Subjective memory complaints in young people; their relationship withobjective cognitive performance and the role of neuroticism / Quejas subjetivas de memoria en jóvenes; su relación con el rendimiento cognitivo objetivo y el papel del neuroticismo

Las percepciones de olvidos recurrentes o episodios de distracción en la vida diaria se denominan quejas subjetivas de memoria (QSM). Su naturaleza se ha estudiado ampliamente en adultos mayores, pero su importancia y relación con el rendimiento neurocognitivo no se han abordado por completo en adultos más jóvenes. Se han sugerido algunos rasgos psicológicos como posibles moderadores de la asociación entre el rendimiento de la memoria objetiva y subjetiva. El primer objetivo de este estudio fue analizar la correspondencia entre la percepción objetiva y subjetiva de los fallos de memoria en jóvenes. En segundo lugar, estudiamos si el rasgo psicológico del neuroticismo podría estar influyendo en esta relación. Para ello, medimos QSM, diferentes dominios cognitivos (memoria episódica y de trabajo y funciones ejecutivas) y neuroticismo en 80 hombres y mujeres jóvenes. Los resultados mostraron que solo la memoria episódica inmediata estaba estadísticamente relacionada con los QSM. Curiosamente, las relaciones negativas entre el rendimiento de la memoria objetiva y subjetiva solo aparecieron en participantes con mayor neuroticismo. Por lo tanto, las quejas de memoria reportadas por los jóvenes podrían reflejar un peor rendimiento de la memoria episódica inmediata, mientras que el neuroticismo jugaría un papel principal en la asociación entre los déficits de memoria y las QSM. Este estudio proporciona datos que pueden ayudar a comprender mejor las QSM en los jóvenes.(AU)

Perceptions of recurrent forgetfulness or episodes of distraction in daily life are referred to as subjective memory complaints (SMCs). Their nature has been extensively studied in older adults, but their significance and relationship with neurocognitive performance have not been fully ad-dressed in younger adults. Some psychological traits have been suggested as possible moderators of the association between objective and subjective memory performance. The first aim of this study was to analyze the corre-spondence between the objective and subjective perception of memory failures in young people. Second, we studied whether the psychological trait of neuroticism could be influencing this relationship. Todo this, we measured SMCs, different cognitive domains (episodic and working memory and executive functions), and neuroticism in 80 young men and women. Results showed that only immediate episodic memory was statisti-cally related to SMCs. Interestingly, the negative relationships between ob-jective and subjective memory performance only appeared in participants with higher neuroticism. Thus, memory complaints reported by young people could reflect poorer immediate episodic memory performance, whereas neuroticism would play a main role in the association between memory deficits and SMCs. This study provides data that can help to bet-ter understand SMCs in young people.(AU)

Executive functions and addictions: a Structural Equation Modeling Approach and the Italian validation of the Adult Executive Functioning Inventory (ADEXI).

INTRODUCTION: the work aims to observe the associations between psychoactive substance use and gambling and executive functioning as well as to validate the Italian version of the "Adult Executive Functioning Inventory" (ADEXI) scale. METHODS: data were collected through a representative cross-sectional study among 5,160 people (18-84 years old) called IPSAD® (Italian Population Survey on Alcohol and Other Drugs). Structural Equation Modeling (SEM) was performed to explore the associations between ADEXI and other behaviors measured with standardized questionnaires. Cronbach α has been performed to investigate the psychometric properties of the Italian version of the ADEXI scale. RESULTS: SEM showed that both WM and INH were correlated with problematic cannabis use (WM r = 0.112; INH r = 0.251) and gambling (WM r = 0.101; INH r = 0.168), while problematic alcohol use was correlated only with INH (r = 0.233). Cronbach α for the WM subscale was 0.833 (CI 0.826-0.840), while for INH was 0.694 (CI 0.680-0.708). CONCLUSION: results pointed out a strong correlation between addictions (substance-related and non-substance-related) and WM and INH impairments among the adult general population. Moreover, the ADEXI scale could be considered a valuable tool for general population surveys to detect working memory and inhibition characteristics.

