Authors: Babak Shahbaba, Bo Zhou, Shiwei Lan, Hernando Ombao, David Moorman, Sam Behseta
arXiv
We propose a scalable semiparametric Bayesian model to capture dependencies among multiple neurons by detecting their co-firing (possibly with some lag time) patterns over time. After discretizing tim...
Authors: Ru Zhang, Ehtibar N. Dzhafarov
arXiv
We present a general theory of series-parallel mental architectures with selectively influenced stochastically non-independent components. A mental architecture is a hypothetical network of processes...
Authors: M. Hinne, T. Heskes, M. A. J. van Gerven
arXiv
In structural brain networks the connections of interest consist of white-matter fibre bundles between spatially segregated brain regions. The presence, location and orientation of these white matter...
Authors: Stanley E. Lazic
arXiv
The aim of this study was to estimate the number of new cells and neurons added to the dentate gyrus across the lifespan, and to compare the rate of age-associated decline in neurogenesis across speci...
Authors: PierGianLuca Porta Mana, Claudia Bachmann, Abigail Morrison
arXiv
Automated classification methods for disease diagnosis are currently in the limelight, especially for imaging data. Classification does not fully meet a clinician's needs, however: in order to combine...
Authors: Martin Dyrba, Reza Mohammadi, Michel J. Grothe, Thomas Kirste, Stefan J. Teipel
arXiv
Alzheimer's disease (AD) is characterized by a sequence of pathological changes, which are commonly assessed in vivo using MRI and PET. Currently, the most approaches to analyze statistical associatio...
Authors: Guillermo Gallardo, William Wells, Rachid Deriche, Demian Wassermann
arXiv
Current theories hold that brain function is highly related to long-range physical connections through axonal bundles, namely extrinsic connectiv-ity. However, obtaining a groupwise cortical parcellat...
Authors: Daniel Mirman, Jon-Frederick Landrigan, Spiro Kokolis, Sean Verillo, Casey Ferrara, Dorian Pustina
arXiv
Voxel-based lesion-symptom mapping (VLSM) is an important method for basic and translational human neuroscience research. VLSM leverages modern neuroimaging analysis techniques to build on the classic...
Authors: Zhe Wang, Yu Zheng, David C. Zhu, Jian Ren, Tongtong Li
arXiv
This paper explores the discrete Dynamic Causal Modeling (DDCM) and its relationship with Directed Information (DI). We prove the conditional equivalence between DDCM and DI in characterizing the caus...
Authors: Matthias KĂŒmmerer, Thomas S. A. Wallis, Matthias Bethge
arXiv
Here we present DeepGaze II, a model that predicts where people look in images. The model uses the features from the VGG-19 deep neural network trained to identify objects in images. Contrary to other...
Authors: Johannes Friedrich, Pengcheng Zhou, Liam Paninski
arXiv
Fluorescent calcium indicators are a popular means for observing the spiking activity of large neuronal populations, but extracting the activity of each neuron from raw fluorescence calcium imaging da...
Authors: Zhana Kuncheva, Michelle L. Krishnan, Giovanni Montana
arXiv
Characterizing the transcriptome architecture of the human brain is fundamental in gaining an understanding of brain function and disease. A number of recent studies have investigated patterns of brai...
Authors: Camilo Lamus, Matti S. HÀmÀlÀinen, Simona Temereanca, Emery N. Brown, Patrick L. Purdon
arXiv
MEG/EEG are non-invasive imaging techniques that record brain activity with high temporal resolution. However, estimation of brain source currents from surface recordings requires solving an ill-posed...
Authors: Amanmeet Garg, Donghuan Lu, Karteek Popuri, Mirza Faisal Beg
arXiv
Neurodegeneration affects cortical gray matter leading to loss of cortical mantle volume. As a result of such volume loss, the geometrical arrangement of the regions on the cortical surface is expecte...
Authors: Mainak Jas, Tom DuprĂ© La Tour, Umut ĆimĆekli, Alexandre Gramfort
arXiv
Neural time-series data contain a wide variety of prototypical signal waveforms (atoms) that are of significant importance in clinical and cognitive research. One of the goals for analyzing such data...