Decoding visual information from high-density diffuse optical tomography neuroimaging data

[1]  Heather M Lugar,et al.  Global motion detection and censoring in high‐density diffuse optical tomography , 2020, Human brain mapping.

[2]  Adam T. Eggebrecht,et al.  Global Motion Detection and Censoring in High-Density Diffuse Optical Tomography , 2020, bioRxiv.

[3]  Ali R. Khan,et al.  Assessing Time-Resolved fNIRS for Brain-Computer Interface Applications of Mental Communication , 2020, Frontiers in Neuroscience.

[4]  Adam T. Eggebrecht,et al.  Portable, field-based neuroimaging using high-density diffuse optical tomography , 2020, NeuroImage.

[5]  Andrew K. Fishell,et al.  Mapping brain function during naturalistic viewing using high-density diffuse optical tomography , 2019, Scientific Reports.

[6]  Edward F. Chang,et al.  Speech synthesis from neural decoding of spoken sentences , 2019, Nature.

[7]  Katrin Krumbholz,et al.  Is Human Auditory Cortex Organization Compatible With the Monkey Model? Contrary Evidence From Ultra-High-Field Functional and Structural MRI , 2018, Cerebral cortex.

[8]  J. Hirsch,et al.  The present and future use of functional near‐infrared spectroscopy (fNIRS) for cognitive neuroscience , 2018, Annals of the New York Academy of Sciences.

[9]  Hamid Dehghani,et al.  Lightweight sCMOS-based high-density diffuse optical tomography , 2018, Neurophotonics.

[10]  Damien A. Fair,et al.  Behavioral interventions for reducing head motion during MRI scans in children , 2018, NeuroImage.

[11]  Vinoo Alluri,et al.  Identifying musical pieces from fMRI data using encoding and decoding models , 2018, Scientific Reports.

[12]  Robert J Cooper,et al.  Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system , 2017, Neurophotonics.

[13]  Chris I. Baker,et al.  Deconstructing multivariate decoding for the study of brain function , 2017, NeuroImage.

[14]  Yizhen Zhang,et al.  Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision , 2016, Cerebral cortex.

[15]  Androu Abdalmalak,et al.  Single-session communication with a locked-in patient by functional near-infrared spectroscopy , 2017, Neurophotonics.

[16]  Evan M. Gordon,et al.  Precision Functional Mapping of Individual Human Brains , 2017, Neuron.

[17]  Richard N. Aslin,et al.  Decoding the infant mind: Multivariate pattern analysis (MVPA) using fNIRS , 2017, PloS one.

[18]  Leigh R. Hochberg,et al.  Review: Human Intracortical Recording and Neural Decoding for Brain–Computer Interfaces , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[19]  Tomoyasu Horikawa,et al.  Generic decoding of seen and imagined objects using hierarchical visual features , 2015, Nature Communications.

[20]  Jack L. Gallant,et al.  Decoding the Semantic Content of Natural Movies from Human Brain Activity , 2016, Frontiers in systems neuroscience.

[21]  Jeremy C. Hebden,et al.  Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system , 2016, Biomedical optics express.

[22]  Andrew K. Fishell,et al.  Optical imaging of functional connectivity at the bedside , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[23]  Adam T Eggebrecht,et al.  Functional Imaging of the Developing Brain at the Bedside Using Diffuse Optical Tomography. , 2016, Cerebral cortex.

[24]  Obert,et al.  Functional imaging of the human brain using a modular , fibre-less , high-density diffuse optical tomography system , 2016 .

[25]  Milene Bonte,et al.  Decoding Articulatory Features from fMRI Responses in Dorsal Speech Regions , 2015, The Journal of Neuroscience.

[26]  Adam T. Eggebrecht,et al.  Mapping cortical responses to speech using high-density diffuse optical tomography , 2015, NeuroImage.

[27]  Evan M. Gordon,et al.  Functional System and Areal Organization of a Highly Sampled Individual Human Brain , 2015, Neuron.

[28]  Mahlega S. Hassanpour,et al.  Mapping distributed brain function and networks with diffuse optical tomography , 2014, Nature Photonics.

[29]  Abraham Z. Snyder,et al.  Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: In vivo validation against fMRI , 2014, NeuroImage.

[30]  Giancarlo Valente,et al.  Brain-Based Translation: fMRI Decoding of Spoken Words in Bilinguals Reveals Language-Independent Semantic Representations in Anterior Temporal Lobe , 2014, The Journal of Neuroscience.

[31]  I. Toni,et al.  Shared Representations for Working Memory and Mental Imagery in Early Visual Cortex , 2013, Current Biology.

[32]  Y Kamitani,et al.  Neural Decoding of Visual Imagery During Sleep , 2013, Science.

[33]  A. Schwartz,et al.  High-performance neuroprosthetic control by an individual with tetraplegia , 2013, The Lancet.

[34]  Kai Licha,et al.  Optical imaging. , 2013, Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer.

[35]  Brian R White,et al.  High-density diffuse optical tomography of term infant visual cortex in the nursery. , 2012, Journal of biomedical optics.

[36]  Abraham Z. Snyder,et al.  A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping , 2012, NeuroImage.

[37]  J. Gallant,et al.  Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies , 2011, Current Biology.

[38]  Yoko Mano,et al.  Decoding what one likes or dislikes from single-trial fNIRS measurements , 2011, Neuroreport.

[39]  D. Louis Collins,et al.  Unbiased average age-appropriate atlases for pediatric studies , 2011, NeuroImage.

[40]  J. Culver,et al.  Brain Specificity of Diffuse Optical Imaging: Improvements from Superficial Signal Regression and Tomography , 2010, Front. Neuroenerg..

[41]  Joseph P Culver,et al.  Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance. , 2010, Journal of biomedical optics.

