A Cortical Mechanism Linking Saliency Detection and Motor Reactivity in Rhesus Monkeys.

Sudden and surprising sensory events trigger neural processes that swiftly adjust behavior. To study the phylogenesis and the mechanism of this phenomenon, we trained two male rhesus monkeys to keep a cursor inside a visual target by exerting force on an isometric joystick. We examined the effect of surprising auditory stimuli on exerted force, scalp electroencephalographic (EEG) activity, and local field potentials (LFPs) recorded from the dorsolateral prefrontal cortex. Auditory stimuli elicited (1) a biphasic modulation of isometric force, a transient decrease followed by a corrective tonic increase, and (2) EEG and LFP deflections dominated by two large negative-positive waves (N70 and P130). The EEG potential was symmetrical and maximal at the scalp vertex, highly reminiscent of the human "vertex potential." Electrocortical potentials and force were tightly coupled: the P130 amplitude predicted the magnitude of the corrective force increase, particularly in the LFPs recorded from deep rather than superficial cortical layers. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to salient sensory events.Significance Statement Survival in the natural world depends on an animal's capacity to adapt ongoing behavior to abrupt unexpected events. To study the neural mechanisms underlying this capacity, we trained monkeys to apply constant force on a joystick while we recorded their brain activity from the scalp and the prefrontal cortex contralateral to the hand holding the joystick. Unexpected auditory stimuli elicited a biphasic force modulation: a transient reduction followed by a corrective adjustment. The same stimuli also elicited EEG and LFP responses, dominated by a biphasic wave that predicted the magnitude of the behavioral adjustment. These results disclose a phylogenetically preserved corticomotor mechanism supporting adaptive behavior in response to unexpected events.

Site-dependent shaping of field potential waveforms.

The activity of neuron populations gives rise to field potentials (FPs) that extend beyond the sources. Their mixing in the volume dilutes the original temporal motifs in a site-dependent manner, a fact that has received little attention. And yet, it potentially rids of physiological significance the time-frequency parameters of individual waves (amplitude, phase, duration). This is most likely to happen when a single source or a local origin is erroneously assumed. Recent studies using spatial treatment of these signals and anatomically realistic modeling of neuron aggregates provide convincing evidence for the multisource origin and site-dependent blend of FPs. Thus, FPs generated in primary structures like the neocortex and hippocampus reach far and cross-contaminate each other but also, they add and even impose their temporal traits on distant regions. Furthermore, both structures house neurons that act as spatially distinct (but overlapped) FP sources whose activation is state, region, and time dependent, making the composition of so-called local FPs highly volatile and strongly site dependent. Since the spatial reach cannot be predicted without source geometry, it is important to assess whether waveforms and temporal motifs arise from a single source; otherwise, those from each of the co-active sources should be sought.

Red-emitting 4-methyl coumarin fused barbituric acid as an electrochemical sensor for catechol detection and probe for latent fingerprints.

Herein, we have reported a red-emitting 4-methyl coumarin fused barbituric acid azo dye (4-MCBA) synthesized by conventional method. Density functional theory (DFT) studies of tautomer compounds were done using (B3LYP) with a basis set of 6-31G(d,p). NLO analysis has shown that tautomer has mean first-order hyperpolarisabilities (ß) value of 1.8188 × 10-30 esu and 1.0470 × 10-30 esu for azo and hydrazone forms, respectively, which is approximately nine and five times greater than the magnitude of urea. 4-MCBA exhibited two absorption peaks in the range of 290-317 and 379-394 nm, and emission spectra were observed at 536 nm. CV study demonstrated that the modified 4-MCBA/MGC electrode exhibited excellent electrochemical sensitivity towards the detection of catechol and the detection limit is 9.39 µM under optimum conditions. The 4-MCBA employed as a fluorescent probe for the visualisation of LFPs on various surfaces exhibited Level-I to level-II LFPs, with low background interference.

Intraoperative Local Field Potential Beta Power and Three-Dimensional Neuroimaging Mapping Predict Long-Term Clinical Response to Deep Brain Stimulation in Parkinson Disease: A Retrospective Study.

