The striatum, the hippocampus, and short-term memory binding: Volumetric analysis of the subcortical grey matter's role in mild cognitive impairment

Exploring Research Trend and Hotspots on Oxidative Stress in Ischemic Stroke (2001-2022): Insights from Bibliometric

Oxidative stress is widely involved in the pathological process of ischemic stroke and ischemia-reperfusion. Several research have demonstrated that eliminating or reducing oxidative stress can alleviate the pathological changes of ischemic stroke. However, current clinical antioxidant treatment did not always perform as expected. This bibliometric research aims to identify research trends, topics, hotspots, and evolution on oxidative stress in the field of ischemic stroke, and to find potentially antioxidant strategies in future clinical treatment. Relevant publications were searched from the Web of Science (WOS) Core Collection databases (2001-2022). VOSviewer was used to visualize and analyze the development trends and hotspots. In the field of oxidative stress and ischemic stroke, the number of publications increased significantly from 2001 to 2022. China and the USA were the leading countries for publication output. The most prolific institutions were Stanford University. Journal of Cerebral Blood Flow and Metabolism and Stroke were the most cited journals. The research topics in this field include inflammation with oxidative stress, mitochondrial damage with oxidative stress, oxidative stress in reperfusion injury, oxidative stress in cognitive impairment and basic research and clinical translation of oxidative stress. Moreover, "NLRP3 inflammasome," "autophagy," "mitophagy," "miRNA," "ferroptosis," and "signaling pathway" are the emerging research hotspots in recent years. At present, multi-target regulation focusing on multi-mechanism crosstalk has progressed across this period, while challenges come from the transformation of basic research to clinical application. New detection technology and new nanomaterials are expected to integrate oxidative stress into the clinical treatment of ischemic stroke better.

Exploring the Association between Amyloid-β and Memory Markers for Alzheimer's Disease in Cognitively Unimpaired Older Adults

BACKGROUND

Memory tests vary in their sensitivity for detection of pre-symptomatic Alzheimer's disease (AD). The Visual Short-Term Memory Binding Test (VSTMBT) identifies AD-related performance deficits in older adults who are otherwise cognitively unimpaired.

OBJECTIVE

We investigated the association of this psychometric measure with brain amyloidosis and atrophy.

DESIGN

Cross-sectional mixed and correlational.

SETTING

Cognitive Reserve Study from Columbia University.

PARTICIPANTS

a sample of 39 cognitively unimpaired older adults (Age: M=65.3, SD=3.07) was obtained from the above study.

MEASUREMENTS

Extensive neuropsychological and neuroimaging (MRI and amyloid-β PET) assessments were carried out.

RESULTS

Performance on the VSTMBT allowed us to split the sample into Low Binding Cost (LBC, N=21) and High Binding Cost (HBC, N=18). Groups were matched according to age [p=0.702], years of education [0.071], and sex [p=0.291]. HBC's performance was comparable to that seen in symptomatic AD. Groups only differed in their amyloid-β deposition on PET in regions of the right ventral stream linked to visual cognition and affected early in AD pathogenesis (lateral-occipital cortex, p = 0.008; fusiform gyrus, p = 0.017; and entorhinal cortex, p = 0.046). Other regions known to be linked to low-level visual integration function also revealed increased amyloid-β deposition in HBC.

CONCLUSIONS

VSTMB deficits are associated with neuropathogenesis (i.e., amyloid-β deposition) in the earliest affected regions in pre-symptomatic AD. The VSTMB test holds potential for the identification of cognitively unimpaired older adults with very early AD pathogenesis and may thus be a useful tool for early intervention trials or other forms of clinical research.

Abnormalities of cerebral blood flow and the regional brain function in Parkinson's disease: a systematic review and multimodal neuroimaging meta-analysis

Background

Parkinson's disease (PD) is a neurodegenerative disease with high incidence rate. Resting state functional magnetic resonance imaging (rs-fMRI), as a widely used method for studying neurodegenerative diseases, has not yet been combined with two important indicators, amplitude low-frequency fluctuation (ALFF) and cerebral blood flow (CBF), for standardized analysis of PD.

Methods

In this study, we used seed-based d-mapping and permutation of subject images (SDM-PSI) software to investigate the changes in ALFF and CBF of PD patients. After obtaining the regions of PD with changes in ALFF or CBF, we conducted a multimodal analysis to identify brain regions where ALFF and CBF changed together or could not synchronize.

