Neuronal Ensemble Activity Research Articles

Transformer-based classification of visceral pain-related local field potential patterns in the brain

Neuronal ensemble activity entrained by local field potential (LFP) patterns underlies a variety of brain functions, including emotion, cognition, and pain perception. Recent advances in machine learning approaches may enable more effective methods for analyzing LFP patterns across multiple brain areas than conventional time-frequency analysis. In this study, we tested the performance of two machine learning algorithms, AlexNet and the Transformer models, to classify LFP patterns in eight pain-related brain regions before and during acetic acid-induced visceral pain behaviors. Over short time windows lasting several seconds, applying AlexNet to LFP power datasets, but not to raw time-series LFP traces from multiple brain areas, successfully achieved superior classification performance compared with simple LFP power analysis. Furthermore, applying the Transformer directly to the raw LFP traces achieved significantly superior classification performance than AlexNet when using LFP power datasets. These results demonstrate the utility of the Transformer in the analysis of neurophysiological signals, and pave the way for its future applications in the decoding of more complex neuronal activity patterns.

Spatial context non-uniformly modulates inter-laminar information flow in the primary visual cortex.

Our visual experience is a result of the concerted activity of neuronal ensembles in the sensory hierarchy. Yet, how the spatial organization of objects influences this activity remains poorly understood. We investigate how inter-laminar information flow within the primary visual cortex (V1) is affected by visual stimuli in isolation or with flankers at spatial configurations that are known to cause non-uniform degradation of perception. By employing dimensionality reduction approaches to simultaneous, layer-specific population recordings, we establish that information propagation between cortical layers occurs along a structurally stable communication subspace. The spatial configuration of contextual stimuli differentially modulates inter-laminar communication efficacy, the balance of feedforward and effective feedback signaling, and contextual signaling in the superficial layers. Remarkably, these modulations mirror the spatially non-uniform aspects of perceptual degradation. Our results suggest a model of retinotopically non-uniform cortical connectivity in the output layers of V1 that influences information flow in the sensory hierarchy.

Experience of Euclidean geometry sculpts the development and dynamics of rodent hippocampal sequential cell assemblies

Euclidean space is the fabric of the world we live in. Whether and how geometric experience shapes our spatial-temporal representations of the world remained unknown. We deprived male rats of experience with crucial features of Euclidean geometry by rearing them inside spheres, and compared activity of large hippocampal neuronal ensembles during navigation and sleep with that of cuboid cage-reared controls. Sphere-rearing from birth permitted emergence of accurate neuronal ensemble spatial codes and preconfigured and plastic time-compressed neuronal sequences. However, sphere-rearing led to diminished individual place cell tuning, more similar neuronal mapping of different track ends/corners, and impaired pattern separation and plasticity of multiple linear tracks, coupled with reduced preconfigured sleep network repertoires. Subsequent experience with multiple linear environments over four days largely reversed these effects. Thus, early-life experience with Euclidean geometry enriches the hippocampal repertoire of preconfigured neuronal patterns selected toward unique representation and discrimination of multiple linear environments.

Firing rate models for gamma oscillations in I-I and E-I networks.

Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional Wilson-Cowan-like models, even when extended to include an explicit dynamic synaptic activation variable, are found unable to capture some dynamics such as Interneuronal Network Gamma oscillations (ING). Use of an explicit delay is helpful in simulations at the expense of complicating mathematical analysis. We resolve this issue by introducing a dynamic variable, u, that acts as an effective delay in the negative feedback loop between firing rate (r) and synaptic gating of inhibition (s). In effect, u endows synaptic activation with second order dynamics. With linear stability analysis, numerical branch-tracking and simulations, we show that our r-u-s rate model captures some key qualitative features of spiking network models for ING. We also propose an alternative formulation, a v-u-s model, in which mean membrane potential v satisfies an averaged current-balance equation. Furthermore, we extend the framework to E-I networks. With our six-variable v-u-s model, we demonstrate in firing rate models the transition from Pyramidal-Interneuronal Network Gamma (PING) to ING by increasing the external drive to the inhibitory population without adjusting synaptic weights. Having PING and ING available in a single network, without invoking synaptic blockers, is plausible and natural for explaining the emergence and transition of two different types of gamma oscillations.

