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

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.

Activation of primate frontal eye fields with a CMUT phased array system.

BACKGROUND: There are pushes toward non-invasive stimulation of neural tissues to prevent issues that arise from invasive brain recordings and stimulation. Transcranial Focused Ultrasound (TFUS) has been examined as a way to stimulate non-invasively, but previous studies have limitations in the application of TFUS. As a result, refinement is needed to improve stimulation results. NEW METHOD: We utilized a custom-built capacitive micromachined ultrasonic transducer (CMUT) that would send ultrasonic waves through skin and skull to targets located in the Frontal Eye Fields (FEF) region triangulated from co-registered MRI and CT scans while a non-human primate subject was performing a discrimination behavioral task. RESULTS: We observed that the stimulation immediately caused changes in the local field potential (LFP) signal that continued until stimulation ended, at which point there was higher voltage upon the cue for the animal to saccade. This co-incided with increases in activity in the alpha band during stimulation. The activity rebounded mid-way through our electrode-shank, indicating a specific point of stimulation along the shank. We observed different LFP signals for different stimulation targets, indicating the ability to"steer" the stimulation through the transducer. We also observed a bias in first saccades towards the opposite direction. CONCLUSIONS: In conclusion, we provide a new approach for non-invasive stimulation during performance of a behavioral task. With the ability to steer stimulation patterns and target using a large amount of transducers, the ability to provide non-invasive stimulation will be greatly improved for future clinical and research applications.

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

[This corrects the article DOI: 10.3389/fnhum.2022.933401.].

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

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.

Hippocampal CA1 and CA3 neural recording in the human brain: validation of depth electrode placement through high-resolution imaging and electrophysiology.

OBJECTIVE: Intracranial human brain recordings typically utilize recording systems that do not distinguish individual neuron action potentials. In such cases, individual neurons are not identified by location within functional circuits. In this paper, verified localization of singly recorded hippocampal neurons within the CA3 and CA1 cell fields is demonstrated. METHODS: Macro-micro depth electrodes were implanted in 23 human patients undergoing invasive monitoring for identification of epileptic seizure foci. Individual neurons were isolated and identified via extracellular action potential waveforms recorded via macro-micro depth electrodes localized within the hippocampus. A morphometric survey was performed using 3T MRI scans of hippocampi from the 23 implanted patients, as well as 46 normal (i.e., nonepileptic) patients and 26 patients with a history of epilepsy but no history of depth electrode placement, which provided average dimensions of the hippocampus along typical implantation tracks. Localization within CA3 and CA1 cell fields was tentatively assigned on the basis of recording electrode site, stereotactic positioning of the depth electrode in comparison with the morphometric survey, and postsurgical MRI. Cells were selected as candidate CA3 and CA1 principal neurons on the basis of waveform and firing rate characteristics and confirmed within the CA3-to-CA1 neural projection pathways via measures of functional connectivity. RESULTS: Cross-correlation analysis confirmed that nearly 80% of putative CA3-to-CA1 cell pairs exhibited positive correlations compatible with feed-forward connection between the cells, while only 2.6% exhibited feedback (inverse) connectivity. Even though synchronous and long-latency correlations were excluded, feed-forward correlation between CA3-CA1 pairs was identified in 1071 (26%) of 4070 total pairs, which favorably compares to reports of 20%-25% feed-forward CA3-CA1 correlation noted in published animal studies. CONCLUSIONS: This study demonstrates the ability to record neurons in vivo from specified regions and subfields of the human brain. As brain-machine interface and neural prosthetic research continues to expand, it is necessary to be able to identify recording and stimulation sites within neural circuits of interest.

Multi-Input, Multi-Output Neuronal Mode Network Approach to Modeling the Encoding Dynamics and Functional Connectivity of Neural Systems.

This letter proposes a novel method, multi-input, multi-output neuronal mode network (MIMO-NMN), for modeling encoding dynamics and functional connectivity in neural ensembles such as the hippocampus. Compared with conventional approaches such as the Volterra-Wiener model, linear-nonlinear-cascade (LNC) model, and generalized linear model (GLM), the NMN has several advantages in terms of estimation accuracy, model interpretation, and functional connectivity analysis. We point out the limitations of current neural spike modeling methods, especially the estimation biases caused by the imbalanced class problem when the number of zeros is significantly larger than ones in the spike data. We use synthetic data to test the performance of NMN with a comparison of the traditional methods, and the results indicate the NMN approach could reduce the imbalanced class problem and achieve better predictions. Subsequently, we apply the MIMO-NMN method to analyze data from the human hippocampus. The results indicate that the MIMO-NMN method is a promising approach to modeling neural dynamics and analyzing functional connectivity of multi-neuronal data.