Results

The final study included 31 eligible trials with 37 data sets. The main analysis results showed that the ALFF of the left striatum and left anterior thalamic projection decreased in PD patients, while the CBF of the right superior frontal gyrus decreased. However, the results of multimodal analysis suggested that there were no statistically significant brain regions. In addition, the decrease of ALFF in the left striatum and the decrease of CBF in the right superior frontal gyrus was correlated with the decrease in clinical cognitive scores.

Conclusion

PD patients had a series of spontaneous brain activity abnormalities, mainly involving brain regions related to the striatum-thalamic-cortex circuit, and related to the clinical manifestations of PD. Among them, the left striatum and right superior frontal gyrus are more closely related to cognition.

Systematic review registration

https://www.crd.york.ac.uk/ PROSPERO (CRD42023390914).

White matter alterations in mild cognitive impairment revealed by meta-analysis of diffusion tensor imaging using tract-based spatial statistics

The neuropathological mechanism of mild cognitive impairment (MCI) remains unclarified. Diffusion tensor imaging (DTI) studies revealed white matter (WM) microarchitecture alterations in MCI, but consistent findings and conclusions have not yet been drawn. The present coordinate-based meta-analysis (CBMA) of tract-based spatial statistics (TBSS) studies aimed to identify the most prominent and robust WM abnormalities in patients with MCI. A systematic search of relevant studies was conducted through January 2022 to identify TBSS studies comparing fractional anisotropy (FA) between MCI patients and healthy controls (HC). We used the seed-based d mapping (SDM) software to achieve the CBMA and analyze regional FA alterations in MCI. Meta-regression analysis was subsequently applied to explore the potential associations between clinical variables and FA changes. MCI patients demonstrated significantly decreased FA in widely distributed areas in the corpus callosum (CC), including the genu, body, and splenium of the CC, as well as one cluster in the left striatum. FA in the body of the CC and in three clusters in the splenium of the CC was negatively associated with the mean age. Additionally, FA in the genu of the CC and in three clusters in the splenium of the CC had negative correlations with the MMSE scores. Disrupted integrities of the CC and left striatum might play vital roles in the process of cognitive decline. These findings enhanced our understanding of the neural mechanism underlying WM neurodegeneration in MCI and provided perspectives for the early detection and intervention of dementia.Registration number: CRD42022235716.

A mechanistic insight into sources of error of visual working memory in multiple sclerosis

Working memory (WM) is one of the most affected cognitive domains in multiple sclerosis (MS), which is mainly studied by the previously established binary model for information storage (slot model). However, recent observations based on the continuous reproduction paradigms have shown that assuming dynamic allocation of WM resources (resource model) instead of the binary hypothesis will give more accurate predictions in WM assessment. Moreover, continuous reproduction paradigms allow for assessing the distribution of error in recalling information, providing new insights into the organization of the WM system. Hence, by utilizing two continuous reproduction paradigms, memory-guided localization (MGL) and analog recall task with sequential presentation, we investigated WM dysfunction in MS. Our results demonstrated an overall increase in recall error and decreased recall precision in MS. While sequential paradigms were better in distinguishing healthy control from relapsing-remitting MS, MGL were more accurate in discriminating MS subtypes (relapsing-remitting from secondary progressive), providing evidence about the underlying mechanisms of WM deficit in progressive states of the disease. Furthermore, computational modeling of the results from the sequential paradigm determined that imprecision in decoding information and swap error (mistakenly reporting the feature of other presented items) was responsible for WM dysfunction in MS. Overall, this study offered a sensitive measure for assessing WM deficit and provided new insight into the organization of the WM system in MS population.

Targeting the function of the transentorhinal cortex to identify early cognitive markers of Alzheimer's disease

Initial neuropathology of early Alzheimer's disease accumulates in the transentorhinal cortex. We review empirical data suggesting that tasks assessing cognitive functions supported by the transenthorinal cortex are impaired as early as the preclinical stages of Alzheimer's disease. These tasks span across various domains, including episodic memory, semantic memory, language, and perception. We propose that all tasks sensitive to Alzheimer-related transentorhinal neuropathology commonly rely on representations of entities supporting the processing and discrimination of items having perceptually and conceptually overlapping features. In the future, we suggest a screening tool that is sensitive and specific to very early Alzheimer's disease to probe memory and perceptual discrimination of highly similar entities.

