Electrophysiology publications

Objective. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established therapy for Parkinson’s disease (PD). Yet, optimizing lead placement and stimulation programming remains challenging. Current techniques rely on imaging and intraoperative microelectrode recordings (MER), while programming relies on trial-and-error clinical testing, which can be time-consuming. DBS-induced local evoked potentials (DLEP), also known as evoked resonant neural activity, have emerged as a potential alternative electrophysiological marker for mapping. However, direct comparisons with traditional spectral features, such as beta-band, high-frequency oscillations (HFOs), and aperiodic component are lacking. Approach. We evaluated DLEP across 39 STN DBS leads in 31 subjects with PD undergoing DBS surgery, using both a single-pulse and high-frequency (HF) burst stimulation paradigms. We developed a novel artifact-removal method to enable monopolar DLEP recovery, including estimating the DLEP amplitudes at stimulated contacts, further enhancing spatial sampling of DLEP. We evaluated spectral features and DLEP in respect to imaging-based and MER-based localization, and its predictive power for post-operative programming. Main results. DLEP showed great spatial consistency, maximizing within STN with 100% accuracy for single-pulse and 84.62% for burst stimulation, surpassing spectral measures including beta (89.74%) and HFO (82.05%). DLEP better correlated with clinical outcomes (single-pulses ρ = −0.33, HF bursts ρ = −0.26), than spectral measures (beta ρ = −0.25, HFO ρ = 0.05). Furthermore, single-pulses at low-frequencies are sufficient for DLEP-based mapping. Significance. We show how DLEP provide higher STN-spatial specificity and correlation with postoperative programming compared to spectral features. To support clinical translation of DLEP, we developed two methods aimed to recover artifact-free DLEP and estimating DLEP amplitudes at stimulating contacts. DLEP appear distinct from beta and HFO activity, yet strongly tied to aperiodic spectral components, suggesting that DLEP amplitude reflects underlying STN excitability. This study highlights that DLEP are a robust and clinically valuable marker for DBS targeting and programming.

Brain-machine interfaces (BMIs) offer a viable option for restoring function in patients with motor disabilities post-stroke. Most BMI systems rely on signals from the motor cortex (M1), which is often compromised after stroke. The cerebellum, a subcortical structure involved in motor control, remains an underexplored source for neuroprosthetic control. Using chronic electrophysiological recordings in a rat stroke model, we show that cerebellar neural activity can effectively drive BMI control, performing comparably to M1-driven control. We observed this even in animals with motor impairments post-stroke. Simultaneous M1-cerebellum recordings during cerebellar BMI control revealed that cerebellar "direct" neurons driving the interface were influenced by both local cerebellar and distant M1 neurons. While cerebellar influence remained stable, M1's interaction with cerebellar direct neurons shifted from longer to shorter timescales after stroke. These findings highlight that cerebellar direct neural control is possible in the stroke brain and reveal changes in M1-cerebellar network dynamics post-stroke.

Intracortical microelectrode arrays (MEAs) are vital tools for brain‐machine interface applications and basic neuroscience research, with the potential to advance treatments for neurological disorders and enhance the understanding of the nervous system. However, implanting intracortical electrodes can damage native tissue along the insertion path and trigger inflammatory responses characterized by neuronal loss and glial activation. While flexible electrodes reduce some of these adverse effects compared to rigid counterparts, their mechanical compliance often leads to buckling during insertion, necessitating the use of insertion aids such as stiff shuttles or dissolvable coatings. These aids, however, introduce additional complexity and can cause further tissue damage. In this work, microfabricated polyimide MEAs featuring a buckling‐resistant, trace‐stacked (BRATS) design are presented. It is demonstrated that BRATS MEAs can penetrate agarose brain phantoms and the rat cerebral cortex without the need for insertion aids. Once implanted, BRATS MEAs established a stable and functional electrical interface with the brain, enabling high‐fidelity, single‐unit electrophysiological recordings. Compared to conventional flexible MEAs inserted with a stiff shuttle, BRATS MEAs elicited significantly lower inflammatory responses and preserved a higher density of neurons near the implant site one week post‐implantation.

