Single Unit publications

Implantable microelectrode arrays (MEAs) are powerful tools for neurophysiological studies and hold tremendous potential as a key component of clinical neuroprostheses. However, their long-term efficacy is hampered by inflammatory responses to implantation. This study examines the impact of MEA substrate rigidity on neural recording quality and inflammatory tissue responses. We implanted stiff silicon-based and flexible polyimide-based MEAs with similar geometries in the deep brain region of the mouse striatum and performed weekly impedance and electrophysiological measurements over 4 weeks. The flexible MEAs demonstrated more reliable recording quality in terms of stable signal-to-noise ratio, single-unit yield, peak-to-peak amplitude, noise, and impedance, compared to the stiff probes, whose performance deteriorated over time. Endpoint histological analyses were performed to assess the glial scarring (Iba-1, GFAP), blood-brain barrier integrity (IgG), mechanosensitive ion channel expression (Piezo1), and neuronal population (NeuN and NF200) around the implant site. We found reduced microglial activation and IgG fouling within a 50-μm radius around the flexible MEAs compared to the stiff group. Additionally, a higher expression of Piezo1 was observed localized around the stiff MEA, correlating positively with increased Iba-1 and GFAP intensity. Our results show that flexible MEAs have improved device-tissue integration, indicated by lower inflammation levels and better recording stability. This research underscores the critical role of MEA substrate rigidity in influencing adverse tissue reactions, especially for deep brain regions. This understanding will improve our ability to design stable and reliable devices for chronic neural interface devices and beyond.

This work presents three open datasets featuring various levels of processing, containing neural recordings from the auditory cortex of rats. These recordings were obtained during experiments using the auditory oddball paradigm before, during and after the local microiontophoretic application of acetylcholine. The primary objective of these datasets is to investigate how the brain processes predictable versus unexpected auditory stimuli, and the role of cholinergic inputs during such processing. The data include multi-unit recordings of neuronal activity during the presentation of standard and deviant tones, classified by stimulus type and cortical sub-region. These resources enable quantitative investigations of deviance detection, stimulus-specific adaptation, cholinergic modulation and predictive-coding mechanisms at multiple temporal scales.

The hippocampus is classically linked to memory, yet increasing evidence points to a broader role in perceptual inference and deviance detection. Predictive coding theories propose that perception minimizes mismatches between expected and actual sensory input, expressed in neural signatures such as mismatch negativity (MMN) and P300. Although MMN arises mainly from sensory and prefrontal cortices, the hippocampus is anatomically interconnected with both and may also contribute to prediction error processing. We recorded single- and multi-unit activity and local field potentials (LFPs) from DG and CA1 in urethane-anesthetized rats during an auditory oddball paradigm and a no-repetition control sequence to dissociate prediction error from repetition suppression. Approximately 20% of hippocampal neurons were sound responsive, and a subset showed deviant selectivity. Spiking activity predominantly reflected prediction errors, while LFPs revealed complementary contributions from repetition suppression and prediction error. Early LFP components were enhanced for randomly presented deviants, whereas later components within the P300 latency range were stronger for predictable deviants, indicating temporally distinct phases of error signaling and top-down modulation. These findings identify the hippocampus as an active contributor to auditory deviance detection and support a hierarchical model in which hippocampal circuits participate in predictive sensory processing beyond memory.

Vasomotion, vascular oscillations at ~ 0.1 Hz, may serve as a biomarker and therapeutic target for neurodegenerative diseases, but its origins, structure across brain vasculature, and correlation with neural activity remain unclear. This study examined the spatiotemporal characteristics of cerebral vasomotion and its relationship to neural activity in anaesthetised Hooded Lister rats using simultaneous recordings of neuronal activity and haemodynamics in motor and whisker barrel cortices. In a subset of rats, tissue oxygen was also measured. Blood pressure was pharmacologically modulated to alter vascular oscillations. We found that vasomotion was driven by the arterial tree. Two prominent activity patterns emerged: fast vasomotion across the entire hemisphere and slow vasomotion seen as a travelling wave running through the surface arteries. Moreover, vasomotion was associated with low tissue oxygen and was largely independent of spontaneous neural activity and therefore not a product of neurovascular coupling.