Age-related changes of deep-brain neurophysiological activity

Cognitive decline with age is associated with brain atrophy and reduced brain activations, but the underlying neurophysiological mechanisms are unclear, especially in deeper brain structures primarily affected by healthy aging or neurodegenerative processes. Here, we characterize time-resolved, resting-state magnetoencephalography activity of the hippocampus and subcortical brain regions in a large cohort of healthy young (20-30 years) and older (70-80 years) volunteers from the Cam-CAN (Cambridge Centre for Ageing and Neuroscience) open repository. The data show age-related changes in both rhythmic and arrhythmic signal strength in multiple deeper brain regions, including the hippocampus, striatum, and thalamus. We observe a slowing of neural activity across deeper brain regions, with increased delta and reduced gamma activity, which echoes previous reports of cortical slowing. We also report reduced occipito-parietal alpha peak associated with increased theta-band activity in the hippocampus, an effect that may reflect compensatory processes as theta activity, and slope of arrhythmic activity were more strongly expressed when short-term memory performances were preserved. Overall, this study advances the understanding of the biological nature of inter-individual variability in aging. The data provide new insight into how hippocampus and subcortical neurophysiological activity evolve with biological age, and highlight frequency-specific effects associated with cognitive decline versus cognitive maintenance.

Hippocampal and motor regions contribute to memory benefits after enacted encoding: cross-sectional and longitudinal evidence

The neurobiological underpinnings of action-related episodic memory and how enactment contributes to efficient memory encoding are not well understood. We examine whether individual differences in level (n = 338) and 5-year change (n = 248) in the ability to benefit from motor involvement during memory encoding are related to gray matter (GM) volume, white matter (WM) integrity, and dopamine-regulating genes in a population-based cohort (age range = 25-80 years). A latent profile analysis identified 2 groups with similar performance on verbal encoding but with marked differences in the ability to benefit from motor involvement during memory encoding. Impaired ability to benefit from enactment was paired with smaller HC, parahippocampal, and putamen volume along with lower WM microstructure in the fornix. Individuals with reduced ability to benefit from encoding enactment over 5 years were characterized by reduced HC and motor cortex GM volume along with reduced WM microstructure in several WM tracts. Moreover, the proportion of catechol-O-methyltransferase-Val-carriers differed significantly between classes identified from the latent-profile analysis. These results provide converging evidence that individuals with low or declining ability to benefit from motor involvement during memory encoding are characterized by low and reduced GM volume in regions critical for memory and motor functions along with altered WM microstructure.

Acupuncture on mild cognitive impairment: A systematic review of neuroimaging studies

Mild cognitive impairment (MCI) is a multifactorial and complex central neurodegenerative disease. Acupuncture appears to be an effective method for cognitive function improvement in MCI patients. Neural plasticity remaining in the MCI brain implies that acupuncture-associated benefits may not be limited to the cognitive function. Instead, neurological alternations in the brain play a vital role in corresponding to the cognitive improvement. However, previous studies have mainly focused on the effects of cognitive function, leaving neurological findings relatively unclear. This systematic review summarized existing studies that used various brain imaging techniques to explore the neurological effect regarding acupuncture use for MCI treatment. Potential neuroimaging trials were searched, collected, and identified independently by two researchers. Four Chinese databases, four English databases, and additional sources were searched to identify studies reporting the use of acupuncture for MCI from the inception of databases until 1 June 2022. Methodological quality was appraised using the Cochrane risk-of-bias tool. In addition, general, methodological, and brain neuroimaging information was extracted and summarized to investigate the potential neural mechanisms by which acupuncture affects patients with MCI. In total, 22 studies involving 647 participants were included. The methodological quality of the included studies was moderate to high. The methods used included functional magnetic resonance imaging, diffusion tensor imaging, functional near-infrared spectroscopy, and magnetic resonance spectroscopy. Acupuncture-induced brain alterations observed in those patients with MCI tended to be observable in the cingulate cortex, prefrontal cortex, and hippocampus. The effect of acupuncture on MCI may play a role in regulating the default mode network, central executive network, and salience network. Based on these studies, researchers could extend the recent research focus from the cognitive domain to the neurological level. Future researches should develop additional relevant, well-designed, high-quality, and multimodal neuroimaging researches to detect the effects of acupuncture on the brains of MCI patients.

