Hippocampal function evaluation system and data creation method

Abstract

This system for evaluating hippocampus function comprises an acquisition unit that acquires image data representing the hippocampi of a subject and an identification unit that identifies volume data representing the volume of the subject's left hippocampal-amygdala transition area in accordance with the image data.

Description

Technical Field

[0001] The present invention relates to a hippocampal function evaluation system and a data creation method.

Background Art

[0002] It is said that newborn neurons are maintained throughout life even in the adult brain (Non-Patent Document 1), and are generated in the subventricular zone of the lateral ventricle and the subgranular layer of the hippocampal dentate gyrus (DG). It has been reported in rodents that newborn neurons in the DG are associated with pattern separation, which is the ability to detect similar but distinct features (Non-Patent Documents 2 and 3), and in fMRI that imposes behavioral analysis tasks on human subjects, BOLD (blood oxygenation level dependent effect) activity in the hippocampal DG has been observed (Non-Patent Documents 4 and 5).

[0003] On the other hand, the function of reproducing neural activity corresponding to complete stimulus information from incomplete stimulus information is called pattern completion, which is found in the hippocampal CA3 region in rodents (Non-Patent Document 6), and is said to be associated with the CA1 region and the CA3 region in humans (Non-Patent Document 7).

[0004] Further, studies using transgenic mice have suggested that young granule cells in the DG are involved in pattern separation, old cells are associated with pattern completion, and young neurons switch to pattern completion as they age (Non-Patent Document 8).

[0005] It has been reported that even adult rats placed in an enriched environment show an increase in the number and volume of newborn neurons in the subgranular layer of the dentate gyrus, which is affected by the expansion of dendrites and the increase of glial cells, and that the hippocampal volume has plasticity (Non-Patent Document 9).

[0006] Meanwhile, the inventors have been conducting research with the aim of establishing diagnostic and treatment methods for 1) diffuse axonal injury due to traffic accidents, falls, etc., 2) hypoxic encephalopathy due to myocardial infarction or stroke, and 3) higher brain dysfunction caused by carbon monoxide poisoning, etc., and have proposed methods and systems for evaluating hippocampal function that do not require large-scale equipment and can evaluate the hippocampal function of subjects in a simple and accurate manner (Patent Documents 1-3). [Prior art documents] [Patent Documents]

[0007] [Patent Document 1] Japanese Patent Publication No. 2015-195835 [Patent Document 2] Japanese Patent Publication No. 2019-63512 [Patent Document 3] Japanese Patent Publication No. 2019-63513 [Non-patent literature]

[0008] [Non-Patent Document 1] Eriksson et al. (1998). Neurogenesis in the adult human hippocampus. Nature medicine, 4. 1313. [Non-Patent Document 2] Leutgeb et al. (2007). Pattern separation in the dentate gyr us and CA3 of the hippocampus. Science,315,961-966. [Non-Patent Document 3] Franca, TF, Bitencourt, AM, Maximilla, NR, Barros, DM, & Monserrat, JM (2017). Hippocampal neurogenesis and pattern separation: A meta analysis of behavioral data. Hippocampus, 27, 937-950. [Non-Patent Document 4] Bakker et al. (2008). Pattern separation in the human hippocampal CA3 and dentate gyrus. Science, 319, 1640-1642. [Non-Patent Document 5] Shiroma, et.al (2015). Cerebellar Contribution to Pattern Separation of Human Hippocampal Memory Circuits. The Cerebellum, 1-18. [Non-Patent Document 6] Rolls, E. (2013). The mechanisms for pattern completion and pattern separation in the hippocampus. Frontiers in Systems Neuroscience, 7, 74. [Non-Patent Document 7] Bakker et al. (2008). Pattern separation in the human hippocampal CA3 and dentate gyrus. Science 319, 1640-1642. [Non-Patent Document 8] Nakashiba et al. (2012). Young dentate granule cells mediate pattern separation, whereas old granule cells facilitate pattern completion. Cell, 149, 188-201. [Non-Patent Document 9] Kempermann, G., Kuhn, HG, & Gage, FH (1997). More hippocampal neurons in adult mice living in an enriched environment. Nature, 386, 493. [Overview of the Initiative] [Problems that the invention aims to solve]

[0009] However, the relationship between hippocampal subfield volume and pattern separation and pattern completion has not been clarified until now. It was thought that establishing a new hippocampal function evaluation system from this perspective could further enhance objectivity and reliability.

[0010] This invention has been made in view of the above circumstances, and aims to provide a novel hippocampal function evaluation system and data creation method that can objectively and reliably evaluate human hippocampal function using hippocampal subfield volume as an indicator. [Means for solving the problem]

[0011] To solve the above problems, the hippocampal function evaluation system of the present invention comprises an acquisition unit that acquires image data representing the hippocampus of a subject, and an identification unit that identifies volume data representing the volume of the left hippocampal-amygdala transition area of ​​the subject according to the image data.

[0012] The data creation method of the present invention is a data creation method for evaluating human hippocampal function, characterized by comprising a step of acquiring image data representing the hippocampus of a subject, and a step of identifying volume data representing the volume of the left hippocampus-amygdala transition area of the subject according to the said image data.

Effects of the Invention

[0013] According to the hippocampal function evaluation system and the data creation method of the present invention, human hippocampal function can be evaluated objectively and with high reliability.

Brief Description of the Drawings

[0014] [Figure 1] This is a block diagram illustrating the configuration of a hippocampal function evaluation system as an example. [Figure 2] This is a flowchart of processing executed by the hippocampal function evaluation system. [Figure 3] This is a diagram showing an overview of volume identification for hippocampal subfields. [Figure 4] This is a diagram showing the hippocampus and perihippocampal areas of a healthy subject. It shows the hippocampus and perihippocampal areas in the sagittal (a), coronal (b), (c) axial directions, and (d) 3D view. The subfields (parahippocampal gyrus, subiculum, presubiculum, Ammon's horn (CA)1, CA 2 / 3, CA4, dentate gyrus granule cells (GC-DG), hippocampus-amygdala transition area (HATA), fimbria, hippocampal molecular layer, hippocampal fissure, hippocampal tail) are displayed in respective colors (yellow, deep purple, blue, red, green, gray, light blue, light green, pink, brown, purple, light purple). A, anterior; P, posterior; L, left; R, right. [Figure 5]These are (a to m) scatter plots of segmented brain regions showing a significant association with the Lure task. The analysis results are from 57 healthy subjects. The sites showing a negative correlation with the Lure task correct answer rate were (K) Whole brain gray matter, (e) Bilateral cerebral white matter, (d) Brain stem, (c) 4th ventricle, (a) Right cerebellum cortex, (b) Left cerebellum cortex, (i) Left hippocampus, (j) Left thalamus, and (h) Left ventral diencephalon. In addition, a positive correlation was observed in (m) Left choroid plexus. [Figure 6] These are (a to c) scatter plots of segmented brain regions showing a significant association with the Same task. Positive correlations were observed in (a) Right thalamus, (b) Bilateral anterior cingulate cortex, and (C) Right caudate. [Figure 7] These are (a to f) scatter plots obtained by analyzing the volume of the hippocampus-amygdala transition area (HATA) and the Lure correct answer rate (%) using standard resolution T1 data. (a to c) are compared by volume, and (d to f) are compared by the whole-brain weight ratio × 10⁴. [Figure 8] This is a diagram showing the HATA volumes of a 22-year-old male high scorer with 98 points (the average value of the task correct answer rate for 31 male subjects is 49.9 ± 21.3; mean ± SD) and a 22-year-old male low scorer with 13 points, measured by fMRI after administering a hippocampal behavioral analysis task. Ratio indicates the TIV whole-brain weight ratio × 10⁴. [Mode for Carrying Out the Invention]

[0015] The inventors focused on the relationship between hippocampal subfield volume and pattern separation and pattern completion, and discovered a novel finding: a negative correlation between the volume of the left hippocampal-amygdal junction (left HATA) and hippocampal function. The amygdala is an organ that functions in relation to emotions, and therefore shrinks when emotions are stable and enlarges when emotions fluctuate drastically. The inventors confirmed a relationship between improved hippocampal memory and pattern separation and the shrinkage of the left hippocampal-amygdal junction (left HATA). In other words, a small volume of the left hippocampal-amygdal junction (left HATA) can be considered indicative of good hippocampal function, while a large volume of the left hippocampal-amygdal junction (left HATA) can be considered indicative of impaired hippocampal function. This invention is based on these novel findings. In this invention, "hippocampus" includes the dentate gyrus.

