Synaptic Integration of Entorhinal Cortical Inputs to Dentate Gyrus Granule Cells: A Multiscale Computational Model for Investigating Hippocampal Response to Electrical Stimulation

2025-07-13

Recent advancements in neuroprosthetic systems and brain-computer interfaces present significant potential for recording and electrically stimulating the hippocampus, a brain region that is critical for the formation of long-term memory, thereby offering new opportunities for understanding its role, but also modulate and possibly enhance and restore its function. However, these advances are accompanied by considerable challenges due to the intricate architecture of neural tissue and the incomplete understanding of how electrical stimulation interacts with the hippocampal network. To address these challenges, we have developed a detailed computational model based on a rat hippocampal network that replicates its intricate architecture and integrates electrical stimulation via simulated neighboring electrodes.

A hybrid meta-FEM approach for numerical computation of wear parameters

2025-01-29

Due to the interlocking of asperities, rubber friction is a dissipative process that converts mechanical energy into heat and produces material wear. Furthermore, wear is the loss of material under the frictional sliding of two bodies against each other. The wear parameters calibrated by using Linear Friction Tester (LFT) experiments lead to an overestimation of wear when used in Laboratory Abrasion & Skid Tester 100 (LAT100) simulations. Furthermore, calibration of wear parameters by LAT100 experiment uses assumptions regarding the contact area and slip velocity which cannot be measured directly. Therefore, numerical calibration can be one way to obtain reliable wear parameters. To numerically calibrate the wear parameters, a hybrid meta-finite element method (FEM) approach is developed. For the FEM representation of the LAT100 experiment, a steady state rolling framework is adopted and an arbitrary LAGRANGIAN-EULERIAN(ALE) adaptive meshing procedure is used for wear calculation. Due to the mesh dependency of the ALE adaptive meshing, a failure surface algorithm is developed. The workflow is composed of a loop of three main steps. First, an initial set of wear parameters is identified by the minimization algorithm. Next, the failure surface algorithm decides if these wear parameters are passed to the FEM or the meta-model. Finally, the FEM or the meta-model predicts the wear mass, and a new iteration is started from step one. The loop ends once optimal wear parameters are found. Both approaches are able to predict the amount of wear of the LAT100 with a similar accuracy.

Distributed Temporal Coding of Visual Memory Categories in Human Hippocampal Neurons Revealed by an Interpretable Decoding Model

Advanced Science · 2025-07-08 · 2 citations

The hippocampus is crucial for forming new episodic memories. While its role in encoding spatial and temporal information (where and when) is well understood, how it encodes objects (what) remains unclear due to the high dimensionality of object space. Rather than encoding each object separately, the hippocampus may encode object categories to reduce complexity. Here, an experimental-modeling approach to investigate how the hippocampus encodes visual memory categories in humans is developed. Spikes are recorded from hippocampal CA3 and CA1 neurons in 24 epilepsy patients performing a delayed match-to-sample task involving five image categories. An interpretable memory decoding model is employed to decode memory categories from hippocampal spiking activity and identify the spatio-temporal characteristics of hippocampal encoding. Using this model, the optimal temporal resolutions for decoding each visual memory category per neuron are estimated. Results indicate that visual memory categories can be decoded from hippocampal spike patterns, supporting the presence of category-specific coding. Hippocampal neuron ensembles encode memory categories in a distributed manner, akin to a population code, while individual neurons use a temporal code. Additionally, CA3 and CA1 neurons exhibit similar and redundant memory category information, likely due to strong and diffuse feedforward synaptic connections from CA3 to CA1 regions.

Development of Macrocyclic Peptide-Based Proteasome Inhibitors with Enhanced Blood-Brain Barrier Penetration for Treating Brain Neoplasms

Journal of Medicinal Chemistry · 2025-09-08 · 2 citations

Proteasome inhibitors are effective in treating hematologic cancers but have limited utility in brain tumors due to poor blood–brain barrier (BBB) penetration and metabolic instability. In this study, we developed novel macrocyclic peptide epoxyketone inhibitors with improved drug-like properties. Compounds were screened for cytotoxicity against brain cancer cell lines, permeability (PAMPA-BBB and Caco-2), and metabolic stability. Lead compound 10 demonstrated potent in vitro activity (IC50 < 100 nM), low P-gp efflux, and favorable microsomal and plasma stability. In vivo pharmacokinetic studies in mice showed that compound 10 maintained therapeutic plasma levels and achieved measurable brain concentrations without toxicity. Co-administration of a P-gp inhibitor significantly enhanced brain exposure of compound 35, confirming efflux as a key parameter. The incorporation of fluorinated phenyl and α,α-dimethylglycine moieties contributed to improved BBB permeability and metabolic stability. These findings support further development of macrocyclic epoxyketone inhibitors as promising candidates for brain cancer therapy.

