Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Medicine and Health Sciences (3)
- Molecular and Cellular Neuroscience (2)
- Social and Behavioral Sciences (2)
- Anatomy (1)
- Applied Behavior Analysis (1)
-
- Applied Mathematics (1)
- Artificial Intelligence and Robotics (1)
- Astrophysics and Astronomy (1)
- Biochemistry, Biophysics, and Structural Biology (1)
- Bioinformatics (1)
- Biological Psychology (1)
- Biomechanics (1)
- Biometry (1)
- Biostatistics (1)
- Categorical Data Analysis (1)
- Cognition and Perception (1)
- Cognitive Neuroscience (1)
- Cognitive Psychology (1)
- Computational Biology (1)
- Computational Engineering (1)
- Computational Linguistics (1)
- Computer Engineering (1)
- Computer Sciences (1)
- Computer and Systems Architecture (1)
- Data Storage Systems (1)
- Digital Circuits (1)
- Discourse and Text Linguistics (1)
- Institution
- Keyword
-
- AI (1)
- AIS plasticity (1)
- Abstraction (1)
- Action potential (1)
- Aesthetics (1)
-
- Affective Computing (1)
- Artificial Intelligence (1)
- Axon (1)
- Axon initial segment (1)
- Bioinformatics (1)
- Biomedical signal processing (1)
- Brain (1)
- Computer Architecture (1)
- Data collection (1)
- Datasets as topic (1)
- Dendrite (1)
- Emotion (1)
- High dimensional data (1)
- High-performance computing (1)
- High-throughput genomics (1)
- Humans (1)
- Large-scale biological data analysis (1)
- Logic (1)
- Magnetic resonance imaging (1)
- Message-passing interface (1)
- Morality (1)
- Neural Networks (1)
- Neuroimaging (1)
- Neurology (1)
- Non-negative matrix factorization (1)
Articles 1 - 4 of 4
Full-Text Articles in Computational Neuroscience
The Brain Imaging Data Structure, A Format For Organizing And Describing Outputs Of Neuroimaging Experiments, Krzysztof Gorgolewski, Tibor Auer, Vince Calhoun, R Cameron Craddock, Samir Das, Eugene Duff, Guillaume Flandin, Tristan Glatard, Yaroslav Halchenko
The Brain Imaging Data Structure, A Format For Organizing And Describing Outputs Of Neuroimaging Experiments, Krzysztof Gorgolewski, Tibor Auer, Vince Calhoun, R Cameron Craddock, Samir Das, Eugene Duff, Guillaume Flandin, Tristan Glatard, Yaroslav Halchenko
Dartmouth Scholarship
The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this …
“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams
“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams
Senior Honors Theses
Alan Turing asked if machines can think, but intelligence is more than logic and reason. I ask if a machine can feel pain or joy, have visions and dreams, or paint a masterpiece. The human brain sets the bar high, and despite our progress, artificial intelligence has a long way to go. Studying neurology from a software engineer’s perspective reveals numerous uncanny similarities between the functionality of the brain and that of a computer. If the brain is a biological computer, then it is the embodiment of artificial intelligence beyond anything we have yet achieved, and its architecture is advanced …
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
COBRA Preprint Series
Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …
Neuron Morphology Influences Axon Initial Segment Plasticity, Allan T. Gulledge, Jaime J. Bravo
Neuron Morphology Influences Axon Initial Segment Plasticity, Allan T. Gulledge, Jaime J. Bravo
Dartmouth Scholarship
In most vertebrate neurons, action potentials are initiated in the axon initial segment (AIS), a specialized region of the axon containing a high density of voltage-gated sodium and potassium channels. It has recently been proposed that neurons use plasticity of AIS length and/or location to regulate their intrinsic excitability. Here we quantify the impact of neuron morphology on AIS plasticity using computational models of simplified and realistic somatodendritic morphologies. In small neurons (e.g., dentate granule neurons), excitability was highest when the AIS was of intermediate length and located adjacent to the soma. Conversely, neurons having larger dendritic trees (e.g., pyramidal …