Cerebellar nuclei cells produce distinct pathogenic spike signatures in mouse models of ataxia, dystonia, and tremor.

The cerebellum contributes to a diverse array of motor conditions, including ataxia, dystonia, and tremor. The neural substrates that encode this diversity are unclear. Here, we tested whether the neural spike activity of cerebellar output neurons is distinct between movement disorders with different impairments, generalizable across movement disorders with similar impairments, and capable of causing distinct movement impairments. Using in vivo awake recordings as input data, we trained a supervised classifier model to differentiate the spike parameters between mouse models for ataxia, dystonia, and tremor. The classifier model correctly assigned mouse phenotypes based on single-neuron signatures. Spike signatures were shared across etiologically distinct but phenotypically similar disease models. Mimicking these pathophysiological spike signatures with optogenetics induced the predicted motor impairments in otherwise healthy mice. These data show that distinct spike signatures promote the behavioral presentation of cerebellar diseases.

Intentional movement is fundamental to achieving many goals, whether they are as complicated as driving a car or as routine as feeding ourselves with a spoon. The cerebellum is a key brain area for coordinating such movement. Damage to this region can cause various movement disorders: ataxia (uncoordinated movement); dystonia (uncontrolled muscle contractions); and tremor (involuntary and rhythmic shaking). While abnormal electrical activity in the brain associated with movement disorders has been recorded for decades, previous studies often explored one movement disorder at a time. Therefore, it remained unclear whether the underlying brain activity is similar across movement disorders. Van der Heijden and Brown et al. analyzed recordings of neuron activity in the cerebellum of mice with movement disorders to create an activity profile for each disorder. The researchers then used machine learning to generate a classifier that could separate profiles associated with manifestations of ataxia, dystonia, and tremor based on unique features of their neural activity. The ability of the model to separate the three types of movement disorders indicates that abnormal movements can be distinguished based on neural activity patterns. When additional manifestations of these abnormal movements were considered, multiple mouse models of dystonia and tremor tended to show similar profiles. Ataxia models had several different types of neural activity that were all distinct from the dystonia and tremor profiles. After identifying the activity associated with each movement disorder, Van der Heijden and Brown et al. induced the same activity in the cerebella of healthy mice, which then caused the corresponding abnormal movements. These findings lay an important groundwork for the development of treatments for neurological disorders involving ataxia, dystonia, and tremor. They identify the cerebellum, and specific patterns of activity within it, as potential therapeutic targets. While the different activity profiles of ataxia may require more consideration, the neural activity associated with dystonia and tremor appears to be generalizable across multiple manifestations, suggesting potential treatments could be broadly applicable for these disorders.

[The role of astrocytes, circadian rhythms and light pollution in the pathogenesis of Alzheimer's disease]. / Rol' astrotsitov, tsirkadiannykh ritmov i «svetovogo zagryazneniya¼ v patogeneze bolezni Al'tsgeimera.

Currently, more and more importance is being attached to the interaction of brain neurons with astrocytes in order to study the pathogenesis, and in the future, to develop methods for the prevention, early diagnosis and treatment of neurodegenerative diseases of the brain. In this review article, the authors attempt to demonstrate the role of astrocytes, disturbances in circadian rhythms, sleep-wake patterns, and light pollution in the development of Alzheimer's disease. Based on the analysis of literature data, possible mechanisms of synchronization and desynchronization of these processes are presented.

Neural correlates of perisaccadic visual mislocalization in extrastriate cortex.

When interacting with the visual world using saccadic eye movements (saccades), the perceived location of visual stimuli becomes biased, a phenomenon called perisaccadic mislocalization. However, the neural mechanism underlying this altered visuospatial perception and its potential link to other perisaccadic perceptual phenomena have not been established. Using the electrophysiological recording of extrastriate areas in four male macaque monkeys, combined with a computational model, we were able to quantify spatial bias around the saccade target (ST) based on the perisaccadic dynamics of extrastriate spatiotemporal sensitivity captured by a statistical model. This approach could predict the perisaccadic spatial bias around the ST, consistent with behavioral data, and revealed the precise neuronal response components underlying representational bias. These findings also establish the crucial role of increased sensitivity near the ST for neurons with receptive fields far from the ST in driving the ST spatial bias. Moreover, we showed that, by allocating more resources for visual target representation, visual areas enhance their representation of the ST location, even at the expense of transient distortions in spatial representation. This potential neural basis for perisaccadic ST representation also supports a general role for extrastriate neurons in creating the perception of stimulus location.

