TITLE

Using competitive layer model implemented by Lotka-Volterra recurrent neural networks for detecting brain activated regions from fMRI data

AUTHOR(S)
Zheng, Bochuan; Yi, Zhang
PUB. DATE
May 2013
SOURCE
Neural Computing & Applications;May2013 Supplement, Vol. 22, p395
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
The competitive layer model (CLM) implemented by the Lotka-Volterra recurrent neural networks (LV RNNs) is prominently characterized by its capability of binding neurons with similar feature into the same layer by competing among neurons at different layers in a column. This paper proposes to use the CLM of the LV RNN for detecting brain activated regions from the fMRI data. The correlated voxels from brain fMRI data can be obtained, and the clusters from fMRI time series can be uncovered. Experiments on synthetic and real fMRI data demonstrate the effectiveness of binding activated voxels into the 'active' layers of the CLM. The activated voxels can be detected more accurately than some existing methods by the proposed method.
ACCESSION #
87661106

 

Related Articles

  • Identifying Neural Drivers with Functional MRI: An Electrophysiological Validation. David, Olivier; Guillemain, Isabelle; Saillet, Sandrine; Reyt, Sebastien; Deransart, Colin; Segebarth, Christoph; Depaulis, Antoine // PLoS Biology;Dec2008, Vol. 6 Issue 12, pe315 

    Neural long-range interactions can be distinguished from hemodynamic confounds in functional magnetic resonance imaging using new data analysis techniques that will allow experimental validation of models of brain function.

  • Brain imaging: fMRI 2.0. Smith, Kerri // Nature;4/5/2012, Vol. 484 Issue 7392, p24 

    The article offers information on the growing trend for the use of functional magnetic resonance imaging (fMRI) as proxy for measuring neurons activity. It mentions that a more detailed model of the brain's organization, function, and networks was being planned to be created by neuroscientists...

  • Almost Periodic Solution for a Lotka-Volterra Recurrent Neural Networks with Harvesting Terms on Time Scales. Li Yang; Yonghong Yang; Yaqin Li; Tianwei Zhang // Engineering Letters;Dec2016, Vol. 24 Issue 4, p455 

    By using the theory of exponential dichotomy and Banach fixed point theorem, this paper is concerned with the problem of the existence and uniqueness of almost periodic solution in a harvesting Lotka-Volterra recurrent neural networks on time scales. To a certain extent, our work in this paper...

  • A Survey of the Sources of Noise in fMRI. Greve, Douglas; Brown, Gregory; Mueller, Bryon; Glover, Gary; Liu, Thomas // Psychometrika;Jul2013, Vol. 78 Issue 3, p396 

    Functional magnetic resonance imaging (fMRI) is a noninvasive method for measuring brain function by correlating temporal changes in local cerebral blood oxygenation with behavioral measures. fMRI is used to study individuals at single time points, across multiple time points (with or without...

  • The ''Parahippocampal Place Area'' Responds Preferentially to High Spatial Frequencies in Humans and Monkeys. Rajimehr, Reza; Devaney, Kathryn J.; Bilenko, Natalia Y.; Young, Jeremy C.; Tootell, Roger B. H. // PLoS Biology;Apr2011, Vol. 9 Issue 4, p1 

    Defining the exact mechanisms by which the brain processes visual objects and scenes remains an unresolved challenge. Valuable clues to this process have emerged from the demonstration that clusters of neurons (''modules'') in inferior temporal cortex apparently respond selectively to specific...

  • Estimating neural response functions from fMRI. Kumar, Sukhbinder; Penny, William // Frontiers in Neuroinformatics;May2014, Vol. 8, p1 

    This paper proposes a methodology for estimating Neural Response Functions (NRFs) from fMRI data. These NRFs describe non-linear relationships between experimental stimuli and neuronal population responses. The method is based on a two-stage model comprising an NRF and a Hemodynamic Response...

  • Analyzing the resting state functional connectivity in the human language system using near infrared spectroscopy. Molavi, Behnam; May, Lillian; Gervain, Judit; Carreiras, Manuel; Werker, Janet F.; Dumont, Guy A. // Frontiers in Human Neuroscience;Jan2014, Vol. 8, p1 

    We have evaluated the use of phase synchronization to identify resting state functional connectivity (RSFC) in the language system in infants using functional near infrared spectroscopy (fNIRS). We used joint probability distribution of phase between fNIRS channels with a seed channel in the...

  • Transcranial magnetic stimulation assisted by neuronavigation of magnetic resonance images. Viesca, N. Angeline; Alcauter, S. Sarael; Barrios, A. Fernando; González, O. Jorge J.; Márquez, F. Jorge A. // AIP Conference Proceedings;Oct2012, Vol. 1494 Issue 1, p91 

    Technological advance has improved the way scientists and doctors can learn about the brain and treat different disorders. A non-invasive method used for this is Transcranial Magnetic Stimulation (TMS) based on neuron excitation by electromagnetic induction. Combining this method with functional...

  • Neural correlates of mindfulness meditation-related anxiety relief. Zeidan, Fadel; Martucci, Katherine T.; Kraft, Robert A.; McHaffie, John G.; Coghill, Robert C. // Social Cognitive & Affective Neuroscience;Jun2014, Vol. 9 Issue 6, p751 

    Anxiety is the cognitive state related to the inability to control emotional responses to perceived threats. Anxiety is inversely related to brain activity associated with the cognitive regulation of emotions. Mindfulness meditation has been found to regulate anxiety. However, the brain...

Share

Read the Article

Courtesy of VIRGINIA BEACH PUBLIC LIBRARY AND SYSTEM

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics