bluuebunny/crossref_metadata_2025 huggingface dataset:
Themes and Strategies for Studying the Biology of Stroke Recovery in the Poststroke Epoch
Authors: Carmichael S. Thomas
Published: February 2008

Background and Purpose—

This review will focus on the emerging principles of neural repair after stroke, and on the overlap between cellular mechanisms of neural repair in stroke and clinical principles of recovery and rehabilitation.

Summary of Review—Stroke induces axonal sprouting and neurogenesis. Axonal sprouting occurs in tissue adjacent to the stroke and its connected cortical areas, and from sites that are contralateral to the infarct. Neurogenesis produces newly born immature neurons in peri-infarct striatum and cortex. Stimulation of both axonal sprouting and neurogenesis is associated with improved recovery in animal models of stroke. A unique cellular environment in the poststroke brain supports neural repair: an association of angiogenic and remodeling blood vessels with newly born immature neurons in a neurovasclar niche. Controversies in the field of neural repair after stroke persist, and relate to the locations of axonal sprouting in animal models of stroke and how these correlate to patterns of human remapping and recovery, and to the different models of stroke used in studies of neurogenesis.

Conclusions—

On a cellular level, the phenomenology of neural repair after stroke has been defined and unique regenerative environments in the poststroke brain identified. As the field moves toward specific studies of causal mechanisms in poststroke repair, it will need to maintain a perspective of the animal models suited to the study of neural repair after stroke as they relate to the patterns of recovery in humans in this disease.
Nitric Oxide Modulates Spreading Depolarization Threshold in the Human and Rodent Cortex
Authors: Petzold Gabor C. , Haack Stephan , von Bohlen und Halbach Oliver , Priller Josef , Lehmann Thomas-Nicolas , Heinemann Uwe , Dirnagl Ulrich , Dreier Jens P.
Published: February 2008

Background and Purpose—

Recent clinical data have suggested that prolonged cortical spreading depolarizations (CSDs) contribute to the pathogenesis of delayed ischemic neurologic deficits after subarachnoid hemorrhage. Elevated extracellular potassium concentrations and lowered nitric oxide (NO) levels have been detected in experimental and clinical subarachnoid hemorrhage. We investigated whether a similar extracellular composition renders the brain more susceptible to CSDs.

Methods—

Electrophysiologic and blood flow changes were studied in vivo in rats. Intrinsic optical signals, alterations of NO level, and electrophysiologic changes were investigated in rodent and human brain slices.

Results—

Elevation of subarachnoid extracellular potassium in rats in vivo triggered CSDs. Using NO-sensitive dyes, we found that CSDs induce NO synthesis in neurons and endothelial cells. When we blocked NO synthesis in vivo, CSDs occurred at a significantly lower threshold and propagated with a wave of ischemia. This increased susceptibility for CSDs by a low NO level was confirmed in rat and human neocortical slices and depended on P/Q-type calcium channels and
N
-methyl-
d
-aspartate receptors, but not on guanylate cyclase. Mice deficient in endothelial NO synthase, in contrast to mice deficient in neuronal NO synthase, had an inherently lower threshold.

Conclusions—

Basal NO production determined CSD threshold. The threshold effect depended predominantly on endothelial NO synthase. Reduced NO levels, as in patients with subarachnoid hemorrhage, may render the brain more susceptible to CSDs. Because CSDs have been linked to the pathogenesis of delayed ischemic neurologic deficits, raising its threshold by increasing NO availability may prove therapeutically beneficial in patients with subarachnoid hemorrhage.
A Hierarchy of Evolution Programs: An Experimental Study
Authors: Michalewicz Zbigniew
Published: February 2008

In this paper we present the concept of evolution programs and discuss a hierarchy of such programs for a particular problem. We argue that (for a particular problem) stronger evolution programs (in terms of the problem-specific knowledge incorporated in the system) should perform better than weaker ones. This hypothesis is based on a number of experiments and a simple intuition that problem-specific knowledge enhances an algorithm's performance; at the same time it narrows the applicability of an algorithm. Trade-offs between the effort of finding an effective representation for general-purpose evolution programs and the effort of developing more specialized systems are also discussed.
A Sequential Niche Technique for Multimodal Function Optimization
Authors: Beasley David , Bull David R. , Martin Ralph R.
Published: February 2008

A technique is described that allows unimodal function optimization methods to be extended to locate all optima of multimodal problems efficiently. We describe an algorithm based on a traditional genetic algorithm (GA). This technique involves iterating the GA but uses knowledge gained during one iteration to avoid re-searching, on subsequent iterations, regions of problem space where solutions have already been found. This gain is achieved by applying a fitness derating function to the raw fitness function, so that fitness values are depressed in the regions of the problem space where solutions have already been found. Consequently, the likelihood of discovering a new solution on each iteration is dramatically increased. The technique may be used with various styles of GAs or with other optimization methods, such as simulated annealing. The effectiveness of the algorithm is demonstrated on a number of multimodal test functions. The technique is at least as fast as fitness sharing methods. It provides an acceleration of between 1 and l0p on a problem with p optima, depending on the value of p and the convergence time complexity.
Using Genetic Algorithms to Explore Pattern Recognition in the Immune System
Authors: Forrest Stephanie , Javornik Brenda , Smith Robert E. , Perelson Alan S.
Published: February 2008

This paper describes an immune system model based on binary strings. The purpose of the model is to study the pattern-recognition processes and learning that take place at both the individual and species levels in the immune system. The genetic algorithm (GA) is a central component of the model. The paper reports simulation experiments on two pattern-recognition problems that are relevant to natural immune systems. Finally, it reviews the relation between the model and explicit fitness-sharing techniques for genetic algorithms, showing that the immune system model implements a form of implicit fitness sharing.
A Genetic Algorithm for Channel Routing in VLSI Circuits
Authors: Lienig Jens , Thulasiraman K.
Published: February 2008

A new genetic algorithm for channel routing in the physical design process of VLSI circuits is presented. The algorithm is based on a problem-specific representation scheme and problem-specific genetic operators. The genetic encoding and our genetic operators are described in detail. The performance of the algorithm is tested on different benchmarks, and it is shown that the results obtained using the proposed algorithm are either qualitatively similar to or better than the best published results.
Evolutionary Divide and Conquer (I): A Novel Genetic Approach to the TSP
Authors: Valenzuela Christine L. , Jones Antonia J.
Published: February 2008

Experiments with genetic algorithms using permutation operators applied to the traveling salesman problem (TSP) tend to suggest that these algorithms fail in two respects when applied to very large problems: they scale rather poorly as the number of cities n increases, and the solution quality degrades rapidly. We propose an alternative approach for genetic algorithms applied to hard combinatoric search which we call Evolutionary Divide and Conquer (EDAC). This method has potential for any search problem in which knowledge of good solutions for subproblems can be exploited to improve the solution of the problem itself. The idea is to use the genetic algorithm to explore the space of problem subdivisions rather than the space of solutions themselves. We give some preliminary results of this method applied to the geometric TSP.
Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
Authors: Srinivas N. , Deb Kalyanmoy
Published: February 2008

In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands that the user have knowledge about the underlying problem. Moreover, in solving multiobjective problems, designers may be interested in a set of Pareto-optimal points, instead of a single point. Since genetic algorithms (GAs) work with a population of points, it seems natural to use GAs in multiobjective optimization problems to capture a number of solutions simultaneously. Although a vector evaluated GA (VEGA) has been implemented by Schaffer and has been tried to solve a number of multiobjective problems, the algorithm seems to have bias toward some regions. In this paper, we investigate Goldberg's notion of nondominated sorting in GAs along with a niche and speciation method to find multiple Pareto-optimal points simultaneously. The proof-of-principle results obtained on three problems used by Schaffer and others suggest that the proposed method can be extended to higher dimensional and more difficult multiobjective problems. A number of suggestions for extension and application of the algorithm are also discussed.
Toward a Theory of Evolution Strategies: The (μ, λ)-Theory
Authors: Beyer Hans-Georg
Published: February 2008

The multimembered evolution strategy (ES) acting on μ parents and λ offspring is analyzed for real-valued, N-dimensional parameter spaces (N ≳ 30). N-dependent progress rate formulas are derived for (1, λ) and (μ, λ) strategies on spherical models. The analytical results obtained are compared with simulation experiments for the (hyper)sphere and the inclined (hyper)plane.
Empirical Studies of the Genetic Algorithm with Noncoding Segments
Authors: Wu Annie S. , Lindsay Robert K.
Published: February 2008

The genetic algorithm (GA) is a problem-solving method that is modeled after the process of natural selection. We are interested in studying a specific aspect of the GA: the effect of noncoding segments on GA performance. Noncoding segments are segments of bits in an individual that provide no contribution, positive or negative, to the fitness of that individual. Previous research on noncoding segments suggests that including these structures in the GA may improve GA performance. Understanding when and why this improvement occurs will help us to use the GA to its full potential. In this article we discuss our hypotheses on noncoding segments and describe the results of our experiments. The experiments may be separated into two categories: testing our program on problems from previous related studies, and testing new hypotheses on the effect of noncoding segments.
Classifier Fitness Based on Accuracy
Authors: Wilson Stewart W.
Published: February 2008

In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier's fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier's fitness is given by a measure of the prediction's accuracy. The system executes the genetic algorithm in niches defined by the match sets, instead of panmictically. These aspects of XCS result in its population tending to form a complete and accurate mapping X × A → P from inputs and actions to payoff predictions. Further, XCS tends to evolve classifiers that are maximally general, subject to an accuracy criterion. Besides introducing a new direction for classifier system research, these properties of XCS make it suitable for a wide range of reinforcement learning situations where generalization over states is desirable.
Toward a Theory of Evolution Strategies: Self-Adaptation
Authors: Beyer Hans-Georg
Published: February 2008

This paper analyzes the self-adaptation (SA) algorithm widely used to adapt strategy parameters of the evolution strategy (ES) in order to obtain maximal ES performance. The investigations are concentrated on the adaptation of one general mutation strength σ (called σSA) in (1, λ) ESs. The hypersphere serves as the fitness model.

