Brain activity measuring device

Abstract

[Problem] The purpose of the present invention is to provide a brain activity measurement device capable of measuring brain activity across a wide area. [Solution] A brain activity measurement device provided with: a brain diagnosis probe; a detection signal receiving unit for receiving a detection signal generated by the brain diagnosis probe; and a signal analysis unit for analyzing the detection signal received by the detection signal reception unit and obtaining measurement information for measuring brain activity, in which the brain diagnosis probe has a plurality of sheet-like probe parts which are each provided in the skull of a subject organism through a hole provided in the skull.

Description

Technical Field

[0001] This invention relates to a brain activity measurement device. More specifically, it relates to a brain activity measurement device capable of measuring brain activity over a wide area, suitable for using calcium-sensitive fluorescent proteins or photogenes for brain activity measurement. Background Technology

[0002] Japanese Patent No. 3718500 discloses a probe and device for measuring the characteristics of hemodynamics and oxygenation in the brain. This device uses a probe with optical fibers. Therefore, this device can only measure brain activity at sites where optical fibers are laid.

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent No. 3718500 Summary of the Invention

[0006] The problem that the invention aims to solve

[0007] The purpose of this invention is to provide a brain activity measuring device that can measure brain activity over a wide area.

[0008] Another objective of this invention, different from the above, is to provide a brain activity measurement device 1 suitable for measuring brain activity using calcium-sensitive fluorescent proteins or photogenes.

[0009] The purpose of this invention is to solve any of the above-mentioned problems.

[0010] Technical solutions to the problem

[0011] The above-mentioned research is basically based on the following insight: by using multiple thin-film probes, thin-film probes can be placed inside the brain, resulting in the measurement of brain activity over a wide area, and is also suitable for measuring brain activity using calcium-sensitive fluorescent proteins or photogenes.

[0012] The brain activity measurement device 1 described in this specification includes a brain diagnostic probe 3, a detection signal receiving unit 5, and a signal analysis unit 7.

[0013] The brain diagnostic probe 3 has multiple thin probe sections 9. The multiple thin probe sections 9 are then disposed within the skull 11 through holes 13 provided in the skull 11 of the target organism.

[0014] The detection signal receiving unit 5 is a component used to receive the detection signal generated by the brain diagnostic probe 3.

[0015] The signal analysis unit 7 is a component used to analyze the detection signal received by the detection signal receiving unit 5 and obtain measurement information for measuring brain activity.

[0016] Preferably, the multiple thin-film probes each have one or two corresponding undulations of the brain parenchyma and vascular system at the site of application.

[0017] A preferred embodiment of the brain activity measuring device 1 is that the multi-piece thin-film probe portion 9 has at least one shape that is laid in the subdural space, subarachnoid space, ventricular wall and sulci of the target organism.

[0018] A preferred embodiment of the brain activity measuring device 1 is that the multi-sheet thin probe portion 9 has a shape that covers an area of ​​1% to 90% of the brain of the target organism.

[0019] A preferred embodiment of the brain activity measuring device 1 is that at least one of the multiple thin-film probe sections 9 has a first light source 15, a first detection section 17, and a first light control section 19 for controlling the light output from the first light source 15. The first light source 15 is preferably used to excite luminescent substances contained in the brain.

[0020] In a preferred embodiment of the brain activity measuring device 1, at least one of the multiple thin-film probe sections 9 has a second light source 21, which has a wavelength different from that of the first light source 15. The second light source 21 is then used to measure the brain of the subject organism.

[0021] In a preferred embodiment of the brain activity measurement device 1, the signal analysis unit 7 uses machine learning to analyze the brain activity of the target organism and obtain the target organism's intention information. Then, this brain activity measurement device 1 further includes an intention information output unit 23 that outputs intention information.

[0022] A preferred example of the brain activity measurement device 1 is that the signal analysis unit 7 uses machine learning to analyze the activity of nerve cells in the target organism.

[0023] A preferred embodiment of the brain activity measuring device 1 is that the nerve cells of the target organism emit light due to predetermined light stimulation by gene introduction or the introduction of luminescent substances.

