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Positron emission tomography (PET) utilizes radiotracers like [18F]fluorodeoxyglucose (FDG) to measure brain activity in health and disease. Performing behavioral tasks between the FDG injection and the PET scan allows the FDG signal to reflect task-related brain networks. Building on this principle, we introduce an approach called behavioral task–associated PET (beta-PET) consisting of two scans: the first after a mouse is familiarized with a conditioning chamber, and the second upon recall of contextual threat. Associative threat conditioning occurs between scans. Beta-PET focuses on brain regions encoding threat memory (e.g., amygdala, prefrontal cortex) and contextual aspects (e.g., hippocampus, subiculum, entorhinal cortex). Our results show that beta-PET identifies a biologically defined network encoding contextual threat memory and its uncoupling in a mouse model of long sepsis. Moreover, machine learning algorithms (linear logistic regression) and ordinal trends analysis demonstrate that beta-PET robustly predicts the behavioral defense response and its breakdown during long sepsis. [ABSTRACT FROM AUTHOR]

During non-rapid eye movement (NREM) sleep, neural ensembles in the entorhinal-hippocampal circuit responsible for encoding recent memories undergo reactivation to facilitate the process of memory consolidation. This reactivation is widely acknowledged as pivotal for the formation of stable memory and its impairment is closely associated with memory dysfunction. To date, the neural mechanisms driving the reactivation of neural ensembles during NREM sleep remain poorly understood. Here, we show that the neural ensembles in the medial entorhinal cortex (MEC) that encode spatial experiences exhibit reactivation during NREM sleep. Notably, this reactivation consistently coincides with isolated theta waves. In addition, we found that the nucleus reuniens (RE) in the midline thalamus exhibits typical theta waves during NREM sleep, which are highly synchronized with those occurring in the MEC in male mice. Closed-loop optogenetic inhibition of the RE-MEC pathway specifically suppressed these isolated theta waves, resulting in impaired reactivation and compromised memory consolidation following a spatial memory task in male mice. The findings suggest that theta waves originating from the ventral midline thalamus play a role in initiating memory reactivation and consolidation during sleep. The neural mechanisms of memory consolidation during sleep are poorly understood. Here the authors show that isolated theta waves from nucleus reuniens initiate neural ensemble reactivation during sleep required for spatial memory consolidation. [ABSTRACT FROM AUTHOR]

In Alzheimer's disease (AD), reports on the association between false recognition and brain structure have been inconsistent. In dementia with Lewy bodies (DLB), no such association has been reported. This study aimed to identify brain regions associated with false recognition in AD and DLB by analyzing regional gray matter volume (rGMV). We included 184 patients with AD and 60 patients with DLB. The number of false recognitions was assessed using the Alzheimer's Disease Assessment Scale' word recognition task. Brain regions associated with the number of false recognitions were examined by voxel-based morphometry analysis. The number of false recognitions significantly negatively correlated with rGMV in the bilateral hippocampus, left parahippocampal gyrus, bilateral amygdala, and bilateral entorhinal cortex in patients with AD (p < 0.05, family-wise error [FEW] corrected) and in the bilateral hippocampus, left parahippocampal gyrus, right inferior frontal gyrus, right middle frontal gyrus, right basal forebrain, right insula, left medial and lateral orbital gyri, and left fusiform in those with DLB (p < 0.05, FWE corrected). Bilateral hippocampus and left parahippocampal gyrus were associated with false recognition in both diseases. However, we found there were regions where the association between false recognition and rGMV differed from disease to disease. [ABSTRACT FROM AUTHOR]

Complex sensory information arrives in the brain from an animal's first-person ('egocentric') perspective. However, animals can efficiently navigate as if referencing map-like ('allocentric') representations. The postrhinal (POR) and retrosplenial (RSC) cortices are thought to mediate between sensory input and internal maps, combining egocentric representations of physical cues with allocentric head direction (HD) information. Here we show that neurons in the POR and RSC of female Long-Evans rats are tuned to distinct but complementary aspects of local space. Egocentric bearing (EB) cells recorded in square and L-shaped environments reveal that RSC cells encode local geometric features, while POR cells encode a more global account of boundary geometry. Additionally, POR HD cells can incorporate egocentric information to fire in two opposite directions with two oppositely placed identical visual landmarks, while only a subset of RSC HD cells possess this property. Entorhinal grid and HD cells exhibit consistently allocentric spatial firing properties. These results reveal significant regional differences in the neural encoding of spatial reference frames. Whether and how the postrhinal (POR) and retrosplenial (RSC) cortices interact with each other and impact downstream allocentric representations are not fully understood. Here authors present single neuron recordings from freely moving rats exploring different environments to reveal distinct egocentric (self-centered) and allocentric (world-centered) coding frameworks for landmarks and boundaries in interconnected cortical regions. [ABSTRACT FROM AUTHOR]

Preventative treatment for Alzheimer's Disease (AD) is dire, yet mechanisms underlying early regional vulnerability remain unknown. In AD, one of the earliest pathophysiological correlates to cognitive decline is hyperexcitability, which is observed first in the entorhinal cortex. Why hyperexcitability preferentially emerges in specific regions in AD is unclear. Using regional, cell-type-specific proteomics and electrophysiology in wild-type mice, we uncovered a unique susceptibility of the entorhinal cortex to human amyloid precursor protein (hAPP). Entorhinal hyperexcitability resulted from selective vulnerability of parvalbumin (PV) interneurons, with respect to surrounding excitatory neurons. This effect was partially replicated with an APP chimera containing a humanized amyloid-beta sequence. EC hyperexcitability could be ameliorated by co-expression of human Tau with hAPP at the expense of increased pathological tau species, or by enhancing PV interneuron excitability in vivo. This study suggests early interventions targeting inhibitory neurons may protect vulnerable regions from the effects of APP/amyloid and tau pathology. In this study using an adult-onset mouse model of Alzheimer's pathology, we uncovered a neuron-type-specific mechanism responsible for region-specific circuit dysfunction. Short-term expression of human amyloid precursor protein (hAPP) led to hyperexcitability in the entorhinal cortex, but not in isocortex, due to a distinct vulnerability of PV interneurons in the entorhinal region. [ABSTRACT FROM AUTHOR]

Our brains create new memories by capturing the 'who/what', 'where' and 'when' of everyday experiences. On a neuronal level, mechanisms facilitating a successful transfer into episodic memory are still unclear. We investigated this by measuring single neuron activity in the human medial temporal lobe during encoding of item-location associations. While previous research has found predictive effects in population activity in human MTL structures, we could attribute such effects to two specialized sub-groups of neurons: concept cells in the hippocampus, amygdala and entorhinal cortex (EC), and a second group of parahippocampal location-selective neurons. In both item- and location-selective populations, firing rates were significantly higher during successfully encoded trials. These findings are in line with theories of hippocampal indexing, since selective index neurons may act as pointers to neocortical representations. Overall, activation of distinct populations of neurons could directly support the connection of the 'what' and 'where' of episodic memory. Whether specialized neuronal firing in the human MTL predicts successful memory encoding remains unknown. Here, the authors find this to be the case for two distinct populations of single neurons responding to items and locations, respectively. [ABSTRACT FROM AUTHOR]