Starting from an introduction to the basic concept of self-adaptation, a framework for the analysis of σSA is developed on two levels: a microscopic level, concerning the description of the stochastic changes from one generation to the next, and a macroscopic level, describing the evolutionary dynamics of the σSA over time (generations). The σSA requires the fixing of a new strategy parameter, known as the learning parameter. The influence of this parameter on ES performance is investigated and rules for its tuning are presented and discussed. The results of the theoretical analysis are compared with ES experiments; it will be shown that applying Schwefel's τ-scaling rule guarantees the linear convergence order of the ES.
Evolutionary Algorithms for Constrained Parameter Optimization Problems
Authors: Michalewicz Zbigniew , Schoenauer Marc
Published: February 2008

Evolutionary computation techniques have received a great deal of attention regarding their potential as optimization techniques for complex numerical functions. However, they have not produced a significant breakthrough in the area of nonlinear programming due to the fact that they have not addressed the issue of constraints in a systematic way. Only recently have several methods been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems; however, these methods have several drawbacks, and the experimental results on many test cases have been disappointing.

In this paper we (1) discuss difficulties connected with solving the general nonlinear programming problem; (2) survey several approaches that have emerged in the evolutionary computation community; and (3) provide a set of 11 interesting test cases that may serve as a handy reference for future methods.
How Mutation and Selection Solve Long-Path Problems in Polynomial Expected Time
Authors: Rudolph Günter
Published: February 2008

It is shown by means of Markov chain analysis that unimodal binary long-path problems can be solved by mutation and elitist selection in a polynomially bounded number of trials on average.
Evolutionary Program Induction Directed by Logic Grammars
Authors: Wong Man Leung , Leung Kwong Sak
Published: February 2008

Program induction generates a computer program that can produce the desired behavior for a given set of situations. Two of the approaches in program induction are inductive logic programming (ILP) and genetic programming (GP). Since their formalisms are so different, these two approaches cannot be integrated easily, although they share many common goals and functionalities. A unification will greatly enhance their problem-solving power. Moreover, they are restricted in the computer languages in which programs can be induced. In this paper, we present a flexible system called LOGENPRO (The LOgic grammar-based GENetic PROgramming system) that uses some of the techniques of GP and ILP. It is based on a formalism of logic grammars. The system applies logic grammars to control the evolution of programs in various programming languages and represent context-sensitive information and domain-dependent knowledge. Experiments have been performed to demonstrate that LOGENPRO can emulate GP and GP with automatically defined functions (ADFs). Moreover, LOGENPRO can employ knowledge such as argument types in a unified framework. The experiments show that LOGENPRO has superior performance to that of GP and GP with ADFs when more domain-dependent knowledge is available. We have applied LOGENPRO to evolve general recursive functions for the even-n-parity problem from noisy training examples. A number of experiments have been performed to determine the impact of domain-specific knowledge and noise in training examples on the speed of learning.
Algebraic Theory of Recombination Spaces
Authors: Stadler Peter F. , Wagner Günter P.
Published: February 2008

A new mathematical representation is proposed for the configuration space structure induced by recombination, which we call “P-structure.” It consists of a mapping of pairs of objects to the power set of all objects in the search space. The mapping assigns to each pair of parental “genotypes” the set of all recombinant genotypes obtainable from the parental ones. It is shown that this construction allows a Fourier decomposition of fitness landscapes into a superposition of “elementary landscapes.” This decomposition is analogous to the Fourier decomposition of fitness landscapes on mutation spaces. The elementary landscapes are obtained as eigenfunctions of a Laplacian operator defined for P-structures. For binary string recombination, the elementary landscapes are exactly the p-spin functions (Walsh functions), that is, the same as the elementary landscapes of the string point mutation spaces (i.e., the hypercube). This supports the notion of a strong homomorphism between string mutation and recombination spaces. However, the effective nearest neighbor correlations on these elementary landscapes differ between mutation and recombination and among different recombination operators. On average, the nearest neighbor correlation is higher for one-point recombination than for uniform recombination. For one-point recombination, the correlations are higher for elementary landscapes with fewer interacting sites as well as for sites that have closer linkage, confirming the qualitative predictions of the Schema Theorem. We conclude that the algebraic approach to fitness landscape analysis can be extended to recombination spaces and provides an effective way to analyze the relative hardness of a landscape for a given recombination operator.
Genetic Algorithms, Path Relinking, and the Flowshop Sequencing Problem
Authors: Reeves Colin R. , Yamada Takeshi
Published: February 2008

