Biomedical subjects

K T Blackwell

Publications and source records attributed to K T Blackwell.

11 recordsLinked to original sources

PubMed1999

Ryanodine receptor modulation of in vitro associative learning in Hermissenda crassicornis.

Classical conditioning of the mollusc, Hermissenda crassicornis, is a model system used to study cellular correlates of associative learning. Paired presentation of light and turbulence, but not unpaired presentations, causes Hermissenda to contract its foot in response to light alone. Intracellular recordings from the type B photoreceptors of the Hermissenda eye reveal a learning specific increase of input resistance, and a reduction of voltage-dependent potassium currents, both of which depend on an elevation of intracellular calcium. Two previously demonstrated sources of calcium are influx through voltage-dependent channels, and release of calcium from intracellular stores through the IP3 receptor channel. Both modeling studies and identification of memory-related genes using RNA fingerprinting suggest that a third source of calcium, release from intracellular stores through the ryanodine receptor, may be involved in classical conditioning. We describe here an experiment suggesting that this third source of calcium is necessary for the cellular changes underlying associative memory storage. Paired presentations of a light stimulus with a turbulence stimulus resulted in a significant increase in input resistance. Unpaired presentations of light and turbulence did not produce a significant increase in input resistance. A third group of nervous systems first was incubated in dantrolene to block release of calcium through the ryanodine receptor, and then received paired training. There was no change in input resistance for this group. The effect of dantrolene on light adaptation of the photoreceptor was assessed by measuring the generator potential of a second light pulse presented some number of seconds after a first light pulse. The results show that at interpulse intervals of 5 s, 10 s and 20 s, the generator potential of the dantrolene group is significantly greater than that of the control group. These results suggest a role for the ryanodine receptor in both a cellular correlate of classical conditioning and light adaptation.

Action Potentials↗

PubMed1998

The effect of white and filtered noise on contrast detection thresholds.

Models of the dipper effect seen in contrast discrimination experiments predict that small amounts of noise should facilitate detection of a subthreshold sinusoidal grating. Although facilitation of chromatic sine waves has been measured with chromatic or luminance noise, a facilitory effect of luminance sinusoidal gratings has not been measured, most likely because the stimulus characteristics were not tuned for revealing facilitation. The present study measures contrast detection thresholds (CDTs) of sinusoidal gratings in two-dimensional, static, band-limited white noise and low-pass and high-pass filtered noise using a two-interval forced-choice paradigm. The results show facilitation in near threshold white noise of middle frequency sinusoidal gratings, and facilitation in filtered noise of sinusoidal gratings whose frequency is far outside the pass band of the noise. Based on these results, a model of contrast detection thresholds is modified such that the facilitation is attributed to reduced observer uncertainty caused by small amounts of noise.

Contrast Sensitivity↗

PubMed1998

Pattern matching in a model of dendritic spines.

Pattern matching, the ability to recognize and maximally respond to an input pattern that is similar to a previously learned pattern, is an essential step in any learning process. To investigate the properties of pattern matching in biological neurons, and in particular the role of a calcium-dependent potassium conductance, a circuit model of a small area of dendritic membrane with a number of dendritic spines is developed. Circuit model simulations show that dendritic membrane depolarization is greater in response to a previously learned pattern of synaptic inputs than in response to a novel pattern of synaptic inputs. These simulations, in combination with an analysis of the circuit model equations, reveal that when a synaptic input pattern is similar to the learned pattern of synaptic inputs, the total dendritic depolarization is a linear combination of dendritic depolarization contributed by individual spines. When at least one synaptic input differs markedly from the learned value, dendritic depolarization is a nonlinear combination of individual spine depolarizations. These principles of spine interactions are captured in a computationally simple set of 'similarity measure' equations which are shown to reproduce the response surface of the circuit model output. Thus, these similarity measure equations not only describe a biologically plausible model of pattern matching, they also satisfy computational requirements for use in artificial neural networks.

Animals↗

PubMed1996

Orange juice classification with a biologically based neural network.

Dystal, an artificial neural network, was used to classify orange juice products. Nine varieties of oranges collected from six geographical regions were processed into single-strength, reconstituted or frozen concentrated orange juice. The data set represented 240 authentic and 173 adulterated samples of juices; 16 variables [8 flavone and flavanone glycoside concentrations measured by high-performance liquid chromatography (HPLC) and 8 trace element concentrations measured by inductively coupled plasma spectroscopy] were selected to characterize each juice and were used as input to Dystal. Dystal correctly classified 89.8% of the juices as authentic or adulterated. Classification performance increased monotonically as the percentage of pulpwash in the sample increased. Dystal correctly identified 92.5% of the juices by variety (Valencia vs non-Valencia).

Algorithms↗

PubMed1996

Utility of a Wisconsin Card Sorting Test short form in persons with Alzheimer's and Parkinson's disease.

The utility of administering only the first deck of 64 cards from the Wisconsin Card Sorting Test (WCST-64) in persons with Alzheimer's (AD) and Parkinson's disease (PD) was evaluated. There were 35 elderly subjects matched for gender, age, and education in each of four groups: controls, PD without dementia (PDN), PD with dementia (PDD), and AD. Additionally, the control and PDN subjects were matched for level of cognitive functioning as were the PDD and AD groups. Results revealed that demented persons performed significantly worse than nondemented subjects. The WCST-64 was also sensitive to the subtle executive deficits demonstrated by persons with PD without dementia. The findings support the use of the WCST-64 in elderly persons with AD and PD.

