# US 10,945,627 B2 · Systems and methods for super-resolving electromagnetic localization and causality > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,945,627 B2 - Document ID: US10945627B2 - Status: Granted - Kind: B2 - Application number: 16/017,400 - Filed: 2018-06-25 - Published: 2019-01-10 - Granted: 2021-03-16 - Earliest claimed: 2016-01-21 - Assignees: Truust Neuroimaging, Inc. - Applicants: TRUUST NEUROIMAGING, Inc. - Inventors: Henrik D. Kjeldsen; Lars H. Bredvig - Web page: https://patentgrep.com/patent/US10945627B2 ## CPC - A61B 5/4064: {Evaluating the brain (for intracranial pressure A61B5/031; for cerebral blood gases A61B5/14553; using EEG A61B5/369)} - A61B 5/245: specially adapted for magnetoencephalographic [MEG] signals - A61B 5/7235: {Details of waveform analysis (detecting specific parameters of the electrocardiograph cycle A61B5/349)} - A61N 1/0529: {Electrodes for brain stimulation} - G01R 33/323: {Detection of MR without the use of RF or microwaves, e.g. force-detected MR, thermally detected MR, MR detection via electrical conductivity, optically detected MR} - A61B 5/372: Analysis of electroencephalograms - G06F 2218/22: Source localisation; Inverse modelling - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - A61N: ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY (measurement of bioelectric currents A61B; surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body A61B18/00; anaesthetic apparatus in general A61M; incandescent lamps H01K; infrared radiators for heating H05B) - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Systems and methods are described for super-resolving electromagnetic localization by obtaining electric field data and/or magnetic field data captured over a period of time by at least one multi-channel recording device having a first resolution, applying holographic backpropagation constrained by sparsity approximation and/or low-rank approximation in a near-field and/or a far-field to the captured data, reconstructing electromagnetic energy flow information at a second resolution in one iteration, the second resolution being higher than the first resolution in at least two of three spatial dimensions, and generating data indicating an energy source location, an energy sink location, and/or a causality relation based on the electromagnetic energy flow information at the second resolution. ## Claims ### Claim 1 A system for super-resolving electromagnetic neuroimaging, the system comprising: at least one multi-channel recording device for capturing data including at least one of electric field data and magnetic field data in neural tissue of a subject over a period of time, the at least one multi-channel recording device having a first resolution; at least one memory to record the captured data and to store processor executable instructions; and at least one processor coupled to the at least one multi-channel recording device and the at least one memory, wherein upon execution of the processor executable instructions by the at least one processor, the at least one processor: applies holographic backpropagation to the captured data, the holographic backpropagation constrained by at least one of sparsity and low-rank approximation in at least one of a near-field and a far-field; reconstructs electromagnetic energy flow information at a second resolution in one iteration, the electromagnetic energy flow information comprising a Poynting vector, the second resolution being higher than the first resolution in at least two of three spatial dimensions; and generates, based on the electromagnetic energy flow information at the second resolution, data indicating at least one of a neural energy source location, a neural energy sink location, and a neural causality relation. ### Claim 2 (depends on 1) The system of claim 1, wherein the neural causality relation distinguishes contact-based neural transmission and field-based neural transmission. ### Claim 3 (depends on 1) The system of claim 1, wherein the at least one multi-channel recording device includes a near-field multi-channel recording device. ### Claim 4 (depends on 1) The system of claim 1, wherein the at least one multi-channel recording device includes a far-field multi-channel recording device. ### Claim 5 (depends on 1) The system of claim 1, wherein the at least one multi-channel recording device includes at least one of a microelectrode array (MEA) device, an electroencephalography (EEG) device, an electrocorticography (ECoG) device, and a magnetoencephalography (MEG) device. ### Claim 6 (depends on 1) The system of claim 1, wherein the electromagnetic energy flow information comprises more than one Poynting vector. ### Claim 7 (depends on 1) The system of claim 1, wherein the causality relation is a flow direction of the Poynting vector field. ### Claim 8 A system for super-resolving electromagnetic localization, the system comprising: at least one multi-channel recording device for capturing data including at least one of electric field data and magnetic field data over a period of time, the at least one multi-channel recording device having a first resolution; at least one memory to record the captured data and to store processor executable instructions; and at least one processor coupled to the at least one multi-channel recording device and the at least one memory, wherein upon execution of the processor executable instructions by the at least one processor, the at least one processor: applies holographic backpropagation to the captured