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.

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.

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.

Model-based asessment of an in-vivo predictive relationship from CA1 to CA3 in the rodent hippocampus.

Although an anatomical connection from CA1 to CA3 via the Entorhinal Cortex (EC) and through backprojecting interneurons has long been known it exist, it has never been examined quantitatively on the single neuron level, in the in-vivo nonpatholgical, nonperturbed brain. Here, single spike activity was recorded using a multi-electrode array from the CA3 and CA1 areas of the rodent hippocampus (N = 7) during a behavioral task. The predictive power from CA3→CA1 and CA1→CA3 was examined by constructing Multivariate Autoregressive (MVAR) models from recorded neurons in both directions. All nonsignificant inputs and models were identified and removed by means of Monte Carlo simulation methods. It was found that 121/166 (73 %) CA3→CA1 models and 96/145 (66 %) CA1→CA3 models had significant predictive power, thus confirming a predictive 'Granger' causal relationship from CA1 to CA3. This relationship is thought to be caused by a combination of truly causal connections such as the CA1→EC→CA3 pathway and common inputs such as those from the Septum. All MVAR models were then examined in the frequency domain and it was found that CA3 kernels had significantly more power in the theta and beta range than those of CA1, confirming CA3's role as an endogenous hippocampal pacemaker.

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.

Nonlinear modeling of dynamic interactions within neuronal ensembles using Principal Dynamic Modes.

A methodology for nonlinear modeling of multi-input multi-output (MIMO) neuronal systems is presented that utilizes the concept of Principal Dynamic Modes (PDM). The efficacy of this new methodology is demonstrated in the study of the dynamic interactions between neuronal ensembles in the Pre-Frontal Cortex (PFC) of a behaving non-human primate (NHP) performing a Delayed Match-to-Sample task. Recorded spike trains from Layer-2 and Layer-5 neurons were viewed as the "inputs" and "outputs", respectively, of a putative MIMO system/model that quantifies the dynamic transformation of multi-unit neuronal activity between Layer-2 and Layer-5 of the PFC. Model prediction performance was evaluated by means of computed Receiver Operating Characteristic (ROC) curves. The PDM-based approach seeks to reduce the complexity of MIMO models of neuronal ensembles in order to enable the practicable modeling of large-scale neural systems incorporating hundreds or thousands of neurons, which is emerging as a preeminent issue in the study of neural function. The "scaling-up" issue has attained critical importance as multi-electrode recordings are increasingly used to probe neural systems and advance our understanding of integrated neural function. The initial results indicate that the PDM-based modeling methodology may greatly reduce the complexity of the MIMO model without significant degradation of performance. Furthermore, the PDM-based approach offers the prospect of improved biological/physiological interpretation of the obtained MIMO models.

Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions.

One key problem in computational neuroscience and neural engineering is the identification and modeling of functional connectivity in the brain using spike train data. To reduce model complexity, alleviate overfitting, and thus facilitate model interpretation, sparse representation and estimation of functional connectivity is needed. Sparsities include global sparsity, which captures the sparse connectivities between neurons, and local sparsity, which reflects the active temporal ranges of the input-output dynamical interactions. In this paper, we formulate a generalized functional additive model (GFAM) and develop the associated penalized likelihood estimation methods for such a modeling problem. A GFAM consists of a set of basis functions convolving the input signals, and a link function generating the firing probability of the output neuron from the summation of the convolutions weighted by the sought model coefficients. Model sparsities are achieved by using various penalized likelihood estimations and basis functions. Specifically, we introduce two variations of the GFAM using a global basis (e.g., Laguerre basis) and group LASSO estimation, and a local basis (e.g., B-spline basis) and group bridge estimation, respectively. We further develop an optimization method based on quadratic approximation of the likelihood function for the estimation of these models. Simulation and experimental results show that both group-LASSO-Laguerre and group-bridge-B-spline can capture faithfully the global sparsities, while the latter can replicate accurately and simultaneously both global and local sparsities. The sparse models outperform the full models estimated with the standard maximum likelihood method in out-of-sample predictions.