A structural and resting-state functional connectivity investigation of the pulvinar in elderly individuals and Alzheimer's disease patients

In Alzheimer's disease (AD), structural and functional changes in the brain may give rise to disruption of specific cognitive functions. The aim of this study is to investigate the functional connectivity alterations in the pulvinar's subdivisions and total pulvinar voxel-based morphometry (VBM) changes in individuals with AD and healthy controls. A seed-based functional connectivity analysis was applied to the anterior, inferior, lateral, and medial pulvinar in each hemisphere. Furthermore, VBM analysis was carried out to compare gray matter (GM) volume differences in the pulvinar and thalamus between the two groups. Connectivity analysis revealed that the pulvinar subdivisions had decreased connectivity in individuals with AD. In addition, the pulvinar and thalamus in each hemisphere were significantly smaller in the AD group. The pulvinar may have a role in AD-related cognitive impairments and the intrinsic connectivity network changes and GM loss in pulvinar subdivisions suggest the cognitive deterioration occurring in those with AD. HIGHLIGHTS: The pulvinar may play a role in pathophysiology of cognitive impairments in those with Alzheimer's disease (AD). Decreased structural volume and functional connectivity were found in patients with AD. The inferior pulvinar is functionally the most affected subdivision by AD compared to the others.

Interaction within and between cortical networks subserving multisensory learning and its reorganization due to musical expertise

Recent advancements in the field of network science allow us to quantify inter-network information exchange and model the interaction within and between task-defined states of large-scale networks. Here, we modeled the inter- and intra- network interactions related to multisensory statistical learning. To this aim, we implemented a multifeatured statistical learning paradigm and measured evoked magnetoencephalographic responses to estimate task-defined state of functional connectivity based on cortical phase interaction. Each network state represented the whole-brain network processing modality-specific (auditory, visual and audiovisual) statistical learning irregularities embedded within a multisensory stimulation stream. The way by which domain-specific expertise re-organizes the interaction between the networks was investigated by a comparison of musicians and non-musicians. Between the modality-specific network states, the estimated connectivity quantified the characteristics of a supramodal mechanism supporting the identification of statistical irregularities that are compartmentalized and applied in the identification of uni-modal irregularities embedded within multisensory stimuli. Expertise-related re-organization was expressed by an increase of intra- and a decrease of inter-network connectivity, showing increased compartmentalization.

Mapping cerebral atrophic trajectory from amnestic mild cognitive impairment to Alzheimer's disease

Alzheimer's disease (AD) patients suffer progressive cerebral atrophy before dementia onset. However, the region-specific atrophic processes and the influences of age and apolipoprotein E (APOE) on atrophic trajectory are still unclear. By mapping the region-specific nonlinear atrophic trajectory of whole cerebrum from amnestic mild cognitive impairment (aMCI) to AD based on longitudinal structural magnetic resonance imaging data from Alzheimer's disease Neuroimaging Initiative (ADNI) database, we unraveled a quadratic accelerated atrophic trajectory of 68 cerebral regions from aMCI to AD, especially in the superior temporal pole, caudate, and hippocampus. Besides, interaction analyses demonstrated that APOE ε4 carriers had faster atrophic rates than noncarriers in 8 regions, including the caudate, hippocampus, insula, etc.; younger patients progressed faster than older patients in 32 regions, especially for the superior temporal pole, hippocampus, and superior temporal gyrus; and 15 regions demonstrated complex interaction among age, APOE, and disease progression, including the caudate, hippocampus, etc. (P < 0.05/68, Bonferroni correction). Finally, Cox proportional hazards regression model based on the identified region-specific biomarkers could effectively predict the time to AD conversion within 10 years. In summary, cerebral atrophic trajectory mapping could help a comprehensive understanding of AD development and offer potential biomarkers for predicting AD conversion.

Silver Nanoparticles Impair Cognitive Functions and Modify the Hippocampal Level of Neurotransmitters in a Coating-Dependent Manner

Due to their potent antibacterial properties, silver nanoparticles (AgNPs) are widely used in industry and medicine. However, they can cross the brain-blood barrier, posing a risk to the brain and its functions. In our previous study, we demonstrated that oral administration of bovine serum albumin (BSA)-coated AgNPs caused an impairment in spatial memory in a dose-independent manner. In this study, we evaluated the effects of AgNPs coating material on cognition, spatial memory functioning, and neurotransmitter levels in rat hippocampus. AgNPs coated with BSA (AgNPs(BSA)), polyethylene glycol (AgNPs(PEG)), or citrate (AgNPs(Cit)) or silver ions (Ag+) were orally administered at a dose of 0.5 mg/kg b.w. to male Wistar rats for a period of 28 days, while the control (Ctrl) rats received 0.2 mL of water. The acquisition and maintenance of spatial memory related to place avoidance were assessed using the active allothetic place avoidance task, in which rats from AgNPs(BSA), AgNPs(PEG), and Ag+ groups performed worse than the Ctrl rats. In the retrieval test assessing long-term memory, only rats from AgNPs(Cit) and Ctrl groups showed memory maintenance. The analysis of neurotransmitter levels indicated that the ratio between serotonin and dopamine concentration was disturbed in the AgNPs(BSA) rats. Furthermore, treatment with AgNPs or Ag+ resulted in the induction of peripheral inflammation, which was reflected by the alterations in the levels of serum inflammatory mediators. In conclusion, depending on the coating material used for their stabilization, AgNPs induced changes in memory functioning and concentration of neurotransmitters.