Systemic Blockade of the CB1 Receptor Augments Hippocampal Gene Expression Involved in Synaptic Plasticity but Perturbs Hippocampus-Dependent Learning Task.

Chronic and acute agonism as well as acute antagonism of CB1 receptors reveal modulation of learning and memory during stable performance of a delayed-nonmatch-to-sample (DNMS) memory task. However, it remains unclear how chronic blockade of the CB1 receptor alters acquisition of the behavioral task. We examined the effects of chronic rimonabant exposure during DNMS task acquisition to determine if blockade of the CB1 receptor with the antagonist rimonabant enhanced acquisition of operant task. Long-Evans rats, trained in the DNMS task before imposition of the trial delay, were surgically implanted with osmotic mini pumps to administer rimonabant (1.0 mg/kg/day) or vehicle (dimethyl sulfoxide/Tween-80/Saline). Following surgical recovery, DNMS training was resumed with the imposition of gradually longer delays (1-30 sec). The number of days required to achieve stable performance with either increasing length of delay or reversal of task contingency was compared between vehicle and rimonabant-treated rats. Following the completion of DNMS training, animals were euthanized, and both hippocampi were harvested for gene expression assay analysis. Rimonabant treatment animals required more time to achieve stable DNMS performance than vehicle-treated controls. Quantitative real-time polymerase chain reaction analysis revealed that the expressions of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor subunit, brain-derived neurotrophic factor, and synapsin 1 (Syn1) were significantly increased. These results are consistent with rimonabant increasing mRNAs for proteins associated with hippocampal synapse remodeling, but that those alterations did not necessarily accelerate the acquisition of an operant behavioral task that required learning new contingencies.

White Matter is the Predilection Site of Late-Delayed Radiation-Induced Brain Injury in Non-Human Primates.

Fractionated whole-brain irradiation for the treatment of intracranial neoplasia causes progressive neurodegeneration and neuroinflammation. The long-term consequences of single-fraction high-dose irradiation to the brain are unknown. To assess the late effects of brain irradiation we compared transcriptomic gene expression profiles from nonhuman primates (NHP; rhesus macaques Macaca mulatta) receiving single-fraction total-body irradiation (TBI; n = 5, 6.75-8.05 Gy, 6-9 years prior to necropsy) to those receiving fractionated whole-brain irradiation (fWBI; n = 5, 40 Gy, 8 × 5 Gy fractions; 12 months prior to necropsy) and control comparators (n = 5). Gene expression profiles from the dorsolateral prefrontal cortex (DLPFC), hippocampus (HC) and deep white matter (WM; centrum semiovale) were compared. Stratified analyses by treatment and region revealed that radiation-induced transcriptomic alterations were most prominent in animals receiving fWBI, and primarily affected white matter in both TBI and fWBI groups. Unsupervised canonical and ontologic analysis revealed that TBI or fWBI animals demonstrated shared patterns of injury, including white matter neuroinflammation, increased expression of complement factors and T-cell activation. Both irradiated groups also showed evidence of impaired glutamatergic neurotransmission and signal transduction within white matter, but not within the dorsolateral prefrontal cortex or hippocampus. Signaling pathways and structural elements involved in extracellular matrix (ECM) deposition and remodeling were noted within the white matter of animals receiving fWBI, but not of those receiving TBI. These findings indicate that those animals receiving TBI are susceptible to neurological injury similar to that observed after fWBI, and these changes persist for years postirradiation. Transcriptomic profiling reaffirmed that macrophage/microglial-mediated neuroinflammation is present in radiation-induced brain injury (RIBI), and our data provide novel evidence that the complement system may contribute to the pathogenesis of RIBI. Finally, these data challenge the assumption that the hippocampus is the predilection site of injury in RIBI, and indicate that impaired glutamatergic neurotransmission may occur in white matter injury.

