Record Neural Activity Research Articles

Circuits and mechanisms for TMS-induced corticospinal waves: Connecting sensitivity analysis to the network graph.

Transcranial magnetic stimulation (TMS) is a non-invasive, FDA-cleared treatment for neuropsychiatric disorders with broad potential for new applications, but the neural circuits that are engaged during TMS are still poorly understood. Recordings of neural activity from the corticospinal tract provide a direct readout of the response of motor cortex to TMS, and therefore a new opportunity to model neural circuit dynamics. The study goal was to use epidural recordings from the cervical spine of human subjects to develop a computational model of a motor cortical macrocolumn through which the mechanisms underlying the response to TMS, including direct and indirect waves, could be investigated. An in-depth sensitivity analysis was conducted to identify important pathways, and machine learning was used to identify common circuit features among these pathways. Sensitivity analysis identified neuron types that preferentially contributed to single corticospinal waves. Single wave preference could be predicted using the average connection probability of all possible paths between the activated neuron type and L5 pyramidal tract neurons (PTNs). For these activations, the total conduction delay of the shortest path to L5 PTNs determined the latency of the corticospinal wave. Finally, there were multiple neuron type activations that could preferentially modulate a particular corticospinal wave. The results support the hypothesis that different pathways of circuit activation contribute to different corticospinal waves with participation of both excitatory and inhibitory neurons. Moreover, activation of both afferents to the motor cortex as well as specific neuron types within the motor cortex initiated different I-waves, and the results were interpreted to propose the cortical origins of afferents that may give rise to certain I-waves. The methodology provides a workflow for performing computationally tractable sensitivity analyses on complex models and relating the results to the network structure to both identify and understand mechanisms underlying the response to acute stimulation.

Fabrication and evaluation of Wrap Around Neural-Pass to record and stimulate neural activity in the cervical spinal cord

Abstract We have successfully fabricated a Wrap Around Recording Electrode to record neural activity in the Cervical Spinal Cord (CSC) and a Wrap Around Stimulating Electrode to stimulate the CSC. These are used in the Wrap Around Neural-Pass to improve the QOL of patients with CSC injury by restoring motor, sensory, upper limb, and lower limb nerves minimally invasively that invades only the CSC. The fabricated electrodes had sufficient wrapping ability to be wrapped around the CSC of rats and could record neural activity in the rat’s spinal cord. We also clarified the optimal polymerization conditions for PEDOT used as the stimulating electrode material for the Wrap Around Stimulating Electrode, and the electrodes had low impedance, high Cathodal Charge Storage Capacity (CSCC), and Charge Injection Capacity (CIC) suitable for stimulating the CSC nerves.

Understanding the neural code of stress to control anhedonia.

Anhedonia, the diminished drive to seek, value, and learn about rewards, is a core feature of major depressive disorder1-3. The neural underpinnings of anhedonia and how this emotional state drives behaviour remain unclear. Here we investigated the neural code of anhedonia by taking advantage of the fact that when mice are exposed to traumatic social stress, susceptible animals become socially withdrawn and anhedonic, whereas others remain resilient. By performing high-density electrophysiology to record neural activity patterns in the basolateral amygdala (BLA) and ventral CA1 (vCA1), we identified neural signatures of susceptibility and resilience. When mice actively sought rewards, BLA activity in resilient mice showed robust discrimination between reward choices. By contrast, susceptible mice exhibited a rumination-like signature, in which BLA neurons encoded the intention to switch or stay on a previously chosen reward. Manipulation of vCA1 inputs to the BLA in susceptible mice rescued dysfunctional neural dynamics, amplified dynamics associated with resilience, and reversed anhedonic behaviour. Finally, when animals were at rest, the spontaneous BLA activity of susceptible mice showed a greater number of distinct neural population states. This spontaneous activity allowed us to decode group identity and to infer whether a mouse had a history of stress better than behavioural outcomes alone. This work reveals population-level neural dynamics that explain individual differences in responses to traumatic stress, and suggests that modulating vCA1-BLA inputs can enhance resilience by regulating these dynamics.

