We have developed a novel (patent pending) electric field measurement technology called Electric Field Encephalography (EFEG) for brain signal monitoring. NeuroFieldz technology is comprised of a system of high density array of sensors for measuring and analyzing the electric fields generated by the brain arising from intrinsic activity or external stimuli. The EFEG brain monitoring technique is a new modality that has several advantages over the current modalities, electroencephalography EEG (which measures the electric potential on the scalp) and magnetoencephalography MEG (which measures the magnetic field). Compared with MEG, EFEG has higher spatial resolution, is unaffected by stray magnetic fields, and does not require expensive bulky cryogenic equipment, thus making it field-deployable. Compared with EEG, EFEGTM is reference-less, has higher spatial resolution, leads to increased number of uncorrelated signals, and improves source reconstruction precision. EFEG also provides dynamical information on millisecond time scales which is much faster than fMRI. The accurate source localization provided by EFEG will be of immense benefit in analyzing and localizing neurological signals (e.g. epileptic), as well as understanding the brains response to external stimuli
Related Publications
Versek, Craig; Banijamali, S Mohammad Ali; Bex, Peter; Lashkari, Kameran; Kamarthi, Sagar; Sridhar, Srinivas Portable diagnostic system for age-related macular degeneration screening using visual evoked potentials Journal Article In: Eye and brain, pp. 111–127, 2021. Tags: Neurotechnology Versek, Craig William; Banijamali, Mohammad Ali S; Bex, Peter J; Lashkari, Kameran; Kamarthi, Sagar V; Sridhar, Srinivas Portable Objective Diagnostics using Visual Evoked Potentials for Age-related Macular Degeneration Journal Article In: medRxiv, 2020. Abstract | Tags: Neurotechnology, Opthalmology Versek, Craig; Banijamali, S Mohammad Ali; Bex, Peter J; Lashkari, Kameran; Kamarthi, Sagar V; Sridhar, Srinivas Portable Objective Diagnostics using Visual Evoked Potentials for Age-related Macular Degeneration Journal Article In: medRxiv, pp. 2020–01, 2020. Tags: Neurotechnology Sridhar, Srinivas; Versek, Craig; Bex, Peter Portable brain and vision diagnostic and therapeutic system Miscellaneous 2019, (US Patent App. 16/347,049). Abstract | Tags: Neurotechnology, Opthalmology Sridhar, Srinivas; Versek, Craig; Banijamali, Ali; Tran, Anthony; Cardozo, Armando; Lashkari, Kameran; Bex, Peter Portable VEP Diagnostics for NeuroVisual Disorders Journal Article In: Investigative Ophthalmology & Visual Science, vol. 60, no. 9, pp. 3591–3591, 2019. Abstract | Tags: Neurotechnology Sridhar, Srinivas; Petrov, Yury; Yavuzcetin, Ozgur Electric field encephalography: electric field based brain signal detection and monitoring Miscellaneous 2016, (US Patent App. 14/420,613). Abstract | Tags: Neurotechnology Petrov, Yury; Nador, Jeffrey; Hughes, Christopher; Tran, Stanley; Yavuzcetin, Ozgur; Sridhar, Srinivas Ultra-dense EEG sampling results in two-fold increase of functional brain information Journal Article In: Neuroimage, vol. 90, pp. 140–145, 2014. Abstract | Tags: Neurotechnology Petrov, Yury; Sridhar, Srinivas Electric Field Encephalography: Electric fields and their application to functional brain imaging. Journal Article In: 2013. Abstract | Tags: Neurotechnology Petrov, Yury; Sridhar, Srinivas Electric field encephalography as a tool for functional brain research: a modeling study Journal Article In: PloS one, vol. 8, no. 7, 2013. Abstract | Tags: Nanomedicine, Neurotechnology@article{versek2021portable,
title = {Portable diagnostic system for age-related macular degeneration screening using visual evoked potentials},
author = {Craig Versek and S Mohammad Ali Banijamali and Peter Bex and Kameran Lashkari and Sagar Kamarthi and Srinivas Sridhar},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Eye and brain},
pages = {111–127},
publisher = {Taylor & Francis},
keywords = {Neurotechnology},
pubstate = {published},
tppubtype = {article}
}
@article{versek2020portable,
title = {Portable Objective Diagnostics using Visual Evoked Potentials for Age-related Macular Degeneration},