Efficient state of charge estimation of lithium-ion batteries in electric vehicles using evolutionary intelligence-assisted GLA-CNN-Bi-LSTM deep learning model.

The battery's performance heavily influences the safety, dependability, and operational efficiency of electric vehicles (EVs). This paper introduces an innovative hybrid deep learning architecture that dramatically enhances the estimation of the state of charge (SoC) of lithium-ion (Li-ion) batteries, crucial for efficient EV operation. Our model uniquely integrates a convolutional neural network (CNN) with bidirectional long short-term memory (Bi-LSTM), optimized through evolutionary intelligence, enabling an advanced level of precision in SoC estimation. A novel aspect of this work is the application of the Group Learning Algorithm (GLA) to tune the hyperparameters of the CNN-Bi-LSTM network meticulously. This approach not only refines the model's accuracy but also significantly enhances its efficiency by optimizing each parameter to best capture and integrate both spatial and temporal information from the battery data. This is in stark contrast to conventional models that typically focus on either spatial or temporal data, but not both effectively. The model's robustness is further demonstrated through its training across six diverse datasets that represent a range of EV discharge profiles, including the Highway Fuel Economy Test (HWFET), the US06 test, the Beijing Dynamic Stress Test (BJDST), the dynamic stress test (DST), the federal urban driving schedule (FUDS), and the urban development driving schedule (UDDS). These tests are crucial for ensuring that the model can perform under various real-world conditions. Experimentally, our hybrid model not only surpasses the performance of existing LSTM and CNN frameworks in tracking SoC estimation but also achieves an impressively quick convergence to true SoC values, maintaining an average root mean square error (RMSE) of less than 1 %. Furthermore, the experimental outcomes suggest that this new deep learning methodology outstrips conventional approaches in both convergence speed and estimation accuracy, thus promising to significantly enhance battery life and overall EV efficiency.

Study of factors affecting the magnetic sensing capability of shape memory alloys for non-destructive evaluation of cracks in concrete: Using response surface methodology (RSM) and artificial neural network (ANN) approaches.

Currently, the field of structural health monitoring (SHM) is focused on investigating non-destructive evaluation techniques for the identification of damages in concrete structures. Magnetic sensing has particularly gained attention among the innovative non-destructive evaluation techniques. Recently, the embedded magnetic shape memory alloy (MSMA) wire has been introduced for the evaluation of cracks in concrete components through magnetic sensing techniques while providing reinforcement as well. However, the available research in this regard is very scarce. This study has focused on the analyses of parameters affecting the magnetic sensing capability of embedded MSMA wire for crack detection in concrete beams. The response surface methodology (RSM) and artificial neural network (ANN) models have been used to analyse the magnetic sensing parameters for the first time. The models were trained using the experimental data obtained through literature. The models aimed to predict the alteration in magnetic flux created by a concrete beam that has a 1 mm wide embedded MSMA wire after experiencing a fracture or crack. The results showed that the change in magnetic flux was affected by the position of the wire and the position of the crack with respect to the position of the magnet in the concrete beam. RSM optimisation results showed that maximum change in magnetic flux was obtained when the wire was placed at a depth of 17.5 mm from the top surface of the concrete beam, and a crack was present at an axial distance of 8.50 mm from the permanent magnet. The change in magnetic flux was 9.50 % considering the aforementioned parameters. However, the ANN prediction results showed that the optimal wire and crack position were 10 mm and 1.1 mm, respectively. The results suggested that a larger beam requires a larger diameter of MSMA wire or multiple sensors and magnets for crack detection in concrete beams.

A randomized clinical trial to evaluate feasibility, tolerability, and preliminary target engagement for a novel executive working memory training in adolescents with ADHD.

