Mesenchymal Stem Cells Promote an Increase in Neuronal Oscillation via Glutamate Tonic Release.

Mesenchymal stromal cells (MSCs) hold therapeutic potential for neurological disorders, but their impact on neuronal activity remains unclear. We investigated the effects of SB623 cells (Notch-1 intracellular domain-transfected MSCs) and parental MSCs on human induced pluripotent stem cell (iPSC)-derived neurons using multi-electrode arrays. SB623 cells significantly increased neuronal activity and oscillation in a dose-dependent manner, surpassing astrocytes in promoting network bursts. Strikingly, glutamatergic neurons showed a rapid increase in activity and bursts compared to GABAergic neurons, suggesting glutamate release from SB623 cells. We confirmed this by finding high glutamate levels in SB623 cell conditioned medium, which were reduced by glutaminase inhibition. Glutamate release was further implicated by the reduced excitability in co-cultures with astrocytes, known glutamate scavengers. Our findings reveal a novel mechanism for MSCs: promoting neuronal activity and network formation through tonic glutamate release, with potential implications for MSC-based therapies.

Metabolic flexibility ensures proper neuronal network function in moderate neuroinflammation.

Microglia, brain-resident macrophages, can acquire distinct functional phenotypes, which are supported by differential reprogramming of cell metabolism. These adaptations include remodeling in glycolytic and mitochondrial metabolic fluxes, potentially altering energy substrate availability at the tissue level. This phenomenon may be highly relevant in the brain, where metabolism must be precisely regulated to maintain appropriate neuronal excitability and synaptic transmission. Direct evidence that microglia can impact on neuronal energy metabolism has been widely lacking, however. Combining molecular profiling, electrophysiology, oxygen microsensor recordings and mathematical modeling, we investigated microglia-mediated disturbances in brain energetics during neuroinflammation. Our results suggest that proinflammatory microglia showing enhanced nitric oxide release and decreased CX3CR1 expression transiently increase the tissue lactate/glucose ratio that depends on transcriptional reprogramming in microglia, not in neurons. In this condition, neuronal network activity such as gamma oscillations (30-70 Hz) can be fueled by increased ATP production in mitochondria, which is reflected by elevated oxygen consumption. During dysregulated inflammation, high energy demand and low glucose availability can be boundary conditions for neuronal metabolic fitness as revealed by kinetic modeling of single neuron energetics. Collectively, these findings indicate that metabolic flexibility protects neuronal network function against alterations in local substrate availability during moderate neuroinflammation.

Adult-born granule cells modulate CA2 network activity during retrieval of developmental memories of the mother.

Adult-born granule cells (abGCs) project to the CA2 region of the hippocampus, but it remains unknown how this circuit affects behavioral function. Here, we show that abGC input to the CA2 of adult mice is involved in the retrieval of remote developmental memories of the mother. Ablation of abGCs impaired the ability to discriminate between a caregiving mother and a novel mother, and this ability returned after abGCs were regenerated. Chemogenetic inhibition of projections from abGCs to the CA2 also temporarily prevented the retrieval of remote mother memories. These findings were observed when abGCs were inhibited at 4-6 weeks old, but not when they were inhibited at 10-12 weeks old. We also found that abGCs are necessary for differentiating features of CA2 network activity, including theta-gamma coupling and sharp wave ripples, in response to novel versus familiar social stimuli. Taken together, these findings suggest that abGCs are necessary for neuronal oscillations associated with discriminating between social stimuli, thus enabling retrieval of remote developmental memories of the mother by their adult offspring.

Perturbing cortical networks: in vivo electrophysiological consequences of pan-neuronal chemogenetic manipulations using deschloroclozapine.