author = {Craig William Versek and Mohammad Ali S Banijamali and Peter J Bex and Kameran Lashkari and Sagar V Kamarthi and Srinivas Sridhar},
year = {2020},
date = {2020-01-01},
journal = {medRxiv},
publisher = {Cold Spring Harbor Laboratory Press},
abstract = {Delayed Dark Adapted vision Recovery (DAR) is a biomarker for Age-related Macular Degeneration (AMD); however, its measurement is burdensome for patients and examiners. We developed a portable, wireless, quick-setup system that employs a headset with a smartphone to deliver and analyze controlled dichoptic photobleach and pattern reversal stimuli, and with custom electroencephalography (EEG) electrodes, to measure objective Dark Adapted Visual Evoked Potentials (DAVEP) at multiple locations of the visual field in one comfortable 20-minute session, without requiring subject reporting. DAVEP responses post photobleach (up to 15 minutes), were measured concurrently in both eyes of 13 patients with AMD and 8 others not diagnosed with AMD. New unexpected features were observed in the DAVEP responses at high latencies to scotopic stimulus intensities. The amplitude recovery of the DAVEP response was significantly delayed in AMD patients compared with controls. We developed DAVEP1 scores, a simple metric for DAR, using it to successfully identify all 100% of AMD subjects and correctly classify 90% of subject eyes. Deficits in DAR in patients with AMD can be identified with this objective VEP based system using the DAVEP1 metric, a promising new objective biomarker for this disease that can be easily tested in a clinic.},
keywords = {Neurotechnology, Opthalmology},
pubstate = {published},
tppubtype = {article}
}
@article{versek2020portableb,
title = {Portable Objective Diagnostics using Visual Evoked Potentials for Age-related Macular Degeneration},
author = {Craig Versek and S Mohammad Ali Banijamali and Peter J Bex and Kameran Lashkari and Sagar V Kamarthi and Srinivas Sridhar},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {medRxiv},
pages = {2020–01},
publisher = {Cold Spring Harbor Laboratory Press},
keywords = {Neurotechnology},
pubstate = {published},
tppubtype = {article}
}
@misc{sridhar2019portableb,
title = {Portable brain and vision diagnostic and therapeutic system},
author = {Srinivas Sridhar and Craig Versek and Peter Bex},
year = {2019},
date = {2019-10-01},
abstract = {A portable wireless neuromonitoring device can be used to diagnose and/or treat conditions of the brain and vision system. The device includes a sensor unit mountable on the head of a human subject and capable of recording signals from the brain in EEG and/or EFEG (electric field encephalography) mode, and the device can be used for simultaneous stimulus display and recording with latency of less than 1 millisecond. The device also includes electrodes that allow rapid set-up and measurement with low impedance contact with the scalp. The device can also be used in conjunction with virtual reality or alternate reality environments.},
note = {US Patent App. 16/347,049},
keywords = {Neurotechnology, Opthalmology},
pubstate = {published},
tppubtype = {misc}
}
@article{sridhar2019portable,
title = {Portable VEP Diagnostics for NeuroVisual Disorders},
author = {Srinivas Sridhar and Craig Versek and Ali Banijamali and Anthony Tran and Armando Cardozo and Kameran Lashkari and Peter Bex},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
journal = {Investigative Ophthalmology & Visual Science},
volume = {60},
number = {9},
pages = {3591--3591},
publisher = {The Association for Research in Vision and Ophthalmology},
abstract = {Purpose: Visual Evoked Potentials (VEPs) provide objective neuro-opthalmologic assessments that avoid patient task performance but utilizes invasive and cumbersome apparatus. We have developed a system that combines a scalp neuroelectric potential and field sensor with a smartphone in a portable wireless display headset called the NeuroDotVR (Figure 1). The system records VEPs and Fields (VEPF) in response to dichoptic stimuli presented on the smartphone display for a range of neuro-oplthalmologic disorders. We evaluate the NeuroDotVR for Dark Adaptation Recovers (DAR), a key biomarker for age-related macular degeneration (AMD).
