Volumetry of hippocampus and amygdala with high-resolution MRI and three-dimensional analysis software: minimizing the discrepancies between laboratories

Characterising mental wellbeing and associations with subcortical grey matter volume at short intervals in early adolescence

This temporally rich, longitudinal study of early adolescents (N = 88, 277 datasets, 12-13 years) investigated the relationship between bilateral subcortical grey matter volume (GMV) in the hippocampus, amygdala, accumbens-area, caudate, putamen and pallidum with self-reported mental wellbeing at four timepoints, across 12 months. Generalised Estimating Equations (GEE) revealed (1) higher 'total wellbeing' was associated with smaller left caudate and larger left accumbens-area; (2) higher eudaimonic wellbeing was associated with smaller left caudate and larger right caudate; and (3) higher hedonic wellbeing was associated with larger left accumbens-area. Further analyses and plots highlighted different associations between GMV and wellbeing for adolescents who consistently experienced 'moderate-to-flourishing' wellbeing (n = 63, 201 datasets), compared with those who experienced 'languishing' wellbeing at any timepoint (n = 25, 76 datasets). These findings demonstrate several associations between subcortical GMV and measures of wellbeing, at short intervals in early adolescence. Taken together, sub-types of wellbeing appear uniquely associated with specific subcortical regions; and there may be a distinct neurobiological and wellbeing profile for adolescents who experience poorer wellbeing over the course of their first year(s) of secondary school. This study implicates the bilateral caudate and left accumbens-area as important targets for future research into the mental wellbeing of adolescents.

Hippocampal damage disrupts the latent decision-making processes underlying approach-avoidance conflict processing in humans

Rodent and human data implicate the hippocampus in the arbitration of approach-avoidance conflict (AAC), which arises when an organism is confronted with a stimulus associated simultaneously with reward and punishment. Yet, the precise contributions of this structure are underexplored, particularly with respect to the decision-making processes involved. We assessed humans with hippocampal damage and matched neurologically healthy controls on a computerized AAC paradigm in which participants first learned whether individual visual images were associated with the reward or loss of game points and were then asked to approach or avoid pairs of stimuli with non-conflicting or conflicting valences. To assess hippocampal involvement more broadly in response conflict, we also administered a Stroop and a Go/No-go task. On the AAC paradigm, following similar learning outcomes in individuals with hippocampal damage and matched controls, both participant groups approached positive and negative image pairs at the same rate but critically, those with hippocampal damage approached conflict pairs more often than controls. Choice and response AAC data were interrogated using the hierarchical drift diffusion model, which revealed that, compared to controls, individuals with hippocampal damage were more biased towards approach, required less evidence to make a decision during conflict trials, and were slower to accumulate evidence towards avoidance when confronted with conflicting image pairs. No significant differences were found between groups in performance accuracy or response time on the response conflict tasks. Taken together, these findings demonstrate the importance of the hippocampus to the evidence accumulation processes supporting value-based decision-making under motivational conflict.

Effect of epileptiform discharges and hippocampal volume on cognitive dysfunction following clipping of ruptured aneurysms in the anterior circulation

Introduction

Cognitive dysfunction after aneurysmal subarachnoid hemorrhage (aSAH) remains unclear due to various neurological impairments. This study aimed to evaluate the changes in hippocampal volume, cognitive function, and interictal epileptiform discharges after clipping in patients with aSAH of anterior circulation.

Methods

Patients with modified Rankin Scale scores of 0-3 points who underwent clipping were evaluated. Aneurysmal locations were classified as middle cerebral artery (MCA), internal carotid artery (ICA), and anterior cerebral artery (ACA). Surgery was performed using the transsylvian approach or interhemispheric approach. Hippocampal volume measurement, neuropsychological assessments, and interictal electroencephalogram evaluations were performed postoperatively at the subacute phase. Epileptiform discharges were assessed using the spike index (SI).

Results

We included 60 patients (23 men, 37 women; median age, 57.4 years). Aneurysmal locations were found in the MCA, ICA, and ACA in 23, 19, and 18 patients, respectively. The postoperative hippocampal volume was significantly reduced on the clipping approach side in the MCA and ICA groups (MCA, p < .001; ICA, p < .001). There was no correlation between hippocampal volume and cognitive function. A significant difference was noted in elevated SI on the approach side of the MCA (p < .001), ICA (p < .001), and ACA (p < .001) in the transsylvian approach group. The elevated SI on the left approach side showed significant differences in some neuropsychological assessments (performance intellectual quotient, p = .028; perceptual organization, p = .045; working memory, p = .003).

Discussion

Cognitive dysfunction in the subacute phase after clipping for aSAH was not correlated with hippocampal volume reduction but was correlated with interictal epileptiform discharges.

Advancing Thalamic Nuclei Segmentation: The Impact of Compressed Sensing on MRI Processing

The thalamus is a collection of gray matter nuclei that play a crucial role in sensorimotor processing and modulation of cortical activity. Characterizing thalamic nuclei non-invasively with structural MRI is particularly relevant for patient populations with Parkinson's disease, epilepsy, dementia, and schizophrenia. However, severe head motion in these populations poses a significant challenge for in vivo mapping of thalamic nuclei. Recent advancements have leveraged the compressed sensing (CS) framework to accelerate structural MRI acquisition times in MPRAGE sequence variants, while fast segmentation tools like FastSurfer have reduced processing times in neuroimaging research. In this study, we evaluated thalamic nuclei segmentations derived from six different MPRAGE variants with varying degrees of CS acceleration (from about 9 to about 1-min acquisitions). Thalamic segmentations were initialized from either FastSurfer or FreeSurfer, and the robustness of the thalamic nuclei segmentation tool to different initialization inputs was evaluated. Our findings show minimal sequence effects with no systematic bias, and low volume variability across sequences for the whole thalamus and major thalamic nuclei. Notably, CS-accelerated sequences produced less variable volumes compared to non-CS sequences. Additionally, segmentations of thalamic nuclei initialized from FastSurfer and FreeSurfer were highly comparable. We provide the first evidence supporting that a good segmentation quality of thalamic nuclei with CS T1-weighted image acceleration in a clinical 3T MRI system is possible. Our findings encourage future applications of fast T1-weighted MRI to study deep gray matter. CS-accelerated sequences and rapid segmentation methods are promising tools for future studies aiming to characterize thalamic nuclei in vivo at 3T in both healthy individuals and clinical populations.

Do total hippocampus and hippocampal subfield volumes relate to navigation ability? A call towards methodological consistency

Despite the need for successful navigation, humans vary greatly in their ability to navigate, and these individual differences may relate to variation in brain structure. While prior research provides support for a correlation between hippocampal volume and navigation ability in both navigation experts and in older individuals, this relationship is under scrutiny for healthy, young adults. We assessed 99 healthy young adults' ability to navigate in a virtual, desktop maze and correlated their performance with total hippocampal gray matter volume. For a subset of these individuals, we further segmented the medial temporal lobe-including regions of the hippocampus-into anatomically-distinct subregions to uniquely examine the association between volumes of hippocampal subfields and navigation. Given the need to distinguish between similar-looking maze hallways and partially overlapping routes, young adults with stronger pattern separation ability may perform better in this task. Thus, we theorized that successful navigation would positively correlate with hippocampal CA3 and dentate gyrus (DG) subfield volumes due to these regions' role in pattern separation. CA1 and entorhinal cortex (ERC) are both associated with rodent spatial memory, too, suggesting a possible relationship between their volumes and navigation performance. Consistent with our hypotheses, we observed a positive relationship between volumes of hippocampal subfields and wayfinding accuracy, while ERC and parahippocampal cortex volumes correlated with navigation efficiency. However, when analyzing total hippocampal volume, a nuanced interpretation is warranted. We found evidence of Simpson's Paradox, where total hippocampal volume and navigation accuracy displayed no correlation in males, a negative correlation in females, yet a positive correlation when considering the full sample of males and females combined. Furthermore, no significant relationship was observed between total hippocampal volume and path efficiency. Given these findings, we urge caution in interpreting the results because these associations differ by analysis techniques (including voxel-based morphometry), after sex stratification, and with anterior and posterior hippocampal subdivisions. Overall, this study enhances our understanding of the relationship between brain volume and navigation ability for young adults but also emphasizes the need for methodological consistency across studies with respect to boundary definitions, neuroimaging techniques, statistical methods, and factors that give rise to individual differences.

An improved 3D-UNet-based brain hippocampus segmentation model based on MR images

OBJECTIVE

Accurate delineation of the hippocampal region via magnetic resonance imaging (MRI) is crucial for the prevention and early diagnosis of neurosystemic diseases. Determining how to accurately and quickly delineate the hippocampus from MRI results has become a serious issue. In this study, a pixel-level semantic segmentation method using 3D-UNet is proposed to realize the automatic segmentation of the brain hippocampus from MRI results.

METHODS

Two hundred three-dimensional T1-weighted (3D-T1) nongadolinium contrast-enhanced magnetic resonance (MR) images were acquired at Hangzhou Cancer Hospital from June 2020 to December 2022. These samples were divided into two groups, containing 175 and 25 samples. In the first group, 145 cases were used to train the hippocampus segmentation model, and the remaining 30 cases were used to fine-tune the hyperparameters of the model. Images for twenty-five patients in the second group were used as the test set to evaluate the performance of the model. The training set of images was processed via rotation, scaling, grey value augmentation and transformation with a smooth dense deformation field for both image data and ground truth labels. A filling technique was introduced into the segmentation network to establish the hippocampus segmentation model. In addition, the performance of models established with the original network, such as VNet, SegResNet, UNetR and 3D-UNet, was compared with that of models constructed by combining the filling technique with the original segmentation network.