[0016] The following describes one embodiment of the hippocampal function evaluation system 100 and data creation method of the present invention.

[0017] Figure 1 is a block diagram illustrating the configuration of the hippocampal function evaluation system 100 according to this embodiment. The hippocampal function evaluation system 100 of this embodiment is a system for evaluating the hippocampal function of a subject. Specifically, the hippocampal function evaluation system 100 comprises a control device 10 and a storage device 20.

[0018] The control device 10 is one or more processors that control each element of the hippocampal function evaluation system 100. Specifically, the control device 10 is composed of one or more types of processors, such as a CPU (Central Processing Unit), SPU (Sound Processing Unit), DSP (Digital Signal Processor), FPGA (Field Programmable Gate Array), or ASIC (Application Specific Integrated Circuit). The control device 10 evaluates the hippocampal function of the subject.

[0019] The storage device 20 is one or more memories that store programs executed by the control device 10 and various data used by the control device 10. The storage device 20 is composed of known recording media such as magnetic recording media or semiconductor recording media, or a combination of multiple types of recording media. Alternatively, a separate storage device 20 (e.g., cloud storage) may be provided, and the control device 10 may perform writing and reading to the storage device 20 via a communication network such as a mobile communication network or the Internet. In other words, the storage device 20 may be omitted from the hippocampal function evaluation system 100.

[0020] As illustrated in Figure 1, the control device 10 of this embodiment executes a program stored in the storage device 20 to realize multiple functions (acquisition unit 11, identification unit 13, and evaluation unit 15) for evaluating the hippocampal function of a subject.

[0021] The acquisition unit 11 acquires image data D1 representing the subject's hippocampus from the storage device 20. The image data D1 is displayed on a display device (not shown). Image data D1 is, for example, anatomical three-dimensional image data of the hippocampus obtained using a known device such as an MRI scanner. When using anatomical three-dimensional image data of the hippocampus, it is preferable to be able to display images for each hippocampal subfield. Specifically, the hippocampal tail, hippocampal peristome, anterior hippocampal peristome, parahippocampal peristome, Ammon's horn (CA)1, CA3, CA4, dentate gyrus granule cell layer (GC-DG), hippocampal molecular layer, hippocampo-amygdal transition region (HATA), and hippocampal fimbria can be displayed. The hippocampal cleft can also be displayed.

[0022] Furthermore, image data D1 may be data that has undergone various image processing, such as motion correction, skull removal, intensity normalization, white matter separation, 3D visualization of gray matter / white matter (tessellation), and brain surface extraction. Such image processing can be performed using, for example, Freesurfer 6.0 (http: / / surfer.nmr.mgh.harvard.edu).

[0023] The identification unit 13 identifies data D2 representing the volume of the subject's left hippocampal-amygdal junction (left HATA) (hereinafter referred to as "volume data"). In this embodiment, the identification unit 13 identifies the volume data D2 according to the image data D1 acquired by the acquisition unit 11. Any known technique can be used to identify the volume data D2. The volume data D2 may be the volume itself, or it may be data obtained by applying a predetermined correction process to the volume (for example, a value obtained by multiplying the volume by a coefficient). The identified volume data D2 is stored in the storage device 20.

[0024] Furthermore, head size correlates with body size, and brain size correlates with head size. Therefore, it is preferable that the identification unit 13 identifies standardized data of the volume of the left hippocampus-amygdala junction (left HATA) as volume data D2.

[0025] Specific methods for identifying volume data D2 include, for example, 1) analyzing raw hippocampal volume data directly, 2) analyzing the value obtained by dividing hippocampal volume by the body size of the brain and skull, and 3) using a "residue" method that removes shared variations such as brain volume, skull size, and height using multiple regression or ANCOVA. Factors such as gender and age can also be adjusted. The identification unit 13 can identify volume data D2 representing the volume of the hippocampal subfield (left hippocampal-amygdal junction (left HATA)) according to these methods.