The central nervous system controls movement by combining neuromotor modules, known as muscle synergies. Previous studies suggest that spinal premotor interneurons (PreM‐INs) contribute to the encoding of stable muscle synergies for voluntary movement. But descending and sensory inputs also influence motor outputs through the spinal interneuronal network, which may be configured by its inputs to encode different sets of muscle synergies depending on the network state, thereby recruiting different selections of synergies. Here we tested this possibility of state‐dependent synergy encoding by examining the muscle synergies represented by the same upstream spinal interneurons under different activity states induced by various optogenetic stimulation patterns. Lumbosacral spinal units and electromyographic (EMG) activities of hindlimb muscles were simultaneously recorded from anaesthetized Thy1‐ChR2 mice as the spinal cord was stimulated by one or two optic fibres at different intensities. The synergy encoded by each unit was revealed as a ‘muscle field’ derived from spike‐triggered averages of EMG, whereas the entire muscle synergy set was factorized from the EMG. We found that although the muscle synergy set remained stable across stimulation conditions, the muscle fields of the same units were matched to different synergies within the set in different states. Thus the interneurons may flexibly adjust their connectivity with the motoneurons of the muscles as descending and sensory afferents impose different states on the spinal network. State‐dependent encoding of muscle synergies may allow different synergies to be selected for producing stable movement in an ever‐changing workspace environment. image Key points Muscle synergies for locomotion can be represented by spinal interneurons, as revealed by the interneurons’ muscle fields derived from spike‐triggered averages of EMG. The muscle field of a single spinal interneuron may vary under different stimulation conditions, as demonstrated by optogenetic stimulation. Encoding of muscle synergies is dependent on the state of spinal activities, thus facilitating the selection of appropriate synergies in different dynamic environments.

The discrete events of our narrative experience are organized by the neural substrate that underlies episodic memory. This narrative process is segmented into distinct units by event boundaries, which facilitate a replay process that acts to consolidate each event into a narrative memory. High-frequency oscillations (HFOs) may synchronize neural activity during these processes. We use intracranial recordings from participants viewing and freely recalling a continuous, audiovisual stimulus. We find that hippocampal HFOs increase following event boundaries and hippocampal-cortical coincident HFOs (co-HFOs) occur in cortical regions that underlie event segmentation (inferior parietal, precuneus, lateral occipital, and inferior frontal cortices). Event-specific co-HFO patterns that occur during event viewing reoccur following event boundaries for the subsequent three events and during recall. This is consistent with models that support replay as a mechanism for memory consolidation. Therefore, HFOs may coordinate activity across brain regions that facilitate event segmentation, encode memory of discrete events, and bind representations to assemble memory of a coherent, continuous experience.

Introduction Deep brain stimulation (DBS) is a neuromodulation method for treatment of various neurological disorders. Research on DBS has often focused on local inhibition or excitation effects, at the site of stimulation. However, it is well-known that DBS can lead to robust evoked potentials (EP) not only at the stimulation site, representing the local effect, but also in distant brain regions, representing the effects on distant targets. While the significance of these EPs for therapeutic outcomes is not known, it appears that the electrical effects of DBS have a partial modulatory impact on downstream targets. Nonetheless, it partly remains unclear through what mechanism DBS pulses travel to the distant targets or what portion of the pulses travel along the normal pathways from the stimulation site. The possible scenarios include orthodromic or antidromic pathways, accessory pathways, normally inhibited pathways, and direct electromagnetic activation of distant sites. We hypothesize that the pathways that transmit DBS pulses include the pathways that transmit intrinsic neural signals. Methods To test this, we performed a transfer function analysis on deep brain recordings from children with dystonia, during DBS-off condition and compared its impulse response with the transmission of signals from electrical stimulation during DBS-on condition. We compared impulse responses derived from intrinsic neural signals during voluntary movement (DBS-off) to evoked potentials (EPs) recorded during electrical stimulation (DBS-on), focusing on directional transmission (orthodromic vs. antidromic). Results DBS EPs were more accurately predicted by impulse responses corresponding to direct axonal activation rather than somatic relay. Significant correlations between intrinsic signal transfer functions and EPs, particularly in orthodromic directions ( p -value < 0.01) from pallidum to thalamus and subthalamic nucleus, support our hypothesis that DBS travels along physiological pathways. Discussion These results suggest that DBS engages existing motor pathways to reach distant targets, offering mechanistic insight into its network effects. This supports future approaches that could tailor treatment plans based on individual connectivity maps to improve clinical efficacy of DBS.