RESULTS

The results showed that the performance of the segmentation model improved after the filling technique was introduced. Specifically, when the filling technique was introduced into VNet, SegResNet, 3D-UNet and UNetR, the segmentation performance of the models trained with an input image size of 48 × 48 × 48 improved. Among them, the 3D-UNet-based model with the filling technique achieved the best performance, with a Dice score (Dice score) of 0.7989 ± 0.0398 and a mean intersection over union (mIoU) of 0.6669 ± 0.0540, which were greater than those of the original 3D-UNet-based model. In addition, the oversegmentation ratio (OSR), average surface distance (ASD) and Hausdorff distance (HD) were 0.0666 ± 0.0351, 0.5733 ± 0.1018 and 5.1235 ± 1.4397, respectively, which were better than those of the other models. In addition, when the size of the input image was set to 48 × 48 × 48, 64 × 64 × 64 and 96 × 96 × 96, the model performance gradually improved, and the Dice scores of the proposed model reached 0.7989 ± 0.0398, 0.8371 ± 0.0254 and 0.8674 ± 0.0257, respectively. In addition, the mIoUs reached 0.6669 ± 0.0540, 0.7207 ± 0.0370 and 0.7668 ± 0.0392, respectively.

CONCLUSION

The proposed hippocampus segmentation model constructed by introducing the filling technique into a segmentation network performed better than models built solely on the original network and can improve the efficiency of diagnostic analysis.

Associations between renal function, hippocampal volume, and cognitive impairment in 544 outpatients

Background

Cognitive impairment and brain atrophy are common in chronic kidney disease patients. It remains unclear whether differences in renal function, even within normal levels, influence hippocampal volume (HCV) and cognition. We aimed to investigate the association between estimated glomerular filtration rate (eGFR), HCV and cognition in outpatients.

Methods

This single-center retrospective study enrolled 544 nonrenal outpatients from our hospital. All participants underwent renal function assessment and 3.0 T magnetic resonance imaging (MRI) in the same year. HCV was also measured, and cognitive assessments were obtained. The correlations between eGFR, HCV, and cognitive function were analyzed. Logistic regression analysis was performed to identify the risk factors for hippocampal atrophy and cognitive impairment. Receiver-operator curves (ROCs) were performed to find the cut-off value of HCV that predicts cognitive impairment.

Results

The mean age of all participants was 66.5 ± 10.9 years. The mean eGFR of all participants was 88.5 ± 15.1 mL/min/1.73 m2. eGFR was positively correlated with HCV and with Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Univariate and multivariate logistic regression analysis showed Age ≥ 65 years, eGFR < 75 mL/min/1.73 m2, Glucose ≥6.1 mmol/L and combined cerebral microvascular diseases were independent risk factors for hippocampal atrophy and Age ≥ 65 years, left hippocampal volume (LHCV) <2,654 mm3 were independent risk factors for cognitive impairment in outpatients. Although initial unadjusted logistic regression analysis indicated that a lower eGFR (eGFR < 75 mL/min/1.73 m2) was associated with poorer cognitive function, this association was lost after adjusting for confounding variables. ROC curve analysis demonstrated that LHCV <2,654 mm3 had the highest AUROC [(0.842, 95% CI: 0.808-0.871)], indicating that LHCV had a credible prognostic value with a high sensitivity and specificity for predicting cognitive impairment compared with age in outpatients.

Conclusion

Higher eGFR was associated with higher HCV and better cognitive function. eGFR < 75 mL/min/1.73 m2 was an independent risk factor for hippocampal atrophy after adjusting for age. It is suggested that even eGFR < 75 mL/min/1.73 m2, lower eGFR may still be associated with hippocampal atrophy, which is further associated with cognitive impairment. LHCV was a favorable prognostic marker for predicting cognitive impairment rather than age.

A short-interval longitudinal study of associations between psychological distress and hippocampal grey matter in early adolescence

This study of Australian adolescents (N = 88, 12-13-years-old) investigated the relationship between hippocampal grey matter volume (GMV) and self-reported psychological distress (K10) at four timepoints, across 12 months. Participants were divided into two groups; those who had K10 scores between 10 and 15 for all four timepoints were categorised as "low distress" (i.e., control group; n = 38), while participants who had K10 scores of 16 or higher at least once over the year were categorised as "moderate-high distress" (n = 50). Associations were tested by GEE fitting of GMV and K10 measures at the same time point, and in the preceding and subsequent timepoints. Analyses revealed smaller preceding left GMV and larger preceding right GMV were associated with higher subsequent K10 scores in the "moderate-high distress" group. This was not observed in the control group. In contrast, the control group showed significant co-occurring associations (i.e., at the same TP) between GMV and K10 scores. The "moderate-high distress" group experienced greater variability in distress. These results suggest that GMV development in early adolescence is differently associated with psychological distress for those who experience "moderate-high distress" at some point over the year, compared to controls. These findings offer a novel way to utilise short-interval, multiple time-point longitudinal data to explore changes in volume and experience of psychological distress in early adolescents. The results suggest hippocampal volume in early adolescence may be linked to fluctuations in psychological distress.

High-resolution MRI synthesis using a data-driven framework with denoising diffusion probabilistic modeling

Objective. High-resolution magnetic resonance imaging (MRI) can enhance lesion diagnosis, prognosis, and delineation. However, gradient power and hardware limitations prohibit recording thin slices or sub-1 mm resolution. Furthermore, long scan time is not clinically acceptable. Conventional high-resolution images generated using statistical or analytical methods include the limitation of capturing complex, high-dimensional image data with intricate patterns and structures. This study aims to harness cutting-edge diffusion probabilistic deep learning techniques to create a framework for generating high-resolution MRI from low-resolution counterparts, improving the uncertainty of denoising diffusion probabilistic models (DDPM).Approach. DDPM includes two processes. The forward process employs a Markov chain to systematically introduce Gaussian noise to low-resolution MRI images. In the reverse process, a U-Net model is trained to denoise the forward process images and produce high-resolution images conditioned on the features of their low-resolution counterparts. The proposed framework was demonstrated using T2-weighted MRI images from institutional prostate patients and brain patients collected in the Brain Tumor Segmentation Challenge 2020 (BraTS2020).Main results. For the prostate dataset, the bicubic interpolation model (Bicubic), conditional generative-adversarial network (CGAN), and our proposed DDPM framework improved the noise quality measure from low-resolution images by 4.4%, 5.7%, and 12.8%, respectively. Our method enhanced the signal-to-noise ratios by 11.7%, surpassing Bicubic (9.8%) and CGAN (8.1%). In the BraTS2020 dataset, the proposed framework and Bicubic enhanced peak signal-to-noise ratio from resolution-degraded images by 9.1% and 5.8%. The multi-scale structural similarity indexes were 0.970 ± 0.019, 0.968 ± 0.022, and 0.967 ± 0.023 for the proposed method, CGAN, and Bicubic, respectively.Significance. This study explores a deep learning-based diffusion probabilistic framework for improving MR image resolution. Such a framework can be used to improve clinical workflow by obtaining high-resolution images without penalty of the long scan time. Future investigation will likely focus on prospectively testing the efficacy of this framework with different clinical indications.

An imaging review of the hippocampus and its common pathologies

The hippocampus is a complex structure located in the mesial temporal lobe that plays a critical role in cognitive and memory-related processes. The hippocampal formation consists of the dentate gyrus, hippocampus proper, and subiculum, and its importance in the neural circuitry makes it a key anatomic structure to evaluate in neuroimaging studies. Advancements in imaging techniques now allow detailed assessment of hippocampus internal architecture and signal features that has improved identification and characterization of hippocampal abnormalities. This review aims to summarize the neuroimaging features of the hippocampus and its common pathologies. It provides an overview of the hippocampal anatomy on magnetic resonance imaging and discusses how various imaging techniques can be used to assess the hippocampus. The review explores neuroimaging findings related to hippocampal variants (incomplete hippocampal inversion, sulcal remnant and choroidal fissure cysts), and pathologies of neoplastic (astrocytoma and glioma, ganglioglioma, dysembryoplastic neuroepithelial tumor, multinodular and vacuolating neuronal tumor, and metastasis), epileptic (mesial temporal sclerosis and focal cortical dysplasia), neurodegenerative (Alzheimer's disease, progressive primary aphasia, and frontotemporal dementia), infectious (Herpes simplex virus and limbic encephalitis), vascular (ischemic stroke, arteriovenous malformation, and cerebral cavernous malformations), and toxic-metabolic (transient global amnesia and opioid-associated amnestic syndrome) etiologies.

Toward hippocampal volume measures on ultra-high field magnetic resonance imaging: a comprehensive comparison study between deep learning and conventional approaches

The hippocampus is a complex brain structure that plays an important role in various cognitive aspects such as memory, intelligence, executive function, and path integration. The volume of this highly plastic structure is identified as one of the most important biomarkers of specific neuropsychiatric and neurodegenerative diseases. It has also been extensively investigated in numerous aging studies. However, recent studies on aging show that the performance of conventional approaches in measuring the hippocampal volume is still far from satisfactory, especially in terms of delivering longitudinal measures from ultra-high field magnetic resonance images (MRIs), which can visualize more boundary details. The advancement of deep learning provides an alternative solution to measuring the hippocampal volume. In this work, we comprehensively compared a deep learning pipeline based on nnU-Net with several conventional approaches including Freesurfer, FSL and DARTEL, for automatically delivering hippocampal volumes: (1) Firstly, we evaluated the segmentation accuracy and precision on a public dataset through cross-validation. Results showed that the deep learning pipeline had the lowest mean (L = 1.5%, R = 1.7%) and the lowest standard deviation (L = 5.2%, R = 6.2%) in terms of volume percentage error. (2) Secondly, sub-millimeter MRIs of a group of healthy adults with test-retest 3T and 7T sessions were used to extensively assess the test-retest reliability. Results showed that the deep learning pipeline achieved very high intraclass correlation coefficients (L = 0.990, R = 0.986 for 7T; L = 0.985, R = 0.983 for 3T) and very small volume percentage differences (L = 1.2%, R = 0.9% for 7T; L = 1.3%, R = 1.3% for 3T). (3) Thirdly, a Bayesian linear mixed effect model was constructed with respect to the hippocampal volumes of two healthy adult datasets with longitudinal 7T scans and one disease-related longitudinal dataset. It was found that the deep learning pipeline detected both the subtle and disease-related changes over time with high sensitivity as well as the mild differences across subjects. Comparison results from the aforementioned three aspects showed that the deep learning pipeline significantly outperformed the conventional approaches by large margins. Results also showed that the deep learning pipeline can better accommodate longitudinal analysis purposes.

