This is a reprint of one issue in the Cambridge University Press journal Behavioral and Brain Sciences, originally based on the symposium Controversies in neuroscience IV: Motor learning and synaptic plasticity in the cerebellum, held in Portland Oregon on August 24 to 26, 1993. These symposia were organized by the Robert S. Dow Neurological Sciences Institute and supported by NIH, NSF, and the Good Samaritan Foundation. The subjects of the symposium were the role of the cerebellum in motor learning and the connection between motor learning and synaptic plasticity.

HIV infection and abuse of central nervous system (CNS) stimulants are both associated with brain damage and dysfunction. CNS stimulant overdose can lead to microinfarction, hemorrhagic lesions, and vasculitis (Bostwick, 1981; Cahill et al., 1981), and may impact frontostriatal systems. Investigations of HIV-infected (HIV+) individuals have demonstrated deficits in attention, speed of information processing, motor functioning, executive functioning, and learning efficiency. These deficits are consistent with frontostriatal involvement (Heaton et al., 1995; Martin, 1994). Given the rise in AIDS cases attributable to drug use at a time when the number of AIDS cases due to sexual transmission is stable or declining, it is critical to determine if drug use, especially CNS stimulants, potentiates HIV-related neuronal injury.

Over the past decade a number of reviewers have argued that the pattern of spared and impaired cognitive functions observed in the cognitive aging literature can be understood within the context of a neuropsychologically constrained model that proposes that the prefrontal cortex is more vulnerable to the effects of normal aging than other cortical regions (Dempster, 1992; Hartley, 1993; Moscovitch & Winocur, 1992; West, 1996). While this model has served as a valuable heuristic in my own thinking about cognitive aging, the current review of Greenwood and theoretical work emerging from other laboratories argues that the “frontal lobe hypothesis” (FLH) no longer provides a useful or accurate framework within which to understand brain behavior relationships in cognitive aging. While I agree with several of the ideas developed in the review of Greenwood (this issue) I believe the continued utility of the FLH can be demonstrated by considering two questions: (1) What does the FLH predict about cognitive aging and is there support for these predictions? and (2) Has the time come to move beyond a general specification of the FLH? In answering these questions I will provide one or two findings from the empirical literature. These are intended to be illustrative, not exhaustive.

A neural network model with dynamic thresholds, asymmetric connections, and clustered memories simulates spread activation that is hypothesized for semantic networks in the brain. By altering the parameters of the dynamic threshold a large range of disturbances can be generated in the model. These disturbances show metaphorical resemblance to certain general clinical descriptions of mental disturbances found in psychiatric patients engaged in various cognitive tasks. Even though the model is highly theoretical and metaphoric, it may help to gain certain insights into the relation between alterations of certain neural parameters, for example, thresholds and connectivity, and clinical symptoms in patients. (JINS, 2000, 6, 608–619.)

Neuropsychological aspects of neuropsychiatric diseases that are common in old age or that present problems for diagnosis and treatment especially in the old patient represent the objective of this book. There are several good reasons for addressing this topic. Disorders of brain function become more frequent in old age and neuropsychology thus gains importance in geriatric medical evaluation and in distinguishing the many dimensions of neuropsychological deviations from “normal senescence.” Research in this area has recently intensified and valuable insights have accumulated; however, few books on this topic are currently available. The Handbook of Neuropsychology and Aging focuses on neuropsychological aspects; specifically, on geriatric psychiatry and neurology. Here, the editor has attempted to bring together outstanding researchers to cover the entire field of geriatric neuropsychiatry.

West argues that the frontal aging hypothesis remains a useful construct, largely on the basis of evidence that cognitive functions dependent on frontal regions decline at an earlier age than those independent of frontal regions. This point was considered in my review, which found only sparse evidence in its favor. Few investigations have been aimed at determining the age at which decline begins for a set of functions. West cites one behavioral study (Shimamura & Jurica, 1994) and one PET study (Shaw et al., 1984). Given the size of the literature from which these studies are drawn, a finding of age effects in one “frontal” memory task with mean age 61 but not in one “nonfrontal” memory task can only suggest that age-related functional decline is more rapid in the frontal-dependent task. This finding must be viewed in the context of a broader range of functions. Several large scale studies aimed at this question have examined age-related declines on a broad range of functions and concluded verbal abilities are preserved until late in life while visuospatial abilities decline throughout adulthood (Arenberg, 1978; Eisdorfer et al., 1959; Koss et al., 1991). Shaw et al. (1984) must also be considered in the context of other studies of resting cerebral blood flow and metabolism which I reviewed which did not find selectively reduced prefrontal blood flow (Azari et al., 1992; Martin et al., 1991). Indeed, it is difficult either to prove or to disprove the somewhat vaguely-conceived frontal aging hypothesis using the current

