Brain activity measuring device

Abstract

[Problem] The purpose of the present invention is to provide a brain activity measuring device that is capable of measuring brain activity over a wide region. [Solution] The brain activity measuring device comprises: a brain diagnosis probe; a detection signal reception unit for receiving a detection signal from 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. The brain diagnosis probe has multiple sheet-shaped probe units, and each of the multiple sheet-shaped probe units is placed inside the skull via a hole prepared in the skull of the living organism in question.

Description

Brain activity measurement device

[0001] The present invention relates to a brain activity measuring device, and more specifically to a brain activity measuring device that can measure brain activity over a wide area and is suitable for measuring brain activity using calcium-sensitive fluorescent proteins or optogenes.

[0002] Japanese Patent Publication No. 3718500 describes a probe and device for measuring cerebral hemodynamics and oxygenation characteristics. This device uses a probe with an optical fiber. Therefore, this device can only measure brain activity in the area where the optical fiber is installed.

[0003] Patent No. 3718500

[0004] An object of the present invention is to provide a brain activity measurement device that can measure brain activity over a wide area. Another object of the present invention is to provide a brain activity measurement device 1 that is suitable for measuring brain activity using calcium-sensitive fluorescent proteins or optogenes. An object of the present invention is to solve any of the above problems.

[0005] The above problem is basically solved based on the finding that by using multiple sheet-like probe parts, the sheet-like probe parts can be laid out inside the brain, resulting in measurement of brain activity over a wide area, and is also suitable for measuring brain activity using calcium-sensitive fluorescent proteins or optogenes.

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

[0007] It is preferable that each of the plurality of sheet-like probe units has undulations corresponding to either or both of the undulations of the brain parenchyma and the vascular structure of the area where it is laid. In a preferred example of the brain activity measuring device 1, the plurality of sheet-like probe units 9 have a shape that allows them to be laid in at least one of the subdural space, the subarachnoid space, the ventricular wall, and the cerebral sulci of the target organism.

[0008] In a preferred example of the brain activity measuring device 1, the plurality of sheet-like probe units 9 have a shape that covers an area of ​​1% to 90% of the brain of the target organism.

[0009] In a preferred example of the brain activity measuring device 1, at least one of the plurality of sheet-like probe units 9 has a first light source 15, a first detection unit 17, and a first light control unit 19 for controlling the light output from the first light source 15. The first light source 15 is preferably used to excite a luminescent substance contained in the brain.

[0010] In a preferred example of the brain activity measuring device 1, at least one of the plurality of sheet-like probe units 9 has a second light source 21 having a wavelength different from the wavelength of the first light source 15. The second light source 21 is used to treat the brain of the target organism.

[0011] In a preferred example of the brain activity measuring device 1, the signal analysis unit 7 uses machine learning to analyze the brain activity of the target organism and obtain the intention information of the target organism. This brain activity measuring device 1 further includes an intention information output unit 23 that outputs the intention information.

[0012] In a preferred example of the brain activity measuring device 1, the signal analysis unit 7 analyzes the activity of nerve cells of the target organism using machine learning.

[0013] In a preferred example of the brain activity measuring device 1, nerve cells of a target organism are introduced with a gene or a luminescent substance, so that they emit light in response to a predetermined optical stimulus.

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

[0015] A preferred example 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 supplied by the power supply unit 33.

[0016] The brain activity measurement device of this invention can be laid out over a wide area of ​​the brain by using multiple sheet-like probe units, thereby enabling measurement of brain activity over a wide area and making it suitable for measuring brain activity using calcium-sensitive fluorescent proteins or optogenes.

[0017] FIG. 1 is a block diagram for explaining a brain activity measuring device. FIG. 2 is a conceptual diagram showing an example of the installation of a brain diagnostic probe. FIG. 3 is a diagram showing an example of a sheet-type probe unit. FIG. 4 is a conceptual diagram showing how a first detection unit detects fluorescence emitted by a fluorescent substance. FIG. 5 is a conceptual diagram showing an example of the design of a circuit on a sheet-type probe unit having first and second light sources.

[0018] The following describes embodiments of the present invention with reference to the drawings. The present invention is not limited to the embodiments described below, but also includes appropriate modifications of the embodiments that are obvious to those skilled in the art.

[0019] Fig. 1 is a block diagram illustrating a brain activity measuring device. As shown in Fig. 1, the brain activity measuring device 1 includes a brain diagnostic probe 3, a detection signal receiving unit 5, and a signal analyzing unit 7. The brain diagnostic probe 3 is inserted into the skull (the subdural space, the space between the skull and the surface of the brain) and is an element for performing brain diagnosis. The brain diagnostic probe 3 is publicly known, as described in, for example, Japanese Patent No. 3718500 and Japanese Patent No. 5224482.