DMCA-GAN: Dual Multilevel Constrained Attention GAN for MRI-Based Hippocampus Segmentation

Precise segmentation of the hippocampus is essential for various human brain activity and neurological disorder studies. To overcome the small size of the hippocampus and the low contrast of MR images, a dual multilevel constrained attention GAN for MRI-based hippocampus segmentation is proposed in this paper, which is used to provide a relatively effective balance between suppressing noise interference and enhancing feature learning. First, we design the dual-GAN backbone to effectively compensate for the spatial information damage caused by multiple pooling operations in the feature generation stage. Specifically, dual-GAN performs joint adversarial learning on the multiscale feature maps at the end of the generator, which yields an average Dice coefficient (DSC) gain of 5.95% over the baseline. Next, to suppress MRI high-frequency noise interference, a multilayer information constraint unit is introduced before feature decoding, which improves the sensitivity of the decoder to forecast features by 5.39% and effectively alleviates the network overfitting problem. Then, to refine the boundary segmentation effects, we construct a multiscale feature attention restraint mechanism, which forces the network to concentrate more on effective multiscale details, thus improving the robustness. Furthermore, the dual discriminators D1 and D2 also effectively prevent the negative migration phenomenon. The proposed DMCA-GAN obtained a DSC of 90.53% on the Medical Segmentation Decathlon (MSD) dataset with tenfold cross-validation, which is superior to the backbone by 3.78%.

Hippocampal subfield associations with memory depend on stimulus modality and retrieval mode

Hippocampal atrophy is a well-known feature of age-related memory decline, and hippocampal subfields may contribute differently to this decline. In this cross-sectional study, we investigated the associations between hippocampal subfield volumes and performance in free recall and recognition memory tasks in both verbal and visual modalities in older adults without dementia. We collected MRIs from 97 (41 males) right-handed participants aged over 60. We segmented the right and left hippocampi into (i) dentate gyrus and cornu ammonis 4 (DG/CA4); (ii) CA2 and CA3 (CA2/CA3); (iii) CA1; (iv) strata radiatum, lacunosum and moleculare; and (v) subiculum. Memory was assessed with verbal free recall and recognition tasks, as well as visual free recall and recognition tasks. Amyloid-β and hippocampal tau positivity were assessed using [18F]AZD4694 and [18F]MK6240 PET tracers, respectively. The verbal free recall and verbal recognition performances were positively associated with CA1 and strata radiatum, lacunosum and moleculare volumes. The verbal free recall and visual free recall were positively correlated with the right DG/CA4. The visual free recall, but not verbal free recall, was also associated with the right CA2/CA3. The visual recognition was not significantly associated with any subfield volume. Hippocampal tau positivity, but not amyloid-β positivity, was associated with reduced DG/CA4, CA2/CA3 and strata radiatum, lacunosum and moleculare volumes. Our results suggest that memory performances are linked to specific subfields. CA1 appears to contribute to the verbal modality, irrespective of the free recall or recognition mode of retrieval. In contrast, DG/CA4 seems to be involved in the free recall mode, irrespective of verbal or visual modalities. These results are concordant with the view that DG/CA4 plays a primary role in encoding a stimulus' distinctive attributes, and that CA2/CA3 could be instrumental in recollecting a visual memory from one of its fragments. Overall, we show that hippocampal subfield segmentation can be useful for detecting early volume changes and improve our understanding of the hippocampal subfields' roles in memory.

Evaluation of 'Normal' Cognitive Functions and Correlation With MRI Volumetry: Towards a Definition of Vascular Cognitive Impairment

Introduction It is important to establish criteria to define vascular cognitive impairment (VCI) in India as VCI is an image-based diagnosis and magnetic resonance imaging (MRI) changes resulting from age with prevalent vascular risk factors may confound MRI interpretation. The objective of this study was to establish normative community data for MRI volumetry including white matter hyperintensity volume (WMHV), correlated with age-stratified cognitive scores and vascular risk factors (VRFs), in adults aged 40 years and above.  Methods We screened 2651 individuals without known neurological morbidity, living in Mumbai and nearby rural areas, using validated Marathi translations of Kolkata Cognitive Battery (KCB) and geriatric depression score (GDS). We stratified 1961 persons with GDS ≤9 by age and cognitive score, and randomly selected 10% from each subgroup for MRI brain volumetry. Crude volumes were standardized to reflect percentage of intracranial volume.  Results MRI volumetry studies were done in 199 individuals (F/M = 90/109; 73 with body mass index (BMI) ≥25; 44 hypertensives; 29 diabetics; mean cognitive score 76.3). Both grey and white matter volumes decreased with increasing age. WMHV increased with age and hypertension. Grey matter volume (GMV) decreased with increasing WMHV. Positive predictors of cognition included standardized hippocampal volume (HCV), urban living, education, and BMI, while WMHV and age were negative predictors. Urban dwellers had higher cognitive scores than rural, and, paradoxically, smaller HCV.  Conclusion In this study of MRI volumetry correlated with age, cognitive scores and VRFs, increasing age and WMHV predicted lower cognitive scores, whereas urban living and hippocampal volume predicted higher scores. Age and WMHV also correlated with decreasing GMV. Further study is warranted into sociodemographic and biological factors that mutually influence cognition and brain volumes, including nutritional and endocrine factors, especially at lower cognitive score bands. In this study, at the lower KCB score bins, the lack of laboratory data pertaining to nutritional and endocrine deficiencies is a drawback that reflects the logistical limitations of screening large populations at the community level. Our volumetric data which is age and cognition stratified, and takes into account the vascular risk factors associated, nevertheless constitutes important baseline data for the Indian population. Our findings could possibly contribute to the formulation of baseline criteria for defining VCI in India and could help in early diagnosis and control of cognitive decline and its key risk factors.

Hippocampal grading provides higher classification accuracy for those in the AD trajectory than hippocampal volume

Much research has focused on neurodegeneration in aging and Alzheimer's disease (AD). We developed Scoring by Nonlocal Image Patch Estimator (SNIPE), a non-local patch-based measure of anatomical similarity and hippocampal segmentation to measure hippocampal change. While SNIPE shows enhanced predictive power over hippocampal volume, it is unknown whether SNIPE is more strongly associated with group differences between normal controls (NC), early MCI (eMCI), late (lMCI), and AD than hippocampal volume. Alzheimer's Disease Neuroimaging Initiative older adults were included in the first analyses (N = 1666, 513 NCs, 269 eMCI, 556 lMCI, and 328 AD). Sub-analyses investigated amyloid positive individuals (N = 834; 179 NC, 148 eMCI, 298 lMCI, and 209 AD) to determine accuracy in those on the AD trajectory. We compared SNIPE grading, SNIPE volume, and Freesurfer volume as features in seven different machine learning techniques classifying participants into their correct cohort using 10-fold cross-validation. The best model was then validated in the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL). SNIPE grading provided the highest classification accuracy for all classifications in both the full and amyloid positive sample. When classifying NC:AD, SNIPE grading provided an 89% accuracy (full sample) and 87% (amyloid positive sample). Freesurfer volume provided much lower accuracies of 65% (full sample) and 46% (amyloid positive sample). In the AIBL validation cohort, SNIPE grading provided a 90% classification accuracy for NC:AD. These findings suggest SNIPE grading provides increased classification accuracy over both SNIPE and Freesurfer volume. SNIPE grading offers promise to accurately identify people with and without AD.

Structured memory representations develop at multiple time scales in hippocampal-cortical networks

Influential views of systems memory consolidation posit that the hippocampus rapidly forms representations of specific events, while neocortical networks extract regularities across events, forming the basis of schemas and semantic knowledge. Neocortical extraction of schematic memory representations is thought to occur on a protracted timescale of months, especially for information that is unrelated to prior knowledge. However, this theorized evolution of memory representations across extended timescales, and differences in the temporal dynamics of consolidation across brain regions, lack reliable empirical support. To examine the temporal dynamics of memory representations, we repeatedly exposed human participants to structured information via sequences of fractals, while undergoing longitudinal fMRI for three months. Sequence-specific activation patterns emerged in the hippocampus during the first 1-2 weeks of learning, followed one week later by high-level visual cortex, and subsequently the medial prefrontal and parietal cortices. Schematic, sequence-general representations emerged in the prefrontal cortex after 3 weeks of learning, followed by the medial temporal lobe and anterior temporal cortex. Moreover, hippocampal and most neocortical representations showed sustained rather than time-limited dynamics, suggesting that representations tend to persist across learning. These results show that specific hippocampal representations emerge early, followed by both specific and schematic representations at a gradient of timescales across hippocampal-cortical networks as learning unfolds. Thus, memory representations do not exist only in specific brain regions at a given point in time, but are simultaneously present at multiple levels of abstraction across hippocampal-cortical networks.