Modeling and Analysis of Environmental Electromagnetic Interference in Multiple-Channel Neural Recording Systems for High Common-Mode Interference Rejection Performance.

Environmental electromagnetic interference (EMI) has always been a major interference source for multiple-channel neural recording systems, and little theoretical work has been attempted to address it. In this paper, equivalent circuit models are proposed to model both electromagnetic interference sources and neural signals in such systems, and analysis has been performed to generate the design guidelines for neural probes and the subsequent recording circuit towards higher common-mode interference (CMI) rejection performance while maintaining the recorded neural action potential (AP) signal quality. In vivo animal experiments with a configurable 32-channel neural recording system are carried out to validate the proposed models and design guidelines. The results show the power spectral density (PSD) of environmental 50 Hz EMI interference is reduced by three orders from 4.43 × 10-3 V2/Hz to 4.04 × 10-6 V2/Hz without affecting the recorded AP signal quality in an unshielded experiment environment.

Cholinergic input to mouse visual cortex signals a movement state and acutely enhances layer 5 responsiveness.

Acetylcholine is released in visual cortex by axonal projections from the basal forebrain. The signals conveyed by these projections and their computational significance are still unclear. Using two-photon calcium imaging in behaving mice, we show that basal forebrain cholinergic axons in the mouse visual cortex provide a binary locomotion state signal. In these axons, we found no evidence of responses to visual stimuli or visuomotor prediction errors. While optogenetic activation of cholinergic axons in visual cortex in isolation did not drive local neuronal activity, when paired with visuomotor stimuli, it resulted in layer-specific increases of neuronal activity. Responses in layer 5 neurons to both top-down and bottom-up inputs were increased in amplitude and decreased in latency, whereas those in layer 2/3 neurons remained unchanged. Using opto- and chemogenetic manipulations of cholinergic activity, we found acetylcholine to underlie the locomotion-associated decorrelation of activity between neurons in both layer 2/3 and layer 5. Our results suggest that acetylcholine augments the responsiveness of layer 5 neurons to inputs from outside of the local network, possibly enabling faster switching between internal representations during locomotion.

Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.

Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recently, plasmonic-based electrochemical impedance microscopy (P-EIM) was demonstrated for the label-free mapping of the ignition and propagation of action potentials in neuron cells with subcellular resolution. However, limited by the signal-to-noise ratio in the high-speed P-EIM video, action potential mapping was achieved by averaging 90 cycles of signals. Such extensive averaging is not desired and may not always be feasible due to factors such as neuronal desensitization. In this study, we utilized advanced signal processing techniques to detect action potentials in P-EIM extracted signals with fewer averaged cycles. Matched filtering successfully detected action potential signals with as few as averaging five cycles of signals. Long short-term memory (LSTM) recurrent neural network achieved the best performance and was able to detect single-cycle stimulated action potential successfully [satisfactory area under the receiver operating characteristic curve (AUC) equal to 0.855]. Therefore, we show that deep learning-based signal processing can dramatically improve the usability of P-EIM mapping of neuronal electrical signals.

Phospholipase C beta 1 in the dentate gyrus gates fear memory formation through regulation of neuronal excitability.

Memory processes rely on a molecular signaling system that balances the interplay between positive and negative modulators. Recent research has focused on identifying memory-regulating genes and their mechanisms. Phospholipase C beta 1 (PLCß1), highly expressed in the hippocampus, reportedly serves as a convergence point for signal transduction through G protein-coupled receptors. However, the detailed role of PLCß1 in memory function has not been elucidated. Here, we demonstrate that PLCß1 in the dentate gyrus functions as a memory suppressor. We reveal that mice lacking PLCß1 in the dentate gyrus exhibit a heightened fear response and impaired memory extinction, and this excessive fear response is repressed by upregulation of PLCß1 through its overexpression or activation using a newly developed optogenetic system. Last, our results demonstrate that PLCß1 overexpression partially inhibits exaggerated fear response caused by traumatic experience. Together, PLCß1 is crucial in regulating contextual fear memory formation and potentially enhancing the resilience to trauma-related conditions.

Emergent perceptual biases from state-space geometry in trained spiking recurrent neural networks.