Distributed Temporal Coding of Visual Memory Categories in Human Hippocampal Neurons

Research Square · 2024-11-26

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall of stimulus features and categories

Frontiers in Computational Neuroscience · 2024-02-08 · 15 citations

Objective: Here, we demonstrate the first successful use of static neural stimulation patterns for specific information content. These static patterns were derived by a model that was applied to a subject's own hippocampal spatiotemporal neural codes for memory. Approach: We constructed a new model of processes by which the hippocampus encodes specific memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of targeted content into short-term memory. A memory decoding model (MDM) of hippocampal CA3 and CA1 neural firing was computed which derives a stimulation pattern for CA1 and CA3 neurons to be applied during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results: MDM electrical stimulation delivered to the CA1 and CA3 locations in the hippocampus during the sample phase of DMS trials facilitated memory of images from the DMS task during a delayed recognition (DR) task that also included control images that were not from the DMS task. Across all subjects, the stimulated trials exhibited significant changes in performance in 22.4% of patient and category combinations. Changes in performance were a combination of both increased memory performance and decreased memory performance, with increases in performance occurring at almost 2 to 1 relative to decreases in performance. Across patients with impaired memory that received bilateral stimulation, significant changes in over 37.9% of patient and category combinations was seen with the changes in memory performance show a ratio of increased to decreased performance of over 4 to 1. Modification of memory performance was dependent on whether memory function was intact or impaired, and if stimulation was applied bilaterally or unilaterally, with nearly all increase in performance seen in subjects with impaired memory receiving bilateral stimulation. Significance: These results demonstrate that memory encoding in patients with impaired memory function can be facilitated for specific memory content, which offers a stimulation method for a future implantable neural prosthetic to improve human memory.

Patterned Hippocampal Stimulation Facilitates Memory in Patients With a History of Head Impact and/or Brain Injury

Frontiers in Human Neuroscience · 2022-07-25 · 11 citations

Rationale: Deep brain stimulation (DBS) of the hippocampus is proposed for enhancement of memory impaired by injury or disease. Many pre-clinical DBS paradigms can be addressed in epilepsy patients undergoing intracranial monitoring for seizure localization, since they already have electrodes implanted in brain areas of interest. Even though epilepsy is usually not a memory disorder targeted by DBS, the studies can nevertheless model other memory-impacting disorders, such as Traumatic Brain Injury (TBI). Methods: Human patients undergoing Phase II invasive monitoring for intractable epilepsy were implanted with depth electrodes capable of recording neurophysiological signals. Subjects performed a delayed-match-to-sample (DMS) memory task while hippocampal ensembles from CA1 and CA3 cell layers were recorded to estimate a multi-input, multi-output (MIMO) model of CA3-to-CA1 neural encoding and a memory decoding model (MDM) to decode memory information from CA3 and CA1 neuronal signals. After model estimation, subjects again performed the DMS task while either MIMO-based or MDM-based patterned stimulation was delivered to CA1 electrode sites during the encoding phase of the DMS trials. Each subject was sorted ( post hoc ) by prior experience of repeated and/or mild-to-moderate brain injury (RMBI), TBI, or no history (control) and scored for percentage successful delayed recognition (DR) recall on stimulated vs. non-stimulated DMS trials. The subject’s medical history was unknown to the experimenters until after individual subject memory retention results were scored. Results: When examined compared to control subjects, both TBI and RMBI subjects showed increased memory retention in response to both MIMO and MDM-based hippocampal stimulation. Furthermore, effects of stimulation were also greater in subjects who were evaluated as having pre-existing mild-to-moderate memory impairment. Conclusion: These results show that hippocampal stimulation for memory facilitation was more beneficial for subjects who had previously suffered a brain injury (other than epilepsy), compared to control (epilepsy) subjects who had not suffered a brain injury. This study demonstrates that the epilepsy/intracranial recording model can be extended to test the ability of DBS to restore memory function in subjects who previously suffered a brain injury other than epilepsy, and support further investigation into the beneficial effect of DBS in TBI patients.

Altered adult neurogenesis and gliogenesis in patients with mesial temporal lobe epilepsy

Nature Neuroscience · 2022 · 103 citations

• Neuroscience
• Psychology
• Biology

Corrigendum: Patterned hippocampal stimulation facilitates memory in patients with a history of head impact and/or brain injury

Frontiers in Human Neuroscience · 2022-10-06

Corrigendum: Patterned Hippocampal Stimulation Facilitates Memory in Patients With a History of Head Impact and/or Brain InjuryName of all authors as they appear in the published original article Brent M. Roeder1‡, Mitchell R. Riley1‡, Xiwei She2, Alexander S. Dakos1†, Brian S. Robinson2†, Bryan J. Moore2, Daniel E. Couture3, Adrian W. Laxton3, Gautam Popli4, Heidi M. Munger Clary4, Maria Sam4, Christi Heck5, George Nune5, Brian Lee6, Charles Liu6, Susan Shaw7, Hui Gong7, Vasilis Z. Marmarelis2, Theodore W. Berger2, Sam A. Deadwyler1, Dong Song2§ and Robert E. Hampson1,4*§Keywords: deep brain stimulation, hippocampus, memory, non-linear dynamics, traumatic brain injury, epilepsy, memory encoding, memory decodingCorrigendum on: https://www.frontiersin.org/articles/10.3389/fnhum.2022.933401/fullIncorrect Author NameIn the published article, an author name was incorrectly written as Heidi M. Clary. The correct spelling is Heidi M. Munger Clary. In the published article, there was an error in the author contributions. Heidi M. Munger Clary's initials were provided as HC. The correct initials are HMMC.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Accelerating input-output model estimation with parallel computing for testing hippocampal memory prostheses in human

Journal of Neuroscience Methods · 2022-01-31 · 10 citations