[0026] The evaluation unit 15 evaluates the subject's hippocampal function according to the volume data D2 identified by the identification unit 13. Specifically, the evaluation unit 15 evaluates the subject's hippocampal function (e.g., pattern separation and pattern completion) according to the volume data D2 identified by the identification unit 13 and the negative correlation between reference data representing the volume of the left hippocampus-amygdala transition area (left HATA) and hippocampal function. The subject's hippocampal function is evaluated according to the volume data D2 and data (hereinafter referred to as "preparation data") D3 representing the negative correlation between reference data and hippocampal function. The preparation data D3 is created in advance and stored in the memory device 20.

[0027] The reference data is data representing the volume of the left hippocampal-amygdal junction (left HATA) that has been previously identified for the subject (or other subjects). Then, for example, preparation data D3 is created by associating the evaluation of hippocampal function with this reference data. For example, the evaluation unit 15 identifies the evaluation corresponding to the volume data D2 in the preparation data D3 as the subject's hippocampal function. The evaluation unit 15 may be omitted from the hippocampal evaluation function system.

[0028] For example, the evaluation unit 15 can determine that if the volume of the left hippocampus-amygdal junction (left HATA) is small, hippocampal function is good, and if the volume of the left hippocampus-amygdal junction (left HATA) is large, hippocampal function is impaired.

[0029] In one embodiment of the hippocampal function evaluation system 100, for example, the evaluation unit 15 evaluates that hippocampal function is impaired if the numerical value indicated by the volume data D2 from the identification unit 13 is above a set threshold. On the other hand, the evaluation unit 15 evaluates that hippocampal function is improved if the numerical value indicated by the volume data D2 is below a set threshold. Such thresholds can be appropriately set according to the negative correlation between reference data representing the volume of the left hippocampus-amygdala transition area and hippocampal function. Furthermore, the thresholds may be set taking into account the characteristics and conditions of the subject.

[0030] In another embodiment of the hippocampal function evaluation system 100, for example, the evaluation unit 15 may evaluate the subject's hippocampal function according to the difference between previously measured volume data (A) of the left hippocampal-amygdal junction of the same subject and newly measured volume data (B) of the left hippocampal-amygdal junction. For example, the subject's hippocampal function is evaluated by comparing the difference (absolute value) between volume data (A) and volume data (B) with a predetermined threshold. Such a threshold can be appropriately set according to the negative correlation between reference data representing the volume of the left hippocampal-amygdal junction and hippocampal function. For example, if the difference between volume data (A) and volume data (B) is greater than the threshold, the evaluation unit 15 evaluates that the subject's hippocampal function has changed compared to before, and if the difference between volume data (A) and volume data (B) is smaller than the threshold, it evaluates that the subject's hippocampal function has been maintained from before.

[0031] Furthermore, the evaluation unit 15 may evaluate that the subject's hippocampal function has decreased compared to before if volume data (B) is larger than volume data (A), and that the subject's hippocampal function has improved compared to before if volume data (B) is smaller than volume data (A).

[0032] Figure 2 is a flowchart of the process by which the hippocampal function evaluation system 100 evaluates the hippocampal function of a subject. The process in Figure 2 is initiated, for example, in response to instructions from the administrator of the hippocampal function evaluation system 100.

[0033] The acquisition unit 11 acquires image data D1 from the storage device 20 (Sa1). The identification unit 13 identifies volume data D2 representing the volume of the subject's left hippocampus-amygdala transition area according to the image data D1 acquired by the acquisition unit 11 (Sa2). The evaluation unit 15 evaluates the subject's hippocampal function according to the volume data D2 identified by the identification unit 13 (Sa3). Specifically, hippocampal function is evaluated based on the negative correlation between the volume data D2 identified by the identification unit 13 and hippocampal function.

[0034] Furthermore, the hippocampal function evaluation system 100 may also include, for example, a memory unit for storing information regarding the volume of the left hippocampal-amygdala transition area, and a display unit for displaying the volume of each hippocampal subfield.

[0035] The hippocampal function evaluation system 100 of the present invention can be used to evaluate a subject's hippocampal function and related mental illnesses, mental state, and stress levels based on the volume of the left hippocampal-amygdal junction (left HATA), and is highly objective and reliable.