Learning from errors: Distinct neural networks for monitoring errors and maintaining corrects through repeated practice and feedback

How memory representations are eventually established and maintained in the brain is one of central issues in memory research. Although the hippocampus and various brain regions have been shown to be involved in learning and memory, how they coordinate to support successful memory through errors is unclear. In this study, a retrieval practice (RP) - feedback (FB) paradigm was adopted to address this issue. Fifty-six participants (27 in the behavioral group, and 29 in the fMRI group) learned 120 Swahili-Chinese words associations and underwent two RP-answer FB cycles (i.e., RP1, FB1, RP2, FB2). The responses of the fMRI group were recorded in the fMRI scanner. The trials were divided based on participant's performance (correct or incorrect, C or I) during the two RPs and the final test (i.e., trial type, CCC, ICC, IIC III). The results showed that the regions in the salience and executive control networks (S-ECN) during RP, but not during FB, was strongly predictive of final successful memory. Their activation was just before the errors were corrected (i.e., RP1 in ICC trials and RP2 in IIC trials). The anterior insula (AI) is a core region in monitoring repeated errors, and it had differential connectivity with the default mode network (DMN) regions and the hippocampus during the RP and FB phases to inhibit incorrect answers and update memory. In contrast, maintaining corrected memory representation requires repeated RP and FB, which was associated with the DMN activation. Our study clarified how different brain regions support error monitoring and memory maintenance through repeated RP and FB, and emphasized the role of the insula in learning from errors.

Hippocampal activity during memory and visual perception: The role of representational content

The functional organisation of the medial temporal lobe (MTL) has long been described on the basis of cognitive processes such as recollection or familiarity. However, this view has recently been challenged, and researchers have proposed decomposing cognitive phenomena into representations and operations. According to the representational view, representations, such as scenes for the hippocampus and objects for the perirhinal cortex, are critical in understanding the role of MTL regions in cognition. In the present study, 51 healthy young participants underwent functional magnetic resonance imaging (fMRI) while completing a visual-discrimination task. Subsequently, half of the participants performed a patch-cue recognition procedure in which "Rec" responses are believed to reflect the operation of pattern completion, whereas the other half performed a whole-item remember/know procedure. We replicated the previously-reported demonstration that hippocampal involvement in pattern completion is preferential for scenes as compared with objects. In contrast, the perirhinal cortex was more recruited for object processing than for scene processing. We further extended these results to the operations of strength-signal memory and visual discrimination. Finally, the modulation of hippocampal engagement in pattern completion by representational content was found to be specific to its anterior segment. This observation is consistent with the proposal that this segment would process broad/global representations, whereas the posterior hippocampus would perform sharp/local representations. Taken together, these results favour the representational view of MTL functional organisation, but support that this specialisation differs along the hippocampal long-axis.

Grey matter changes on brain MRI in subjective cognitive decline: a systematic review

Introduction

People with subjective cognitive decline (SCD) report cognitive deterioration. However, their performance in neuropsychological evaluation falls within the normal range. The present study aims to analyse whether structural magnetic resonance imaging (MRI) reveals grey matter changes in the SCD population compared with healthy normal controls (HC).

Methods

Parallel systematic searches in PubMed and Web of Science databases were conducted, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Quality assessment was completed using the Newcastle-Ottawa Scale (NOS).

Results

Fifty-one MRI studies were included. Thirty-five studies used a region of interest (ROI) analysis, 15 used a voxel-based morphometry (VBM) analysis and 10 studies used a cortical thickness (CTh) analysis. Ten studies combined both, VBM or CTh analysis with ROI analysis.

Conclusions

Medial temporal structures, like the hippocampus or the entorhinal cortex (EC), seemed to present grey matter reduction in SCD compared with HC, but the samples and results are heterogeneous. Larger sample sizes could help to better determine if these grey matter changes are consistent in SCD subjects.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01031-6.

Category-specific memory encoding in the medial temporal lobe and beyond: the role of reward

The medial temporal lobe (MTL), including the hippocampus (HC), perirhinal cortex (PRC), and parahippocampal cortex (PHC), is central to memory formation. Reward enhances memory through interplay between the HC and substantia nigra/ventral tegmental area (SNVTA). While the SNVTA also innervates the MTL cortex and amygdala (AMY), their role in reward-enhanced memory is unclear. Prior research suggests category specificity in the MTL cortex, with the PRC and PHC processing object and scene memory, respectively. It is unknown, however, whether reward modulates category-specific memory processes. Furthermore, no study has demonstrated clear category specificity in the MTL for encoding processes contributing to subsequent recognition memory. To address these questions, we had 39 healthy volunteers (27 for all memory-based analyses) undergo functional magnetic resonance imaging while performing an incidental encoding task pairing objects or scenes with high or low reward, followed by a next-day recognition test. Behaviorally, high reward preferably enhanced object memory. Neural activity in the PRC and PHC reflected successful encoding of objects and scenes, respectively. Importantly, AMY encoding effects were selective for high-reward objects, with a similar pattern in the PRC. The SNVTA and HC showed no clear evidence of successful encoding. This behavioral and neural asymmetry may be conveyed through an anterior-temporal memory system, including the AMY and PRC, potentially in interplay with the ventromedial prefrontal cortex.

Intergenerational transmission of psychological trauma: A structural neuroimaging study

Traumatic events have an important effect in human life and may lead to psychopathological disturbances by affecting the personal and social lives of individuals. Recently, various studies have been reported in the literature showing that the traumatic experiences may be associated with intergenerational psychopathologies. However, there is limited data regarding the neuroimaging studies investigating changes in brain structures in children of traumatized mothers. In this study, we aimed to investigate the potential changes in the hippocampus and amygdala volumes in the children of mothers exposed to mass trauma. The traumatic event experienced by the mothers was the two devastating earthquakes they experienced when they were teenagers. Hippocampus and amygdala volumes were evaluated in magnetic resonance imaging of 40 children whose mothers were exposed to earthquakes and 27 children in control group. Bilateral amygdala volumes were significantly smaller in the children of mothers exposed to earthquake compared to the control group. In addition, right amygdala and hippocampus volumes were smaller in children of mothers exposed to earthquakes than left. This is one of the pioneering neuroimaging studies on the intergenerational transmission of trauma. Our study shows that there may be a potential relationship between intergenerational trauma and various brain structures.

Category-sensitive incidental reinstatement in medial temporal lobe subregions during word recognition

During associative retrieval, the brain reinstates neural representations that were present during encoding. The human medial temporal lobe (MTL), with its subregions hippocampus (HC), perirhinal cortex (PRC), and parahippocampal cortex (PHC), plays a central role in neural reinstatement. Previous studies have given compelling evidence for reinstatement in the MTL during explicitly instructed associative retrieval. High-confident recognition may be similarly accompanied by recollection of associated information from the encoding context. It is unclear, however, whether high-confident recognition memory elicits reinstatement in the MTL even in the absence of an explicit instruction to retrieve associated information. Here, we addressed this open question using high-resolution fMRI. Twenty-eight male and female human volunteers engaged in a recognition memory task for words that they had previously encoded together with faces and scenes. Using complementary univariate and multivariate approaches, we show that MTL subregions including the PRC, PHC, and HC differentially reinstate category-sensitive representations during high-confident word recognition, even though no explicit instruction to retrieve the associated category was given. This constitutes novel evidence that high-confident recognition memory is accompanied by incidental reinstatement of associated category information in MTL subregions, and supports a functional model of the MTL that emphasizes content-sensitive representations during both encoding and retrieval.

Evolution of magnetic resonance imaging features in cerebral parenchyma from prolonged focal status epilepticus: a case study

It has rarely been documented that permanent alteration of cerebral structures occurs by focal status epilepticus (FSE). We report the case of a 16-year-old boy with FSE in whom serial T1-weighted magnetic resonance volumetry and conventional magnetic resonance imaging were useful for investigating an evolving pattern of morphological changes during and after the FSE, including cortical laminar necrosis (CLN), increased T2 signal intensities, and marked regional atrophy on the corresponding areas. Despite cessation of FSE after adequate medication (combination therapy including clobazam of 1 mg/kg/day), further significant cerebral atrophy was detected at the limited regions where discrete CLN had occurred during the FSE.

The PaleoArchiNeo (PAN) human brain atlas: A dataset on a standard neuroanatomical MRI template following a phylogenetic approach

Cortical atlases provide consistent divisions of the human cortex into areas that have common structural as well as meaningful and distinctive functional characteristics. They constitute a fundamental tool to study and quantify changes in healthy and pathological states. Historically, the most widely used atlases follow the cytoarchitecture described by Brodmann and/or the myeloarchitectonic characteristics described by Vogt-Vogt. These histological approaches have since been combined to the standard anatomical nomenclature of gyri and sulci, referring to the corresponding cytoarchitectonic area(s) present in a gyrus, when applicable or necessary (e.g. area 4 of Brodmann in the pre-central gyrus). More recently, common functional features depicted by resting state functional MRI have guided the division of the cortex into functional regions of interest. However, to date, there are no human MRI atlases that divide the cortex considering the common evolutionary changes experienced by the mammalian cortex. Hence, the present dataset describes the PaleoArchiNeo (PAN) Human Brain, a voxel-based atlas that divides the human cortex into five regions of interest (ROIs) following a phylogenetic approach: 1- archicortex, 2- paleocortex, 3- peri-archicortex, 4- proisocortex, 5- neocortex, and thirty neocortical sub-ROIs that follow the gyral Terminologia Anatomica.The masks of the ROIs and sub-ROIs were segmented on the T1-weighted MNI ICBM 152 2009c symmetric average brain MRI model, the latest version of the most widely used standard brain template. The segmentations have been performed manually by anatomist experts, following the MRI anatomical landmarks that have been previously described, correlated, and validated with histology by other groups.

