Electrophysiology publications

Purpose: We aim to develop a robust method to improve the estimation accuracy of motor-evoked potential (MEP) recruitment curves (RCs), including motor threshold, in small-sample settings which typically involve fewer than 40 stimuli. Methods: We present a hierarchical Bayesian (HB) method to model MEP size as a rectified-logistic function of stimulation intensity. This method is designed to account for small samples, handle outliers without discarding data, quantify estimation uncertainty, and simulate synthetic data that closely matches real observations, useful for optimizing experimental design. We validate its performance on transcranial magnetic stimulation (TMS), epidural spinal cord stimulation (SCS), and synthetic TMS datasets, and provide an open-source library for Python, called hbMEP, for diverse applications. Results: The rectified-logistic outperformed sigmoidal functions in predictive accuracy on TMS and SCS datasets, as demonstrated through cross-validation. A mixture extension of the HB model improved robustness to outliers by further increasing its predictive accuracy. The HB model reduced threshold estimation error by up to 70% on sparse synthetic TMS data compared to non-hierarchical models. Bayesian estimation with the HB model reduced the required number of participants by at least 23% to detect a shift in threshold with 80% power, compared to frequentist testing. Empirical results on human SCS data further validated its applicability to real data. Conclusion: By improving accuracy on sparse data, our method minimizes the number of stimuli needed to probe each individual's neuromuscular parameters across multiple muscles simultaneously, thereby reducing session duration and the risk of inadvertent neuromodulation. Our approach provides a more statistically powerful and conclusive framework for inferring changes in threshold, and therefore corticospinal excitability. The hbMEP library streamlines and unifies the analysis of RCs across stimulation modalities and experimental paradigms.

Purpose Present-day cochlear implants (CIs) can deliver usable speech reception in quiet surroundings. Most CI users, however, show impaired sensitivity to temporal fine structure, which hampers their use of pitch contours and spatial cues to segregate competing talkers. In previous short-term animal studies, we used intraneural (IN) electrodes to stimulate pathways originating from various cochlear turns. Neurons in the inferior colliculus synchronized to apical stimulation at higher rates than to stimulation of the middle-to-basal pathways that are stimulated primarily by today’s CIs. Here, we use non-invasive recordings to test the safety and efficacy of up to 6 months of IN implantation and stimulation in cats. Methods Deafened cats (ten female, two male) were implanted with IN and/or conventional CI electrodes. The IN electrodes were single activated-iridium shanks that targeted apical-turn fibers. Scalp recordings were made from sedated animals at 2–3-week intervals. Auditory brainstem responses to single electrical pulses (eABR) tracked sensitivity and growth of responses. Frequency following responses to electrical pulse trains (eFFR) assessed brainstem temporal transmission at varying pulse rates. Results Thresholds for eABR were lower for IN than for CI stimulation, dynamic ranges were wider, and (by inference) spread of activation was more restricted. The eFFR evaluated at latencies comparable to those of inferior-colliculus spikes synchronized at maximum pulse rates averaging > 360 pulses/s for IN compared to ~ 240 pulses/s for CI stimulation. The eABR thresholds and eFFR cutoff rates were stable out to 6 months after implantation. Conclusions The results demonstrate the safety and efficacy of chronic IN stimulation in an animal model. In a future clinical device, an IN electrode could augment cochlear-implant performance by enhancing temporal acuity, thereby improving speech reception amid competing sounds.