Columnar processing in primate pFC: evidence for executive control microcircuits.

A common denominator for many cognitive disorders of human brain is the disruption of neural activity within pFC, whose structural basis is primarily interlaminar (columnar) microcircuits or "minicolumns." The importance of this brain region for executive decision-making has been well documented; however, because of technological constraints, the minicolumnar basis is not well understood. Here, via implementation of a unique conformal multielectrode recording array, the role of interlaminar pFC minicolumns in the executive control of task-related target selection is demonstrated in nonhuman primates performing a visuomotor DMS task. The results reveal target-specific, interlaminar correlated firing during the decision phase of the trial between multielectrode recording array-isolated minicolumnar pairs of neurons located in parallel in layers 2/3 and layer 5 of pFC. The functional significance of individual pFC minicolumns (separated by 40 µm) was shown by reduced correlated firing between cell pairs within single minicolumns on error trials with inappropriate target selection. To further demonstrate dependence on performance, a task-disrupting drug (cocaine) was administered in the middle of the session, which also reduced interlaminar firing in minicolumns that fired appropriately in the early (nondrug) portion of the session. The results provide a direct demonstration of task-specific, real-time columnar processing in pFC indicating the role of this type of microcircuit in executive control of decision-making in primate brain.

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.

Neural activity in frontal cortical cell layers: evidence for columnar sensorimotor processing.

The mammalian frontal cortex (FCx) is at the top of the brain's sensorimotor hierarchy and includes cells in the supragranular Layer 2/3, which integrate convergent sensory information for transmission to infragranular Layer 5 cells to formulate motor system outputs that control behavioral responses. Functional interaction between these two layers of FCx was examined using custom-designed ceramic-based microelectrode arrays (MEAs) that allowed simultaneous recording of firing patterns of FCx neurons in Layer 2/3 and Layer 5 in nonhuman primates performing a simple go/no-go discrimination task. This unique recording arrangement showed differential encoding of task-related sensory events by cells in each layer with Layer 2/3 cells exhibiting larger firing peaks during presentation of go target and no-go target task images, whereas Layer 5 cells showed more activity during reward contingent motor responses in the task. Firing specificity to task-related events was further demonstrated by synchronized firing between pairs of cells in different layers that occupied the same vertically oriented "column" on the MEA. Pairs of cells in different layers recorded at adjacent "noncolumnar" orientations on the MEA did not show synchronized firing during the same task-related events. The results provide required evidence in support of previously suggested task-related sensorimotor processing in the FCx via functionally segregated minicolumns.

Memory encoding in hippocampal ensembles is negatively influenced by cannabinoid CB1 receptors.

It has previously been demonstrated that the detrimental effect on the performance of a delayed nonmatch to sample (DNMS) memory task by exogenously administered cannabinoid (CB1) receptor agonist, WIN 55212-2 (WIN), is reversed by the receptor antagonist rimonabant. In addition, rimonabant administered alone elevates DNMS performance, presumably through the suppression of negative modulation by released endocannabinoids during normal task performance. Other investigations have shown that rimonabant enhances encoding of DNMS task-relevant information on a trial-by-trial, delay-dependent basis. In this study, these reciprocal pharmacological actions were completely characterized by long-term, chronic intrahippocampal infusion of both agents (WIN and rimonabant) in successive 2-week intervals. Such long-term exposure allowed extraction and confirmation of task-related firing patterns, in which rimonabant reversed the effects of CB1 agonists. This information was then utilized to artificially impose the facilitatory effects of rimonabant and to reverse the effects of WIN on DNMS performance, by delivering multichannel electrical stimulation in the same firing patterns to the same hippocampal regions. Direct comparison of normal and WIN-injected subjects, in which rimonabant injections and ensemble firing facilitated performance, verified reversal of the modulation of hippocampal memory processes by CB1 receptor agonists, including released endocannabinoids.

Differential but complementary mnemonic functions of the hippocampus and subiculum.

