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Biomedical subjects

J A Reggia

Publications and source records attributed to J A Reggia.

At least 19 recordsLinked to original sources

Cortical map asymmetries in the context of transcallosal excitatory influences.

There is long-standing disagreement among experimentalists about whether transcallosal interhemispheric influences are primarily excitatory or inhibitory. Past computational models exploring this issue have encountered a similar dilemma: inhibitory callosal influences best explain hemispheric functional asymmetries, but excitatory callosal influences best explain transcallosal diaschisis. We recently hypothesized that this dilemma might be resolved by assuming excitatory callosal influences and a subcortical mechanism for cross-midline inhibition. Here we explore the feasibility of this hypothesis by examining a model of map formation in corresponding left and right cortical regions. The results show for the first time that both map asymmetries and diaschisis-like changes can be produced in a single model, suggesting that subcortical inhibitory processes may contribute more to asymmetric cortical functionality than is generally recognized.

Brain Diseases↗

Conditions enabling the evolution of inter-agent signaling in an artificial world.

In the research described here we extend past computational investigations of animal signaling by studying an artificial world in which a population of initially noncommunicating agents evolves to communicate about food sources and predators. Signaling in this world can be either beneficial (e.g., warning of nearby predators) or costly (e.g., attracting predators or competing agents). Our goals were twofold: to examine systematically environmental conditions under which grounded signaling does or does not evolve, and to determine how variations in assumptions made about the evolutionary process influence the outcome. Among other things, we found that agents warning of nearby predators were a common occurrence whenever predators had a significant impact on survival and signaling could interfere with predator success. The setting most likely to lead to food signaling was found to be difficult-to-locate food sources that each have relatively large amounts of food. Deviations from the selection methods typically used in traditional genetic algorithms were also found to have a substantial impact on whether communication evolved. For example, constraining parent selection and child placement to physically neighboring areas facilitated evolution of signaling in general, whereas basing parent selection upon survival alone rather than survival plus fitness measured as success in food acquisition was more conducive to the emergence of predator alarm signals. We examine the mechanisms underlying these and other results, relate them to existing experimental data about animal signaling, and discuss their implications for artificial life research involving evolution of communication.

Animals↗

Cortical spreading depression and the pathogenesis of brain disorders: a computational and neural network-based investigation.

This paper reviews our recent studies of the role of cortical spreading depression (CSD) in the pathogenesis of brain disorders. Our investigation is a computational one, involving the development and utilization of a complex neuro-metabolic model of the interactions assumed to occur in the cortex during the passage of multiple CSD waves. Incorporating these neuro-metabolic changes of CSD within a neural network model of normoxic cortex produces cortical activation patterns during the passage of a CSD wave that, projected onto the visual fields, resemble the visual hallucinations observed during the migraine aura. When focal ischemia is simulated with the model, the evoked CSD waves are found to affect the expansion of the infarction into the ischemic penumbra. Our findings support the hypothesis that CSD does play an important pathogenic role in these and other neurological disorders, and suggest additional experimental studies that may further substantiate it.

Animals↗

The callosal dilemma: explaining diaschisis in the context of hemispheric rivalry via a neural network model.

It is often suggested that a major factor in diaschisis is the loss of transcallosal excitation to the intact hemisphere from the lesioned one. However, there is long-standing disagreement in the broader experimental literature about whether transcallosal interhemispheric influences in the human brain are primarily excitatory or inhibitory. Some experimental data are apparently better explained by assuming inhibitory callosal influences. Past neural network models attempting to explore this issue have encountered the same dilemma: in intact models, inhibitory callosal influences best explain strong cerebral lateralization like that occurring with language, but in lesioned models, excitatory callosal influences best explain experimentally observed hemispheric activation patterns following brain damage. We have now developed a single neural network model that can account for both types of data, i.e., both diaschisis and strong hemisphere specialization in the normal brain, by combining excitatory callosal influences with subcortical cross-midline inhibitory interactions. The results suggest that subcortical competitive processes may be a more important factor in cerebral specialization than is generally recognized.