White matter microstructure alterations in systemic lupus erythematosus: A preliminary coordinate-based meta-analysis of diffusion tensor imaging studies

BACKGROUND

Systemic lupus erythematosus is often accompanied with neuropsychiatric symptoms. Neuroimaging evidence indicated that microstructural white matter (WM) abnormalities play role in the neuropathological mechanism. Diffusion tensor imaging (DTI) studies allows the assessment of the microstructural integrity of WM tracts, but existing findings were inconsistent. This present study aimed to conduct a coordinate-based meta-analysis (CBMA) to identify statistical consensus of DTI studies in SLE.

METHODS

Relevant studies that reported the differences of fractional anisotropy (FA) between SLE patients and healthy controls (HC) were searched systematically. Only studies reported the results in Talairach or Montreal Neurological Institute (MNI) coordinates were included. The anisotropic effect size version of signed differential mapping (AES-SDM) was applied to detect WM alterations in SLE.

RESULTS

Totally, five studies with seven datasets which included 126 patients and 161 HC were identified. The pooled meta-analysis demonstrated that SLE patients exhibited significant FA reduction in the left striatum and bilateral inferior network, mainly comprised the corpus callosum (CC), bilateral inferior fronto-occipital fasciculus (IFOF), bilateral anterior thalamic projections, bilateral superior longitudinal fasciculus (SLF), left inferior longitudinal fasciculus (ILF), and left insula. No region with higher FA was identified.

CONCLUSIONS

Disorders of the immune system might lead to subtle WM microstructural alterations in SLE, which might be related with cognitive deficits or emotional distress symptoms. This provides a better understanding of the pathological mechanism of microstructural brain abnormalities in SLE.

The role of glucocorticoid receptor gene in the association between attention deficit-hyperactivity disorder and smaller brain structures

ADHD is associated with smaller subcortical brain volumes and cortical surface area, with greater effects observed in children than adults. It is also associated with dysregulation of the HPA axis. Considering the effects of the glucocorticoid receptor (NR3C1) in neurophysiology, we hypothesize that the blurred relationships between brain structures and ADHD in adults could be partly explained by NR3C1 gene variation. Structural T1-weighted images were acquired on a 3 T scanner (N = 166). Large-scale genotyping was performed, and it was followed by quality control and pruning procedures, which resulted in 48 independent NR3C1 gene variants analyzed. After a stringent Bonferroni correction, two SNPs (rs2398631 and rs72801070) moderated the association between ADHD and accumbens and amygdala volumes in adults. The significant SNPs that interacted with ADHD appear to have a role in gene expression regulation, and they are in linkage disequilibrium with NR3C1 variants that present well-characterized physiological functions. The literature-reported associations of ADHD with accumbens and amygdala were only observed for specific NR3C1 genotypes. Our findings reinforce the influence of the NR3C1 gene on subcortical volumes and ADHD. They suggest a genetic modulation of the effects of a pivotal HPA axis component in the neuroanatomical features of ADHD.

Fractionating the episodic buffer

The episodic buffer is a putative component of working memory proposed to account for several short-term memory functions, including unexpectedly preserved immediate prose recall by amnesic patients. Over the course of time, this component has increasingly become associated with binding functions. Considering recent findings regarding the performance of both memory-impaired and healthy individuals on the range of tasks purported to require the contribution of the episodic buffer, we suggest that it should be fractionated into two functional systems. One is a schematic store instantiated in brain areas responsible for conceptual and schema representations, which is likely to be hippocampus-independent, and preserved in the face of amnesia. In contrast, short-term maintenance of novel associative binding is likely to require the contribution of the hippocampus and may therefore not be functionally dissociable from long-term memory.

Grey Matter Loss at Different Stages of Cognitive Decline: A Role for the Thalamus in Developing Alzheimer's Disease

Background:

Alzheimer’s disease (AD) is characterized by cognitive impairment and large loss of grey matter volume and is the most prevalent form of dementia worldwide. Mild cognitive impairment (MCI) is the stage that precedes the AD dementia stage, but individuals with MCI do not always convert to the AD dementia stage, and it remains unclear why.