[0020] FIG. 2 is a conceptual diagram showing an example of the placement of a brain diagnostic probe. As shown in FIG. 2, the brain diagnostic probe 3 has multiple sheet-like probe units 9. Each of the multiple sheet-like probe units 9 is placed within the skull 11 of the subject organism via a hole 13 formed in the skull 11. The number of holes 13 may be one or more. The hole 13 may be formed on the side of the skull, the rear of the skull, or the upper part of the skull. In the example shown in FIG. 2, two holes are formed. The number of sheet-like probe units 9 may be, for example, two to 100, three to 50, or four to 20. An example of the subject organism is an animal, and a preferred example of the subject organism is a human or a non-human mammal. Among these, a human is preferred as the subject organism.

[0021] The multiple sheet-like probe units 9 preferably have a shape that covers 1% to 90% of the brain of the target organism. Here, the brain area refers to the area between the cerebrum and the skull. The area of ​​the brain covered by the multiple sheet-like probe units 9 may be 5% to 90%, 10% to 90%, 15% to 80%, 20% to 50%, 20% to 40%, or 30% to 70%.

[0022] FIG. 3 shows examples of a sheet-like probe unit. FIG. 3( a) shows a rectangular sheet-like probe, FIG. 3( b) shows a sheet-like probe with a rounded tip, FIG. 3( c) shows a sheet-like probe with chamfered tip corners, and FIG. 3( d) shows a sheet-like probe with a shape that narrows toward the tip and is rounded at the very tip. As shown in FIG. 3 , the shape of the sheet-like probe unit 9 may be a strip (rectangular) or may have a tapered tip for easier insertion into the brain. The shape of the sheet-like probe unit 9 may be rounded or have chamfered tip corners. The sheet-like probe unit 9 is preferably a flexible sheet. Furthermore, the sheet-like probe unit 9 is intended to be placed between the skull and the brain surface, and is preferably placed in a manner that conforms to the cerebral cortex. Therefore, the sheet-like probe unit 9 preferably has excellent biocompatibility. The sheet-like probe portion 9 preferably has a certain degree of flexibility and hardness, and has the property of adhering to the brain surface by moisture, but does not adhere to the brain surface and can be removed from the brain surface.

[0023] Each of the multiple sheet-like probe units preferably has undulations corresponding to either or both of the undulations of the brain parenchyma and the vascular structure at the location where it is placed. The brain has various regions, including the frontal lobe, parietal lobe, temporal lobe, and occipital lobe, and a sheet-like probe unit 9 may be placed at each of these regions. The sheet-like probe unit 9 may also be shaped to fit the location where it is placed. The width W (the length of the maximum width) of the sheet-like probe unit 9 is, for example, 0.5 cm to 6 cm, 1 cm to 5 cm, 1 cm to 4 cm, 1 cm to 3 cm, or 2 cm to 4 cm. The length L (the length of the maximum length) of the sheet-like probe unit 9 is, for example, 2 cm to 20 cm, 4 cm to 15 cm, or 5 cm to 10 cm.

[0024] For example, each of the multiple sheet-like probe units 9 has a predetermined location where it is to be placed. For example, each sheet-like probe unit 9 preferably has a shape and properties suitable for placement in at least one of the cerebral cortex, ventricles, subdural space, subarachnoid space, ventricular walls, and cerebral sulci of a target organism. Furthermore, each of the multiple sheet-like probe units 9 has undulations (concavities and depressions) corresponding to either or both of the undulations of the brain parenchyma and the vasculature at the location where it is to be placed, allowing it to be as close to and in close contact with the brain parenchyma as possible. For example, the undulations of the brain parenchyma and the vasculature may be examined in advance using CT or MRI, and a custom-made undulation shape may be created corresponding to the shape. In this example, the method may include a brain surface topography acquisition process, which is a process for acquiring either or both of the undulations of the brain parenchyma and the vasculature (brain surface topography information) at a location in the target organism where the sheet-like probe unit 9 is to be placed, and a surface adjustment sheet-like probe unit creation process, which obtains a sheet-like probe unit 9 having a surface topography based on the brain surface topography information. The brain surface topography acquisition step may use a method capable of acquiring the brain topography, such as the above-mentioned CT or MRI. The obtained brain surface topography information may then be stored in a memory unit as appropriate. Next, in the surface-adjusting sheet-like probe unit creation step, the brain surface topography information may be read from the memory unit and the surface topography of the sheet-like probe unit may be adjusted. For example, after elements and circuits necessary to function as a sheet-like probe unit are installed on a flexible substrate, the surface may be coated with resin to create the sheet-like probe unit 9. Then, when coating the flexible substrate with resin, the surface topography of the sheet-like probe unit 9 may be adjusted based on the brain surface topography information to obtain a sheet-like probe unit 9 whose surface topography corresponds to the topography of the brain parenchyma and the vascular structure. Such processing can be achieved, for example, using a three-dimensional printer. Of course, a resin layer may be formed on the flexible substrate, and then the resin layer may be processed based on the brain surface topography information to obtain a sheet-like probe unit 9 whose surface topography corresponds to the topography of the brain parenchyma and the vascular structure.