The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms using deep learning to measure phosphorylated tau (p-tau) and TDP-43 (pTDP-43) pathology, which are both known to accumulate in the MTL and are associated with MTL neurodegeneration. We focus on these pathologies in the context of Alzheimer's disease (AD) and limbic predominant age-related TDP-43 encephalopathy (LATE) and apply our deep learning algorithms to distinct histology sections, on which MTL subregions were digitally annotated. We demonstrate that both quantitative pathology measures show high agreement with expert visual ratings of pathology and discriminate well between pathology stages. In 140 cases with antemortem MR imaging, we compare the association of semi-quantitative and quantitative postmortem measures of these pathologies in the hippocampus with in vivo structural measures of the MTL and its subregions. We find widespread associations of p-tau pathology with MTL subregional structural measures, whereas pTDP-43 pathology had more limited associations with the hippocampus and entorhinal cortex. Quantitative measurements of p-tau pathology resulted in a significantly better model of antemortem structural measures than semi-quantitative ratings and showed strong associations with cortical thickness and volume. By providing a more granular measure of pathology, the quantitative p-tau measures also showed a significant negative association with structure in a severe AD subgroup where semi-quantitative ratings displayed a ceiling effect. Our findings demonstrate the advantages of using quantitative neuropathology to understand the relationship of pathology to structure, particularly for p-tau, and motivate the use of quantitative pathology measurements in future studies. [ABSTRACT FROM AUTHOR]

Background: Anti-N-methyl-d-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis. Methods: Structural networks from 61 NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and 61 age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically constrained tractography and volumetry of a selection of subcortical and white matter brain volumes was performed. We calculated global, modular, and nodal graph measures with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were investigated regarding their potential association with clinical course, disease severity, and cognitive outcome. Results: Patients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p = 0.049; right: p = 0.013) and increased node strength of right precuneus (p = 0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p = 0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p = 0.021). We found decreased left (p = 0.013) and right (p = 0.001) hippocampal volumes that were associated with hippocampal node strength (left p = 0.009; right p < 0.001). Conclusions: Focal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis. [ABSTRACT FROM AUTHOR]

In layer II of the entorhinal cortex, the principal neurons that project to the dentate gyrus and the CA3/2 hippocampal fields markedly express the large glycoprotein reelin (Re + ECLII neurons). In rodents, neurons located at the dorsal extreme of the EC, which border the rhinal fissure, express the highest levels, and the expression gradually decreases at levels successively further away from the rhinal fissure. Here, we test two predictions deducible from the hypothesis that reelin expression is strongly correlated with neuronal metabolic rate. Since the mitochondrial turnover rate serves as a proxy for energy expenditure, the mitophagy rate arguably also qualifies as such. Because messenger RNA of the canonical promitophagic BCL2 and adenovirus E1B 19-kDa-interacting protein 3 (Bnip3) is known to be highly expressed in the EC, we predicted that Bnip3 would be upregulated in Re + ECLII neurons, and that the degree of upregulation would strongly correlate with the expression level of reelin in these neurons. We confirm both predictions, supporting that the energy requirement of Re + ECLII neurons is generally high and that there is a systematic increase in metabolic rate as one moves successively closer to the rhinal fissure. Intriguingly, the systematic variation in energy requirement of the neurons that manifest the observed reelin gradient appears to be consonant with the level of spatial and temporal detail by which they encode information about the external environment. [ABSTRACT FROM AUTHOR]

The primate including the human hippocampus implicated in episodic memory and navigation represents a spatial view, very different from the place representations in rodents. To understand this system in humans, and the computations performed, the pathway for this spatial view information to reach the hippocampus was analysed in humans. Whole-brain effective connectivity was measured with magnetoencephalography between 30 visual cortical regions and 150 other cortical regions using the HCP-MMP1 atlas in 21 participants while performing a 0-back scene memory task. In a ventromedial visual stream, V1–V4 connect to the ProStriate region where the retrosplenial scene area is located. The ProStriate region has connectivity to ventromedial visual regions VMV1–3 and VVC. These ventromedial regions connect to the medial parahippocampal region PHA1–3, which, with the VMV regions, include the parahippocampal scene area. The medial parahippocampal regions have effective connectivity to the entorhinal cortex, perirhinal cortex, and hippocampus. In contrast, when viewing faces, the effective connectivity was more through a ventrolateral visual cortical stream via the fusiform face cortex to the inferior temporal visual cortex regions TE2p and TE2a. A ventromedial visual cortical 'Where' stream to the hippocampus for spatial scenes was supported by diffusion topography in 171 HCP participants at 7 T. A ventromedial cortical 'Where' visual pathway in humans for spatial scenes is revealed with MEG. It is fundamental to episodic memory and navigation. [ABSTRACT FROM AUTHOR]

The consolidation of discrete experiences into a coherent narrative shapes the cognitive map, providing structured mental representations of our experiences. In this process, past memories are reactivated and replayed in sequence, fostering hippocampal-cortical dialogue. However, brain-wide engagement coinciding with sequential reactivation (or replay) of memories remains largely unexplored. In this study, employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of memory replay. We find that during mental simulation, past memories are replayed in fast sequences as detected via EEG. These transient replay events are associated with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Replay occurrence strengthens functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing the cognitive map. On the other hand, when subjects are at rest following learning, memory reactivation of task-related items is stronger than that of pre-learning rest, and is also associated with heightened hippocampal activation and augmented hippocampal connectivity to the entorhinal cortex. Together, our findings highlight a distributed, brain-wide engagement associated with transient memory reactivation and its sequential replay. This study uses simultaneous EEG-fMRI to investigate how the brain replays past experiences, revealing that transient replay events by EEG correspond with increased hippocampal activity and enhanced connectivity with the default mode network in fMRI. [ABSTRACT FROM AUTHOR]

Increasing evidence suggests that alternative splicing plays an important role in Alzheimer's disease (AD) pathology. We used long-read sequencing in combination with a novel bioinformatics tool (FICLE) to profile transcript diversity in the entorhinal cortex of female transgenic (TG) mice harboring a mutant form of human tau. Our analyses revealed hundreds of novel isoforms and identified differentially expressed transcripts – including specific isoforms of Apoe, App, Cd33, Clu, Fyn and Trem2 – associated with the development of tau pathology in TG mice. Subsequent profiling of the human cortex from AD individuals and controls revealed similar patterns of transcript diversity, including the upregulation of the dominant TREM2 isoform in AD paralleling the increased expression of the homologous transcript in TG mice. Our results highlight the importance of differential transcript usage, even in the absence of gene-level expression alterations, as a mechanism underpinning gene regulation in the development of AD neuropathology. The authors used long-read sequencing to reveal novel isoforms and differential transcript use in a transgenic model of tau pathology. Similar patterns were found in the human cortex, supporting a role for alternative splicing in Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Inflammation is an important factor in Alzheimer's disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman's correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer's Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman's correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3–9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention. [ABSTRACT FROM AUTHOR]

The relationship between the triglyceride glucose-body mass index (TyG-BMI) index and Alzheimer's disease (AD) pathology, cognition, and brain structure remains unclear. This study aimed to investigate these associations, focusing on cerebrospinal fluid (CSF) biomarkers, cognitive measures, and brain imaging data. Eight hundred and fifty-five non-demented participants were included. Linear regression was used to explore associations between the TyG-BMI index and AD pathology, cognition, and brain structure. The association between the TyG-BMI index and AD risk was assessed using Kaplan–Meier and Cox proportional hazards models. Longitudinal relationships were assessed using linear mixed-effects models. Mediation analyses were conducted to examine AD pathology's potential mediating role between the TyG-BMI index and cognition as well as brain structure. In the linear regression analyses, higher TyG-BMI levels were associated with increased Aβ42 and decreased Tau, pTau, Tau/Aβ42, pTau/Aβ42, and pTau/Tau. Positive correlations were observed with mini-mental state examination (MMSE), memory (MEM), executive function (EF), and the volumes of the hippocampus, entorhinal cortex, and middle temporal regions, while negative correlations were found with Alzheimer's Disease Assessment Scale (ADAS). Longitudinally, the TyG-BMI index was inversely associated with ADAS, and positively with MMSE, MEM, EF, hippocampus, entorhinal, and middle temporal. High TyG-BMI levels were correlated with lower AD risk (HR 0.996 [0.994, 0.999]). Mediation analyses revealed AD pathology mediated the association between TyG-BMI index and cognition as well as brain structure. Additionally, the TyG-BMI index could mediate cognitive changes by influencing brain structure. The TyG-BMI index is associated with AD pathology, cognition, and brain structure. [ABSTRACT FROM AUTHOR]

In the human brain, the regions responsible for emotion processing, motivation, and memory are heavily influenced by olfaction, whose neural pathway is directly exposed to the outer world. In this study, we used fMRI to examine how different olfactory conditions might affect the functional connectivity circuit underlying working memory in the brain. To this end, 30 adults (aged 20–35), 13 males and 17 females, with high educational levels were chosen. Participants were screened for potential olfactory issues before undergoing the Sniffin' sticks test, which was part of the inclusion criteria. Before imaging, each participant was given the required level of training and was then asked to complete four olfactory tests involving pleasant and unpleasant odors, air, and null stimulation. The results of Seed-based analysis suggested a function connection between the inferior parietal region and the left frontal pole region upon olfactory stimulation with vanilla scent in contrast to null stimulation in this comparison, ROI-based analysis revealed an inverse synchronous among the entorhinal cortex, orbitofrontal cortex, and dorsolateral prefrontal cortex (dlPFC). Both dlPFC and hippocampus were involved in olfactory discrimination between two different stimulants. Our findings indicate the presence of inverse correlations between several regions associated with olfaction and working memory, with pleasant scents leaving a stronger impact on the working memory-related areas, particularly the inferior parietal region. [ABSTRACT FROM AUTHOR]

The marine flavobacterium Krokinobactereikastus light-driven sodium pump (KR2) generates an outward sodium ion current under 530 nm light stimulation, representing a promising optogenetic tool for seizure control. However, the specifics of KR2 application to suppress epileptic activity have not yet been addressed. In the present study, we investigated the possibility of KR2 photostimulation to suppress epileptiform activity in mouse brain slices using the 4-aminopyrindine (4-AP) model. We injected the adeno-associated viral vector (AAV-PHP.eB-hSyn-KR2-YFP) containing the KR2 sodium pump gene enhanced with appropriate trafficking tags. KR2 expression was observed in the lateral entorhinal cortex and CA1 hippocampus. Using whole-cell patch clamp in mouse brain slices, we show that KR2, when stimulated with LED light, induces a substantial hyperpolarization of entorhinal neurons. However, continuous photostimulation of KR2 does not interrupt ictal discharges in mouse entorhinal cortex slices induced by a solution containing 4-AP. KR2-induced hyperpolarization strongly activates neuronal HCN channels. Consequently, turning off photostimulation resulted in HCN channel-mediated rebound depolarization accompanied by a transient increase in spontaneous network activity. Using low-frequency pulsed photostimulation, we induced the generation of short HCN channel-mediated discharges that occurred in response to the light stimulus being turned off; these discharges reliably interrupt ictal activity. Thus, low-frequency pulsed photostimulation of KR2 can be considered as a potential tool for controlling epileptic seizures. [ABSTRACT FROM AUTHOR]

Minimal experiments, such as head-fixed wheel-running and sleep, offer experimental advantages but restrict the amount of observable behavior, making it difficult to classify functional cell types. Arguably, the grid cell, and its striking periodicity, would not have been discovered without the perspective provided by free behavior in an open environment. Here, we show that by shifting the focus from single neurons to populations, we change the minimal experimental complexity required. We identify grid cell modules and show that the activity covers a similar, stable toroidal state space during wheel running as in open field foraging. Trajectories on grid cell tori correspond to single trial runs in virtual reality and path integration in the dark, and the alignment of the representation rapidly shifts with changes in experimental conditions. Thus, we provide a methodology to discover and study complex internal representations in even the simplest of experiments. Here the authors present a topological data approach to navigate neural recordings, revealing that even the simplest tasks can illuminate complexities of internal spatial representations such as grid cell tori and boundary vector circles. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurological condition characterized by impaired cognitive function and behavioral alterations. While AD research historically centered around mis-folded proteins, advances in mass spectrometry techniques have triggered increased exploration of the AD lipidome with lipid dysregulation emerging as a critical player in AD pathogenesis. Gangliosides are a class of glycosphingolipids enriched within the central nervous system. Previous work has suggested a shift in a-series gangliosides from complex (GM1) to simple (GM2 and GM3) species may be related to the development of neurodegenerative disease. In addition, complex gangliosides with 20 carbon sphingosine chains have been shown to increase in the aging brain. In this study, we utilized matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) to interrogate the in situ relationship of a-series gangliosides with either 18 or 20 carbon sphingosine chains (d18:1 or d20:1, respectively) in the post-mortem human AD brain. Here, we expanded upon previous literature and demonstrated a significant decrease in the GM1 d20:1 to GM1 d18:1 ratio in regions of the dentate gyrus and entorhinal cortex in AD relative to control brain tissue. Then, we demonstrated that the MALDI-MSI profile of GM3 co-localizes with histologically confirmed amyloid beta (Aβ) plaques and found a significant increase in both GM1 and GM3 in proximity to Aβ plaques. Collectively, this study demonstrates a perturbation of the ganglioside profile in AD, and validates a pipeline for MALDI-MSI and classic histological staining in the same tissue sections. This demonstrates feasibility for integrating untargeted mass spectrometry imaging approaches into a digital pathology framework. [ABSTRACT FROM AUTHOR]

Speech-in-noise (SIN) perception is a primary complaint of individuals with audiometric hearing loss. SIN performance varies drastically, even among individuals with normal hearing. The present genome-wide association study (GWAS) investigated the genetic basis of SIN deficits in individuals with self-reported normal hearing in quiet situations. GWAS was performed on 279,911 individuals from the UB Biobank cohort, with 58,847 reporting SIN deficits despite reporting normal hearing in quiet. GWAS identified 996 single nucleotide polymorphisms (SNPs), achieving significance (p < 5*10−8) across four genomic loci. 720 SNPs across 21 loci achieved suggestive significance (p < 10−6). GWAS signals were enriched in brain tissues, such as the anterior cingulate cortex, dorsolateral prefrontal cortex, entorhinal cortex, frontal cortex, hippocampus, and inferior temporal cortex. Cochlear cell types revealed no significant association with SIN deficits. SIN deficits were associated with various health traits, including neuropsychiatric, sensory, cognitive, metabolic, cardiovascular, and inflammatory conditions. A replication analysis was conducted on 242 healthy young adults. Self-reported speech perception, hearing thresholds (0.25–16 kHz), and distortion product otoacoustic emissions (1–16 kHz) were utilized for the replication analysis. 73 SNPs were replicated with a self-reported speech perception measure. 211 SNPs were replicated with at least one and 66 with at least two audiological measures. 12 SNPs near or within MAPT, GRM3, and HLA-DQA1 were replicated for all audiological measures. The present study highlighted a polygenic architecture underlying SIN deficits in individuals with self-reported normal hearing. [ABSTRACT FROM AUTHOR]

