Genetic polymorphisms associated with the inflammatory response in bacterial meningitis.

BACKGROUND Bacterial meningitis (BM) is an infectious disease that results in high mortality and morbidity. Despite efficacious antibiotic therapy, neurological sequelae are often observed in patients after disease. Currently, the main challenge in BM treatment is to develop adjuvant therapies that reduce the occurrence of sequelae. In recent papers published by our group, we described the associations between the single nucleotide polymorphisms (SNPs) AADAT +401C > T, APEX1 Asn148Glu, OGG1 Ser326Cys and PARP1 Val762Ala and BM. In this study, we analyzed the associations between the SNPs TNF -308G > A, TNF -857C > T, IL-8 -251A > T and BM and investigated gene-gene interactions, including the SNPs that we published previously. METHODS The study was conducted with 54 BM patients and 110 healthy volunteers (as the control group). The genotypes were investigated via primer-introduced restriction analysis-polymerase chain reaction (PIRA-PCR) or polymerase chain reaction-based restriction fragment length polymorphism (PCR-RFLP) analysis. Allelic and genotypic frequencies were also associated with cytokine and chemokine levels, as measured with the x-MAP method, and cell counts. We analyzed gene-gene interactions among SNPs using the generalized multifactor dimensionality reduction (GMDR) method. RESULTS We did not find significant association between the SNPs TNF -857C > T and IL-8 -251A > T and the disease. However, a higher frequency of the variant allele TNF -308A was observed in the control group, associated with changes in cytokine levels compared to individuals with wild type genotypes, suggesting a possible protective role. In addition, combined inter-gene interaction analysis indicated a significant association between certain genotypes and BM, mainly involving the alleles APEX1 148Glu, IL8 -251 T and AADAT +401 T. These genotypic combinations were shown to affect cyto/chemokine levels and cell counts in CSF samples from BM patients. CONCLUSIONS In conclusion, this study revealed a significant association between genetic variability and altered inflammatory responses, involving important pathways that are activated during BM. This knowledge may be useful for a better understanding of BM pathogenesis and the development of new therapeutic approaches.

Sociodemographic, behavioral and genetic determinants of allostatic load in a Swiss population-based study.

Allostatic load (AL) is a marker of physiological dysregulation which reflects exposure to chronic stress. High AL has been related to poorer health outcomes including mortality. We examine here the association of socioeconomic and lifestyle factors with AL. Additionally, we investigate the extent to which AL is genetically determined. We included 803 participants (52% women, mean age 48±16years) from a population and family-based Swiss study. We computed an AL index aggregating 14 markers from cardiovascular, metabolic, lipidic, oxidative, hypothalamus-pituitary-adrenal and inflammatory homeostatic axes. Education and occupational position were used as indicators of socioeconomic status. Marital status, stress, alcohol intake, smoking, dietary patterns and physical activity were considered as lifestyle factors. Heritability of AL was estimated by maximum likelihood. Women with a low occupational position had higher AL (low vs. high OR=3.99, 95%CI [1.22;13.05]), while the opposite was observed for men (middle vs. high OR=0.48, 95%CI [0.23;0.99]). Education tended to be inversely associated with AL in both sexes(low vs. high OR=3.54, 95%CI [1.69;7.4]/OR=1.59, 95%CI [0.88;2.90] in women/men). Heavy drinking men as well as women abstaining from alcohol had higher AL than moderate drinkers. Physical activity was protective against AL while high salt intake was related to increased AL risk. The heritability of AL was estimated to be 29.5% ±7.9%. Our results suggest that generalized physiological dysregulation, as measured by AL, is determined by both environmental and genetic factors. The genetic contribution to AL remains modest when compared to the environmental component, which explains approximately 70% of the phenotypic variance.