OBJECTIVE: Working memory training for Attention-Deficit/Hyperactivity Disorder (ADHD) has focused on increasing working memory capacity, with inconclusive evidence for its effectiveness. Alternative training targets are executive working memory (EWM) processes that promote flexibility or bolster stability of working memory contents to guide behavior via selective attention. This randomized, placebo-controlled study was designed to assess feasibility, tolerability, and behavioral target engagement of a novel EWM training for ADHD. METHOD: 62 ADHD-diagnosed adolescents (12-18 years) were randomized to EWM training or placebo arms for 20 remotely coached sessions conducted over 4-5 weeks. Primary outcome measures were behavioral changes on EWM tasks. Secondary outcomes were intervention tolerability, trial retention, and responsiveness to adaptive training difficulty manipulations. RESULTS: Linear regression analyses found intervention participants showed medium effect size improvements, many of which were statistically significant, on Shifting and Filtering EWM task accuracy and Shifting and Updating reaction time measures. Intervention participants maintained strong self-rated motivation, mood, and engagement and progressed through the adaptive difficulty measures, which was further reflected in high trial retention. CONCLUSIONS: The results suggest that these EWM processes show promise as training targets for ADHD. The subsequent NIMH R33-funded extension clinical trial will seek to replicate and extend these findings.

Grasp and remember: the impact of human and robotic actions on object preference and memory.

Goal contagion, the tendency to adopt others' goals, significantly impacts cognitive processes, which gains particular importance in the emerging field of human-robot interactions. The present study explored how observing human versus robotic actions affects preference and memory. Series of objects undergoing either human or robotic grasping actions together with static (no action) objects were presented, while participants indicated their preference for each object. After a short delay, their memory for grasped, static and new (unstudied) stimuli was tested. Human actions enhanced preference and subsequent recollection of objects, more than robotic actions. In the context of human action, static objects were also perceived as more familiar at recognition. The goal contagion's influence on memory was found to be independent from its impact on preference. These findings highlight the critical role of human interaction in eliciting the impact of goal contagion on cognitive evaluations, memory engagement and the creation of detailed associative memories.

Pilot study on the feasibility of shape memory alloy implantation for Vancouver type B1 periprosthetic femoral fractures in a canine model: a step toward advancing treatment modalities.

BACKGROUND: Cerclage wiring is commonly used for treating fractures; however, it has several limitations, including mechanical weakness, decreased blood circulation, and technical complexity. In this study, we developed an implant using a shape memory alloy (SMA) and tested its efficacy in treating Vancouver type B1 (VB1) periprosthetic femoral fractures (PFFs) in a canine model. METHODS: The mid-diaphyseal fracture models underwent reduction via the SMA plate (SMA group) or the cerclage cable plate (cable group) method in randomly selected pelvic limbs. An intraoperative evaluation was conducted to assess the surgical time and difficulty related to implant fitting. Clinical assessments, radiography, microcomputed tomography (micro-CT), histological analysis, positron emission tomography (PET)/CT, and galvanic corrosion analysis were conducted for 52 weeks to evaluate bone healing and blood perfusion. RESULTS: The results for bone healing and blood perfusion were not significantly different between the groups (p > 0.05). In addition, no evidence of galvanic corrosion was present in any of the implants. However, the median surgical time was 75 min (range, 53-82 min) for the SMA group and 126 min (range, 120-171 min) for the cable group, which was a statistically significant difference (p = 0.0286). CONCLUSIONS: This study assessed the ability of a newly developed shape memory alloy (SMA) to treat VB1 periprosthetic femoral fractures (PFFs) in canines for over a 52-week period and revealed outcomes comparable to those of traditional methods in terms of bone healing and mechanical stability. Despite the lower surgical complexity and potential time-saving benefits of this treatment, further research is needed to confirm its efficacy.

Learning a Memory-Enhanced Multi-Stage Goal-Driven Network for Egocentric Trajectory Prediction.

