Medial Entorhinal Cortex Research Articles

Waveform-based classification of dentate spikes.

Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer's disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing.

Contribution of the medial entorhinal cortex to performance on the Traveling Salesperson Problem in rats

In order to successfully navigate through space, animals must rely on multiple cognitive processes, including orientation in space, memory of object locations, and navigational decisions based on that information. Although highly-controlled behavioral tasks are valuable for isolating and targeting specific processes, they risk producing a narrow understanding of complex behavior in natural contexts. The Traveling Salesperson Problem (TSP) is an optimization problem that can be used to study naturalistic foraging behaviors, in which subjects select routes between multiple baited targets. Foraging is a spontaneous, yet complex, behavior, involving decision-making, attention, course planning, and memory. Previous research found that hippocampal lesions in rats impaired TSP task performance, particularly on measures of spatial memory. Although traditional laboratory tests have shown the medial entorhinal cortex (MEC) to play an important role in spatial memory, if and how the MEC is involved in finding efficient solutions to the TSP remains unknown. In the current study, rats were trained on the TSP, learning to retrieve bait from targets in a variety of spatial configurations. After recovering from either an MEC lesion or control sham surgery, the rats were tested on eight new configurations. Our results showed that, similar to rats with hippocampal lesions, MEC-lesioned rats were impaired on measures of spatial memory, but not spatial decision-making, with greatest impairments on configurations requiring a global navigational strategy for selecting the optimal route. These findings suggest that the MEC is important for effective spatial navigation, especially when global cue processing is required.

Lateral entorhinal cortex subpopulations represent experiential epochs surrounding reward.

During goal-directed navigation, 'what' information, describing the experiences occurring in periods surrounding a reward, can be combined with spatial 'where' information to guide behavior and form episodic memories. This integrative process likely occurs in the hippocampus, which receives spatial information from the medial entorhinal cortex; however, the source of the 'what' information is largely unknown. Here, we show that mouse lateral entorhinal cortex (LEC) represents key experiential epochs during reward-based navigation tasks. We discover separate populations of neurons that signal goal approach and goal departure and a third population signaling reward consumption. When reward location is moved, these populations immediately shift their respective representations of each experiential epoch relative to reward, while optogenetic inhibition of LEC disrupts learning the new reward location. Therefore, the LEC contains a stable code of experiential epochs surrounding and including reward consumption, providing reward-centric information to contextualize the spatial information carried by the medial entorhinal cortex.

Comparison of head direction cell firing characteristics across thalamo-parahippocampal circuitry.

Head direction (HD) cells, which fire persistently when an animal's head is pointed in a particular direction, are widely thought to underlie an animal's sense of spatial orientation and have been identified in several limbic brain regions. Robust HD cell firing is observed throughout the thalamo-parahippocampal system, although recent studies report that parahippocampal HD cells exhibit distinct firing properties, including conjunctive aspects with other spatial parameters, which suggest they play a specialized role in spatial processing. Few studies, however, have quantified these apparent differences. Here, we performed a comparative assessment of HD cell firing characteristics across the anterior dorsal thalamus (ADN), postsubiculum (PoS), parasubiculum (PaS), medial entorhinal (MEC), and postrhinal (POR) cortices. We report that HD cells with a high degree of directional specificity were observed in all five brain regions, but ADN HD cells display greater sharpness and stability in their preferred directions, and greater anticipation of future headings compared to parahippocampal regions. Additional analysis indicated that POR HD cells were more coarsely modulated by other spatial parameters compared to PoS, PaS, and MEC. Finally, our analyses indicated that the sharpness of HD tuning decreased as a function of laminar position and conjunctive coding within the PoS, PaS, and MEC, with cells in the superficial layers along with conjunctive firing properties showing less robust directional tuning. The results are discussed in relation to theories of functional organization of HD cell tuning in thalamo-parahippocampal circuitry.