BACKGROUND: Directional deep brain stimulation (DBS) leads allow a fine-tuning control of the stimulation field, however, this new technology could increase the DBS programming time because of the higher number of the possible combinations used in directional DBS than in standard nondirectional electrodes. Neuroimaging leads localization techniques and local field potentials (LFPs) recorded from DBS electrodes implanted in basal ganglia are among the most studied biomarkers for DBS programing. OBJECTIVE: This study aimed to evaluate whether intraoperative LFPs beta power and neuroimaging reconstructions correlate with contact selection in clinical programming of DBS in patients with Parkinson disease (PD). MATERIALS AND METHODS: In this retrospective study, routine intraoperative LFPs recorded from all contacts in the subthalamic nucleus (STN) of 14 patients with PD were analyzed to calculate the beta band power for each contact. Neuroimaging reconstruction obtained through Brainlab Elements Planning software detected contacts localized within the STN. Clinical DBS programming contact scheme data were collected after one year from the implant. Statistical analysis evaluated the diagnostic performance of LFPs beta band power and neuroimaging data for identification of the contacts selected with clinical programming. We evaluated whether the most effective contacts identified based on the clinical response after one year from implant were also those with the highest level of beta activity and localized within the STN in neuroimaging reconstruction. RESULTS: LFPs beta power showed a sensitivity of 67%, a negative predictive value (NPV) of 84%, a diagnostic odds ratio (DOR) of 2.7 in predicting the most effective contacts as evaluated through the clinical response. Neuroimaging reconstructions showed a sensitivity of 62%, a NPV of 77%, a DOR of 1.20 for contact effectivity prediction. The combined use of the two methods showed a sensitivity of 87%, a NPV of 87%, a DOR of 2.7 for predicting the clinically more effective contacts. CONCLUSIONS: The combined use of LFPs beta power and neuroimaging localization and segmentations predict which are the most effective contacts as selected on the basis of clinical programming after one year from implant of DBS. The use of predictors in contact selection could guide clinical programming and reduce time needed for it.

Estimation of ANT-DBS Electrodes on Target Positioning Based on a New PerceptTM PC LFP Signal Analysis.

Deep brain stimulation of the Anterior Nucleus of the Thalamus (ANT-DBS) is an effective therapy in epilepsy. Poorer surgical outcomes are related to deviations of the lead from the ANT-target. The target identification relies on the visualization of anatomical structures by medical imaging, which presents some disadvantages. This study aims to research whether ANT-LFPs recorded with the PerceptTM PC neurostimulator can be an asset in the identification of the DBS-target. For this purpose, 17 features were extracted from LFPs recorded from a single patient, who stayed at an Epilepsy Monitoring Unit for a 5-day period. Features were then integrated into two machine learning (ML)-based methodologies, according to different LFP bipolar montages: Pass1 (nonadjacent channels) and Pass2 (adjacent channels). We obtained an accuracy of 76.6% for the Pass1-classifier and 83.33% for the Pass2-classifier in distinguishing locations completely inserted in the target and completely outside. Then, both classifiers were used to predict the target percentage of all combinations, and we found that contacts 3 (left hemisphere) and 2 and 3 (right hemisphere) presented higher signatures of the ANT-target, which agreed with the medical images. This result opens a new window of opportunity for the use of LFPs in the guidance of DBS target identification.

Sensing and sensitive visualization of latent fingerprints on various surfaces using a versatile fluorescent aggregation-induced emission-based coumarin derivative.

The marked rise in criminal activity in society has made a difficult task for forensic scientists who aim to track any crime scene effectively, therefore visualization of latent fingerprints (LFPs) plays an increasingly vital role in forensics. In the present report, a highly sensitive solvatochromism, aggregation-induced emission-based 2-(4-nitrophenyl)-3H-benzocoumarin fluorescent dye (CFD) was fabricated using an ultrasonication protocol. The fluorescence properties of the CFD were analyzed using fluorescence spectrophotometer. The CFD produced a greenish yellow emission in solid and fluid states. An in-depth visualization of LFPs showed detailed ridge patterns under normal and ultraviolet light sources (254 and 365 nm) due to the excellent chemisorption of CFD onto the ridge patterns on the finger. All three types of ridge details were visualized without any background interference when using a simple and quick powder dusting method. Results revealed that, the present fluorescent dye can be used successfully for detection of latent fingerprints (LFPs) on various nonporous substrates surfaces, in organic light-emitting diodes applications (OLEDs), and for electrochemical sensing.

Subthalamic nucleus oscillations correlate with vulnerability to freezing of gait in patients with Parkinson's disease.