In a previous paper, a simple genetic algorithm (GA) was developed for finding (approximately) the minimum makespan of the n-job, m-machine permutation flowshop sequencing problem (PFSP). The performance of the algorithm was comparable to that of a naive neighborhood search technique and a proven simulated annealing algorithm. However, recent results have demonstrated the superiority of a tabu search method in solving the PFSP. In this paper, we reconsider the implementation of a GA for this problem and show that by taking into account the features of the landscape generated by the operators used, we are able to improve its performance significantly.
DNA Computation: Theory, Practice, and Prospects
Authors: Maley Carlo C.
Published: February 2008

L. M. Adleman launched the field of DNA computing with a demonstration in 1994 that strands of DNA could be used to solve the Hamiltonian path problem for a simple graph. He also identified three broad categories of open questions for the field. First, is DNA capable of universal computation? Second, what kinds of algorithms can DNA implement? Third, can the error rates in the manipulations of the DNA be controlled enough to allow for useful computation? In the two years that have followed, theoretical work has shown that DNA is in fact capable of universal computation. Furthermore, algorithms for solving interesting questions, like breaking the Data Encryption Standard, have been described using currently available technology and methods. Finally, a few algorithms have been proposed to handle some of the apparently crippling error rates in a few of the common processes used to manipulate DNA. It is thus unlikely that DNA computation is doomed to be only a passing curiosity. However, much work remains to be done on the containment and correction of errors. It is far from clear if the problems in the error rates can be solved sufficiently to ever allow for general-purpose computation that will challenge the more popular substrates for computation. Unfortunately, biological demonstrations of the theoretical results have been sadly lacking. To date, only the simplest of computations have been carried out in DNA. To make significant progress, the field will require both the assessment of the practicality of the different manipulations of DNA and the implementation of algorithms for realistic problems. Theoreticians, in collaboration with experimentalists, can contribute to this research program by settling on a small set of practical and efficient models for DNA computation.
Schema Theory for Genetic Programming with One-Point Crossover and Point Mutation
Authors: Poli Riccardo , Langdon William B.
Published: February 2008

We review the main results obtained in the theory of schemata in genetic programming (GP), emphasizing their strengths and weaknesses. Then we propose a new, simpler definition of the concept of schema for GP, which is closer to the original concept of schema in genetic algorithms (GAs). Along with a new form of crossover, one-point crossover, and point mutation, this concept of schema has been used to derive an improved schema theorem for GP that describes the propagation of schemata from one generation to the next. We discuss this result and show that our schema theorem is the natural counterpart for GP of the schema theorem for GAs, to which it asymptotically converges.
An Evolutionary Algorithm for Interval Solid Transportation Problems
Authors: Jiménez Fernando , Verdegay José L.
Published: February 2008

The Solid Transportation Problem arises when bounds are given on three item properties. Usually, these properties are source, destination and mode of transport (conveyance), and may be given in an interval way. This paper deals with solid transportation problems in which the data in the constraint set are expressed in an interval form, i.e. when sources, destinations and conveyances have interval values instead of point values. An arbitrary linear or nonlinear objective function is also considered. To solve the problem, an Evolutionary Algorithm which extends and generalizes other approaches considering only point values, is proposed.
Multi-objective Genetic Algorithms: Problem Difficulties and Construction of Test Problems
Authors: Deb Kalyanmoy
Published: February 2008

In this paper, we study the problem features that may cause a multi-objective genetic algorithm (GA) difficulty in converging to the true Pareto-optimal front. Identification of such features helps us develop difficult test problems for multi-objective optimization. Multi-objective test problems are constructed from single-objective optimization problems, thereby allowing known difficult features of single-objective problems (such as multi-modality, isolation, or deception) to be directly transferred to the corresponding multi-objective problem. In addition, test problems having features specific to multi-objective optimization are also constructed. More importantly, these difficult test problems will enable researchers to test their algorithms for specific aspects of multi-objective optimization.
Why Does the Brain Have So Many Visual Areas?
Authors: Kaas Jon H.
Published: February 2008

Mammals vary in number of visual areas from a few to 20 or more as a result of new visual areas being added to the middle levels of processing hierarchies. Having more visual areas probably increases visual abilities, perhaps in part by allowing more stimulus parameters to be considered. Proposals that each visual area computes and thereby “detects” a specific stimulus attribute have so far dealt with attributes that most mammals can detect and thus do not relate to the issue of species differences in numbers of areas. The problem of forming and maintaining complex patterns of interconnections between many different sets of distinct processing models within an area may limit multiplying functions within a field. In addition, the adding of new visual areas is a way of avoiding constraints on modifying existing visual areas that are imposed by the ongoing functional requirements. Thus, increasing the number of visual or other cortical areas is an effective and apparently common mechanism for evolving new capacities.
Neural Processes Involved in Directing Attention
Authors: Harter M. Russell , Miller Steven L. , Price Natalie J. , LaLonde Margaret E. , Keyes Alvin L.
Published: February 2008