How does the human brain construct cognitive maps for decision-making and inference? Here, we conduct an fMRI study on a navigation task in multidimensional abstract spaces. Using a deep neural network model, we assess learning levels and categorized paths into exploration and exploitation stages. Univariate analyses show higher activation in the bilateral hippocampus and lateral prefrontal cortex during exploration, positively associated with learning level and response accuracy. Conversely, the bilateral orbitofrontal cortex (OFC) and retrosplenial cortex show higher activation during exploitation, negatively associated with learning level and response accuracy. Representational similarity analysis show that the hippocampus, entorhinal cortex, and OFC more accurately represent destinations in exploitation than exploration stages. These findings highlight the collaboration between the medial temporal lobe and prefrontal cortex in learning abstract space structures. The hippocampus may be involved in spatial memory formation and representation, while the OFC integrates sensory information for decision-making in multidimensional abstract spaces. An fMRI study on a navigation task in multidimensional abstract spaces showed that the human hippocampus, entorhinal cortex, and orbitofrontal cortex collaborate in learning abstract space structures. [ABSTRACT FROM AUTHOR]

Sensory impairment and brain atrophy is common among older adults, increasing the risk of dementia. Yet, the degree to which multiple co-occurring sensory impairments (MSI across vision, proprioception, vestibular function, olfactory, and hearing) are associated with brain morphometry remain unexplored. Data were from 208 cognitively unimpaired participants (mean age 72 ± 10 years; 59% women) enrolled in the Baltimore Longitudinal Study of Aging. Multiple linear regression models were used to estimate cross-sectional associations between MSI and regional brain imaging volumes. For each additional sensory impairment, there were associated lower orbitofrontal gyrus and entorhinal cortex volumes but higher caudate and putamen volumes. Participants with MSI had lower mean volumes in the superior frontal gyrus, orbitofrontal gyrus, superior parietal lobe, and precuneus compared to participants with < 2 impairments. While MSI was largely associated with lower brain volumes, our results suggest the possibility that MSI was associated with higher basal ganglia volumes. Longitudinal analyses are needed to evaluate the temporality and directionality of these associations. [ABSTRACT FROM AUTHOR]

Integrating energy systems with information systems in smart grids offers a promising avenue for combating electricity theft by leveraging real-time data insights. Suspicious activity indicative of theft can be identified through anomalous consumption patterns observed in smart networks. However, a smart model is required for capturing and analysing the data intelligently to accurately detect electricity theft. In the paper, electricity theft has been detected using an encoder-decoder-based classifier that integrates two models of convolutional neural networks (CNN). The aim is to scan the strength of the data and built a smart model that analysed the connections in complex data and determine the pattern of theft. The model comprises three compartments: the auto-encoder, the wide convolutional neural network (1-D CNN model), and the deep convolutional neural network (2-D CNN model). The auto-encoder has been trained on the complex and in-depth linkage between the theft data and the normal data as it removes noise and unnecessary information. The 1-D CNN model gathers relevant connections and general features, while the 2-D CNN model determines the rate at which energy theft occurs and differentiates between the energy-stealing consumers and normal consumers. The efficacy of the approach is underscored by its superiority over traditional deep learning and machine learning techniques. This paper elucidates the distinct advantages and applications of the proposed model in combating electricity theft within smart grid environments. [ABSTRACT FROM AUTHOR]

Hippocampal afferent inputs, terminating on proximal and distal subfields of the cornus ammonis (CA), enable the functional discrimination of 'what' (item identity) and 'where' (spatial location) elements of a spatial representation. This kind of information is supported by structures such as the retrosplenial cortex (RSC). Spatial content learning promotes the expression of hippocampal synaptic plasticity, particularly long-term depression (LTD). In the CA1 region, this is specifically facilitated by the learning of item-place features of a spatial environment. Gene-tagging, by means of time-locked fluorescence in situ hybridization (FISH) to detect nuclear expression of immediate early genes, can reveal neuronal populations that engage in experience-dependent information encoding. In the current study, using FISH, we examined if learning-facilitated LTD results in subfield-specific information encoding in the hippocampus and RSC. Rats engaged in novel exploration of small items during stimulation of Schaffer collateral-CA1 synapses. This resulted in LTD (> 24 h). FISH, to detect nuclear expression of Homer1a, revealed that the distal-CA1 and proximal-CA3 subcompartments were particularly activated by this event. By contrast, all elements of the proximodistal cornus ammonis-axis showed equal nuclear Homer1a expression following LTD induction solely by means of afferent stimulation. The RSC exhibited stronger nuclear Homer1a expression in response to learning-facilitated LTD, and to novel item-place experience, compared to LTD induced by sole afferent stimulation in CA1. These results show that both the cornus ammonis and RSC engage in differentiated information encoding of item-place learning that is salient enough, in its own right, to drive the expression of hippocampal LTD. These results also reveal a novel role of the RSC in item-place learning. [ABSTRACT FROM AUTHOR]

The pathophysiology of Fronto Temporal Dementia (FTD) remains poorly understood, specifically the role of astroglia. Our aim was to explore the hypothesis of astrocytic alterations as a component for FTD pathophysiology. We performed an in-depth tri-dimensional (3-D) anatomical and morphometric study of glial fibrillary acidic protein (GFAP)-positive and glutamine synthetase (GS)-positive astrocytes in the human entorhinal cortex (EC) of FTD patients. The studies at this level in the different types of human dementia are scarce. We observed a prominent astrocyte atrophy of GFAP-positive astrocytes and co-expressing GFAP/GS astrocytes, characterised by a decrease in area and volume, whilst minor changes in GS-positive astrocytes in FTD compared to non-dementia controls (ND) samples. This study evidences the importance of astrocyte atrophy and dysfunction in human EC. We hypothesise that FTD is not only a neuropathological disease, but also a gliopathological disease having a major relevance in the understanding the astrocyte role in FTD pathological processes and development. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the efficacy of ethyl cinnamate (EC) (75 μg/ml) in ameliorating the effects of γ-radiation (2, 5, and 8 Gy) on normal liver BRL-3A cells at 1 and 24 h post-irradiation. γ-radiation-induced persistent damage to normal hepatocytes is partly mediated by reactive oxygen species (ROS)-regulated early apoptosis and prolonged inhibition of survival factors. EC treatment increased superoxide dismutase (SOD) activity, decreased ROS yield and lipid peroxidation (LPO), activated the PI3-AKT pathway and p-Bcl-2, and reduced cleaved caspase -3, - 9, and Bax. This study highlights for the first time the potential of ethyl cinnamate as an efficient radioprotector. [ABSTRACT FROM AUTHOR]