data, the holographic backpropagation constrained by at least one of sparsity and low-rank approximation in at least one of a near-field and a far-field; reconstructs electromagnetic energy flow information at a second resolution in one iteration, the electromagnetic energy flow information comprising a Poynting vector, the second resolution being higher than the first resolution in at least two of three spatial dimensions; and generates, based on the electromagnetic energy flow information at the second resolution, data indicating at least one of an energy source location, an energy sink location, and a causality relation. ### Claim 9 A system for super-resolving electromagnetic localization, the system comprising: at least one communication interface; at least one memory to record the captured data and to store processor executable instructions; and at least one processor coupled to the at least one communication interface and the at least one memory, wherein upon execution of the processor executable instructions by the at least one processor, the at least one processor: obtains, via the at least one communication interface, the captured data including at least one of electric field data and magnetic field data captured over a period of time by at least one multi-channel recording device, the at least one multi-channel recording device having a first resolution; applies holographic backpropagation to the captured data, the holographic backpropagation constrained by at least one of sparsity and low-rank approximation in at least one of a near-field and a far-field; reconstructs electromagnetic energy flow information at a second resolution in one iteration, the electromagnetic energy flow information comprising a Poynting vector, the second resolution being higher than the first resolution in at least two of three spatial dimensions; and generates, based on the electromagnetic energy flow information at the second resolution, data indicating at least one of an energy source location, an energy sink location, and a causality relation. ### Claim 10 A method for super-resolving electromagnetic neuroimaging, the method comprising: obtaining captured data including at least one of electric field data and magnetic field data from neural tissue of a subject over a period of time by at least one multi-channel recording device, the at least one multi-channel recording device having a first resolution; applying, via at least one processor, holographic backpropagation to the captured data, the holographic backpropagation constrained by at least one of sparsity and low-rank approximation in at least one of a near-field and a far-field; reconstructing, via the at least one processor, electromagnetic energy flow information at a second resolution in one iteration, the electromagnetic energy flow information comprising a Poynting vector, the second resolution being higher than the first resolution in at least two of three spatial dimensions; and generating, via the at least one processor, data indicating at least one of a neural energy source location, a neural energy sink location, and a neural causality relation based on the electromagnetic energy flow information at the second resolution. ### Claim 11 (depends on 10) The method of claim 10, wherein the neural causality relation distinguishes contact-based neural transmission and field-based neural transmission. ### Claim 12 (depends on 10) The method of claim 10, further comprising: capturing, via the at least one multi-channel recording device, the captured data including at least one of electric field data and magnetic field data. ### Claim 13 (depends on 10) The method of claim 10, wherein the at least one multi-channel recording device includes a near-field multi-channel recording device. ### Claim 14 (depends on 10) The method of claim 10, wherein the at least one multi-channel recording device includes a far-field multi-channel recording device. ### Claim 15 (depends on 10) The method of claim 10, wherein the at least one multi-channel recording device includes at least one of a microelectrode array (MEA) device, an electroencephalography (EEG) device, an electrocorticography (ECoG) device, and a magnetoencephalography (MEG) device. ### Claim 16 (depends on 10) The method of claim 10, wherein the electromagnetic energy flow information comprises at least one Poynting vector. ### Claim 17 (depends on 10) The method of claim 10, wherein the causality relation is a flow direction of the Poynting vector field. ### Claim 18 A method for super-resolving electromagnetic localization, the method comprising: obtaining captured data including at least one of electric field data and magnetic field data captured over a period of time by at least one multi-channel recording device, the at least one multi-channel recording device having a first resolution; applying holographic backpropagation to the captured data, the holographic backpropagation constrained by at least one of sparsity and low-rank approximation in at least one of a near-field and a far-field; reconstructing electromagnetic energy flow information at a second resolution in one iteration, the electromagnetic energy flow information comprising a Poynting vector, the second resolution being higher than the first resolution in at least two of three spatial dimensions; and generating data indicating at least one of an energy source location, an energy sink location, and a causality relation based on the electromagnetic energy flow information at the second resolution.