Environmental overlap influences goal-oriented coding of spatial sequences differently along the long-axis of hippocampus

When navigating our world we often first plan or retrieve a route to our goal, avoiding alternative paths to other destinations. Inspired by computational and animal models, we have recently demonstrated evidence that the human hippocampus supports prospective spatial coding, mediated by interactions with the prefrontal cortex. But the relationship between such signals and the need to discriminate possible routes based on their goal remains unclear. In the current study, we combined human fMRI, multi-voxel pattern analysis, and an established paradigm for contrasting memories of nonoverlapping routes with those of routes that cross paths and must be disambiguated. By classifying goal-oriented representations at the initiation of a navigational route, we demonstrate that environmental overlap modulates goal-oriented representations in the hippocampus. This modulation manifest through representational shifts from posterior to anterior components of the right hippocampus. Moreover, declines in goal-oriented decoding due to overlapping memories were predicted by the strength of the alternative memory, suggesting co-expression and competition between alternatives in the hippocampus during prospective thought. Moreover, exploratory whole-brain analyses revealed that a region of frontopolar cortex, which we have previously tied to prospective route planning, represented goal-states in new overlapping routes. Together, our findings provide insight into the influences of contextual overlap on the long-axis of the hippocampus and a broader memory and planning network that we have long-associated with such navigation tasks.

Effect of 3-Month Aerobic Dance on Hippocampal Volume and Cognition in Elderly People With Amnestic Mild Cognitive Impairment: A Randomized Controlled Trial

As an intermediate state between normal aging and dementia, mild cognitive impairment (MCI), especially amnestic MCI (aMCI), is a key stage in the prevention and intervention of Alzheimer’s disease (AD). Whether dancing could increase the hippocampal volume of seniors with aMCI remains debatable. The aim of this study was to investigate the influence of aerobic dance on hippocampal volume and cognition after 3 months of aerobic dance in older adults with aMCI. In this randomized controlled trial, 68 elderly people with aMCI were randomized to either the aerobic dance group or the control group using a 1:1 allocation ratio. Ultimately, 62 of 68 participants completed this study, and the MRI data of 54 participants were included. A specially designed aerobic dance routine was performed by the dance group three times per week for 3 months, and all participants received monthly healthcare education after inclusion. MRI with a 3.0T MRI scanner and cognitive assessments were performed before and after intervention. High-resolution three-dimensional (3D) T1-weighted anatomical images were acquired for the analysis of hippocampal volume. A total of 35 participants (mean age: 71.51 ± 6.62 years) were randomized into the aerobic dance group and 33 participants (mean age: 69.82 ± 7.74 years) into the control group. A multiple linear regression model was used to detect the association between intervention and the difference of hippocampal volumes as well as the change of cognitive scores at baseline and after 3 months. The intervention group showed greater right hippocampal volume (β [95% CI]: 0.379 [0.117, 0.488], p = 0.002) and total hippocampal volume (β [95% CI]: 0.344 [0.082, 0.446], p = 0.005) compared to the control group. No significant association of age or gender was found with unilateral or global hippocampal volume. There was a correlation between episodic memory and intervention, as the intervention group showed a higher Wechsler Memory Scale-Revised Logical Memory (WMS-RLM) score (β [95% CI]: 0.326 [1.005, 6.773], p = 0.009). Furthermore, an increase in age may cause a decrease in the Mini-Mental State Examination (MMSE) score (β [95% CI]: −0.366 [−0.151, −0.034], p = 0.002). In conclusion, 3 months of aerobic dance could increase the right and total hippocampal volumes and improve episodic memory in elderly persons with aMCI.

Clinical Trial Registration: This study was registered on the Chinese Clinical Trial Registry [www.chictr.org.cn], identifier [ChiCTR-INR-15007420].

Distinct networks coupled with parietal cortex for spatial representations inside and outside the visual field

Our mental representation of egocentric space is influenced by the disproportionate sensory perception of the body. Previous studies have focused on the neural architecture for egocentric representations within the visual field. However, the space representation underlying the body is still unclear. To address this problem, we applied both functional Magnitude Resonance Imaging (fMRI) and Magnetoencephalography (MEG) to a spatial-memory paradigm by using a virtual environment in which human participants remembered a target location left, right, or back relative to their own body. Both experiments showed larger involvement of the frontoparietal network in representing a retrieved target on the left/right side than on the back. Conversely, the medial temporal lobe (MTL)-parietal network was more involved in retrieving a target behind the participants. The MEG data showed an earlier activation of the MTL-parietal network than that of the frontoparietal network during retrieval of a target location. These findings suggest that the parietal cortex may represent the entire space around the self-body by coordinating two distinct brain networks.

Developmental Timing of Trauma in Women Predicts Unique Extracellular Vesicle Proteome Signatures

BACKGROUND

Exposure to traumatic events is a risk factor for negative physical and mental health outcomes. However, the underlying biological mechanisms that perpetuate these lasting effects are not known.

METHODS

We investigated the impact and timing of sexual trauma, a specific type of interpersonal violence, experienced during key developmental windows of childhood, adolescence, or adulthood on adult health outcomes and associated biomarkers, including circulating cell-free mitochondrial DNA levels and extracellular vesicles (EVs), in a predominantly Black cohort of women (N = 101).

RESULTS

Significant changes in both biomarkers examined, circulating cell-free mitochondrial DNA levels and EV proteome, were specific to developmental timing of sexual trauma. Specifically, we identified a large number of keratin-related proteins from EVs unique to the adolescent sexual trauma group. Remarkably, the majority of these keratin proteins belong to a 17q21 gene cluster, which suggests a potential local epigenetic regulatory mechanism altered by adolescent trauma to impact keratinocyte EV secretion or its protein cargo. These results, along with changes in fear-potentiated startle and skin conductance detected in these women, suggest that sexual violence experienced during the specific developmental window of adolescence may involve unique programming of the skin, the body's largest stress organ.

CONCLUSIONS

Together, these descriptive studies provide novel insight into distinct biological processes altered by trauma experienced during specific developmental windows. Future studies will be required to mechanistically link these biological processes to health outcomes.

Dynamic targeting enables domain-general inhibitory control over action and thought by the prefrontal cortex

Over the last two decades, inhibitory control has featured prominently in accounts of how humans and other organisms regulate their behaviour and thought. Previous work on how the brain stops actions and thoughts, however, has emphasised distinct prefrontal regions supporting these functions, suggesting domain-specific mechanisms. Here we show that stopping actions and thoughts recruits common regions in the right dorsolateral and ventrolateral prefrontal cortex to suppress diverse content, via dynamic targeting. Within each region, classifiers trained to distinguish action-stopping from action-execution also identify when people are suppressing their thoughts (and vice versa). Effective connectivity analysis reveals that both prefrontal regions contribute to action and thought stopping by targeting the motor cortex or the hippocampus, depending on the goal, to suppress their task-specific activity. These findings support the existence of a domain-general system that underlies inhibitory control and establish Dynamic Targeting as a mechanism enabling this ability.

Altered Hippocampal Resting-state Functional Connectivity in Highly Superior Autobiographical Memory

Individuals with Highly Superior Autobiographical Memory (HSAM) provide the opportunity to investigate the neurobiological substrates of enhanced memory performance. While previous studies started to assess the neural correlates of memory retrieval in HSAM, here we assessed for the first time the intrinsic connectivity of a core memory region, the hippocampus, with the whole brain, in 8 HSAM subjects (HSAMs) and 21 controls during resting-state functional neuroimaging. We found in HSAMs vs. controls disrupted hippocampal resting-state functional connectivity (rsFC) with high-level control regions belonging to the saliency network (the anterior cingulate cortex and the left and right insulae), and to the ventral fronto-parietal attentional network (the temporo-parietal junction and the inferior frontal gyrus), also involved with salience detection. Conversely, HSAMs showed enhanced hippocampal rsFC with sensory regions along the fusiform gyrus and the inferior temporal cortex. This altered pattern of hippocampal rsFC might be interpreted as a reduced capability of HSAMs to discriminate and select salient information, with a subsequent increase in the probability to encode and consolidate sensory information irrespective of their task-relevancy. Ultimately, these findings provide evidence that HSAM might be paradoxically enabled by an altered hippocampal rsFC that bypasses regions involved with salience detection in favor of specialized sensory regions.

Charting the human amygdala development across childhood and adolescence: Manual and automatic segmentation

The developmental pattern of the amygdala throughout childhood and adolescence has been inconsistently reported in previous neuroimaging studies. Given the relatively small size of the amygdala on full brain MRI scans, discrepancies may be partly due to methodological differences in amygdalar segmentation. To investigate the impact of volume extraction methods on amygdala volume, we compared FreeSurfer, FSL and volBrain segmentation measurements with those obtained by manual tracing. The manual tracing method, which we used as the 'gold standard', exhibited almost perfect intra- and inter-rater reliability. We observed systematic differences in amygdala volumes between automatic (FreeSurfer and volBrain) and manual methods. Specifically, compared with the manual tracing, FreeSurfer estimated larger amygdalae, and volBrain produced smaller amygdalae while FSL demonstrated a mixed pattern. The tracing bias was not uniform, but higher for smaller amygdalae. We further modeled amygdalar growth curves using accelerated longitudinal cohort data from the Chinese Color Nest Project (http://deepneuro.bnu.edu.cn/?p=163). Trajectory modeling and statistical assessments of the manually traced amygdalae revealed linearly increasing and parallel developmental patterns for both girls and boys, although the amygdalae of boys were larger than those of girls. Compared to these trajectories, the shapes of developmental curves were similar when using the volBrain derived volumes. FreeSurfer derived trajectories had more nonlinearities and appeared flatter. FSL derived trajectories demonstrated an inverted U shape and were significantly different from those derived from manual tracing method. The use of amygdala volumes adjusted for total gray-matter volumes, but not intracranial volumes, resolved the shape discrepancies and led to reproducible growth curves between manual tracing and the automatic methods (except FSL). Our findings revealed steady growth of the human amygdala, mirroring its functional development across the school age. Methodological improvements are warranted for current automatic tools to achieve more accurate amygdala structure at school age, calling for next generation tools.