[0025] The sheet-like probe may be a flexible printed circuit board. From the viewpoint of biocompatibility, a flexible printed circuit board with copper foil attached to the surface is preferred. Examples of such flexible printed circuit boards are described in Japanese Patent Nos. 7194857 and 7164752. A flexible printed circuit board allows components such as a light source, a detection unit, a control unit (and a memory unit), and the like, which will be described later, to be mounted on the board while maintaining flexibility. However, it is preferable for the flexible printed circuit board to be entirely coated and have 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 translucent to allow light to pass through.

[0026] In a preferred example of the brain activity measuring device 1, at least one of the multiple sheet-like probe units 9 (preferably all of the sheet-like probe units 9) has a first detection unit 17. The sheet-like probe unit 9 may have a first light source 15, a 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 may be used to excite a luminescent substance contained in the brain. In this example, for example, a luminescent substance is introduced into the brain of the target organism. In this way, it is preferable that the neurons 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 the 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 neurons of a target organism. Examples of GECI include GCaMP proteins (GCaMP3 protein, GCaMP6s protein, GCaMP7 protein, RCaMP1) and aequorin (aequorin). However, GECI discovered in the future may also be used. Methods for introducing GECI are known, for example, as described in Japanese Patent No. 5854686. When GECI is introduced, the GECI emits light in response to calcium fluctuations when the brain is activated. For example, GECI contained in brain neurons emits light. In this way, methods for 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 unit 9 may have multiple first light sources 15. The first light control unit 19 controls the light intensity and ON / OFF of the first light sources 15. The first light control unit 19 may receive control commands from the control unit 20 and control the first light sources 15 in accordance with the control commands. The control unit 20 may be implemented, for example, by a computer or a processor. The control unit 20 may output information to the first light control unit 15 for controlling the first light sources 15 based on measurement information obtained by the signal analysis unit 7. The terms control unit 19 and control unit 20 are functional, and the two may be physically the same element. Furthermore, the first light control unit 19 may store a program and control the first light sources 15 based on commands from the program. The first light control unit 19 may control multiple first light sources 15. The multiple first light sources 15 may be installed, for example, at equal intervals on the sheet-like probe unit 9. Examples of the 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 a wavelength corresponding to the luminescent material. The use of the first light source 15 can excite the fluorescent material. An example of the first light source 15 is a light source that emits visible light, and preferably emits light with a wavelength of 400 nm or more and 600 nm or less. The light from the first light source 15 may be, for example, pulsed light or continuous light.

[0028] An example of the first detection unit 17 is an optical sensor. The first detection unit 17 may measure a physical quantity other than light that is associated with brain activity. The first detection unit 17 may detect luminescence from a luminescent substance. The first detection unit 17 may detect reflected light after the first light source 15 irradiates light, or may detect light emitted in response to light emitted by the luminescent substance when the first light source 15 irradiates light. An example of the first detection unit 17 is a photodiode (PD). It is preferable that each sheet-like probe unit 9 has multiple first detection units 17.

[0029] 4 is a conceptual diagram showing how the first detector detects fluorescence emitted by a fluorescent substance. In this example, for example, light output from the first light source 15 excites GECI introduced into a neuron. The light emitted by the excited GECI (indicated by an arrow) is then detected by the first detector 17.

[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 may be performed, for example, by the first detection unit 17. A normal photodiode can perform these processes. The detection signal receiving unit 5 is connected so as to receive a signal 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. The detection signal receiving unit 5 may also be installed outside the brain. For example, the brain activity measuring device 1 may further include a wireless output unit 25 for wirelessly outputting the detection signal to the outside of the target organism. The wireless output unit 25 may output the detection signal wirelessly, and the detection signal receiving unit 5 may receive the detection signal.

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

[0032] The signal analysis unit 7 is a component 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 may be implemented by a computer or a processor.