Objective. Infrared neural stimulation (INS) has emerged as a potent neuromodulation technology, offering safe and focal stimulation with superior spatial recruitment profiles compared to conventional electrical methods. However, the neural dynamics induced by INS stimulation remain poorly understood. Elucidating these dynamics will help develop new INS stimulation paradigms and advance its clinical application. Approach. In this study, we assessed the local network dynamics of INS entrainment in the auditory thalamocortical circuit using the chronically implanted rat model. Our approach focused on measuring INS energy-based local field potential (LFP) recruitment induced by focal thalamocortical stimulation. We further characterized linear and nonlinear oscillatory LFP activity in response to single-pulse and periodic INS and performed spectral decomposition to uncover specific LFP band entrainment to INS. Finally, we examined spike-field transformations across the thalamocortical synapse using spike-LFP coherence coupling measures. Main results. We found that INS significantly increases LFP amplitude as a log-linear function of INS energy per pulse, primarily entraining to LFP β and γ bands with synchrony extending to 200 Hz in some cases. A subset of neurons demonstrated nonlinear, chaotic oscillations linked to information transfer across cortical circuits. Finally, we utilized spike-field coherences to correlate spike coupling to LFP frequency band activity and suggest an energy-dependent model of network activation resulting from INS stimulation. Significance. We show that INS reliably drives robust network activity and can potently modulate cortical field potentials across a wide range of frequencies in a stimulus parameter-dependent manner. Based on these results, we propose design principles for developing full coverage, all-optical thalamocortical auditory neuroprostheses.

Long-term robust intracortical microelectrode (IME) neural recording quality is negatively affected by the neuroinflammatory response following microelectrode insertion. This adversely impacts brain-machine interface (BMI) performance for patients with neurological disorders or amputations. Recent studies suggest that the leakage of blood-brain barrier (BBB) and microhemorrhage caused by IME insertions contribute to increased neuroinflammation and reduced neural recording performance. Here, we evaluated dexamethasone sodium phosphate-loaded platelet-inspired nanoparticles (DEXSPPIN) to simultaneously augment local hemostasis and serve as an implant-site targeted drug-delivery vehicle. Weekly systemic treatment or control therapy was provided to rats for 8 weeks following IME implantation, while evaluating extracellular single-unit recording performance. End-point immunohistochemistry was performed to further assess the local tissue response to the IMEs. Treatment with DEXSPPIN significantly increased the recording capabilities of IMEs compared to controls over the 8-week observation period. Immunohistochemical analyses of neuron density, activated microglia/macrophage density, astrocyte density, and BBB permeability suggested that the improved neural recording performance may be attributed to reduced neuron degeneration and neuroinflammation. Overall, we found that DEXSPPIN treatment promoted an anti-inflammatory environment that improved neuronal density and enhanced IME recording performance.

Diverse biological factors, such as sex and age, confer heterogeneity on sensory processing challenges in autism. These factors result in major difficulties in the processing of contextual information in social and non-social situations. To assess divergence in autistic traits, it is critical to consider sex- and age-related variability. Nevertheless, these differences remain largely elusive. Animal models of autism offer the possibility to examine contextual processing at the single-neuron level. Here, we investigated predictive processing of contextual auditory cues in the auditory midbrain of control and prenatally valproic acid-induced rats, a well-established animal model of autism. The rats were prepubertal and adult female and male animals. We performed single-unit recordings in the inferior colliculus of control and prenatally, or in utero , exposed rats under the classical oddball paradigm and non-repetitive cascade control sequences to study neuronal mismatch. This is the neuronal correlate of mismatch negativity, the brain’s automatic response to interruptions in environmental regularity. When comparing control and exposed rats, our results demonstrated a reduction in neuronal mismatch in rats exposed to valproic acid. However, exposed adult females exhibited an increased neuronal mismatch compared to their control counterparts. With respect to sex distinctions, valproic acid induced sex differences in neuronal mismatch of prepubertal and adult rats that are not observable in control animals. Moreover, we detected an age-dependent refinement in prediction error that is not affected by the drug. But valproic acid altered typical developmental trajectory of neuronal mismatch in both sexes. Such observations support sex- and age-related effects of in utero valproic acid exposure in contextual auditory processing at the neural level of the inferior colliculus. In autism, atypical predictive processing of environmental regularities underlies unusual responses to novel experiences. The present study highlights the importance of sex and age, that confer heterogeneity to these challenges.