Fibronectin Produced by Cerebral Endothelial and Vascular Smooth Muscle Cells Contributes to Perivascular Extracellular Matrix in Late-Delayed Radiation-Induced Brain Injury.

Late-delayed radiation-induced brain injury (RIBI) is a major adverse effect of fractionated whole-brain irradiation (fWBI). Characterized by progressive cognitive dysfunction, and associated cerebrovascular and white matter injury, RIBI deleteriously affects quality of life for cancer patients. Despite extensive morphological characterization of the injury, the pathogenesis is unclear, thus limiting the development of effective therapeutics. We previously reported that RIBI is associated with increased gene expression of the extracellular matrix (ECM) protein fibronectin (FN1). We hypothesized that fibronectin contributes to perivascular ECM, which may impair diffusion to the dependent parenchyma, thus contributing to the observed cognitive decline. The goal of this study was to determine the localization of fibronectin in RIBI and further characterize the composition of perivascular ECM, as well as identify the cell of origin for FN1 by in situ hybridization. Briefly, fibronectin localized to the vascular basement membrane of morphologically normal blood vessels from control comparators and animals receiving fWBI, and to the perivascular space of edematous and fibrotic vascular phenotypes of animals receiving fWBI. Additional mild diffuse parenchymal staining in areas of vascular injury suggested blood-brain-barrier disruption and plasma fibronectin extravasation. Perivascular ECM lacked amyloid and contained lesser amounts of collagens I and IV, which localized to the basement membrane. These changes occurred in the absence of alterations in microvascular area fraction or microvessel density. Fibronectin transcripts were rarely expressed in control comparators, and were most strongly induced within cerebrovascular endothelial and vascular smooth muscle cells after fWBI. Our results demonstrate that fibronectin is produced by cerebrovascular endothelial and smooth muscle cells in late-delayed RIBI and contributes to perivascular ECM, which we postulate may contribute to diffusion barrier formation. We propose that pathways that antagonize fibronectin deposition and matrix assembly or enhance degradation may serve as potential therapeutic targets in RIBI.

Designing Patient-Specific Optimal Neurostimulation Patterns for Seizure Suppression.

Neurostimulation is a promising therapy for abating epileptic seizures. However, it is extremely difficult to identify optimal stimulation patterns experimentally. In this study, human recordings are used to develop a functional 24 neuron network statistical model of hippocampal connectivity and dynamics. Spontaneous seizure-like activity is induced in silico in this reconstructed neuronal network. The network is then used as a testbed to design and validate a wide range of neurostimulation patterns. Commonly used periodic trains were not able to permanently abate seizures at any frequency. A simulated annealing global optimization algorithm was then used to identify an optimal stimulation pattern, which successfully abated 92% of seizures. Finally, in a fully responsive, or closed-loop, neurostimulation paradigm, the optimal stimulation successfully prevented the network from entering the seizure state. We propose that the framework presented here for algorithmically identifying patient-specific neurostimulation patterns can greatly increase the efficacy of neurostimulation devices for seizures.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall.

OBJECTIVE: We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient's own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. APPROACH: We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. MAIN RESULTS: MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. SIGNIFICANCE: These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

Sparse Large-Scale Nonlinear Dynamical Modeling of Human Hippocampus for Memory Prostheses.

In order to build hippocampal prostheses for restoring memory functions, we build sparse multi-input, multi-output (MIMO) nonlinear dynamical models of the human hippocampus. Spike trains are recorded from hippocampal CA3 and CA1 regions of epileptic patients performing a variety of memory-dependent delayed match-to-sample (DMS) tasks. Using CA3 and CA1 spike trains as inputs and outputs respectively, sparse generalized Laguerre-Volterra models are estimated with group lasso and local coordinate descent methods to capture the nonlinear dynamics underlying the CA3-CA1 spike train transformations. These models can accurately predict the CA1 spike trains based on the ongoing CA3 spike trains during multiple memory events, e.g., sample presentation, sample response, match presentation and match response, of the DMS task, and thus will serve as the computational basis of human hippocampal memory prostheses.

Mechanism-Based and Input-Output Modeling of the Key Neuronal Connections and Signal Transformations in the CA3-CA1 Regions of the Hippocampus.