The medial entorhinal cortex (MEC) is hypothesized to function as a cognitive map for memory-guided navigation. How this map develops during learning and influences memory remains unclear. By imaging MEC calcium dynamics while mice successfully learned a novel virtual environment over ten days, we discovered that the dynamics gradually became more spatially consistent and then stabilized. Additionally, grid cells in the MEC not only exhibited improved spatial tuning consistency, but also maintained stable phase relationships, suggesting a network mechanism involving synaptic plasticity and rigid recurrent connectivity to shape grid cell activity during learning. Increased c-Fos expression in the MEC in novel environments further supports the induction of synaptic plasticity. Unsuccessful learning lacked these activity features, indicating that a consistent map is specific for effective spatial memory. Finally, optogenetically disrupting spatial consistency of the map impaired memory-guided navigation in a well-learned environment. Thus, we demonstrate that the establishment of a spatially consistent MEC map across learning both correlates with, and is necessary for, successful spatial memory. The medial entorhinal cortex (MEC) is hypothesized to function as a cognitive map for memory-guided navigation. Here, the authors demonstrate that the establishment of a spatially consistent MEC map across learning correlates with, and is necessary for, successful spatial memory. [ABSTRACT FROM AUTHOR]

How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming a trajectory through an abstract two-dimensional value space. During this task, the entorhinal cortex exhibited a grid-like representation with an orientation aligned to the axis through the value space most informative for choices. A network of brain regions, including ventromedial prefrontal cortex, tracked the prospective value difference between options. These findings suggest that the entorhinal grid system supports the prediction of future values by representing a cognitive map, which might be used to generate lower-dimensional value signals to guide prospective decision making. Values of choice options often change over time. Here, the authors show that during prospective decision making the entorhinal cortex encodes changing values using a grid-like representation, suggesting the formation of a cognitive value map. [ABSTRACT FROM AUTHOR]

Objectives. To assess the morphological features of brain structures in patients with temporal lobe epilepsy and comorbid depression. Materials and methods. A total of 80 patients with temporal lobe epilepsy (18–60 years old, including 38 with comorbid depression) and 48 healthy subjects of comparable age were examined over the period January 1, 2017 to December 31, 2020. Brain MRI scans were obtained following an epileptic protocol using a 1.5-T scanner. Diagnoses of focal temporal lobe epilepsy were established by neurologists specializing in epilepsy in accordance with the 2017 International League Against Epilepsy classification. The presence and severity of depressive disorder was determined by psychiatrists by clinical interview and Beck Depression Inventory (BDI-II) self-reports. Volumes of subcortical structures and cortical thickness were evaluated by processing MRI data in FreeSurfer 6.0 software. At the group level, analysis of covariance with the Holm–Bonferroni correction was used for statistical analysis. Results. Morphometric analysis revealed significant decreases in the volumes of the brainstem and thalamus bilaterally, along with an increase in the volume of the choroid plexus in the left hemisphere in patients with epilepsy as compared with healthy controls. In addition, patients with epilepsy, as compared with healthy controls, had significantly greater thickness of the entorhinal cortex and the temporal pole and isthmus of the cingulate gyrus in the left hemisphere, while in the right hemisphere patients had significantly lesser thickness of the middle temporal gyrus and inferior temporal gyrus. There was no association between the presence of depression and significant MRI structural changes. Conclusions. These data identify a relationship between temporal lobe epilepsy and the morphology of brain structures, while comorbid depression showed no such link. [ABSTRACT FROM AUTHOR]

The hippocampal subfield CA3 is thought to function as an auto-associative network that stores experiences as memories. Information from these experiences arrives directly from the entorhinal cortex as well as indirectly through the dentate gyrus, which performs sparsification and decorrelation. The computational purpose for these dual input pathways has not been firmly established. We model CA3 as a Hopfield-like network that stores both dense, correlated encodings and sparse, decorrelated encodings. As more memories are stored, the former merge along shared features while the latter remain distinct. We verify our model's prediction in rat CA3 place cells, which exhibit more distinct tuning during theta phases with sparser activity. Finally, we find that neural networks trained in multitask learning benefit from a loss term that promotes both correlated and decorrelated representations. Thus, the complementary encodings we have found in CA3 can provide broad computational advantages for solving complex tasks. While the hippocampus is well-known to store specific memories, it can also learn common features that are shared across individual memories. Here, the authors show how this ability arises from dual input pathways and how it can inspire better machine learning methods. [ABSTRACT FROM AUTHOR]

Speech-driven 3D human face animation has made admirable progress. However, synthesizing 3D facial speakers with head motion is still an unsolved problem. This is because head motion, as a speech-independent appearance representation, is difficult to model by a speech-driven approach. To solve this problem, we propose 3D head-talk, which generates 3D face animations combined with extreme head motion. In this work, we face a key challenge to generate natural head movements that match the speech rhythm. We first form an end-to-end autoregressive model by combining a dual-tower and single-tower Transformer, with a speech encoder encoding the long-term audio environment, a facial grid encoder encoding subtle changes in the vertices of the 3D facial grid, and a single-tower decoder automatically regressing to predict a series of 3D facial animation grids. Next, the predicted 3D facial animation sequence is edited by a motion field generator containing head motion to obtain an output sequence containing extreme head motion. Finally, the natural 3D face animation under extreme head motion is presented in combination with the input audio. The quantitative and qualitative results show that our method outperforms current state-of-the-art methods, and stabilizes the non-area region while maintaining the appearance of extreme head motion. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disease that is the main form of dementia. Abnormal deposition of amyloid-beta (Aβ) peptides in neurons and synapses cause neuronal loss and cognitive deficits. We have previously reported that ferroptosis and necroptosis were implicated in Aβ25−35 neurotoxicity, and their specific inhibitors had attenuating effects on cognitive impairment induced by Aβ25−35 neurotoxicity. Here, we aimed to examine the impact of ferroptosis and necroptosis inhibition following the Aβ25−35 neurotoxicity on the neuronal excitability of dentate gyrus (DG) and the possible involvement of voltage-gated Ca2+ channels in their effects. After inducing Aβ25−35 neurotoxicity, electrophysiological alterations in the intrinsic properties and excitability were recorded by the whole-cell patch-clamp under current-clamp condition. Voltage-clamp recordings were also performed to shed light on the involvement of calcium channel currents. Aβ25−35 neurotoxicity induced a considerable reduction in input resistance (Rin), accompanied by a profoundly decreased excitability and a reduction in the amplitude of voltage-gated calcium channel currents in the DG granule cells. However, three days of administration of either ferrostatin-1 (Fer-1), a ferroptosis inhibitor, or Necrostatin-1 (Nec-1), a necroptosis inhibitor, in the entorhinal cortex could almost preserve the normal excitability and the Ca2+ currents. In conclusion, these findings suggest that ferroptosis and necroptosis involvement in EC amyloidopathy could be a potential candidate to prevent the suppressive effect of Aβ on the Ca2+ channel current and neuronal function, which might take place in neurons during the development of AD. [ABSTRACT FROM AUTHOR]

