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Alzheimer's Disease (AD) shows both complex alterations of functional dependencies between brain regions and a decreased ability to perform Visual Short-Term Memory Binding (VSTMB) tasks. Recent advances in network neuroscience toward understanding the complexity of hierarchical brain function here enables us to establish a link between these two phenomena. Here, we study data on two types of dementia at Mild Cognitive Impairment (MCI) stage—familial AD patients (E280A mutation of the presenilin-1 gene) and elderly MCI patients at high risk of sporadic AD, both with age-matched controls. We analyzed Electroencephalogram (EEG) signals recorded during the performance of Visual Short-Term Memory (VSTM) tasks by these participants. Functional connectivity was computed using the phase-lag index in Alpha and Beta; and network analysis was employed using network indices of hierarchical spread (degree variance) and complexity. Hierarchical characteristics of EEG functional connectivity networks revealed abnormal patterns in familial MCI VSTMB function and sporadic MCI VSTMB function. The middle-aged familial MCI binding network displayed a larger degree variance in lower Beta compared to healthy controls (p = 0.0051, Cohen's d = 1.0124), while the elderly sporadic MCI binding network displayed greater hierarchical complexity in Alpha (p = 0.0140, Cohen's d = 1.1627). Characteristics in healthy aging were not shown to differ. These results indicate that activity in MCI exhibits cross-frequency network reorganization characterized by increased heterogeneity of node roles in the functional hierarchy. Aging itself is not found to cause VSTM functional hierarchy differences.

Additional description of protocols, tests as well as analysis and results

En este proyecto se va a optimizar el recorrido de un grafo ponderado mediante la aplicación del algoritmo A*. Este es un algoritmo que, además de los pesos de las aristas, evalúa una heurística en cada nodo para determinar si el camino está avanzando por el recorrido óptimo. Se va a utilizar una porción del plano de Metro de Madrid para realizar la aplicación del algoritmo.--ABSTRACT--In this project we will try and optimize the path-finding in a weighted graph by means of the A*(a star) algorithm. This algorithm works with each node’s heuristic apart from the edge’s weight itself to determine if the path is going through the optimal route. A fraction of the Metro Madrid’s subway map will serve as an example for this application of the algorithm.

Supplemental material, MSJ888881_supplemental_material for Fatigue in multiple sclerosis is associated with multimodal interoceptive abnormalities by Cecilia Gonzalez Campo, Paula C Salamone, Nicolás Rodríguez-Arriagada, Fabian Richter, Eduar Herrera, Diana Bruno, Fátima Pagani Cassara, Vladimiro Sinay, Adolfo M García, Agustín Ibáñez and Lucas Sedeño in Multiple Sclerosis Journal

A 109/103(2)

A 109/103(4)