We propose a memory-enhanced multi-stage goal-driven network (ME-MGNet) for egocentric trajectory prediction in dynamic scenes. Our key idea is to build a scene layout memory inspired by human perception in order to transfer knowledge from prior experiences to the current scenario in a top-down manner. Specifically, given a test scene, we first perform scene-level matching based on our scene layout memory to retrieve trajectories from visually similar scenes in the training data. This is followed by trajectory-level matching and memory filtering to obtain a set of goal features. In addition, a multi-stage goal generator takes these goal features and uses a backward decoder to produce several stage goals. Finally, we integrate the above steps into a conditional autoencoder and a forward decoder to produce trajectory prediction results. Experiments on three public datasets, JAAD, PIE, and KITTI, and a new egocentric trajectory prediction dataset, Fuzhou DashCam (FZDC), validate the efficacy of the proposed method.

AI-Driven Data Analysis of Quantifying Environmental Impact and Efficiency of Shape Memory Polymers.

This research investigates the environmental sustainability and biomedical applications of shape memory polymers (SMPs), focusing on their integration into 4D printing technologies. The objectives include comparing the carbon footprint, embodied energy, and water consumption of SMPs with traditional materials such as metals and conventional polymers and evaluating their potential in medical implants, drug delivery systems, and tissue engineering. The methodology involves a comprehensive literature review and AI-driven data analysis to provide robust, scalable insights into the environmental and functional performance of SMPs. Thermomechanical modeling, phase transformation kinetics, and heat transfer analyses are employed to understand the behavior of SMPs under various conditions. Significant findings reveal that SMPs exhibit considerably lower environmental impacts than traditional materials, reducing greenhouse gas emissions by approximately 40%, water consumption by 30%, and embodied energy by 25%. These polymers also demonstrate superior functionality and adaptability in biomedical applications due to their ability to change shape in response to external stimuli. The study concludes that SMPs are promising sustainable alternatives for biomedical applications, offering enhanced patient outcomes and reduced environmental footprints. Integrating SMPs into 4D printing technologies is poised to revolutionize healthcare manufacturing processes and product life cycles, promoting sustainable and efficient medical practices.

The Neurotrophin System in the Postnatal Brain-An Introduction.

Neurotrophins can bind to and signal through specific receptors that belong to the class of the Trk family of tyrosine protein kinase receptors. In addition, they can bind and signal through a low-affinity receptor, termed p75NTR. Neurotrophins play a crucial role in the development, maintenance, and function of the nervous system in vertebrates, but they also have important functions in the mature nervous system. In particular, they are involved in synaptic and neuronal plasticity. Thus, it is not surprisingly that they are involved in learning, memory and cognition and that disturbance in the neurotrophin system can contribute to psychiatric diseases. The neurotrophin system is sensitive to aging and changes in the expression levels correlate with age-related changes in brain functions. Several polymorphisms in genes coding for the different neurotrophins or neurotrophin receptors have been reported. Based on the importance of the neurotrophins for the central nervous system, it is not surprisingly that several of these polymorphisms are associated with psychiatric diseases. In this review, we will shed light on the functions of neurotrophins in the postnatal brain, especially in processes that are involved in synaptic and neuronal plasticity.

Compromised Cerebral Arterial Perfusion, Altered Brain Tissue Integrity, and Cognitive Impairment in Adolescents with Complex Congenital Heart Disease.