A spatial transformation-based CAN model for information integration within grid cell modules

The hippocampal-entorhinal circuit is considered to play an important role in the spatial cognition of animals. However, the mechanism of the information flow within the circuit and its contribution to the function of the grid-cell module are still topics of discussion. Prevailing theories suggest that grid cells are primarily influenced by self-motion inputs from the Medial Entorhinal Cortex, with place cells serving a secondary role by contributing to the visual calibration of grid cells. However, recent evidence suggests that both self-motion inputs and visual cues may collaboratively contribute to the formation of grid-like patterns. In this paper, we introduce a novel Continuous Attractor Network model based on a spatial transformation mechanism. This mechanism enables the integration of self-motion inputs and visual cues within grid-cell modules, synergistically driving the formation of grid-like patterns. From the perspective of individual neurons within the network, our model successfully replicates grid firing patterns. From the view of neural population activity within the network, the network can form and drive the activated bump, which describes the characteristic feature of grid-cell modules, namely, path integration. Through further exploration and experimentation, our model can exhibit significant performance in path integration. This study provides a new insight into understanding the mechanism of how the self-motion and visual inputs contribute to the neural activity within grid-cell modules. Furthermore, it provides theoretical support for achieving accurate path integration, which holds substantial implications for various applications requiring spatial navigation and mapping.

Minute-scale oscillatory sequences in medial entorhinal cortex

The medial entorhinal cortex (MEC) hosts many of the brain’s circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience1. Whereas location is known to be encoded by spatially tuned cell types in this brain region2,3, little is known about how the activity of entorhinal cells is tied together over time at behaviourally relevant time scales, in the second-to-minute regime. Here we show that MEC neuronal activity has the capacity to be organized into ultraslow oscillations, with periods ranging from tens of seconds to minutes. During these oscillations, the activity is further organized into periodic sequences. Oscillatory sequences manifested while mice ran at free pace on a rotating wheel in darkness, with no change in location or running direction and no scheduled rewards. The sequences involved nearly the entire cell population, and transcended epochs of immobility. Similar sequences were not observed in neighbouring parasubiculum or in visual cortex. Ultraslow oscillatory sequences in MEC may have the potential to couple neurons and circuits across extended time scales and serve as a template for new sequence formation during navigation and episodic memory formation.

Valproate treatment induces age- and sex-dependent neuronal activity changes according to a patch clamp study.

Autism spectrum disorder is a heterogeneous neurodevelopmental disorder characterized by impaired social interactions, restricted, and stereotyped behaviors. The valproic acid model is one of the most recognized and broadly used models in rats to induce core symptoms of this disorder. Comorbidity of epilepsy and autism occurs frequently, due to similar background mechanisms that include the imbalance of excitation and inhibition. In this series of experiments, treatment was performed on rat dams with a single 500mg/kg dose i.p. valproate injection on embryonic day 12.5. Intracellular whole-cell patch clamp recordings were performed on brain slices prepared from adolescent and adult offspring of both sexes on pyramidal neurons of the medial prefrontal cortex and entorhinal cortex. Current clamp stimulation utilizing conventional current step protocols and dynamic clamp stimulation were applied to assess neuronal excitability. Membrane properties and spiking characteristics of layer II-III pyramidal cells were analyzed in both cortical regions. Significant sex-dependent and age-dependent differences were found in several parameters in the control groups. Considering membrane resistance, rheobase, voltage sag slope, and afterdepolarization slope, we observed notable changes mainly in the female groups. Valproate treatment seemed to enhance these differences and increase network excitability. However, it is possible that compensatory mechanisms took place during the maturation of the network while reaching the age-group of 3 months. Based on the results, the expression of the hyperpolarization-activated cyclic nucleotide-gated channels may be appreciably affected by the valproate treatment, which influences fundamental electrophysiological properties of the neurons such as the voltage sag. Remarkable changes appeared in the prefrontal cortex; however, also the entorhinal cortex shows similar tendencies.

Multimodal and multiregional atlas of Alzheimer’s disease changes

AbstractBackgroundAlzheimer’s disease (AD) is the most common form of dementia. The progression of AD throughout the brain follows a stereotypical pattern that can be described by the quantification of histopathological changes in several brain regions. As part of The Seattle Alzheimer’s Disease Cell Atlas (SEA‐AD, https://sea-ad.org), we previously quantified pathological proteins in the middle temporal gyrus (MTG) and used them to describe disease progression, vulnerable cell types, and the MTG molecular changes related to diseaseMethodIn this work, we expanded our results and undertook a comparative approach. We measured a battery of neuropathological proteins (staining NeuN, AT8, IBA1, GFAP, 6e10, pTDP43, and a‐Syn immunoreactivity, and analyzing them with machine learning) in the middle temporal gyrus, the middle frontal gyrus, and medial entorhinal cortex in 84 donors. In addition, we undertook a multimodal single‐cell analysis of such regions, profiling cells using single‐cell RNA‐seq, ATAC‐seq, Multiome, and spatial transcriptomic.Borrowing from our hierarchically resolved cell types in MTG, based on the BRAIN initiative cell type reference, we used machine learning algorithms to create multimodal cell type maps across regions. We used Bayesian statistics to identify differentially accessible regulatory elements, link them to the affected genes and the regulatory transcriptional machinery binding in such elements.ResultWe identified regional vulnerable neuronal populations and a core set of transcriptionally similar cell types susceptible to disease across the cortex. We created a cortex‐wide disease progression map combining neuropathological data from our three profiled regions with latent Bayesian statistical algorithms. In each area, we developed an AD pseudo‐progression timescale that describes the burden of disease in the area and, next, combined all areas to create a cortex‐wide holistic pseudo‐progression. We used the mapped cell types and our developed scale to synchronize changes occurring in each patient, describing abundances, gene expression, and chromatin accessibility modifications.ConclusionThe progression scale developed in this study serves as a reference to align changes across brain regions and, in the future, to reconcile differences across cohorts.