Brain Injuries↗

Interhemispheric effects of simulated lesions in a neural model of letter identification.

Experimental studies have produced conflicting results about the extent to which the intact, nonlesioned cerebral hemisphere is responsible for recovery from cognitive deficits following focal brain damage such as a stroke. To obtain a better theoretical understanding of interhemispheric interactions during recovery, we examined the effects of simulated lesions to a bihemispheric neural model of letter identification under various assumptions about hemispheric asymmetries, corpus callosum influence, and lesion size. Among other results, the model demonstrates that the intact hemispheric region's participation in the recovery process is a function of preexisting lateralization and lesion size, indicating that interpretation of experimental work should take these factors into account.

Artificial Intelligence↗

Interhemispheric effects of simulated lesions in a neural model of single-word reading.

A neural model consisting of paired cerebral hemispheric regions interacting via homotopic callosal connections was trained to generate pronunciations for 50 monosyllabic words. Lateralization of this task occurred readily when different underlying cortical asymmetries were present. Following simulated focal cortical lesions of systematically varied sizes, acute changes in the distribution of cortical activation were found to be most consistent with experimental data when interhemispheric interactions were assumed to be excitatory. During subsequent recovery, the contribution of the unlesioned hemispheric region to performance improvement was a function of both the amount of preexisting lateralization and the side and size of the lesion. These results are discussed in the context of unresolved issues concerning the mechanisms underlying language lateralization, the nature of interhemispheric interactions, and the role of the nondominant hemisphere in recovery from adult aphasia.

Functional Laterality↗

Post-lesion lateralisation shifts in a computational model of single-word reading.

The mechanisms underlying lateralisation of language are incompletely understood. Existing data is inconclusive, for example, in determining which underlying asymmetries in hemispheric anatomy/physiology lead to lateralisation, the precise role of interhemispheric connections in this process, and exactly how and why lateralisation can shift following focal brain damage. Although these issues will ultimately be settled by experimentation, it is likely that computational modelling can be used to suggest, focus, and even interpret such empirical work. We have recently studied the emergence of lateralisation in an artificial neural network model having paired cerebral hemispheric regions, as the model learned to generate the correct pronunciation for simple words. In this paper we extend this previous work by examining the immediate and longer-term changes in lateralisation that occur following simulated acute hemispheric lesions. Among other things, the results demonstrate that the extent to which the non-lesioned model hemispheric region contributes to recovery is a function of lesion size, prelesion lateralisation, and assumptions about the excitatory/inhibitory influences of the corpus callosum. The relevance of these results to the currently controversial suggestion that language lateralisation shifts following focal damage to language areas, and that the unlesioned hemisphere contributes to recovery from stroke-induced aphasia in adults, is discussed.

Journal Article↗

A computational model of lateralization and asymmetries in cortical maps.

While recent experimental work has defined asymmetries and lateralization in left and right cortical maps, the mechanisms underlying these phenomena are currently not established. In order to explore some possible mechanisms in theory, we studied a neural model consisting of paired cerebral hemispheric regions interacting via a simulated corpus callosum. Starting with random synaptic strengths, unsupervised (Hebbian) synaptic modifications led to the emergence of a topographic map in one or both hemispheric regions. Because of uncertainties concerning the nature of hemispheric interactions, both excitatory and inhibitory callosal influences were examined independently. A sharp transition in model behavior was observed depending on callosal strength. For excitatory or weakly inhibitory callosal interactions, complete and symmetric mirror-image maps generally appeared in both hemispheric regions. In contrast, with stronger inhibitory callosal interactions, partial to complete map lateralization tended to occur, and the maps in each hemispheric region often became complementary. Lateralization occurred readily toward the side having a larger cortical region or higher excitability. Asymmetric synaptic plasticity, however, had only a transitory effect on lateralization. These results support the hypotheses that interhemispheric competition occurs, that multiple underlying asymmetries may lead to function lateralization, and that the effects of asymmetric synaptic plasticity may vary depending on whether supervised or unsupervised learning is involved. To our knowledge, this is the first computational model to demonstrate the emergence of topographic map lateralization and asymmetries.