Pathophysiology of sporadic Alzheimer's disease (SAD) and familial Alzheimer's disease (FAD) remains poorly known, including the exact role of neuroglia and specifically astroglia, in part because studies of astrocytes in human Alzheimer's disease (AD) brain samples are scarce. As far as we know, this is the first study of a 3-D immunohistochemical and microstructural analysis of glial fibrillary acidic protein (GFAP)- and glutamine synthetase (GS)-positive astrocytes performed in the entorhinal cortex (EC) of human SAD and FAD samples. In this study, we report prominent atrophic changes in GFAP and GS astrocytes in the EC of both SAD and FAD characterised by a decrease in area and volume when compared with non-demented control samples (ND). Furthermore, we did not find neither astrocytic loss nor astrocyte proliferation or hypertrophy (gliosis). In contrast with the astrogliosis classically accepted hypothesis, our results show a highly marked astrocyte atrophy that could have a major relevance in AD pathological processes being fundamental and key for AD mnesic and cognitive alterations equivalent in both SAD and FAD. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess, monitor, and analyzed water quality parameters recorded from reservoirs in of Saudi Arabia for Electrical Conductivity (EC) forecasting. Water quality parameters play a key role in the lives of humans, plants, and animals depending on those reservoirs for survival. In this paper, we evaluate the performance of a novel autoencoder stacked LSTM transfer learning (TL + aeSLSTM) model for EC forecasting. Although various factors such as pH, EC, CaCO3, Turbidity, Salinity, Sodium (Na+), Potassium (K+), Magnesium (Mg), Calcium (Ca2+), Fluoride (F−), Chloride (Cl−), Bromide (Br−), Nitrate (NO3−), and Sulfate ( SO 4 2 - ) affects EC forecasting, in this paper we utilized Total Dissolved Solids (TDS) and Na as our source dataset for EC forecasting. In order to select the most appropriate or suitable transfer learning model network for EC forecasting, a trail-by-error approach was employed where parameters e.g., hidden layers, number of neurons, batch-size, epochs, optimizers, and activation functions were varied and applied to each model. To assess the performance of the proposed model to the baseline model, we employed the most common evaluation metrics ie. MSE, MAE, and MAPE. Superior performance by the novel TL + aeSLSTM over the state-of-the-art models illustrates the capability of the model to utilize both the advantage of the autoencoder, stacked LSTM, and transfer learning capability for EC forecasting. The results show that the least value of train MAE, train MSE, train RMSE, test MAE, test MSE, test RMSE when Na is used as the source dataset for EC forecasting by the TL + aeSLSTM are 248.044, 519.292, 22.788, 206.114, 212.004, and 14.560, respectively. [ABSTRACT FROM AUTHOR]

The pathological features of Alzheimer's disease are the formation of amyloid plaques and entanglement of nerve fibers. Studies have shown that Cu may be involved in the formation of amyloid plaques. However, their role has been controversial. The aim of this study was to explore the role of Cu in AD. We applied the "R" software for our differential analysis. Differentially expressed genes were screened using the limma package. Copper metabolism-related genes and the intersection set of differential genes with GSE5281 were searched; functional annotation was performed. The protein–protein interaction network was constructed using several modules to analyse the most significant hub genes. The hub genes were then qualified, and a database was used to screen for small-molecule AD drugs. We identified 87 DEGs. gene ontology analysis focused on homeostatic processes, response to toxic substances, positive regulation of transport, and secretion. The enriched molecular functions are mainly related to copper ion binding, molecular function regulators, protein-containing complex binding, identical protein binding and signalling receptor binding. The KEGG database is mainly involved in central carbon metabolism in various cancers, Parkinson's disease and melanoma. We identified five hub genes, FGF2, B2M, PTPRC, CD44 and SPP1, and identified the corresponding small molecule drugs. Our study identified key genes possibly related to energy metabolism in the pathological mechanism of AD and explored potential targets for AD treatment by establishing interaction networks. [ABSTRACT FROM AUTHOR]

In fear conditioning with time intervals between the conditioned (CS) and unconditioned (US) stimuli, a neural representation of the CS must be maintained over time to be associated with the later US. Usually, temporal associations are studied by investigating individual brain regions. It remains unknown, however, the effect of the interval at the network level, uncovering functional connections cooperating for the CS transient memory and its fear association. We investigated the functional network supporting temporal associations using a task in which a 5-s interval separates the contextual CS from the US (CFC-5s). We quantified c-Fos expression in forty-nine brain regions of male rats following the CFC-5s training, used c-Fos correlations to generate functional networks, and analyzed them by graph theory. Control groups were trained in contextual fear conditioning, in which CS and US overlap. The CFC-5s training additionally activated subdivisions of the basolateral, lateral, and medial amygdala; prelimbic, infralimbic, perirhinal, postrhinal, and intermediate entorhinal cortices; ventral CA1 and subiculum. The CFC-5s network had increased amygdala centrality and higher amygdala internal and external connectivity with the retrosplenial cortex, thalamus, and hippocampus. Amygdala and thalamic nuclei were network hubs. Functional connectivity among these brain regions could support CS transient memories and their association. [ABSTRACT FROM AUTHOR]

Traditional convolutional neural network (CNN) methods rely on dense tensors, which makes them suboptimal for spatially sparse data. In this paper, we propose a CNN model based on sparse tensors for efficient processing of high-resolution shapes represented as binary voxel occupancy grids. In contrast to a dense CNN that takes the entire voxel grid as input, a sparse CNN processes only on the non-empty voxels, thus reducing the memory and computation overhead caused by the sparse input data. We evaluate our method on two clinically relevant skull reconstruction tasks: (1) given a defective skull, reconstruct the complete skull (i.e., skull shape completion), and (2) given a coarse skull, reconstruct a high-resolution skull with fine geometric details (shape super-resolution). Our method outperforms its dense CNN-based counterparts in the skull reconstruction task quantitatively and qualitatively, while requiring substantially less memory for training and inference. We observed that, on the 3D skull data, the overall memory consumption of the sparse CNN grows approximately linearly during inference with respect to the image resolutions. During training, the memory usage remains clearly below increases in image resolution—an × 8 increase in voxel number leads to less than × 4 increase in memory requirements. Our study demonstrates the effectiveness of using a sparse CNN for skull reconstruction tasks, and our findings can be applied to other spatially sparse problems. We prove this by additional experimental results on other sparse medical datasets, like the aorta and the heart. Project page at https://github.com/Jianningli/SparseCNN. [ABSTRACT FROM AUTHOR]

The representation of grid cells in the medial entorhinal cortex region is crucial for path integration. In this paper, we proposed a grid cell modeling mechanism by mapping the agent's self-motion in Euclidean space to the neuronal activity of grid cells. Our representational model can achieve multi-scale hexagonal patterns of grid cells from recurrent neural network (RNN) and enables path integration for 1D, 2D and 3D spaces. Different from the existing works which need to learn weights of RNN to get the vector representation of grid cells, our method can obtain weights by direct matrix operations. Moreover, compared with the classical models based on continuous attractor network, our model avoids the connection matrix's symmetry limitation and spatial representation redundancy problems. In this paper, we also discuss the connection pattern between grid cells and place cells to demonstrate grid cells' functioning as a metric for coding space. [ABSTRACT FROM AUTHOR]

The clearance of brain interstitial fluid (ISF) is important in maintaining brain homeostasis. ISF clearance impairment leads to toxic material accumulation in the brain, and ischemic stroke could impair ISF clearance. The present study investigates ISF clearance under normal and ischemic conditions. The carboxylate-modified FluoSpheres beads (0.04 μm in diameter) were injected into the striatum. Sham or transient middle cerebral artery occlusion surgeries were performed on the mice. The brain sections were immunostained with cell markers, and bead distribution at various time points was examined with a confocal microscope. Primary mouse neuronal cultures were incubated with the beads to explore in vitro endocytosis. Two physiological routes for ISF clearance were identified. The main one was to the lateral ventricle (LV) through the cleft between the striatum and the corpus callosum (CC)/external capsule (EC), where some beads were captured by the ependymal macrophages and choroid plexus. An alternative and minor route was to the subarachnoid space through the CC/EC and the cortex, where some of the beads were endocytosed by neurons. After ischemic stroke, a significant decrease in the main route and an increase in the minor route were observed. Additionally, microglia/macrophages engulfed the beads in the infarction. In conclusion, we report that the physiological clearance of ISF and beads mainly passes through the cleft between the CC/EC and striatum into the LV, or alternatively through the cortex into the subarachnoid space. Stroke delays the main route but enhances the minor route, and microglia/macrophages engulf the beads in the infarction. [ABSTRACT FROM AUTHOR]