The transplantation of regionally specific spinal neural progenitor cells (sNPCs) has shown promise for functional restoration after spinal cord injury (SCI) by forming connections with host neural circuits. Here, 3D‐printed organoid scaffolds for transplantation using clinically relevant human induced pluripotent stem cell‐derived regionally specific sNPCs is developed. Scaffolds with microscale channels are printed, and sNPCs are subsequently printed within these channels. The scaffolds direct axonal projections along the channels and guide the cells to simulate in vivo‐like conditions, leading to more effective cell maturation and the development of neuronal networks crucial for restoring function after SCI. The scaffolds, with organoids assembled along their lengths, are transplanted into the transected spinal cords of rats. This significantly promotes the functional recovery of the rats. At 12 weeks post‐transplantation, the majority of the cells in the scaffolds differentiate into neurons and integrate into the host spinal cord tissue. These results demonstrate their potential to create a relay system along the spinal cord and form synapses in both the rostral and caudal directions relative to the scaffold. It is envisioned that combining sNPCs, organoid assembly, and 3D printing strategies can ultimately lead to a transformative treatment approach for SCI.

Dopamine (DA)-producing neurons of the ventral tegmental area (VTA) regulate consummatory behavior in a state-dependent manner (e.g. when hungry or thirsty). The mechanisms by which and extent to which DA neurons are regulated by these interoceptive signals are poorly understood. Here, we identify transient receptor potential canonical type 6 (TRPC6) channels as selective mediators of neuropeptide receptor-induced calcium signaling in VTA-DA neurons. These channels regulate DA neuron activity and consummatory behavior in a state-dependent manner. We find that TRPC6 channels regulate distinct aspects of neuropeptide-induced calcium signals in DA neurons but make little contribution to calcium dynamics associated with metabotropic neurotransmitter receptor signaling. We further show that TRPC6 channels regulate scalable reward valuation and consummatory behavior in hungry but not thirsty mice. These findings demonstrate that neuropeptide-and neurotransmitter-activated G-protein coupled receptors (GPCRs) regulate cellular calcium dynamics through distinct mechanisms, and that TRPC6 channels are important determinants of how animals respond to different homeostatic demands.

Circadian sensitivity significantly influences the severity of noise-induced hearing loss (NIHL), but the underlying mechanisms remain unclear. Here, we applied single-cell RNA sequencing to 97,043 cochlear cells, identifying macrophages as the primary immune responders to acoustic trauma, with a notable increase in their proportion in the cochlea. Immunofluorescence confirmed significant recruitment and activation of cochlear macrophages following noise exposure, while in vivo macrophage depletion resulted in the recovery of hearing. Furthermore, analyses of differentially-expressed genes and pathways revealed pronounced activation of NLRP3 inflammasome signaling in macrophages during night-time noise exposure. Measurements of elevated IL-1β and IL-18 expression in cochlear macrophages by multiplex immunohistochemistry correlated with heightened inflammation in the night-time exposure group. These findings were further confirmed by the administration of the selective NLRP3 inhibitor CY-09, which mitigated inflammasome activation, preserved synaptic integrity, and protect against hearing loss. In conclusion, our findings underscore the role of macrophage-driven NLRP3 inflammasome activation in mediating circadian variations in cochlear damage, offering a potential therapeutic target for mitigating NIHL.

Nicotine addiction remains a major cause of disease and premature death worldwide. Nicotine modulates neural pathways that underlie both rewarding and aversive behavioral effects, but persistent activation of brain reward circuitry drives nicotine consumption despite the negative consequences. When nicotine users attempt to quit, additional neural mechanisms are recruited to generate an aversive withdrawal state, which contributes to the remarkably high relapse rate among nicotine users. The interpeduncular nucleus (IPN) and its presynaptic inputs from the medial habenula are key mediators of aversive nicotine withdrawal symptoms, but the downstream neural targets mediating these effects are unknown. The aversive effects of acute exposure to high doses of nicotine require inhibitory IPN GABAergic projections to the laterodorsal tegmentum (LDTg), a key driver of reward-related dopamine signaling. Here we show that optogenetic inhibition of these IPN→LDTg projections reduces behavioral and physiological effects of nicotine withdrawal in male and female mice. Using fiber photometry, we found that nicotine withdrawal reduced reward-related signaling with decreases in both LDTg neuronal activity and nucleus accumbens dopamine release. These studies demonstrate a direct link between aversive and appetitive neural pathways that is active during nicotine withdrawal, providing novel targets for treating nicotine addiction.

Damage to the cochlear outer hair cell (OHC) is a major cause of deafness in mammals. OHCs amplify the auditory signals to enhance the sensitivity and sound frequency selectivity of the auditory system. However, detailed mechanisms underlying functional OHC regulation remain unclear. Here, it is demonstrated that volume‐regulated anion channels (VRACs) are essential for OHC function. VRAC subunits are highly expressed in OHCs. Genetic deletion of leucin‐rich repeat containing 8A (LRRC8A), the obligatory VRAC subunit, in hair cells results in hearing loss, whereas re‐expressing LRRC8A in the cochlea restores hearing in LRRC8A‐deficient mice. By employing patch‐clamp electrophysiology, it is shown that VRAC in OHCs is activated by hypotonicity and is involved in regulating cell volume. Furthermore, the nonlinear capacitance (NLC), a measure of electromotility, is decreased in the OHCs from LRRC8A‐deficient mice. Therefore, LRRC8A deficiency compromises electromotility of OHCs and impairs signal amplification. In conclusion, the findings highlight the essential role of VRAC in OHC electromotility and its necessity for auditory function.

The neural mechanisms of consciousness remain elusive. Previous studies on both human and non-human animals, through manipulation of level of conscious arousal, have reported that specific time-series features correlate with level of consciousness, such as spectral power in certain frequency bands. However, such features often lack principled, theoretical justifications as to why they should be related with level of consciousness. This raises two significant issues: firstly, many other types of times-series features which could also reflect conscious level have been ignored due to researcher biases toward specific analyses; and secondly, it is unclear how to interpret identified features to understand the neural activity underlying consciousness, especially when they are identified from recordings which summate activity across large areas such as electroencephalographic recordings. To address the first concern, here we propose a new approach: in the absence of any theoretical priors, we should be maximally agnostic and treat as many known features as feasible as equally promising candidates. To apply this approach, we use h ighly c omparative t ime- s eries a nalysis ( hctsa ), a toolbox which provides over 7,700 different univariate time-series features originating from different research fields. To address the second issue, we employ hctsa to high-quality neural recordings from a relatively simple brain, the fly brain ( Drosophila melanogaster ), extracting features from local field potentials during wakefulness, general anesthesia, and sleep. At Stage 1 of this registered report, we constructed a classifier for each feature, for discriminating wakefulness and anesthesia in a discovery group of flies ( N = 13). At Stage 2, we assessed their performances on four independent groups of evaluation flies, from which recordings were made during anesthesia and sleep, and which were originally blinded to the data analysis team ( N = 49). We found only 47 time-series features, applied to recordings obtained from the center of the fly brain, to also significantly classify wake from anesthesia or sleep in all 4 of these evaluation datasets. Most of these were related to autocorrelation, and they indicated that signals during wakefulness remained correlated to their past for a longer timescale than during anesthesia and sleep. Meanwhile, time-series features related to well-known potential markers of consciousness, such as those related to complexity or spectral power, failed to generalize across all the flies. However, many of these complexity and spectral features have a consistent direction of effect due to anesthesia or sleep across flies, suggesting that even slight variations in experiment setup can reduce generalizability of classifiers. These results caution the current state of frequent discoveries of new potential consciousness markers, which may not generalize across datasets, and point to autocorrelation as a class of dynamical properties which does.

