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.

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.

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.

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.

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.

Modulation of food consumption and sleep-wake cycle in mice by the neutral CB1 antagonist ABD459.

The brain endocannabinoid system is a potential target for the treatment of psychiatric and metabolic conditions. Here, a novel CB1 receptor antagonist (ABD459) was synthesized and assayed for pharmacological efficacy in vitro and for modulation of food consumption, vigilance staging and cortical electroencephalography in the mouse. ABD459 completely displaced the CB1 agonist CP99540 at a Ki of 8.6 nmol/l, and did not affect basal, but antagonized CP55940-induced GTPγS binding with a KB of 7.7 nmol/l. Acute ABD459 (3-20 mg/kg) reliably inhibited food consumption in nonfasted mice, without affecting motor activity. Active food seeking was reduced for 5-6 h postdrug, with no rebound after washout. Epidural recording of electroencephalogram confirmed that ABD459 (3 mg/kg) robustly reduced rapid eye movement (REM) sleep, with no alterations of wakefulness or non-REM sleep. Effects were strongest during 3 h postdrug, followed by a progressive washout period. The CB1 antagonist AM251 (3 mg/kg) and agonist WIN-55,212-2 (WIN-2: 3 mg/kg) also reduced REM, but variously affected other vigilance stages. WIN-2 caused a global suppression of normalized spectral power. AM251 and ABD459 lowered delta power and increased power in the theta band in the hippocampus, but not the prefrontal cortex. The neutral antagonist ABD459 thus showed a specific role of endocannabinoid release in attention and arousal, possibly through modulation of cholinergic activity.

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.

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.

Cannabinoids alter spontaneous firing, bursting, and cell synchrony of hippocampal principal cells.

Both natural and synthetic cannabinoid receptor (e.g., CB1) agonists such as Δ(9)-THC, WIN 55,212-2 (WIN-2), and HU-210 disrupt spatial cognition presumably through the inhibition of synchrony of hippocampal ensemble firing to task-related events. Although the CB1 receptor agonist CP 55,940 also disrupts the synchronous firing of hippocampal neurons, it does not seem to affect the average firing rate. This difference is not readily explained by the chemical structure and pharmacology of the different compounds thus warranting a more detailed examination into (i) how other cannabinoids affect the spontaneous firing, bursting, and cell synchrony of hippocampal principal cells located in CA3 and CA1 subfields, and (ii) whether these effects are indeed mediated through CB1 receptors, which will be explored by the selective antagonist AM-251. Male Long-Evans rats surgically implanted with multielectrode arrays to hippocampal CA3 and CA1 were anesthetized and principal cells discharging at 0.25-6.0 Hz were isolated and "tracked" following the systemic administration of Tween-80, Δ(9)-THC (1 or 3 mg/kg) or WIN-2 (1 mg/kg) or HU-210 (100 µg/kg), and 1.5 mg/kg AM-281. All cannabinoids except for 1 mg/kg Δ(9) -THC reliably reduced average firing rates and altered "burst" characteristics, which were reversible with AM-281 for Δ(9)-THC and WIN-2 but not for HU-210. In addition, all cannabinoids disrupted intrasubfield and intersubfield ensemble synchrony of pyramidal cells, which is an effect insensitive to AM-281 and thus unlikely to be CB1 mediated. We consider these cannabinoid effects on spike timing and firing/bursting of principal hippocampal neurons carried by CB1 and non-CB1 receptors to be physiological underpinnings of the cognitive impairments inherent to cannabinoid exposure.

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.

Cannabinoid and cholinergic systems interact during performance of a short-term memory task in the rat.

It is now well established that cannabinoid agonists such as Δ(9)-tetrahydrocannabinol (THC), anandamide, and WIN 55,212-2 (WIN-2) produce potent and specific deficits in working memory (WM)/short-term memory (STM) tasks in rodents. Although mediated through activation of CB1 receptors located in memory-related brain regions such as the hippocampus and prefrontal cortex, these may, in part, be due to a reduction in acetylcholine release (i.e., cholinergic hypofunction). To determine the interaction between cannabinoid and cholinergic systems, we exposed rats treated with WIN-2 or cholinergic drugs to a hippocampal-dependent delayed nonmatch to sample (DNMS) task to study STM, and recorded hippocampal single-unit activity in vivo. WIN-2 induced significant deficits in DNMS performance and reduced the average firing and bursting rates of hippocampal principal cells through a CB1 receptor-mediated mechanism. Rivastigmine, an acetylcholinesterase inhibitor, reversed these STM deficits and normalized hippocampal discharge rates. Effects were specific to 1 mg/kg WIN-2 as rivastigmine failed to reverse the behavioral and physiological deficits that were observed in the presence of MK-801, an NMDA receptor antagonist. This supports the notion that cannabinoid-modulated cholinergic activity is a mechanism underlying the performance deficits in DNMS. Whether deficits are due to reduced nicotinic or muscarinic receptor activation, or both, awaits further analysis.

Recruitment of hippocampal neurons to encode behavioral events in the rat: alterations in cognitive demand and cannabinoid exposure.

Successful performance by rats of a delayed-nonmatch-to-sample (DNMS) task is hippocampal dependent. We have shown that neurons in hippocampus differentially encode task-relevant events. These responses are critical for correct DNMS performance and are diminished by exogenous cannabinoids. We therefore reasoned that hippocampal neural correlates of behavior are likely shaped during learning; however, to date, no work has examined these correlates during DNMS acquisition training. Consequently, the present study assessed the emergence of hippocampal neural encoding when (i) cognitive task demands were increased through prolongation of delay intervals between sample and nonmatch phase and (ii) when animals are under cannabinoid treatment and performance is compromised. Adult, male Long-Evans rats were trained to perform the DNMS task without delay and then implanted with multielectrode recording arrays directed to CA3 and CA1 subfields of the hippocampus. Following recovery, single units were isolated and animals divided into two treatment groups: vehicle or WIN 55,212-2 (WIN-2, 0.35 mg/kg). Ensemble firing was monitored during retraining in DNMS task at 0 s, and subsequently delay intervals were progressively increased to 1-10 s, 11-20 s, and 21-30 s when animals met criterion (80% correct) at each respective interval. Hippocampal CA3 and CA1 principal cells were isolated and recorded throughout treatment. Extension of the delay led to an increase in the number of task-correlated neurons in controls. This recruitment of novel cells was reduced/prevented in the presence of WIN-2 and was paralleled by impairment in acquisition learning at longer delay intervals. Moreover, WIN-2 suppressed hippocampal ensemble firing during the sample (encoding) but not nonmatch phase of the DNMS task across all delays. These cannabinoid-induced alterations in hippocampal neuronal activity may explain the observed deficits in DNMS performance.