In this study we describe how the hippocampus and subiculum act in concert to encode information in a spatial delayed-nonmatch-to-sample (DNMS) task. This encoding was functionally partitioned between neurons within subiculum and hippocampus to uniquely identify trial-specific information accounting for both spatial and temporal constraints on performance within and between trials. Encoding by subicular neurons in the task was normally accurate and specific, but only if delays were shorter than 15 s, whereas trial-specific information encoded by hippocampal neurons was subject to strong biases from prior trial sequences and was accessible only when delays exceeded 15 s. The two structures operated in a complementary manner to encode information correctly on 75% of all trials using the above strategies. The remaining 25% of trials were at risk due to inherent idiosyncrasies by which hippocampal and subicular neurons encoded information and became errors when the random sequence of trials conflicted with these constraints.

Systemic and nasal delivery of orexin-A (Hypocretin-1) reduces the effects of sleep deprivation on cognitive performance in nonhuman primates.

Hypocretin-1 (orexin-A) was administered to sleep-deprived (30-36 h) rhesus monkeys immediately preceding testing on a multi-image delayed match-to-sample (DMS) short-term memory task. The DMS task used multiple delays and stimulus images and effectively measures cognitive defects produced by sleep deprivation (Porrino et al., 2005). Two methods of administration of orexin-A were tested, intravenous injections (2.5-10.0 microg/kg, i.v.) and a novel method developed for nasal delivery via an atomizer spray mist to the nostrils (dose estimated 1.0 microg/kg). Results showed that orexin-A delivered via the intravenous and nasal routes significantly improved performance in sleep-deprived monkeys; however, the nasal delivery method was significantly more effective than the highest dose (10 microg/kg) of intravenous orexin-A tested. The improvement in performance by orexin-A was specific to trials classified as high versus low cognitive load as determined by performance difficulty under normal testing conditions. Except for the maximum intravenous dose (10 microg/kg), neither delivery method affected task performance in alert non-sleep-deprived animals. The improved performance in sleep-deprived animals was accompanied by orexin-A related alterations in local cerebral glucose metabolism (CMRglc) in specific brain regions shown previously to be engaged by the task and impaired by sleep deprivation (Porrino et al., 2005). Consistent with the differential effects on performance, nasal delivered orexin-A produced a more pronounced reversal of sleep deprivation induced changes in brain metabolic activity (CMRglc) than intravenous orexin-A. These findings provide strong evidence for the effectiveness of intranasal orexin-A in alleviating cognitive deficits produced by loss of sleep.

Endocannabinoids modulate encoding of sequential memory in the rat hippocampus.

RATIONALE: This report investigated the role of endocannabinoids in the encoding of task-relevant information by ensembles of hippocampal neurons under conditions in which the CB1 receptor antagonist, rimonabant, was administered during performance of a short-term memory delayed non-match to sample (DNMS) task in rats. OBJECTIVE: The influence of endocannabinoids on the encoding of task relevant information was determined via examination of the firing patterns of ensembles of CA1/CA3 hippocampal neurons during individual trials while rats performed a DNMS task. MATERIALS AND METHODS: Multivariate discriminant analysis of the firing patterns of ensembles of hippocampal neurons was used to extract trial-specific codes for task-relevant information under different types of trial sequences. RESULTS: It was discovered that rimonabant blocked an inherent hippocampal memory encoding bias used by all animals. This bias was characterized as the preferential encoding of sample information on individual trials based on the similarity (i.e., same or different) and duration of the delay in the preceding trial. CONCLUSIONS: The results indicate that endocannabinoids are a major influence on the strategic encoding biases of hippocampal ensembles and that pharmacological blockade of CB1 receptors facilitated performance by eliminating such influences.

Facilitation of task performance and removal of the effects of sleep deprivation by an ampakine (CX717) in nonhuman primates.