Neural processes associated with two aspects of visual-spatial attention were investigated with event-related potential (ERPs): those that direct spatial attention to a given point in space and those that modulate the processing of sensory input after attention has been directed. The subjects were 6- to 9-year-old children (51 boys and 35 girls). An arrow cue directed attention from the central to peripheral visual field; targets were then flashed in the attended or ignored visual field 600 msec after the cue.

The directing of attention to the left vs. right visual field was associated with hemispheric differences in slow potentials prior to the presentation of the targets. The earliest potential, which started about 200 msec after the cue and was negative over the hemisphere contralateral to the direction of attention, was greatest over the parietal area and appeared to reflect processes directing attention per se. The last potential, which peaked 60 msec after the target and was positive over the hemisphere contralateral to the direction of attention, was greatest over the occipital-parietal region. It appeared to reflect the modulation of cortical excitability in the regions receiving input from the relevant and irrelevant visual fields. The effects of spatial attention on P1, N1, and P3 ERP components following the targets replicated previous results. Boys appeared more aroused (as indicated by CNVs) and reflected faster and greater selective processing (as indicated by reaction time, and N1-P1 latency and amplitude) than girls.
Does Scopolamine Directly Impair Memory?
Authors: Grober Ellen , Leipzig Rosanne M. , Lipton Richard B. , Wisniewski Wendy , Schroeder Mary , Davies Peter , Ritter Walter , Buschke Herman
Published: February 2008

Enhanced cued recall, a procedure which circumvents inattention and induces semantic processing, was used to determine if scopolamine produces direct impairment of specific memory mechanisms or indirect impairment of memory secondary to impairment of other cognitive processes. In two studies, cognitively normal young adults given moderate or high doses of scopolamine maintained maximum cued recall in spite of a dose-dependent decrement in free recall. This finding suggests that cholinergic blockade may impair memory indirectly through effects on other cognitive processes.
Enhancement of Metabolic Activity in the Diencephalon of Monkeys Performing Working Memory Task: A 2-Deoxyglucose Study in Behaving Rhesus Monkeys
Authors: Friedman Harriet R. , Janas Janice D. , Goldman-Rakic Patricia S.
Published: February 2008

The 2-deoxyglucose (2-DG) method was used to study the effect of working memory processing on local cerebral glucose utilization (LCGU) in the diencephalon of the rhesus monkey. Monkeys were given [14C]2-DG while performing either one of three tasks that engaged working memory (WORK group) or one of two control tasks (CONT group) that used associative or non associative processes. The tasks of the WORK group—spatial delayed response, spatial delayed alternation, and delayed object alternation—are alike in that the information guiding a correct response changes from trial to trial and only the accurate record of the preceding response (or cue) is relevant for each successive trial. The CONT group, in contrast, performed on either a visual pattern discrimination test, in which the correct stimulus–response association was invariant across all trials and all test sessions, or on a sensorimotor task in which there was no explicit memory requirement.

LCGU was examined in five diencephalic regions: the mammillary bodies, the anteroventral and anteromedial thalamus, and the parvocellular and magnocellular components of the mediodorsal thalamic nucleus. Comparisons across the two groups showed that mean LCGU in the anterior and mediodorsal thalamic nuclei was significantly elevated (by 12–16%) in the WORK group relative to the CONT group. Mean LCGU in the mammillary bodies also was higher in the WORK group than in the CONT group, but this difference was not significant.

The present findings suggest that the anterior and mediodorsal thalamic nuclei represent diecephalic components of a neural network processing working memory. Together with our previous report on the enhancement of metabolic activity in the hippocampus and dentate gyrus, these results show that working memory has a wide-ranging influence on cerebral metabolism and emphasize the cooperative, rather than dissociable, roles of the hippocampus and medial thalamus in this function.
On the Interaction of Selective Attention and Lexical Knowledge: A Connectionist Account of Neglect Dyslexia
Authors: Mozer Michael C. , Behrmann Marlene
Published: February 2008

Neglect dyslexia, a reading impairment acquired as a consequence of brain injury, is traditionally interpreted as a disturbance of selective attention. Patients with neglect dyslexia may ignore the left side of an open book, the beginning words of a line of text, or the beginning letters of a single word. These patients provide a rich but sometimes contradictory source of data regarding the locus of attentional selectivity. We have reconsidered the patient data within the framework of an existing connectionist model of word recognition and spatial attention. We show that the effects of damage to the model resemble the reading impairments observed in neglect dyslexia. In simulation experiments, we account for a broad spectrum of behaviors including the following: (1) when two noncontiguous stimuli are presented simultaneously, the contralesional stimulus is neglected (extinction); (2) explicit instructions to the patient can reduce the severity of neglect; (3) stimulus position in the visual field affects reading performance; (4) words are read much better than pronounceable nonwords; (5) the nature of error responses depends on the morphemic composition of the stimulus; and (6) extinction interacts with lexical knowledge (if two words are presented that form a compound, e.g., COW and BOY, the patient is more likely to report both than in a control condition, e.g., SUN and FLY). The convergence of findings from the neuropsychological research and the computational modeling sheds light on the role of attention in normal visuospatial processing, supporting a hybrid view of attentional selection that has properties of both early and late selection.
Simulating Visual Attention
Authors: Sandon Peter A.
Published: February 2008

Selective visual attention serializes the processing of stimulus data to make efficient use of limited processing resources in the human visual system. This paper describes a connectionist network that exhibits a variety of attentional phenomena reported by Treisman, Wolford, Duncan, and others. As demonstrated in several simulations, a hierarchical, multiscale network that uses feature arrays with strong lateral inhibitory connections provides responses in agreement with a number of prominent behaviors associated with visual attention. The overall network design is consistent with a range of data reported in the psychological literature, and with neurophysiol-ogical characteristics of primate vision.
Orienting Attention across the Vertical Meridian: Evidence from Callosotomy Patients
Authors: Reuter-Lorenz P. A. , Fendrich R.
Published: February 2008

This study investigates whether interhemispheric interactions mediated by the corpus callosum play a role in orienting attention across the vertical meridian. Patients with complete or partial section of the corpus callosum participated in a spatial precueing task under conditions that required covert shifts of attention within or between the visual fields. Patients with complete callosal section demonstrated normal costs on invalid trials when the cue and target appeared in the same visual field. However, these patients were impaired on invalid trials in which attention had to be redirected across the vertical meridian. The between–within difference emerged only for patients with complete callosal section; it was not evident for a patient with section restricted to the anterior two-thirds of the callosum. Control experiments demonstrated that the deficit (1) is specific to shifts across the vertical meridian, (2) is not due to shifting between left and right hemispace, and (3) is related to the voluntary allocation of attention in response to the cue. These results suggest that interhemispheric communication, which is normally mediated by the posterior region of the corpus callosum, contributes to the efficient movement of attention between visual fields.
Late Positive Event-Related Potentials after Commissural Section in Humans
Authors: Kutas Marta , Hillyard Steven A. , Volpe Bruce T. , Gazzaniga Michael S.
Published: February 2008

The lateral distribution of the P300 component of the event-related brain potential (ERP) was studied in five epileptic patients whose corpus callosum had been surgically sectioned and in seven neurologically intact controls. The P300 was elicited in an auditory “oddball” task using high- and low-pitched tones and in a visual oddball task in which target words were presented either to the left or right visual fields, or to both fields simultaneously. Commissurotomy altered the normal pattern of bilaterally symmetrical P300 waves over the left and right hemispheres, but in a different manner for auditory and visual stimuli. The auditory P3 to binaural tones was larger in amplitude over the right than the left hemisphere for the patients. In the visual task, the laterality of the P300 varied with the visual field of the target presentation. Left field targets elicited much larger P300 amplitudes over the right than the left hemisphere, as did bilateral targets. In contrast, right field targets triggered P300 waves of about the same amplitude over the two hemispheres. The overall amplitude of the P300 to simultaneous bilateral targets was less than the sum of the individual P300 amplitudes produced in response to the unilateral right and left field targets. These shifts in P300 laterality argue against the view that the P300 is an index of diffuse arousal or activation that is triggered in both hemispheres simultaneously irrespective of which hemisphere processes the target information. The results further demonstrate that the P300 does not depend for its production on interhemispheric comparisons of information mediated by the corpus callosum, as suggested recently by Knight et al. (1989).
Learning without Memory
Authors: Garcia John
Published: February 2008

After a CS–US learning trial, powerful feedback (FB) selectively modulates the hedonic value of the US, perhaps affecting the CS as well. FB. operates regardless of the subject's attributions or awareness, often influencing the subject's unconscious motives in a single trial. Most of the evidence comes from feeding research where the taste US and the internal FB are independently manipulated, but similar influences are at work with painful, thermal and sexual USs in a wide variety of species including humans. Implications for cognitive theorizing and neural research on mechanisms of learning are discussed.
Can We Lose Memories of Faces? Content Specificity and Awareness in a Prosopagnosic
Authors: Etcoff Nancy L. , Freeman Roy , Cave Kyle R.
Published: February 2008