Advanced technologies for the study of neuronal cross-organ regulation: a narrative review

The nervous system plays an integral role in the homeostasis of living organisms through the regulation of multiple organ systems. Research has highlighted the extensive role of the nervous system in regulating organ function, including key aspects such as metabolic processes, respiratory, cardiovascular, and immune responses. These findings are inseparable from the development of new technologies such as viral tracing, optogenetics, whole-tissue imaging, and neural activity recording. As technology continues to advance, our understanding of the regulatory role of the nervous system in other organs has expanded to more complex cognitive and emotional control systems, such as the cerebral cortex and subcortical areas. Recent studies have also shown the bidirectional cross-organ regulatory mechanisms between the gut microbiota and the brain. In addition, the body–brain axis also monitors inflammatory responses to ensure a balance between proinflammatory and anti-inflammatory responses. This review delves into the intricate regulatory functions of the nervous system as they pertain to cross-organ communication, emphasizing the broader implications that extend beyond mere metabolic regulation. It employs cutting-edge technologies such as viral tracing, whole-tissue clearing, optogenetics, and in vivo neuronal activity recording to dissect the influence of the nervous system on various organs, including but not limited to the heart, liver, and spleen. These advanced methodologies have substantially broadened our comprehension of the fundamental operations of the nervous system within diverse physiological systems, revealing the complex neural networks that orchestrate organ-specific functions. Our review highlights the significant potential of advanced technologies in neuronal cross-organ regulation to pave the way for therapeutic strategies aimed at addressing a wide array of conditions that impact organ health.

Predicting modular functions and neural coding of behavior from a synaptic wiring diagram

A long-standing goal in neuroscience is to understand how a circuit’s form influences its function. Here, we reconstruct and analyze a synaptic wiring diagram of the larval zebrafish brainstem to predict key functional properties and validate them through comparison with physiological data. We identify modules of strongly connected neurons that turn out to be specialized for different behavioral functions, the control of eye and body movements. The eye movement module is further organized into two three-block cycles that support the positive feedback long hypothesized to underlie low-dimensional attractor dynamics in oculomotor control. We construct a neural network model based directly on the reconstructed wiring diagram that makes predictions for the cellular-resolution coding of eye position and neural dynamics. These predictions are verified statistically with calcium imaging-based neural activity recordings. This work demonstrates how connectome-based brain modeling can reveal previously unknown anatomical structure in a neural circuit and provide insights linking network form to function.

Ecological brain: reframing the study of human behaviour and cognition.

The last decade has seen substantial advances in the capacity to record behaviour and neural activity in humans in real-world settings, to simulate real-world situations in laboratory settings and to apply sophisticated analyses to large-scale data. Along with these developments, a growing number of groups has begun to advocate for real-world neuroscience and cognitive science. Here, we review the arguments and the available methods for real-world research and outline an overarching framework that embeds key ideas proposed in the literature integrating them into a cyclic process of 'bringing the lab to the real world' (recording behavioural and neural activity in real-world settings) and 'bringing the real-world to the lab' (manipulating the environments in which behaviours occur in the laboratory) that combines exploratory and confirmatory research and is interdisciplinary (including those sciences concerned with the natural, built or virtual environment). We highlight the benefits brought by this framework emphasizing the greater potential for novel discovery, theory development and human-centred applications to the environment.

Recording Neural Activity in Freely Moving Mice Using Fiber Photometry

Recording Neural Activity in Freely Moving Mice Using Fiber Photometry

Recording Neural Activity in Freely Moving Mice Using Fiber Photometry

Recording Neural Activity in Freely Moving Mice Using Fiber Photometry

Fabrication of Flat-Interface Nerve Electrodes for Recording Neural Activity

Fabrication of Flat-Interface Nerve Electrodes for Recording Neural Activity

Recording Neural Activity of Unfolded Hippocampal Tissue Using Penetrating Microelectrode Array

Recording Neural Activity of Unfolded Hippocampal Tissue Using Penetrating Microelectrode Array