STXBP1 encephalopathy: A neurodevelopmental disorder including epilepsy

OBJECTIVE To give a comprehensive overview of the phenotypic and genetic spectrum of STXBP1 encephalopathy (STXBP1-E) by systematically reviewing newly diagnosed and previously reported patients. METHODS We recruited newly diagnosed patients with STXBP1 mutations through an international network of clinicians and geneticists. Furthermore, we performed a systematic literature search to review the phenotypes of all previously reported patients. RESULTS We describe the phenotypic features of 147 patients with STXBP1-E including 45 previously unreported patients with 33 novel STXBP1 mutations. All patients have intellectual disability (ID), which is mostly severe to profound (88%). Ninety-five percent of patients have epilepsy. While one-third of patients presented with Ohtahara syndrome (21%) or West syndrome (9.5%), the majority has a nonsyndromic early-onset epilepsy and encephalopathy (53%) with epileptic spasms or tonic seizures as main seizure type. We found no correlation between severity of seizures and severity of ID or between mutation type and seizure characteristics or cognitive outcome. Neurologic comorbidities including autistic features and movement disorders are frequent. We also report 2 previously unreported adult patients with prominent extrapyramidal features. CONCLUSION De novo STXBP1 mutations are among the most frequent causes of epilepsy and encephalopathy. Most patients have severe to profound ID with little correlation among seizure onset, seizure severity, and the degree of ID. Accordingly, we hypothesize that seizure severity and ID present 2 independent dimensions of the STXBP1-E phenotype. STXBP1-E may be conceptualized as a complex neurodevelopmental disorder rather than a primary epileptic encephalopathy.

Familial component of epilepsy in cleft lip and palate

It is well recognized that offspring of women with epilepsy who are taking anticonvulsant medications have an increased incidence of clefting abnormalities. This increase has been attributed to the teratogenic effects of anticonvulsant medications but an alternative explanation involving a genetic association of epilepsy and clefting has also been proposed. Five family studies attempting to resolve this controversy have been inconclusive either because of study design or analytic limitations. This family study was designed to determine whether epilepsy aggregates in families ascertained by an individual with a clefting disorder. The Mayo Clinic medical linkage registry was used to identify individuals with cleft lip with or without cleft palate and cleft palate in southeast Minnesota from 1935-1986. Only those cases who were 15 years or younger during this period were included in the study. The proband's parents and descendants of their parents, including the proband's sibs, children, grandchildren, niece/nephews, grandnieces/nephews, halfsibs and spouses were also identified and all of their medical records were reviewed for seizure disorders. The standardized morbidity ratios for epilepsy of 0.9 (95% CI 0.2-2.6) observed for first degree relatives (excluding parents) and 0.0 for second degree relatives were not increased. The SMRs ranged from 0.7-2.2 for the individual relative types (parents 1.5, sibs 0.7, children 2.2, probands 1.1, spouses 2.0) and were also not increased. These results do not support the suggestions of some that clefting and epilepsy aggregate together in families. ^

Genetic diversity among alfalfa genotypes (Medicago sativa L.) of non-dormant cultivars using SSR markers and agronomic traits

The aim of this study was to assess genetic diversity among 40 alfalfa (Medicago sativa L.) genotypes of different non-dormant (FD=8) cultivars. Biomass yield, regrowth speed and reaction to spring black stem, lepto leaf spot, and rust were evaluated. Analyses of variances were performed using a mixed model to examine the agronomic variation among individuals. A principal component analysis on standardized agronomic data was performed. Agronomic data were also used to calculate Gower's distance and UPGMA algorithm. For the molecular analysis, six SSR markers were evaluated and 84 alleles were identified. The genetic distance was estimated using standard Nei's distance. Average standard genetic diversity was 0.843, indicating a high degree of variability among genotypes. Finally, a generalized procrustes analysis was performed to calculate the correlation between molecular and agronomic distance, indicating a 65.4% of consensus. This value is likely related to the low number of individuals included in the study, which might have underestimated the real phenotypic variability among genotypes. Despite the low number of individuals and SSR markers analyzed, this study provides a baseline for future diversity studies to identify genetically distant alfalfa individuals or cultivars.

Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

Genetic analysis of the mouse X inactivation center defines an 80-kb multifunction domain

Dosage compensation in mammals occurs by X inactivation, a silencing mechanism regulated in cis by the X inactivation center (Xic). In response to developmental cues, the Xic orchestrates events of X inactivation, including chromosome counting and choice, initiation, spread, and establishment of silencing. It remains unclear what elements make up the Xic. We previously showed that the Xic is contained within a 450-kb sequence that includes Xist, an RNA-encoding gene required for X inactivation. To characterize the Xic further, we performed deletional analysis across the 450-kb region by yeast-artificial-chromosome fragmentation and phage P1 cloning. We tested Xic deletions for cis inactivation potential by using a transgene (Tg)-based approach and found that an 80-kb subregion also enacted somatic X inactivation on autosomes. Xist RNA coated the autosome but skipped the Xic Tg, raising the possibility that X chromosome domains escape inactivation by excluding Xist RNA binding. The autosomes became late-replicating and hypoacetylated on histone H4. A deletion of the Xist 5′ sequence resulted in the loss of somatic X inactivation without abolishing Xist expression in undifferentiated cells. Thus, Xist expression in undifferentiated cells can be separated genetically from somatic silencing. Analysis of multiple Xic constructs and insertion sites indicated that long-range Xic effects can be generalized to different autosomes, thereby supporting the feasibility of a Tg-based approach for studying X inactivation.

Epilepsy in mice deficient in the 65-kDa isoform of glutamic acid decarboxylase

γ-Aminobutyric acid (GABA), the major inhibitory neurotransmitter in the mammalian brain, is synthesized by two glutamate decarboxylase isoforms, GAD65 and GAD67. The separate role of the two isoforms is unknown, but differences in saturation with cofactor and subcellular localization suggest that GAD65 may provide reserve pools of GABA for regulation of inhibitory neurotransmission. We have disrupted the gene encoding GAD65 and backcrossed the mutation into the C57BL/6 strain of mice. In contrast to GAD67−/− animals, which are born with developmental abnormalities and die shortly after birth, GAD65−/− mice appear normal at birth. Basal GABA levels and holo-GAD activity are normal, but the pyridoxal 5′ phosphate-inducible apo-enzyme reservoir is significantly decreased. GAD65−/− mice develop spontaneous seizures that result in increased mortality. Seizures can be precipitated by fear or mild stress. Seizure susceptibility is dramatically increased in GAD65−/− mice backcrossed into a second genetic background, the nonobese diabetic (NOD/LtJ) strain of mice enabling electroencephalogram analysis of the seizures. The generally higher basal brain GABA levels in this backcross are significantly decreased by the GAD65−/− mutation, suggesting that the relative contribution of GABA synthesized by GAD65 to total brain GABA levels is genetically determined. Seizure-associated c-fos-like immunoreactivity reveals the involvement of limbic regions of the brain. These data suggest that GABA synthesized by GAD65 is important in the dynamic regulation of neural network excitability, implicate at least one modifier locus in the NOD/LtJ strain, and present GAD65−/− animals as a model of epilepsy involving GABA-ergic pathways.

Generalized transduction in Streptomyces coelicolor

We report the isolation of generalized transducing phages for Streptomyces species able to transduce chromosomal markers or plasmids between derivatives of Streptomyces coelicolor, the principal genetic model system for this important bacterial genus. We describe four apparently distinct phages (DAH2, DAH4, DAH5, and DAH6) that are capable of transducing multiple chromosomal markers at frequencies ranging from 10−5 to 10−9 per plaque-forming unit. The phages contain DNA ranging in size from 93 to 121 kb and mediate linked transfer of genetic loci at neighboring chromosomal sites sufficiently close to be packaged within the same phage particle. The key to our ability to demonstrate transduction by these phages was the establishment of conditions expected to severely reduce superinfection killing during the selection of transductants. The host range of these phages, as measured by the ability to form plaques, extends to species as distantly related as Streptomyces avermitilis and Streptomyces verticillus, which are among the most commercially important species of this genus. Transduction of plasmid DNA between S. coelicolor and S. verticillus was observed at frequencies of ≈10−4 transductants per colony-forming unit.