Visit‐to‐visit blood pressure variability and medial temporal perfusion in APOE e4 homozygotes

AbstractBackgroundBlood pressure variability (BPV), independent of traditionally studied/targeted average blood pressure levels, is an emerging risk factor for cognitive impairment and Alzheimer’s dementia, possibly through links with cerebrovascular disease. Recent studies suggest vulnerability of the medial temporal lobes to tau accumulation and atrophy among individuals with elevated BPV, especially older APOE e4 carriers. Increased BPV has also been linked with lower cerebral blood flow (CBF) and perfusion decline in medial temporal regions, but it remains unclear how BPV and APOE e4 may interact to influence CBF. The aim of the current study was to determine whether the relationship between BPV and medial temporal lobe CBF varies by APOE e4 dose in older adults without dementia.Method105 older adults without dementia from the Alzheimer’s Disease Neuroimaging Initiative underwent 3‐4 blood pressure measurements between study baseline and 12‐months follow‐up and arterial spin labeling (ASL)‐MRI at 12‐months follow‐up or later (range: 0 – 84 months). Visit‐to‐visit BPV was calculated as variability independent of mean. CBF was determined for medial temporal regions (residualized by precentral [reference region] CBF), including hippocampus, parahippocampal gyrus, and entorhinal cortex. Venipuncture determined APOE e4 allele count (0 alleles: n = 71; 1 allele: n = 28; 2 alleles: n = 6). Multiple linear regression examined the interaction of BPV x APOE e4 dose on medial temporal CBF, controlling for age, sex, race/ethnicity, antihypertensive use, mean blood pressure, and cerebral metabolism (FDG‐PET).ResultElevated BPV was associated with lower CBF in entorhinal cortex (ß = ‐.96 [‐1.62, ‐.31]; p = .005) and parahippocampal gyrus (ß = ‐.63 [‐1.26, ‐.0002]; p = .049) in individuals with 2 APOE e4 alleles, whereas BPV was not significantly associated with CBF in these regions in individuals with 0 or 1 APOE e4 alleles (p’s > = .08). There was no significant interaction of BPV x APOE e4 dose on hippocampal CBF.ConclusionHigher BPV is associated with lower medial temporal CBF in APOE e4/e4 carriers, suggesting BPV may be an understudied vascular risk factor for those at greatest genetic risk for Alzheimer’s disease, with potential therapeutic implications.

Entorhinohippocampal cholecystokinin modulates spatial learning by facilitating neuroplasticity of hippocampal CA3-CA1 synapses

The hippocampus is broadly impacted by neuromodulations. However, how neuropeptides shape the function of the hippocampus and the related spatial learning and memory remains unclear. Here, we discover the crucial role of cholecystokinin (CCK) in heterosynaptic neuromodulation from the medial entorhinal cortex (MEC) to the hippocampus. Systematic knockout of the CCK gene impairs CA3-CA1 LTP and space-related performance. The MEC provides most of the CCK-positive neurons projecting to the hippocampal region, which potentiates CA3-CA1 long-term plasticity heterosynaptically in a frequency- and NMDA receptor (NMDAR)-dependent manner. Selective inhibition of MEC CCKergic neurons or downregulation of their CCK mRNA levels also impairs CA3-CA1 LTP formation and animals' performance in the water maze. This excitatory extrahippocampal projection releases CCK upon high-frequency excitation and is active during animal exploration. Our results reveal the critical role of entorhinal CCKergic projections in bridging intra- and extrahippocampal circuitry at electrophysiological and behavioral levels.