Prosopagnosia is a neurological syndrome in which patients cannot recognize faces. Kecently it has been shown that some prosopagnosics give evidence of "covert" recognition: they show greater autonomic responses to familiar faces than to unfamiliar ones, and respond differently to familiar faces in learning and interference tasks. Although some patients do not show covert recognition, this has usually been attributed to an "apperceptive" deficit that impairs perceptual analysis of the input. The implication is that prosopagnosia is a deficit in access to, or awareness of, memories of faces: the inducing brain injury does not destroy the memories themselves. We present a case study that challenges this view. LH suffers from prosopagnosia as the result of a closed head injury. He cannot recognize familiar faces or report that they are familiar, nor answer questions about the faces from memory, though he can (1) recognize common objects and subtly varying shapes, (2) match faces while ignoring irrelevant information such as emotional expression or angle of view, (3) recognize sex, age, and like-ability from faces, and (4) recognize people by a number of nonfacial channels. The only other categories of shapes that he has marked trouble recognizing are animals and emotional expressions, though even these impairments were not as severe as the one for faces. Three measures (sympathetic skin response, pupil dilation, and learning correct and incorrect names of faces) failed to show any signs of covert face recognition in LH, though the measures were sensitive enough to reflect autonomic reactions in LH to stimuli other than faces, and face familiarity in normal controls. Thus prosopagnosia cannot always be attributed to a mere absence of awareness (i.e., preserved information about faces whose output is disconnected from conscious cognitive processing), to an apperceptive deficit (i.e., preserved information about faces that cannot be accessed due to improperly analyzed perceptual input), or to an inability to recognize complex or subtly varying shapes (i.e., loss or degradation of shape memory in general). We conclude that it is possible for brain injury to eliminate the storage of information about familiar faces and certain related shapes.
Separable Mechanisms in Face Processing: Evidence from Hemispheric Specialization
Authors: Hillger Lynn A. , Koenig Olivier
Published: February 2008

This article addresses three issues in face processing: First, is face processing primarily accomplished by the right hemisphere, or do both left- and right-hemisphere mechanisms play important roles? Second, are the mechanisms the same as those involved in general visual processing, or are they dedicated to face processing? Third, how can the mechanisms be characterized more precisely in terms of processes such as visual parsing? We explored these issues using the divided visual field methodology in four experiments. Experiments 1 and 2 provided evidence that both left- and right-hemisphere mechanisms are involved in face processing. In Experiment 1, a right-hemisphere advantage was found for both Same and Different trials when Same faces were identical and Different faces differed on all three internal facial features. Experiment 2 replicated the right-hemisphere advantage for Same trials but showed a left-hemisphere advantage for Different trials when one of three facial features differed between the target and the probe faces. Experiment 3 showed that the right-hemisphere advantage obtained with upright faces in Experiment 2 disappeared when the faces were inverted. This result suggests that there are right-hemisphere mechanisms specialized for processing upright faces, although it could not be determined whether these mechanisms are completely face-specific. Experiment 3 also provided evidence that the left-hemisphere mechanisms utilized in face processing tasks are general-purpose visual mechanisms not restricted to particular classes of visual stimuli. In Experiment 4, a left-hemisphere advantage was obtained when the task was to find one facial feature that was the same between the target and the probe faces. We suggest that left-hemisphere advantages shown in face processing are due to the parsing and analysis of the local elements of a face.
Cognitive Neuroscience Analyses of Memory: A Historical Perspective
Authors: Polster Michael R. , Nadel Lynn , Schacter Daniel L.
Published: February 2008

As part of the general trend toward interdisciplinary research in recent years, a growing number of investigators have come to consider both cognitive and neuroscientific perspectives when theorizing about memory. Although such cognitive neuroscience analyses are a relatively recent development, the approach has precedents in earlier scientific thinking about memory. In this article we present a historical review of three major issues in memory research---consolidation processes, the nature of memory representations, and multiple memory systems. We discuss the nature of the relation between cognitive and neuroscientific approaches to each of these issues with respect to the distinction between collateral, complementary, and convergent relations (Schacter, 1986). Although some early investigators offered analyses that linked psychological and physiological perspectives, there is little historical evidence of systematic or sustained interdisciplinary research. However, more recent work, especially with respect to hypotheses about memory systems, suggests progress toward establishing programmatic interdisciplinary research.
Spatio-Temporal Cortical Patterns Evoked in Monkeys by a Discrimination Task
Authors: Krieger Don , Sclabassi Robert J. , Coppola Richard , Nakamura Richard
Published: February 2008