Objective:

We aimed to assess grey matter loss across the brain at different stages of the clinical continuum of AD to gain a better understanding of disease progression.

Methods:

In this large-cohort study (N = 1,386) using neuroimaging data from the Alzheimer’s Disease Neuroimaging Initiative, voxel-based morphometry analyses were performed between healthy controls, individuals with early and late and AD dementia stage.

Results:

Clear patterns of grey matter loss in mostly hippocampal and temporal regions were found across clinical stages, though not yet in early MCI. In contrast, thalamic volume loss seems one of the first signs of cognitive decline already during early MCI, whereas this volume loss does not further progress from late MCI to AD dementia stage. AD dementia stage converters already show grey matter loss in hippocampal and mid-temporal areas as well as the posterior thalamus (pulvinar) and angular gyrus at baseline.

Conclusion:

This study confirms the role of temporal brain regions in AD development and suggests additional involvement of the thalamus/pulvinar and angular gyrus that may be linked to visuospatial, attentional, and memory related problems in both early MCI and AD dementia stage conversion.

Deficits in short-term memory binding are detectable in individuals with brain amyloid deposition in the absence of overt neurodegeneration in the Alzheimer's disease continuum

The short-term memory binding (STMB) test involves the ability to hold in memory the integration between surface features, such as shapes and colours. The STMB test has been used to detect Alzheimer's disease (AD) at different stages, from preclinical to dementia, showing promising results. The objective of the present study was to verify whether the STMB test could differentiate patients with distinct biomarker profiles in the AD continuum. The sample comprised 18 cognitively unimpaired (CU) participants, 30 mild cognitive impairment (MCI) and 23 AD patients. All participants underwent positron emission tomography (PET) with Pittsburgh compound-B labelled with carbon-11 ([¹¹C]PIB) assessing amyloid beta (Aβ) aggregation (A) and 18fluorine-fluorodeoxyglucose ([¹⁸F]FDG)-PET assessing neurodegeneration (N) (A-N- [n = 35]); A+N- [n = 11]; A+ N+ [n = 19]). Participants who were negative and positive for amyloid deposition were compared in the absence (A-N- vs. A+N-) of neurodegeneration. When compared with the RAVLT and SKT memory tests, the STMB was the only cognitive task that differentiated these groups, predicting the group outcome in logistic regression analyses. The STMB test showed to be sensitive to the signs of AD pathology and may represent a cognitive marker within the AD continuum.

Memory precision of object-location binding is unimpaired in APOE ε4-carriers with spatial navigation deficits

Research suggests that tests of memory fidelity, feature binding and spatial navigation are promising for early detection of subtle behavioural changes related to Alzheimer's disease. In the absence of longitudinal data, one way of testing the early detection potential of cognitive tasks is through the comparison of individuals at different genetic risk for Alzheimer's dementia. Most studies have done so using samples aged 70 years or older. Here, we tested whether memory fidelity of long-term object-location binding may be a sensitive marker even among cognitively healthy individuals in their mid-60s by comparing participants at low and higher risk based on presence of the ε4-allele of the apolipoprotein gene (n = 26 ε3ε3, n = 20 ε3ε4 carriers). We used a continuous report paradigm in a visual memory task that required participants to recreate the spatial position of objects in a scene. We employed mixture modelling to estimate the two distinct memory processes that underpin the trial-by-trial variation in localization errors: retrieval success which indexes the proportion of trials where participants recalled any information about an object's position and the precision with which participants retrieved this information. Prior work has shown that these memory paradigms that separate retrieval success from precision are capable of detecting subtle differences in mnemonic fidelity even when retrieval success could not. Nonetheless, Bayesian analyses found good evidence that ε3ε4 carriers did not remember fewer object locations [F(1, 42) = 0.450, P = 0.506, BF01 = 3.02], nor was their precision for the spatial position of objects reduced compared to ε3ε3 carriers [F(1, 42) = 0.12, P = 0.726, BF01 = 3.19]. Because the participants in the sample presented here were a subset of a study on apolipoprotein ε4-carrier status and spatial navigation in the Sea Hero Quest game [Coughlan et al., 2019. PNAS, 116(9)], we obtained these data to contrast genetic effects on the two tasks within the same sample (n = 33). Despite the smaller sample size, wayfinding deficits among ε3ε4 carriers could be replicated [F(1, 33) = 5.60, P = 0.024, BF10 = 3.44]. Object-location memory metrics and spatial navigation scores were not correlated (all r < 0.25, P > 0.1, 0 < BF10 < 3). These findings show spared object-location binding in the presence of a detrimental apolipoprotein ε4 effect on spatial navigation. This suggests that the sensitivity of memory fidelity and binding tasks may not extend to individuals with one ε4-allele in their early to mid-60s. The results provide further support to prior proposals that spatial navigation may be a sensitive marker for the earliest cognitive changes in Alzheimer's disease, even before episodic memory.