Animals↗

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↗

Interhemispheric effects on map organization following simulated cortical lesions.

During recent years there has been increasing use of neural models to investigate the implications of hypotheses about brain and cognitive disorders. Here we systematically study the effects of sudden simulated lesions on cortical maps in a neural model consisting of left and right hemispheric regions connected by a corpus callosum. The model identifies conditions under which damage to one hemispheric region leads to reorganization of the contralateral, intact hemispheric region. The intact hemisphere's participation in the recovery process is found to be a function of pre-existing map lateralization/symmetry and lesion size, indicating that interpretation of future experimental work should take these factors into account.

Brain Diseases↗

A neural network model of lateralization during letter identification.

The causes of cerebral lateralization of cognitive and other functions are currently not well understood. To investigate one aspect of function lateralization, a bihemispheric neural network model for a simple visual identification task was developed that has two parallel interacting paths of information processing. The model is based on commonly accepted concepts concerning neural connectivity, activity dynamics, and synaptic plasticity. A combination of both unsupervised (Hebbian) and supervised (Widrow-Hoff) learning rules is used to train the model to identify a small set of letters presented as input stimuli in the left visual hemifield, in the central position, and in the right visual hemifield. Each visual hemifield projects onto the contralateral hemisphere, and the two hemispheres interact via a simulated corpus callosum. The contribution of each individual hemisphere to the process of input stimuli identification was studied for a variety of underlying asymmetries. The results indicate that multiple asymmetries may cause lateralization. Lateralization occurred toward the side having larger size, higher excitability, or higher learning rate parameters. It appeared more intensively with strong inhibitory callosal connections, supporting the hypothesis that the corpus callosum plays a functionally inhibitory role. The model demonstrates clearly the dependence of lateralization on different hemisphere parameters and suggests that computational models can be useful in better understanding the mechanisms underlying emergence of lateralization.

Adult↗

Computational studies of lateralization of phoneme sequence generation.

The mechanisms underlying cerebral lateralization of language are poorly understood. Asymmetries in the size of hemispheric regions and other factors have been suggested as possible underlying causal factors, and the corpus callosum (interhemispheric connections) has also been postulated to play a role. To examine these issues, we created a neural model consisting of paired cerebral hemispheric regions interacting via the corpus callosum. The model was trained to generate the correct sequence of phonemes for 50 monosyllabic words (simulated reading aloud) under a variety of assumptions about hemispheric asymmetries and callosal effects. After training, the ability of the full model and each hemisphere acting alone to perform this task was measured. Lateralization occurred readily toward the side having larger size, higher excitability, or higher-learning-rate parameter. Lateralization appeared most readily and intensely with strongly inhibitory callosal connections, supporting past arguments that the effective functionality of the corpus callosum is inhibitory. Many of the results are interpretable as the outcome of a "race to learn" between the model's two hemispheric regions, leading to the concept that asymmetric hemispheric plasticity is a critical common causative factor in lateralization. To our knowledge, this is the first computational model to demonstrate spontaneous lateralization of function, and it suggests that such models can be useful for understanding the mechanisms of cerebral lateralization.

Algorithms↗

Metrics for cortical map organization and lateralization.

Cerebral lateralization refers to the poorly understood fact that some functions are better controlled by one side of the brain than the other (e.g. handedness, language). Of particular concern here are the asymmetries apparent in cortical topographic maps that can be demonstrated electrophysiologically in mirror-image locations of the cerebral cortex. In spite of great interest in issues surrounding cerebral lateralization, methods for measuring the degree of organization and asymmetry in cortical maps are currently quite limited. In this paper, several measures are developed and used to assess the degree of organization, lateralization, and mirror symmetry in topographic map formation. These measures correct for large constant displacements as well as curving of maps. The behavior of the measures is tested on several topographic maps obtained by self-organization of an initially random artificial neural network model of a bihemispheric brain, and the results are compared with subjective assessments made by humans.

Brain Mapping↗