One of the most fascinating aspects of brain research is the subject of language. As in many other cases, the malfunctions that occur in different persons for various reasons give us insight on the mechanisms that support our ability to talk, read and listen. Following the work of Plaut and associates, we deal with the dyslexia disorder, which is the overall name for a large number of reading disorders. A Boltzmann machine neural network scheme was trained to implement the nonlinear mapping task of graphic representation into semantic representation, which may model the brain sections responsible for the translation of a written word into meanings and syllables. After training, various types of lesions were applied and the performance of the network was tested in order to measure the effect of each lesion on the error rate and type distribution that were detected. The system's errors were classified into several categories and the distribution of errors between the categories was studied. Using the simulations, it is demonstrated that a finite scheduling process in the Boltzmann machine causes the distribution of the network's errors to be unique and different from its expected error distribution. The phenomenon is given a mathematical explanation rooted in the statistical mechanics basics of the Boltzmann machine. Test results suggest the localization of certain reading functions within the network. Comparison is made to relevant types of dyslexia and shows resemblance in major symptoms as well as in certain known side effects. (JINS, 2000, 6, 620–626.)

In a recent article, Temkin et al. (1999) contrasted four models for detecting significant change in individual performance on neuropsychological tests. Two of these models relied on the calculation of the Reliable Change Index (RCI) by Jacobson and Truax (1991), with and without a correction for practice associated with repeated testing. The other two models were based on simple linear regression and multiple regression, respectively. The models were contrasted based on the width of 90% prediction intervals (PI) and normal-distribution-based prediction accuracy of classifying unusual cases. Participants were tested twice (Time 1 and Time 2), on seven common neuropsychological measures. Prediction accuracy was based on the discrepancy between obtained and predicted Time 2 scores.

I cannot count the times that patients have looked at me and said, “No one really understands me unless they have had a brain injury themselves!” I agree, and therefore avoid such over-used phrases as, “I understand” and “I know what you're going through” when communicating with TBI patients.

Fifty-eight studies of the neuropathological and neuropsychological outcomes of cerebral anoxia were reviewed. Neuropathological reports were examined for the variety, extent, and specificity of lesions resulting from an anoxic event. While most attention has focused on damage to the hippocampus following anoxic brain injury, the review indicated that watershed cerebral cortex and the basal ganglia were both more frequently damaged than the hippocampus. The hippocampus was the sole affected structure in only 18% of reported cases. Neurological, neuropsychological and psychiatric studies were analyzed. Of 67 individual case reports, a memory disturbance was documented in 36 (54%), but a memory disturbance without report of additional cognitive deficits occurred in only 13 (19.4%). Changes in personality and behavior were noted in 31 (46.2%). Visuospatial or, less frequently, visual recognition problems were noted in 21 individual cases (31.3%) reviewed. Memory deficits were found in all 14 group studies reviewed, while in 9 papers changes in behavior or personality were also documented. Six studies also reported visuospatial deficits. Careful reading of the literature reveals a range of cognitive and behavioral changes that reflect very well the neuropathological outcomes of anoxic episodes. (JINS, 2000, 6, 86–99.)

This edited book has the stated purpose of filling the gap between books on normal memory and books dealing with abnormal memory by focusing specifically on memory in neurodegenerative conditions. The editor has done so by organizing the book into three main sections representative of different perspectives on memory. Each of these sections, biological, cognitive, and clinical, are summarized to coalesce the respective viewpoints into a cogent state of the art perspective for each section. The editor's intended audience includes neuropsychologists, neurologists, psychiatrists, and neuroscientists.

Negative phenomena can occur with seizures, but some ictal negative manifestations are rare and may lead to misdiagnosis. A patient series is presented with unusual ictal negative phenomena: neglect syndrome, catastrophic depression, apraxia, aphasia, amnesia, homonomous hemianopsia, and hemiparesis. One had repeated episodes with PLEDs but no parenchymal lesions. Clinicians should consider seizures in the setting of unexplained deficits, even if there are no positive ictal phenomena. (JINS, 2000, 6, 731–733.)

Because lesions usually affect contiguous areas of the brain, cognitive neuropsychology has generally posited modularity of brain function, assuming that specific regions of the brain have specific dedicated functions. However, a review of 36 published functional neuroimaging studies suggests that functions are distributed over multiple regions. Or, in other words, specific brain regions are usually multifunctional. By a technique of “virtual lesions,” I measure the contribution that regions of the brain make to tasks imaged in 36 PET experiments, and propose a new and more detailed interlink between neuropsychology and functional neuroimaging. (JINS, 2000, 6, 627–635.)