[0024] A preferred embodiment of the brain activity measurement device 1 further includes a wireless output unit 25, which is used to wirelessly output detection signals or measurement information to the outside of the target organism.

[0025] A preferred embodiment of the brain activity measuring device 1 further includes: a deep brain stimulation electrode 31; a power supply unit 33 that supplies power to the deep brain stimulation electrode 31; and a power supply control unit 35 that controls the power supply of the power supply unit 33.

[0026] The effects of the invention

[0027] The brain activity measurement device of the present invention can be deployed over a wide area of ​​the brain by using multiple thin-film probes, resulting in the measurement of brain activity over a wide area, and is suitable for brain activity measurement using calcium-sensitive fluorescent proteins or photogenes. Attached Figure Description

[0028] [ Figure 1 ] Figure 1 This is a block diagram used to illustrate a brain activity measurement device.

[0029] [ Figure 2 ] Figure 2 This is a conceptual diagram illustrating an example of the deployment of probes used for brain diagnosis.

[0030] [ Figure 3 ] Figure 3 This is a diagram showing an example of a thin-film probe section.

[0031] [ Figure 4 ] Figure 4 This is a conceptual diagram showing the fluorescence emitted by the fluorescent substance detected by the first detection unit.

[0032] [ Figure 5 ] Figure 5 This is a conceptual diagram illustrating a design example of a circuit on a thin-film probe section having a first and a second light source. Detailed Implementation

[0033] Hereinafter, the embodiments for carrying out the present invention will be described with reference to the accompanying drawings. The present invention is not limited to the embodiments described below, but also includes appropriate modifications that can be made from the embodiments as will be understood by those skilled in the art.

[0034] Figure 1 This is a block diagram used to illustrate a brain activity measurement device. (Example) Figure 1 As shown, the brain activity measuring device 1 includes a brain diagnostic probe 3, a detection signal receiving unit 5, and a signal analysis unit 7. The brain diagnostic probe 3 is an essential component for insertion into the skull (the space between the skull and the brain surface, the subdural space) to perform brain diagnosis. The brain diagnostic probe 3 is, for example, described in Japanese Patent No. 3718500 or Japanese Patent No. 5224482, and is prior art.

[0035] Figure 2 This is a conceptual diagram illustrating an example of the deployment of probes used for brain diagnosis. For example... Figure 2As shown, the brain diagnostic probe 3 has multiple thin probe sections 9. These multiple thin probe sections 9 are then positioned within the skull 11 of the target organism through holes 13 provided in the skull 11. There may be one or more holes 13. The holes 13 may be located on the side, the back, or the upper part of the skull. Figure 2 In the example, two holes are provided. The number of sheets of the thin-film probe portion 9 can be two to one hundred, three to fifty, or four to twenty. The target organism is an animal, preferably a human or a mammal other than a human. Humans are preferred as the target organism.

[0036] The multi-piece thin-film probe section 9 is preferably shaped to cover an area of ​​1% to 90% of the brain of the target organism. Here, the term "brain area" refers to the area between the cerebrum and the skull. The area of ​​the brain covered by the multi-piece thin-film probe section 9 can be 5% to 90%, 10% to 90%, 15% to 80%, 20% to 50%, 20% to 40%, or 30% to 70%.

[0037] Figure 3 This is a diagram showing an example of a thin-film probe section. Figure 3 (a) indicates a thin, rectangular probe. Figure 3 (b) indicates a thin-film probe with a rounded tip. Figure 3 (c) indicates a thin-film probe with a chamfered front end. Figure 3 (d) indicates a thin, sheet-like probe that narrows towards the front and becomes rounded at the very tip. For example... Figure 3 As shown, the sheet-like probe portion 9 can be short and rectangular, or it can have a tapered tip for easy insertion into the brain. The sheet-like probe portion 9 can also have a rounded tip and chamfered corners. Preferably, the sheet-like probe portion 9 is flexible and sheet-like. Furthermore, the sheet-like probe portion 9 is preferably intended to be laid between the skull and the brain surface, particularly along the cerebral cortex. Thus, the sheet-like probe portion 9 preferably has excellent biocompatibility. The sheet-like probe portion 9 preferably has the following properties: a certain degree of flexibility and rigidity; although it has the property of adhering tightly to water, it does not adhere to the brain surface and can be removed from the brain surface.