Granule cells (GC) in the dentate gyrus receive main excitatory input from the entorhinal cortex (EC) via the perforant pathway (PP). In adults, this excitatory input is rapidly curtailed by feedforward inhibition, creating a short temporal window for integration of excitatory inputs. However, the delayed maturation and integration of interneurons into the circuitry involved in feedforward inhibition suggests a developmental delay in the inhibition associated with EC input to GCs. Here, we explored developmental changes in inhibition associated with EC input to the GCs using whole-cell recordings in postnatal days P2 to P62 mouse hippocampal slices. PP- evoked excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs) in the GCs were voltage-separated using a low-chloride pipette solution. Short-latency EPSCs could be evoked in granule cells from P2, and their delay remained stable during development. In contrast, the delay of IPSCs was highly dependent on age. In the first postnatal week, IPSC delays reached tens of milliseconds and showed high variability across trials. IPSC delays gradually decreased with age to reach adult values by the end of the first postnatal month. The temporal integration window, assessed as a time difference between EPSC and IPSC delays, decreased during the postnatal period. Thus, GABAergic inhibition associated with EC input to GCs undergoes significant changes during postnatal development and enables a large integration window for excitatory EC inputs to GCs during the neonatal period. [ABSTRACT FROM AUTHOR]

The spread pattern of progressive degeneration seen in Alzheimer's disease (AD) to small-scale medial temporal lobe subregions is critical for early diagnosis. In this context, it was aimed to examine the morphometric changes of the hippocampal subfields, amygdala nuclei, entorhinal cortex (ERC), and parahippocampal cortex (PHC) using MRI. MRI data of patients diagnosed with 20 Alzheimer's disease dementia (ADD), 30 amnestic mild cognitive impairment (aMCI), and 30 subjective cognitive impairment (SCI) without demographic differences were used. Segmentation and parcellation were performed using FreeSurfer. The segmentation process obtained volume values of 12 hippocampal subfields and 9 amygdala nuclei. Thickness values of ERC and PHC were calculated with the parcellation process. ANCOVA was performed using age, education and gender as covariates to evaluate the intergroup differences. Linear discriminant analysis was used to investigate whether atrophy predicted groups at an early stage. ERC and PHC thickness decreased significantly throughout the disease continuum, while only ERC was affected in the early stage. When the hippocampal and amygdala subfields were compared volumetrically, significant differences were found in the amygdala between the SCI and aMCI groups. In the early period, only volume reduction in the anterior amygdaloid area of the amygdala nuclei exceeded the significance threshold. Research on AD primarily focuses on original hippocampocentric structures and their main function which is episodic memory. Our results emphasized the significance of so far relatively neglected olfactocentric structures and their functions, such as smell and social cognition in the pre-dementia stages of the AD process. [ABSTRACT FROM AUTHOR]

Objectives: To develop and validate an automatic classification algorithm for diagnosing Alzheimer's disease (AD) or mild cognitive impairment (MCI). Methods and materials: This study evaluated a high-performance interpretable network algorithm (TabNet) and compared its performance with that of XGBoost, a widely used classifier. Brain segmentation was performed using a commercially approved software. TabNet and XGBoost were trained on the volumes or radiomics features of 102 segmented regions for classifying subjects into AD, MCI, or cognitively normal (CN) groups. The diagnostic performances of the two algorithms were compared using areas under the curves (AUCs). Additionally, 20 deep learning–based AD signature areas were investigated. Results: Between December 2014 and March 2017, 161 AD, 153 MCI, and 306 CN cases were enrolled. Another 120 AD, 90 MCI, and 141 CN cases were included for the internal validation. Public datasets were used for external validation. TabNet with volume features had an AUC of 0.951 (95% confidence interval [CI], 0.947–0.955) for AD vs CN, which was similar to that of XGBoost (0.953 [95% CI, 0.951–0.955], p = 0.41). External validation revealed the similar performances of two classifiers using volume features (0.871 vs. 0.871, p = 0.86). Likewise, two algorithms showed similar performances with one another in classifying MCI. The addition of radiomics data did not improve the performance of TabNet. TabNet and XGBoost focused on the same 13/20 regions of interest, including the hippocampus, inferior lateral ventricle, and entorhinal cortex. Conclusions: TabNet shows high performance in AD classification and detailed interpretation of the selected regions. Clinical relevance statement: Using a high-performance interpretable deep learning network, the automatic classification algorithm assisted in accurate Alzheimer's disease detection using 3D T1-weighted brain MRI and detailed interpretation of the selected regions. Key Points: • MR volumetry data revealed that TabNet had a high diagnostic performance in differentiating Alzheimer's disease (AD) from cognitive normal cases, which was comparable with that of XGBoost. • The addition of radiomics data to the volume data did not improve the diagnostic performance of TabNet. • Both TabNet and XGBoost selected the clinically meaningful regions of interest in AD, including the hippocampus, inferior lateral ventricle, and entorhinal cortex. [ABSTRACT FROM AUTHOR]

This study proposes a method based on fully convolutional neural networks (FCNs) to identify migratory birds from their songs, with the objective of recognizing which birds pass through certain areas and at what time. To determine the best FCN architecture, extensive experimentation was conducted through a grid search, exploring the optimal depth, width, and activation function of the network. The results showed that the optimal number of filters is 400 in the widest layer, with 4 convolutional blocks with maxpooling and an adaptive activation function. The proposed FCN offers a significant advantage over other techniques, as it can recognize the sound of a bird in audio of any length with an accuracy greater than 85%. Furthermore, due to its architecture, the network can detect more than one species from audio and can carry out near-real-time sound recognition. Additionally, the proposed method is lightweight, making it ideal for deployment and use in IoT devices. The study also presents a comparative analysis of the proposed method against other techniques, demonstrating an improvement of over 67% in the best-case scenario. These findings contribute to advancing the field of bird sound recognition and provide valuable insights into the practical application of FCNs in real-world scenarios. [ABSTRACT FROM AUTHOR]

Hippocampal theta oscillations orchestrate faster beta-to-gamma oscillations facilitating the segmentation of neural representations during navigation and episodic memory. Supra-theta rhythms of hippocampal CA1 are coordinated by local interactions as well as inputs from the entorhinal cortex (EC) and CA3 inputs. However, theta-nested gamma-band activity in the medial septum (MS) suggests that the MS may control supra-theta CA1 oscillations. To address this, we performed multi-electrode recordings of MS and CA1 activity in rodents and found that MS neuron firing showed strong phase-coupling to theta-nested supra-theta episodes and predicted changes in CA1 beta-to-gamma oscillations on a cycle-by-cycle basis. Unique coupling patterns of anatomically defined MS cell types suggested that indirect MS-to-CA1 pathways via the EC and CA3 mediate distinct CA1 gamma-band oscillations. Optogenetic activation of MS parvalbumin-expressing neurons elicited theta-nested beta-to-gamma oscillations in CA1. Thus, the MS orchestrates hippocampal network activity at multiple temporal scales to mediate memory encoding and retrieval. Timing is key for efficient coding and communication across brain areas. Here, the authors found that the medial septum orchestrates hippocampal network activity at multiple temporal scales likely mediating memory encoding and retrieval. [ABSTRACT FROM AUTHOR]

