Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography

Topographic non-invasive near infrared spectroscopy (NIRS) has become a well-established tool for functional brain imaging. Applying up to 100 optodes over the head of a subject, allows achieving a spatial resolution in the centimeter range. This resolution is poor compared to other functional imaging tools. However, recently it was shown that diffuse optical tomography (DOT) as an extension of NIRS based on high-density (HD) probe arrays and supplemented by an advanced image reconstruction procedure allows describing activation patterns with a spatial resolution in the millimeter range. Building on these findings, we hypothesize that HD-DOT may render very focal activations accessible which would be missed by the traditionally used sparse arrays. We examined activation patterns in the primary somatosensory cortex, since its somatotopic organization is very fine-grained. We performed a vibrotactile stimulation study of the first and fifth finger in eight human subjects, using a 900-channel continuous-wave DOT imaging system for achieving a higher resolution than conventional topographic NIRS. To compare the results to a well-established high-resolution imaging technique, the same paradigm was investigated in the same subjects by means of functional magnetic resonance imaging (fMRI). In this work, we tested the advantage of ultrahigh-density probe arrays and show that highly focal activations would be missed by classical next-nearest neighbor NIRS approach, but also by DOT, when using a sparse probe array. Distinct activation patterns for both fingers correlated well with the expected neuroanatomy in five of eight subjects. Additionally we show that activation for different fingers is projected to different tissue depths in the DOT image. Comparison to the fMRI data yielded similar activation foci in seven out of ten finger representations in these five subjects when comparing the lateral localization of DOT and fMRI results.

[1]  W. Eric L. Grimson,et al.  Anatomical atlas-guided diffuse optical tomography of brain activation , 2009, NeuroImage.

[2]  Yaling Pei,et al.  Image quality improvement via spatial deconvolution in optical tomography: time-series imaging. , 2005, Journal of biomedical optics.

[3]  R. Barbour,et al.  Normalized-constraint algorithm for minimizing inter-parameter crosstalk in DC optical tomography. , 2001, Optics express.

[4]  Jens Steinbrink,et al.  Contrast enhanced high-resolution diffuse optical tomography of the human brain using ICG , 2011, Optics express.

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

[6]  A Villringer,et al.  fMRI shows multiple somatotopic digit representations in human primary somatosensory cortex , 2000, Neuroreport.

[7]  D. Boas,et al.  Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. , 2002, Optics express.

[8]  M. Schweiger,et al.  Image reconstruction in optical tomography. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[9]  A. Hielscher,et al.  Instrumentation for fast functional optical tomography , 2002 .

[10]  Anders Björkman,et al.  Optimizing the mapping of finger areas in primary somatosensory cortex using functional MRI. , 2008, Magnetic resonance imaging.

[11]  Y X Wang,et al.  Leu‐enkephalin induced by IL‐2 administration mediates analgesic effect of IL‐2 , 2000, Neuroreport.

[12]  H. Dehghani,et al.  Diffuse optical imaging , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[13]  A. Mittnacht,et al.  Near infrared spectroscopy in children at high risk of low perfusion , 2010, Current opinion in anaesthesiology.

[14]  Qianqian Fang,et al.  Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates , 2010, Biomedical optics express.

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

[16]  Jens Frahm,et al.  Finger representations in human primary somatosensory cortex as revealed by high-resolution functional MRI of tactile stimulation , 2008, NeuroImage.

[17]  亀山 正樹,et al.  Frontal lobe function in bipolar disorder : a multichannel near-infrared spectroscopy study , 2005 .

[18]  David Highton,et al.  Noninvasive cerebral oximetry: is there light at the end of the tunnel? , 2010, Current opinion in anaesthesiology.

[19]  A. Villringer,et al.  Beyond the Visible—Imaging the Human Brain with Light , 2003, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[20]  D. Boas,et al.  Diffuse optical tomography system to image brain activation with improved spatial resolution and validation with functional magnetic resonance imaging. , 2006, Applied optics.

[21]  Terry M. Peters,et al.  3D statistical neuroanatomical models from 305 MRI volumes , 1993, 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference.

[22]  S R Arridge,et al.  Recent advances in diffuse optical imaging , 2005, Physics in medicine and biology.

[23]  T. Ono,et al.  Brain Cortical Mapping by Simultaneous Recording of Functional Near Infrared Spectroscopy and Electroencephalograms from the Whole Brain During Right Median Nerve Stimulation , 2009, Brain Topography.

[24]  David C. Alsop,et al.  The Sensory Somatotopic Map of the Human Hand Demonstrated at 4 Tesla , 1999, NeuroImage.

[25]  K. Kubota,et al.  Cortical Mapping of Gait in Humans: A Near-Infrared Spectroscopic Topography Study , 2001, NeuroImage.

[26]  J. Schunk,et al.  Neuroenergetics Original Research Article , 2022 .

[27]  M. Raichle,et al.  Focal physiological uncoupling of cerebral blood flow and oxidative metabolism during somatosensory stimulation in human subjects. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[28]  A Villringer,et al.  Somatotopic organization of human secondary somatosensory cortex. , 2001, Cerebral cortex.

[29]  S. Arridge,et al.  Optical imaging in medicine: II. Modelling and reconstruction , 1997, Physics in medicine and biology.

[30]  Harry L Graber,et al.  Image correction algorithm for functional three-dimensional diffuse optical tomography brain imaging. , 2007, Applied optics.

[31]  David A. Boas,et al.  Near-infrared spectroscopy shows right parietal specialization for number in pre-verbal infants , 2010, NeuroImage.

[32]  C H Schmitz,et al.  Optical tomographic imaging of dynamic features of dense-scattering media. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.

[33]  Klaus-Robert Müller,et al.  Enhanced Performance by a Hybrid Nirs–eeg Brain Computer Interface , 2022 .

[34]  S. Francis,et al.  Mapping human somatosensory cortex in individual subjects with 7 T functional MRI 1 Running title : Mapping human somatosensory cortex , 2010 .

[35]  D. Boas,et al.  Resting state functional connectivity of the whole head with near-infrared spectroscopy , 2010, Biomedical optics express.

[36]  Martin Wolf,et al.  Task complexity relates to activation of cortical motor areas during uni- and bimanual performance: A functional NIRS study , 2009, NeuroImage.

[37]  David A Boas,et al.  Diffuse optical imaging of the whole head. , 2006, Journal of biomedical optics.

[38]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited , 1995, NeuroImage.

[39]  Simon R. Arridge,et al.  Three-dimensional whole-head optical tomography of passive motor evoked responses in the neonate , 2006, NeuroImage.

[40]  Masao Iwase,et al.  Frontal cortex activation associated with speeded processing of visuospatial working memory revealed by multichannel near-infrared spectroscopy during Advanced Trail Making Test performance , 2010, Behavioural Brain Research.

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

[42]  Hamid Dehghani,et al.  Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography. , 2009, Applied optics.

[43]  Tianzi Jiang,et al.  Reduced prefrontal activation during Tower of London in first-episode schizophrenia: A multi-channel near-infrared spectroscopy study , 2010, Neuroscience Letters.

[44]  Hanli Liu,et al.  Development of a compensation algorithm for accurate depth localization in diffuse optical tomography. , 2010, Optics letters.

[45]  D. Boas,et al.  Hemodynamic evoked response of the sensorimotor cortex measured noninvasively with near-infrared optical imaging. , 2003, Psychophysiology.

[46]  D. Delpy,et al.  Methods of quantitating cerebral near infrared spectroscopy data. , 1988, Advances in experimental medicine and biology.

[47]  Yong Xu,et al.  Using co-variations in the Hb signal to detect visual activation: A near infrared spectroscopic imaging study , 2009, NeuroImage.

[48]  D. Boas,et al.  Improving the diffuse optical imaging spatial resolution of the cerebral hemodynamic response to brain activation in humans. , 2004, Optics letters.

[49]  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.

[50]  K. Paulsen,et al.  Spatially varying optical property reconstruction using a finite element diffusion equation approximation. , 1995, Medical physics.

[51]  D. Kiper,et al.  Testing the potential of a virtual reality neurorehabilitation system during performance of observation, imagery and imitation of motor actions recorded by wireless functional near-infrared spectroscopy (fNIRS) , 2010, Journal of NeuroEngineering and Rehabilitation.

[52]  Niels Birbaumer,et al.  Hemodynamic brain-computer interfaces for communication and rehabilitation , 2009, Neural Networks.

[53]  David A Boas,et al.  Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units. , 2009, Optics express.

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

[55]  R. Barbour,et al.  Influence of Systematic Errors in Reference States on Image Quality and on Stability of Derived Information for dc Optical Imaging. , 2001, Applied optics.

[56]  Isabell Wartenburger,et al.  The processing of prosody: Evidence of interhemispheric specialization at the age of four , 2007, NeuroImage.

[57]  H. Jasper,et al.  The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. , 1999, Electroencephalography and clinical neurophysiology. Supplement.

[58]  A. Hielscher,et al.  Three-dimensional optical tomography of hemodynamics in the human head. , 2001, Optics express.

[59]  Brian R White,et al.  Neonatal hemodynamic response to visual cortex activity: high-density near-infrared spectroscopy study. , 2010, Journal of biomedical optics.