Spatial memory requires hypocretins to elevate medial entorhinal gamma oscillations

The hypocretin (Hcrt) (also known as orexin) neuropeptidic wakefulness-promoting system is implicated in the regulation of spatial memory, but its specific role and mechanisms remain poorly understood. In this study, we revealed the innervation of the medial entorhinal cortex (MEC) by Hcrt neurons in mice. Using the genetically encoded G-protein-coupled receptor activation-based Hcrt sensor, we observed a significant increase in Hcrt levels in the MEC during novel object-place exploration. We identified the function of Hcrt at presynaptic glutamatergic terminals, where it recruits fast-spiking parvalbumin-positive neurons and promotes gamma oscillations. Bidirectional manipulations of Hcrt neurons' projections from the lateral hypothalamus (LHHcrt) to MEC revealed the essential role of this pathway in regulating object-place memory encoding, but not recall, through the modulation of gamma oscillations. Our findings highlight the significance of the LHHcrt-MEC circuitry in supporting spatial memory and reveal a unique neural basis for the hypothalamic regulation of spatial memory.

Pattern of ventral temporal lobe interconnections in rhesus macaques.

The entorhinal cortex (EC, A28) is linked through reciprocal pathways with nearby perirhinal and visual, auditory, and multimodal association cortices in the temporal lobe, in pathways associated with the flow of information for memory processing. The density and laminar organization of these pathways is not well understood in primates. We studied interconnections within the ventral temporal lobe in young adult rhesus monkeys of both sexes with the aid of neural tracers injected in temporal areas (Ts1, Ts2, TE1, area 36, temporal polar area TPro, and area 28) to determine the density and laminar distribution of projection neurons within the temporal lobe. These temporal areas can be categorized into three different cortical types based on their laminar architecture: the sensory association areas Ts1, Ts2, and TE1 have six layers (eulaminate); the perirhinal limbic areas TPro and area 36 have an incipient layer IV (dysgranular); and area 28 lacks layer IV (agranular). We found that (1) temporal areas that are similar in laminar architecture by cortical type are strongly interconnected, and (2) the laminar pattern of connections is dependent on the difference in cortical laminar structure between linked areas. Thus, agranular A28 is more strongly connected with other agranular/dysgranular areas than with eulaminate cortices. Further, A28 predominantly projected via feedback-like pathways that originated in the deep layers, and received feedforward-like projections from areas of greater laminar differentiation, which emanated from the upper layers. Our results are consistent with the Structural Model, which relates the density and laminar distribution of connections to the relationship of the laminar structure between the linked areas. These connections were viewed in the context of the inhibitory microenvironment of A28, which is the key recipient of pathways from the cortex and of the output of hippocampus. Our findings revealed a higher population of calretinin (CR)-expressing neurons in EC, with a significantly higher density in its lateral division. Medial EC had a higher density of CR neurons in the deep layers, particularly in layer Va. In contrast, parvalbumin (PV) neurons were more densely distributed in the deep layers of the lateral subdivisions of rostral EC, especially in layer Va, whereas the densities of calbindin (CB) neurons in the medial and lateral EC were comparable in all layers, except for layer IIIa, in which medial EC had a higher CB population than the lateral. The pattern of connections in the inhibitory microenvironment of EC, which sends and receives input from the hippocampus, may shed light on signal propagation in this network associated with diverse aspects of memory, and disruptions in neurologic and psychiatric diseases that affect this region.

Memory consolidation: Building influence over the entorhinal cortex

Memory consolidation involves interactions between the hippocampus and other cortical areas. A new study identifies neurons in the medial entorhinal cortex that over learning increase their coordination with hippocampal replay events, suggesting a route for consolidation of spatial memories.

Direct cortical inputs to hippocampal area CA1 transmit complementary signals for goal-directed navigation

The subregions of the entorhinal cortex (EC) are conventionally thought to compute dichotomous representations for spatial processing, with the medial EC (MEC) providing a global spatial map and the lateral EC (LEC) encoding specific sensory details of experience. Yet, little is known about the specific types of information EC transmits downstream to the hippocampus. Here, we exploit invivo sub-cellular imaging to record from EC axons in CA1 while mice perform navigational tasks in virtual reality (VR). We uncover distinct yet overlapping representations of task, location, and context in both MEC and LEC axons. MEC transmitted highly location- and context-specific codes; LEC inputs were biased by ongoing navigational goals. However, during tasks with reliable reward locations, the animals' position could be accurately decoded from either subregion. Our results revise the prevailing dogma about EC information processing, revealing novel ways spatial and non-spatial information is routed and combined upstream of the hippocampus.