(1) Introduction: Adolescents with complex congenital heart disease (CCHD) show brain tissue injuries in regions associated with cognitive deficits. Alteration in cerebral arterial perfusion (CAP), as measured by arterial transit time (ATT), may lead to perfusion deficits and potential injury. Our study aims to compare ATT values between CCHD patients and controls and assess the associations between ATT values, MD values, and cognitive scores in adolescents with CCHD. (2) Methods: 37 CCHD subjects, 14-18 years of age, who had undergone surgical palliation and 30 healthy controls completed cognitive testing and brain MRI assessments using a 3.0-Tesla scanner. ATT values and regional brain mean diffusivity [MD] were assessed for the whole brain using diffusion tensor imaging. (3) Results: The mean MoCA values [23.1 ± 4.1 vs. 28.1 ± 2.3; p < 0.001] and General Memory Index, with a subscore of WRAML2 [86.8 ± 15.4 vs. 110.3 ± 14.5; p < 0.001], showed significant cognitive deficits in CCHD patients compared to controls. The mean global ATT was significantly higher in CCHD patients versus controls (mean ± SD, s, 1.26 ± 0.11 vs. 1.19 ± 0.11, p = 0.03), respectively. The partial correlations between ATT values, MD values, and cognitive scores (p < 0.005) showed significant associations in areas including the hippocampus, prefrontal cortices, cerebellum, caudate, anterior and mid cingulate, insula, thalamus, and lingual gyrus. (4) Conclusions: Adolescents with CCHD had prolonged ATTs and showed correlation with clinical measurements of cognitive impairment and MRI measurements of brain tissue integrity. This suggests that altered CAP may play a role in brain tissue injury and cognitive impairment after surgical palliation.

Mechanical and Shape Memory Properties of Additively Manufactured Polyurethane (PU)/Halloysite Nanotube (HNT) Nanocomposites.

This paper investigates the impact of halloysite nanotube (HNT) content on mechanical and shape memory properties of additively manufactured polyurethane (PU)/HNT nanocomposites. The inclusion of 8 wt% HNTs increases their tensile strength by 30.4% when compared with that of virgin PU at 44.75 MPa. Furthermore, consistently significant increases in tensile modulus, compressive strength and modulus, as well as specific energy absorption are also manifested by 47.2%, 34.0%, 125% and 72.7% relative to neat PU at 2.29 GPa, 3.88 MPa, 0.28 GPa and 0.44 kJ/kg respectively. However, increasing HNT content reduces lateral strain due to the restricted mobility of polymeric chains, leading to a decrease in negative Poisson's ratio (NPR). As such, shape recovery ratio and time of PU/HNT nanocomposites are reduced by 9 and 45% with the inclusion of 10 wt% HNTs despite an increasing shape fixity ratio up to 12% relative to those of neat PU.

Drawing as a means to characterize memory and cognition.

As psychological research embraces more naturalistic questions and large-scale analytic methods, drawing has emerged as an exciting tool for studying cognition. Drawing provides rich information about how we view the world, ranging from largely veridical perceptual representations to abstracted meta-cognitive representations. Drawing also requires the integration of multiple processes (e.g., vision, memory, motor learning), and experience with drawing can have an impact on such processes. As a result, drawing presents several interesting cognitive questions, while also providing a way to gain insight into a multitude of others. This Special Issue features 25 cutting-edge studies utilizing drawing to reveal discoveries transversing fields in psychology. These diverse studies investigate drawing across children, young adults, older adults, and special populations such as individuals with blindness, anterograde amnesia, apraxia, and semantic dementia. These studies detail new discoveries about the mechanisms underlying memory, attention, mathematical reasoning, and other cognitive processes. They employ a range of methods including psychophysical experiments, deep learning, and neuroimaging. Finally, many of these studies cover topics about the impact of drawing as a process on other cognitive processes, including how drawing expertise impacts other processes like visual memory or spatial abilities. Overall, this collection of studies paves the way for an exciting future of drawing as a commonplace tool used by psychologists to understand complex phenomena.

Neural ensembles: role of intrinsic excitability and its plasticity.

Synaptic connectivity defines groups of neurons that engage in correlated activity during specific functional tasks. These co-active groups of neurons form ensembles, the operational units involved in, for example, sensory perception, motor coordination and memory (then called an engram). Traditionally, ensemble formation has been thought to occur via strengthening of synaptic connections via long-term potentiation (LTP) as a plasticity mechanism. This synaptic theory of memory arises from the learning rules formulated by Hebb and is consistent with many experimental observations. Here, we propose, as an alternative, that the intrinsic excitability of neurons and its plasticity constitute a second, non-synaptic mechanism that could be important for the initial formation of ensembles. Indeed, enhanced neural excitability is widely observed in multiple brain areas subsequent to behavioral learning. In cortical structures and the amygdala, excitability changes are often reported as transient, even though they can last tens of minutes to a few days. Perhaps it is for this reason that they have been traditionally considered as modulatory, merely supporting ensemble formation by facilitating LTP induction, without further involvement in memory function (memory allocation hypothesis). We here suggest-based on two lines of evidence-that beyond modulating LTP allocation, enhanced excitability plays a more fundamental role in learning. First, enhanced excitability constitutes a signature of active ensembles and, due to it, subthreshold synaptic connections become suprathreshold in the absence of synaptic plasticity (iceberg model). Second, enhanced excitability promotes the propagation of dendritic potentials toward the soma and allows for enhanced coupling of EPSP amplitude (LTP) to the spike output (and thus ensemble participation). This permissive gate model describes a need for permanently increased excitability, which seems at odds with its traditional consideration as a short-lived mechanism. We propose that longer modifications in excitability are made possible by a low threshold for intrinsic plasticity induction, suggesting that excitability might be on/off-modulated at short intervals. Consistent with this, in cerebellar Purkinje cells, excitability lasts days to weeks, which shows that in some circuits the duration of the phenomenon is not a limiting factor in the first place. In our model, synaptic plasticity defines the information content received by neurons through the connectivity network that they are embedded in. However, the plasticity of cell-autonomous excitability could dynamically regulate the ensemble participation of individual neurons as well as the overall activity state of an ensemble.

Epithelial organoid supports resident memory CD8 T cell differentiation.

Resident memory T cells (TRMs) play a vital role in regional immune defense. Although laboratory rodents have been extensively used to study fundamental TRM biology, poor isolation efficiency and low cell survival rates have limited the implementation of TRM-focused high-throughput assays. Here, we engineer a murine vaginal epithelial organoid (VEO)-CD8 T cell co-culture system that supports CD8 TRM differentiation. These in-vitro-generated TRMs are phenotypically and transcriptionally similar to in vivo TRMs. Pharmacological and genetic approaches showed that transforming growth factor ß (TGF-ß) signaling plays a crucial role in their differentiation. The VEOs in our model are susceptible to viral infections and the CD8 T cells are amenable to genetic manipulation, both of which will allow a detailed interrogation of antiviral CD8 T cell biology. Altogether we have established a robust in vitro TRM differentiation system that is scalable and can be subjected to high-throughput assays that will rapidly add to our understanding of TRMs.

Longitudinal assessment of glymphatic changes following mild traumatic brain injury: Insights from perivascular space burden and DTI-ALPS imaging.

Introduction: Traumatic brain injury (TBI) even in the mild form may result in long-lasting post-concussion symptoms. TBI is also a known risk to late-life neurodegeneration. Recent studies suggest that dysfunction in the glymphatic system, responsible for clearing protein waste from the brain, may play a pivotal role in the development of dementia following TBI. Given the diverse nature of TBI, longitudinal investigations are essential to comprehending the dynamic changes in the glymphatic system and its implications for recovery. Methods: In this prospective study, we evaluated two promising glymphatic imaging markers, namely the enlarged perivascular space (ePVS) burden and Diffusion Tensor Imaging-based ALPS index, in 44 patients with mTBI at two early post-injury time points: approximately 14 days (14Day) and 6-12 months (6-12Mon) post-injury, while also examining their associations with post-concussion symptoms. Additionally, 37 controls, comprising both orthopedic patients and healthy individuals, were included for comparative analysis. Results: Our key findings include: (1) White matter ePVS burden (WM-ePVS) and ALPS index exhibit significant correlations with age. (2) Elevated WM-ePVS burden in acute mTBI (14Day) is significantly linked to a higher number of post-concussion symptoms, particularly memory problems. (3) The increase in the ALPS index from acute (14Day) to the chronic (6-12Mon) phases in mTBI patients correlates with improvement in sleep measures. Furthermore, incorporating WM-ePVS burden and the ALPS index from acute phase enhances the prediction of chronic memory problems beyond socio-demographic and basic clinical information. Conclusion: ePVS burden and ALPS index offers distinct values in assessing glymphatic structure and activity. Early evaluation of glymphatic function could be crucial for understanding TBI recovery and developing targeted interventions to improve patient outcomes.