Fabrication of Flat-Interface Nerve Electrodes for Recording Neural Activity

Fabrication of Flat-Interface Nerve Electrodes for Recording Neural Activity

Glassy Carbon Fiber‐Like Multielectrode Arrays for Neurochemical Sensing and Electrophysiology Recording

AbstractReal‐time measurement of neurochemical and electrophysiological activities in the living brain is vital for advancing neuroscience and understanding brain disorders. Carbon fiber microelectrodes (CFEs) have been widely utilized for in vivo electrochemical detection due to their subcellular size, biocompatibility, and desirable electrochemical properties, and CFE arrays have demonstrated excellent multi‐site chronic sensing of dopamine (DA) and neural activity recording capabilities. However, manual fabrication of CFE arrays lacks reproducibility and batch production capacity. Alternatively, photolithography enables batch fabrication of glassy carbon (GC) multielectrode arrays (GC‐MEAs) with high resolution and reproducibility, but the insertion of planar flexible MEAs poses challenges. In this study, GC fiber‐like (GCF) MEAs are presented and fabricated using photolithography. The GCF MEAs feature fiber‐like GC electrodes with small cross‐sections, facilitating self‐insertion into brain tissue without additional aids. Batch fabrication of GCF MEAs allows for customizable designs with minimal manual intervention. Comparative analysis with CFEs demonstrates improved electrochemical properties of GCF. In vivo experiments in mouse brains confirm the GCF MEAs' ability to measure neurotransmitter concentrations and record neural activities. This novel fabrication approach is promising for multimodal electrical and chemical measurements with minimal footprint, offering significant advancements in neural interface technology for neuroscience research and clinical applications.

Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages.

Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we have engineered robotic neural recording devices-'cranial exoskeletons'-that assist mice in maneuvering recording headstages that are orders of magnitude larger and heavier than the mice, while they navigate physical behavioral environments. We discovered optimal controller parameters that enable mice to locomote at physiologically realistic velocities while maintaining natural walking gaits. We show that mice learn to work with the robot to make turns and perform decision-making tasks. Robotic imaging and electrophysiology headstages were used to record recordings of Ca2+ activity of thousands of neurons distributed across the dorsal cortex and spiking activity of hundreds of neurons across multiple brain regions and multiple days, respectively.

Terminal differentiation precedes functional circuit integration in the peduncle neurons in regenerating Hydra vulgaris

Understanding how neural circuits are regenerated following injury is a fundamental question in neuroscience. Hydra is a powerful model for studying this process because it has a simple neural circuit structure, significant and reproducible regenerative abilities, and established methods for creating transgenics with cell-type-specific expression. While Hydra is a long-standing model for regeneration and development, little is known about how neural activity and behavior is restored following significant injury. In this study, we ask if regenerating neurons terminally differentiate prior to reforming functional neural circuits, or if neural circuits regenerate first and then guide the constituent naive cells toward their terminal fate. To address this question, we developed a dual-expression transgenic Hydra line that expresses a cell-type-specific red fluorescent protein (tdTomato) in ec5 peduncle neurons, and a calcium indicator (GCaMP7s) in all neurons. With this transgenic line, we can simultaneously record neural activity and track the reappearance of the terminally-differentiated ec5 neurons. Using SCAPE (Swept Confocally Aligned Planar Excitation) microscopy, we monitored both calcium activity and expression of tdTomato-positive neurons in 3D with single-cell resolution during regeneration of Hydra’s aboral end. The synchronized neural activity associated with a regenerated neural circuit was observed approximately 4 to 8 hours after expression of tdTomato in ec5 neurons. These data suggest that regenerating ec5 neurons undergo terminal differentiation prior to re-establishing their functional role in the nervous system. The combination of dynamic imaging of neural activity and gene expression during regeneration make Hydra a powerful model system for understanding the key molecular and functional processes involved in neural regeneration following injury.

Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics.