In his forward to Clinical Neuropsychology Arthur Benton comments, “More aptly than might have been anticipated, clinical neuropsychology is coming of age. I mean by this that it is evolving from what was largely a set of assessment procedures coupled with a diagnostic inference to be drawn from them into a true discipline, conscious of its conceptual bases and concerned with the cognitive and neuromechanisms that mediate the behavior of normal individuals and patients with brain disease.” Dr. Benton's assessment catches the thrust of the book well. It concerns itself with the development and maturation of the field, its relationship to sister disciplines such as behavioral neurology and neuropsychiatry, focuses in on important practice and credentialing issues, and provides cogent reviews of progress in many important content areas.

In less than 150 pages, the author has written a lucid and broad-ranging primer on functional imaging with much to offer the neuropsychologist. The book consists of three sections: “Basic Concepts,” “Three Methods of Imaging Brain Activation,” and “Establishing the Correspondence of Activation Patterns to Behavioral Functions,” with brief Preface and Postscript (“Imaging Consciousness”). The level of description is more conceptual than technical, relying more heavily on beautifully illustrated visual models of the techniques than on more mathematical accounts, and thus the material is likely to be easily accessible to clinical and basic neuroscientists alike. The text should serve well as required reading for upper division and graduate courses introducing the topic, and will be a painless and thought-provoking introduction for scientists in other areas of specialization as well.

Hinton-Bayre (2000) raises a point that may occur to many readers who are familiar with the Reliable Change Index (RCI). In our previous paper comparing four models for detecting significant change in neuropsychological performance (Temkin et al., 1999), we used a formula for calculating Sdiff, the measure of variability for the test–retest difference, that differs from the one Hinton-Bayre has seen employed in other studies of the RCI. In fact, there are two ways of calculating Sdiff—a direct method and an approximate method. As stated by Jacobson and Truax (1991, p. 14), the direct method is to compute “the standard error of the difference between the two test scores” or equivalently [begin square root](s12 + s22 − 2s1s2rxx′)[end square root] where si is the standard deviation at time i and rxx′ is the test–retest correlation or reliability coefficient. Jacobson and Truax also provide a formula for the approximation of Sdiff when one does not have access to retest data on the population of interest, but does have a test–retest reliability coefficient and an estimate of the cross-sectional standard deviation, i.e., the standard deviation at a single point in time. This approximation assumes that the standard deviations at Time 1 and Time 2 are equal, which may be close to true in many cases. Since we had the longitudinal data to directly calculate the standard error of the difference between scores at Time 1 and Time 2, we used the direct method. Which method is preferable? When the needed data are available, it is the one we used.

From the outset, it should be made clear that this book is not a new text on cognitive neuroscience. It does not pretend to cover the whole area comprehensively and is unsuitable for those wanting a thorough introduction or overview of cognitive neuroscience with colored illustrations. Instead, this volume could be considered a companion to such a text. Findings and Current Opinion in Cognitive Neuroscience, contains a set of 46 articles carefully selected from Current Opinion in Neurobiology, which is part of an even wider series offering current opinions on a wide range of scientific–medical topics (e.g., Current Opinion in Neurology and Neurosurgery). Those who browse in medical or academic libraries will be familiar with the series, which is unique. Instead of the traditional journal format, a collection of short review articles are presented, each written by an expert in the particular field. Each article summarizes current thinking in the area or field, and concludes with an annotated bibliography. Six issues of each set of current opinions are published annually. Each issue is dedicated to a particular aspect of an area.

Connolly's preface to this book ends with Jacob Bronowski's very apt quote, “the hand is the cutting edge of the mind.” The “Preface” illustrates his fascination with the complexity of human movement.

Dr. Hinton-Bayre has correctly noted a discrepancy here between the Jacobson and Temkin procedures. His comparison of prediction bounds both confirms this and suggests too that the differences are minor.

Of all the symptoms associated with aphasia, anomia may be the most pervasive. Virtually all individuals with aphasia have some degree of word-finding difficulty. Even when an individual experiences significant recovery in aphasia, anomic deficits typically remain, resulting in frustration for the anomic individual, their communication partners, and the clinicians attempting to treat them. This volume in the Foundations of Neuropsychology Series, devoted entirely to naming and its disorders, provides a welcome review incorporating current clinical findings and theoretical viewpoints.