This letter examines the results of input-output (nonparametric) modeling based on the analysis of data generated by a mechanism-based (parametric) model of CA3-CA1 neuronal connections in the hippocampus. The motivation is to obtain biological insight into the interpretation of such input-output (Volterra-equivalent) models estimated from synthetic data. The insights obtained may be subsequently used to interpretat input-output models extracted from actual experimental data. Specifically, we found that a simplified parametric model may serve as a useful tool to study the signal transformations in the hippocampal CA3-CA1 regions. Input-output modeling of model-based synthetic data show that GABAergic interneurons are responsible for regulating neuronal excitation, controlling the precision of spike timing, and maintaining network oscillations, in a manner consistent with previous studies. The input-output model obtained from real data exhibits intriguing similarities with its synthetic-data counterpart, demonstrating the importance of a dynamic resonance in the system/model response around 2 Hz to 3 Hz. Using the input-output model from real data as a guide, we may be able to amend the parametric model by incorporating more mechanisms in order to yield better-matching input-output model. The approach we present can also be applied to the study of other neural systems and pathways.

Multi-resolution multi-trial sparse classification model for decoding visual memories from hippocampal spikes in human.

To understand how memories are encoded in the hippocampus, we build memory decoding models to classify visual memories based on hippocampal activities in human. Model inputs are spatio-temporal patterns of spikes recorded in the hippocampal CA3 and CA1 regions of epilepsy patients performing a delayed match-to-sample (DMS) task. Model outputs are binary labels indicating categories and features of sample images. To solve the super high-dimensional estimation problem with short data length, we develop a multi-trial, sparse model estimation method utilizing B-spline basis functions with a large range of temporal resolutions and a regularized logistic classifier. Results show that this model can effectively avoid overfitting and provide significant amount of prediction to memory categories and features using very limited number of data points. Stable estimation of sparse classification function matrices for each label can be obtained with this multi-resolution, multi-trial procedure. These classification models can be used not only to predict memory contents, but also to design optimal spatio-temporal patterns for eliciting specific memories in the hippocampus, and thus have important implications to the development of hippocampal memory prostheses.

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3.

Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs.

Cerebrovascular Remodeling and Neuroinflammation is a Late Effect of Radiation-Induced Brain Injury in Non-Human Primates.

Fractionated whole-brain irradiation (fWBI) is a mainstay of treatment for patients with intracranial neoplasia; however late-delayed radiation-induced normal tissue injury remains a major adverse consequence of treatment, with deleterious effects on quality of life for affected patients. We hypothesize that cerebrovascular injury and remodeling after fWBI results in ischemic injury to dependent white matter, which contributes to the observed cognitive dysfunction. To evaluate molecular effectors of radiation-induced brain injury (RIBI), real-time quantitative polymerase chain reaction (RT-qPCR) was performed on the dorsolateral prefrontal cortex (DLPFC, Brodmann area 46), hippocampus and temporal white matter of 4 male Rhesus macaques (age 6-11 years), which had received 40 Gray (Gy) fWBI (8 fractions of 5 Gy each, twice per week), and 3 control comparators. All fWBI animals developed neurologic impairment; humane euthanasia was elected at a median of 6 months. Radiation-induced brain injury was confirmed histopathologically in all animals, characterized by white matter degeneration and necrosis, and multifocal cerebrovascular injury consisting of perivascular edema, abnormal angiogenesis and perivascular extracellular matrix deposition. Herein we demonstrate that RIBI is associated with white matter-specific up-regulation of hypoxia-associated lactate dehydrogenase A (LDHA) and that increased gene expression of fibronectin 1 (FN1), SERPINE1 and matrix metalloprotease 2 (MMP2) may contribute to cerebrovascular remodeling in late-delayed RIBI. Additionally, vascular stability and maturation associated tumor necrosis super family member 15 (TNFSF15) and vascular endothelial growth factor beta (VEGFB) mRNAs were increased within temporal white matter. We also demonstrate that radiation-induced brain injury is associated with decreases in white matter-specific expression of neurotransmitter receptors SYP, GRIN2A and GRIA4. We additionally provide evidence that macrophage/microglial mediated neuroinflammation may contribute to RIBI through increased gene expression of the macrophage chemoattractant CCL2 and macrophage/microglia associated CD68. Global patterns in cerebral gene expression varied significantly between regions examined (P < 0.0001, Friedman's test), with effects most prominent within cerebral white matter.