[42]  Brian R. White,et al.  Phase-encoded retinotopy as an evaluation of diffuse optical neuroimaging , 2010, NeuroImage.

[43]  M. Grabowecky,et al.  Rapid eye-fixation training without eyetracking , 2009, Psychonomic bulletin & review.

[44]  Martin A. Lindquist,et al.  Modeling the hemodynamic response function in fMRI: Efficiency, bias and mis-modeling , 2009, NeuroImage.

[45]  F. Tong,et al.  Decoding reveals the contents of visual working memory in early visual areas , 2009, Nature.

[46]  Tom Chau,et al.  Decoding subjective preference from single-trial near-infrared spectroscopy signals , 2009, Journal of neural engineering.

[47]  Hamid Dehghani,et al.  Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction. , 2009, Communications in numerical methods in engineering.

[48]  J. Gallant,et al.  Identifying natural images from human brain activity , 2008, Nature.

[49]  Brian A. Wandell,et al.  Population receptive field estimates in human visual cortex , 2008, NeuroImage.

[50]  B. Wandell,et al.  Visual Field Maps in Human Cortex , 2007, Neuron.

[51]  Hamid Dehghani,et al.  Retinotopic mapping of adult human visual cortex with high-density diffuse optical tomography , 2007, Proceedings of the National Academy of Sciences.

[52]  Giuseppe Iaria,et al.  Occipital sulci of the human brain: Variability and probability maps , 2007, The Journal of comparative neurology.

[53]  Cuntai Guan,et al.  Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain–computer interface , 2007, NeuroImage.

[54]  Jean-Baptiste Poline,et al.  Inverse retinotopy: Inferring the visual content of images from brain activation patterns , 2006, NeuroImage.

[55]  G. Rees,et al.  Neuroimaging: Decoding mental states from brain activity in humans , 2006, Nature Reviews Neuroscience.

[56]  D. Boas,et al.  Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging. , 2006, Applied optics.

[57]  F. Tong,et al.  Decoding Seen and Attended Motion Directions from Activity in the Human Visual Cortex , 2006, Current Biology.

[58]  Charles E Metz,et al.  Receiver operating characteristic analysis: a tool for the quantitative evaluation of observer performance and imaging systems. , 2006, Journal of the American College of Radiology : JACR.

[59]  Yihong Yang,et al.  Head motion suppression using real-time feedback of motion information and its effects on task performance in fMRI , 2005, NeuroImage.

[60]  F. Tong,et al.  Decoding the visual and subjective contents of the human brain , 2005, Nature Neuroscience.

[61]  A. M. Dale,et al.  A hybrid approach to the skull stripping problem in MRI , 2004, NeuroImage.

[62]  B. Fischer,et al.  Visual field representations and locations of visual areas V1/2/3 in human visual cortex. , 2003, Journal of vision.

[63]  P Kochunov,et al.  Improvement in variability of the horizontal meridian of the primary visual area following high‐resolution spatial normalization , 2003, Human brain mapping.

[64]  Stefan Geyer,et al.  Brodmann's Areas , 2003 .

[65]  B. Pogue,et al.  Multiwavelength three-dimensional near-infrared tomography of the breast: initial simulation, phantom, and clinical results. , 2003, Applied optics.

[66]  David A. Boas,et al.  A Quantitative Comparison of Simultaneous BOLD fMRI and NIRS Recordings during Functional Brain Activation , 2002, NeuroImage.

[67]  J Mazziotta,et al.  A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[68]  Anders M. Dale,et al.  A hybrid approach to the Skull Stripping problem in MRI , 2001, NeuroImage.

[69]  John C. Mazziotta,et al.  A Probabilistic Atlas and Reference System for the Human Brain , 2001 .

[70]  Anders M. Dale,et al.  Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex , 2001, IEEE Transactions on Medical Imaging.

[71]  K. Amunts,et al.  Brodmann's Areas 17 and 18 Brought into Stereotaxic Space—Where and How Variable? , 2000, NeuroImage.

[72]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[73]  Bruce J. Tromberg,et al.  In-vivo local determination of tissue optical properties , 1999, European Conference on Biomedical Optics.

[74]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[75]  D. Heeger,et al.  Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1 , 1996, The Journal of Neuroscience.

[76]  A. Toga,et al.  Three-Dimensional Statistical Analysis of Sulcal Variability in the Human Brain , 1996, The Journal of Neuroscience.

[77]  E. DeYoe,et al.  Mapping striate and extrastriate visual areas in human cerebral cortex. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[78]  C. Metz.  Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[79]  J.J. Vidal,et al.  Real-time detection of brain events in EEG , 1977, Proceedings of the IEEE.

[80]  Laurel J. Lewis,et al.  Linear systems analysis , 1969 .

[81]  D. Hubel,et al.  Comparison of the effects of unilateral and bilateral eye closure on cortical unit responses in kittens. , 1965, Journal of neurophysiology.

[82]  D. Hubel,et al.  Extent of recovery from the effects of visual deprivation in kittens. , 1965, Journal of neurophysiology.

[83]  D. Hubel,et al.  Binocular interaction in striate cortex of kittens reared with artificial squint. , 1965, Journal of neurophysiology.

[84]  D. Hubel,et al.  SINGLE-CELL RESPONSES IN STRIATE CORTEX OF KITTENS DEPRIVED OF VISION IN ONE EYE. , 1963, Journal of neurophysiology.

[85]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[86]  W. Youden,et al.  Index for rating diagnostic tests , 1950, Cancer.

[87]  W. Penfield,et al.  SOMATIC MOTOR AND SENSORY REPRESENTATION IN THE CEREBRAL CORTEX OF MAN AS STUDIED BY ELECTRICAL STIMULATION , 1937 .