Neural Variability Quenching Predicts Individual Perceptual Abilities
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[1] Andrew M. Clark,et al. Stimulus onset quenches neural variability: a widespread cortical phenomenon , 2010, Nature Neuroscience.
[2] P. Rossini,et al. Pre- and poststimulus alpha rhythms are related to conscious visual perception: a high-resolution EEG study. , 2005, Cerebral cortex.
[3] F. L. D. Silva,et al. Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.
[4] D G Pelli,et al. Why use noise? , 1999, Journal of the Optical Society of America. A, Optics, image science, and vision.
[5] Arnaud Delorme,et al. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.
[6] Sygal Amitay,et al. Learning to detect a tone in unpredictable noise. , 2014, The Journal of the Acoustical Society of America.
[7] G. Deco,et al. Emerging concepts for the dynamical organization of resting-state activity in the brain , 2010, Nature Reviews Neuroscience.
[8] Keiichi Kitajo,et al. Internal noise determines external stochastic resonance in visual perception , 2008, Vision Research.
[9] F A Wichmann,et al. Ning for Helpful Comments and Suggestions. This Paper Benefited Con- Siderably from Conscientious Peer Review, and We Thank Our Reviewers the Psychometric Function: I. Fitting, Sampling, and Goodness of Fit , 2001 .
[10] J. Mumford,et al. Greater Neural Pattern Similarity Across Repetitions Is Associated with Better Memory , 2010, Science.
[11] Tatiana Pasternak,et al. Trial-to-trial variability of the prefrontal neurons reveals the nature of their engagement in a motion discrimination task , 2010, Proceedings of the National Academy of Sciences.
[12] G. Legge,et al. Contrast discrimination in noise. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[13] D H Brainard,et al. The Psychophysics Toolbox. , 1997, Spatial vision.
[14] Shahina Pardhan,et al. Contrast sensitivity loss with aging: sampling efficiency and equivalent noise at different spatial frequencies. , 2004, Journal of the Optical Society of America. A, Optics, image science, and vision.
[15] Lyle J. Graham,et al. Orientation and Direction Selectivity of Synaptic Inputs in Visual Cortical Neurons A Diversity of Combinations Produces Spike Tuning , 2003, Neuron.
[16] Nicholas J. Priebe,et al. The Emergence of Contrast-Invariant Orientation Tuning in Simple Cells of Cat Visual Cortex , 2007, Neuron.
[17] D. Moore,et al. Early and rapid perceptual learning , 2004, Nature Neuroscience.
[18] S. MacDonald,et al. Neuroscience and Biobehavioral Reviews Review Moment-to-moment Brain Signal Variability: a next Frontier in Human Brain Mapping? , 2022 .
[19] Eero P. Simoncelli,et al. Partitioning neuronal variability , 2014, Nature Neuroscience.
[20] S Makeig,et al. Blind separation of auditory event-related brain responses into independent components. , 1997, Proceedings of the National Academy of Sciences of the United States of America.
[21] Biyu J. He,et al. Average Is Optimal: An Inverted-U Relationship between Trial-to-Trial Brain Activity and Behavioral Performance , 2013, PLoS Comput. Biol..
[22] David J. Heeger,et al. Neural variability: friend or foe? , 2015, Trends in Cognitive Sciences.
[23] Stanislas Dehaene,et al. Cortical activity is more stable when sensory stimuli are consciously perceived , 2015, Proceedings of the National Academy of Sciences.
[24] Richard Coppola,et al. Reduced Variability of Ongoing and Evoked Cortical Activity Leads to Improved Behavioral Performance , 2012, PloS one.
[25] W. Newsome,et al. The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.
[26] A E Burgess,et al. Visual signal detection. IV. Observer inconsistency. , 1988, Journal of the Optical Society of America. A, Optics and image science.
[27] Biyu J. He. Spontaneous and Task-Evoked Brain Activity Negatively Interact , 2013, The Journal of Neuroscience.
[28] Klaus Linkenkaer-Hansen,et al. Dynamics of mu-rhythm suppression caused by median nerve stimulation: a magnetoencephalographic study in human subjects , 2000, Neuroscience Letters.
[29] Jonathan D. Cohen,et al. Reproducibility Distinguishes Conscious from Nonconscious Neural Representations , 2010, Science.
[30] C. Grady,et al. The modulation of BOLD variability between cognitive states varies by age and processing speed. , 2013, Cerebral cortex.
[31] D. M. Green,et al. Signal detection theory and psychophysics , 1966 .
[32] S. Luck,et al. The effects of electrode impedance on data quality and statistical significance in ERP recordings. , 2010, Psychophysiology.
[33] Zoltan Dienes,et al. Using Bayes to get the most out of non-significant results , 2014, Front. Psychol..
[34] Douglas D Garrett,et al. Brain signal variability is parametrically modifiable. , 2014, Cerebral cortex.
[35] W. Klimesch. Alpha-band oscillations, attention, and controlled access to stored information , 2012, Trends in Cognitive Sciences.
[36] M. Carandini. Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex , 2004, PLoS biology.
[37] J. Maunsell,et al. Attention improves performance primarily by reducing interneuronal correlations , 2009, Nature Neuroscience.
[38] Christos Constantinidis,et al. Variability of Prefrontal Neuronal Discharges before and after Training in a Working Memory Task , 2012, PloS one.
[39] H. Levitt. Transformed up-down methods in psychoacoustics. , 1971, The Journal of the Acoustical Society of America.
[40] Peter Neri,et al. How inherently noisy is human sensory processing? , 2010, Psychonomic bulletin & review.
[41] Emily Buss,et al. Psychometric functions for pure tone intensity discrimination: slope differences in school-aged children and adults. , 2009, The Journal of the Acoustical Society of America.
[42] John J. Foxe,et al. The Role of Alpha-Band Brain Oscillations as a Sensory Suppression Mechanism during Selective Attention , 2011, Front. Psychology.
[43] E. Wagenmakers,et al. How to quantify the evidence for the absence of a correlation , 2015, Behavior research methods.
[44] Gert Pfurtscheller,et al. The cortical activation model (CAM). , 2006, Progress in brain research.
[45] Jude F. Mitchell,et al. Differential Attention-Dependent Response Modulation across Cell Classes in Macaque Visual Area V4 , 2007, Neuron.
[46] Anthony R. McIntosh,et al. Functional Embedding Predicts the Variability of Neural Activity , 2011, Front. Syst. Neurosci..
[47] C. Grady,et al. The Importance of Being Variable , 2011, The Journal of Neuroscience.
[48] A. Pouget,et al. Variance as a Signature of Neural Computations during Decision Making , 2011, Neuron.
[49] A. Stancák,et al. Desynchronization of cortical rhythms following cutaneous stimulation: effects of stimulus repetition and intensity, and of the size of corpus callosum , 2003, Clinical Neurophysiology.
[50] A. Grinvald,et al. Dynamics of Ongoing Activity: Explanation of the Large Variability in Evoked Cortical Responses , 1996, Science.