[0036] The present invention is also specified as a method for creating data to evaluate the hippocampal function of a subject (hereinafter referred to as the "data creation method").

[0037] Specifically, the data creation method includes the steps of acquiring image data D1 representing the subject's hippocampus and identifying volume data D2 representing the volume of the subject's left hippocampal-amygdal junction.

[0038] Here, volume data D2 may be the volume itself, as described above, or it may be data on which a predetermined correction process has been applied to the volume. Data on which a predetermined correction process has been applied to the volume refers to, for example, various forms of data relating to the volume of the left hippocampal-amygdal junction (such as numerical values ​​relating to the volume of the left hippocampal-amygdal junction (left HATA)). For example, using the volume data D2 identified by the data creation method of the present invention, the hippocampal function of a subject can be evaluated based on a negative correlation (preparation data D3) between reference data representing the volume of the left hippocampal-amygdal junction (HATA) and hippocampal function.

[0039] The hippocampal function evaluation system and data creation method of the present invention are not limited to the embodiments described above.

[0040] Furthermore, the present invention is also specified as an evaluation method for evaluating the hippocampal function of a subject. Specifically, the evaluation method acquires volume data D2 and evaluates the subject's hippocampal function according to the negative correlation between the volume data D2 and hippocampal function, based on reference data representing the volume of the left hippocampus-amygdala junction. The volume data D2 is acquired from the storage device 20 by the acquisition unit 11. [Examples]

[0041] Examples are shown below and explained in more detail, but the present invention is not limited to the following examples. <1> Selection of subjects Fifty-eight healthy subjects (mean age 25 ± 4.4 years, range 18–40 years, 31 males 24.5 ± 3.5 years, 27 females 25.5 ± 5.2 years) participated. All subjects were right-handed based on the Edinpara handedness scale (Oldfield, 1971). None of the subjects had any signs or history of neuropsychiatric disorders.

[0042] <2> Behavioral memory task Previous reports have revealed the existence of memory circuits in the hippocampus using functional MRI (hereinafter referred to as fMRI) with a lure task established for pattern separation (Non-Patent Literature 5).

[0043] In this study, we determined the score and reaction time of a behavioral memory task without analyzing the fMRI BOLD signal (Blood Oxygen Level Dependent Signal). The behavioral memory task was conducted according to methods described in Patent Document 1 and Non-Patent Document 5, etc., by presenting photographs one by one on a screen and asking participants to answer by pressing a button corresponding to each photograph. There were three buttons, and participants were instructed to distinguish between photographs they were seeing for the first time (New), photographs that were the same as those seen in previous trials (Same), and photographs that were similar to but different from those seen in previous trials (Lure), and to press the corresponding button with a different finger (red button for New, blue button for Same, and green button for Lure).

[0044] The fMRI behavioral paradigm used a fast event-associated fMRI design based on an explicit forced-choice task that included three options: novel stimulus, same stimulus, and lure stimulus.

[0045] The fully randomized fMRI task consisted of 108 trials, comprising 16 lure sets, 16 same sets, and 44 unrelated novel stimuli. Visual stimuli were presented on goggle displays for 2500ms, with stimulus intervals ranging from 0 to 100ms to prevent adaptive responses. Visual stimuli were presented to subjects using 800x600 resolution magnetic field-sensitive goggles (Resonance Technologies, Salem, Massachusetts) under computer control using Presentation® software (Neurobehavioral Systems, Austin, Texas).

[0046] Responses and reaction times were recorded in a button box (Current Designs, Philadelphia, Pennsylvania). The accuracy rate for the Lure and Same tasks was calculated and defined as the respective scores.

[0047] <3> Acquisition of structural MRI Anatomical images were acquired using a 3 Tesla MRI scanner (Discovery MR750, GE Medical Systems, Waukesha, Wisconsin, USA) with a 32-channel head coil and advanced manual shimming to the temporal lobe. Anatomical three-dimensional (3D) T1-weighted images (an example of "image data") were acquired using a spoiled gradient recalled echo (SPGR) sequence with a high resolution of 1 mm slice thickness (matrix size 256 × 256, effective field of view 256 × 256 mm, repetition time 6.9 ms, echo time 3 ms, flip angle 15 degrees).