Freezing of gait (FOG) is a disabling clinical phenomenon often found in patients with advanced Parkinson's disease (PD). FOG impairs motor function, causes falls and leads to loss of independence. Whereas dual tasking that distracts patients' attention precipitates FOG, auditory or visual cues ameliorate this phenomenon. The pathophysiology of FOG remains unclear. Previous studies suggest that the basal ganglia are involved in the generation of FOG. Investigation of the modulation of neuronal activities within basal ganglia structures during walking is warranted. To this end, we recorded local field potentials (LFP) from the subthalamic nucleus (STN) while PD patients performed single-task gait (ST) or walked while dual-tasking (DT). An index of FOG (iFOG) derived from trunk accelerometry was used as an objective measure to differentiate FOG-vulnerable gait from normal gait. Two spectral activities recorded from the STN region were associated with vulnerability to freezing. Greater LFP power in the low beta (15-21 Hz) and theta (5-8 Hz) bands were noted during periods of vulnerable gait in both ST and DT states. Whereas the elevation of low beta activities was distributed across STN, the increase in theta activity was focal and found in ventral STN and/or substantia nigra (SNr) in ST. The results demonstrate that low beta and theta band oscillations within the STN area occur during gait susceptible to freezing in PD. They also add to the evidence that narrow band ~18 Hz activity may be linked to FOG.

Non-Linear Dynamical Analysis of Resting Tremor for Demand-Driven Deep Brain Stimulation.

Parkinson's Disease (PD) is currently the second most common neurodegenerative disease. One of the most characteristic symptoms of PD is resting tremor. Local Field Potentials (LFPs) have been widely studied to investigate deviations from the typical patterns of healthy brain activity. However, the inherent dynamics of the Sub-Thalamic Nucleus (STN) LFPs and their spatiotemporal dynamics have not been well characterized. In this work, we study the non-linear dynamical behaviour of STN-LFPs of Parkinsonian patients using ε -recurrence networks. RNs are a non-linear analysis tool that encodes the geometric information of the underlying system, which can be characterised (for example, using graph theoretical measures) to extract information on the geometric properties of the attractor. Results show that the activity of the STN becomes more non-linear during the tremor episodes and that ε -recurrence network analysis is a suitable method to distinguish the transitions between movement conditions, anticipating the onset of the tremor, with the potential for application in a demand-driven deep brain stimulation system.

Alterations in Functional Cortical Hierarchy in Hemiparkinsonian Rats.

Parkinson's disease and experimentally induced hemiparkinsonism are characterized by increased beta synchronization between cortical and subcortical areas. This change in beta connectivity might reflect either a symmetric increase in interareal influences or asymmetric changes in directed influences among brain areas. We assessed patterns of functional and directed connectivity within and between striatum and six cortical sites in each hemisphere of the hemiparkinsonian rat model. LFPs were recorded in resting and walking states, before and after unilateral 6-hydroxydopamine lesion. The hemiparkinsonian state was characterized by increased oscillatory activity in the 20-40 Hz range in resting and walking states, and increased interhemispheric coupling (phase lag index) that was more widespread at rest than during walking. Spectral Granger-causality analysis revealed that the change in symmetric functional connectivity comprised profound reorganization of hierarchical organization and directed influence patterns. First, in the lesioned hemisphere, the more anterior, nonprimary motor areas located at the top of the cortical hierarchy (i.e., receiving many directed influences) tended to increase their directed influence onto the posterior primary motor and somatosensory areas. This enhanced influence of "higher" areas may be related to the loss of motor control due to the 6-OHDA lesion. Second, the drive from the nonlesioned toward the lesioned hemisphere (in particular to striatum) increased, most prominently during walking. The nature of these adaptations (disturbed signaling or compensation) is discussed. The present study demonstrates that hemiparkinsonism is associated with a profound reorganization of the hierarchical organization of directed influence patterns among brain areas, perhaps reflecting compensatory processes.SIGNIFICANCE STATEMENT Parkinson's disease classically first becomes manifest in one hemibody before affecting both sides, suggesting that degeneration is asymmetrical. Our results suggest that asymmetrical degeneration of the dopaminergic system induces an increased drive from the nonlesioned toward the lesioned hemisphere and a profound reorganization of functional cortical hierarchical organization, leading to a stronger directed influence of hierarchically higher placed cortical areas over primary motor and somatosensory cortices. These changes may represent a compensatory mechanism for loss of motor control as a consequence of dopamine depletion.

Permutation Mutual Information: A Novel Approach for Measuring Neuronal Phase-Amplitude Coupling.

