous. For parameter values within biological ranges, the system exhibits a capacity for associative recall, with a controlled amount of extraneous firing, following Hebb-like synaptic changes.

Action Potentials↗

Modelling afferent connectivity, postsynaptic plasticity, and signal discrimination.

We model a small system of hypothetical neurons having ongoing afferent input ("stimulus") short-term refraction/inhibition, and brief-latency intercellular excitatory feedback loops. We incorporate postsynaptic plasticity: synapses onto a given cell are grouped into dendritic "neighborhoods" wherein sufficiently large local postsynaptic potentials sums cause proportional changes in local synaptic efficacy. The efficacies record multiple cell-to-cell and time-to-time correlations. The efficacy patterns fall into several classes, for each of which there is a stereotypical relationship leading from "steady-state" stimuli to corresponding sets of possible "responses" (periodic firing patterns). We examine the system's ability to discriminate between stimuli via firing patterns and to retain information during change of efficacies. There is an optimal region for efficacy configurations inside of which discrimination is good and outside of which the system can be inactive, particularly forgetful, or perseverative. We find that stimulus discrimination is enhanced by divergence and convergence in the pattern of afferent input. Perseverative firing patterns, invoked or suppressed by cotransmitters, can play a role in associative activities of the network.

Computer Simulation↗

The early growth of cancer.

In this paper, we compare two types of stochastic models for the initial growth of cancerous tumors. In one type, the random element enters via the initial time of growth or via the initial size of the growth clone. In the other type, tumors differ from one another essentially via their growth rates. We present a simple test to distinguish between the two types when tumor size distributions are available from several time points. Size distributions are the key elements of such kinetic analysis given the limitation that an individual tumor can be measured only once, at the time of sacrifice of an experimental animal. We discuss these concepts in connection with data from particular experiments on carcinogenic growth in the livers of mice.

Animals↗

Optimal use of sampled tissue sections for estimating the number of hepatocellular foci.

Statistical techniques were applied to computer-simulated data to evaluate the importance of various factors that may affect the estimation of the number of hepatocellular foci from foci transections. The simulations were modeled after mouse foci for which three-dimensional size distributions and densities were determined from serial section reconstructions. The foci had been induced in male C57BL/6 X C3H F1 mice at 20 and 28 weeks after a single injection, in infancy, of diethylnitrosamine. In an earlier report, we had shown that the number of foci per cu cm could be accurately estimated from profiles using a conditional estimator when the investigator is unable to identify profiles smaller than a certain size (epsilon). In the present study, emphasis was placed on assessing the value of step serial sections in order to make optimal use of the small tissue samples in mouse liver. Since all mathematical estimators of N3 are based on measurement of sampled profiles (n2') and ultimately derive from the fundamental relationship. N3' = N2'/2mu, (where N3' is the number of foci per cu cm, N2' is the number of profiles per sq cm, and mu, is the average adjusted focus radius), the relative importance of N2' and mu, on the conditional estimator was evaluated. This was accomplished by comparing the errors resulting from use of the conditional estimator with those resulting from use of two other estimators. The latter two estimators consisted of a "sampled focus estimator," which used sampled intact foci to estimate N3, and a "reference estimator," which used profiles from foci with a mu, that was known. Additionally, in order to provide a stable variance for the conditional estimator, we adopted a simple smoothing procedure. As expected, none of the estimators showed any significant bias. However, somewhat surprising was the finding that the standard deviations from use of all three estimators were almost identical. Consequently, it appears that the variance resulting from application of the smoothed conditional estimator to large sets of profile data is not due to difficulty in estimating mu epsilon. In these instances, the faulty estimates of N2' resulted almost entirely from the variability in sampling foci from tissue blocks which constituted only about 1/25 of the liver volume. In addition, the ability to reduce the error in estimating the number of foci by increasing the number of profiles was also evaluated. We simulated a sectioning protocol for the 28-week mouse livers in which the distances between the 5-micron-thick step sections in a 1-mm block of liver were progressively decreased from 1000 to 50 micron.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