Brain activity measurement device

Abstract

The purpose of this invention is to provide a brain activity measurement device that can measure brain activity over a wide area. [Solution] A brain activity measurement device comprising a brain diagnostic probe, a detection signal receiving unit for receiving detection signals from the brain diagnostic probe, and a signal analysis unit for analyzing the detection signals received by the detection signal receiving unit and obtaining measurement information for measuring brain activity, wherein the brain diagnostic probe has a plurality of sheet-like probe sections, and each of the plurality of sheet-like probe sections is placed inside the skull of the target 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 that can measure brain activity over a wide area and is suitable for measuring brain activity using calcium-sensitive fluorescent proteins and optogenes.

Background Art

[0002] Japanese Patent No. 3718500 describes a probe and a device for measuring the hemodynamics and oxygen processing characteristics of the brain. This device uses a probe having an optical fiber. Therefore, this device can only measure brain activity at the site where the optical fiber is laid.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] An object of this invention is to provide a brain activity measurement device that can measure brain activity over a wide area. Another object of this invention, separate from the above, is to provide a brain activity measurement device 1 suitable for measuring brain activity using calcium-sensitive fluorescent proteins and optogenes. This invention aims to solve any of the above.

Means for Solving the Problems

[0005] Basically, the above problems are based on the finding that by using a plurality of sheet-like probe parts, the sheet-like probe parts can be laid in the brain, and as a result, brain activity over a wide area can be measured, and it is also suitable for performing brain activity measurement using calcium-sensitive fluorescent proteins and optogenes.

[0006] The brain activity measurement device 1 described in this specification comprises a brain diagnostic probe 3, a detection signal receiving unit 5, and a signal analysis unit 7. The brain diagnostic probe 3 has multiple sheet-like probe sections 9. Each of the multiple sheet-like probe sections 9 is placed inside the skull 11 of the target organism through a hole 13 provided in the skull 11. The detection signal receiving unit 5 is an element for receiving detection signals from the brain diagnostic probe 3. The signal analysis unit 7 analyzes the detection signal received by the detection signal receiving unit 5 and is an element for obtaining measurement information for measuring brain activity.

[0007] Preferably, each of the multiple sheet-like probe sections has an undulation that corresponds to either or both the undulation of the brain parenchyma and / or vascular structure of the area where it is laid. A preferred example of the brain activity measurement device 1 is one in which multiple sheet-like probe sections 9 are shaped to be laid in at least one of the following locations: the subdural space, subarachnoid space, ventricular wall, and sulcus of the target organism.

[0008] A preferred example of the brain activity measurement device 1 is one in which multiple sheet-like probe sections 9 have a shape that covers an area of ​​1% to 90% of the brain of the target organism.

[0009] A preferred example of the brain activity measurement device 1 is one in which at least one of the multiple sheet-like probe sections 9 includes 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. Preferably, the first light source 15 is used to excite light-emitting substances contained in the brain.

[0010] A preferred example of the brain activity measurement device 1 is one in which at least one of the multiple sheet-like probe sections 9 has a second light source 21 having a different wavelength from the first light source 15. The second light source 21 is used to treat the brain of the target organism.

[0011] A preferred example of the brain activity measurement device 1 is one in which the signal analysis unit 7 uses machine learning to analyze the brain activity of the target organism and obtain information about the organism's intentions. Furthermore, this brain activity measurement device 1 has an intention information output unit 23 that outputs the intention information.

[0012] 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.

[0013] A preferred example of the brain activity measurement device 1 is one in which the nerve cells of the target organism emit light in response to a predetermined light stimulus, after gene transfer or introduction of a light-emitting substance.

[0014] A preferred example of the brain activity measurement device 1 further includes a wireless output unit 25 for wirelessly outputting detection signals or measurement information to the outside of the target organism.

[0015] A preferred example of the brain activity measurement 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 for controlling the power supplied by the power supply unit 33. [Effects of the Invention]

[0016] The brain activity measurement device of this invention can be laid over a wide area of ​​the brain by using multiple sheet-like probe sections, and as a result can measure brain activity over a wide area, making it suitable for measuring brain activity using calcium-sensitive fluorescent proteins and photogenes. [Brief explanation of the drawing]

[0017] [Figure 1] Figure 1 is a block diagram illustrating a brain activity measurement device. [Figure 2] Figure 2 is a conceptual diagram showing an example of the placement of a brain diagnostic probe. [Figure 3] Figure 3 shows an example of a sheet-like probe section. [Figure 4] Figure 4 is a conceptual diagram showing how the first detection unit detects the fluorescence emitted by the fluorescent substance. [Figure 5] FIG. 5 is a conceptual diagram showing a design example of a circuit on a sheet-like probe portion having first and second light sources. BEST MODE FOR CARRYING OUT THE INVENTION

[0018] Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. The present invention is not limited to the embodiments described below, and includes those appropriately modified by those skilled in the art within a self-evident range from the following embodiments.

[0019] FIG. 1 is a block diagram for explaining a brain activity measurement device. As shown in FIG. 1, the brain activity measurement 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 inserted into the skull (the gap between the skull and the brain surface, the subdural space) and is an element for performing brain diagnosis. The brain diagnostic probe 3 is known, for example, as described in Japanese Patent No. 3718500 and Japanese Patent No. 5224482.

[0020] FIG. 2 is a conceptual diagram showing an example of laying the brain diagnostic probe. As shown in FIG. 2, the brain diagnostic probe 3 has a plurality of sheet-like probe portions 9. Each of the plurality of sheet-like probe portions 9 is installed in the skull 11 through a hole 13 provided in the skull 11 of the target organism. The hole 13 may be one or two or more. The hole 13 may be provided on the side surface of the skull, on the rear side of the skull, or on the upper part of the skull. In the example of FIG. 2, two holes are provided. The number of the sheet-like probe portions 9 is, for example, two or more and 100 or less, and may be three or more and 50 or less, or four or more and 20 or less. Examples of the target organism are animals, and preferred examples of the target organism are humans or mammals other than humans. Among these, humans are preferred as the target organism.

[0021] The multiple sheet-like probe portions 9 are preferably shaped to cover an area of ​​1% to 90% of the target organism's brain. Here, the brain area refers to the area between the cerebrum and the skull. The brain area covered by the multiple sheet-like probe portions 9 may be 5% to 90%, 10% to 90%, 15% to 80%, 20% to 50%, 20% to 40%, or 30% to 70%.

[0022] Figure 3 shows examples of sheet-like probe portions. Figure 3(a) shows a sheet-like probe with a rectangular shape, Figure 3(b) shows a sheet-like probe with a rounded tip, Figure 3(c) shows a sheet-like probe with chamfered corners at the tip, and Figure 3(d) shows a sheet-like probe that narrows towards the tip and has a rounded tip. As shown in Figure 3, the shape of the sheet-like probe portion 9 may be strip-shaped (rectangular), or it may have a tapered tip to facilitate insertion into the brain. The shape of the sheet-like probe portion 9 may have a rounded tip or chamfered corners at the tip. It is preferable that the sheet-like probe portion 9 is a flexible sheet. Furthermore, it is assumed that the sheet-like probe portion 9 will be laid between the skull and the brain surface, and it is particularly preferable that it be laid along the cerebral cortex. Therefore, it is preferable that the sheet-like probe portion 9 has excellent biocompatibility. The sheet-like probe portion 9 preferably has a certain degree of flexibility and rigidity, and while it has the property of adhering to moisture, it does not adhere to the brain surface and can be removed from the brain surface.

[0023] Preferably, each of the multiple sheet-like probe sections has an undulation that corresponds to either or both the undulation of the brain parenchyma and / or vascular structure of the area where it is laid. The brain has various parts, including, for example, the frontal lobe, parietal lobe, temporal lobe, and occipital lobe, and sheet-like probe sections 9 may be laid in each of these areas. The sheet-like probe section 9 may also be shaped to match the area where it is laid. An example of the width W (length of the widest part) of the sheet-like probe section 9 is 0.5 cm or more and 6 cm or less, but it may also be 1 cm or more and 5 cm or less, 1 cm or more and 4 cm or less, 1 cm or more and 3 cm or less, or 2 cm or more and 4 cm or less. An example of the length L (length of the longest part) of the sheet-like probe section 9 is 2 cm or more and 20 cm or less, but it may also be 4 cm or more and 15 cm or less, or 5 cm or more and 10 cm or less.

[0024] For example, each of the multiple sheet-like probe sections 9 has a predetermined location where it is to be laid. For example, each sheet-like probe section 9 preferably has a shape and properties suitable for being laid on at least one of the following areas of the target organism: the cerebral cortex, ventricles, subdural space, subarachnoid space, ventricular wall, and sulcus. Furthermore, each of the multiple sheet-like probe sections 9 has a surface texture (unevenness) corresponding to either or both the undulations of the brain parenchyma and the vascular structure of the area where it is to be laid, so that it can get as close to and in close contact with the brain parenchyma as possible. For example, the undulations of the brain parenchyma and the vascular structure may be examined in advance using CT or MRI, and the uneven shape may be custom-made according to that shape. In this example, the process may include a brain surface shape acquisition step, which is a step of acquiring either or both (brain surface undulation information) of the brain parenchyma and vascular structure of the area of ​​the target organism that includes the area where the sheet-like probe section 9 is to be laid, and a surface adjustment sheet-like probe section creation step, which is a step of obtaining a sheet-like probe section 9 having a surface shape based on the brain surface undulation information. The brain surface shape acquisition process can be carried out using methods that can acquire the shape of the brain, such as CT or MRI as described above. The obtained brain surface relief information can then be stored in a memory unit as appropriate. Next, in the surface adjustment sheet-like probe unit creation process, the brain surface relief information can be read from the memory unit and the surface shape of the sheet-like probe unit can be adjusted. For example, after setting the elements and circuits necessary to function as a sheet-like probe unit on a flexible substrate, the surface can be coated with resin to create the sheet-like probe unit 9. When coating the flexible substrate with resin, the surface shape of the sheet-like probe unit 9 can be adjusted based on the brain surface relief information to obtain a sheet-like probe unit 9 whose surface shape corresponds to the relief of the brain parenchyma and vascular structure. Such processing can be achieved, for example, by using a 3D printer. Of course, after forming the resin layer on the flexible substrate, the resin layer can be processed based on the brain surface relief information to obtain a sheet-like probe unit 9 whose surface shape corresponds to the relief of the brain parenchyma and vascular structure.

[0025] A flexible printed circuit board may be used for the sheet-shaped probe. From the viewpoint of biocompatibility, a flexible printed circuit board with copper foil attached to its surface is preferred. Examples of such flexible printed circuit boards are described in Japanese Patent No. 7194857 and Japanese Patent No. 7164752. With a flexible printed circuit board, the light source, detection unit, control unit (and memory unit), etc., described later can be installed on the board while maintaining flexibility. However, it is preferable that the entire flexible printed circuit board is coated and has a coating layer. This is to prevent the light source and other elements from being left behind in the brain or damaging the brain surface. The coating layer is preferably transparent or semi-transparent in order to transmit light.

[0026] A preferred example of the brain activity measurement device 1 is that at least one of the multiple sheet-like probe sections 9 (preferably all of the sheet-like probe sections 9) has a first detection section 17. The sheet-like probe section 9 may have 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 detection section 17 is used to detect signals related to brain activity. The first light source 15 may be used to excite luminescent substances contained in the brain. In this example, for example, a luminescent substance is introduced into the brain of the target organism. It is preferable that the nerve cells of the target organism emit light in response to a predetermined light stimulus by gene transfer or introduction of a luminescent substance. An example of a luminescent substance is a fluorescent protein. Examples of fluorescent proteins include green fluorescent protein (e.g., GFP), red fluorescent protein (e.g., DsRed), and calcium-sensitive fluorescent protein (GECI). A calcium-sensitive fluorescent protein is a fluorescent protein that is sensitive to calcium. For example, a luminescent substance (GECI) is introduced into the nerve cells of the target organism. Examples of GECIs include GCaMP proteins (GCaMP3, GCaMP6s, GCaMP7, and RCaMP1) and aequorin. However, GECIs discovered in the future may also be used. Methods for introducing GECIs are publicly known, for example, as described in Japanese Patent Publication No. 5854686. When GECIs are introduced, they emit light in response to changes in calcium levels when the brain is activated. For example, GECIs contained in nerve cells of the brain emit light. This method of measuring brain function using luminescent substances can measure brain function more accurately and quickly than methods such as functional near-infrared spectroscopy and optical topography.

[0027] Each sheet-like probe section 9 may have a plurality of first light sources 15. The first optical control unit 19 controls the light intensity and ON / OFF status of the first light sources 15. The first optical control unit 19 may receive control commands from the control unit 20 and control the first light sources 15 according to the control commands. The control unit 20 may be implemented, for example, by a computer or processor. The signal analysis unit 7 may output information to the first optical control unit 15 for controlling the first light sources 15 based on the measurement information obtained by the signal analysis unit 7. The expressions "control unit 19" and "control unit 20" are functional, and they may be physically the same element. In addition, the first optical control unit 19 may store a program and control the first light sources 15 based on the commands of that program. The first optical control unit 19 may control a plurality of first light sources 15. The plurality of first light sources 15 may be installed at equal intervals on the sheet-like probe section 9, for example. Examples of first light sources 15 are light-emitting diodes and LEDs. The output of the first light sources 15 is preferably at an intensity that does not damage the brain. The wavelength of the light output by the first light source 15 is preferably the wavelength corresponding to the light-emitting material. By using the first light source 15, the fluorescent material can be excited. An example of the first light source 15 is visible light, and it is preferably a light source that emits light with a wavelength of 400 nm to 600 nm. The light from the first light source 15 may be pulsed light or continuous light, for example.

[0028] An example of the first detection unit 17 is a light sensor. The first detection unit 17 may measure physical quantities other than light that are related to brain activity. The first detection unit 17 may detect the emission of light from a light-emitting material. The first detection unit 17 may detect reflected light after the first light source 15 has irradiated it, or it may detect light emitted by the light-emitting material in reaction to the first light source 15 irradiating it. An example of the first detection unit 17 is a photodiode (PD). Preferably, each sheet-like probe unit 9 has a plurality of first detection units 17.

[0029] Figure 4 is a conceptual diagram showing how the first detection unit detects fluorescence emitted by a fluorescent substance. In this example, for instance, light emitted from the first light source 15 excites GECI introduced into nerve cells. The first detection unit 17 then detects the light emitted by the excited GECI (arrow).

[0030] The optical 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 optical signal into a detection signal and the process of outputting the detection signal to the detection signal receiving unit 5 can be performed by the first detection unit 17, for example. A normal photodiode can perform these processes. The detection signal receiving unit 5 is connected to receive signals from the brain diagnostic probe 3. The detection signal receiving unit 5 may be installed inside the brain together with the brain diagnostic probe 3. Alternatively, the detection signal receiving unit 5 may be located outside the brain. For example, the brain activity measurement device 1 may further have a wireless output unit 25 for wirelessly outputting the detection signal to the outside of the target organism. The wireless output unit 25 may wirelessly output the detection signal, and the detection signal receiving unit 5 may receive the detection signal.

[0031] The detection signal receiving unit 5 is an element for receiving detection signals from the brain diagnostic probe 3. If the detection signal receiving unit 5 and the brain diagnostic probe 3 are connected by a wire, the detection signal receiving unit 5 should receive the detection signal output from the brain diagnostic probe 3 via the wire, such as an electrical or optical signal. If the detection signal is output as a wireless signal, the detection signal receiving unit 5 should have an element for receiving wireless signals, such as an antenna, and should receive the detection signal, which is a wireless signal.

[0032] The signal analysis unit 7 is an element that analyzes the detection signal received by the detection signal receiving unit 5 and obtains measurement information for measuring brain activity. The signal analysis unit 7 can be implemented using a computer or processor.

[0033] A computer has an input unit, an output unit, a control unit, an arithmetic unit, and a memory unit, and each element is connected by a bus or the like to enable the exchange of information. For example, the memory unit may store a program or various kinds of information. When predetermined information is input from the input unit, the control unit reads the program stored in the memory unit. The control unit then reads the information stored in the memory unit as appropriate and transmits it to the arithmetic unit. The control unit also transmits the input information to the arithmetic unit as appropriate. The arithmetic unit performs calculations using the received information and stores it in the memory unit. The control unit reads the calculation results stored in the memory unit and outputs them from the output unit. In this way, various processes and steps are executed. Each unit and each means is responsible for executing these various processes. A computer may have a processor, and the processor may implement various functions and steps. A computer may be standalone. A computer may have some of its functions distributed between a server and terminals. In that case, it is preferable that the server and terminals can exchange information via a network such as the internet or an intranet. A computer may include a processor and memory connected to the processor. The memory may store instructions, which, when executed by the processor, cause the computer to perform various processes or to function as various components. The computer may build a learning model by providing various training data and perform various calculations through machine learning. In this case, the computer may perform various analyses and interpretations using the learning model created by AI (artificial intelligence) machine learning and deep learning. Doing so will improve the accuracy of machine learning.

[0034] For example, the signal analysis unit 7 has a learning model built on past detected signals and brain activity. The signal analysis unit 7 can then use this learning model to analyze the detected signals and obtain real-time measurement information on brain activity. Alternatively, the signal analysis unit 7 may store past measurement information of the target organism and obtain real-time measurement information by comparing it with past measurement information. Examples of measurement information include the degree and progression of brain diseases. Brain diseases refer to diseases caused by the death of brain nerve cells that are most important for information transmission in the brain nervous system, problems with the formation and function of synapses that transmit information between brain nerve cells, and abnormal symptoms or reductions in the electrical activity of brain nerves. An example of a brain disease is a degenerative brain disease. A degenerative brain disease is an aging-related disease defined as the gradual loss of specific populations of nerve cells and the formation of 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. A learning model can be constructed using the degree and progression of each of these diseases, along with past detection signals related to each, as training data. Furthermore, by using the detection signals obtained in this study and information about brain activity, the accuracy of the learning model for the target organism can be improved. For example, examples of the progression of Alzheimer's disease include mild cognitive impairment (MCI), early stage, middle stage, and late stage.

[0035] The measurement information obtained by the signal analysis unit 7 is output as appropriate. Examples of output include display on a monitor, printing on paper, or outputting as electronic information to a doctor's or the target organism's terminal. A preferred example of the brain activity measurement device 1 is one which further includes a wireless output unit 25 for wirelessly outputting the measurement information to the outside of the target organism. In particular, if the signal analysis unit 7 is expected to be located inside the brain of the target organism or is physically connected to the target organism, having such a wireless output unit 25 can make life easier for the target organism.

[0036] A preferred example of the brain activity measurement device 1 is one in which at least one of a plurality of sheet-like probe units 9 has a second light source 21 having a different wavelength from the first light source 15. The second light source 21 is used to treat the brain of a target organism. This example may have, for example, a second optical control unit for controlling the output of the second light source 21. The second optical control unit may be installed in the sheet-like probe unit 9. The second optical control unit may have a computer or processor and control the output of the second light source 21. Alternatively, the second optical control unit may 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 to the second optical control unit for controlling the second light source 21 based on measurement information obtained by the signal analysis unit 7. The expressions "second control unit" and "control unit 20" are functional, and they may be physically the same element. This brain activity measurement device 1 also functions as a device for treating brain diseases with light. Furthermore, if the first light source 15 is not present, the sheet-shaped probe 9 will have a second light source 21.

[0037] In this example, the second optical control unit or control unit 20 stores the detection signal or measurement information regarding brain activity and information regarding the output of the second light source 21 (which may also include information regarding which part of the second light source 21 to turn ON). The second optical control unit or control unit 20 then receives the detection signal or measurement information regarding brain activity, reads the information regarding the output of the second light source 21 from the storage unit, and controls the output of the second light source 21. Alternatively, the second optical control unit or control unit 20 may construct a learning model relating the detection signal or measurement information and the output of the second light source 21, and use this learning model to obtain information for controlling the output of the second light source 21 from the detection signal or measurement information. In this way, the brain can be appropriately treated based on the measurement information of the brain.

[0038] The brain activity measurement device 1 having a second light source 21 can be preferably used in cases where optogenetics are introduced into the target organism. Optogenetics are genes that can activate nerve cells based on light of a specific wavelength. Examples of photoactive proteins generated by the introduction of these optogenetics include channelrhodopsin 2, mutant ChR2, ChR2 / H134R, ChR2 / C128X (where X is T, A, or S) or ChR2 / D156A, ChR2 / E123T (ChETA), halorhodopsin, archaerodopsin 3, archaerodopsin T, OptoXRs, photoactivated adenylate cyclase, and melanopsin. Methods for introducing optogenetics that express these proteins are well known.

[0039] Figure 5 is a conceptual diagram showing an example of a circuit design on a sheet-like probe having first and second light sources. In the example shown in Figure 5, a circuit board is formed on the sheet-like probe. The circuit board is equipped with a first light source 15, a first detection unit 17, and a second light source 21, which are connected by wiring.

[0040] A preferred example of the brain activity measurement device 1 is one in which the signal analysis unit 7 uses machine learning to analyze the brain activity of the target organism and obtain information about the organism's intentions. For example, this example can be preferably used when the target organism is in a state where communication is difficult, such as being unable to speak. In this example, a learning model is constructed using detection signals corresponding to the state of each intention (e.g., grateful, happy, OK, NG, unpleasant, want it to stop). The signal analysis unit 7 can then use such a learning model to obtain information about the organism's intentions based on the obtained detection signals. Furthermore, it is preferable that the brain activity measurement device 1 further includes an intention information output unit 23 that outputs intention information. Examples of the intention information output unit 23 include a monitor attached to the target organism and a monitor that exists separately from the target organism. If the intention information output unit 23 is a monitor attached to the target organism, for example, the monitor may display icons corresponding to the state of each intention (e.g., a smiling icon, an angry icon). In this way, the intentions of a target organism with whom communication is difficult (e.g., an individual with advanced dementia or paralysis, or a mammal other than a human) can be displayed in an easily understandable format.

[0041] A preferred example of the brain activity measurement device 1 is one in which the signal analysis unit 7 uses machine learning to analyze the activity of nerve cells in the target organism. For example, when using the GECI described earlier, the activity of nerve cells in the target organism can be analyzed.