Methods: DAR was measured simultaneously in both eyes of# patients with AMD and# age-matched controls. Following a 60s photobleach (400 cd/m 2 white cellphone screen), recovery of visual sensitivity was recorded with VEPFs to pattern reversal checkerboard …},
keywords = {Neurotechnology},
pubstate = {published},
tppubtype = {article}
}
Methods: DAR was measured simultaneously in both eyes of# patients with AMD and# age-matched controls. Following a 60s photobleach (400 cd/m 2 white cellphone screen), recovery of visual sensitivity was recorded with VEPFs to pattern reversal checkerboard …@misc{sridhar2016electric,
title = {Electric field encephalography: electric field based brain signal detection and monitoring},
author = {Srinivas Sridhar and Yury Petrov and Ozgur Yavuzcetin},
year = {2016},
date = {2016-03-01},
abstract = {Systems and methods for measuring brain activity of a subject are disclosed, comprising: positioning a plurality of electric field sensors at multiple positions on the exterior of a skull of the subject; measuring one to three components of a plurality of instantaneous electric field vectors generated by a plurality of electric field sources, the electric field vectors being measured by the plurality of electric field sensors; and determining brain activity of the subject based on the measurement of the plurality of instantaneous electric field vectors.},
note = {US Patent App. 14/420,613},
keywords = {Neurotechnology},
pubstate = {published},
tppubtype = {misc}
}
@article{petrov2014ultra,
title = {Ultra-dense EEG sampling results in two-fold increase of functional brain information},
author = {Yury Petrov and Jeffrey Nador and Christopher Hughes and Stanley Tran and Ozgur Yavuzcetin and Srinivas Sridhar},
year = {2014},
date = {2014-01-01},
journal = {Neuroimage},
volume = {90},
pages = {140--145},
publisher = {Academic Press},
abstract = {We used an ultra-density electroencephalography (ud-EEG) sensor array with improved electrical characteristics to reveal unexpected strong potential variation at 1 cm scale. A new classification paradigm demonstrates that ud-EEG provides twice the signal to noise ratio for data classification compared with contemporary hd-EEG. These results suggest a paradigm shift from current thinking by showing that higher spatial resolution sampling of EEG is required and leads to increased functional brain information that is useful for diverse neurological applications. Contemporary high-density electroencephalographic systems (hd-EEG) comprising up to 256 electrodes have inter-electrode separations of 2–4 cm. Because electric currents of the brain are believed to strongly diffuse before reaching the scalp surface, higher-density electrode coverage is often deemed unnecessary. We used an ultra-dense electroencephalography (ud-EEG) sensor array to reveal strong potential variation at 1 cm scale and discovered that it reflects functional brain activity. A new classification paradigm demonstrates that ud-EEG provides twice the signal to noise ratio for brain-response classification compared with contemporary hd-EEG. These results suggest a paradigm shift from current thinking by showing that higher spatial resolution sampling of EEG is required and leads to increased functional brain information that is useful for diverse neurological applications.},
keywords = {Neurotechnology},
pubstate = {published},
tppubtype = {article}
}
@article{petrovelectric,
title = {Electric Field Encephalography: Electric fields and their application to functional brain imaging.},
author = {Yury Petrov and Srinivas Sridhar},
year = {2013},
date = {2013-07-03},
abstract = {We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2–3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision
},
keywords = {Neurotechnology},
pubstate = {published},
tppubtype = {article}
}
@article{petrov2013electric,
title = {Electric field encephalography as a tool for functional brain research: a modeling study},
author = {Yury Petrov and Srinivas Sridhar},
year = {2013},
date = {2013-01-01},
journal = {PloS one},
volume = {8},
number = {7},
publisher = {Public Library of Science},
abstract = {We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2–3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.},
keywords = {Nanomedicine, Neurotechnology},
pubstate = {published},
tppubtype = {article}
}