A stimulus held in working memory is perceived as contracted toward the average stimulus. This contraction bias has been extensively studied in psychophysics, but little is known about its origin from neural activity. By training recurrent networks of spiking neurons to discriminate temporal intervals, we explored the causes of this bias and how behavior relates to population firing activity. We found that the trained networks exhibited animal-like behavior. Various geometric features of neural trajectories in state space encoded warped representations of the durations of the first interval modulated by sensory history. Formulating a normative model, we showed that these representations conveyed a Bayesian estimate of the interval durations, thus relating activity and behavior. Importantly, our findings demonstrate that Bayesian computations already occur during the sensory phase of the first stimulus and persist throughout its maintenance in working memory, until the time of stimulus comparison.

Retrosplenial inputs drive visual representations in the medial entorhinal cortex.

The importance of visual cues for navigation and goal-directed behavior is well established, although the neural mechanisms supporting sensory representations in navigational circuits are largely unknown. Navigation is fundamentally dependent on the medial entorhinal cortex (MEC), which receives direct projections from neocortical visual areas, including the retrosplenial cortex (RSC). Here, we perform high-density recordings of MEC neurons in awake, head-fixed mice presented with simple visual stimuli and assess the dynamics of sensory-evoked activity. We find that a large fraction of neurons exhibit robust responses to visual input. Visually responsive cells are located primarily in layer 3 of the dorsal MEC and can be separated into subgroups based on functional and molecular properties. Furthermore, optogenetic suppression of RSC afferents within the MEC strongly reduces visual responses. Overall, our results demonstrate that the MEC can encode simple visual cues in the environment that may contribute to neural representations of location necessary for accurate navigation.

Experience-dependent information routing through the basolateral amygdala shapes behavioral outcomes.

It is well established that the basolateral amygdala (BLA) is an emotional processing hub that governs a diverse repertoire of behaviors. Selective engagement of a heterogeneous cell population in the BLA is thought to contribute to this flexibility in behavioral outcomes. However, whether this process is impacted by previous experiences that influence emotional processing remains unclear. Here we demonstrate that previous positive (enriched environment [EE]) or negative (chronic unpredictable stress [CUS]) experiences differentially influence the activity of populations of BLA principal neurons projecting to either the nucleus accumbens core or bed nucleus of the stria terminalis. Chemogenetic manipulation of these projection-specific neurons can mimic or occlude the effects of CUS and EE on behavioral outcomes to bidirectionally control avoidance behaviors and stress-induced helplessness. These data demonstrate that previous experiences influence the responsiveness of projection-specific BLA principal neurons, biasing information routing through the BLA, to drive divergent behavioral outcomes.

Astroglial networks control visual responses of superior collicular neurons and sensory-motor behavior.

Astroglial networks closely interact with neuronal populations, but their functional contribution to neuronal representation of sensory information remains unexplored. The superior colliculus (SC) integrates multi-sensory information by generating distinct spatial patterns of neuronal functional responses to specific sensory stimulation. Here, we report that astrocytes from the mouse SC form extensive networks in the retinorecipient layer compared to visual cortex. This strong astroglial connectivity relies on high expression of gap-junction proteins. Genetic disruption of this connectivity functionally impairs SC retinotopic and orientation preference responses. These alterations are region specific, absent in primary visual cortex, and associated at the circuit level with a specific impairment of collicular neurons synaptic transmission. This has implications for SC-related visually induced innate behavior, as disrupting astroglial networks impairs light-evoked temporary arrest. Our results indicate that astroglial networks shape synaptic circuit activity underlying SC functional visual responses and play a crucial role in integrating visual cues to drive sensory-motor behavior.

Spiking Laguerre Volterra networks-predicting neuronal activity from local field potentials.

Objective.Understanding the generative mechanism between local field potentials (LFP) and neuronal spiking activity is a crucial step for understanding information processing in the brain. Up to now, most approaches have relied on simply quantifying the coupling between LFP and spikes. However, very few have managed to predict the exact timing of spike occurrence based on LFP variations.Approach.Here, we fill this gap by proposing novel spiking Laguerre-Volterra network (sLVN) models to describe the dynamic LFP-spike relationship. Compared to conventional artificial neural networks, the sLVNs are interpretable models that provide explainable features of the underlying dynamics.Main results.The proposed networks were applied on extracellular microelectrode recordings of Parkinson's Disease patients during deep brain stimulation (DBS) surgery. Based on the predictability of the LFP-spike pairs, we detected three neuronal populations with unique signal characteristics and sLVN model features.Significance.These clusters were indirectly associated with motor score improvement following DBS surgery, warranting further investigation into the potential of spiking activity predictability as an intraoperative biomarker for optimal DBS lead placement.

Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information.

When preparing a movement, we often rely on partial or incomplete information, which can decrement task performance. In behaving monkeys we show that the degree of cued target information is reflected in both, neural variability in motor cortex and behavioral reaction times. We study the underlying mechanisms in a spiking motor-cortical attractor model. By introducing a biologically realistic network topology where excitatory neuron clusters are locally balanced with inhibitory neuron clusters we robustly achieve metastable network activity across a wide range of network parameters. In application to the monkey task, the model performs target-specific action selection and accurately reproduces the task-epoch dependent reduction of trial-to-trial variability in vivo where the degree of reduction directly reflects the amount of processed target information, while spiking irregularity remained constant throughout the task. In the context of incomplete cue information, the increased target selection time of the model can explain increased behavioral reaction times. We conclude that context-dependent neural and behavioral variability is a signum of attractor computation in the motor cortex.

Tunable anti-ambipolar vertical bilayer organic electrochemical transistor enable neuromorphic retinal pathway.

Increasing demand for bio-interfaced human-machine interfaces propels the development of organic neuromorphic electronics with small form factors leveraging both ionic and electronic processes. Ion-based organic electrochemical transistors (OECTs) showing anti-ambipolarity (OFF-ON-OFF states) reduce the complexity and size of bio-realistic Hodgkin-Huxley(HH) spiking circuits and logic circuits. However, limited stable anti-ambipolar organic materials prevent the design of integrated, tunable, and multifunctional neuromorphic and logic-based systems. In this work, a general approach for tuning anti-ambipolar characteristics is presented through assembly of a p-n bilayer in a vertical OECT (vOECT) architecture. The vertical OECT design reduces device footprint, while the bilayer material tuning controls the anti-ambipolarity characteristics, allowing control of the device's on and off threshold voltages, and peak position, while reducing size thereby enabling tunable threshold spiking neurons and logic gates. Combining these components, a mimic of the retinal pathway reproducing the wavelength and light intensity encoding of horizontal cells to spiking retinal ganglion cells is demonstrated. This work enables further incorporation of conformable and adaptive OECT electronics into biointegrated devices featuring sensory coding through parallel processing for diverse artificial intelligence and computing applications.

Demixing fluorescence time traces transmitted by multimode fibers.

Optical methods based on thin multimode fibers (MMFs) are promising tools for measuring neuronal activity in deep brain regions of freely moving mice thanks to their small diameter. However, current methods are limited: while fiber photometry provides only ensemble activity, imaging techniques using of long multimode fibers are very sensitive to bending and have not been applied to unrestrained rodents yet. Here, we demonstrate the fundamentals of a new approach using a short MMF coupled to a miniscope. In proof-of-principle in vitro experiments, we disentangled spatio-temporal fluorescence signals from multiple fluorescent sources transmitted by a thin (200 µm) and short (8 mm) MMF, using a general unconstrained non-negative matrix factorization algorithm directly on the raw video data. Furthermore, we show that low-cost open-source miniscopes have sufficient sensitivity to image the same fluorescence patterns seen in our proof-of-principle experiment, suggesting a new avenue for novel minimally invasive deep brain studies using multimode fibers in freely behaving mice.

Outward potassium current in neurons of aestivated land snail Achatina fulica.

Aestivation and hibernation represent distinct forms of animal quiescence, characterized by physiological changes, including ion composition. Intracellular ion flows play a pivotal role in eliciting alterations in membrane potential and facilitating cellular communication, while outward K+ currents aid in the restitution and upkeep of the resting membrane potential. This study explores the relationship between inward and outward currents during aestivation in Achatina fulica snails. Specimens were collected near MSUBIT University in Shenzhen and divided into two groups. The first group was kept on a lattice diet, while the second one consisted of aestivating individuals, that were deprived of food and water until a cork-like structure sealed their shells. Recording of current from isolated neurons were conducted using the single-electrode voltage clamp mode with an AxoPatch 200B amplifier. Electrophysiological recordings on pedal ganglia neurons revealed significant differences in the inactivation processes of the Ia and Ikdr components. Alterations in the Ikdr component may inhibit pacemaker activity in pedal ganglion neurons, potentially contributing to locomotion cessation in aestivated animals. The KS current remains unaffected during aestivation. Changes in slow K+ current components could disrupt the resting membrane potential, possibly leading to cell depolarization and influx of Ca2+ and Na+ ions, impacting cell homeostasis. Thus, maintaining the constancy of outward K+ current is essential for cell stability.