Introduction: Chemogenetic techniques, specifically the use of Designer Receptors Exclusively Activated by Designer Drugs (DREADDs), have become invaluable tools in neuroscience research. Yet, the understanding of how Gq- and Gicoupled DREADDs alter local field potential (LFP) oscillations in vivo remains incomplete. Methods: This study investigates the in vivo electrophysiological effects of DREADD actuation by deschloroclozapine, on spontaneous firing rate and LFP oscillations recorded from the anterior cingulate cortex in lightly anesthetized male rats. Results: Unexpectedly, in response to the administration of deschloroclozapine, we observed inhibitory effects with pan-neuronal hM3D(Gq) stimulation, and excitatory effects with pan-neuronal hM4D(Gi) stimulation in a significant portion of neurons. These results emphasize the need to account for indirect perturbation effects at the local neuronal network level in vivo, particularly when not all neurons express the chemogenetic receptors uniformly. In the current study, for instance, the majority of cells that were transduced with both hM3D(Gq) and hM4D(Gi) were GABAergic. Moreover, we found that panneuronal cortical chemogenetic modulation can profoundly alter oscillatory neuronal activity, presenting a potential research tool or therapeutic strategy in several neuropsychiatric models and diseases. Discussion: These findings help to optimize the use of chemogenetic techniques in neuroscience research and open new possibilities for novel therapeutic strategies.

Sex differences in neuronal oscillatory activity and memory in the methylazoxymethanol acetate model of schizophrenia.

The methylazoxymethanol acetate (MAM) rodent model is used to study aspects of schizophrenia. However, numerous studies that have employed this model have used only males, resulting in a dearth of knowledge on sex differences in brain function and behaviour. The purpose of this study was to determine whether differences exist between male and female MAM rats in neuronal oscillatory function within and between the prefrontal cortex (PFC), ventral hippocampus (vHIP) and thalamus, behaviour, and in proteins linked to schizophrenia neuropathology. We showed that female MAM animals exhibited region-specific alterations in theta power, elevated low and high gamma power in all regions, and elevated PFC-thalamus high gamma coherence. Male MAM rats had elevated beta and low gamma power in PFC, and elevated vHIP-thalamus coherence. MAM females displayed impaired reversal learning whereas MAM males showed impairments in spatial memory. Glycogen synthase kinase-3 (GSK-3) was altered in the thalamus, with female MAM rats displaying elevated GSK-3α phosphorylation. Male MAM rats showed higher expression and phosphorylation GSK-3α, and higher expression of GSK-ß. Sex-specific changes in phosphorylated Tau levels were observed in a region-specific manner. These findings demonstrate there are notable sex differences in behaviour, oscillatory network function, and GSK-3 signaling in MAM rats, thus highlighting the importance of inclusion of both sexes when using this model to study schizophrenia.

Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia.

Sensory processing and sensorimotor integration are abnormal in dystonia, including impaired modulation of beta-corticomuscular coherence. However, cortex-muscle interactions in either direction are rarely described, with reports limited predominantly to investigation of linear coupling, using corticomuscular coherence or Granger causality. Information-theoretic tools such as transfer entropy detect both linear and non-linear interactions between processes. This observational case-control study applies transfer entropy to determine intra- and cross-frequency cortex-muscle coupling in young people with dystonia/dystonic cerebral palsy. Fifteen children with dystonia/dystonic cerebral palsy and 13 controls, aged 12-18 years, performed a grasp task with their dominant hand. Mechanical perturbations were provided by an electromechanical tapper. Bipolar scalp EEG over contralateral sensorimotor cortex and surface EMG over first dorsal interosseous were recorded. Multi-scale wavelet transfer entropy was applied to decompose signals into functional frequency bands of oscillatory activity and to quantify intra- and cross-frequency coupling between brain and muscle. Statistical significance against the null hypothesis of zero transfer entropy was established, setting individual 95% confidence thresholds. The proportion of individuals in each group showing significant transfer entropy for each frequency combination/direction was compared using Fisher's exact test, correcting for multiple comparisons. Intra-frequency transfer entropy was detected in all participants bidirectionally in the beta (16-32 Hz) range and in most participants from EEG to EMG in the alpha (8-16 Hz) range. Cross-frequency transfer entropy across multiple frequency bands was largely similar between groups, but a specific coupling from low-frequency EMG to beta EEG was significantly reduced in dystonia [P = 0.0061 (corrected)]. The demonstration of bidirectional cortex-muscle communication in dystonia emphasizes the value of transfer entropy for exploring neural communications in neurological disorders. The novel finding of diminished coupling from low-frequency EMG to beta EEG in dystonia suggests impaired cortical feedback of proprioceptive information with a specific frequency signature that could be relevant to the origin of the excessive low-frequency drive to muscle.