Neuronal current imaging: An experimental method to investigate electrical currents in dogs with idiopathic epilepsy

BACKGROUND

The diagnosis of idiopathic epilepsy (IE) in dogs is based on exclusion of other potential causes of seizures. Recently, a novel magnetic resonance imaging (MRI) sequence that utilizes a variant of the rotary saturation approach has been suggested to detect weak transient magnetic field oscillations generated by neuronal currents in humans with epilepsy.

HYPOTHESIS/OBJECTIVES

Effects on the magnetic field evoked by intrinsic epileptic activity can be detected by MRI in the canine brain. As proof-of-concept, the novel MRI sequence to detect neuronal currents was applied in dogs.

ANIMALS

Twelve dogs with IE and 5 control dogs without a history of epileptic seizures were examined.

METHODS

Prospective case-control study as proof-of-concept. All dogs underwent a clinical neurological examination, scalp electroencephalography, cerebrospinal fluid analysis, and MRI. The MRI examination included a spin-locking (SL) experiment applying a low-power on-resonance radiofrequency pulse in a predefined frequency domain in the range of oscillations generated by the epileptogenic tissue.

RESULTS

In 11 of 12 dogs with IE, rotary saturation effects were detected by the MRI sequence. Four of 5 control dogs did not show rotary saturation effects. One control dog with a diagnosis of neuronal ceroid lipofuscinosis had SL-related effects, but did not have epileptic seizures clinically.

CONCLUSIONS AND CLINICAL IMPORTANCE

The proposed MRI method detected neuronal currents in dogs with epileptic seizures and represents a potential new line of research to investigate neuronal currents possibly related to IE in dogs.

Prenatal Maternal Stress From a Natural Disaster and Hippocampal Volumes: Gene-by-Environment Interactions in Young Adolescents From Project Ice Storm

Gene-by-environment interactions influence brain development from conception to adulthood. In particular, the prenatal period is a window of vulnerability for the interplay between environmental and genetic factors to influence brain development. Rodent and human research demonstrates that prenatal maternal stress (PNMS) alters hippocampal volumes. Although PNMS affects hippocampal size on average, similar degrees of PNMS lead to different effects in different individuals. This differential susceptibility to the effects of PNMS may be due to genetic variants. Hence, we investigated the role of genetic variants of two SNPs that are candidates to moderate the effects of PNMS on hippocampal volume: COMT (rs4680) and BDNF (rs6265). To investigate this, we assessed 53 children who were in utero during the January 1998 Quebec ice storm. In June 1998 their mothers responded to questionnaires about their objective, cognitive, and subjective levels of stress from the ice storm. When children were 11 1/2 years old, T1-weighted structural magnetic resonance imaging (MRI) scans were obtained using a 3T scanner and analyzed to determine hippocampal volumes. We collected and genotyped the children's saliva DNA. Moderation analyses were conducted to determine whether either or both of the SNPs moderate the effect of PNMS on hippocampal volumes. We found that objective hardship was associated with right hippocampal volume in girls, and that the BDNF and COMT genotypes were associated with left hippocampal volume in boys and girls. In addition, SNPs located on COMT moderated the effect of maternal objective distress in boys, and subjective distress in girls, on both right hippocampal volume. Thus, we conclude that an individual's genotype alters their susceptibility to the effects of PNMS.

Automated, open-source segmentation of the Hippocampus and amygdala with the open Vanderbilt archive of the temporal lobe

Examining volumetric differences of the amygdala and anterior-posterior regions of the hippocampus is important for understanding cognition and clinical disorders. However, the gold standard manual segmentation of these structures is time and labor-intensive. Automated, accurate, and reproducible techniques to segment the hippocampus and amygdala are desirable. Here, we present a hierarchical approach to multi-atlas segmentation of the hippocampus head, body and tail and the amygdala based on atlases from 195 individuals. The Open Vanderbilt Archive of the temporal Lobe (OVAL) segmentation technique outperforms the commonly used FreeSurfer, FSL FIRST, and whole-brain multi-atlas segmentation approaches for the full hippocampus and amygdala and nears or exceeds inter-rater reproducibility for segmentation of the hippocampus head, body and tail. OVAL has been released in open-source and is freely available.

Hippocampal atrophy and quantitative EEG markers in mild cognitive impairment in temporal lobe epilepsy versus extra-temporal lobe epilepsy

OBJECTIVE

Cognitive impairment in temporal lobe epilepsy is widely acknowledged as one of the most well-known comorbidities. This study aimed to explore cognitive impairment and to determine the potential clinical, radiological, and quantitative electroencephalography markers for cognitive impairment in temporal lobe epilepsy patients versus extra-temporal lobe epilepsy.

METHODS

Forty-five patients with temporal lobe epilepsy and forty-five patients with extra-temporal lobe epilepsy were recruited for an administered digit span test, verbal fluency test, mini-mental state examination, digital symbol test, and Montreal cognitive assessment. Also, they were subjected to magnetic resonance imaging assessment for hippocampal atrophy and a quantitative electroencephalography assessment for electroencephalography markers (median frequency, peak frequency, and the alpha-to-theta ratio).

RESULTS

Patients with extra-temporal lobe epilepsy showed non-significant higher epilepsy durations and a higher frequency of seizures. Temporal lobe epilepsy patients showed a more statistically significant family history of epilepsy (37.7%), more history of febrile convulsions (13.3%), higher hippocampal atrophy (17.8%), and lower cognitive scales, especially mini-mental state examination and Montreal cognitive assessment; lower digital symbol test, verbal fluency test, and backward memory of digit span test. Also, temporal lobe epilepsy patients had a strong negative correlation with electroencephalography markers: median frequency, peak frequency, and the alpha-to-theta ratio (r =  - 0.68, P < 0.005 and r =  - 0.64, P < 0.005 and r =  - 0.66, P < 0.005 respectively).

CONCLUSION

Cognitive impairment in patients with temporal lobe epilepsy was correlated with hippocampal atrophy and quantitative electroencephalography abnormalities, especially peak frequency, median frequency, and alpha-to-theta ratio that could be used alone for the identification of early cognitive impairment.

TRIAL REGISTRATION

Clinicaltrials.gov: NCT04376671.

A Novel Method for Differential Prognosis of Brain Degenerative Diseases Using Radiomics-Based Textural Analysis and Ensemble Learning Classifiers

We propose a novel approach to develop a computer-aided decision support system for radiologists to help them classify brain degeneration process as physiological or pathological, aiding in early prognosis of brain degenerative diseases. Our approach applies computational and mathematical formulations to extract quantitative information from biomedical images. Our study explores the longitudinal OASIS-3 dataset, which consists of 4096 brain MRI scans collected over a period of 15 years. We perform feature extraction using Pyradiomics python package that quantizes brain MRI images using different texture analysis methods. Studies indicate that Radiomics has rarely been used for analysis of brain cognition; hence, our study is also a novel effort to determine the efficiency of Radiomics features extracted from structural MRI scans for classification of brain degenerative diseases and to create awareness about Radiomics. For classification tasks, we explore various ensemble learning classification algorithms such as random forests, bagging-based ensemble classifiers, and gradient-boosted ensemble classifiers such as XGBoost and AdaBoost. Such ensemble learning classifiers have not been used for biomedical image classification. We also propose a novel texture analysis matrix, Decreasing Gray-Level Matrix or DGLM. The features extracted from this filter helped to further improve the accuracy of our decision support system. The proposed system based on XGBoost ensemble learning classifiers achieves an accuracy of 97.38%, with sensitivity 99.82% and specificity 97.01%.

Hippocampal volume as treatment predictor in antidepressant naïve patients with major depressive disorder

Major depression disorder (MDD) limits psychosocial functioning and quality of life. One of the biological alterations is a hippocampal volume (HV) reduction. Previous prospective neuroimaging studies present inconsistencies regarding HV reductions and clinical features and response of antidepressant treatment of the participants. To clarify the relationship between antidepressant response and the HV reported, we prospectively evaluated antidepressant-naïve subjects diagnosed with MDD for the first time. We recruited twenty-one subjects and applied the Hamilton Depression Rating Scale (HAM-D), Montgomery-Asberg Depression Rating Scale (MADRS), Beck Depression Inventory (BDI), and the Clinical Global Impression (CGI) scale. The participants underwent brain Magnetic Resonance Imaging (MRI) scanning to measure the HV, and subsequently were treated naturalistically with first-line antidepressant medication for eight weeks. Thirteen subjects met the criteria for remission at eight weeks of treatment. The baseline right and left hippocampal volumes were larger in subjects who achieved remission (p = 0.012) and (p = 0.001), respectively. The main finding of this study is that the antidepressant naïve subjects who met the criteria for clinical remission according to the HAM-D, MADRS, and the CGI scale scores, had larger pretreatment hippocampal volumes. Our results assess the HV as a treatment outcome predictor.

Developmental variation in testosterone:cortisol ratio alters cortical- and amygdala-based cognitive processes

Testosterone (T) and cortisol (C) are the end products of neuroendocrine axes that interact with the process of shaping brain structure and function. Relative levels of T:C (TC ratio) may alter prefrontal-amygdala functional connectivity in adulthood. What remains unclear is whether TC-related effects are rooted to childhood and adolescence. We used a healthy cohort of 4-22-year-olds to test for associations between TC ratios, brain structure (amygdala volume, cortical thickness (CTh), and their coordinated growth), as well as cognitive and behavioral development. We found greater TC ratios to be associated with the growth of specific brain structures: 1) parietal CTh; 2) covariance of the amygdala with CTh in visual and somatosensory areas. These brain parameters were in turn associated with lower verbal/executive function and higher spatial working memory. In sum, individual TC profiles may confer a particular brain phenotype and set of cognitive strengths and vulnerabilities, prior to adulthood.