Laminar pattern of sensory-evoked dynamic high-frequency oscillatory activity in the macaque auditory cortex.

High-frequency (>60Hz) neuroelectric signals likely have functional roles distinct from low-frequency (<30Hz) signals. While high-gamma activity (>60Hz) does not simply equate to neuronal spiking, they are highly correlated, having similar information encoding. High-gamma activity is typically considered broadband and poorly phase-locked to sensory stimuli and thus is typically analyzed after transformations into absolute amplitude or spectral power. However, those analyses discard signal polarity, compromising the interpretation of neuroelectric events that are essentially dipolar. In the spectrotemporal profiles of field potentials in auditory cortex, we show high-frequency spectral peaks not phase-locked to sound onset, which follow the broadband peak of phase-locked onset responses. Isolating the signal components comprising the high-frequency peaks reveals narrow-band high-frequency oscillatory events, whose instantaneous frequency changes rapidly from >150 to 60Hz, which may underlie broadband high-frequency spectral peaks in previous reports. The laminar amplitude distributions of the isolated activity had two peak positions, while the laminar phase patterns showed a counterphase relationship between those peaks, indicating the formation of dipoles. Our findings suggest that nonphase-locked HGA arises in part from oscillatory or recurring activity of supragranular-layer neuronal ensembles in auditory cortex.

Single-Trial Representations of Decision-Related Variables by Decomposed Frontal Corticostriatal Ensemble Activity.

The frontal cortex-striatum circuit plays a pivotal role in adaptive goal-directed behaviors. However, it remains unclear how decision-related signals are mediated through cross-regional transmission between the medial frontal cortex and the striatum by neuronal ensembles in making decision based on outcomes of past action. Here, we analyzed neuronal ensemble activity obtained through simultaneous multiunit recordings in the secondary motor cortex (M2) and dorsal striatum (DS) in rats performing an outcome-based left-or-right choice task. By adopting tensor component analysis (TCA), a single-trial-based unsupervised dimensionality reduction approach, for concatenated ensembles of M2 and DS neurons, we identified distinct three spatiotemporal neural dynamics (TCA components) at the single-trial level specific to task-relevant variables. Choice-position-selective neural dynamics reflected the positions chosen and was correlated with the trial-to-trial fluctuation of behavioral variables. Intriguingly, choice-pattern-selective neural dynamics distinguished whether the incoming choice was a repetition or a switch from the previous choice before a response choice. Other neural dynamics was selective to outcome and increased within-trial activity following response. Our results demonstrate how the concatenated ensembles of M2 and DS process distinct features of decision-related signals at various points in time. Thereby, the M2 and DS collaboratively monitor action outcomes and determine the subsequent choice, whether to repeat or switch, for action selection.

A method to find temporal structure of neuronal coactivity patterns with across-trial correlations

BackgroundThe across-trial correlation of neurons' coactivity patterns emerges to be important for information coding, but methods for finding their temporal structures remain largely unexplored. New methodIn the present study, we propose a method to find time clusters in which coactivity patterns of neurons are correlated across trials. We transform the multidimensional neural activity at each timing into a coactivity pattern of binary states, and predict the coactivity patterns at different timings. We devise a method suitable for these coactivity pattern predictions, call general event prediction. Cross-temporal prediction accuracy is then used to estimate across-trial correlations between coactivity patterns at two timings. We extract time clusters from the cross-temporal prediction accuracy by a modified k-means algorithm. ResultsThe feasibility of the proposed method is verified through simulations based on ground truth. We apply the proposed method to a calcium imaging dataset recorded from the motor cortex of mice, and demonstrate time clusters of motor cortical coactivity patterns during a motor task. Comparison with existing methodsWhile the existing cosine similarity method, which does not account for across-trial correlation, shows temporal structures only for contralateral neural responses, the proposed method reveals those for both contralateral and ipsilateral neural responses, demonstrating the effect of across-trial correlations. ConclusionsThis study introduces a novel method for measuring the temporal structure of neuronal ensemble activity.