Disrupting abnormal neuronal oscillations with adaptive delayed feedback control.

Closed-loop neuronal stimulation has a strong therapeutic potential for neurological disorders such as Parkinson's disease. However, at the moment, standard stimulation protocols rely on continuous open-loop stimulation and the design of adaptive controllers is an active field of research. Delayed feedback control (DFC), a popular method used to control chaotic systems, has been proposed as a closed-loop technique for desynchronisation of neuronal populations but, so far, was only tested in computational studies. We implement DFC for the first time in neuronal populations and access its efficacy in disrupting unwanted neuronal oscillations. To analyse in detail the performance of this activity control algorithm, we used specialised in vitro platforms with high spatiotemporal monitoring/stimulating capabilities. We show that the conventional DFC in fact worsens the neuronal population oscillatory behaviour, which was never reported before. Conversely, we present an improved control algorithm, adaptive DFC (aDFC), which monitors the ongoing oscillation periodicity and self-tunes accordingly. aDFC effectively disrupts collective neuronal oscillations restoring a more physiological state. Overall, these results support aDFC as a better candidate for therapeutic closed-loop brain stimulation.

The pulvinar as a hub of visual processing and cortical integration.

The pulvinar nucleus of the thalamus is a crucial component of the visual system and plays significant roles in sensory processing and cognitive integration. The pulvinar's extensive connectivity with cortical regions allows for bidirectional communication, contributing to the integration of sensory information across the visual hierarchy. Recent findings underscore the pulvinar's involvement in attentional modulation, feature binding, and predictive coding. In this review, we highlight recent advances in clarifying the pulvinar's circuitry and function. We discuss the contributions of the pulvinar to signal modulation across the global cortical network and place these findings within theoretical frameworks of cortical processing, particularly the global neuronal workspace (GNW) theory and predictive coding.

Spectral and phase-coherence correlates of impaired auditory mismatch negativity (MMN) in schizophrenia: A MEG study.

BACKGROUND: Reduced auditory mismatch negativity (MMN) is robustly impaired in schizophrenia. However, mechanisms underlying dysfunctional MMN generation remain incompletely understood. This study aimed to examine the role of evoked spectral power and phase-coherence towards deviance detection and its impairments in schizophrenia. METHODS: Magnetoencephalography data was collected in 16 male schizophrenia patients and 16 male control participants during an auditory MMN paradigm. Analyses of event-related fields (ERF), spectral power and inter-trial phase-coherence (ITPC) focused on Heschl's gyrus, superior temporal gyrus, inferior/medial frontal gyrus and thalamus. RESULTS: MMNm ERF amplitudes were reduced in patients in temporal, frontal and subcortical regions, accompanied by decreased theta-band responses, as well as by a diminished gamma-band response in auditory cortex. At theta/alpha frequencies, ITPC to deviant tones was reduced in patients in frontal cortex and thalamus. Patients were also characterized by aberrant responses to standard tones as indexed by reduced theta-/alpha-band power and ITPC in temporal and frontal regions. Moreover, stimulus-specific adaptation was decreased at theta/alpha frequencies in left temporal regions, which correlated with reduced MMNm spectral power and ERF amplitude. Finally, phase-reset of alpha-oscillations after deviant tones in left thalamus was impaired, which correlated with impaired MMNm generation in auditory cortex. Importantly, both non-rhythmic and rhythmic components of spectral activity contributed to the MMNm response. CONCLUSIONS: Our data indicate that deficits in theta-/alpha- and gamma-band activity in cortical and subcortical regions as well as impaired spectral responses to standard sounds could constitute potential mechanisms for dysfunctional MMN generation in schizophrenia, providing a novel perspective towards MMN deficits in the disorder.