Impact of Mesial Temporal Lobe Resection on Brain Structure in Medically Refractory Epilepsy

OBJECTIVE

Surgical resection can decrease seizure frequency in medically intractable temporal lobe epilepsy. However, the functional and structural consequences of this intervention on brain circuitry are poorly understood. We investigated structural changes that occur in brain circuits after mesial temporal lobe resection for refractory epilepsy. Specifically, we used neuroimaging techniques to evaluate changes in 1) contralesional hippocampal and bilateral mammillary body volume and 2) brain-wide cortical thickness.

METHODS

Serial T1-weighted brain magnetic resonance images were acquired before and after surgery (1.6 ± 0.5 year interval) in 21 patients with temporal lobe epilepsy (9 women, 12 men; mean age, 39.4 ± 11.5 years) who had undergone unilateral temporal lobe resection (14 anterior temporal lobectomy; 7 selective amygdalohippocampectomy). Blinded manual segmentation of the unresected hippocampal formation and bilateral mammillary bodies was performed using the Pruessner and Copenhaver protocols, respectively. Brain-wide cortical thickness estimates were computed using the CIVET pipeline.

RESULTS

Surgical resection was associated with a 5% reduction in contralesional hippocampal volume (P < 0.01) and a 9.5% reduction in mammillary body volume (P = 0.03). In addition, significant changes in cortical thickness were observed in contralesional anterior and middle cingulate gyrus and insula (P_{false discovery rate} < 0.01) as well as in other temporal, frontal, and occipital regions (P_{false discovery rate} < 0.05). Postoperative verbal memory function was significantly associated with cortical thickness change in contralesional inferior temporal gyrus (R² = 0.39; P = 0.03).

CONCLUSIONS

These results indicate that mesial temporal lobe resection is associated with both volume loss in spared Papez circuitry and changes in cortical thickness across the brain.

Distinct patterns of hippocampal activity associated with color and spatial source memory

The hippocampus is known to be involved in source memory across a wide variety of stimuli and source types. Thus, source memory activity in the hippocampus is thought to be domain-general such that different types of source information are similarly processed in the hippocampus. However, there is some evidence of domain-specificity for spatial and temporal source information. The current fMRI study aimed to determine whether patterns of activity in the hippocampus differed for two types of visual source information: spatial location and background color. Participants completed three runs of a spatial memory task and three runs of a color memory task. During the study phase, 32 line drawings of common objects and animals were presented to either the left or right of fixation for the spatial memory task or on either a red or green background for the color memory task. During the test phase of both tasks, 48 object word labels were presented in the center of the screen and participants classified the corresponding item as old and previously on the "left"/on a "green" background, old and previously on the "right"/on a "red" background, or "new." Two analysis methods were employed to assess whether hippocampal activity differed between the two source types: a general linear model analysis and a classification-based searchlight multivoxel pattern analysis (MVPA). The searchlight MVPA revealed that activity associated with spatial memory and color memory could be classified with above-chance accuracy in a region of the right anterior hippocampus, and a follow-up analysis revealed that there was a significant effect of memory accuracy. These results indicate that different types of source memory are represented by distinct patterns of activity in the hippocampus.

Evidence for a gradient within the medial temporal lobes for flexible retrieval under hierarchical task rules

A fundamental question in memory research is how the hippocampus processes contextual cues to retrieve distinct mnemonic associations. Prior research has emphasized the importance of hippocampal-prefrontal interactions for context-dependent memory. Our fMRI study examined the human medial temporal lobes (MTL) and their prefrontal interactions when retrieving memories associated with hierarchically organized task contexts. Participants learned virtual object-location associations governed by subordinate and superordinate task rules, which could be independently cued to change. On each fMRI trial, participants retrieved the correct object for convergent rule and location contextual information. Results demonstrated that hippocampal activity and hippocampal-prefrontal functional interconnectivity distinguished retrieval under different levels of hierarchically organized task rules. In explicit contrast to the hippocampal tail, anterior (body and head) regions were recruited specifically for superordinate changes in the contextual hierarchy. The hippocampal body also differed in its functional connectivity with the prefrontal cortex for superordinate versus subordinate changes. Our findings demonstrate a gradient in MTL for associative retrieval under changing task rules, and advance understanding of hippocampal-prefrontal interactions that support flexible contextual memory.

3D MRI Reconstruction Based on 2D Generative Adversarial Network Super-Resolution

The diagnosis of brain pathologies usually involves imaging to analyze the condition of the brain. Magnetic resonance imaging (MRI) technology is widely used in brain disorder diagnosis. The image quality of MRI depends on the magnetostatic field strength and scanning time. Scanners with lower field strengths have the disadvantages of a low resolution and high imaging cost, and scanning takes a long time. The traditional super-resolution reconstruction method based on MRI generally states an optimization problem in terms of prior information. It solves the problem using an iterative approach with a large time cost. Many methods based on deep learning have emerged to replace traditional methods. MRI super-resolution technology based on deep learning can effectively improve MRI resolution through a three-dimensional convolutional neural network; however, the training costs are relatively high. In this paper, we propose the use of two-dimensional super-resolution technology for the super-resolution reconstruction of MRI images. In the first reconstruction, we choose a scale factor of 2 and simulate half the volume of MRI slices as input. We utilize a receiving field block enhanced super-resolution generative adversarial network (RFB-ESRGAN), which is superior to other super-resolution technologies in terms of texture and frequency information. We then rebuild the super-resolution reconstructed slices in the MRI. In the second reconstruction, the image after the first reconstruction is composed of only half of the slices, and there are still missing values. In our previous work, we adopted the traditional interpolation method, and there was still a gap in the visual effect of the reconstructed images. Therefore, we propose a noise-based super-resolution network (nESRGAN). The noise addition to the network can provide additional texture restoration possibilities. We use nESRGAN to further restore MRI resolution and high-frequency information. Finally, we achieve the 3D reconstruction of brain MRI images through two super-resolution reconstructions. Our proposed method is superior to 3D super-resolution technology based on deep learning in terms of perception range and image quality evaluation standards.

Role of testosterone: cortisol ratio in age- and sex-specific cortico-hippocampal development and cognitive performance

Testosterone (T) and cortisol (C) are steroid hormones that have been argued to play opposing roles in shaping physical and behavioral development in humans. While there is evidence linking T and C to different memory processes during adulthood, it remains unclear how the relative levels of T and C (TC ratio) may influence brain and behavioral development, whether they are influenced by sex of the child, and whether or not they occur as a result of stable changes in brain structure (organizational changes), as opposed to transient changes in brain function (activational changes). As such, we tested for associations among TC ratio, cortico-hippocampal structure, and standardized tests of executive, verbal, and visuo-spatial function in a longitudinal sample of typically developing 4-22-year-old children and adolescents. We found greater TC ratios to be associated with greater coordinated growth (i.e. covariance) between the hippocampus and cortical thickness in several areas primarily devoted to visual function. In addition, there was an age-related association between TC ratio and parieto-hippocampal covariance, as well as a sex-specific association between TC ratio and prefrontal-hippocampal covariance. Differences in brain structure related to TC ratio were in turn associated with lower verbal/executive function, as well as greater attention in tests of visuo-spatial abilities. These results support the notion that TC ratio may shift the balance between top-down (cortex to hippocampus) and bottom-up (hippocampus to cortex) processes, impairing more complex, cortical-based tasks and optimizing visuospatial tasks relying primarily on the hippocampus.

Auditory Beat Stimulation Modulates Memory-Related Single-Neuron Activity in the Human Medial Temporal Lobe

Auditory beats are amplitude-modulated signals (monaural beats) or signals that subjectively cause the perception of an amplitude modulation (binaural beats). We investigated the effects of monaural and binaural 5 Hz beat stimulation on neural activity and memory performance in neurosurgical patients performing an associative recognition task. Previously, we had reported that these beat stimulation conditions modulated memory performance in opposite directions. Here, we analyzed data from a patient subgroup, in which microwires were implanted in the amygdala, hippocampus, entorhinal cortex and parahippocampal cortex. We identified neurons responding with firing rate changes to binaural versus monaural 5 Hz beat stimulation. In these neurons, we correlated the differences in firing rates for binaural versus monaural beats to the memory-related differences for remembered versus forgotten items and associations. In the left hemisphere, we detected statistically significant negative correlations between firing rate differences for binaural versus monaural beats and remembered versus forgotten items/associations. Importantly, such negative correlations were also observed between beat stimulation-related firing rate differences in the pre-stimulus window and memory-related firing rate differences in the post-stimulus windows. In line with concepts of homeostatic plasticity, our findings suggest that beat stimulation is linked to memory performance via shifting baseline firing levels.