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.

The first-spike latency (FSL) is an important temporal characteristic of a neurophysiological response. We study the FSLs of sound-driven responses in individual neurons in the rat’s auditory midbrain. Responses were elicited by a train of stimuli created using multiple presentations of two tone bursts with different frequencies. Presentations of the two sounds were interleaved temporally in a random order. We found that the mean and the temporal variation of FSL of the response elicited by a sound was increased when the sound was presented more frequently or when it was moved from the ear that drove an excitatory response to the ear that drove an inhibitory effect. Furthermore, the FSL of response to one sound was dependent on the spatial location of the other sound. Results suggested that the timing of the first spike could be used by midbrain neurons to encode information related to the probability of occurrence and spatial location of a sound. It could also be used to gauge how the sound was related to the other sound in spatial location. These results enhance our understanding of neural bases of binaural hearing, especially in an environment with temporally separated competing sounds.

Experiencing a single severe stressor is sufficient to drive sexually dimorphic psychiatric disease development. The ventral subiculum (vSUB) emerges as a site where stress may induce sexually dimorphic adaptations due to its sex-specific organization and pivotal role in stress integration. Using a 1 h acute restraint stress model in mice, we uncover that stress causes a net decrease in vSUB activity in females driven by adrenergic receptor signaling. By contrast, males exhibit a net increase in vSUB activity that is driven by corticosterone signaling. We further identified sexually dimorphic changes in vSUB output to the anterior bed nucleus of the stria terminalis and in anxiety-like behaviors in response to stress. These findings reveal striking changes in psychiatric disease-relevant brain regions and behavior following stress with sex-, cell-type, and synapse-specificity that contribute to our understanding of sexually dimorphic adaptations that may shape stress-related psychiatric disease risk.

The "cocktail party problem" challenges our ability to understand speech in noisy environments and often includes background music. Here, we explored the role of background music in speech-in-noise listening. Participants listened to an audiobook in familiar and unfamiliar music while tracking keywords in either speech or song lyrics. We used EEG to measure neural tracking of the audiobook. When speech was masked by music, the modeled temporal response function (TRF) peak latency at 50 ms (P1TRF) was prolonged compared to unmasked. Additionally, P1TRF amplitude was larger in unfamiliar background music, suggesting improved speech tracking. We observed prolonged latencies at 100 ms (N1TRF) when speech was not the attended stimulus, though only in less musical listeners. Our results suggest early neural representations of speech are stronger with both attention and concurrent unfamiliar music, indicating familiar music is more distracting. One's ability to perceptually filter "musical noise" at the cocktail party also depends on objective musical listening abilities.

Human decision-making involves the coordinated activity of multiple brain areas, acting in concert, to enable humans to make choices. Most decisions are carried out under conditions of uncertainty, where the desired outcome may not be achieved if the wrong decision is made. In these cases, humans deliberate before making a choice. The neural dynamics underlying deliberation are unknown and intracranial recordings in clinical settings present a unique opportunity to record high temporal resolution electrophysiological data from many (hundreds) brain locations during behavior. Combined with dynamic systems modeling, these allow identification of latent brain states that describe the neural dynamics during decision-making, providing insight into these neural dynamics and computations. Results show that the neural dynamics underlying risky decisions, but not decisions without risk, converge to separate subspaces depending on the subject's preferred choice and that the degree of overlap between these subspaces declines as choice approaches, suggesting a network level representation of evidence accumulation. These results bridge the gap between regression analyses and data driven models of latent states and suggest that during risky decisions, deliberation and evidence accumulation toward a final decision are represented by the same neural dynamics, providing novel insights into the neural computations underlying human choice.

Fear retrieval is fundamental for animals to rapidly enter a self-defense state, which enhances their survival rate. Although the cellular mechanisms and neural circuits underlying fear retrieval have been relatively well studied, particularly in classic fear-related nuclei such as the amygdala, the neural circuits and intrinsic microcircuits of some non-classical fear-related nuclei remain poorly understood. A disinhibitory microcircuit in the temporal association cortex (TeA) was identified in this study, demonstrating a critical role in fear retrieval. Additionally, the response of the TeA to fear retrieval is largely driven by acetylcholine (Ach), which then relay information to the tail of striatum (TS) to mediate freezing behavior. Together, these findings demonstrate the essential role of the TeA and its microcircuit in auditory fear retrieval in response to pure tones, providing new insights into the mechanisms of fear retrieval in the cortex.

Auditory processing in the cerebral cortex is considered to begin with thalamocortical inputs to layer 4 (L4) of the primary auditory cortex (A1). In this canonical model, A1 L4 inputs initiate a hierarchical cascade that propagates to higher-order cortices for slower integration of complex sounds. Here, we identify parallel ascending pathways in mice that bypass A1 and directly reach the secondary auditory cortex (A2), alongside the canonical hierarchical route. We found that layer 6 (L6) of both A1 and A2 receive short-latency (<10 ms) sound inputs via higher-order thalamic nuclei. Additionally, A2 L4 is innervated by a caudal subdivision of the traditionally defined primary thalamus, which we now re-classify as non-primary. Notably, both identified thalamic regions receive projections from distinct subdivisions of the higher-order inferior colliculus, which in turn receive direct projections from cochlear nucleus neurons. Thus, higher-order auditory cortex integrates both slower, pre-processed information and rapid, direct sensory inputs, enabling parallel processing of fast sensory information across cortical areas.

Atypical sensory processing, particularly in the auditory domain, is one of the most common and quality-of-life affecting symptoms seen in autism spectrum disorders (ASD). Fragile X Syndrome (FXS) is a leading inherited cause of ASD and a majority of FXS individuals present with auditory processing alterations. While auditory hypersensitivity is a common phenotype observed in FXS and Fmr1 knockout (KO) rodent models, it is important to consider other auditory coding impairments that could contribute to sound processing difficulties and disrupted language comprehension in FXS. We have shown previously that a Fmr1 KO rat model of FXS exhibits heightened sound sensitivity that coincided with abnormal perceptual integration of stimulus bandwidth, indicative of altered spectral processing. Frequency discrimination is a fundamental aspect of sound encoding that is important for a range of auditory processes, such as source segregation and speech comprehension, and disrupted frequency coding could thus contribute to a range of auditory issues in FXS and ASD. Here we explicitly characterized spectral processing deficits in male Fmr1 KO rats using an operant conditioning tone discrimination assay and in vivo electrophysiological recordings from the auditory cortex and inferior colliculus. We found that Fmr1 KO rats exhibited poorer frequency resolution, which corresponded with neuronal hyperactivity and broader frequency tuning in auditory cortical but not collicular neurons. Using an experimentally informed population model, we show that these cortical physiological differences can recapitulate the observed behavior discrimination deficits, with decoder performance being tightly linked to differences in cortical tuning width and signal-to-noise ratios. Together, these findings indicate that cortical hyperexcitability in Fmr1 KO rats may act to preserve signal-to-noise ratios and signal detection threshold at the expense of sound sensitivity and fine feature discrimination, highlighting a potential mechanistic locus for a range of auditory behavioral phenotypes in FXS.