Cross-frequency phase-amplitude coupling (PAC) in neuronal oscillations network plays an important functional role in large scale neuronal communication and neuronal encoding. In the present study, a novel approach named permutation mutual information (PMI) was applied in measuring PAC. It is derived from the permutation entropy based on the mutual information theory, by which the mutual information of permutations of two time series can be evaluated. In order to verify the ability of PMI, a numerical test was performed by using both simulation data and experimental data. The performances of PMI were compared with that of two well-known methods, which were the mean vector length (MVL) and the modulation index (MI). It was found that the performance of PMI was similar to that of MI when measuring PAC intensity, but the coupling sensitivity of PMI was the highest among all these three approaches. Moreover, there was the lowest sensitivity in the MVL measurement, suggesting that MVL was a more conservative approach in detecting the existence of PAC. In addition, an ROC analysis showed that PMI performed better in measuring PAC compared to that of others. Furthermore, the experimental data, obtained from rats' hippocampal CA3 regions, were analyzed by using the three approaches. The result was essentially in line with that of the simulation performances. In a word, the results suggest that PMI is a better choice for assessing PAC under the certain conditions.

Long-Term Stability of Motor Cortical Activity: Implications for Brain Machine Interfaces and Optimal Feedback Control.

The human motor system is capable of remarkably precise control of movements--consider the skill of professional baseball pitchers or surgeons. This precise control relies upon stable representations of movements in the brain. Here, we investigated the stability of cortical activity at multiple spatial and temporal scales by recording local field potentials (LFPs) and action potentials (multiunit spikes, MSPs) while two monkeys controlled a cursor either with their hand or directly from the brain using a brain-machine interface. LFPs and some MSPs were remarkably stable over time periods ranging from 3 d to over 3 years; overall, LFPs were significantly more stable than spikes. We then assessed whether the stability of all neural activity, or just a subset of activity, was necessary to achieve stable behavior. We showed that projections of neural activity into the subspace relevant to the task (the "task-relevant space") were significantly more stable than were projections into the task-irrelevant (or "task-null") space. This provides cortical evidence in support of the minimum intervention principle, which proposes that optimal feedback control (OFC) allows the brain to tightly control only activity in the task-relevant space while allowing activity in the task-irrelevant space to vary substantially from trial to trial. We found that the brain appears capable of maintaining stable movement representations for extremely long periods of time, particularly so for neural activity in the task-relevant space, which agrees with OFC predictions. SIGNIFICANCE STATEMENT: It is unknown whether cortical signals are stable for more than a few weeks. Here, we demonstrate that motor cortical signals can exhibit high stability over several years. This result is particularly important to brain-machine interfaces because it could enable stable performance with infrequent recalibration. Although we can maintain movement accuracy over time, movement components that are unrelated to the goals of a task (such as elbow position during reaching) often vary from trial to trial. This is consistent with the minimum intervention principle of optimal feedback control. We provide evidence that the motor cortex acts according to this principle: cortical activity is more stable in the task-relevant space and more variable in the task-irrelevant space.

The neurogenesis of P1 and N1: A concurrent EEG/LFP study.

It is generally recognised that event related potentials (ERPs) of electroencephalogram (EEG) primarily reflect summed post-synaptic activity of the local pyramidal neural population(s). However, it is still not understood how the positive and negative deflections (e.g. P1, N1 etc) observed in ERP recordings are related to the underlying excitatory and inhibitory post-synaptic activity. We investigated the neurogenesis of P1 and N1 in ERPs by pharmacologically manipulating inhibitory post-synaptic activity in the somatosensory cortex of rodent, and concurrently recording EEG and local field potentials (LFPs). We found that the P1 wave in the ERP and LFP of the supragranular layers is determined solely by the excitatory post-synaptic activity of the local pyramidal neural population, as is the initial segment of the N1 wave across cortical depth. The later part of the N1 wave was modulated by inhibitory post-synaptic activity, with its peak and the pulse width increasing as inhibition was reduced. These findings suggest that the temporal delay of inhibition with respect to excitation observed in intracellular recordings is also reflected in extracellular field potentials (FPs), resulting in a temporal window during which only excitatory post-synaptic activity and leak channel activity are recorded in the ERP and evoked LFP time series. Based on these findings, we provide clarification on the interpretation of P1 and N1 in terms of the excitatory and inhibitory post-synaptic activities of the local pyramidal neural population(s).

Information processing in the primate basal ganglia during sensory-guided and internally driven rhythmic tapping.