[0038] Preferably, the multiple thin-film probe portions each have one or two undulations corresponding to the undulations of the brain parenchyma and the vascular system at the site of application. Since the brain contains various sites, such as the frontal lobe, parietal lobe, temporal lobe, and occipital lobe, the thin-film probe portions 9 can be applied to each site. Furthermore, the thin-film probe portions 9 can be shaped to conform to the site of application. Examples of the width W (length of the widest portion) of the thin-film probe portion 9 are 0.5 cm to 6 cm, or 1 cm to 5 cm, or 1 cm to 4 cm, or 1 cm to 3 cm, or 2 cm to 4 cm. Examples of the length L (length of the longest portion) of the thin-film probe portion 9 are 2 cm to 20 cm, or 4 cm to 15 cm, or 5 cm to 10 cm.

[0039] For example, multiple sheet-like probe portions 9 have been determined to be laid at predetermined locations. For example, each sheet-like probe portion 9 preferably has at least one shape or property suitable for laying in the cerebral cortex, ventricles, subdural space, subarachnoid space, ventricular walls, and sulci of the target organism. Then, each of the multiple sheet-like probe portions 9 has undulations (concavities and convexities) corresponding to any one or two of the undulations of the brain parenchyma and vascular system at the predetermined location where it is laid, thus allowing it to be as close as possible to the brain parenchyma and in close contact. For example, the undulations of the brain parenchyma or vascular system can be carefully examined beforehand using CT or MRI, and the undulations and convexities corresponding to their shapes can be customized. In this example, only the following steps are required: a brain surface shape acquisition step, which is a step of acquiring any one or two of the undulations of the brain parenchyma and vascular system (brain surface undulation information) at the location of the target organism containing the predetermined location where the sheet-like probe portions 9 are laid; and a surface adjustment sheet-like probe portion manufacturing step, which obtains a sheet-like probe portion 9 having a surface shape based on the brain surface undulation information. The brain surface shape acquisition process can be performed using methods similar to CT or MRI that can acquire brain shape. The obtained brain surface undulation information can then be appropriately stored in a storage unit. Next, in the process of manufacturing the sheet-like probe section, the brain surface undulation information is read from the storage unit, and the surface shape of the sheet-like probe section is adjusted. For example, after setting the necessary components or circuits for functioning as a sheet-like probe section on a flexible substrate, resin is applied to its surface to form the sheet-like probe section 9. Then, when applying resin to the flexible substrate, the surface shape of the sheet-like probe section 9 is adjusted based on the brain surface undulation information to obtain a sheet-like probe section 9 whose surface shape corresponds to the undulations of the brain parenchyma or the vascular system. This processing can be achieved, for example, using a 3D printer. Alternatively, after forming a resin layer on the flexible substrate, the resin layer can be processed based on the brain surface undulation information to obtain a sheet-like probe section 9 whose surface shape corresponds to the undulations of the brain parenchyma or the vascular system.

[0040] Thin-film probes can also use flexible printed circuit boards (PCBs). From the viewpoint of biocompatibility, a flexible PCB with copper foil on its surface is preferred. Examples of such flexible PCBs are described in Japanese Patent Nos. 7194857 and 7164752. With a flexible PCB, flexibility can be maintained while the light source, detection unit, control unit (and storage unit), etc., described later, can be mounted on the substrate. Ideally, the flexible PCB should have a coating that covers its entire surface. This is to avoid leaving light sources or components in the brain, or damaging the brain surface. To allow light to pass through, the coating is preferably transparent or translucent.

[0041] A preferred embodiment of the brain activity measuring device 1 is that at least one (preferably all) of the multiple sheet-like probe portions 9 has a first detection unit 17. The sheet-like probe portions 9 may also have a first light source 15, the first detection unit 17, and a first light control unit 19 for controlling the light output from the first light source 15. The first detection unit 17 is used to detect signals related to brain activity. The first light source 15 can then be used to excite luminescent substances contained in the brain. In this example, for instance, luminescent substances are introduced into the brain of the target organism. Thus, the nerve cells of the target organism preferably emit light upon predetermined light stimulation by gene introduction or the introduction of luminescent substances. Examples of luminescent substances are fluorescent proteins. Examples of fluorescent proteins are green fluorescent protein (e.g., GFP), red fluorescent protein (e.g., DsRed), and calcium-sensitive fluorescent protein (GECI). Calcium-sensitive fluorescent protein is a fluorescent protein that is sensitive to calcium. For example, the nerve cells of the target organism are introduced with luminescent substances (GECI). Examples of GECIs include GCaMP proteins (GCaMP3, GCaMP6s, GCaMP7, and RCaMP1) and jellyfish protein (Equinine). Of course, the use of GECIs invented in the future is also acceptable. Methods for introducing GECIs, such as those described in Japanese Patent No. 5854686, are existing technologies. When GECIs are introduced, if the brain is activated, the GECIs will emit light in response to changes in calcium. For example, GECIs contained in brain nerve cells emit light. Thus, compared to methods such as functional near-infrared spectroscopy or optical topological examination, methods using luminescent substances to measure brain function can accurately and rapidly measure brain function.

[0042] Each sheet-shaped probe portion 9 may also have multiple first light sources 15. A first light control unit 19 controls the light intensity and ON / OFF state of the first light sources 15. The first light control unit 19 may also receive control commands from a control unit 20 and control the first light sources 15 according to the control commands. The control unit 20 may, for example, be implemented using a computer or processor. Information for controlling the first light sources 15 may also be output to the first light control unit 15 based on measurement information obtained from the signal analysis unit 7. The descriptions of control unit 19 and control unit 20 are functional descriptions; both may be physically identical. Furthermore, the first light control unit 19 may store a program and control the first light sources 15 based on the instructions of the program. The first light control unit 19 may also control multiple first light sources 15. Multiple first light sources 15 may, for example, be arranged at equal intervals on the sheet-shaped probe portion 9. Examples of first light sources 15 are light-emitting diodes (LEDs) and LEDs. The output of the first light source 15 is preferably of an intensity that will not damage the brain. The wavelength of the light output by the first light source 15 is preferably a wavelength corresponding to the luminescent material. By using the first light source 15, fluorescent materials can be excited. An example of the first light source 15 is visible light, preferably a light source emitting light with a wavelength of 400 nm to 600 nm. The light from the first light source 15 may be, for example, pulsed light or continuous light.

[0043] An example of the first detection unit 17 is a light sensor. The first detection unit 17 can also measure physical quantities other than light that are related to brain activity. The first detection unit 17 can also detect the emission of light from a luminescent substance. The first detection unit 17 can detect the reflected light after the first light source 15 illuminates it, and it can also detect the light emitted by the luminescent substance in response to the illumination of the first light source 15. An example of the first detection unit 17 is a photodiode (PD). Each sheet-like probe portion 9 preferably has multiple first detection units 17.

[0044] Figure 4 This is a conceptual diagram illustrating how the first detection unit detects the fluorescence emitted by the fluorescent substance. In this example, for instance, light emitted from the first light source 15 excites GECIs that have been introduced into the nerve cells. Then, the first detection unit 17 detects the light emitted by the excited GECIs (arrows).

[0045] The light signal detected by the first detection unit 17 is converted into a detection signal and output to the detection signal receiving unit 5. The process of converting the light signal into a detection signal and outputting the detection signal to the detection signal receiving unit 5 can be performed by the first detection unit 17, for example. A typical photodiode can perform this process. The detection signal receiving unit 5 is connected in a manner that allows it to receive signals from the brain diagnostic probe 3. The detection signal receiving unit 5 can also be installed inside the brain along with the brain diagnostic probe 3. Furthermore, the detection signal receiving unit 5 can also be installed outside the brain. For example, the brain activity measuring device 1 can further include a wireless output unit 25, which wirelessly outputs the detection signal to the outside of the target organism. The detection signal can then be wirelessly output by the wireless output unit 25, and the detection signal receiving unit 5 can receive the detection signal.

[0046] The detection signal receiving unit 5 is a component for receiving the detection signal generated by the brain diagnostic probe 3. When the detection signal receiving unit 5 is wired to the brain diagnostic probe 3, it can simply receive the detection signal output from the brain diagnostic probe 3 via a wired connection, such as an electrical signal or an optical signal. Furthermore, when the detection signal is output wirelessly, the detection signal receiving unit 5 only needs to have an antenna or other component for receiving wireless signals; receiving the wireless signal is equivalent to receiving the detection signal.

[0047] The signal analysis unit 7 is a component used to analyze the detection signal received by the detection signal receiving unit 5 to obtain measurement information for measuring brain activity. The signal analysis unit 7 can be implemented using a computer or processor.

[0048] A computer has an input unit, an output unit, a control unit, an arithmetic unit, and a storage unit. These components are connected via a bus or similar means to transmit and receive information. For example, the storage unit may store programs or various types of information. When predetermined information is input from the input unit, the control unit reads the program stored in the storage unit. Then, the control unit appropriately reads the information already stored in the storage unit and transmits it to the arithmetic unit. Furthermore, the control unit appropriately transmits the input information to the arithmetic unit. The arithmetic unit performs calculations using the received information and stores the results in the storage unit. The control unit reads the calculation results stored in the storage unit and outputs them from the output unit. Thus, various processes or procedures are executed. Each unit or section performs these various processes. The computer may also have a processor that implements various functions or procedures. The computer may be a standalone computer. Alternatively, a portion of the computer's functionality may be distributed across servers and terminals. In this case, the servers and terminals preferably transmit and receive information via a network such as the Internet or an internal network. The computer may also have a processor and memory linked to the processor. Then, commands can also be stored in memory. Executing these commands via the processor causes the computer to perform various procedures or function as a component. The computer can also be fed various training data to build learning models and perform various calculations through machine learning. In this case, the computer can also use learning models created through AI (artificial intelligence) machine learning / deep learning to perform various analyses or interpretations. If so, the accuracy of machine learning is improved.

[0049] For example, a learning model related to past detection signals and brain activity is constructed in the signal analysis unit 7. Then, the signal analysis unit 7 can obtain measurement information related to real-time brain activity simply by using the learning model to analyze the detection signals. Furthermore, the signal analysis unit 7 can also store past measurement information of the target organism and compare it with past measurement information to obtain real-time measurement information. Examples of measurement information include the degree or progression of brain diseases. Brain diseases are defined as the extinction of brain nerve cells most important for information transmission in the brain's nervous system, problems with the formation or function of synapses that transmit information between brain nerve cells, and diseases caused by symptoms or reductions in the electrical activity of brain nerves. Examples of brain diseases include degenerative brain diseases. Degenerative brain diseases are aging diseases defined as involving the progressive loss of specific groups of nerve cells and related to protein aggregates. Examples of degenerative brain diseases include stroke, paralysis, dementia, Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis (ALS). A learning model can be constructed simply by using the severity or progression of each disease and its associated past detection signals as training data. Furthermore, by using the obtained detection signals and information related to brain activity, the accuracy of the learning model related to the target organism can be improved. For example, examples of Alzheimer's disease progression include mild cognitive impairment (MCI), early stage, middle stage, and late stage.

[0050] The measurement information obtained by the signal analysis unit 7 is output appropriately. Examples of output include displaying on a monitor, printing on paper, or outputting as electronic information to a terminal of a physician or the target organism. A preferred embodiment of the brain activity measurement device 1 further includes a wireless output unit 25 for wirelessly outputting the measurement information to the outside of the target organism. Especially assuming that the signal analysis unit 7 is located inside the brain of the target organism or is physically connected to the target organism, having the wireless output unit 25 can make life more convenient for the target organism.