Ketamine evoked disruption of entorhinal and hippocampal spatial maps

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.

Grid cells in rats deprived of geometric experience during development

The medial entorhinal cortex (MEC) is part of the brain's network for dynamic representation of location. The most abundant class of neurons in this circuit is the grid cell, characterized by its periodic, hexagonally patterned firing fields. While in developing animals some MEC cell types express adult-like firing patterns already on the first exposure to an open spatial environment, only days after eye opening, grid cells mature more slowly, over a 1-to-2-wk period after the animals leave their nest. Whether the later emergence of a periodic grid pattern reflects a need for experience with spatial environments has not been determined. We here show that grid-like firing patterns continue to appear during exploration of open square environments in rats that are raised for the first months of their life in opaque spherical environments, in the absence of stable reference boundaries to guide spatial orientation. While strictly periodic firing fields were initially absent in these animals, clear grid patterns developed after only a few trials of training. In rats that were tested in the same open environment but raised for the first months of life in opaque cubes, with sharp vertical boundaries, grid-like firing was from the beginning indistinguishable from that of nondeprived control animals growing up in large enriched cages. Thus, although a minimum of experience with peripheral geometric boundaries is required for expression of regular grid patterns in a new environment, the effect of restricted spatial experience is overcome with short training, consistent with a preconfigured experience-independent basis for the grid pattern.

Treadmill exercise prevents the hyperexcitability of pyramidal neurons in medial entorhinal cortex in the 3xTg-AD mouse model of Alzheimer's disease

Neuronal hyperactivity is a key abnormality in early stage Alzheimer's disease (AD). Medial entorhinal cortex (mEC) plays a vital role in memory function and is affected early in AD. Growing evidence indicates benefits of regular exercise on memory and cognitive function in humans with AD, although, the underlying mechanisms are not clear. Therefore, this study was designed to test the effects of 16 weeks treadmill exercise on spatial learning memory and the underlying cellular mechanisms in 6-month-old 3xTg-AD mice. Whole-cell patch clamp was used to examine neuronal intrinsic excitability, spontaneous excitatory postsynaptic currents (sEPSCs) and spontaneous inhibitory postsynaptic currents (sIPSCs) of mEC layer II/III pyramidal neurons in the following groups: wild type (WT + sham), 3xTg-AD (AD+sham), WT receiving exercise (WT + Ex), and AD receiving exercise (AD+Ex). We found that at a behavioral level, treadmill exercise decreased working memory errors in radial arm maze (RAM) test in 6-month-old AD mice. At a cellular level, we found that treadmill exercise prevented the abnormal increase in mEC pyramidal neuron input resistance and action potential firing in 6-month-old 3xTg-AD mice compared with WT + sham and AD+Ex mice; further, sEPSC amplitude and frequency were normal in AD+Ex but overactive in AD+sham; additionally, GABAergic inhibition was normal in AD+Ex mice but reduced in AD+sham. In conclusion, our results indicate that treadmill exercise improves spatial learning memory and prevents network hyperexcitability in mEC by reducing pyramidal neuronal intrinsic excitability and normalizing excitatory and inhibitory synaptic transmission in 3xTg-AD mice.

Theta-band phase locking during encoding leads to coordinated entorhinal-hippocampal replay

Precisely timed interactions between hippocampal and cortical neurons during replay epochs are thought to support learning. Indeed, research has shown that replay is associated with heightened hippocampal-cortical synchrony. Yet many caveats remain in our understanding. Namely, it remains unclear how this offline synchrony comes about, whether it is specific to particular behavioral states, and how-if at all-it relates to learning. In this study, we sought to address these questions by analyzing coordination between CA1 cells and neurons of the deep layers of the medial entorhinal cortex (dMEC) while rats learned a novel spatial task. During movement, we found a subset of dMEC cells that were particularly locked to hippocampal LFP theta-band oscillations and that were preferentially coordinated with hippocampal replay during offline periods. Further, dMEC synchrony with CA1 replay peaked ∼10ms after replay initiation in CA1, suggesting that the distributed replay reflects extra-hippocampal information propagation and is specific to "offline" periods. Finally, theta-modulated dMEC cells showed a striking experience-dependent increase in synchronization with hippocampal replay trajectories, mirroring the animals' acquisition of the novel task and coupling to the hippocampal local field. Together, these findings provide strong support for the hypothesis that synergistic hippocampal-cortical replay supports learning and highlights phase locking to hippocampal theta oscillations as a potential mechanism by which such cross-structural synchrony comes about.