Purpose Present-day cochlear-implant (CI) users can achieve high levels of speech reception in quiet surroundings. Nevertheless, sensitivity to the temporal pitch of sounds is limited, which contributes to deficits in speech reception amid multiple talkers and in appreciation of musical melodies. Short-term, invasive neurophysiological studies in animals have demonstrated limitations in neural phase locking in the tonotopic range of the auditory pathway that is activated by CIs. It remains an open question, however, whether those neural limitations can account for perceptual deficits in those animal species, let alone in human CI users. For that reason, we have evaluated non-invasive recordings of phase locking from cats chronically implanted with a CI. Methods Ten deafened cats (eight female) were implanted with an animal version of a clinical CI array. The electrically evoked frequency following response (eFFRs) was recorded from the scalps of sedated animals at ≥ 10 weeks post-implantation. Stimuli consisted of constant-amplitude electrical pulse trains at rates from ~ 40 to 640 pulses per second. Results Recordings of the eFFR demonstrated robust responses synchronized to electrical pulse trains across all stimulus rates. Analyses of eFFR amplitude and phase transfer functions confirmed that the eFFR, as with its normal-hearing counterpart, originates from multiple subcortical and cortical generators. The slopes of segments of eFFR phase transfer functions revealed stimulus-to-response latencies of generators that dominated the eFFR across restricted ranges of pulse rates. Those rate ranges must coincide with the limits of phase locking by putative generators at successive levels of the auditory neuroaxis and could inform our understanding of the limits to perceptual temporal acuity. Conclusion The eFFR demonstrated here in an animal model provides a valuable non-invasive measure of temporal processing in electric cochlear stimulation that can be related to ongoing perceptual measures in the same animals and is well-suited to evaluate novel modes of auditory prosthesis for enhancing temporal acuity.

The value associated with reward is sensitive to external factors, such as the time between the choice and reward delivery as classically manipulated in temporal discounting tasks. Subjective preference for two reward options is dependent on objective variables of reward magnitude and reward delay. Single neuron correlates of reward value have been observed in regions, including ventral striatum, orbital, and medial prefrontal cortex. Brain imaging studies show cortico-striatal-limbic network activity related to subjective preferences. To explore how oscillatory dynamics represent reward processing across brain regions, we measured local field potentials of rats performing a temporal discounting task. Our goal was to use a data-driven approach to identify an electrophysiological marker that correlates with reward preference. We found that reward-locked oscillations at beta frequencies signaled the magnitude of reward and decayed with longer temporal delays. Electrodes in orbitofrontal/medial prefrontal cortex, anterior insula, ventral striatum, and amygdala individually increased power and were functionally connected at beta frequencies during reward outcome. Beta power during reward outcome correlated with subjective value as defined by a computational model fit to the discounting behavior. These data suggest that cortico-striatal beta oscillations are a reward signal correlated, which may represent subjective value and hold potential to serve as a biomarker and potential therapeutic target.

Compound nerve action potentials (CNAPs) were used as a metric to assess the stimulation performance of a novel high-density, transverse, intrafascicular electrode in rat models. We show characteristic CNAPs recorded from distally implanted cuff electrodes. Evaluation of the CNAPs as a function of stimulus current and calculation of recruitment plots were used to obtain a qualitative approximation of the neural interface’s placement and orientation inside the nerve. This method avoids elaborate surgeries required for the implantation of EMG electrodes and thus minimizes surgical complications and may accelerate the healing process of the implanted subject.

Objective: Intuitive control of conventional prostheses is hampered by their inability to provide the real-time tactile and proprioceptive feedback of natural sensory pathways. The macro-sieve electrode (MSE) is a candidate interface to amputees’ truncated peripheral nerves for introducing sensory feedback from external sensors to facilitate prosthetic control. Its unique geometry enables selective control of the complete nerve cross-section by current steering. Unlike previously studied interfaces that target intact nerve, the MSE’s implantation requires transection and subsequent regeneration of the target nerve. Therefore, a key determinant of the MSE’s suitability for this task is whether it can elicit sensory percepts at low current levels in the face of altered morphology and caliber distribution inherent to axon regeneration. The present in vivo study describes a combined rat sciatic nerve and behavioral model developed to answer this question. Approach: Rats learned a go/no-go detection task using auditory stimuli and then underwent surgery to implant the MSE in the sciatic nerve. After healing, they were trained with monopolar electrical stimuli with one multi-channel and eight single-channel stimulus configurations. Psychometric curves derived by the method of constant stimuli (MCS) were used to calculate 50% detection thresholds and associated psychometric slopes. Thresholds and slopes were calculated at two time points 3 weeks apart. Main Results: For the multi-channel stimulus configuration, the average current required for stimulus detection was 19.37 μA (3.87 nC) per channel. Single-channel thresholds for leads located near the nerve’s center were, on average, half those of leads located near the periphery (54.92 μA vs. 110.71 μA, or 10.98 nC vs. 22.14 nC). Longitudinally, 3 of 5 leads’ thresholds decreased or remained stable over the 3-week span. The remaining two leads’ thresholds increased by 70–74%, possibly due to scarring or device failure. Significance: This work represents an important first step in establishing the MSE’s viability as a sensory feedback interface. It further lays the groundwork for future experiments that will extend this model to the study of other devices, stimulus parameters, and task paradigms.