Gamma (γ) and beta (ß) oscillations seem to play complementary functions in the cortico-basal ganglia-thalamo-cortical circuit (CBGT) during motor behavior. We investigated the time-varying changes of the putaminal spiking activity and the spectral power of local field potentials (LFPs) during a task where the rhythmic tapping of monkeys was guided by isochronous stimuli separated by a fixed duration (synchronization phase), followed by a period of internally timed movements (continuation phase). We found that the power of both bands and the discharge rate of cells showed an orderly change in magnitude as a function of the duration and/or the serial order of the intervals executed rhythmically. More LFPs were tuned to duration and/or serial order in the ß- than the γ-band, although different values of preferred features were represented by single cells and by both bands. Importantly, in the LFPs tuned to serial order, there was a strong bias toward the continuation phase for the ß-band when aligned to movements, and a bias toward the synchronization phase for the γ-band when aligned to the stimuli. Our results suggest that γ-oscillations reflect local computations associated with stimulus processing, whereas ß-activity involves the entrainment of large putaminal circuits, probably in conjunction with other elements of CBGT, during internally driven rhythmic tapping.

High-Gamma Activity Is Coupled to Low-Gamma Oscillations in Precentral Cortices and Modulates with Movement and Speech.

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger-flexion or word-reading tasks. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Dynamic temporal neural patterns based on multichannel LFPs Identify different brain states during anesthesia in pigeons: comparison of three anesthetics.

Anesthetic-induced brain activity study is crucial in avian cognitive-, consciousness-, and sleep-related research. However, the neurobiological mechanisms underlying the generation of brain rhythms and specific connectivity of birds during anesthesia are poorly understood. Although different kinds of anesthetics can be used to induce an anesthesia state, a comparison study of these drugs focusing on the neural pattern evolution during anesthesia is lacking. Here, we recorded local field potentials (LFPs) using a multi-channel micro-electrode array inserted into the nidopallium caudolateral (NCL) of adult pigeons (Columba livia) anesthetized with chloral hydrate, pelltobarbitalum natricum or urethane. Power spectral density (PSD) and functional connectivity analyses were used to measure the dynamic temporal neural patterns in NCL during anesthesia. Neural decoding analysis was adopted to calculate the probability of the pigeon's brain state and the kind of injected anesthetic. In the NCL during anesthesia, we found elevated power activity and functional connectivity at low-frequency bands and depressed power activity and connectivity at high-frequency bands. Decoding results based on the spectral and functional connectivity features indicated that the pigeon's brain states during anesthesia and the injected anesthetics can be effectively decoded. These findings provide an important foundation for future investigations on how different anesthetics induce the generation of specific neural patterns.

Hyper-parameter tuning and feature extraction for asynchronous action detection from sub-thalamic nucleus local field potentials.

Introduction: Decoding brain states from subcortical local field potentials (LFPs) indicative of activities such as voluntary movement, tremor, or sleep stages, holds significant potential in treating neurodegenerative disorders and offers new paradigms in brain-computer interface (BCI). Identified states can serve as control signals in coupled human-machine systems, e.g., to regulate deep brain stimulation (DBS) therapy or control prosthetic limbs. However, the behavior, performance, and efficiency of LFP decoders depend on an array of design and calibration settings encapsulated into a single set of hyper-parameters. Although methods exist to tune hyper-parameters automatically, decoders are typically found through exhaustive trial-and-error, manual search, and intuitive experience. Methods: This study introduces a Bayesian optimization (BO) approach to hyper-parameter tuning, applicable through feature extraction, channel selection, classification, and stage transition stages of the entire decoding pipeline. The optimization method is compared with five real-time feature extraction methods paired with four classifiers to decode voluntary movement asynchronously based on LFPs recorded with DBS electrodes implanted in the subthalamic nucleus of Parkinson's disease patients. Results: Detection performance, measured as the geometric mean between classifier specificity and sensitivity, is automatically optimized. BO demonstrates improved decoding performance from initial parameter setting across all methods. The best decoders achieve a maximum performance of 0.74 ± 0.06 (mean ± SD across all participants) sensitivity-specificity geometric mean. In addition, parameter relevance is determined using the BO surrogate models. Discussion: Hyper-parameters tend to be sub-optimally fixed across different users rather than individually adjusted or even specifically set for a decoding task. The relevance of each parameter to the optimization problem and comparisons between algorithms can also be difficult to track with the evolution of the decoding problem. We believe that the proposed decoding pipeline and BO approach is a promising solution to such challenges surrounding hyper-parameter tuning and that the study's findings can inform future design iterations of neural decoders for adaptive DBS and BCI.

Chronic corticosterone exposure impairs emotional regulation and cognitive function through disturbing neural oscillations in mice.

Corticosterone is a stress hormone, which is often associated with a variety of the central nervous system diseases. The study was to investigate the effects of Chronic corticosterone exposure (CCE) on the alteration of neural oscillatory patterns which supported a wide range of basic and higher cognitive activities, and a potential mechanism. Accordingly, a chronic corticosterone exposure model was established in C57BL mice. Behavioral experiments showed that emotion regulation and short-term working memory were significantly impaired in CCE mice. Neural oscillation analysis showed that the increase of corticosterone reduced the theta-band energy but increased the gamma-band energy in the hippocampus dentate gyrus (DG) region. Moreover, the theta rhythm synchronization between perforant path (PP) and DG, and the strength of theta-gamma cross-frequency coupling were significantly attenuated in CCE mice. Meanwhile, CCE treatment could inhibit the expression of PSD95, SYP and NMDAR2A/B and increased the expression of GAD67 and GABAR. These results suggest that CCE may lead to emotion regulation and short-term working memory dysfunction through disturbing neural activity patterns, which was closely associated with disrupting the excitatory-inhibitory balance.

Directional prefrontal-thalamic information flow is selectively required during spatial working memory retrieval.

Introduction: Spatial working memory is a kind of short-term memory that allows temporarily storing and manipulating spatial information. Evidence suggests that spatial working memory is processed through three distinctive phases: Encoding, maintenance, and retrieval. Though the medial prefrontal cortex (mPFC) and mediodorsal thalamus (MD) are involved in memory retrieval, how the functional interactions and information transfer between mPFC and MD remains largely unclear. Methods: We recorded local field potentials (LFPs) from mPFC and MD while mice performed a spatial working memory task in T-maze. The temporal dynamics of functional interactions and bidirectional information flow between mPFC and MD was quantitatively assessed by using directed transfer function. Results: Our results showed a significantly elevated information flow from mPFC to MD, varied in time and frequency (theta in particular), accompanying successful memory retrieval. Discussion: Elevated theta information flow, a feature that was absent on error trials, indicates an important role of the directional information transfer from mPFC to MD for memory retrieval.

Behavioral state-dependent oscillatory activity in prefrontal cortex induced by chronic social defeat stress.

Chronic stress contributes to the onset and exacerbation of major depressive disorder (MDD) through the oscillatory activity in the prefrontal cortex (PFC). However, the oscillations on which chronic social stress converges to yield the behavioral state of social avoidance are largely unknown. Here, we use a chronic social defeat stress model and in vivo electrophysiological recordings to uncover a novel neurophysiological measure that predicts the social behavioral state in stressed animals. First, in this study, we find that chronic social defeat stress model induces depression-like behaviors (anhedonia and social avoidance). Second, we find statistically significant differences in PFC oscillatory activity across different frequency ranges in social behavioral state, and the oscillatory activity correlates with stress-induced behavioral state. Finally, we show that the social behavioral states are accurately decoded from the oscillatory activity based on machine learning. Together, these results demonstrate that naturally occurring differences in PFC oscillation underlie the social behavioral state that accompanies the emergence of stress-induced behavioral dysfunction.

A dentate gyrus-CA3 inhibitory circuit promotes evolution of hippocampal-cortical ensembles during memory consolidation.

Memories encoded in the dentate gyrus (DG) ‒ CA3 circuit of the hippocampus are routed from CA1 to anterior cingulate cortex (ACC) for consolidation. Although CA1 parvalbumin inhibitory neurons (PV INs) orchestrate hippocampal-cortical communication, we know less about CA3 PV INs or DG ‒ CA3 principal neuron ‒ IN circuit mechanisms that contribute to evolution of hippocampal-cortical ensembles during memory consolidation. Using viral genetics to selectively mimic and boost an endogenous learning-dependent circuit mechanism, DG cell recruitment of CA3 PV INs and feed-forward inhibition (FFI) in CA3, in combination with longitudinal in vivo calcium imaging, we demonstrate that FFI facilitates formation and maintenance of context-associated neuronal ensembles in CA1. Increasing FFI in DG ‒ CA3 promoted context specificity of neuronal ensembles in ACC over time and enhanced long-term contextual fear memory. In vivo LFP recordings in mice with increased FFI in DG ‒ CA3 identified enhanced CA1 sharp-wave ripple ‒ ACC spindle coupling as a potential network mechanism facilitating memory consolidation. Our findings illuminate how FFI in DG ‒ CA3 dictates evolution of ensemble properties in CA1 and ACC during memory consolidation and suggest a teacher-like function for hippocampal CA1 in stabilization and re-organization of cortical representations.