[0051] A preferred embodiment of the brain activity measurement device 1 is that at least one of the multiple thin-film probe sections 9 has a second light source 21, which has a wavelength different from that of the first light source 15. The second light source 21 is then used to treat the brain of the target organism. In this example, a second light control unit for controlling the output of the second light source 21 may also be provided. The second light control unit may also be provided in the thin-film probe section 9. The second light control unit may also have a computer or processor to control the output of the second light source 21. Furthermore, the second light control unit may also receive control commands from the control unit 20 and control the second light source 21 according to the control commands. The control unit 20 may, for example, output information for controlling the second light source 21 to the second light control unit based on the measurement information obtained by the signal analysis unit 7. The descriptions of the second control unit and the control unit 20 are functional descriptions; both may be physically identical. This brain activity measurement device 1 also functions as a treatment device for brain diseases performed by light. Furthermore, in the absence of the first light source 15, the second light source 21 is present in the thin-film probe 9 as a light source.

[0052] In this example, the second light control unit or control unit 20 stores detection signals or measurement information related to brain activity, as well as information related to the output of the second light source 21 (which may also include information regarding which part of the second light source 21 should be turned on). Then, upon receiving the detection signals or measurement information related to brain activity, the second light control unit or control unit 20 reads the information related to the output of the second light source 21 from the storage unit and controls the output of the second light source 21. Furthermore, the second light control unit or control unit 20 may also construct a learning model related to the detection signals or measurement information and the output of the second light source 21, using this learning model to obtain information for controlling the output of the second light source 21 from the detection signals or measurement information. By doing so, the brain can be appropriately treated based on brain measurement information.

[0053] The brain activity measurement device 1, equipped with a second light source 21, is particularly preferred for use in introducing optogenetics into a target organism. Optogenetics are genes that can activate nerve cells based on light of a specific wavelength. Examples of photoactive proteins produced by introducing these optogenetics include light-sensitive channel-2, variant ChR2, ChR2 / H134R, ChR2 / C128X (X being T, A, or S), or ChR2 / D156A, ChR2 / E123T (ChETA), chlororhodopsin, archeopithelin 3, archeopithelin T, OptoXRs, photoactivated adenylate cyclase, and melanopsin. Methods for introducing optogenetics expressing these proteins are existing technologies.

[0054] Figure 5 This is a conceptual diagram illustrating a design example of a circuit on a thin-film probe section having first and second light sources. Figure 5 In the example shown, a circuit board is formed on the thin-film probe section. A first light source 15, a first detection section 17, and a second light source 21 are disposed on the circuit board and connected by wiring.

[0055] A preferred embodiment of the brain activity measurement device 1 is that the signal analysis unit 7 uses machine learning to analyze the brain activity of the target organism and obtain the target organism's intention information. This embodiment is preferred when the target organism is in a state where it is difficult to communicate its intentions, such as being unable to speak. In this example, a learning model is constructed, for example, using detection signals corresponding to the states of each intention (thank you, happy, OK, NG, unhappy, want to stop). The signal analysis unit 7 can obtain the target organism's intention information simply by using the learning model and the obtained detection signals. Furthermore, this brain activity measurement device 1 preferably further includes an intention information output unit 23 that outputs intention information. Examples of the intention information output unit 23 include a display installed on the target organism and a display separate from the target organism. When the intention information output unit 23 is installed on the target organism's display, for example, icons corresponding to the states of each intention (smiley face icon, angry icon, etc.) can also be displayed on the display. If so, it would be possible to display the intentions of target organisms (e.g., people who have progressed to dementia or paralysis, or mammals other than humans) in an easily recognizable form.

[0056] A preferred embodiment of the brain activity measurement device 1 is that the signal analysis unit 7 uses machine learning to analyze the activity of nerve cells in the target organism. For example, the activity of nerve cells in the target organism can be analyzed using the previously described GECI.

[0057] A preferred embodiment of the brain activity measuring device 1 further includes: a deep brain stimulation electrode 31; a power supply unit 33 that supplies power to the deep brain stimulation electrode 31; and a power supply control unit 35 that controls the power supply of the power supply unit 33. Deep brain stimulation electrodes, such as those described in Japanese Patent No. 6603656, are existing technology. Furthermore, deep brain stimulation systems using deep brain stimulation electrodes, such as those described in Japanese Patent No. 2008-513082, are also existing technology. The preferred embodiment of the brain activity measuring device 1 can be achieved by appropriately utilizing the aforementioned existing technology. For example, the power supply control unit 35 can receive information from the control unit 20. The power supply control unit 35 can also receive control commands from the control unit 20 and control the power supply unit 33 according to the control commands. Since the control unit 20 receives measurement information, it is only necessary to output control commands corresponding to the measurement information to the power supply unit 33. In this way, the deep brain stimulation electrode 31 can be driven in accordance with the brain's activity level. The description of the power supply control unit 35 and the control unit 20 is a functional description; the two can also be physically identical components.