Neural implants that deliver multi-site electrical stimulation to the nervous systems are no longer the last resort but routine treatment options for various neurological disorders. Multi-site electrical stimulation is also widely used to study nervous system function and neural circuit transformations. These technologies increasingly demand dynamic electrical stimulation and closed-loop feedback control for real-time assessment of neural function, which is technically challenging since stimulus-evoked artifacts overwhelm the small neural signals of interest. We report a novel and versatile artifact removal method that can be applied in a variety of settings, from single- to multi-site stimulation and recording and for current waveforms of arbitrary shape and size. The method capitalizes on linear electrical coupling between stimulating currents and recording artifacts, which allows us to estimate a multi-channel linear Wiener filter to predict and subsequently remove artifacts via subtraction. We confirm and verify the linearity assumption and demonstrate feasibility in a variety of recording modalities, including in vitro sciatic nerve stimulation, bilateral cochlear implant stimulation, and multi-channel stimulation and recording between the auditory midbrain and cortex. We demonstrate a vast enhancement in the recording quality with a typical artifact reduction of 25-40 dB. The method is efficient and can be scaled to arbitrary number of stimulus and recording sites, making it ideal for applications in large-scale arrays, closed-loop implants, and high-resolution multi-channel brain-machine interfaces.

Objective: Electrical stimulation of the human brain is commonly used for eliciting and inhibiting neural activity for clinical diagnostics, modifying abnormal neural circuit function for therapeutics, and interrogating cortical connectivity. However, recording electrical signals with concurrent stimulation results in dominant electrical artifacts that mask the neural signals of interest. Here we develop a method to reproducibly and robustly recover neural activity during concurrent stimulation. We concentrate on signal recovery across an array of electrodes without channel-wise fine-tuning of the algorithm. Our goal includes signal recovery with trains of stimulation pulses, since repeated, high-frequency pulses are often required to induce desired effects in both therapeutic and research domains. We have made all of our code and data publicly available. Approach: We developed an algorithm that automatically detects templates of artifacts across many channels of recording, creating a dictionary of learned templates using unsupervised clustering. The artifact template that best matches each individual artifact pulse is subtracted to recover the underlying activity. To assess the success of our method, we focus on whether it extracts physiologically interpretable signals from real recordings. Main results: We demonstrate our signal recovery approach on invasive electrophysiologic recordings from human subjects during stimulation. We show the recovery of meaningful neural signatures in both electrocorticographic (ECoG) arrays and deep brain stimulation (DBS) recordings. In addition, we compared cortical responses induced by the stimulation of primary somatosensory (S1) by natural peripheral touch, as well as motor cortex activity with and without concurrent S1 stimulation. Significance: Our work will enable future advances in neural engineering with simultaneous stimulation and recording.

Facial paralysis can be a devastating condition, causing disfiguring facial droop, slurred speech, eye dryness, scarring and blindness. This study investigated the utility of closed-loop functional electric stimulation (FES) for reanimating paralyzed facial muscles in a quantitative rodent model. The right buccal and marginal mandibular branches of the rat facial nerve were transected for selective, unilateral paralysis of whisker muscles. Microwire electrodes were implanted bilaterally into the facial musculature for FES and electromyographic (EMG) recording. With the rats awake and head-fixed, whisker trajectories were tracked bilaterally with optical micrometers. First, the relationship between EMG and volitional whisker movement was quantified on the intact side of the face. Second, the effect of FES on whisker trajectories was quantified on the paralyzed side. Third, closed-loop experiments were performed in which the EMG signal on the intact side triggered FES on the paralyzed side to restore symmetric whisking. The results demonstrate a novel in vivo platform for developing control strategies for neuromuscular facial prostheses.