The genetic link between the Chinese bamboo partridge (Bambusicola thoracica) and the chicken and junglefowls of the genus Gallus.

Further comparison of mitochondrial control-region DNA base sequences of 16 avian species belonging to the subfamily Phasianinae revealed the following: (i) Generalized perdicine birds (quails and partridges) are of ancient lineages. Even the closest pair, the common quail (Coturnix coturnix japonica) and the Chinese bamboo partridge (Bambusicola thoracica), maintained only 85.71% identity. (ii) The 12 species of phasianine birds previously and presently studied belonged to three distinct branches. The first branch was made exclusively of members of the genus Gallus, while the second branch was made of pheasants of the genera Phasianus, Chrysolophus, and Syrmaticus. Gallopheasants of the genus Lophura were distant cousins to these pheasants. The great argus (Argusianus argus) and peafowls of the genus Pavo constituted the third branch. The position of peacock-pheasants of the genus Polyplectron in the third branch was similar to that of the genus Lophura in the second branch. Members of the fourth phasianine branch, such as tragopans and monals, were not included in the present study. (iii) The one perdicine species, Bambusicola thoracica, was more closely related to phasianine genera Gallus and Pavo than to members of other perdicine genera. The above might indicate that Bambusicola belong to one-stem perdicine lineage that later splits into two sublineages that yielded phasianine birds, one evolving to Gallus, and the other differentiating toward Pavo and its allies.

Definition and diagnostic criteria of sleep-related hypermotor epilepsy

The syndrome known as nocturnal frontal lobe epilepsy is recognized worldwide and has been studied in a wide range of clinical and scientific settings (epilepsy, sleep medicine, neurosurgery, pediatric neurology, epidemiology, genetics). Though uncommon, it is of considerable interest to practicing neurologists because of complexity in differential diagnosis from more common, benign sleep disorders such as parasomnias, or other disorders like psychogenic nonepileptic seizures. Moreover, misdiagnosis can have substantial adverse consequences on patients' lives. At present, there is no consensus definition of this disorder and disagreement persists about its core electroclinical features and the spectrum of etiologies involved. To improve the definition of the disorder and establish diagnostic criteria with levels of certainty, a consensus conference using formal recommended methodology was held in Bologna in September 2014. It was recommended that the name be changed to sleep-related hypermotor epilepsy (SHE), reflecting evidence that the attacks are associated with sleep rather than time of day, the seizures may arise from extrafrontal sites, and the motor aspects of the seizures are characteristic. The etiology may be genetic or due to structural pathology, but in most cases remains unknown. Diagnostic criteria were developed with 3 levels of certainty: witnessed (possible) SHE, video-documented (clinical) SHE, and video-EEG-documented (confirmed) SHE. The main research gaps involve epidemiology, pathophysiology, treatment, and prognosis.

Virtual car accidents of epilepsy patients, interictal epileptic activity, and medication.

OBJECTIVE To investigate effects of interictal epileptic activity (IEA) and antiepileptic drugs (AEDs) on reactivity and aspects of the fitness to drive for epilepsy patients. METHODS Forty-six adult patients with demonstration of focal or generalized bursts of IEA in electroencephalography (EEG) readings within 1 year prior to inclusion irrespective of medication performed a car driving computer test or a single light flash test (39 patients performed both). Reaction times (RTs), virtual crashes, or lapses (RT ≥ 1 s in the car or flash test) were measured in an IEA burst-triggered fashion during IEA and compared with RT-measurements during unremarkable EEG findings in the same session. RESULTS IEA prolonged RTs both in the flash and car test (p < 0.001) in individual patients up to 200 ms. Generalized IEA with spike/waves (s/w) had the largest effect on RT prolongation (p < 0.001, both tests), whereas mean RT during normal EEG, age, gender, and number of AEDs had no effect. The car test was better than the flash test in detecting RT prolongations (p = 0.030). IEA increased crashes/lapses >26% in sessions with generalized IEA with s/w. The frequency of IEA-associated RT >1 s exceeded predictions (p < 0.001) based on simple RT shift, suggesting functional impairment beyond progressive RT prolongation by IEA. The number of AEDs correlated with prolonged RTs during normal EEG (p < 0.021) but not with IEA-associated RT prolongation or crashes/lapses. SIGNIFICANCE IEA prolonged RTs to varying extents, dependent on IEA type. IEA-associated RTs >1 s were more frequent than predicted, suggesting beginning cerebral decompensation of visual stimulus processing. AEDs somewhat reduced psychomotor speed, but it was mainly the IEA that contributed to an excess of virtual accidents.

