1.1k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National Institutes of HealthUS16 papers
- Massachusetts Institute of TechnologyUS8 papers
- Czech Academy of Sciences, Institute of Computer ScienceCZ6 papers
- University of CambridgeGB6 papers
- University of OxfordGB5 papers
- University College LondonGB4 papers
- Bernstein Center for Computational Neuroscience BerlinDE3 papers
- Charité - Universitätsmedizin BerlinDE3 papers
- Columbia UniversityUS3 papers
- Czech Academy of SciencesCZ3 papers
- Georgia Institute of TechnologyUS3 papers
- Harvard UniversityUS3 papers
44 papers
Characterizing Timing Parameters in Commercial SERF-OPM Multichannel Systems for Biomagnetic Field Sensing
Eric Elzenheimer, Hartmut Matz, Jan Zerfowski +6
Spin-Exchange Relaxation-Free Optically Pumped Magnetometers (SERF-OPMs) are increasingly used in multichannel biomagnetic sensing, yet their timing performance remains poorly char…
Murine AI excels at cats and cheese: Structural differences between human and mouse neurons and their implementation in generative AIs
Rino Saiga, Kaede Shiga, Yo Maruta +19
Mouse and human brains have different functions that depend on their neuronal networks. In this study, we analyzed nanometer-scale three-dimensional structures of brain tissues of…
Processing, evaluating and understanding FMRI data with afni_proc.py
Richard C. Reynolds, Daniel R. Glen, Gang Chen +3
FMRI data are noisy, complicated to acquire, and typically go through many steps of processing before they are used in a study or clinical practice. Being able to visualize and und…
Reliability and predictability of phenotype information from functional connectivity in large imaging datasets
Jessica Dafflon, Dustin Moraczewski, Eric Earl +5
One of the central objectives of contemporary neuroimaging research is to create predictive models that can disentangle the connection between patterns of functional connectivity a…
A sensitivity analysis to quantify the impact of neuroimaging preprocessing strategies on subsequent statistical analyses
Brice Ozenne, Martin Norgaard, Cyril Pernet +1
Even though novel imaging techniques have been successful in studying brain structure and function, the measured biological signals are often contaminated by multiple sources of no…
Large language models surpass human experts in predicting neuroscience results
Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun +36
Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offe…
ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms
Daniel Levitas, Soichi Hayashi, Sophia Vinci-Booher +6
Data standardization has become one of the leading methods neuroimaging researchers rely on for data sharing and reproducibility. Data standardization promotes a common framework t…
On the Emergent "Quantum" Theory in Complex Adaptive Systems
Tristan Hubsch, Djordje Minic, Konstantin Nikolic +1
We explore the concept of emergent quantum-like theory in complex adaptive systems, and examine in particular the concrete example of such an emergent (or "mock") quantum theory in…
The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…
In Vivo Magnetic Resonance Spectroscopy by J-Locked Chemical Shift Encoding for Determination of Neurochemical Concentration and Transverse Relaxation Time
Li An, Jun Shen
Cell pathology in neuropsychiatric disorders has mainly been accessible by analyzing postmortem tissue samples. Although molecular transverse relaxation informs local cellular micr…
Mixture Components Inference for Sparse Regression: Introduction and Application for Estimation of Neuronal Signal from fMRI BOLD
Anna Pidnebesna, Iveta Fajnerova, Jiri Horacek +1
Sparse linear regression methods including the well-known LASSO and the Dantzig selector have become ubiquitous in the engineering practice, including in medical imaging. Among oth…
The positive-negative mode link between brain connectivity, demographics, and behavior: A pre-registered replication of Smith et al. 2015
Nikhil Goyal1, Dustin Moraczewski, Peter A. Bandettini +2
In mental health research, it has proven difficult to find measures of brain function that provide reliable indicators of mental health and well-being, including susceptibility to…
Neuromatch Academy: Teaching Computational Neuroscience with global accessibility
Tara van Viegen, Athena Akrami, Kate Bonnen +32
Neuromatch Academy designed and ran a fully online 3-week Computational Neuroscience summer school for 1757 students with 191 teaching assistants working in virtual inverted (or fl…
Quasiconformal model with CNN features for large deformation image registration
Ho Law, Gary P. T. Choi, Ka Chun Lam +1
Image registration has been widely studied over the past several decades, with numerous applications in science, engineering and medicine. Most of the conventional mathematical mod…
FitzHugh-Nagumo oscillators on complex networks mimic epileptic-seizure-related synchronization phenomena
M. Gerster, R. Berner, J. Sawicki +5
We study patterns of partial synchronization in a network of FitzHugh-Nagumo oscillators with empirical structural connectivity measured in human subjects. We report the spontaneou…
Permutation Inference for Canonical Correlation Analysis
Anderson M. Winkler, Olivier Renaud, Stephen M. Smith +1
Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements. As…
Quantum Computing at the Frontiers of Biological Sciences
Prashant S. Emani, Jonathan Warrell, Alan Anticevic +15
The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we pus…
Partial synchronization in empirical brain networks as a model for unihemispheric sleep
Lukas Ramlow, Jakub Sawicki, Anna Zakharova +3
We analyze partial synchronization patterns in a network of FitzHugh-Nagumo oscillators with empirical structural connectivity measured in healthy human subjects. We report a dynam…
Knowing what you know in brain segmentation using Bayesian deep neural networks
Patrick McClure, Nao Rho, John A. Lee +7
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours. The network was tra…
Distributed Weight Consolidation: A Brain Segmentation Case Study
Patrick McClure, Charles Y. Zheng, Jakub R. Kaczmarzyk +5
Collecting the large datasets needed to train deep neural networks can be very difficult, particularly for the many applications for which sharing and pooling data is complicated b…
Causal network discovery by iterative conditioning: comparison of algorithms
Jakub Kořenek, Jaroslav Hlinka
Estimating causal interactions in complex dynamical systems is an important problem encountered in many fields of current science. While a theoretical solution for detecting the ca…
Effect of time of day on reward circuitry. A discussion of Byrne et al. 2017
Adam Steel, Cibu Thomas, Chris I Baker
Byrne and colleagues present a paper on a timely topic with potentially important results. However, we think that issues in the design and analysis complicate the interpretation an…
Extrapolating Expected Accuracies for Large Multi-Class Problems
Charles Zheng, Rakesh Achanta, Yuval Benjamini
The difficulty of multi-class classification generally increases with the number of classes. Using data from a subset of the classes, can we predict how well a classifier will scal…
Chimera states in brain networks: empirical neural vs. modular fractal connectivity
Teresa Chouzouris, Iryna Omelchenko, Anna Zakharova +3
Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay…