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Markow ZE, Tripathy K, Svoboda AM, Schroeder ML, Rafferty SM, Richter EJ, Eggebrecht AT, Anastasio MA, Chevillet MA, Mugler EM, Naufel SN, Yin A, Trobaugh JW, Culver JP. Identifying Naturalistic Movies from Human Brain Activity with High-Density Diffuse Optical Tomography. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.27.566650. [PMID: 38076976 PMCID: PMC10705261 DOI: 10.1101/2023.11.27.566650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Modern neuroimaging modalities, particularly functional MRI (fMRI), can decode detailed human experiences. Thousands of viewed images can be identified or classified, and sentences can be reconstructed. Decoding paradigms often leverage encoding models that reduce the stimulus space into a smaller yet generalizable feature set. However, the neuroimaging devices used for detailed decoding are non-portable, like fMRI, or invasive, like electrocorticography, excluding application in naturalistic use. Wearable, non-invasive, but lower-resolution devices such as electroencephalography and functional near-infrared spectroscopy (fNIRS) have been limited to decoding between stimuli used during training. Herein we develop and evaluate model-based decoding with high-density diffuse optical tomography (HD-DOT), a higher-resolution expansion of fNIRS with demonstrated promise as a surrogate for fMRI. Using a motion energy model of visual content, we decoded the identities of novel movie clips outside the training set with accuracy far above chance for single-trial decoding. Decoding was robust to modulations of testing time window, different training and test imaging sessions, hemodynamic contrast, and optode array density. Our results suggest that HD-DOT can translate detailed decoding into naturalistic use.
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Toth J, Kurtin DL, Brosnan M, Arvaneh M. Opportunities and obstacles in non-invasive brain stimulation. Front Hum Neurosci 2024; 18:1385427. [PMID: 38562225 PMCID: PMC10982339 DOI: 10.3389/fnhum.2024.1385427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 03/05/2024] [Indexed: 04/04/2024] Open
Abstract
Non-invasive brain stimulation (NIBS) is a complex and multifaceted approach to modulating brain activity and holds the potential for broad accessibility. This work discusses the mechanisms of the four distinct approaches to modulating brain activity non-invasively: electrical currents, magnetic fields, light, and ultrasound. We examine the dual stochastic and deterministic nature of brain activity and its implications for NIBS, highlighting the challenges posed by inter-individual variability, nebulous dose-response relationships, potential biases and neuroanatomical heterogeneity. Looking forward, we propose five areas of opportunity for future research: closed-loop stimulation, consistent stimulation of the intended target region, reducing bias, multimodal approaches, and strategies to address low sample sizes.
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Affiliation(s)
- Jake Toth
- Automatic Control and Systems Engineering, Neuroscience Institute, Insigneo Institute, University of Sheffield, Sheffield, United Kingdom
| | | | - Méadhbh Brosnan
- School of Psychology, University College Dublin, Dublin, Ireland
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Mahnaz Arvaneh
- Automatic Control and Systems Engineering, Neuroscience Institute, Insigneo Institute, University of Sheffield, Sheffield, United Kingdom
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3
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Srinivasan S, Acharya D, Butters E, Collins-Jones L, Mancini F, Bale G. Subject-specific information enhances spatial accuracy of high-density diffuse optical tomography. FRONTIERS IN NEUROERGONOMICS 2024; 5:1283290. [PMID: 38444841 PMCID: PMC10910052 DOI: 10.3389/fnrgo.2024.1283290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 02/02/2024] [Indexed: 03/07/2024]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a widely used imaging method for mapping brain activation based on cerebral hemodynamics. The accurate quantification of cortical activation using fNIRS data is highly dependent on the ability to correctly localize the positions of light sources and photodetectors on the scalp surface. Variations in head size and shape across participants greatly impact the precise locations of these optodes and consequently, the regions of the cortical surface being reached. Such variations can therefore influence the conclusions drawn in NIRS studies that attempt to explore specific cortical regions. In order to preserve the spatial identity of each NIRS channel, subject-specific differences in NIRS array registration must be considered. Using high-density diffuse optical tomography (HD-DOT), we have demonstrated the inter-subject variability of the same HD-DOT array applied to ten participants recorded in the resting state. We have also compared three-dimensional image reconstruction results obtained using subject-specific positioning information to those obtained using generic optode locations. To mitigate the error introduced by using generic information for all participants, photogrammetry was used to identify specific optode locations per-participant. The present work demonstrates the large variation between subjects in terms of which cortical parcels are sampled by equivalent channels in the HD-DOT array. In particular, motor cortex recordings suffered from the largest optode localization errors, with a median localization error of 27.4 mm between generic and subject-specific optodes, leading to large differences in parcel sensitivity. These results illustrate the importance of collecting subject-specific optode locations for all wearable NIRS experiments, in order to perform accurate group-level analysis using cortical parcellation.
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Affiliation(s)
- Sruthi Srinivasan
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Deepshikha Acharya
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Emilia Butters
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Liam Collins-Jones
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Flavia Mancini
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
| | - Gemma Bale
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
- Department of Physics, University of Cambridge, Cambridge, United Kingdom
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4
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Gao Q, Zhang L. Brief mindfulness meditation intervention improves attentional control of athletes in virtual reality shooting competition: Evidence from fNIRS and eye tracking. PSYCHOLOGY OF SPORT AND EXERCISE 2023; 69:102477. [PMID: 37665918 DOI: 10.1016/j.psychsport.2023.102477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 06/13/2023] [Accepted: 06/23/2023] [Indexed: 09/06/2023]
Abstract
Attentional control is a crucial cognitive ability for sports performance. The current research aimed to investigate whether a brief (20-min) pre-competition mindfulness meditation (MM) intervention enhances athletes' attentional control during competitions and alters the activity of brain regions related to attentional control. We created a virtual reality shooting competition to compare the eye-gaze indicators and functional near-infrared spectroscopy (fNIRS) parameters of 78 university athletes after 20 min of MM or 20 min of mind wandering (MW). Participants' average fixation durations (AFDs) on task-relevant information (targets) were significantly longer in the MM group. In contrast, both average fixation counts (AFCs) and AFDs on task-irrelevant information (the ranking screen) were significantly lower in the MM group than in the MW group. Additionally, the MM group exhibited significantly stronger activation of the left and right dorsolateral prefrontal cortex (dlPFC) as well as higher levels of oxygenated haemoglobin [HbO] and greater functional connectivity (FC) of the right dlPFC, which was considered evidence of recruitment for attentional control. Moreover, the MM group achieved significantly better shooting performance than the MW group. Overall, the findings suggest that one session 20-min MM practice pre-competition facilitates focus during competition and improves athletic performance. We recommend the application of brief mindfulness practice in sports, especially in closed-skill sports that require high attention participation (e.g., shooting, archery, darts, golf, gymnastics, skating etc.).
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Affiliation(s)
- Qian Gao
- School of Psychology, Beijing Sport University, Beijing, China
| | - Liwei Zhang
- School of Psychology, Beijing Sport University, Beijing, China.
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5
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Schroeder ML, Sherafati A, Ulbrich RL, Wheelock MD, Svoboda AM, Klein ED, George TG, Tripathy K, Culver JP, Eggebrecht AT. Mapping cortical activations underlying covert and overt language production using high-density diffuse optical tomography. Neuroimage 2023; 276:120190. [PMID: 37245559 PMCID: PMC10760405 DOI: 10.1016/j.neuroimage.2023.120190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 05/05/2023] [Accepted: 05/23/2023] [Indexed: 05/30/2023] Open
Abstract
Gold standard neuroimaging modalities such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and more recently electrocorticography (ECoG) have provided profound insights regarding the neural mechanisms underlying the processing of language, but they are limited in applications involving naturalistic language production especially in developing brains, during face-to-face dialogues, or as a brain-computer interface. High-density diffuse optical tomography (HD-DOT) provides high-fidelity mapping of human brain function with comparable spatial resolution to that of fMRI but in a silent and open scanning environment similar to real-life social scenarios. Therefore, HD-DOT has potential to be used in naturalistic settings where other neuroimaging modalities are limited. While HD-DOT has been previously validated against fMRI for mapping the neural correlates underlying language comprehension and covert (i.e., "silent") language production, HD-DOT has not yet been established for mapping the cortical responses to overt (i.e., "out loud") language production. In this study, we assessed the brain regions supporting a simple hierarchy of language tasks: silent reading of single words, covert production of verbs, and overt production of verbs in normal hearing right-handed native English speakers (n = 33). First, we found that HD-DOT brain mapping is resilient to movement associated with overt speaking. Second, we observed that HD-DOT is sensitive to key activations and deactivations in brain function underlying the perception and naturalistic production of language. Specifically, statistically significant results were observed that show recruitment of regions in occipital, temporal, motor, and prefrontal cortices across all three tasks after performing stringent cluster-extent based thresholding. Our findings lay the foundation for future HD-DOT studies of imaging naturalistic language comprehension and production during real-life social interactions and for broader applications such as presurgical language assessment and brain-machine interfaces.
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Affiliation(s)
- Mariel L Schroeder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, USA
| | - Arefeh Sherafati
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Rachel L Ulbrich
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; University of Missouri School of Medicine, Columbia, MO, USA
| | - Muriah D Wheelock
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Alexandra M Svoboda
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; University of Cincinnati Medical Center, Cincinnati, Oh, USA
| | - Emma D Klein
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tessa G George
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Kalyan Tripathy
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; Washington University School of Medicine, St Louis, MO, USA
| | - Joseph P Culver
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; Division of Biology & Biomedical Sciences, Washington University School of Medicine, St Louis, MO, USA; Department of Physics, Washington University in St. Louis, St Louis, MO, USA; Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
| | - Adam T Eggebrecht
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA; Division of Biology & Biomedical Sciences, Washington University School of Medicine, St Louis, MO, USA; Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA.
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Anaya D, Batra G, Bracewell P, Catoen R, Chakraborty D, Chevillet M, Damodara P, Dominguez A, Emms L, Jiang Z, Kim E, Klumb K, Lau F, Le R, Li J, Mateo B, Matloff L, Mehta A, Mugler EM, Murthy A, Nakagome S, Orendorff R, Saung EF, Schwarz R, Sethi R, Sevile R, Srivastava A, Sundberg J, Yang Y, Yin A. Scalable, modular continuous wave functional near-infrared spectroscopy system (Spotlight). JOURNAL OF BIOMEDICAL OPTICS 2023; 28:065003. [PMID: 37325190 PMCID: PMC10261976 DOI: 10.1117/1.jbo.28.6.065003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/26/2023] [Accepted: 05/01/2023] [Indexed: 06/17/2023]
Abstract
Significance We present a fiberless, portable, and modular continuous wave-functional near-infrared spectroscopy system, Spotlight, consisting of multiple palm-sized modules-each containing high-density light-emitting diode and silicon photomultiplier detector arrays embedded in a flexible membrane that facilitates optode coupling to scalp curvature. Aim Spotlight's goal is to be a more portable, accessible, and powerful functional near-infrared spectroscopy (fNIRS) device for neuroscience and brain-computer interface (BCI) applications. We hope that the Spotlight designs we share here can spur more advances in fNIRS technology and better enable future non-invasive neuroscience and BCI research. Approach We report sensor characteristics in system validation on phantoms and motor cortical hemodynamic responses in a human finger-tapping experiment, where subjects wore custom 3D-printed caps with two sensor modules. Results The task conditions can be decoded offline with a median accuracy of 69.6%, reaching 94.7% for the best subject, and at a comparable accuracy in real time for a subset of subjects. We quantified how well the custom caps fitted to each subject and observed that better fit leads to more observed task-dependent hemodynamic response and better decoding accuracy. Conclusions The advances presented here should serve to make fNIRS more accessible for BCI applications.
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Affiliation(s)
- Daniel Anaya
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Gautam Batra
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - Ryan Catoen
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - Mark Chevillet
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | | | - Laurence Emms
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Zifan Jiang
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ealgoo Kim
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Keith Klumb
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Frances Lau
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Rosemary Le
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Jamie Li
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Brett Mateo
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Laura Matloff
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Asha Mehta
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - Akansh Murthy
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Sho Nakagome
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ryan Orendorff
- Meta Platforms, Inc., Menlo Park, California, United States
| | - E-Fann Saung
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Roland Schwarz
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ruben Sethi
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Rudy Sevile
- Meta Platforms, Inc., Menlo Park, California, United States
| | | | - John Sundberg
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Ying Yang
- Meta Platforms, Inc., Menlo Park, California, United States
| | - Allen Yin
- Meta Platforms, Inc., Menlo Park, California, United States
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7
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Blaney G, Fernandez C, Sassaroli A, Fantini S. Dual-slope imaging of cerebral hemodynamics with frequency-domain near-infrared spectroscopy. NEUROPHOTONICS 2023; 10:013508. [PMID: 36601543 PMCID: PMC9807277 DOI: 10.1117/1.nph.10.1.013508] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Significance This work targets the contamination of optical signals by superficial hemodynamics, which is one of the chief hurdles in non-invasive optical measurements of the human brain. Aim To identify optimal source-detector distances for dual-slope (DS) measurements in frequency-domain (FD) near-infrared spectroscopy (NIRS) and demonstrate preferential sensitivity of DS imaging to deeper tissue (brain) versus superficial tissue (scalp). Approach Theoretical studies (in-silico) based on diffusion theory in two-layered and in homogeneous scattering media. In-vivo demonstrations of DS imaging of the human brain during visual stimulation and during systemic blood pressure oscillations. Results The mean distance (between the two source-detector distances needed for DS) is the key factor for depth sensitivity. In-vivo imaging of the human occipital lobe with FD NIRS and a mean distance of 31 mm indicated: (1) greater hemodynamic response to visual stimulation from FD phase versus intensity, and from DS versus single-distance (SD); (2) hemodynamics from FD phase and DS mainly driven by blood flow, and hemodynamics from SD intensity mainly driven by blood volume. Conclusions DS imaging with FD NIRS may suppress confounding contributions from superficial hemodynamics without relying on data at short source-detector distances. This capability can have significant implications for non-invasive optical measurements of the human brain.
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Affiliation(s)
- Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Cristianne Fernandez
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
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Uchitel J, Blanco B, Collins-Jones L, Edwards A, Porter E, Pammenter K, Hebden J, Cooper RJ, Austin T. Cot-side imaging of functional connectivity in the developing brain during sleep using wearable high-density diffuse optical tomography. Neuroimage 2023; 265:119784. [PMID: 36464095 DOI: 10.1016/j.neuroimage.2022.119784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 11/16/2022] [Accepted: 11/30/2022] [Indexed: 12/03/2022] Open
Abstract
Studies of cortical function in newborn infants in clinical settings are extremely challenging to undertake with traditional neuroimaging approaches. Partly in response to this challenge, functional near-infrared spectroscopy (fNIRS) has become an increasingly common clinical research tool but has significant limitations including a low spatial resolution and poor depth specificity. Moreover, the bulky optical fibres required in traditional fNIRS approaches present significant mechanical challenges, particularly for the study of vulnerable newborn infants. A new generation of wearable, modular, high-density diffuse optical tomography (HD-DOT) technologies has recently emerged that overcomes many of the limitations of traditional, fibre-based and low-density fNIRS measurements. Driven by the development of this new technology, we have undertaken the first cot-side study of newborn infants using wearable HD-DOT in a clinical setting. We use this technology to study functional brain connectivity (FC) in newborn infants during sleep and assess the effect of neonatal sleep states, active sleep (AS) and quiet sleep (QS), on resting state FC. Our results demonstrate that it is now possible to obtain high-quality functional images of the neonatal brain in the clinical setting with few constraints. Our results also suggest that sleep states differentially affect FC in the neonatal brain, consistent with prior reports.
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Affiliation(s)
- Julie Uchitel
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; Department of Pediatrics, University of Cambridge, Cambridge, UK.
| | - Borja Blanco
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Liam Collins-Jones
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Andrea Edwards
- Neonatal Intensive Care Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Emma Porter
- Neonatal Intensive Care Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Kelle Pammenter
- Neonatal Intensive Care Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Jem Hebden
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Robert J Cooper
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Topun Austin
- Neonatal Intensive Care Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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9
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Uchitel J, Blanco B, Vidal-Rosas E, Collins-Jones L, Cooper RJ. Reliability and similarity of resting state functional connectivity networks imaged using wearable, high-density diffuse optical tomography in the home setting. Neuroimage 2022; 263:119663. [PMID: 36202159 DOI: 10.1016/j.neuroimage.2022.119663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 09/28/2022] [Accepted: 10/02/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND When characterizing the brain's resting state functional connectivity (RSFC) networks, demonstrating networks' similarity across sessions and reliability across different scan durations is essential for validating results and possibly minimizing the scanning time needed to obtain stable measures of RSFC. Recent advances in optical functional neuroimaging technologies have resulted in fully wearable devices that may serve as a complimentary tool to functional magnetic resonance imaging (fMRI) and allow for investigations of RSFC networks repeatedly and easily in non-traditional scanning environments. METHODS Resting-state cortical hemodynamic activity was repeatedly measured in a single individual in the home environment during COVID-19 lockdown conditions using the first ever application of a 24-module (72 sources, 96 detectors) wearable high-density diffuse optical tomography (HD-DOT) system. Twelve-minute recordings of resting-state data were acquired over the pre-frontal and occipital regions in fourteen experimental sessions over three weeks. As an initial validation of the data, spatial independent component analysis was used to identify RSFC networks. Reliability and similarity scores were computed using metrics adapted from the fMRI literature. RESULTS We observed RSFC networks over visual regions (visual peripheral, visual central networks) and higher-order association regions (control, salience and default mode network), consistent with previous fMRI literature. High similarity was observed across testing sessions and across chromophores (oxygenated and deoxygenated haemoglobin, HbO and HbR) for all functional networks, and for each network considered separately. Stable reliability values (described here as a <10% change between time windows) were obtained for HbO and HbR with differences in required scanning time observed on a network-by-network basis. DISCUSSION Using RSFC data from a highly sampled individual, the present work demonstrates that wearable HD-DOT can be used to obtain RSFC measurements with high similarity across imaging sessions and reliability across recording durations in the home environment. Wearable HD-DOT may serve as a complimentary tool to fMRI for studying RSFC networks outside of the traditional scanning environment and in vulnerable populations for whom fMRI is not feasible.
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Affiliation(s)
- Julie Uchitel
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
| | - Borja Blanco
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom; Department of Psychology, University of Cambridge, Cambridge, United Kingdom.
| | - Ernesto Vidal-Rosas
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
| | - Liam Collins-Jones
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
| | - Robert J Cooper
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
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10
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Jiang S, Carpenter LL, Jiang H. Optical neuroimaging: advancing transcranial magnetic stimulation treatments of psychiatric disorders. Vis Comput Ind Biomed Art 2022; 5:22. [PMID: 36071259 PMCID: PMC9452613 DOI: 10.1186/s42492-022-00119-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/22/2022] [Indexed: 11/10/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) has been established as an important and effective treatment for various psychiatric disorders. However, its effectiveness has likely been limited due to the dearth of neuronavigational tools for targeting purposes, unclear ideal stimulation parameters, and a lack of knowledge regarding the physiological response of the brain to TMS in each psychiatric condition. Modern optical imaging modalities, such as functional near-infrared spectroscopy and diffuse optical tomography, are promising tools for the study of TMS optimization and functional targeting in psychiatric disorders. They possess a unique combination of high spatial and temporal resolutions, portability, real-time capability, and relatively low costs. In this mini-review, we discuss the advent of optical imaging techniques and their innovative use in several psychiatric conditions including depression, panic disorder, phobias, and eating disorders. With further investment and research in the development of these optical imaging approaches, their potential will be paramount for the advancement of TMS treatment protocols in psychiatry.
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11
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Taylor-Williams M, Spicer G, Bale G, Bohndiek SE. Noninvasive hemoglobin sensing and imaging: optical tools for disease diagnosis. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-220074VR. [PMID: 35922891 PMCID: PMC9346606 DOI: 10.1117/1.jbo.27.8.080901] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 06/27/2022] [Indexed: 05/08/2023]
Abstract
SIGNIFICANCE Measurement and imaging of hemoglobin oxygenation are used extensively in the detection and diagnosis of disease; however, the applied instruments vary widely in their depth of imaging, spatiotemporal resolution, sensitivity, accuracy, complexity, physical size, and cost. The wide variation in available instrumentation can make it challenging for end users to select the appropriate tools for their application and to understand the relative limitations of different methods. AIM We aim to provide a systematic overview of the field of hemoglobin imaging and sensing. APPROACH We reviewed the sensing and imaging methods used to analyze hemoglobin oxygenation, including pulse oximetry, spectral reflectance imaging, diffuse optical imaging, spectroscopic optical coherence tomography, photoacoustic imaging, and diffuse correlation spectroscopy. RESULTS We compared and contrasted the ability of different methods to determine hemoglobin biomarkers such as oxygenation while considering factors that influence their practical application. CONCLUSIONS We highlight key limitations in the current state-of-the-art and make suggestions for routes to advance the clinical use and interpretation of hemoglobin oxygenation information.
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Affiliation(s)
- Michaela Taylor-Williams
- University of Cambridge, Department of Physics, Cavendish Laboratory, Cambridge, United Kingdom, United Kingdom
- University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom, United Kingdom
| | - Graham Spicer
- University of Cambridge, Department of Physics, Cavendish Laboratory, Cambridge, United Kingdom, United Kingdom
- University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom, United Kingdom
| | - Gemma Bale
- University of Cambridge, Department of Physics, Cavendish Laboratory, Cambridge, United Kingdom, United Kingdom
- University of Cambridge, Electrical Division, Department of Engineering, Cambridge, United Kingdom, United Kingdom
| | - Sarah E Bohndiek
- University of Cambridge, Department of Physics, Cavendish Laboratory, Cambridge, United Kingdom, United Kingdom
- University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom, United Kingdom
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Ayaz H, Baker WB, Blaney G, Boas DA, Bortfeld H, Brady K, Brake J, Brigadoi S, Buckley EM, Carp SA, Cooper RJ, Cowdrick KR, Culver JP, Dan I, Dehghani H, Devor A, Durduran T, Eggebrecht AT, Emberson LL, Fang Q, Fantini S, Franceschini MA, Fischer JB, Gervain J, Hirsch J, Hong KS, Horstmeyer R, Kainerstorfer JM, Ko TS, Licht DJ, Liebert A, Luke R, Lynch JM, Mesquida J, Mesquita RC, Naseer N, Novi SL, Orihuela-Espina F, O’Sullivan TD, Peterka DS, Pifferi A, Pollonini L, Sassaroli A, Sato JR, Scholkmann F, Spinelli L, Srinivasan VJ, St. Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report. NEUROPHOTONICS 2022; 9:S24001. [PMID: 36052058 PMCID: PMC9424749 DOI: 10.1117/1.nph.9.s2.s24001] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Hasan Ayaz
- Drexel University, School of Biomedical Engineering, Science, and Health Systems, Philadelphia, Pennsylvania, United States
- Drexel University, College of Arts and Sciences, Department of Psychological and Brain Sciences, Philadelphia, Pennsylvania, United States
| | - Wesley B. Baker
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - David A. Boas
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Heather Bortfeld
- University of California, Merced, Departments of Psychological Sciences and Cognitive and Information Sciences, Merced, California, United States
| | - Kenneth Brady
- Lurie Children’s Hospital, Northwestern University Feinberg School of Medicine, Department of Anesthesiology, Chicago, Illinois, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - Sabrina Brigadoi
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
| | - Erin M. Buckley
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Robert J. Cooper
- University College London, Department of Medical Physics and Bioengineering, DOT-HUB, London, United Kingdom
| | - Kyle R. Cowdrick
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Tokyo, Japan
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Anna Devor
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Turgut Durduran
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
- Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain
| | - Adam T. Eggebrecht
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Lauren L. Emberson
- University of British Columbia, Department of Psychology, Vancouver, British Columbia, Canada
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Maria Angela Franceschini
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Jonas B. Fischer
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
| | - Judit Gervain
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Joy Hirsch
- Yale School of Medicine, Department of Psychiatry, Neuroscience, and Comparative Medicine, New Haven, Connecticut, United States
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Keum-Shik Hong
- Pusan National University, School of Mechanical Engineering, Busan, Republic of Korea
- Qingdao University, School of Automation, Institute for Future, Qingdao, China
| | - Roarke Horstmeyer
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
- Duke University, Department of Physics, Durham, North Carolina, United States
| | - Jana M. Kainerstorfer
- Carnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States
- Carnegie Mellon University, Neuroscience Institute, Pittsburgh, Pennsylvania, United States
| | - Tiffany S. Ko
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Daniel J. Licht
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
| | - Adam Liebert
- Polish Academy of Sciences, Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Robert Luke
- Macquarie University, Department of Linguistics, Sydney, New South Wales, Australia
- Macquarie University Hearing, Australia Hearing Hub, Sydney, New South Wales, Australia
| | - Jennifer M. Lynch
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Jaume Mesquida
- Parc Taulí Hospital Universitari, Critical Care Department, Sabadell, Spain
| | - Rickson C. Mesquita
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Noman Naseer
- Air University, Department of Mechatronics and Biomedical Engineering, Islamabad, Pakistan
| | - Sergio L. Novi
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Western University, Department of Physiology and Pharmacology, London, Ontario, Canada
| | | | - Thomas D. O’Sullivan
- University of Notre Dame, Department of Electrical Engineering, Notre Dame, Indiana, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behaviour Institute, New York, United States
| | | | - Luca Pollonini
- University of Houston, Department of Engineering Technology, Houston, Texas, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - João Ricardo Sato
- Federal University of ABC, Center of Mathematics, Computing and Cognition, São Bernardo do Campo, São Paulo, Brazil
| | - Felix Scholkmann
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Lorenzo Spinelli
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Vivek J. Srinivasan
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- NYU Langone Health, Department of Ophthalmology, New York, New York, United States
- NYU Langone Health, Department of Radiology, New York, New York, United States
| | - Keith St. Lawrence
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Tara Urner
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Martin Wolf
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Ursula Wolf
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Shiqi Xu
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Changhuei Yang
- California Institute of Technology, Department of Electrical Engineering, Pasadena, California, United States
| | - Arjun G. Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
| | - Meryem A. Yücel
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Wenjun Zhou
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- China Jiliang University, College of Optical and Electronic Technology, Hangzhou, Zhejiang, China
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Wojtkiewicz S, Bejm K, Liebert A. Lock-in functional near-infrared spectroscopy for measurement of the haemodynamic brain response. BIOMEDICAL OPTICS EXPRESS 2022; 13:1869-1887. [PMID: 35519260 PMCID: PMC9045899 DOI: 10.1364/boe.448038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/13/2022] [Accepted: 02/15/2022] [Indexed: 06/14/2023]
Abstract
Here we show a method of the lock-in amplifying near-infrared signals originating within a human brain. It implies using two 90-degree rotated source-detector pairs fixed on a head surface. Both pairs have a joint sensitivity region located towards the brain. A direct application of the lock-in technique on both signals results in amplifying common frequency components, e.g. related to brain cortex stimulation and attenuating the rest, including all components not related to the stimulation: e.g. pulse, instrumental and biological noise or movement artefacts. This is a self-driven method as no prior assumptions are needed and the noise model is provided by the interfering signals themselves. We show the theory (classical modified Beer-Lambert law and diffuse optical tomography approaches), the algorithm implementation and tests on a finite element mathematical model and in-vivo on healthy volunteers during visual cortex stimulation. The proposed hardware and algorithm complexity suit the entire spectrum of (continuous wave, frequency domain, time-resolved) near-infrared spectroscopy systems featuring real-time, direct, robust and low-noise brain activity registration tool. As such, this can be of special interest in optical brain computer interfaces and high reliability/stability monitors of tissue oxygenation.
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Fan W, Dehghani H, Eggebrecht AT. Investigation of effect of modulation frequency on high-density diffuse optical tomography image quality. NEUROPHOTONICS 2021; 8:045002. [PMID: 34849379 PMCID: PMC8612746 DOI: 10.1117/1.nph.8.4.045002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 11/04/2021] [Indexed: 05/16/2023]
Abstract
Significance: By incorporating multiple overlapping functional near-infrared spectroscopy (fNIRS) measurements, high-density diffuse optical tomography (HD-DOT) images human brain function with fidelity comparable to functional magnetic resonance imaging (fMRI). Previous work has shown that frequency domain high-density diffuse optical tomography (FD-HD-DOT) may further improve image quality over more traditional continuous wave (CW) HD-DOT. Aim: The effects of modulation frequency on image quality as obtainable with FD-HD-DOT is investigated through simulations with a realistic noise model of functional activations in human head models, arising from 11 source modulation frequencies between CW and 1000 MHz. Approach: Simulations were performed using five representative head models with an HD regular grid of 158 light sources and 166 detectors and an empirically derived noise model. Functional reconstructions were quantitatively assessed with multiple image quality metrics including the localization error (LE), success rate, full width at half maximum, and full volume at half maximum (FVHM). All metrics were evaluated against CW-based models. Results: Compared to CW, localization accuracy is improved by >40% throughout brain depths of 13 to 25 mm below the surface with 300 to 500 MHz modulation frequencies. Additionally, the reliable field of view in brain tissue is enlarged by 35% to 48% within an optimal frequency of 300 MHz after considering realistic noise, depending on the dynamic range of the system. Conclusions: These results point to the tremendous opportunities in further development of high bandwidth FD-HD-DOT system hardware for applications in human brain mapping.
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Affiliation(s)
- Weihao Fan
- Washington University, Department of Physics, St. Louis, Missouri, United States
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Adam T. Eggebrecht
- Washington University School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
- Washington University, Department of Biomedical Engineering, St. Louis, Missouri, United States
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Wearable, Integrated EEG-fNIRS Technologies: A Review. SENSORS 2021; 21:s21186106. [PMID: 34577313 PMCID: PMC8469799 DOI: 10.3390/s21186106] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 09/01/2021] [Accepted: 09/04/2021] [Indexed: 02/04/2023]
Abstract
There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG–fNIRS can provide a comprehensive picture of brain electrical and hemodynamic function and has been applied across various fields of brain science. The development of wearable, mechanically and electrically integrated EEG–fNIRS technology is a critical next step in the evolution of this field. A suitable system design could significantly increase the data/image quality, the wearability, patient/subject comfort, and capability for long-term monitoring. Here, we present a concise, yet comprehensive, review of the progress that has been made toward achieving a wearable, integrated EEG–fNIRS system. Significant marks of progress include the development of both discrete component-based and microchip-based EEG–fNIRS technologies; modular systems; miniaturized, lightweight form factors; wireless capabilities; and shared analogue-to-digital converter (ADC) architecture between fNIRS and EEG data acquisitions. In describing the attributes, advantages, and disadvantages of current technologies, this review aims to provide a roadmap toward the next generation of wearable, integrated EEG–fNIRS systems.
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He L, Zhang J, Yu T, Du Y, Liu X, He W. Transcranial Sonography in the Diagnosis of Pituitary Tumor-A Direct Comparison With MRI. Front Endocrinol (Lausanne) 2021; 12:778839. [PMID: 34925240 PMCID: PMC8679660 DOI: 10.3389/fendo.2021.778839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 11/05/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Transcranial sonography (TCS) is a convenient tool for detecting certain brain diseases, such as brain tumors. Few studies have reported on the use of TCS in the area of Sella turcica. The accuracy and repeatability of Sella turcica with or without pituitary tumor is not clear. PURPOSE This study aimed to investigate the feasibility and accuracy of TCS to measure the size of Sella turcica according to the measurement in MRI and determine its diagnostic performance in individuals with pituitary tumor. MATERIALS AND METHODS In this cross-sectional comparative study, healthy volunteers and patients with pituitary tumor were enrolled for examination of TCS and MRI between October 2020 and July 2021. The transverse diameter (D1, cm) of Sella turcica and the volume of the pituitary tumor were measured by TCS and MRI, respectively, and compared by using Student's t-test or Mann-Whitney test, using the receiver operating characteristic (ROC) curve to analyze the diagnostic value of D1 in TCS for pituitary tumor. RESULTS A total of 75 healthy volunteers and 51 patients with pituitary tumor were evaluated. In healthy volunteers, the mean D1 was 1.30 ± 0.35 (range, 0.82-3.22) by TCS and 1.32 ± 0.29 (range, 0.94-3.02) by MRI (P = 0.054). In patients with pituitary tumor, the mean D1 was 2.0 ± 0.65 (range, 0.90-3.48) by TCS and 2.42 ± 1.0 (range, 0.80-4.70) by MRI (P = 0.000). The median measurement volume was 4.41 and 6.59 cm3 in TCS and MR, respectively (P = 0.000). The mean D1 was 1.31 ± 0.35 in healthy volunteers and 2.0 ± 0.65 cm in patients with pituitary tumor (P = 0.000). In the ROC curve analysis, the area under the curve was 0.836, and the optimal cutoff value (1.56) exhibited a sensitivity and specificity of 67.31 and 88.0%, respectively. CONCLUSION The consistency between the two imaging technologies performed well in D1 measurement, while the volume of the pituitary tumor was smaller as assessed by TCS than by MRI. D1 in TCS had good diagnostic performance in pituitary tumor.
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Affiliation(s)
- Lei He
- Department of Ultrasound, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jinghan Zhang
- Department of Ultrasound, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tengfei Yu
- Department of Ultrasound, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yue Du
- Department of Ultrasound, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xinyao Liu
- Department of Ultrasound, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wen He
- Department of Ultrasound, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- *Correspondence: Wen He,
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