Investigation of the relationship between visual feature binding in short- and long-term memory in healthy aging

Binding visual features into coherent object representations is essential both in short- and long-term memory. However, the relationship between feature binding processes at different memory delays remains unexplored. Here, we addressed this question by using the Mnemonic Similarity Task and a delayed-estimation working memory task on a large sample of older adults. The results revealed that higher propensity to misbind object features in working memory is associated with lower lure discrimination performance in the mnemonic similarity task, suggesting that shared feature binding processes underlie the formation of coherent short- and long-term visual object memory representations.

Dose-dependent volume loss in subcortical deep grey matter structures after cranial radiotherapy

•

Subcortical grey matter is susceptible to dose-dependent volume loss after RT.

•

Hippocampal age increases 1 year after radiotherapy, by a median of 11 years.

•

We may need to reconsider current sparing strategies in RT for brain tumours.

•

Future studies should examine the impact of deep GM volume loss on cognition.

Background and purpose

The relation between radiotherapy (RT) dose to the brain and morphological changes in healthy tissue has seen recent increased interest. There already is evidence for changes in the cerebral cortex and white matter, as well as selected subcortical grey matter (GM) structures. We studied this relation in all deep GM structures, to help understand the aetiology of post-RT neurocognitive symptoms.

Materials and methods

We selected 31 patients treated with RT for grade II-IV glioma. Pre-RT and 1 year post-RT 3D T1-weighted MRIs were automatically segmented, and the changes in volume of the following structures were assessed: amygdala, nucleus accumbens, caudate nucleus, hippocampus, globus pallidus, putamen, and thalamus. The volumetric changes were related to the mean RT dose received by each structure. Hippocampal volumes were entered into a population-based nomogram to estimate hippocampal age.

Results

A significant relation between RT dose and volume loss was seen in all examined structures, except the caudate nucleus. The volume loss rates ranged from 0.16 to 1.37%/Gy, corresponding to 4.9–41.2% per 30 Gy. Hippocampal age, as derived from the nomogram, was seen to increase by a median of 11 years.

Conclusion

Almost all subcortical GM structures are susceptible to radiation-induced volume loss, with higher volume loss being observed with increasing dose. Volume loss of these structures is associated with neurological deterioration, including cognitive decline, in neurodegenerative diseases. To support a causal relationship between radiation-induced deep GM loss and neurocognitive functioning in glioma patients, future studies are needed that directly correlate volumetrics to clinical outcomes.

Changes in neuronal excitability and synaptic transmission in nucleus accumbens in a transgenic Alzheimer's disease mouse model

Several previous studies showed that hippocampus and cortex are affected in Alzheimer's disease (AD). However, other brain regions have also been found to be affected and could contribute with new critical information to the pathophysiological basis of AD. For example, volumetric studies in humans have shown a significant atrophy of the striatum, particularly in the nucleus Accumbens (nAc). The nAc is a key component of the limbic reward system and it is involved in cognition and emotional behaviors such as pleasure, fear, aggression and motivations, all of which are affected in neurodegenerative diseases such as AD. However, its role in AD has not been extensively studied. Therefore, using an AD mouse model, we investigated if the nAc was affected in 6 months old transgenic 2xTg (APP/PS1) mice. Immunohistochemistry (IHC) analysis in 2xTg mice showed increased intraneuronal Aβ accumulation, as well as occasional extracellular amyloid deposits detected through Thioflavin-S staining. Interestingly, the intracellular Aβ pathology was associated to an increase in membrane excitability in dissociated medium spiny neurons (MSNs) of the nAc. IHC and western blot analyses showed a decrease in glycine receptors (GlyR) together with a reduction in the pre- and post-synaptic markers SV2 and gephyrin, respectively, which correlated with a decrease in glycinergic miniature synaptic currents in nAc brain slices. Additionally, voltage-clamp recordings in dissociated MSNs showed a decrease in AMPA- and Gly-evoked currents. Overall, these results showed intracellular Aβ accumulation together with an increase in excitability and synaptic alterations in this mouse model. These findings provide new information that might help to explain changes in motivation, anhedonia, and learning in the onset of AD pathogenesis.