Real-time multimodal sensory detection using widefield hippocampal calcium imaging

The hippocampus is a complex structure that has a major role in learning and memory. It also integrates information from multisensory modalities, supporting a comprehensive cognitive map for both spatial and non-spatial information. Previous studies have been limited to real-time spatial decoding, typically using electrodes. However, decoding hippocampal non-spatial information in real time has not been previously described. Here, we have constructed a real-time optical decoder driven by the calcium activity of large neuronal ensembles to decode spatial, visual, and auditory information effectively. Using advanced machine learning techniques, our rapid end-to-end decoding achieves high accuracy and provides a multisensory modality detection method. This method enables the real-time investigation of hippocampal neural coding and allows for direct neural communication with animals and patients affected by functional impairments. The ability to decode multimodal sensory inputs in real time thus forms the basis for an all-optical brain-computer interface.

Visuotactile integration facilitates mirror-induced self-directed behavior through activation of hippocampal neuronal ensembles in mice

Remembering the visual features of oneself is critical for self-recognition. However, the neural mechanisms of how the visual self-image is developed remain unknown because of the limited availability of behavioral paradigms in experimental animals. Here, we demonstrate a mirror-induced self-directed behavior (MSB) in mice, resembling visual self-recognition. Mice displayed increased mark-directed grooming to remove ink placed on their heads when an ink-induced visual-tactile stimulus contingency occurred. MSB required mirror habituation and social experience. The chemogenetic inhibition of dorsal or ventral hippocampal CA1 (vCA1) neurons attenuated MSB. Especially, a subset of vCA1 neurons activated during the mirror exposure was significantly reactivated during re-exposure to the mirror and was necessary for MSB. The self-responding vCA1 neurons were also reactivated when mice were exposed to a conspecific of the same strain. These results suggest that visual self-image may be developed through social experience and mirror habituation and stored in a subset of vCA1 neurons.

A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics.

Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computational modules of large-scale models of brain function, maintaining the specificity of local cortical microcircuits. While MFs have been generated for the isocortex, they are still missing for other parts of the brain. Here we have designed and simulated a multi-layer MF of the cerebellar microcircuit (including Granule Cells, Golgi Cells, Molecular Layer Interneurons, and Purkinje Cells) and validated it against experimental data and the corresponding spiking neural network (SNN) microcircuit model. The cerebellar MF was built using a system of equations, where properties of neuronal populations and topological parameters are embedded in inter-dependent transfer functions. The model time constant was optimised using local field potentials recorded experimentally from acute mouse cerebellar slices as a template. The MF reproduced the average dynamics of different neuronal populations in response to various input patterns and predicted the modulation of the Purkinje Cells firing depending on cortical plasticity, which drives learning in associative tasks, and the level of feedforward inhibition. The cerebellar MF provides a computationally efficient tool for future investigations of the causal relationship between microscopic neuronal properties and ensemble brain activity in virtual brain models addressing both physiological and pathological conditions.

Quantification of prefrontal cortical neuronal ensembles following conditioned fear learning in a Fos-LacZ transgenic rat with photoacoustic imaging in Vivo

Understanding the neurobiology of complex behaviors requires measurement of activity in the discrete population of active neurons, neuronal ensembles, which control the behavior. Conventional neuroimaging techniques ineffectively measure neuronal ensemble activity in the brain in vivo because they assess the average regional neuronal activity instead of the specific activity of the neuronal ensemble that mediates the behavior. Our functional molecular photoacoustic tomography (FM-PAT) system allows direct imaging of Fos-dependent neuronal ensemble activation in Fos-LacZ transgenic rats in vivo. We tested four experimental conditions and found increased FM-PAT signal in prefrontal cortical areas in rats undergoing conditioned fear or novel context exposure. A parallel immunofluorescence ex vivo study of Fos expression found similar findings. These findings demonstrate the ability of FM-PAT to measure Fos-expressing neuronal ensembles directly in vivo and support a mechanistic role for the prefrontal cortex in higher-order processing of response to specific stimuli or environmental cues.

Speech Reception in Young Children with Autism Is Selectively Indexed by a Neural Oscillation Coupling Anomaly.

Communication difficulties are one of the core criteria in diagnosing autism spectrum disorder (ASD), and are often characterized by speech reception difficulties, whose biological underpinnings are not yet identified. This deficit could denote atypical neuronal ensemble activity, as reflected by neural oscillations. Atypical cross-frequency oscillation coupling, in particular, could disrupt the joint tracking and prediction of dynamic acoustic stimuli, a dual process that is essential for speech comprehension. Whether such oscillatory anomalies already exist in very young children with ASD, and with what specificity they relate to individual language reception capacity is unknown. We collected neural activity data using electroencephalography (EEG) in 64 very young children with and without ASD (mean age 3; 17 females, 47 males) while they were exposed to naturalistic-continuous speech. EEG power of frequency bands typically associated with phrase-level chunking (δ, 1-3 Hz), phonemic encoding (low-γ, 25-35 Hz), and top-down control (β, 12-20 Hz) were markedly reduced in ASD relative to typically developing (TD) children. Speech neural tracking by δ and θ (4-8 Hz) oscillations was also weaker in ASD compared with TD children. After controlling gaze-pattern differences, we found that the classical θ/γ coupling was replaced by an atypical β/γ coupling in children with ASD. This anomaly was the single most specific predictor of individual speech reception difficulties in ASD children. These findings suggest that early interventions (e.g., neurostimulation) targeting the disruption of β/γ coupling and the upregulation of θ/γ coupling could improve speech processing coordination in young children with ASD and help them engage in oral interactions.SIGNIFICANCE STATEMENT Very young children already present marked alterations of neural oscillatory activity in response to natural speech at the time of autism spectrum disorder (ASD) diagnosis. Hierarchical processing of phonemic-range and syllabic-range information (θ/γ coupling) is disrupted in ASD children. Abnormal bottom-up (low-γ) and top-down (low-β) coordination specifically predicts speech reception deficits in very young ASD children, and no other cognitive deficit.

Mesoscale calcium imaging in vivo: evolution and contribution to developmental neuroscience.

Calcium imaging is commonly used to visualize neural activity in vivo. In particular, mesoscale calcium imaging provides large fields of view, allowing for the simultaneous interrogation of neuron ensembles across the neuraxis. In the field of Developmental Neuroscience, mesoscopic imaging has recently yielded intriguing results that have shed new light on the ontogenesis of neural circuits from the first stages of life. We summarize here the technical approaches, basic notions for data analysis and the main findings provided by this technique in the last few years, with a focus on brain development in mouse models. As new tools develop to optimize calcium imaging in vivo, basic principles of neural development should be revised from a mesoscale perspective, that is, taking into account widespread activation of neuronal ensembles across the brain. In the future, combining mesoscale imaging of the dorsal surface of the brain with imaging of deep structures would ensure a more complete understanding of the construction of circuits. Moreover, the combination of mesoscale calcium imaging with other tools, like electrophysiology or high-resolution microscopy, will make up for the spatial and temporal limitations of this technique.

Sevoflurane-induced amnesia is associated with inhibition of hippocampal cell ensemble activity after learning

General anesthesia could induce amnesia, however the mechanism remains unclear. We hypothesized that suppression of neuronal ensemble activity in the hippocampus by anesthesia during the post-learning period causes retrograde amnesia. To test this hypothesis, two experiments were conducted with sevoflurane anesthesia (2.5%, 30 min): a hippocampus-dependent memory task, the context pre-exposure facilitation effect (CPFE) procedure to measure memory function and in vivo calcium imaging to observe neural activity in hippocampal CA1 during context exploration and sevoflurane/home cage session. Sevoflurane treatment just after context pre-exposure session impaired the CPFE memory, suggesting sevoflurane induced retrograde amnesia. Calcium imaging showed sevoflurane treatment prevented neuronal activity in CA1. Further analysis of neuronal activity with non-negative matrix factorization, which extracts neural ensemble activity based on synchronous activity, showed that sevoflurane treatment reduced the reactivation of neuronal ensembles between during context exploration just before and one day after sevoflurane inhalation. These results suggest that sevoflurane treatment immediately after learning induces amnesia, resulting from suppression of reactivation of neuronal ensembles.