[0033] A computer has an input unit, an output unit, a control unit, a calculation 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 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 calculation unit. The control unit also transmits the input information as appropriate to the calculation unit. The calculation unit performs calculation processing using the received various 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 performed. Each unit or means executes these various processes. A computer may have a processor, and the processor may realize various functions and steps. A computer may be standalone. A computer may have some of its functions distributed between a server and a terminal. In this case, it is preferable that the server and the terminal can exchange information via a network such as the Internet or an intranet. The computer may include a processor and a memory coupled to the processor. The memory may store instructions that, when executed by the processor, cause the computer to perform various processes or function as various elements. The computer may be provided with various training data to construct a learning model and perform various calculations through machine learning. In this case, the computer may perform various analyses using a learning model created through machine learning and deep learning of AI (artificial intelligence). This improves the accuracy of machine learning.

[0034] For example, the signal analysis unit 7 may have a learning model built on past detection signals and brain activity. The signal analysis unit 7 may then use the learning model to analyze the detection signals and obtain real-time measurement information on brain activity. The signal analysis unit 7 may also store past measurement information on the target organism and compare it with the past measurement information to obtain real-time measurement information. An example of the measurement information is the severity and progression of a brain disease. Brain disease refers to diseases caused by the death of brain neurons, which are essential for information transmission in the nervous system, problems with the formation or function of synapses that transmit information between brain neurons, or abnormal symptoms or a decrease in electrical activity of the brain nerves. An example of a brain disease is a degenerative brain disease. Degenerative brain diseases are aging-related illnesses that are defined as being associated with the gradual loss of specific neuronal populations and protein aggregates. Examples of degenerative brain diseases include stroke, stroke, dementia, Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis. A learning model can be constructed using the severity and progression of each disease and past detection signals related to each disease as training data. Furthermore, the accuracy of the learning model for the target organism can be improved by using the detection signals obtained this time and the status of brain activity. For example, examples of the progression stages of Alzheimer's disease include mild cognitive impairment (MCI), early stage, intermediate stage, and late stage.

[0035] The measurement information obtained by the signal analysis unit 7 is output as appropriate. Examples of output include displaying the information on a monitor, printing it on paper, or outputting it as electronic information to a terminal of a doctor or the target organism. A preferred example of the brain activity measurement device 1 further includes a wireless output unit 25 for wirelessly outputting the measurement information to an external device of the target organism. In particular, when the signal analysis unit 7 is expected to be present in the brain of the target organism or is physically connected to the target organism, having such a wireless output unit 25 can make the life of the target organism easier.

[0036] In a preferred example of the brain activity measuring device 1, at least one of the multiple sheet-like probe units 9 has a second light source 21 having a wavelength different from that of the first light source 15. The second light source 21 is used to treat the brain of a target organism. This example may, for example, have a second light control unit for controlling the output of the second light source 21. The second light control unit may be installed in the sheet-like probe unit 9. The second light control unit may have a computer or processor and control the output of the second light source 21. The second light control unit may also receive a control command from the control unit 20 and control the second light source 21 in accordance with the control command. The control unit 20 may, for example, output information to the second light control unit for controlling the second light source 21 based on measurement information obtained by the signal analysis unit 7. The terms "second control unit" and "control unit 20" are functional, and the two may be physically the same element. This brain activity measuring device 1 also functions as a device for treating brain diseases using light. When the first light source 15 is not present, the sheet-like probe 9 has the second light source 21 as a light source.

[0037] In this example, the second light control unit or control unit 20 stores measurement information related to the detection signal or brain activity and information related to the output of the second light source 21 (which may also include information related to which portion of the second light source 21 should be turned on). The second light control unit or control unit 20 then receives the measurement information related to the detection signal or brain activity, reads 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. The second light control unit or control unit 20 may also construct a learning model related to 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 measuring device 1 having the second light source 21 can be particularly preferably used when optogenetics are introduced into a target organism. Optogenetics are genes that can activate neurons based on light of a specific wavelength. Examples of photoactive proteins generated by introducing these optogenetics include channelrhodopsin 2, mutant ChR2, ChR2 / H134R, ChR2 / C128X (X is T, A, or S), ChR2 / D156A, ChR2 / E123T (ChETA), halorhodopsin, archerhodopsin 3, archerhodopsin T, OptoXRs, photoactivated adenylate cyclase, and melanopsin. Methods for introducing optogenetics that express these proteins are known.