The primary experimental objective of this work was to demonstrate localization and temporal sequencing of the functional steps carried out by nonhuman primate subjects during performance of a sensory discrimination task, i.e., to identify the locale and sequence of activation of regions that participate in sensory discrimination, stimulus classification, and response preparation. Multivariate statistical procedures were applied to evoked transcortical recordings to identify the location and order of occurrence of signals that are effective in discriminating task conditions and parameters. (1) Sensory discrimination, (2) stimulus classification, and (3) response preparation occurred in the expected sequence. Information that enabled discrimination using these procedures was distributed widely across the cortex; however, the maximum information content was localized to striate and prestriate cortex, anterior inferior parietal cortex, and temporal and premotor cortex, respectively. This work provides a perspective on brain mechanisms responsible for cognition and demonstrates a set of powerful multivariate analytic tools for functional mapping, i.e., identifying the location and sequencing of cognitive functions.
Visual Experience Specifically Regulates Synaptic Molecules in Rat Visual Cortex
Authors: Schoups Aniek A. , Black Ira B.
Published: February 2008

To study environmental modulation of synaptic molecular structure, the major postsynaptic density protein (mPSDp) from rat visual cortex was monitored. This membrane component, a Ca2+/calmodulin-dependent protein kinase subunit, was measured during normal postnatal development and after visual deprivation. Total synaptic membrane (SM) protein was used as an index of synapses as a whole.

During the first 2 postnatal months, total SM protein in the visual cortex increased 32–fold. In contrast, the mPSDp increased 455–fold, indicating that different molecular components of the cortical synapse develop differentially. Exposure to complete darkness during the first 2 postnatal weeks prevented normal development of total SM protein in visual cortex, values reaching only 66% of normal. Moreover, environmental lighting preferentially modulated the mPSDp, which attained only 34% of the normal value after dark rearing. Thus, visual deprivation selectively inhibited the normal development of specific synaptic components. Moreover, experience-dependent modulation was area specific. In contrast to the marked effect in visual cortex, light deprivation did not alter synapses in the nonvisual parietal and prefrontal cortices. Finally, the modulation of visual cortex mPSDp was stage specific, since visual experience did not alter the synaptic protein in adults. Our results suggest that early visual experience selectively and specifically modifies molecular synaptic components in the visual cortex.
A Connectionist Model May Shed Light on Neural Mechanisms for Visually Guided Reaching
Authors: Mel Bartlett W.
Published: February 2008

Formal principles of vision-based planning and control of arm movements are used to gain insight into the neurobio-logical mechanisms that underlie this important class of sen-sorimotor behavior. The primary conceptual tool used in this work has been a neurally inspired connectionist system called MURPHY that learns to reach for visual targets among obstacles, crudely based on the style of architecture and representations in sensory and motor areas of cerebral cortex. This system has provided a concrete implementation that demonstrates how areas of cerebral cortex could in principle interact to direct both sensory-locked and internally planned reaching movements. We use MURPHY'S simple, artificial “cortex” as a point of departure in the development of two high-level cortical models for visual limb control, involving the supplementary motor area (SMA), areas 5 and 7 of the posterior parietal lobe, and several visually responsive areas including V2, PO, and areas TPO and STP in the upper bank of the superior temporal sulcus.
A Cognitive-Anatomical Approach to Attention in Lexical Access
Authors: Compton Paul E. , Grossenbacher Peter , Posner Michael I. , Tucker Don M.
Published: February 2008

Recent PET studies have suggested a specific anatomy for feature identification, visual word forms and semantic associations. Our studies seek to explore the time course of access to these systems by use of reaction time and scalp electrical recording. Target detection times suggest that different forms of representation are involved in the detection of letter features, feature conjunctions (letters), and words. Feature search is fastest at the fovea and slows symmetrically with greater foveal eccentricity. It is not influenced by lexicality. Detecting a letter case (conjunction) shows a left to right search which differs between words and consonant strings. Analysis of scalp electrical distribution suggest an occipito-temporal distribution for the analysis of visual features (right sided) and for the visual word form discrimination (left sided). These fit with the PET results, and suggest that the feature related analysis begins within the first 100 millisec and the visual word form discriminates words from strings by about 200 msec. Lexical decision instructions can modify the computations found in both frontal and posterior areas.
Configural and Elemental Associations and the Memory Coherence Problem
Authors: Rudy Jerry W. , Sutherland Robert J.
Published: February 2008

Some important empirical findings and theoretical positions that interest contemporary students of learning and memory are discussed in the context of Luria's (1979) memory coherence perspective. This approach assumes that an important challenge to memory function is remaining closed to the influence of associations that are extraneous to the demands of the task at hand. We argue that the ability to support configural associations between representations of the joint occurrence or conjunction of two or more stimulus elements and a target memory is an important feature of a closed system but that an open system can support only elemental associations with the target. Successful performance in many tasks used to study memory can be achieved by elemental associations, but other tasks require the formation of and retrieval by configural associations. From this perspective, the pattern of spared and impaired performance often seen in animals and people with brain damage to the hippocampal system or in amnesic people of various etiologies results because their memory systems are open and can support only elemental associations.