Retraction of Astrocyte Leaflets From the Synapse Enhances Fear Memory

BackgroundThe formation and retrieval of fear memories depends on orchestrated synaptic activity of neuronal ensembles within the hippocampus, and it is becoming increasingly evident that astrocytes residing in the environment of these synapses play a central role in shaping cellular memory representations. Astrocyte distal processes, known as leaflets, fine-tune synaptic activity by clearing neurotransmitters and limiting glutamate diffusion. However, how astroglial synaptic coverage contributes to mnemonic processing of fearful experiences remains largely unknown. MethodsWe used electron microscopy to observe changes in astroglial coverage of hippocampal synapses during consolidation of fear memory in mice. To manipulate astroglial synaptic coverage, we depleted ezrin, an integral leaflet-structural protein, from hippocampal astrocytes using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 gene editing. Next, a combination of Föster resonance energy transfer analysis, genetically encoded glutamate sensors, and whole-cell patch-clamp recordings was used to determine whether the proximity of astrocyte leaflets to the synapse is critical for synaptic integrity and function. ResultsWe found that consolidation of a recent fear memory is accompanied by a transient retraction of astrocyte leaflets from hippocampal synapses and increased activation of NMDA receptors. Accordingly, astrocyte-specific depletion of ezrin resulted in shorter astrocyte leaflets and reduced astrocyte contact with the synaptic cleft, which consequently boosted extrasynaptic glutamate diffusion and NMDA receptor activation. Importantly, after fear conditioning, these cellular phenotypes translated to increased retrieval-evoked activation of CA1 pyramidal neurons and enhanced fear memory expression. ConclusionsTogether, our data show that withdrawal of astrocyte leaflets from the synaptic cleft is an experience-induced, temporally regulated process that gates the strength of fear memories.

β Bursting in the Retrosplenial Cortex Is a Neurophysiological Correlate of Environmental Novelty Which Is Disrupted in a Mouse Model of Alzheimer's Disease.

The retrosplenial cortex (RSC) plays a significant role in spatial learning and memory and is functionally disrupted in the early stages of Alzheimer's disease (AD). In order to investigate neurophysiological correlates of spatial learning and memory in this region we employed in vivo electrophysiology in awake and freely moving male mice, comparing neural activity between wild-type and J20 mice, a transgenic model of AD-associated amyloidopathy. To determine the response of the RSC to environmental novelty local field potentials (LFPs) were recorded while mice explored novel and familiar recording arenas. In familiar environments we detected short, phasic bursts of β (20-30 Hz) oscillations (β bursts), which arose at a low but steady rate. Exposure to a novel environment rapidly initiated a dramatic increase in the rate, size and duration of β bursts. Additionally, θ-α/β cross-frequency coupling was significantly higher during novelty, and spiking of neurons in the RSC was significantly enhanced during β bursts. Finally, excessive β bursting was seen in J20 mice, including increased β bursting during novelty and familiarity, yet a loss of coupling between β bursts and spiking activity. These findings support the concept that β bursting may be responsible for the activation and reactivation of neuronal ensembles underpinning the formation and maintenance of cortical representations, and that disruptions to this activity in J20 mice may underlie cognitive impairments seen in these animals.SIGNIFICANCE STATEMENT The retrosplenial cortex (RSC) is thought to be involved in the formation, recall and consolidation of contextual memory. The discovery of bursts of β oscillations in this region, which are associated with increased neuronal spiking and strongly upregulated while mice explore novel environments, provides a potential mechanism for the activation of neuronal ensembles, which may underlie the formation of cortical representations of context. Excessive β bursting in the RSC of J20 mice, a mouse model of Alzheimer's disease (AD), alongside the disassociation of β bursting from neuronal spiking, may underlie spatial memory impairments previously shown in these mice. These findings introduce a novel neurophysiological correlate of spatial learning and memory, and a potentially new form of AD-related cortical dysfunction.

Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity.

Apolipoprotein E4 (APOE4) is the greatest known genetic risk factor for developing sporadic Alzheimer's disease. How the interaction of APOE4 microglia with neurons differs from microglia expressing the disease-neutral APOE3 allele remains unknown. Here, we employ CRISPR-edited induced pluripotent stem cells (iPSCs) to dissect the impact of APOE4 in neuron-microglia communication. Our results reveal that APOE4 induces a lipid-accumulated state that renders microglia weakly responsive to neuronal activity. By examining the transcriptional signatures of APOE3 versus APOE4 microglia in response to neuronal conditioned media, we established that neuronal cues differentially induce a lipogenic program in APOE4 microglia that exacerbates pro-inflammatory signals. Through decreased uptake of extracellular fatty acids and lipoproteins, we identified that APOE4 microglia disrupts the coordinated activity of neuronal ensembles. These findings suggest that abnormal neuronal network-level disturbances observed in Alzheimer's disease patients harboring APOE4 may in part be triggered by impairment in lipid homeostasis in non-neuronal cells.

Conceptual framework for neuronal ensemble identification and manipulation related to behavior using calcium imaging.

.SignificanceThe identification and manipulation of spatially identified neuronal ensembles with optical methods have been recently used to prove the causal link between neuronal ensemble activity and learned behaviors. However, the standardization of a conceptual framework to identify and manipulate neuronal ensembles from calcium imaging recordings is still lacking.AimWe propose a conceptual framework for the identification and manipulation of neuronal ensembles using simultaneous calcium imaging and two-photon optogenetics in behaving mice.ApproachWe review the computational approaches that have been used to identify and manipulate neuronal ensembles with single cell resolution during behavior in different brain regions using all-optical methods.ResultsWe proposed three steps as a conceptual framework that could be applied to calcium imaging recordings to identify and manipulate neuronal ensembles in behaving mice: (1) transformation of calcium transients into binary arrays; (2) identification of neuronal ensembles as similar population vectors; and (3) targeting of neuronal ensemble members that significantly impact behavioral performance.ConclusionsThe use of simultaneous two-photon calcium imaging and two-photon optogenetics allowed for the experimental demonstration of the causal relation of population activity and learned behaviors. The standardization of analytical tools to identify and manipulate neuronal ensembles could accelerate interventional experiments aiming to reprogram the brain in normal and pathological conditions.

A luciferase prosubstrate and a red bioluminescent calcium indicator for imaging neuronal activity in mice

Although fluorescent indicators have been broadly utilized for monitoring bioactivities, fluorescence imaging, when applied to mammals, is limited to superficial targets or requires invasive surgical procedures. Thus, there is emerging interest in developing bioluminescent indicators for noninvasive mammalian imaging. Bioluminescence imaging (BLI) of neuronal activity is highly desired but hindered by insufficient photons needed to digitalize fast brain activities. In this work, we develop a luciferase prosubstrate deliverable at an increased dose and activated in vivo by nonspecific esterase. We further engineer a bright, bioluminescent indicator with robust responsiveness to calcium ions (Ca2+) and appreciable emission above 600 nm. Integration of these advantageous components enables the imaging of the activity of neuronal ensembles in awake mice minimally invasively with excellent signal-to-background and subsecond temporal resolution. This study thus establishes a paradigm for studying brain function in health and disease.

P391. Impact of Subanesthetic Ketamine on Neural Spiking Dynamics in Frontal Cortex

Ketamine at subanesthetic doses is a rapid-acting antidepressant, however the neurobiological mechanisms underpinning its therapeutic action remain unclear. Here, we examined the acute effects of ketamine on firing activity of neuronal ensembles in frontal cortex.