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

[0040] In a preferred example of the brain activity measuring 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. This example is preferably used when the target organism is in a state where communication is difficult, such as when the target organism is mute. In this example, a learning model is constructed using detection signals corresponding to each intention state (grateful, happy, OK, NG, uncomfortable, please stop). The signal analysis unit 7 can obtain the target organism's intention information based on the obtained detection signals using such a learning model. The brain activity measuring device 1 preferably further includes an intention information output unit 23 that outputs the intention information. Examples of the intention information output unit 23 include a monitor attached to the target organism and a monitor separate 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 an icon corresponding to each intention state (e.g., a smiling icon, an angry icon, etc.). In this way, the intentions of a target living being with difficulty in communication (for example, a person with advanced dementia or paralysis, or a mammal other than a human) can be displayed in a manner that is easy to accept.

[0041] In a preferred example of the brain activity measuring device 1, the signal analysis unit 7 uses machine learning to analyze the activity of neurons in the target organism. For example, when the above-described GECI is used, the activity of neurons in the target organism can be analyzed.

[0042] A preferred example 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 supplied by the power supply unit 33. Deep brain stimulation electrodes are publicly known, for example, as described in Japanese Patent No. 6603656. A deep brain stimulation system using deep brain stimulation electrodes is also publicly known, as described in Japanese Patent Publication No. 2008-513082. A preferred example of the brain activity measuring device 1 can be realized by appropriately applying these publicly 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 a control command from the control unit 20 and control the power supply unit 33 in accordance with the control command. Since the control unit 20 receives measurement information, it is sufficient to output a control command corresponding to the measurement information to the power supply unit 33. In this manner, the deep brain stimulation electrode 31 can be driven in accordance with the brain activity status. The expressions "supply power control unit 35" and "control unit 20" are functional, and the two may be the same physical element.

[0043] The brain activity measuring device 1 can be used, for example, by creating a hole 13 in the skull of a target organism through a surgical operation and laying multiple sheet-like probe portions 9 on the surface of the brain substance or the like through the hole 13.

[0044] The present invention can be used in the fields of brain-related medical devices and communication tools for obtaining the will of a target organism.

[0045] REFERENCE SIGNS LIST 1 Brain activity measuring device 3 Brain diagnostic probe 5 Detection signal receiving unit 7 Signal analyzing unit 11 Skull of target organism 13 Hole 15 First light source 17 First detecting unit 19 First light control unit 20 Control unit 21 Second light source 23 Intention information output unit 25 Wireless output unit 31 Deep brain stimulation electrode 33 Power supply unit 35 Supply power control unit

Claims

1. A brain activity measuring device comprising: a brain diagnostic probe; a detection signal receiving unit for receiving a detection signal from said brain diagnostic probe; and a signal analysis unit for analyzing the detection signal received by said detection signal receiving unit and obtaining measurement information for measuring brain activity, wherein said brain diagnostic probe has a plurality of sheet-like probe portions, each of said plurality of sheet-like probe portions being placed within the skull of a target organism through a hole provided in the skull.

2. A brain activity measuring device as described in claim 1, wherein each of the plurality of sheet-like probe sections has undulations corresponding to either or both of the undulations of the brain parenchyma and the vascular structure of the area where it is placed.

3. A brain activity measuring device as described in claim 1, wherein each of the plurality of sheet-like probe portions has a shape that allows it to be placed in at least one of the subdural space, the subarachnoid space, the ventricular wall, and the cerebral sulci of the target organism.

4. A brain activity measuring device as described in claim 1, wherein the plurality of sheet-like probe sections have a shape that covers an area of ​​1% to 90% of the brain of the target organism.

5. A brain activity measuring device as described in claim 1, wherein at least one of the plurality of sheet-like probe sections has a first light source, a first detection section, and a first light control section for controlling the light output from the first light source, and the first light source is used to excite a luminescent substance contained in the brain.

6. A brain activity measuring device as described in claim 5, wherein at least one of the plurality of sheet-like probe portions has a second light source having a wavelength different from that of the first light source, and the second light source is used to treat the brain of the target organism.

7. A brain activity measuring device as described in claim 1, wherein the signal analysis unit uses machine learning to analyze the brain activity of the target organism and obtain intention information of the target organism, and the brain activity measuring device further has an intention information output unit that outputs the intention information.

8. A brain activity measuring device as described in claim 1, wherein the signal analysis unit uses machine learning to analyze the activity of the nerve cells of the target organism.

9. A brain activity measuring device as described in claim 8, wherein the nerve cells of the target organism are introduced with a gene or a luminescent substance, so that the nerve cells emit light in response to a predetermined optical stimulus.

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

11. A brain activity measuring device as described in claim 1, further comprising a deep brain stimulation electrode, a power supply unit that supplies power to the deep brain stimulation electrode, and a power supply control unit for controlling the power supplied by the power supply unit.

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