Intracortical microelectrodes are used for recording activity from individual neurons, providing both a valuable neuroscience tool and an enabling medical technology for individuals with motor disabilities. Standard neural probes carrying the microelectrodes are rigid silicon-based structures that can penetrate the brain parenchyma to interface with the targeted neurons. Unfortunately, within weeks after implantation, neural recording quality from microelectrodes degrades, owing largely to a neuroinflammatory response. Key contributors to the neuroinflammatory response include mechanical mismatch at the device-tissue interface and oxidative stress. We developed a mechanically-adaptive, resveratrol-eluting (MARE) neural probe to mitigate both mechanical mismatch and oxidative stress and thereby promote improved neural recording quality and longevity. In this work, we demonstrate that compared to rigid silicon controls, highly-flexible MARE probes exhibit improved recording performance, more stable impedance, and a healing tissue response. With further optimization, MARE probes can serve as long-term, robust neural probes for brain-machine interface applications.

Epidural electrical stimulation of the spinal cord (ES) is used to restore/improve locomotor movements in patients. However, the neuronal mechanisms underlying activation of locomotor networks by ES are unknown. Here, we analyzed the effects of ES on the activity of individual spinal neurons of different functional locomotor groups. Neuronal activity was recorded in decerebrate cats before and during ES that evoked locomotion. During ES initial period (NW-period, before the locomotion onset), the activity was increased in most neurons as compared to that before ES. We found that ES-caused activation of neurons of locomotor network to the average level similar to that observed during locomotion is not sufficient for initiation of locomotion. We demonstrated that the onset of ES-evoked locomotion was associated with specific changes in the activity of individual neurons within functional locomotor groups and in their responses to epidural stimuli. With the locomotion onset, there was a trend for individual neurons with extremely high activity during NW-period to decrease their activity, while for neurons with extremely low activity to become more active. Also, in neurons contributing to generation of a specific mode of locomotion, peaks and troughs in responses to individual epidural stimuli were significantly less pronounced as compared with those observed during NW-period. We suggest that these changes allow ES to maintain the high level of excitability of the locomotor network necessary for its operation without distortion of the locomotor rhythm. The obtained results advance our understanding of the neuronal mechanisms underlying activation of locomotor network by ES.

Closed-loop neural control is a powerful tool for both the scientific exploration of neural function and for mitigating deficiencies found in open-loop deep brain stimulation (DBS). Here, we present a protocol for artificial intelligence-guided neural control in rats using deep reinforcement learning (RL) and infrared neural stimulation (INS). We describe steps for integrating RL closed-loop control into neuroscience and neuromodulation studies. We then detail procedures for using and deploying infrared INS in chronic DBS applications. For complete details on the use and execution of this protocol, please refer to Coventry et al.1 and Coventry and Bartlett.2.

Typical statistical practices in the biological sciences have been increasingly called into question due to difficulties in the replication of an increasing number of studies, many of which are confounded by the relative difficulty of null significance hypothesis testing designs and interpretation of p -values. Bayesian inference, representing a fundamentally different approach to hypothesis testing, is receiving renewed interest as a potential alternative or complement to traditional null significance hypothesis testing due to its ease of interpretation and explicit declarations of prior assumptions. Bayesian models are more mathematically complex than equivalent frequentist approaches, which have historically limited applications to simplified analysis cases. However, the advent of probability distribution sampling tools with exponential increases in computational power now allows for quick and robust inference under any distribution of data. Here we present a practical tutorial on the use of Bayesian inference in the context of neuroscientific studies in both rat electrophysiological and computational modeling data. We first start with an intuitive discussion of Bayes' rule and inference followed by the formulation of Bayesian-based regression and ANOVA models using data from a variety of neuroscientific studies. We show how Bayesian inference leads to easily interpretable analysis of data while providing an open-source toolbox to facilitate the use of Bayesian tools.

Homeostatic plasticity, the ability of neurons to maintain their averaged activity constant around a set point value, is thought to account for the central hyperactivity after hearing loss. Here, we investigated the putative role of GABAergic neurotransmission in this mechanism after a noise-induced hearing loss larger than 50 dB in high frequencies in guinea pigs. The effect of GABAergic inhibition is linked to the normal functioning of K + –Cl– co-transporter isoform 2 (KCC2) which maintains a low intracellular concentration of chloride. The expression of membrane KCC2 were investigated before and after noise trauma in the ventral and dorsal cochlear nucleus (VCN and DCN, respectively) and in the inferior colliculus (IC). Moreover, the effect of gabazine (GBZ), a GABA antagonist, was also studied on the neural activity in IC. We show that KCC2 is downregulated in VCN, DCN and IC 3 days after noise trauma, and in DCN and IC 30 days after the trauma. As expected, GBZ application in the IC of control animals resulted in an increase of spontaneous and stimulus-evoked activity. In the noise exposed animals, on the other hand, GBZ application decreased the stimulus-evoked activity in IC neurons. The functional implications of these central changes are discussed.