Impairments in hippocampal oscillations accompany the loss of LTP induced by GIRK activity blockade.

Learning and memory occurrence requires of hippocampal long-term synaptic plasticity and precise neural activity orchestrated by brain network oscillations, both processes reciprocally influencing each other. As G-protein-gated inwardly rectifying potassium (GIRK) channels rule synaptic plasticity that supports hippocampal-dependent memory, here we assessed their unknown role in hippocampal oscillatory activity in relation to synaptic plasticity induction. In alert male mice, pharmacological GIRK modulation did not alter neural oscillations before long-term potentiation (LTP) induction. However, after an LTP generating protocol, both gain- and loss-of basal GIRK activity transformed LTP into long-term depression, but only specific suppression of constitutive GIRK activity caused a disruption of network synchronization (δ, α, γ bands), even leading to long-lasting ripples and fast ripples pathological oscillations. Together, our data showed that constitutive GIRK activity plays a key role in the tuning mechanism of hippocampal oscillatory activity during long-term synaptic plasticity processes that underlies hippocampal-dependent cognitive functions.

Cortical dopamine D5 receptors regulate neuronal circuit oscillatory activity and memory in rats.

INTRODUCTION: The dopamine D5 receptor (D5R) shows high expression in cortical regions, yet the role of the receptor in learning and memory remains poorly understood. This study evaluated the impact of prefrontal cortical (PFC) D5R knockdown in rats on learning and memory and assessed the role of the D5R in the regulation of neuronal oscillatory activity and glycogen synthase kinase-3 (GSK-3ß), processes integral to cognitive function. MATERIALS AND METHODS: Using an adeno-associated viral (AAV) vector, male rats were infused with shRNA to the D5R bilaterally into the PFC. Local field potential recordings were taken from freely moving animals and spectral power and coherence were evaluated in, and between, the PFC, orbitofrontal cortex (OFC), hippocampus (HIP), and thalamus. Animals were then assessed in object recognition, object location, and object in place tasks. The activity of PFC GSK-3ß, a downstream effector of the D5R, was evaluated. RESULTS: AAV-mediated knockdown of the D5R in the PFC induced learning and memory deficits. These changes were accompanied by elevations in PFC, OFC, and HIP theta spectral power and PFC-OFC coherence, reduced PFC-thalamus gamma coherence, and increased PFC GSK-3ß activity. CONCLUSION: This work demonstrates a role for PFC D5Rs in the regulation of neuronal oscillatory activity and learning and memory. As elevated GSK-3ß activity has been implicated in numerous disorders of cognitive dysfunction, this work also highlights the potential of the D5R as a novel therapeutic target via suppression of GSK-3ß.

High-Throughput Screening Assay for Detecting Drug-Induced Changes in Synchronized Neuronal Oscillations and Potential Seizure Risk Based on Ca2+ Fluorescence Measurements in Human Induced Pluripotent Stem Cell (hiPSC)-Derived Neuronal 2D and 3D Cultures.

Drug-induced seizure liability is a significant safety issue and the basis for attrition in drug development. Occurrence in late development results in increased costs, human risk, and delayed market availability of novel therapeutics. Therefore, there is an urgent need for biologically relevant, in vitro high-throughput screening assays (HTS) to predict potential risks for drug-induced seizure early in drug discovery. We investigated drug-induced changes in neural Ca2+ oscillations, using fluorescent dyes as a potential indicator of seizure risk, in hiPSC-derived neurons co-cultured with human primary astrocytes in both 2D and 3D forms. The dynamics of synchronized neuronal calcium oscillations were measured with an FDSS kinetics reader. Drug responses in synchronized Ca2+ oscillations were recorded in both 2D and 3D hiPSC-derived neuron/primary astrocyte co-cultures using positive controls (4-aminopyridine and kainic acid) and negative control (acetaminophen). Subsequently, blinded tests were carried out for 25 drugs with known clinical seizure incidence. Positive predictive value (accuracy) based on significant changes in the peak number of Ca2+ oscillations among 25 reference drugs was 91% in 2D vs. 45% in 3D hiPSC-neuron/primary astrocyte co-cultures. These data suggest that drugs that alter neuronal activity and may have potential risk for seizures can be identified with high accuracy using an HTS approach using the measurements of Ca2+ oscillations in hiPSC-derived neurons co-cultured with primary astrocytes in 2D.