The deleterious effects of prolonged sleep deprivation on behavior and cognition are a concern in modern society. Persons at risk for impaired performance and health-related issues resulting from prolonged sleep loss would benefit from agents capable of reducing these detrimental effects at the time they are sleep deprived. Agents capable of improving cognition by enhancing brain activity under normal circumstances may also have the potential to reduce the harmful or unwanted effects of sleep deprivation. The significant prevalence of excitatory alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamatergic receptors in the brain provides a basis for implementing a class of drugs that could act to alter or remove the effects of sleep deprivation. The ampakine CX717 (Cortex Pharmaceuticals), a positive allosteric modulator of AMPA receptors, was tested for its ability to enhance performance of a cognitive, delayed match-to-sample task under normal circumstances in well-trained monkeys, as well as alleviate the detrimental effects of 30-36 h of sleep deprivation. CX717 produced a dose-dependent enhancement of task performance under normal alert testing conditions. Concomitant measures of regional cerebral metabolic rates for glucose (CMRglc) during the task, utilizing positron emission tomography, revealed increased activity in prefrontal cortex, dorsal striatum, and medial temporal lobe (including hippocampus) that was significantly enhanced over normal alert conditions following administration of CX717. A single night of sleep deprivation produced severe impairments in performance in the same monkeys, accompanied by significant alterations in task-related CMRglc in these same brain regions. However, CX717 administered to sleep-deprived monkeys produced a striking removal of the behavioral impairment and returned performance to above-normal levels even though animals were sleep deprived. Consistent with this recovery, CMRglc in all but one brain region affected by sleep deprivation was also returned to the normal alert pattern by the drug. The ampakine CX717, in addition to enhancing cognitive performance under normal alert conditions, also proved effective in alleviating impairment of performance due to sleep deprivation. Therefore, the ability to activate specific brain regions under normal alert conditions and alter the deleterious effects of sleep deprivation on activity in those same regions indicate a potential role for ampakines in sustaining performance under these types of adverse conditions.

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.

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.

Nonlinear dynamic modeling of spike train transformations for hippocampal-cortical prostheses.

One of the fundamental principles of cortical brain regions, including the hippocampus, is that information is represented in the ensemble firing of populations of neurons, i.e., spatio-temporal patterns of electrophysiological activity. The hippocampus has long been known to be responsible for the formation of declarative, or fact-based, memories. Damage to the hippocampus disrupts the propagation of spatio-temporal patterns of activity through hippocampal internal circuitry, resulting in a severe anterograde amnesia. Developing a neural prosthesis for the damaged hippocampus requires restoring this multiple-input, multiple-output transformation of spatio-temporal patterns of activity. Because the mechanisms underlying synaptic transmission and generation of electrical activity in neurons are inherently nonlinear, any such prosthesis must be based on a nonlinear multiple-input, multiple-output model. In this paper, we have formulated the transformational process of multi-site propagation of spike activity between two subregions of the hippocampus (CA3 and CA1) as the identification of a multiple-input, multiple-output (MIMO) system, and proposed that it can be decomposed into a series of multiple-input, single-output (MISO) systems. Each MISO system is modeled as a physiologically plausible structure that consists of 1) linear/nonlinear feedforward Volterra kernels modeling synaptic transmission and dendritic integration, 2) a linear feedback Volterra kernel modeling spike-triggered after-potentials, 3) a threshold for spike generation, 4) a summation process for somatic integration, and 5) a noise term representing intrinsic neuronal noise and the contributions of unobserved inputs. Input and output spike trains were recorded from hippocampal CA3 and CA1 regions of rats performing a spatial delayed-nonmatch-to-sample memory task that requires normal hippocampal function. Kernels were expanded with Laguerre basis functions and estimated using a maximum-likelihood method. Complexity of the feedforward kernel was progressively increased to capture higher-order system nonlinear dynamics. Results showed higher prediction accuracies as kernel complexity increased. Self-kernels describe the nonlinearities within each input. Cross-kernels capture the nonlinear interaction between inputs. Second- and third-order nonlinear models were found to successfully predict the CA1 output spike distribution based on CA3 input spike trains. First-order, linear models were shown to be insufficient.

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.