Evolving Applications, Technological Challenges and Future Opportunities in Neuromodulation: Proceedings of the Fifth Annual Deep Brain Stimulation Think Tank.

The annual Deep Brain Stimulation (DBS) Think Tank provides a focal opportunity for a multidisciplinary ensemble of experts in the field of neuromodulation to discuss advancements and forthcoming opportunities and challenges in the field. The proceedings of the fifth Think Tank summarize progress in neuromodulation neurotechnology and techniques for the treatment of a range of neuropsychiatric conditions including Parkinson's disease, dystonia, essential tremor, Tourette syndrome, obsessive compulsive disorder, epilepsy and cognitive, and motor disorders. Each section of this overview of the meeting provides insight to the critical elements of discussion, current challenges, and identified future directions of scientific and technological development and application. The report addresses key issues in developing, and emphasizes major innovations that have occurred during the past year. Specifically, this year's meeting focused on technical developments in DBS, design considerations for DBS electrodes, improved sensors, neuronal signal processing, advancements in development and uses of responsive DBS (closed-loop systems), updates on National Institutes of Health and DARPA DBS programs of the BRAIN initiative, and neuroethical and policy issues arising in and from DBS research and applications in practice.

The relationship between nernst equilibrium variability and the multifractality of interspike intervals in the hippocampus.

Spatiotemporal patterns of action potentials are considered to be closely related to information processing in the brain. Auto-generating neurons contributing to these processing tasks are known to cause multifractal behavior in the inter-spike intervals of the output action potentials. In this paper we define a novel relationship between this multifractality and the adaptive Nernst equilibrium in hippocampal neurons. Using this relationship we are able to differentiate between various drugs at varying dosages. Conventional methods limit their ability to account for cellular charge depletion by not including these adaptive Nernst equilibria. Our results provide a new theoretical approach for measuring the effects which drugs have on single-cell dynamics.

A cognitive prosthesis for memory facilitation by closed-loop functional ensemble stimulation of hippocampal neurons in primate brain.

Very productive collaborative investigations characterized how multineuron hippocampal ensembles recorded in nonhuman primates (NHPs) encode short-term memory necessary for successful performance in a delayed match to sample (DMS) task and utilized that information to devise a unique nonlinear multi-input multi-output (MIMO) memory prosthesis device to enhance short-term memory in real-time during task performance. Investigations have characterized how the hippocampus in primate brain encodes information in a multi-item, rule-controlled, delayed match to sample (DMS) task. The MIMO model was applied via closed loop feedback micro-current stimulation during the task via conformal electrode arrays and enhanced performance of the complex memory requirements. These findings clearly indicate detection of a means by which the hippocampus encodes information and transmits this information to other brain regions involved in memory processing. By employing the nonlinear dynamic multi-input/multi-output (MIMO) model, developed and adapted to hippocampal neural ensemble firing patterns derived from simultaneous recorded multi-neuron CA1 and CA3 activity, it was possible to extract information encoded in the Sample phase of DMS trials that was necessary for successful performance in the subsequent Match phase of the task. The extension of this MIMO model to online delivery of electrical stimulation patterns to the same recording loci that exhibited successful CA1 firing in the DMS Sample Phase provided the means to increase task performance on a trial-by-trial basis. Increased utility of the MIMO model as a memory prosthesis was exhibited by the demonstration of cumulative increases in DMS task performance with repeated MIMO stimulation over many sessions. These results, reported below in this article, provide the necessary demonstrations to further the feasibility of the MIMO model as a memory prosthesis to recover and/or enhance encoding of cognitive information in humans with memory disruptions resulting from brain injury, disease or aging.

Decoding memory features from hippocampal spiking activities using sparse classification models.

To understand how memory information is encoded in the hippocampus, we build classification models to decode memory features from hippocampal CA3 and CA1 spatio-temporal patterns of spikes recorded from epilepsy patients performing a memory-dependent delayed match-to-sample task. The classification model consists of a set of B-spline basis functions for extracting memory features from the spike patterns, and a sparse logistic regression classifier for generating binary categorical output of memory features. Results show that classification models can extract significant amount of memory information with respects to types of memory tasks and categories of sample images used in the task, despite the high level of variability in prediction accuracy due to the small sample size. These results support the hypothesis that memories are encoded in the hippocampal activities and have important implication to the development of hippocampal memory prostheses.