Aged↗

PubMed1993

Associative learning in a network model of Hermissenda crassicornis. II. Experiments.

A companion paper in a previous issue of this journal presented a resistance-capacitance circuit computer model of the four-neuron visual-vestibular network of the invertebrate marine mollusk Hermissenda crassicornis. In the present paper, we demonstrate that changes in the model's output in response to simulated associative training is quantitatively similar to behavioral and electrophysiological changes in response to associative training of Hermissenda crassicornis. Specifically, the model demonstrates many characteristics of conditioning: sensitivity to stimulus contingency, stimulus specificity, extinction, and savings. The model's learning features also are shown to be devoid of non-associative components. Thus, this computational model is an excellent tool for examining the information flow and dynamics of biological associative learning and for uncovering insights concerning associative learning, memory, and recall that can be applied to the development of artificial neural networks.

Animals↗

PubMed1992

Associative learning in a network model of Hermissenda crassicornis. I. Theory.

A time-varying Resistance-Capacitance (RC) circuit computer model was constructed based on known membrane and synaptic properties of the visual-vestibular network of the marine snail Hermissenda crassicornis. Specific biophysical properties and synaptic connections of identified neurons are represented as lumped parameters (circuit elements) in the model; in the computer simulation, differential equations are approximated by difference equations. The model's output, membrane potential, an indirect measure of firing frequency, closely parallels the behavioral and electrophysiologic outputs of Hermissenda in response to the same input stimuli presented during and after associative learning. The parallelism of the computer modeled and the biologic outputs suggests that the model captures the features necessary and sufficient for associative learning.

Animals↗

PubMed1990

Pattern-recognition by an artificial network derived from biologic neuronal systems.

A novel artificial neural network, derived from neurobiological observations, is described and examples of its performance are presented. This DYnamically STable Associative Learning (DYSTAL) network associatively learns both correlations and anticorrelations, and can be configured to classify or restore patterns with only a change in the number of output units. DYSTAL exhibits some particularly desirable properties: computational effort scales linearly with the number of connections, i.e., it is O(N) in complexity; performance of the network is stable with respect to network parameters over wide ranges of their values and over the size of the input field; storage of a very large number of patterns is possible; patterns need not be orthogonal; network connections are not restricted to multi-layer feed-forward or any other specific structure; and, for a known set of deterministic input patterns, the network weights can be computed, a priori, in closed form. The network has been associatively trained to perform the XOR function as well as other classification tasks. The network has also been trained to restore patterns obscured by binary or analog noise. Neither global nor local feedback connections are required during learning; hence the network is particularly suitable for hardware (VLSI) implementation.

Animals↗

PubMed1990

Performance comparison of a neural network with human observers on a visual target detection task.

An experiment is described which compares the performance of a neural network to human performance on a visual task which consists of detecting a target in a background image of correlated noise. A three-layer, feed-forward, multi-layer perceptron is trained to indicate the presence or absence of a target in images also presented to human observers. The basis for the comparison between the network and the human observers is the receiver operating characteristic (ROC) curve. Network performance is comparable to human performance for this particular task.

Artificial Intelligence↗

PubMed1988

Quantitative studies of color constancy.

In order to study color constancy, the color appearance of the center of a center-surround paradigm was measured by using multiple-alternative forced-response matching. The center was presented with (1) no surround, (2) an adjacent chromatic surround, or (3) a chromatic surround separated from the center by an achromatic gap. The center and the surrounds were presented under various simulated illuminants ranging from illuminant A to illuminant D75. We found that when no surround is present, color constancy fails; however, when surrounds are present, some degree of color constancy is displayed. We also found that color constancy is poor when chromatic induction is minimal. In addition, it was determined that, if the ratios of R, G, and B of the center to R, G, and B of the surround remain constant as the illuminant changes, color constancy results. (R, G, and B correspond to the outputs of the retinal color mechanisms).

Color↗

PubMed1982

Measurement of empathy toward rape victims and rapists.

The purpose of the present study was the construction of the Rape Empathy Scale (RES), designed to measure subjects' empathy toward the rape victim and the rapist in a heterosexual rape situation. The results of psychometric analyses of reliability for both a student and juror sample are presented, in addition to evidence of cross-validation on separate student and juror samples. Significant differences between male and female subjects' RES scores were found, as well as differences between scores of women who had experienced a rape situation (rape victims and rape resisters) and women with no previous exposure to rape. RES scores were predictive of both students' and jurors' ratings of defendant guilt, as well as their recommended sentences for the defendant and their attributions of responsibility for the crime. Furthermore, subjects' RES scores were predictive of their social perceptions of the rape victim and defendant, and male jurors' RES scores were negatively correlated with their reported desire to rape a woman. The results are discussed in relation to the low conviction rate for sexual assault cases and the importance of juror selection as a vehicle for increasing the number of just convictions in rape cases.

Adult↗