Effective connectivity among the working memory regions during preparation for and during performance of the n-back task

Recent neuroimaging studies have shown that working memory (WM) task difficulty can be decoded from patterns of brain activation in the WM network during preparation to perform those tasks. The inter-regional connectivity among the WM regions during task preparation has not yet been investigated. We examined this question using the graph modeling methods IMaGES and LOFS, applied to the previously published fMRI data of Manelis and Reder (2013). In that study, subjects performed 1-, 2-, and 3-back tasks. Each block of n-back was preceded by a preparation period and followed by a rest period. The analyses of task-related brain activity identified a network of 18 regions that increased in activation from 1to 3-back (Increase network) and a network of 17 regions that decreased in activation from 1to 3-back (Decrease network). The graph analyses revealed two types of connectivity sub-networks within the Increase and Decrease networks: "default" and "preparation-related." The "default" connectivity was present not only during task performance, but also during task preparation and during rest. We propose that this sub-network may serve as a core system that allows one to quickly activate cognitive, perceptual and motor systems in response to the relevant stimuli. The "preparation-related" connectivity was present during task preparation and task performance, but not at rest, and depended on the n-back condition. The role of this sub-network may be to pre-activate a connectivity "road map" in order to establish a top-down and bottom-up regulation of attention prior to performance on WM tasks. © 2014 Manelis and Reder

White matter abnormalities in adults with bipolar disorder type-II and unipolar depression

Discerning distinct neurobiological characteristics of related mood disorders such as bipolar disorder type-II (BD-II) and unipolar depression (UD) is challenging due to overlapping symptoms and patterns of disruption in brain regions. More than 60% of individuals with UD experience subthreshold hypomanic symptoms such as elevated mood, irritability, and increased activity. Previous studies linked bipolar disorder to widespread white matter abnormalities. However, no published work has compared white matter microstructure in individuals with BD-II vs. UD vs. healthy controls (HC), or examined the relationship between spectrum (dimensional) measures of hypomania and white matter microstructure across those individuals. This study aimed to examine fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and mean diffusivity (MD) across BD-II, UD, and HC groups in the white matter tracts identified by the XTRACT tool in FSL. Individuals with BD-II (n = 18), UD (n = 23), and HC (n = 24) underwent Diffusion Weighted Imaging. The categorical approach revealed decreased FA and increased RD in BD-II and UD vs. HC across multiple tracts. While BD-II had significantly lower FA and higher RD values than UD in the anterior part of the left arcuate fasciculus, UD had significantly lower FA and higher RD values than BD-II in the area of intersections between the right arcuate, inferior fronto-occipital and uncinate fasciculi and forceps minor. The dimensional approach revealed the depression-by-spectrum mania interaction effect on the FA, RD, and AD values in the area of intersection between the right posterior arcuate and middle longitudinal fasciculi. We propose that the white matter microstructure in these tracts reflects a unique pathophysiologic signature and compensatory mechanisms distinguishing BD-II from UD

Connectomic markers of disease expression, genetic risk and resilience in bipolar disorder.

Bipolar disorder (BD) is characterized by emotional dysregulation and cognitive deficits associated with abnormal connectivity between subcortical-primarily emotional processing regions-and prefrontal regulatory areas. Given the significant contribution of genetic factors to BD, studies in unaffected first-degree relatives can identify neural mechanisms of genetic risk but also resilience, thus paving the way for preventive interventions. Dynamic causal modeling (DCM) and random-effects Bayesian model selection were used to define and assess connectomic phenotypes linked to facial affect processing and working memory in a demographically matched sample of first-degree relatives carefully selected for resilience (n=25), euthymic patients with BD (n=41) and unrelated healthy controls (n=46). During facial affect processing, patients and relatives showed similarly increased frontolimbic connectivity; resilient relatives, however, evidenced additional adaptive hyperconnectivity within the ventral visual stream. During working memory processing, patients displayed widespread hypoconnectivity within the corresponding network. In contrast, working memory network connectivity in resilient relatives was comparable to that of controls. Our results indicate that frontolimbic dysfunction during affect processing could represent a marker of genetic risk to BD, and diffuse hypoconnectivity within the working memory network a marker of disease expression. The association of hyperconnectivity within the affect-processing network with resilience to BD suggests adaptive plasticity that allows for compensatory changes and encourages further investigation of this phenotype in genetic and early intervention studies

What is behind a summary-evaluation decision?

Research in psychology has reported that, among the variety of possibilities for assessment methodologies, summary evaluation offers a particularly adequate context for inferring text comprehension and topic understanding. However, grades obtained in this methodology are hard to quantify objectively. Therefore, we carried out an empirical study to analyze the decisions underlying human summary-grading behavior. The task consisted of expert evaluation of summaries produced in critically relevant contexts of summarization development, and the resulting data were modeled by means of Bayesian networks using an application called Elvira, which allows for graphically observing the predictive power (if any) of the resultant variables. Thus, in this article, we analyzed summary-evaluation decision making in a computational framewor

Judith A. Manelis papers, 1986-1990

The collection contains the papers of Judith A. Manelis, the Executive Director of the Communications Department of the United Jewish Appeal-Federation of New York. The papers pertain to the UJA-Federation Campaign for Soviet Jewish Emigres. The materials include ads, mailings, news releases, position papers, stationery, a button, and a poster.The collection consists of one folder and one oversize folder.Published citations should take the following form: Identification of item, date (if known); Judith A. Manelis Papers; *P-970 ; box number; folder number; American Jewish Historical Society, Boston, MA and New York, NY.Judith ManelisJudith A. Manelis served as the Executive Director of the Communications Department of the United Jewish Appeal--Federation of Jewish Philanthropies of New York during 1986-1990.Judith A. Manelis,Judith ManelisFinding Aid available in Reading Room and on Internet.far0315digitized2008071

High-precision estimation of the time of arrival of radio signals

An interpolation algorithm of high-precision estimation of the time of arrival of radio signals has been proposed. Analytical expressions were obtained for specifications of the algorithm that were corroborated by the results of computer simulation. It was shown that with due regard for the complexity adequate to a receiver of the maximum likelihood estimation of the temporal position with quantized output, the proposed interpolation algorithm ensures the noise immunity close to potentially attainable. The performed analysis makes it possible to select parameters of the estimation algorithm in a reasonable way depending on the requirements to its accuracy and complexity of realization