Substantial evidence has shown that the Circadian Locomotor Output Cycles Kaput ( Clock ) gene is a core transcription factor of circadian rhythms that regulates dopamine (DA) synthesis. To shed light on the mechanism of this interaction, flexible multielectrode arrays (MEAs) are developed that can measure both DA concentrations and electrophysiology chronically. The dual functionality is enabled by conducting polymer PEDOT doped with acid‐functionalized carbon nanotubes (CNT). The PEDOT/CNT microelectrode coating maintained stable electrochemical impedance and DA detection by square wave voltammetry for 4 weeks in vitro. When implanted in wild‐type (WT) and Clock mutation (MU) mice, MEAs measured tonic DA concentration and extracellular neural activity with high spatial and temporal resolution for 4 weeks. A diurnal change of DA concentration in WT is observed, but not in MU, and a higher basal DA concentration and stronger cocaine‐induced DA increase in MU. Meanwhile, striatal neuronal firing rate is found to be positively correlated with DA concentration in both animal groups. These findings offer new insights into DA dynamics in the context of circadian rhythm regulation, and the chronically reliable performance and dual measurement capability of this technology hold great potential for a broad range of neuroscience research.

Identifying different sleep stages in humans and other mammals has traditionally relied on electroencephalograms. Such an approach is not feasible in certain animals such as invertebrates, although these animals could also be sleeping in stages. Here, we perform long-term multichannel local field potential recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We acquired consistent spatial recordings of local field potentials across multiple flies, allowing us to compare brain activity across awake and sleep periods. Using machine learning, we uncover distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of microbehaviors associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.

A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

Intracortical microelectrode arrays (MEAs) can be used in a range of applications, from basic neuroscience research to providing an intimate interface with the brain as part of a brain-computer interface (BCI) system aimed at restoring function for people living with neurological disorders or injuries. Unfortunately, MEAs tend to fail prematurely, leading to a loss in functionality for many applications. An important contributing factor in MEA failure is oxidative stress resulting from chronically inflammatory-activated microglia and macrophages releasing reactive oxygen species (ROS) around the implant site. Antioxidants offer a means for mitigating oxidative stress and improving tissue health and MEA performance. Here, we investigate using the clinically available antioxidant dimethyl fumarate (DMF) to reduce the neuroinflammatory response and improve MEA performance in a rat MEA model. Daily treatment of DMF for 16 weeks resulted in a significant improvement in the recording capabilities of MEA devices during the sub-chronic (Weeks 5–11) phase (42% active electrode yield vs. 35% for control). However, these sub-chronic improvements were lost in the chronic implantation phase, as a more exacerbated neuroinflammatory response occurs in DMF-treated animals by 16 weeks post-implantation. Yet, neuroinflammation was indiscriminate between treatment and control groups during the sub-chronic phase. Although worse for chronic use, a temporary improvement (<12 weeks) in MEA performance is meaningful. Providing short-term improvement to MEA devices using DMF can allow for improved use for limited-duration studies. Further efforts should be taken to explore the mechanism behind a worsened neuroinflammatory response at the 16-week time point for DMF-treated animals and assess its usefulness for specific applications.

Background: Commonly encountered nontraumatic, moderate noise is increasingly implicated in anxiety; however, the neural substrates underlying this process remain unclear. Objectives: We investigated the neural circuit mechanism through which chronic exposure to moderate-level noise causes anxiety-like behaviors. Methods: Mice were exposed to chronic, moderate white noise [85 decibel (dB) sound pressure level (SPL)], 4 h/d for 4 wk to induce anxiety-like behaviors, which were assessed by open field, elevated plus maze, light-dark box, and social interaction tests. Viral tracing, immunofluorescence confocal imaging, and brain slice patch-clamp recordings were used to characterize projections from auditory brain regions to the lateral amygdala. Neuronal activities were characterized by in vivo multielectrode and fiber photometry recordings in awake mice. Optogenetics and chemogenetics were used to manipulate specific neural circuitry. Results: Mice chronically (4 wk) exposed to moderate noise (85 dB SPL, 4 h/d) demonstrated greater neuronal activity in the lateral amygdala (LA), and the LA played a critical role in noise-induced anxiety-like behavior in these model mice. Viral tracing showed that the LA received monosynaptic projections from the medial geniculate body (MG) and auditory cortex (ACx). Optogenetic excitation of the MG→LA or ACx→LA circuits acutely evoked anxiety-like behaviors, whereas their chemogenetic inactivation abolished noise-induced anxiety-like behavior. Moreover, mice chronically exposed to moderate noise were more susceptible to acute stress, with more neuronal firing in the LA, even after noise withdrawal. Discussion: Mice exposed to 4 wk of moderate noise (85 dB SPL, 4 h/d) demonstrated behavioral and physiological differences compared to controls. The neural circuit mechanisms involved greater excitation from glutamatergic neurons of the MG and ACx to LA neurons under chronic, moderate noise exposure, which ultimately promoted anxiety-like behaviors. Our findings support the hypothesis that nontraumatic noise pollution is a potentially serious but unrecognized public health concern. https://doi.org/10.1289/EHP12532.