Progressive Excitability Changes in the Medial Entorhinal Cortex in the 3xTg Mouse Model of Alzheimer's Disease Pathology.

Alzheimer's disease (AD) is a chronic neurodegenerative disorder characterized by memory loss and progressive cognitive impairments. In mouse models of AD pathology, studies have found neuronal and synaptic deficits in hippocampus, but less is known about changes in medial entorhinal cortex (MEC), which is the primary spatial input to the hippocampus and an early site of AD pathology. Here, we measured neuronal intrinsic excitability and synaptic activity in MEC layer II (MECII) stellate cells, MECII pyramidal cells, and MEC layer III (MECIII) excitatory neurons at 3 and 10 months of age in the 3xTg mouse model of AD pathology, using male and female mice. At 3 months of age, before the onset of memory impairments, we found early hyperexcitability in intrinsic properties of MECII stellate and pyramidal cells, but this was balanced by a relative reduction in synaptic excitation (E) compared with inhibition (I; E/I ratio), suggesting intact homeostatic mechanisms regulating MECII activity. Conversely, MECIII neurons had reduced intrinsic excitability at this early time point with no change in synaptic E/I ratio. By 10 months of age, after the onset of memory deficits, neuronal excitability of MECII pyramidal cells and MECIII excitatory neurons was largely normalized in 3xTg mice. However, MECII stellate cells remained hyperexcitable, and this was further exacerbated by an increased synaptic E/I ratio. This observed combination of increased intrinsic and synaptic hyperexcitability suggests a breakdown in homeostatic mechanisms specifically in MECII stellate cells at this postsymptomatic time point, which may contribute to the emergence of memory deficits in AD.SIGNIFICANCE STATEMENT AD causes cognitive deficits, but the specific neural circuits that are damaged to drive changes in memory remain unknown. Using a mouse model of AD pathology that expresses both amyloid and tau transgenes, we found that neurons in the MEC have altered excitability. Before the onset of memory impairments, neurons in layer 2 of MEC had increased intrinsic excitability, but this was balanced by reduced inputs onto the cell. However, after the onset of memory impairments, stellate cells in MEC became further hyperexcitable, with increased excitability exacerbated by increased synaptic inputs. Thus, it appears that MEC stellate cells are uniquely disrupted during the progression of memory deficits and may contribute to cognitive deficits in AD.

Memristive Neural Networks for Predicting Seizure Activity.

The biological part of the investigation. Young healthy outbred CD1 mice were used in our study. They were divided into two groups: control (n=6) and the group with induced chronic epileptiform activity (n=6). Local field potentials (LFP) were recorded from the hippocampus and medial entorhinal cortex of the mice of both groups to register neuronal activity. The LFP recordings were used for deep ANN training. Epileptiform activity in mice was modeled by intraperitoneal injection of pilocarpine (280 mg/kg). LFP were recorded in the awake mice a month after the induction of epileptiform activity.Mathematical part of the investigation. A deep long short-term memory (LSTM) ANN capable of predicting biological signals of neuronal activity in mice has been developed. The ANN implementation is based on memristive devices, which are described by the equations of the redox processes running in the memristive thin metal-oxide-metal films, e.g., Au/ZrO2(Y)/TiN/Ti and Au/SiO2(Y)/TiN/Ti. In order to train the developed ANN to predict epileptiform activity, a supervised learning algorithm was used, which allowed us to adjust the network parameters and train LSTM on the described recordings of neuronal activity. After training on the LFP recordings from the hippocampus and medial entorhinal cortex of the mice with chronic epileptiform activity, the proposed deep ANN has demonstrated high values of evaluation metric (root-mean-square error, RMSE) and successfully predicted epileptiform activity shortly before its occurrence (40 ms). The results of the numerical experiments have shown that the RMSE value of 0.019 was reached, which indicates the efficacy of proposed approach. The accuracy of epileptiform activity prediction 40 ms before its occurrence is a significant result and shows the potential of the developed neural network architecture. The proposed deep ANN can be used to predict pathological neuronal activity including epileptic seizure (focal) activity in mice before its actual occurrence. Besides, it can be applied for building a long-term prognosis of the disease course based on the LFP data. Thus, the proposed ANN based on memristive devices represents a novel approach to the prediction and analysis of pathological neuronal activity possessing a potential for improving the diagnosis and prognostication of epileptic seizures and other diseases associated with neuronal activity.