Transparent microelectrode arrays have proven useful in neural sensing, offering a clear interface for monitoring brain activity without compromising high spatial and temporal resolution. The current landscape of transparent electrode technology faces challenges in developing durable, highly transparent electrodes while maintaining low interface impedance and prioritizing scalable processing and fabrication methods. To address these limitations, we introduce artifact-resistant transparent MXene microelectrode arrays optimized for high spatiotemporal resolution recording of neural activity. With 60% transmittance at 550 nm, these arrays enable simultaneous imaging and electrophysiology for multimodal neural mapping. Electrochemical characterization shows low impedance of 563 ± 99 kΩ at 1 kHz and a charge storage capacity of 58 mC cm⁻² without chemical doping. In vivo experiments in rodent models demonstrate the transparent arrays' functionality and performance. In a rodent model of chemically-induced epileptiform activity, we tracked ictal wavefronts via calcium imaging while simultaneously recording seizure onset. In the rat barrel cortex, we recorded multi-unit activity across cortical depths, showing the feasibility of recording high-frequency electrophysiological activity. The transparency and optical absorption properties of Ti₃C₂Tx MXene microelectrodes enable high-quality recordings and simultaneous light-based stimulation and imaging without contamination from light-induced artifacts.

Mechanically adaptive and deployable intracortical probes enable long-term neural electrophysiological recordings

Flexible intracortical probes offer important opportunities for stable neural interfaces by reducing chronic immune responses, but their advances usually come with challenges of difficult implantation and limited recording span. Here, we reported a mechanically adaptive and deployable intracortical probe, which features a foldable fishbone-like structural design with branching electrodes on a temperature-responsive shape memory polymer (SMP) substrate. Leveraging the temperature-triggered soft-rigid phase transition and shape memory characteristic of SMP, this probe design enables direct insertion into brain tissue with minimal footprint in a folded configuration while automatically softening to reduce mechanical mismatches with brain tissue and deploying electrodes to a broader recording span under physiological conditions. Experimental and numerical studies on the material softening and structural folding-deploying behaviors provide insights into the design, fabrication, and operation of the intracortical probes. The chronically implanted neural probe in the rat cortex demonstrates that the proposed neural probe can reliably detect and track individual units for months with stable impedance and signal amplitude during long-term implantation. The work provides a tool for stable neural activity recording and creates engineering opportunities in basic neuroscience and clinical applications.

Quantifying physical degradation alongside recording and stimulation performance of 980 intracortical microelectrodes chronically implanted in three humans for 956-2246 days.

The clinical success of brain-machine interfaces depends on overcoming both biological and material challenges to ensure a long-term stable connection for neural recording and stimulation. Therefore, there is a need to quantify any damage that microelectrodes sustain when they are chronically implanted in the human cortex. Using scanning electron microscopy (SEM), we imaged 980 microelectrodes from Neuroport arrays chronically implanted in the cortex of three people with tetraplegia for 956-2246 days. We analyzed eleven multi-electrode arrays in total: eight arrays with platinum (Pt) electrode tips and three with sputtered iridium oxide tips (SIROF); one Pt array was left in sterile packaging, serving as a control. The arrays were implanted/explanted across three different clinical sites surgeries (Caltech/UCLA, Caltech/USC and APL/Johns Hopkins) in the anterior intraparietal area, Brodmann's area 5, motor cortex, and somatosensory cortex.Human experts rated the electron micrographs of electrodes with respect to five damage metrics: the loss of metal at the electrode tip, the amount of separation between the silicon shank and tip metal, tissue adherence or bio-material to the electrode, damage to the shank insulation and silicone shaft. These metrics were compared to functional outcomes (recording quality, noise, impedance and stimulation ability). Despite higher levels of physical degradation, SIROF electrodes were twice as likely to record neural activity than Pt electrodes (measured by SNR), at the time of explant. Additionally, 1 kHz impedance (measured in vivo prior to explant) significantly correlated with all physical damage metrics, recording, and stimulation performance for SIROF electrodes (but not Pt), suggesting a reliable measurement of in vivo degradation.We observed a new degradation type, primarily occurring on stimulated electrodes ("pockmarked" vs "cracked") electrodes; however, tip metalization damage was not significantly higher due to stimulation or amount of charge. Physical damage was centralized to specific regions of an array often with differences between outer and inner electrodes. This is consistent with degradation due to contact with the biologic milieu, influenced by variations in initial manufactured state. From our data, we hypothesize that erosion of the silicon shank often precedes damage to the tip metal, accelerating damage to the electrode / tissue interface. These findings link quantitative measurements, such as impedance, to the physical condition of the microelectrodes and their capacity to record and stimulate. These data could lead to improved manufacturing or novel electrode designs to improve long-term performance of BMIs making them are vitally important as multi-year clinical trials of BMIs are becoming more common.