[0042] A preferred example of the brain activity measurement device 1 further comprises a deep brain stimulation electrode 31, a power supply unit 33 for supplying power to the deep brain stimulation electrode 31, and a power supply control unit 35 for controlling the power supplied by the power supply unit 33. Deep brain stimulation electrodes are known, for example, as described in Japanese Patent Publication No. 6603656. Furthermore, deep brain stimulation systems using deep brain stimulation electrodes are known, as described in Japanese Patent Publication No. 2008-513082. A preferred example of the brain activity measurement device 1 can be realized by appropriately applying these known technologies. For example, the power supply control unit 35 is configured to receive information from the control unit 20. The power supply control unit 35 may 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 has received measurement information, it only needs to output control commands to the power supply unit 33 according to the measurement information. In this way, the deep brain stimulation electrode 31 can be driven in response to the brain's activity status. The terms "power supply control unit 35" and "control unit 20" are functional, and they may be physically the same element.

[0043] The brain activity measurement device 1 can be used, for example, by surgically creating a hole 13 in the skull of the target organism and laying multiple sheet-like probe parts 9 on the surface of the brain parenchyma or the like through the hole 13. [Industrial applicability]

[0044] This invention can be used in the field of medical devices related to the brain, and in the field of communication tools for obtaining the intentions of target organisms. [Explanation of symbols]

[0045] 1. Brain activity measurement device 3. Brain diagnostic probe 5. Detection signal receiving unit 7 Signal analysis section 11. Skull of the target organism 13 holes 15. The first light source 17 First detection unit 19 First Optical Control Unit 20 Control Unit 21 Second light source 23. Intention Information Output Unit 25 Wireless output section 31 Deep brain stimulation electrodes 33 Power supply section 35 Power Supply Control Unit

Claims

1. Brain diagnostic probes and A detection signal receiving unit for receiving detection signals from the brain diagnostic probe, The aforementioned detection signal receiving unit analyzes the detection signal received and a signal analysis unit obtains measurement information for measuring brain activity, A brain activity measurement device having, The brain diagnostic probe is placed inside the skull of the target organism through a hole provided in the skull. It has multiple sheet-like probe sections, Brain activity measurement device, wherein the plurality of sheet-like probe portions include a sheet-like probe portion for subdural placement, which has a shape that allows it to be laid in the subdural space of the target organism.

2. A brain activity measurement device according to claim 1, A brain activity measurement device in which the plurality of sheet-like probe portions include either or both of the sheet-like probe portions for subarachnoid space placement having a shape for being laid in the subarachnoid space of the target organism, and the sheet-like probe portions for sulcus placement having a shape for being laid in the sulci of the brain of the target organism.

3. A brain activity measuring device according to claim 1 or 2, wherein each of the plurality of sheet-like probe portions has an undulation corresponding to either or both the undulation of the brain parenchyma and the vascular structure of the area on which it is laid.

4. A brain activity measurement device according to claim 1, At least one of the plurality of sheet-like probe sections includes a first light source, a first detection unit, and a first light control unit for controlling the light output from the first light source. The first light source is used to excite the light-emitting substance contained in the brain. Brain activity measurement device.

5. A brain activity measuring device according to claim 4, At least one of the plurality of sheet-like probe portions has a second light source having a wavelength different from the wavelength of the first light source. The second light source is used to treat the brain of the target organism. Brain activity measurement device.

6. A brain activity measurement device according to claim 1, The signal analysis unit uses machine learning to analyze the brain activity of the target organism and obtain information about the organism's intentions. A brain activity measurement device further comprising a will information output unit that outputs the will information.

7. A brain activity measurement device according to claim 1, The signal analysis unit is a brain activity measurement device that uses machine learning to analyze the activity of nerve cells in the target organism.

8. A brain activity measuring device according to claim 7, The nerve cells of the aforementioned target organism emit light in response to a predetermined light stimulus, thereby enabling brain activity measurement.

9. A brain activity measurement device according to claim 1, A brain activity measurement device further comprising a wireless output unit for wirelessly outputting the detection signal or the measurement information to the outside of the target organism.

10. A brain activity measuring device according to claim 1, further comprising a deep brain stimulating electrode, a power supply unit for supplying power to the deep brain stimulating electrode, and a power supply control unit for controlling the power supplied by the power supply unit.

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