Sharon Goodall

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.

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 models 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.

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.

An experimental study of criteria for hypothesis plausibility

Abstract Abductive diagnostic problem-solving systems use causal relations to infer plausible diagnostic hypotheses. An important but controversial issue for such models is what characteristics should define the most plausible hypotheses. While there are theoretical predictions relevant to this issue, there are almost no empirical data on which to base rational decisions. Accordingly, this study examines four different criteria of hypothesis plausibility in diagnosing the site of brain damage in 100 medical patients. The criteria examined are (1) naive minimal cardinality, (2) irredundancy, (3) most probable (Bayesian), and (4) minimal cardinality when adjacency relations are taken into account. Model performance when these different hypothesis plausibility criteria are used confirms the previously predicted inadequacy of minimal cardinality. It also indicates that irredundancy (‘minimality’), the criterion most widely used in current AI models, is not useful in this setting because of the large number of...

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

Abstract 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. [Neurol Res 2001; 23: 465-471]

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.

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.

A connectionist model for dynamic control

Abstract This paper describes an application of connectionist modeling techniques in the area of dynamic device control. In particular, competition-based spreading activation is applied to a simplified problem in camera tracking. Performance measures are obtained for both the fully operational connectionist network and for a partially impaired network. It is found that the connectionist model performed well in both cases, with the performance of the partially impaired network only being mildly diminished. This work shows that there is potential for the use of competitive activation mechanisms in such applications.

Chapter 14 Penumbral tissue damage following acute stroke: a computational investigation

Publisher Summary This chapter discusses a computational study of possible mechanisms that may underlie the spread of ischemic damage from the infarct core to the penumbra (peri-infarct) area. The chapter focuses on primary mechanisms that play a causal role in the activation of a cascade of metabolic events that eventually leads to penumbra tissue death. The chapter also presents a set of theoretical predictions that, if tested experimentally, may help in delineating the pathological mechanisms that play a leading role in this highly important pathological state. There are currently two major hypotheses concerning the primary causal mechanism underlying penumbral tissue death during acute ischemic stroke. The leading theory is that, ischemic (penumbral) damage is caused by the progression of cortical spreading depression (CSD) waves. The movement of CSD waves across the cortex may be viewed as a reaction-diffusion process, involving potassium ions in the extracellular compartment.

Abductive localization of brain damage: incorporating spatial adjacency relations

An important problem in neurology is to localize the site of damage to the nervous system given a patients examination findings. While the reasoning processes involved in this neurologic localization task are a type of diagnostic reasoning, they are distinguished by their heavy use of anatomical (spatial) relationships. Previous attempts to automate neurological localization have met with limited success. This paper describes an abductive problem-solving method for neurological localization based on parsimonious covering theory (PCT). Basic PCT is augmented by adding spatial relationships between elementary anatomic units. Our models localization for 100 stroke patients was compared to that of a neurologist specializing in stroke who was not involved with the models development. In 99 cases, the problem-solving system based on the augmented PCT algorithm identified the location of nervous system damage (brainstem or either hemisphere) found by the stroke expert. In the one case of complete disagreement, the problem-solving system was proven correct. Examination of the detailed localizations in terms of the elementary anatomical units involved indicated a number of interesting differences between human and automated inference processes. These results demonstrate that an augmented PCT approach has substantial promise for neurological localization.