Hippocampal atrophy is associated with psychotic symptom severity following traumatic brain injury

Psychosis is a rare, but particularly serious sequela of traumatic brain injury. However, little is known as to the neurobiological processes that may contribute to its onset. Early evidence suggests that psychotic symptom development after traumatic brain injury may co-occur with hippocampal degeneration, invoking the possibility of a relationship. Particularly regarding the hippocampal head, these degenerative changes may lead to dysregulation in dopaminergic circuits, as is reported in psychoses due to schizophrenia, resulting in the positive symptom profile typically seen in post-injury psychosis. The objective of this study was to examine change in hippocampal volume and psychotic symptoms across time in a sample of moderate-to-severe traumatic brain injury patients. We hypothesized that hippocampal volume loss would be associated with increased psychotic symptom severity. From a database of n = 137 adult patients with prospectively collected, longitudinal imaging and neuropsychiatric outcomes, n = 24 had complete data at time points of interest (5 and 12 months post-traumatic brain injury) and showed increasing psychotic symptom severity on the Personality Assessment Inventory psychotic experiences subscale of the schizophrenia clinical scale across time. Secondary analysis employing stepwise regression with hippocampal volume change (independent variable) and Personality Assessment Inventory psychotic symptom change (dependent variable) from 5 to 12 months post-injury was conducted including age, sex, marijuana use, family history of schizophrenia, years of education and injury severity as control variables. Total right hippocampal volume loss predicted an increase in the Personality Assessment Inventory psychotic experiences subscale (F_{(1, 22)} = 5.396, adjusted R² = 0.161, P = 0.030; β = −0.017, 95% confidence interval = −0.018, −0.016) as did volume of the right hippocampal head (F_{(1, 22)} = 5.764, adjusted R² = 0.172, P = 0.025; β = −0.019, 95% confidence interval = −0.021, −0.017). Final model goodness-of-fit was confirmed using k-fold (k = 5) cross-validation. Consistent with our hypotheses, the current findings suggest that hippocampal degeneration in the chronic stages of moderate-to-severe traumatic brain injury may play a role in the delayed onset of psychotic symptoms after traumatic brain injury. These findings localized to the right hippocampal head are supportive of a proposed aetiological mechanism whereby atrophy of the hippocampal head may lead to the dysregulation of dopaminergic networks following traumatic brain injury; possibly accounting for observed clinical features of psychotic disorder after traumatic brain injury (including prolonged latency period to symptom onset and predominance of positive symptoms). If further validated, these findings may bear important clinical implications for neurorehabilitative therapies following traumatic brain injury.

An exploratory study into the influence of laterality and location of hippocampal sclerosis on seizure prognosis and global cortical thinning

In mesial temporal lobe epilepsy (mTLE), the correlation between disease duration, seizure laterality, and rostro-caudal location of hippocampal sclerosis has not been examined in the context of seizure severity and global cortical thinning. In this retrospective study, we analyzed structural 3 T MRI from 35 mTLE subjects. Regions of FLAIR hyperintensity (as an indicator of sclerosis)—based on 2D coronal FLAIR sequences—in the hippocampus were manually segmented, independently and in duplicate; degree of segmentation agreement was confirmed using the DICE index. Segmented lesions were used for separate analyses. First, the correlation of cortical thickness with disease duration and seizure focus laterality was explored using linear model regression. Then, the relationship between the rostro-caudal location of the FLAIR hyperintense signal and seizure severity, based on the Cleveland Clinic seizure freedom score (ccSFS), was explored using probabilistic voxel-wise mapping and functional connectivity analysis from normative data. The mean DICE Index was 0.71 (range 0.60–0.81). A significant correlation between duration of epilepsy and decreased mean whole brain cortical thickness was identified, regardless of seizure laterality (p < 0.05). The slope of cortical volume loss over time, however, was greater in subjects with right seizure focus. Based on probabilistic voxel-wise mapping, FLAIR hyperintensity in the posterior hippocampus was significantly associated with lower ccSFS scores (greater seizure severity). Finally, the right hippocampus was found to have greater brain-wide connectivity, compared to the left side, based on normative connectomic data. We have demonstrated a significant correlation between duration of epilepsy and right-sided seizure focus with global cortical thinning, potentially due to greater brain-wide connectivity. Sclerosis along the posterior hippocampus was associated with greater seizure severity, potentially serving as an important biomarker of seizure outcome after surgery.

Peri-ictal magnetic resonance imaging characteristics in dogs with suspected idiopathic epilepsy

Background

The pathophysiology of changes in magnetic resonance imaging (MRI) detected after a seizure is not fully understood.

Objective

To characterize and describe seizure‐induced changes detected by MRI.

Animals

Eighty‐one client‐owned dogs diagnosed with idiopathic epilepsy.

Methods

Data collected retrospectively from medical records and included anatomical areas affected, T1‐, T2‐weighted and T2‐FLAIR (fluid‐attenuated inversion recovery) appearance, whether changes were unilateral or bilateral, symmetry, contrast enhancement, mass effect, and, gray and white matter distribution. Diffusion‐ and perfusion weighted maps were evaluated, if available.

Results

Seizure‐induced changes were T2‐hyperintense with no suppression of signal on FLAIR. Lesions were T1‐isointense (55/81) or hypointense (26/81), local mass effect (23/81) and contrast enhancement (12/81). The majority of changes were bilateral (71/81) and symmetrical (69/71). The most common areas affected were the hippocampus (39/81) cingulate gyrus (33/81), hippocampus and piriform lobes (32/81). Distribution analysis suggested concurrence between cingulate gyrus and pulvinar thalamic nuclei, the cingulate gyrus and parahippocampal gyrus, hippocampus and piriform lobe, and, hippocampus and parahippocampal gyrus. Diffusion (DWI) characteristics were a mixed‐pattern of restricted, facilitated, and normal diffusion. Perfusion (PWI) showed either hypoperfusion (6/9) or hyperperfusion (3/9).

Conclusions and Clinical Importance

More areas, than previously reported, have been identified that could incur seizure‐induced changes. Similar to human literature, DWI and PWI changes have been identified that could reflect the underlying metabolic and vascular changes.

Alteration within the Hippocampal Volume in Patients with LHON Disease-7 Tesla MRI Study

Purpose: The aim of this study was to assess the volumetry of the hippocampus in the Leber’s hereditary optic neuropathy (LHON) of blind patients. Methods: A total of 25 patients with LHON were randomly included into the study from the national health database. A total of 15 patients were selected according to the inclusion criteria. The submillimeter segmentation of the hippocampus was based on three-dimensional spoiled gradient recalled acquisition in steady state (3D-SPGR) BRAVO 7T magnetic resonance imaging (MRI) protocol. Results: Statistical analysis revealed that compared to healthy controls (HC), LHON subjects had multiple significant differences only in the right hippocampus, including a significantly higher volume of hippocampal tail (p = 0.009), subiculum body (p = 0.018), CA1 body (p = 0.002), hippocampal fissure (p = 0.046), molecular layer hippocampus (HP) body (p = 0.014), CA3 body (p = 0.006), Granule Cell (GC) and Molecular Layer (ML) of the Dentate Gyrus (DG)–GC ML DG body (p = 0.003), CA4 body (p = 0.001), whole hippocampal body (p = 0.018), and the whole hippocampus volume (p = 0.023). Discussion: The ultra-high-field magnetic resonance imaging allowed hippocampus quality visualization and analysis, serving as a powerful in vivo diagnostic tool in the diagnostic process and LHON disease course assessment. The study confirmed previous reports regarding volumetry of hippocampus in blind individuals.

Cardiorespiratory fitness, hippocampal subfield volumes, and mnemonic discrimination task performance in aging

Aging and exercise have opposing effects on mnemonic discrimination task performance, which putatively taxes pattern separation mechanisms reliant on the dentate gyrus (DG) subfield of the hippocampus. In young adults, increasing cardiorespiratory fitness (CRF) has been shown to improve mnemonic discrimination task performance and increase left anterior DG/CA3 volume. It is unknown how these variables interact in cognitive aging, yet this knowledge is critical, given the established effects of aging on hippocampal plasticity. To investigate these relationships, 65 older adults (aged 55–85 years) completed a submaximal treadmill test to estimate CRF, a mnemonic discrimination task, and a high‐resolution MRI scan to determine hippocampal subfield volumes. Our older adult sample demonstrated the lowest task accuracy in the condition with the greatest stimuli similarity and left DG/CA3 body volume significantly predicted accuracy in this condition. Our results did not provide support for relationships between CRF and task accuracy or CRF and DG/CA3 volume as evidenced in studies of young adults. Instead, CRF predicted bilateral subiculum volume in older adult women, not men. Altogether, these findings provide further support for a role of the DG in behavioral pattern separation in humans and suggest that CRF may have differential effects on hippocampal subfield integrity in older adult men and women. ClinicalTrials.gov identifiers: (a) Neuroimaging Study of Exercise and Memory Function, NCT02057354; (b) The Entorhinal Cortex and Aerobic Exercise in Aging, NCT02775760; (c) Physical Activity and Cognition Study, NCT02773121.

Resection of piriform cortex predicts seizure freedom in temporal lobe epilepsy

Objective

Transsylvian selective amygdalo‐hippocampectomy (tsSAHE) represents a generally recognized surgical procedure for drug‐resistant mesial temporal lobe epilepsy (mTLE). Although postoperative seizure freedom can be achieved in about 70% of tsSAHE, there is a considerable amount of patients with persisting postoperative seizures. This might partly be explained by differing extents of resection of various tsSAHE target volumes. In this study we analyzed the resected proportions of hippocampus, amygdala as well as piriform cortex in regard of postoperative seizure outcome.

Methods

Between 2012 and 2017, 82 of 103 patients with mTLE who underwent tsSAHE at the authors’ institution were included in the analysis. Resected proportions of hippocampus, amygdala and temporal piriform cortex as target structures of tsSAHE were volumetrically assessed and stratified according to favorable (International League Against Epilepsy (ILAE) class 1) and unfavorable (ILAE class 2–6) seizure outcome.

Results

Patients with favorable seizure outcome revealed a significantly larger proportion of resected temporal piriform cortex volumes compared to patients with unfavorable seizure outcome (median resected proportional volumes were 51% (IQR 42–61) versus (vs.) 13 (IQR 11–18), P = 0.0001). Resected proportions of hippocampus and amygdala did not significantly differ for these groups (hippocampus: 81% (IQR 73–88) vs. 80% (IQR 74–92) (P = 0.7); amygdala: 100% (IQR 100–100) vs. 100% (IQR 100–100) (P = 0.7)).

Interpretation

These results strongly suggest temporal piriform cortex to constitute a key target resection volume to achieve seizure freedom following tsSAHE.