Association of chronotype with language and episodic memory processing in children: implications for brain structure.

Introduction: Chronotype refers to individual preference in circadian cycles and is associated with psychiatric problems. It is mainly classified into early (those who prefer to be active in the morning and sleep and wake up early) and late (those who prefer to be active in the evening and sleep and wake up late) chronotypes. Although previous research has demonstrated associations between chronotype and cognitive function and brain structure in adults, little is known regarding these associations in children. Here, we aimed to investigate the relationship between chronotype and cognitive function in children. Moreover, based on the significant association between chronotype and specific cognitive functions, we extracted regions-of-interest (ROI) and examined the association between chronotype and ROI volumes. Methods: Data from 4,493 children (mean age of 143.06 months) from the Adolescent Brain Cognitive Development Study were obtained, wherein chronotype (mid-sleep time on free days corrected for sleep debt on school days) was assessed by the Munich Chronotype Questionnaire. Subsequently, the associations between chronotype, cognitive function, and ROI volumes were evaluated using linear mixed-effects models. Results: Behaviorally, chronotype was negatively associated with vocabulary knowledge, reading skills, and episodic memory performance. Based on these associations, the ROI analysis focused on language-related and episodic memory-related areas revealed a negative association between chronotype and left precentral gyrus and right posterior cingulate cortex volumes. Furthermore, the precentral gyrus volume was positively associated with vocabulary knowledge and reading skills, while the posterior cingulate cortex volume was positively associated with episodic memory performance. Discussion: These results suggest that children with late chronotype have lower language comprehension and episodic memory and smaller brain volumes in the left precentral gyrus and right posterior cingulate cortex associated with these cognitive functions.

Impaired Dynamics of Positional and Contextual Neural Coding in an Alzheimer's Disease Rat Model.

Background: The hippocampal representation of space, formed by the collective activity of populations of place cells, is considered as a substrate of spatial memory. Alzheimer's disease (AD), a widespread severe neurodegenerative condition of multifactorial origin, typically exhibits spatial memory deficits among its early clinical signs before more severe cognitive impacts develop. Objective: To investigate mechanisms of spatial memory impairment in a double transgenic rat model of AD. Methods: In this study, we utilized 9-12-month-old double-transgenic TgF344-AD rats and age-matched controls to analyze the spatial coding properties of CA1 place cells. We characterized the spatial memory representation, assessed cells' spatial information content and direction-specific activity, and compared their population coding in familiar and novel conditions. Results: Our findings revealed that TgF344-AD animals exhibited lower precision in coding, as evidenced by reduced spatial information and larger receptive zones. This impairment was evident in maps representing novel environments. While controls instantly encoded directional context during their initial exposure to a novel environment, transgenics struggled to incorporate this information into the newly developed hippocampal spatial representation. This resulted in impairment in orthogonalization of stored activity patterns, an important feature directly related to episodic memory encoding capacity. Conclusions: Overall, the results shed light on the nature of impairment at both the single-cell and population levels in the transgenic AD model. In addition to the observed spatial coding inaccuracy, the findings reveal a significantly impaired ability to adaptively modify and refine newly stored hippocampal memory patterns.