Ketamine, a rapid-acting anesthetic and acute antidepressant, carries undesirable spatial cognition side effects including out-of-body experiences and spatial memory impairments. The neural substrates that underlie these alterations in spatial cognition however, remain incompletely understood. Here, we used electrophysiology and calcium imaging to examine ketamine's impacts on the medial entorhinal cortex and hippocampus, which contain neurons that encode an animal's spatial position, as mice navigated virtual reality and real world environments. Ketamine acutely increased firing rates, degraded cell-pair temporal firing-rate relationships, and altered oscillations, leading to longer-term remapping of spatial representations. In the reciprocally connected hippocampus, the activity of neurons that encode the position of the animal was suppressed after ketamine administration. Together, these findings demonstrate ketamine-induced dysfunction of the MEC-hippocampal circuit at the single cell, local-circuit population, and network levels, connecting previously demonstrated physiological effects of ketamine on spatial cognition to alterations in the spatial navigation circuit. Ketamine's antidepressant effects can be accompanied by altered spatial cognition. Here, the authors record from thousands of neurons in awake behaving mice to reveal how ketamine disrupts coding in the spatial navigation circuit. [ABSTRACT FROM AUTHOR]

For example, the OB and olfactory peduncle may be affected with Lewy pathology in early stages of dementia with Lewy bodies (DLB) and Parkinson's disease (PD), particularly in cases with amygdalar predominance [[1], [5]]. Keywords: Synuclein; Sex; Lewy body; Preformed fibril; Parkinson's disease EN Synuclein Sex Lewy body Preformed fibril Parkinson's disease 651 654 4 09/15/23 20231001 NES 231001 K. As all lifeforms must display sensitivity to surrounding chemicals, the mammalian olfactory bulb (OB) and its peripheral fibers have evolved to sample the air. Previously, we noted denser inclusions in some limbic structures of female mice after OB/AON fibril infusions [[10]], but AI-driven analyses reveal that female mice form larger limbic inclusions than do males [[4]]. [Extracted from the article]

Neural computation is often traced in terms of either rate- or phase-codes. However, most circuit operations will simultaneously affect information across both coding schemes. It remains unclear how phase and rate coded information is transmitted, in the face of continuous modification at consecutive processing stages. Here, we study this question in the entorhinal cortex (EC)- dentate gyrus (DG)- CA3 system using three distinct computational models. We demonstrate that DG feedback inhibition leverages EC phase information to improve rate-coding, a computation we term phase-to-rate recoding. Our results suggest that it i) supports the conservation of phase information within sparse rate-codes and ii) enhances the efficiency of plasticity in downstream CA3 via increased synchrony. Given the ubiquity of both phase-coding and feedback circuits, our results raise the question whether phase-to-rate recoding is a recurring computational motif, which supports the generation of sparse, synchronous population-rate-codes in areas beyond the DG. How neural codes are passed from one brain area to the next remains poorly understood. Here, the authors show how neuronal feedback inhibition converts incoming temporal information into sparse rate information in a biophysical network model of the dentate gyrus. [ABSTRACT FROM AUTHOR]

Which facets of human spatial navigation do sex and menstrual cycle influence? To answer this question, a cross-sectional online study of reproductive age women and men was conducted in which participants were asked to demonstrate and self-report their spatial navigation skills and strategies. Participants self-reported their sex and current menstrual phase [early follicular (EF), late follicular/periovulatory (PO), and mid/late luteal (ML)], and completed a series of questionnaires and tasks measuring self-reported navigation strategy use, topographical memory, cognitive map formation, face recognition, and path integration. We found that sex influenced self-reported use of cognitive map- and scene-based strategies, face recognition, and path integration. Menstrual phase moderated the influence of sex: compared to men, women had better face recognition and worse path integration, but only during the PO phase; PO women were also better at path integration in the presence of a landmark compared to EF + ML women and men. These findings provide evidence that human spatial navigation varies with the menstrual cycle and suggest that sensitivity of the entorhinal cortex and longitudinal axis of the hippocampus to differential hormonal effects may account for this variation. [ABSTRACT FROM AUTHOR]

Na+/K+-ATPase maintains the neuron's resting potential and the transmembrane gradient of K+ and Na+ cations, thus regulating ion transport and cellular volume. Mutations in Na+/K+-ATPase genes that impair its function can cause significant impairments in the nervous system function, including the development of epilepsy, if not lethal. Different forms of Na+/K+-ATPase are expressed in various classes of neurons and exhibit different characteristics. Thus, the impaired function of Na+/K+-ATPase may differentially affect the functioning of inhibitory and excitatory neurons. This study aims to determine the effects of the Na+/K+-ATPase antagonist ouabain on the electrophysiological characteristics of pyramidal cells and fast-spiking interneurons, as well as its impact on synaptic transmission. The results indicate that exposure to 5 µM ouabain results in depolarization of the resting membrane potential of both types of neurons, as well as decreased amplitude and increased duration of the action potential of pyramidal neurons. Furthermore, ouabain caused a decrease in the amplitude of afterhyperpolarization in fast-spiking interneurons. Moreover, both types of neurons exhibited a decrease in the threshold of action potential generation and the current at which depolarization block occurs. The addition of ouabain did not alter other electrophysiological characteristics of neurons. Furthermore, ouabain rapidly attenuates GABAergic transmission without affecting excitatory synaptic transmission. These new findings on the effects of ouabain on excitatory pyramidal neurons and inhibitory interneurons contribute to the understanding of the mechanism underlying changes in the balance of excitation and inhibition in neural networks under Na+/K+-ATPase function impairment. [ABSTRACT FROM AUTHOR]

Dense vertex-to-vertex correspondence (i.e. registration) between 3D faces is a fundamental and challenging issue for 3D &2D face analysis. While the sparse landmarks are definite with anatomically ground-truth correspondence, the dense vertex correspondences on most facial regions are unknown. In this view, the current methods commonly result in reasonable but diverse solutions, which deviate from the optimum to the dense registration problem. In this paper, we revisit dense registration by a dimension-degraded problem, i.e. proportional segmentation of a line, and employ an iterative dividing and diffusing method to reach an optimum solution that is robust to different initializations. We formulate a local registration problem for dividing and a linear least-square problem for diffusing, with constraints on fixed features on a 3D facial surface. We further propose a multi-resolution algorithm to accelerate the computational process. The proposed method is linked to a novel local scaling metric, where we illustrate the physical significance as smooth adaptions for local cells of 3D facial shapes. Extensive experiments on public datasets demonstrate the effectiveness of the proposed method in various aspects. Generally, the proposed method leads to not only significantly better representations of 3D facial data, but also coherent local deformations with elegant grid architecture for fine-grained registrations. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Development of a noninvasive olfactory stimulation fMRI system in marmosets" published in Scientific Reports. The correction addresses an error in Figure 8 of the original article. The corrected figure and its accompanying legend are provided in the notice. The authors of the article are Terumi Yurimoto, Fumiko Seki, Akihiro Yamada, Junnosuke Okajima, Tomoyuki Yambe, Yoshiaki Takewa, Michiko Kamioka, Takashi Inoue, Yusuke Inoue, and Erika Sasaki. [Extracted from the article]