[0058] The brain activity measuring device 1 can be used, for example, by surgically creating a hole 13 in the skull of the subject organism, and then laying multiple thin-film probe parts 9 on the surface of the brain parenchyma through the hole 13.

[0059] Industrial utilization

[0060] This invention can be utilized in the fields of brain-related medical devices and communication tools for obtaining the intentions of a target organism.

[0061] Explanation of reference numerals in the attached figures

[0062] 1: Brain activity measurement device

[0063] 3: Brain diagnostic probes

[0064] 5: Detection signal receiving unit

[0065] 7: Signal Analysis Department

[0066] 11: The skull of the target organism

[0067] 13: Kong

[0068] 15: First Light Source

[0069] 17: First Testing Department

[0070] 19: First Light Control Department

[0071] 20: Control Department

[0072] 21: Second Light Source

[0073] 23: Department for Outputting Intent Information

[0074] 25: Wireless Output Unit

[0075] 31: Deep Brain Stimulation Electrodes

[0076] 33: Power Supply Department

[0077] 35: Supply to the Power Control Department

Claims

1. A brain activity measuring apparatus characterized by comprising: Having: a brain diagnosis probe; a detection signal receiving section for receiving a detection signal generated by the brain diagnosis probe; and a signal analysis section for analyzing the detection signal received by the detection signal receiving section to obtain measurement information for measuring an activity of a brain, wherein the brain diagnosis probe has a plurality of thin sheet-shaped probe sections, the plurality of thin sheet-shaped probe sections are respectively arranged in a skull of a subject living body via holes provided in the skull.

2. The brain activity measuring apparatus according to claim 1, characterized by the plurality of thin sheet-shaped probe sections respectively have undulations corresponding to either or both of undulations of parenchyma of a site where the probe sections are arranged and a vasculature.

3. The brain activity measuring apparatus according to claim 1, characterized by the plurality of thin sheet-shaped probe sections respectively have shapes arranged in at least one or more of a subdural space, a subarachnoid space, a wall of a cerebral ventricle, and a cerebral sulcus of the subject living body.

4. The brain activity measuring apparatus according to claim 1, characterized by the plurality of thin sheet-shaped probe sections have shapes covering an area of 1% or more and 90% or less of a brain of the subject living body.

5. The brain activity measuring apparatus according to claim 1, wherein at least one of the plurality of thin sheet-shaped probe sections has a first light source, a first detection section, and a first light control section for controlling light output from the first light source, the first light source is for exciting a light-emitting substance included in the brain.

6. The brain activity measuring apparatus according to claim 5, wherein at least one of the plurality of thin sheet-shaped probe sections has a second light source having a wavelength different from that of the first light source, the second light source is for treating the brain of the subject living body.

7. The brain activity measuring apparatus according to claim 1, wherein the signal analysis section uses machine learning to analyze an activity of the brain of the subject living body to obtain intention information of the subject living body, the brain activity measuring apparatus further has an intention information output section for outputting the intention information.

8. The brain activity measuring apparatus according to claim 1, characterized by the signal analysis section uses machine learning to analyze an activity of a nerve cell of the subject living body.

9. The brain activity measuring apparatus according to claim 8, characterized by the nerve cell of the subject living body emits light due to a predetermined light stimulus by gene introduction or introduction of a light-emitting substance.

10. The brain activity measuring apparatus according to claim 1, characterized by further having a wireless output section for wirelessly outputting the detection signal or the measurement information to an outside of the subject living body.

11. The brain activity measuring apparatus according to claim 1, characterized by further having a brain deep stimulation electrode, a power supply section for supplying power to the brain deep stimulation electrode, and a supplied power control section for controlling the supplied power of the power supply section.

Images