[0048] <4> Volume determination All T1-weighted and T2-weighted image data were processed using the freely available software Freesurfer (http: / / surfer.nmr.mgh.harvard.edu). Volume partitioning, including motion correction, skull removal, intensity normalization, white matter separation, gray matter / white matter 3D visualization (tessellation), and brain surface extraction, was identified using Freesurfer 6.0's fully automated reorganization ("recon-all"). The hippocampus subfield was divided into 12 subfields in each hemisphere by applying an automated analysis of the hippocampal subfield using a probabilistic atlas and a modified version of the Van Leemput algorithm (Van Leemput, et al., 2009). Eleven hippocampal subfields were extracted, including the hippocampal tail, hippocampal base, anterior hippocampal base, parahippocampal base, Ammon's horn (CA)1, CA3, CA4, dentate gyrus granular cell layer (GC-DG), hippocampal molecular layer, hippocampo-amygdala transition zone (HATA), and fimbriae. Since the hippocampal cleft is considered to have low reproducibility, the 11 hippocampal subfields excluding the hippocampal cleft were divided into segments.

[0049] For the reasons stated above, in order to evaluate brain structure alone, we identified the volumes of 11 hippocampal subfields excluding the hippocampal fissure (an example of "volume data") by following the procedure illustrated in Figure 3 (Figure 4).

[0050] Then, to correct for brain volume, we calculated the total intracranial volume (TIV) estimated by Freesurfer6.0.

[0051] <5> statistical analysis Continuous variables other than age and Same score showed a normal distribution with P>0.05 using the Kolmogrov-Smirnov test. The Welch t-test was used to test for gender differences, and the Mann·Whitney U test was used for age and Same score.

[0052] To determine the sex differences in the volume of the entire hippocampus and the 11 subfield regions of the hippocampus, we applied analysis of covariance (ANCOVA) with TIV and age as covariates.

[0053] All statistical analyses were performed at an alpha level of p=0.05, using EZR (Saitama Medical Center, Jichi Medical University), the graphical user interface for R (The R Foundation for Statistical Computing). More precisely, it is an improved version of R commander, designed to add statistical functions commonly used in biostatistics.

[0054] <6> result Regarding fMRI hippocampal task performance and reaction time, no gender differences were observed in the gender distribution of subjects (chi-squared test, p = 0.6), age (Mann-whitney U test, t = 0.48), Lure task performance and reaction time (Welch t-test p = 0.49, p = 0.62), Same task performance (Mann-whitney U test p = 0.65), and reaction time (Welch t-test p = 0.65, p = 0.6) (Table 1).

[0055] [Table 1]

[0056] The mean values ​​and standard deviations (SD) of the volume (mm3) of the whole hippocampus and subfields are shown for each subject, for both hippocampi, right side, left side, and AI: Asymmetry Index (%) (Table 2).

[0057] [Table 2]

[0058] The AI ​​is represented by (right volume * left volume) / (right volume + left volume) * 10 0, where "0" indicates that the left and right sides are exactly the same size, a negative value indicates that the left side is larger by a percentage, and a positive value indicates that the right side is larger by a percentage. In the AI ​​of hippocampal volume, the hippocampal volume tended to be larger on the right side for all hippocampal volumes except for presubiculum and parasubiculum. In order of the largest difference, the results were: fimbria (11.6%), parasubiculum (10.9%), HATA (6.1%), hippocampal-tail (5.6%), CA2 / 3 (5.4%), presubiculum (5%), CAI (4.4%), subiculum (3.8%), CA4 (3.8%), DG (3.5%), molecular-layer (3.4%), and total hippocampal volume (2.8%).

[0059] When comparing the volume of the entire hippocampus and its subfields between men and women, the volume of the left deep vein gland (DG) and left fimbria was significantly larger in men than in women (ANCOVA adjusted age and TIV, left DG p=0.014, left fimbria p=0.025) (Table 3).