Modelling the dynamics of genetic algorithms using statistical mechanics

A formalism for modelling the dynamics of Genetic Algorithms (GAs) using methods from statistical mechanics, originally due to Prugel-Bennett and Shapiro, is reviewed, generalized and improved upon. This formalism can be used to predict the averaged trajectory of macroscopic statistics describing the GA's population. These macroscopics are chosen to average well between runs, so that fluctuations from mean behaviour can often be neglected. Where necessary, non-trivial terms are determined by assuming maximum entropy with constraints on known macroscopics. Problems of realistic size are described in compact form and finite population effects are included, often proving to be of fundamental importance. The macroscopics used here are cumulants of an appropriate quantity within the population and the mean correlation (Hamming distance) within the population. Including the correlation as an explicit macroscopic provides a significant improvement over the original formulation. The formalism is applied to a number of simple optimization problems in order to determine its predictive power and to gain insight into GA dynamics. Problems which are most amenable to analysis come from the class where alleles within the genotype contribute additively to the phenotype. This class can be treated with some generality, including problems with inhomogeneous contributions from each site, non-linear or noisy fitness measures, simple diploid representations and temporally varying fitness. The results can also be applied to a simple learning problem, generalization in a binary perceptron, and a limit is identified for which the optimal training batch size can be determined for this problem. The theory is compared to averaged results from a real GA in each case, showing excellent agreement if the maximum entropy principle holds. Some situations where this approximation brakes down are identified. In order to fully test the formalism, an attempt is made on the strong sc np-hard problem of storing random patterns in a binary perceptron. Here, the relationship between the genotype and phenotype (training error) is strongly non-linear. Mutation is modelled under the assumption that perceptron configurations are typical of perceptrons with a given training error. Unfortunately, this assumption does not provide a good approximation in general. It is conjectured that perceptron configurations would have to be constrained by other statistics in order to accurately model mutation for this problem. Issues arising from this study are discussed in conclusion and some possible areas of further research are outlined.

Abnormal visual habituation in pediatric photosensitive epilepsy

Objective - To investigate visual habituation – a measure of visual cortical excitability – in photosensitive patients in pediatric age and compare the findings with a matched sample with idiopathic generalized epilepsies without photosensitivity and with normally developing children. Methods - We presented a full-field black-and-white checkerboard pattern, at 3 reversal/s with 100% contrast binocularly for 600 consecutive trials and measured the N75–P100 and P100–N145 pattern-reversal visual evoked potential inter-peak amplitudes and N75, P100, N145 latencies for the six blocks of 100 responses. As a measure of habituation we used the slope of the linear regression line of the N75–P100 and P100–N145 peak-to-peak amplitudes. The slope of the linear regression line of the N75–P100 and P100–N145 latencies was also analyzed. Results - Statistical analysis revealed significant differences between the three groups in the slope index of N75–P100 PR-VEP amplitude, with increased or constant amplitude in the PS group compare to the IGE and ND across the six blocks. Conclusions - Our results support the notion that photosensitivity is associated with altered control of excitatory and inhibitory cortical processes. The causal relationship between habituation deficit and photo-paroxysmal response needs to be further investigated with longitudinal studies. Significance This study supports the hypothesis that suppression of PR-VEP is a sensitive intermediate phenotype, which discriminates patients with photosensitivity from those with generalized epilepsies in pediatric age.

A Metaheuristic Approach to Solving the Generalized Vertex Cover Problem

AMS Subj. Classification: 90C27, 05C85, 90C59