Dense and persistent odor representations in the olfactory bulb of awake mice.

Recording and analysis of neural activity is often biased toward detecting sparse subsets of highly active neurons, masking important signals carried in low magnitude and variable responses. To investigate the contribution of seemingly noisy activity to odor encoding, we used mesoscale calcium imaging from mice of both sexes to record odor responses from the dorsal surface of bilateral olfactory bulbs (OBs). The outer layer of the mouse OB is comprised of dendrites organized into discrete "glomeruli", which are defined by odor receptor-specific sensory neuron input. We extracted activity from a large population of glomeruli and used logistic regression to classify odors from individual trials with high accuracy. We then used add-in and drop-out analyses to determine subsets of glomeruli necessary and sufficient for odor classification. Classifiers successfully predicted odor identity even after excluding sparse, highly active glomeruli, indicating that odor information is redundantly represented across a large population of glomeruli. Additionally, we found that Random Forest feature selection informed by Gini Inequality (RFGI) reliably ranked glomeruli by their contribution to overall odor classification. RFGI provided a measure of "feature importance" for each glomerulus that correlated with intuitive features like response magnitude. Finally, in agreement with previous work, we found that odor information persists in glomerular activity after odor offset. Together, our findings support a model of olfactory bulb odor coding where sparse activity is sufficient for odor identification, but information is widely, redundantly available across a large population of glomeruli, with each glomerulus representing information about more than one odor.Significance statement This study leverages meso-scale imaging and machine learning to investigate how odor information is first represented in the brain. Typically, recordings of neuronal activity focus on active individual cells, potentially overlooking broader variations in neuronal responses across populations. Our results demonstrate that a considerable amount of olfactory information is redundantly distributed across a large proportion of olfactory bulb glomeruli. Even after excluding a majority of glomeruli, odor identification remained possible. These findings indicate that, although a few glomeruli are sufficient for odor recognition, an abundance of additional information is represented across a broad population. Understanding how the brain manages redundant olfactory information will shed light on its adaptive mechanisms for navigating diverse real-world circumstances and responding to fluctuating internal states.

Applications of 2D Nanomaterials in Neural Interface.

Neural interfaces are crucial conduits between neural tissues and external devices, enabling the recording and modulation of neural activity. However, with increasing demand, simple neural interfaces are no longer adequate to meet the requirements for precision, functionality, and safety. There are three main challenges in fabricating advanced neural interfaces: sensitivity, heat management, and biocompatibility. The electrical, chemical, and optical properties of 2D nanomaterials enhance the sensitivity of various types of neural interfaces, while the newly developed interfaces do not exhibit adverse reactions in terms of heat management and biocompatibility. Additionally, 2D nanomaterials can further improve the functionality of these interfaces, including magnetic resonance imaging (MRI) compatibility, stretchability, and drug delivery. In this review, we examine the recent applications of 2D nanomaterials in neural interfaces, focusing on their contributions to enhancing performance and functionality. Finally, we summarize the advantages and disadvantages of these nanomaterials, analyze the importance of biocompatibility testing for 2D nanomaterials, and propose that improving and developing composite material structures to enhance interface performance will continue to lead the forefront of this field.

Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation

Objective.Micro-electrocorticographic (μECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to useμECoG arrays to decode, in rats, body position during open field navigation, through isolated single-unit activities.Approach. μECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300-3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns.Main results.Single-unit spikes could be extracted during chronic recording fromμECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson's r of 0.607 and 0.571, respectively.Significance. μECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface.