Measuring ensemble interdependence in a string quartet through analysis of multidimensional performance data.

In a musical ensemble such as a string quartet, the musicians interact and influence each other's actions in several aspects of the performance simultaneously in order to achieve a common aesthetic goal. In this article, we present and evaluate a computational approach for measuring the degree to which these interactions exist in a given performance. We recorded a number of string quartet exercises under two experimental conditions (solo and ensemble), acquiring both audio and bowing motion data. Numerical features in the form of time series were extracted from the data as performance descriptors representative of four distinct dimensions of the performance: Intonation, Dynamics, Timbre, and Tempo. Four different interdependence estimation methods (two linear and two nonlinear) were applied to the extracted features in order to assess the overall level of interdependence between the four musicians. The obtained results suggest that it is possible to correctly discriminate between the two experimental conditions by quantifying interdependence between the musicians in each of the studied performance dimensions; the nonlinear methods appear to perform best for most of the numerical features tested. Moreover, by using the solo recordings as a reference to which the ensemble recordings are contrasted, it is feasible to compare the amount of interdependence that is established between the musicians in a given performance dimension across all exercises, and relate the results to the underlying goal of the exercise. We discuss our findings in the context of ensemble performance research, the current limitations of our approach, and the ways in which it can be expanded and consolidated.

Low penetrance of autosomal dominant lateral temporal epilepsy in Italian families without LGI1 mutations.

PURPOSE: In relatively small series, autosomal dominant lateral temporal epilepsy (ADLTE) has been associated with leucine-rich, glioma-inactivated 1 (LGI1) mutations in about 50% of the families, this genetic heterogeneity being probably caused by differences in the clinical characteristics of the families. In this article we report the overall clinical and genetic spectrum of ADLTE in Italy with the aim to provide new insight into its nosology and genetic basis. METHODS: In a collaborative study of the Commission of Genetics of the Italian League Against Epilepsy (LICE) encompassing a 10-year period (2000-2010), we collected 33 ADLTE families, selected on the basis of the following criteria: presence of at least two members concordant for unprovoked partial seizures with prominent auditory and or aphasic symptoms, absence of any known structural brain pathology or etiology, and normal neurologic examination. The clinical, neurophysiologic, and neuroradiologic findings of all patients were analyzed and a genealogic tree was built for each pedigree. The probands' DNA was tested for LGI1 mutations by direct sequencing and, if negative, were genotyped with single-nucleotide polymorphism (SNP) array to search for disease-linked copy-number variation CNV. The disease penetrance in mutated and nonmutated families was assessed as a proportion of obligate carriers who were affected. KEY FINDINGS: The 33 families included a total of 127 affected individuals (61 male, 66 female, 22 deceased). The age at onset ranged between 2 and 60 years (mean 18.7 years). Ninety-one patients (72%) had clear-cut focal (elementary, complex, or secondarily generalized) seizures, characterized by prominent auditory auras in 68% of the cases. Other symptoms included complex visual hallucinations, vertigo, and déjà vu. Aphasic seizures, associated or not with auditory features, were observed in 20% of the cases, whereas tonic-clonic seizures occurred in 86% of the overall series. Sudden noises could precipitate the seizures in about 20% of cases. Seizures, which usually occurred at a low frequency, were promptly controlled or markedly improved by antiepileptic treatment in the majority of patients. The interictal electroencephalography (EEG) studies showed the epileptiform temporal abnormalities in 62% of cases, with a slight predominance over the left region. Magnetic resonance imaging (MRI) or computerized tomography (CT) scans were negative. LGI1 mutations (missense in nine and a microdeletion in one) were found in only 10 families (30%). The patients belonging to the mutated and not mutated groups did not differ except for penetrance estimate, which was 61.3% and 35% in the two groups, respectively (chi-square, p = 0.017). In addition, the disease risk of members of families with mutations in LGI1 was three times higher than that of members of LGI1-negative families (odds ratio [OR] 2.94, confidence interval [CI] 1.2-7.21). SIGNIFICANCE: A large number of ADLTE families has been collected over a 10-year period in Italy, showing a typical and homogeneous phenotype. LGI1 mutations have been found in only one third of families, clinically indistinguishable from nonmutated pedigrees. The estimate of penetrance and OR, however, demonstrates a significantly lower penetrance rate and relative disease risk in non-LGI1-mutated families compared with LGI1-mutated pedigrees, suggesting that a complex inheritance pattern may underlie a proportion of these families.

Association of intronic variants of the KCNAB1 gene with lateral temporal epilepsy.

The KCNAB1 gene is a candidate susceptibility factor for lateral temporal epilepsy (LTE) because of its functional interaction with LGI1, the gene responsible for the autosomal dominant form of LTE. We investigated association between polymorphic variants across the KCNAB1 gene and LTE. The allele and genotype frequencies of 14 KCNAB1 intronic SNPs were determined in 142 Italian LTE patients and 104 healthy controls and statistically evaluated. Single SNP analysis revealed one SNP (rs992353) located near the 3'end of KCNAB1 slightly associated with LTE after multiple testing correction (odds ratio=2.25; 95% confidence interval 1.26-4.04; P=0.0058). Haplotype analysis revealed two haplotypes with frequencies higher in cases than in controls, and these differences were statistically significant after permutation tests (Psim=0.047 and 0.034). One of these haplotypes was shown to confer a high risk for the syndrome (odds ratio=12.24; 95% confidence interval 1.32-113.05) by logistic regression analysis. These results support KCNAB1 as a susceptibility gene for LTE, in agreement with previous studies showing that this gene may alter susceptibility to focal epilepsy.