Voxelwise Meta-Analysis of Gray Matter Abnormalities in Mild Cognitive Impairment and Subjective Cognitive Decline Using Activation Likelihood Estimation

Background: Voxel-based morphometry studies have not yielded consistent results among patients with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Objective: Therefore, we aimed to conduct a meta-analysis of gray matter (GM) abnormalities acquired from these studies to determine their respective neuroanatomical changes. Methods: We systematically searched for voxel-based whole-brain morphometry studies that compared MCI or SCD subjects with healthy controls in PubMed, Web of Science, and EMBASE databases. We used the coordinate-based method of activation likelihood estimation to determine GM changes in SCD, MCI, and MCI sub-groups (amnestic MCI and non-amnestic MCI). Results: A total of 45 studies were included in our meta-analysis. In the MCI group, we found structural atrophy of the bilateral hippocampus, parahippocampal gyrus (PHG), amygdala, right lateral globus pallidus, right insula, and left middle temporal gyrus. The aMCI group exhibited GM atrophy in the bilateral hippocampus, PHG, and amygdala. The naMCI group presented with structural atrophy in the right putamen, right insula, right precentral gyrus, left medial/superior frontal gyrus, and left anterior cingulate. The right lingual gyrus, right cuneus, and left medial frontal gyrus were atrophic GM regions in the SCD group. Conclusion: Our meta-analysis identified unique patterns of neuroanatomical alternations in both the MCI and SCD group. Structural changes in SCD patients provide new evidence for the notion that subtle impairment of visual function, perception, and cognition may be related to early signs of cognitive impairment. In addition, our findings provide a foundation for future targeted interventions at different stages of preclinical Alzheimer’s disease.

Early Detection of Alzheimer's Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning

Early detection is critical for effective management of Alzheimer's disease (AD) and screening for mild cognitive impairment (MCI) is common practice. Among several deep-learning techniques that have been applied to assessing structural brain changes on magnetic resonance imaging (MRI), convolutional neural network (CNN) has gained popularity due to its superb efficiency in automated feature learning with the use of a variety of multilayer perceptrons. Meanwhile, ensemble learning (EL) has shown to be beneficial in the robustness of learning-system performance via integrating multiple models. Here, we proposed a classifier ensemble developed by combining CNN and EL, i.e., the CNN-EL approach, to identify subjects with MCI or AD using MRI: i.e., classification between (1) AD and healthy cognition (HC), (2) MCIc (MCI patients who will convert to AD) and HC, and (3) MCIc and MCInc (MCI patients who will not convert to AD). For each binary classification task, a large number of CNN models were trained applying a set of sagittal, coronal, or transverse MRI slices; these CNN models were then integrated into a single ensemble. Performance of the ensemble was evaluated using stratified fivefold cross-validation method for 10 times. The number of the intersection points determined by the most discriminable slices separating two classes in a binary classification task among the sagittal, coronal, and transverse slice sets, transformed into the standard Montreal Neurological Institute (MNI) space, acted as an indicator to assess the ability of a brain region in which the points were located to classify AD. Thus, the brain regions with most intersection points were considered as those mostly contributing to the early diagnosis of AD. The result revealed an accuracy rate of 0.84 ± 0.05, 0.79 ± 0.04, and 0.62 ± 0.06, respectively, for classifying AD vs. HC, MCIc vs. HC, and MCIc vs. MCInc, comparable to previous reports and a 3D deep learning approach (3D-SENet) based on a more state-of-the-art and popular Squeeze-and-Excitation Networks model using channel attention mechanism. Notably, the intersection points accurately located the medial temporal lobe and several other structures of the limbic system, i.e., brain regions known to be struck early in AD. More interestingly, the classifiers disclosed multiple patterned MRI changes in the brain in AD and MCIc, involving these key regions. These results suggest that as a data-driven method, the combined CNN and EL approach can locate the most discriminable brain regions indicated by the trained ensemble model while the generalization ability of the ensemble model was maximized to successfully capture AD-related brain variations early in the disease process; it can also provide new insights into understanding the complex heterogeneity of whole-brain MRI changes in AD. Further research is needed to examine the clinical implication of the finding, capability of the advocated CNN-EL approach to help understand and evaluate an individual subject's disease status, symptom burden and progress, and the generalizability of the advocated CNN-EL approach to locate the most discriminable brain regions in the detection of other brain disorders such as schizophrenia, autism, and severe depression, in a data-driven way.