[0060] [Table 3]

[0061] However, no significant correlation was found between left DG, left Fimbria, Lure, and Same results (Table 4. Lure; left DG r=-0.08, p=0.57, left Fimbria r=-0.08, p=0.54, Same; left Lure r=-0.07, p=0.61, left Fimbria r=-0.08, p=0.98). Only the left HATA showed a correlation with the Lure results in simple linear regression analysis.

[0062] [Table 4]

[0063] The simple correlation between memory performance and the hippocampus as a whole and its subfields, as well as the results after multiple regression analysis, are shown for the bilateral hippocampus, left hippocampus, and right hippocampus (Table 5). Only the left HATA showed a correlation with the Lure results in the multiple regression analysis.

[0064] [Table 5]

[0065] When examining the simple correlation between Lure and Same tasks for all hippocampal subfields (bilateral, left, and right hippocampi) (Figures 5 and 6), a significant negative correlation was observed only in the left-sided HATA (Figure 5; r=-0.26, p=0.049). After adjusting for TIV, sex, and age as related factors in multiple regression analysis, a significant trend was observed between the left-sided HATA and Lure performance in each subfield (left-sided HATA; β=-0.27, p=0.07).

[0066] Furthermore, a negative correlation was found between the volume of the hippocampal-amygdal transition area (HATA) and the Lure accuracy rate (%) (Figure 7: a~f).

[0067] Furthermore, hippocampal pattern separation ability was measured by fMRI after administering a hippocampal behavioral analysis task. The HATA volumes of a high-scoring 22-year-old male (98 points; mean ± SD for the 31 males with a task accuracy rate of 49.9 ± 21.3) and a low-scoring 22-year-old male (13 points) are shown (Figure 8). The ratio is calculated by dividing the subfield volume by the total intracranial volume (TIV) and raising the result to the power of 10⁴.

[0068] High scorers had TIV 1664.9ml and Left HATA 42.89mm. 3 The ratio was low at 0.26, and those with low scores had TIV 2011.3ml, Left HATA 71.37mm. 3 A high ratio of 0.35 was confirmed.

[0069] As described above, in young subjects, the volume of the left DG and left Fimbria subfields of the hippocampus was larger in males than in females. However, despite this larger volume, no sex differences were observed in performance on pattern separation and pattern completion tasks or response times. Furthermore, a significant negative correlation was observed only between pattern separation and left-sided HATA. After adjusting for related factors such as brain volume, sex, and age, a significant negative correlation was observed only with left-sided HATA.

[0070] Therefore, it was confirmed that the volume of the left hippocampal-amygdal junction in a subject can be identified, and the subject's hippocampal function can be evaluated based on the negative correlation between the identified volume and hippocampal function. [Explanation of Symbols]

[0071] 10: Control device 11: Acquisition part 13: Specific part 15: Evaluation Department 20:Storage device 100: Hippocampal function evaluation system

Claims

1. An acquisition unit that acquires image data representing the subject's hippocampus, A unit that identifies volume data representing the volume of the left hippocampal-amygdal junction of a subject, based on the aforementioned image data, An evaluation unit evaluates the subject's hippocampal function in accordance with the volume data identified by the identification unit, the reference data representing the volume of the left hippocampus-amygdala transition area, and the hippocampal function. A hippocampal function evaluation system equipped with the following features.

2. The evaluation unit evaluates that the subject's hippocampal function is impaired if the numerical value indicated by the volume data is above a set threshold. If the numerical value indicated by the volume data is below a set threshold, the subject's hippocampal function is evaluated as elevated. A hippocampal function evaluation system according to claim 1.

3. The evaluation unit evaluates the subject's hippocampal function according to the difference between the previously measured volume data (A) of the subject's left hippocampal-amygdal junction and the newly measured volume data (B) of the left hippocampal-amygdal junction. A hippocampal function evaluation system according to claim 1.

4. A method for creating data to evaluate the hippocampal function of a subject, A step of identifying reference data representing the volume of the left hippocampal-amygdal junction and preparatory data representing the negative correlation between hippocampal function, The process of obtaining image data representing the subject's hippocampus, The process involves identifying volume data representing the volume of the left hippocampal-amygdal junction of the subject, based on the aforementioned image data. Includes, The hippocampal function of the subject can be evaluated according to the volume data and the preparation data. Data creation method.

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