Excitatory Projections of Wide Field Collicular Neurons to the Nucleus of the Optic Tract in the Rat.

The superficial layers of the mammalian superior colliculus (SC) contain neurons that are generally responsive to visual stimuli but can differ considerably in morphology and response properties. To elucidate the structure and function of these neurons, we combined extracellular recording and juxtacellular labeling, detailed anatomical reconstruction, and ultrastructural analysis of the synaptic contacts of labeled neurons, using transmission electron microscopy. Our labeled neurons project to different brainstem nuclei. Of particular importance are neurons that fit the morphological criteria of the wide field (WF) neurons and whose dendrites are horizontally oriented. They display a rather characteristic axonal projection pattern to the nucleus of optic tract (NOT); thus, we call them superior collicular WF projecting to the NOT (SCWFNOT) neurons. We corroborated the morphological characterization of this neuronal type as a distinct neuronal class with the help of unsupervised hierarchical cluster analysis. Our ultrastructural data demonstrate that SCWFNOT neurons establish excitatory connections with their targets in the NOT. Although, in rodents, the literature about the WF neurons has focused on their extensive projection to the lateral posterior nucleus of the thalamus, as a conduit for information to reach the visual association areas of the cortex, our data suggest that this subclass of WF neurons may participate in the optokinetic nystagmus.

The Neural Representation of Binaural Sound Localization Cues Across Different Subregions of the Chicken's Inferior Colliculus.

The sound localization behavior of the nocturnally hunting barn owl and its underlying neural computations is a textbook example of neuroethology. Differences in sound timing and level at the two ears are integrated in a series of well-characterized steps, from brainstem to inferior colliculus (IC), resulting in a topographical neural representation of auditory space. It remains an important question of brain evolution: How is this specialized case derived from a more plesiomorphic pattern? The present study is the first to match physiology and anatomical subregions in the non-owl avian IC. Single-unit responses in the chicken IC were tested for selectivity to different frequencies and to the binaural difference cues. Their anatomical origin was reconstructed with the help of electrolytic lesions and immunohistochemical identification of different subregions of the IC, based on previous characterizations in owl and chicken. In contrast to barn owl, there was no distinct differentiation of responses in the different subregions. We found neural topographies for both binaural cues but no evidence for a coherent representation of auditory space. The results are consistent with previous work in pigeon IC and chicken higher-order midbrain and suggest a plesiomorphic condition of multisensory integration in the midbrain that is dominated by lateral panoramic vision.

Neurofeedback training can modulate task-relevant memory replay rate in rats.

Hippocampal replay - the time-compressed, sequential reactivation of ensembles of neurons related to past experience - is a key neural mechanism of memory consolidation. Replay typically coincides with a characteristic pattern of local field potential activity, the sharp-wave ripple (SWR). Reduced SWR rates are associated with cognitive impairment in multiple models of neurodegenerative disease, suggesting that a clinically viable intervention to promote SWRs and replay would prove beneficial. We therefore developed a neurofeedback paradigm for rat subjects in which SWR detection triggered rapid positive feedback in the context of a memory-dependent task. This training protocol increased the prevalence of task-relevant replay during the targeted neurofeedback period by changing the temporal dynamics of SWR occurrence. This increase was also associated with neural and behavioral forms of compensation after the targeted period. These findings reveal short-timescale regulation of SWR generation and demonstrate that neurofeedback is an effective strategy for modulating hippocampal replay.

Attention: The blue spot reveals one of its secrets.

The locus coeruleus is the seat of a brain-wide neuromodulatory circuit. Using optogenetic and electrophysiological tools to selectively interrogate noradrenergic neurons in non-human primates, Ghosh and Maunsell show how locus coeruleus neurons contribute to a specific aspect of visual attention.