Astrocytic Kir4.1 channels regulate locomotion by orchestrating neuronal rhythmicity in the spinal network.

Neuronal rhythmogenesis in the spinal cord is correlated with variations in extracellular K+ levels ([K+ ]e ). Astrocytes play important role in [K+ ]e homeostasis and compute neuronal information. Yet it is unclear how neuronal oscillations are regulated by astrocytic K+ homeostasis. Here we identify the astrocytic inward-rectifying K+ channel Kir4.1 (a.k.a. Kcnj10) as a key molecular player for neuronal rhythmicity in the spinal central pattern generator (CPG). By combining two-photon calcium imaging with electrophysiology, immunohistochemistry and genetic tools, we report that astrocytes display Ca2+ transients before and during oscillations of neighboring neurons. Inhibition of astrocytic Ca2+ transients with BAPTA decreases the barium-sensitive Kir4.1 current responsible of K+ clearance. Finally, we show in mice that Kir4.1 knockdown in astrocytes progressively prevents neuronal oscillations and alters the locomotor pattern resulting in lower motor performances in challenging tasks. These data identify astroglial Kir4.1 channels as key regulators of neuronal rhythmogenesis in the CPG driving locomotion.

Bistability at the onset of neuronal oscillations.

The Hodgkin-Huxley (HH) model and squid axon (bathed in reduced Ca2+) fire repetitively for steady current injection. Moreover, for a current-range just suprathreshold, repetitive firing coexists with a stable steady state. Neuronal excitability, as such, shows bistability and hysteresis providing the opportunity for the system to perform as switchable between firing and non-firing states with transient input and providing the backbone as a dynamical mechanism for bursting oscillations. Some conditions for bistability can be derived by intricate analysis (bifurcation theory) and characterized by simulation, but conditions for emergence and robustness of such bistability do not typically follow from intuition. Here, we demonstrate with a semi-quantitative two-variable, V-w, reduction of the HH model features that promote/reduce bistability. Visualization of flow and trajectories in the V-w phase plane provides an intuitive grasp for bistability. The geometry of action potential recovery involves a late phase during which the dynamic negative feedback of [Formula: see text] inactivation and [Formula: see text] activation over/undershoot, respectively, their resting values, thereby leading to hyperexcitabilty and an intrinsically generated opportunity to by-pass the spiral-like stable rest state and initiate the next spike upstroke. We illustrate control of bistability and dependence of the degree of hysteresis on recovery timescales and gating properties. Our dynamical dissection reveals the strongly attracting depolarized phase of the spike, enabling approximations like the resetting feature of adapting integrate-and-fire models. We extend our insights and show that the Morris-Lecar model can also exhibit robust bistability.

Direct electrical brain stimulation of human memory: lessons learnt and future perspectives.

Modulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental level, it remains elusive as to how delivering electrical current in a given brain area leads to enhanced memory processing. Starting from the local and distal physiological effects on neural populations, the mechanisms of enhanced memory encoding, maintenance, consolidation or recall in response to direct electrical stimulation are only now being unravelled. With the advent of innovative neurotechnologies for concurrent recording and stimulation intracranially in the human brain, it becomes possible to study both acute and chronic effects of stimulation on memory performance and the underlying neural activities. In this review, we summarize the effects of various invasive stimulation approaches for modulating memory functions. We first outline the challenges that were faced in the initial studies of memory enhancement and the lessons learnt. Electrophysiological biomarkers are then reviewed as more objective measures of the stimulation effects than behavioural outcomes. Finally, we classify the various stimulation approaches into continuous and phasic modulation with an open or closed loop for responsive stimulation based on analysis of the recorded neural activities. Although the potential advantage of closed-loop responsive stimulation over the classic open-loop approaches is inconclusive, we foresee the emerging results from ongoing longitudinal studies and clinical trials will shed light on both the mechanisms and optimal strategies for improving declarative memory. Adaptive stimulation based on the biomarker analysis over extended periods of time is proposed as a future direction for obtaining lasting effects on memory functions. Chronic tracking and modulation of neural activities intracranially through adaptive stimulation opens tantalizing new avenues to continually monitor and treat memory and cognitive deficits in a range of brain disorders. Brain co-processors created with machine-learning tools and wireless bi-directional connectivity to seamlessly integrate implanted devices with smartphones and cloud computing are poised to enable real-time automated analysis of large data volumes and adaptively tune electrical stimulation based on electrophysiological biomarkers of behavioural states. Next-generation implantable devices for high-density recording and stimulation of electrophysiological activities, and technologies for distributed brain-computer interfaces are presented as selected future perspectives for modulating human memory and associated mental processes.

Multistage classification identifies altered cortical phase- and amplitude-coupling in Multiple Sclerosis.

Distinguishing groups of subjects or experimental conditions in a high-dimensional feature space is a common goal in modern neuroimaging studies. Successful classification depends on the selection of relevant features as not every neuronal signal component or parameter is informative about the research question at hand. Here, we developed a novel unsupervised multistage analysis approach that combines dimensionality reduction, bootstrap aggregating and multivariate classification to select relevant neuronal features. We tested the approach by identifying changes of brain-wide electrophysiological coupling in Multiple Sclerosis. Multiple Sclerosis is a demyelinating disease of the central nervous system that can result in cognitive decline and physical disability. However, related changes in large-scale brain interactions remain poorly understood and corresponding non-invasive biomarkers are sparse. We thus compared brain-wide phase- and amplitude-coupling of frequency specific neuronal activity in relapsing-remitting Multiple Sclerosis patients (n = 17) and healthy controls (n = 17) using magnetoencephalography. Changes in this dataset included both, increased and decreased phase- and amplitude-coupling in wide-spread, bilateral neuronal networks across a broad range of frequencies. These changes allowed to successfully classify patients and controls with an accuracy of 84%. Furthermore, classification confidence predicted behavioral scores of disease severity. In sum, our results unravel systematic changes of large-scale phase- and amplitude coupling in Multiple Sclerosis. Furthermore, our results establish a new analysis approach to efficiently contrast high-dimensional neuroimaging data between experimental groups or conditions.

Association of resting-state theta-gamma coupling with selective visual attention in children with tic disorders.

A tic disorder (TD) is a neurodevelopmental disorder characterized by tics, which are repetitive movements and/or vocalizations that occur due to aberrant sensory gating. Its pathophysiology involves dysfunction in multiple parts of the cortico-striato-thalamo-cortical circuits. Spontaneous brain activity during the resting state can be used to evaluate the baseline brain state, and it is associated with various aspects of behavior and cognitive processes. Theta-gamma coupling (TGC) is an emerging technique for examining how neural networks process information through interactions. However, the resting-state TGC of patients with TD and its correlation with cognitive function have not yet been studied. We investigated the resting-state TGC of 13 patients with TD and compared it with that of 13 age-matched healthy children. The participants underwent resting-state electroencephalography with their eyes closed. At the global level, patients with TD showed a significantly lower resting-state TGC than healthy children. Resting-state TGC with the eyes closed was significantly negatively correlated with the attention quotient calculated for omission errors in a selective visual attention test. These findings indicate that the resting-state brain network, which is important for the attentional processing of visual information, is dysfunctional in patients with TD. Additionally, these findings support the view that TGC reflects information processing and signal interactions at the global level. Patients with TD may have difficulty gating irrelevant sensory information in the resting state while their eyes are closed.

Interferon γ: a master cytokine in microglia-mediated neural network dysfunction and neurodegeneration.

Traditionally, lymphocytic interferon γ (IFN-γ) was considered to be a simple 'booster' of proinflammatory responses by microglia (brain-resident macrophages) during bacterial or viral infection. Recent slice culture (in situ) and in vivo studies suggest, however, that IFN-γ has a unique role in microglial activation. Priming by IFN-γ results in proliferation (microgliosis), enhanced synapse elimination, and moderate nitric oxide release sufficient to impair synaptic transmission, gamma rhythm activity, and cognitive functions. Moreover, IFN-γ is pivotal for driving Toll-like receptor (TLR)-activated microglia into neurotoxic phenotypes that induce energetic and oxidative stress, severe network dysfunction, and neuronal death. Pharmacological targeting of activated microglia could be beneficial during elevated IFN-γ levels, blood-brain barrier leakage, and parenchymal T lymphocyte infiltration associated with, for instance, encephalitis, multiple sclerosis, and Alzheimer's disease.

Single-Transistor Neuron with Excitatory-Inhibitory Spatiotemporal Dynamics Applied for Neuronal Oscillations.

Brain-inspired neuromorphic computing systems with the potential to drive the next wave of artificial intelligence demand a spectrum of critical components beyond simple characteristics. An emerging research trend is to achieve advanced functions with ultracompact neuromorphic devices. In this work, a single-transistor neuron is demonstrated that implements excitatory-inhibitory (E-I) spatiotemporal integration and a series of essential neuron behaviors. Neuronal oscillations, the fundamental mode of neuronal communication, that construct high-dimensional population code to achieve efficient computing in the brain, can also be demonstrated by the neuron transistors. The highly scalable E-I neuron can be the basic building block for implementing core neuronal circuit motifs and large-scale architectural plans to replicate energy-efficient neural computations, forming the foundation of future integrated neuromorphic systems.

Hippocampal-prefrontal theta coupling develops as mice become proficient in associative odorant discrimination learning.

Learning and memory requires coordinated activity between different regions of the brain. Here we studied the interaction between infralimbic medial prefrontal cortex (mPFC) and hippocampal dorsal CA1 during associative odorant discrimination learning in the mouse. We found that as the animal learns to discriminate odorants in a go-no go task, the coupling of high frequency neural oscillations to the phase of theta oscillations (theta-referenced phase-amplitude coupling or tPAC) changes in a manner that results in divergence between rewarded and unrewarded odorant-elicited changes in the theta-phase referenced power (tPRP) for beta and gamma oscillations. In addition, in the proficient animal there was a decrease in the coordinated oscillatory activity between CA1 and mPFC in the presence of the unrewarded odorant. Furthermore, the changes in tPAC resulted in a marked increase in the accuracy for decoding contextual odorant identity from tPRP when the animal became proficient. Finally, we studied the role of Ca2+/calmodulin-dependent protein kinase II α (CaMKIIα), a protein involved in learning and memory, in oscillatory neural processing in this task. We find that the accuracy for decoding the contextual odorant identity from tPRP decreases in CaMKIIα knockout mice and that this accuracy correlates with behavioral performance. These results implicate a role for tPAC and CaMKIIα in olfactory go-no go associative learning in the hippocampal-prefrontal circuit.Significance statementCoupling of neural oscillations within and between hippocampal CA1 and medial prefrontal cortex (mPFC) is involved in spatial learning and memory, but the role of oscillation coupling for other learning tasks is not well understood. Here we performed local field potential recording in CA1 and mPFC in mice learning to differentiate rewarded from unrewarded odorants in an associative learning task. We find that odorant-elicited changes in the power of bursts of gamma oscillations at distinct phases of theta oscillations become divergent as the animal becomes proficient allowing decoding of contextual odorant identity. Finally, we find that the accuracy to decode contextual odorant identity decreases in mice deficient for the expression of Ca2+/calmodulin-dependent protein kinase II α, a protein involved in synaptic plasticity.