Prediction provides key advantages for survival, and cognitive studies have demonstrated that the brain computes multilevel predictions. Evidence for predictions remains elusive at the neuronal level because of the complexity of separating neural activity into predictions and stimulus responses. We overcome this challenge by recording from single neurons from cortical and subcortical auditory regions in anesthetized and awake preparations, during unexpected stimulus omissions interspersed in a regular sequence of tones. We find a subset of neurons that responds reliably to omitted tones. In awake animals, omission responses are similar to anesthetized animals, but larger and more frequent, indicating that the arousal and attentional state levels affect the degree to which predictions are neuronally represented. Omission-sensitive neurons also responded to frequency deviants, with their omission responses getting emphasized in the awake state. Because omission responses occur in the absence of sensory input, they provide solid and empirical evidence for the implementation of a predictive process.

Neurovascular coupling (NVC) is a mechanism that, amongst other known and latent critical functions, ensures activated brain regions are adequately supplied with oxygen and glucose. This biological phenomenon underpins non-invasive perfusion-related neuroimaging techniques and recent reports have implicated NVC impairment in several neurodegenerative disorders. Yet, much remains unknown regarding NVC in health and disease, and only recently has there been burgeoning recognition of a close interplay with brain thermodynamics. Accordingly, we developed a novel multi-modal approach to systematically modulate cortical temperature and interrogate the spatiotemporal dynamics of sensory-evoked NVC. We show that changes in cortical temperature profoundly and intricately modulate NVC, with low temperatures associated with diminished oxygen delivery, and high temperatures inducing a distinct vascular oscillation. These observations provide novel insights into the relationship between NVC and brain thermodynamics, with important implications for brain-temperature related therapies, functional biomarkers of elevated brain temperature, and in-vivo methods to study neurovascular coupling.

The number of people aged 12 years and older using illicit drugs reached 59.3 million in 2020, among which 5.2 million are cocaine users based on the national data. In order to fully understand cocaine addiction and develop effective therapies, a tool is needed to reliably measure real-time cocaine concentration and neural activity in different regions of the brain with high spatial and temporal resolution. Integrated biochemical sensing devices based upon flexible microelectrode arrays (MEA) have emerged as a powerful tool for such purposes; however, MEAs suffer from undesired biofouling and inflammatory reactions, while those with immobilized biologic sensing elements experience additional failures due to biomolecule degradation. Aptasensors are powerful tools for building highly selective sensors for analytes that have been difficult to detect. In this work, DNA aptamer-based electrochemical cocaine sensors were integrated on flexible MEAs and protected with an antifouling zwitterionic poly (sulfobetaine methacrylate) (PSB) coating, in order to prevent sensors from biofouling and degradation by the host tissue. In vitro experiments showed that without the PSB coating, both adsorption of plasma protein albumin and exposure to DNase-1 enzyme have detrimental effects on sensor performance, decreasing signal amplitude and the sensitivity of the sensors. Albumin adsorption caused a 44.4% sensitivity loss, and DNase-1 exposure for 24 hr resulted in a 57.2% sensitivity reduction. The PSB coating successfully protected sensors from albumin fouling and DNase-1 enzyme digestion. In vivo tests showed that the PSB coated MEA aptasensors can detect repeated cocaine infusions in the brain for 3 hrs after implantation without sensitivity degradation. Additionally, the same MEAs can record electrophysiological signals at different tissue depths simultaneously. This novel flexible MEA with integrated cocaine sensors can serve as a valuable tool for understanding the mechanisms of cocaine addiction, while the PSB coating technology can be generalized to improve all implantable devices suffering from biofouling and inflammatory host responses.