National trends in the endovascular and surgical treatment of idiopathic intracranial hypertension.

BACKGROUND: The pattern of surgical treatments for Idiopathic Intracranial Hypertension (IIH) in the United States is not well-studied, specifically the trend of utilizing endovascular venous stenting (EVS) as an emerging technique. METHODS: In this cross-sectional study, we aimed to explore the national trend of utilizing different procedures for the treatment of IIH including EVS, Optic Nerve Sheath Fenestration (ONSF), and CSF Shunting, with a focus on novel endovascular procedures. Moreover, we explored rates of 90-day readmission and length of hospital stay following different procedures, besides the effects of sociodemographic and clinical parameters on procedure choice. RESULTS: 36,437 IIH patients were identified from records between 2010 and 2018. Those in the EVS group were 29 years old on average, and 93.4 % were female. Large academic hospital setting was independently associated with higher EVS utilization, while other factors were not predictive of procedure choice. The proportion of EVS use in IIH hospitalizations increased significantly from 2010 to 2018 (P < 0.001), while there was a relative decline in the frequency of shunting procedures (P = 0.001), with ONSF utilization remaining stable (P = 0.39). The rate of 90-day readmission and length of hospital stay were considerably lower following EVS compared to other procedures (Ps < 0.001). CONCLUSION: This study presents novel population-level data on national trends in the frequency and outcome of EVS for IIH therapy. EVS was associated with shorter length of hospital stays and fewer readmission rates. In addition, a continuous increase in venous stenting compared to other procedures suggests an increasing role for endovascular therapies in IIH.

The Internal Superior Laryngeal Nerve in Humans: Evidence for Pure Sensory Function.

OBJECTIVES: To determine if the internal branch of the superior laryngeal nerve (iSLN) provides direct motor innervation to the interarytenoid muscle, a laryngeal adductor critical for airway protection. We studied the iSLN-evoked motor response in the interarytenoid and other laryngeal muscles. If the iSLN is purely sensory, there will be no detectable short latency motor response upon supramaximal stimulation, indicating the absence of a direct efferent conduction path. STUDY DESIGN: Intraoperative case series. METHODS: In seven anesthetized patients undergoing laryngectomy for unilateral laryngeal carcinoma, the iSLN of the unaffected side was electrically stimulated intraoperatively with 0.1-ms pulses of progressive intensities until supramaximal stimulation was reached. Electromyographic responses were measured in the ipsilateral interarytenoid, thyroarytenoid, and cricothyroid muscles. RESULTS: None of the subjects exhibited short-latency interarytenoid motor responses to iSLN stimulation. Supramaximal electrical stimulation of the intact iSLN evoked ipsilateral motor responses with long latencies: 18.7-38.5 ms in the interarytenoid (n = 6) and 17.8-24.9 ms in the thyroarytenoid (n = 5). Supramaximal stimulation of the recurrent laryngeal nerve evoked ipsilateral motor responses with short latencies: 1.6-3.9 ms in the interarytenoid (n = 6) and 1.6-2.7 ms in the thyroarytenoid (n = 6). CONCLUSION: The iSLN provides no functional efferent motor innervation to the interarytenoid muscles. The iSLN exclusively evokes an interarytenoid motor response via afferent activation of central neural circuits that mediate the laryngeal reflex arc. These findings suggest that the role of the iSLN in vital laryngopharyngeal functions, such as normal swallowing and protection of the airway from aspiration, is purely sensory. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:E207-E211, 2021.

Sensory dysphagia: A case series and proposed classification of an under recognized swallowing disorder.

BACKGROUND: Although sensory feedback is a vital regulator of deglutition, it is not comprehensively considered in the standard dysphagia evaluation. Difficulty swallowing secondary to sensory loss may be termed "sensory dysphagia" and may account for cases receiving diagnoses of exclusion, like functional or idiopathic dysphagia. METHODS AND RESULTS: Three cases of idiopathic dysphagia were suspected to have sensory dysphagia. The patients had (1) effortful swallowing, (2) globus sensation, and (3) aspiration. Endoscopic sensory mapping revealed laryngopharyngeal sensory loss. Despite normal laryngeal motor function during voluntary maneuvers, laryngeal closure was incomplete during swallowing. The causes of sensory loss were identified: cranial neuropathy from Chiari malformation, immune-mediated neuronopathy, and nerve damage from prior traumatic intubation. CONCLUSIONS: Sensory loss may cause dysphagia without primary motor dysfunction. Sensory dysphagia should be classified as a distinct form of swallowing motility disorder to improve diagnosis. Increasing awareness and developing appropriate assessment tools may advance dysphagia care.

Characterizing spiking in noisy type II neurons.

Understanding the dynamics of noisy neurons remains an important challenge in neuroscience. Here, we describe a simple probabilistic model that accurately describes the firing behavior in a large class (type II) of neurons. To demonstrate the usefulness of this model, we show how it accurately predicts the interspike interval (ISI) distributions, bursting patterns and mean firing rates found by: (1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental data from squid giant axon with a noisy input current and (3) experimental data on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple model has 6 parameters, however, in some cases, two of these parameters are coupled and only 5 parameters account for much of the known behavior. From these parameters, many properties of spiking can be found through simple calculation. Thus, we show how the complex effects of noise can be understood through a simple and general probabilistic model.

Optimal stimulus waveforms for eliciting a spike: How close is the spike-triggered average?

Computing the average input stimulus preceding a spike, the spike-triggered average (STA), has been a powerful tool for discovering a neuron's 'preferred' stimulus feature that enables efficient encoding of sensory information. Recent work in the squid giant axon has shown that STA waveforms can be remarkably similar to the energetically optimal stimulus waveforms for eliciting a spike. In the present study, we show using the Hodgkin-Huxley model that the STA can deviate from the global optimal solution if there is averaging of multiple solutions across different time scales and of multiple modes of spike induction. These findings inform attempts to develop model-free stochastic algorithms for finding energy-optimal stimuli, which is relevant to the efficient delivery of exogenous therapeutic stimuli in neurological diseases.

A case of early-onset rapidly progressive dementia.

A 62-year-old man presented with rapidly progressive cognitive decline associated with ataxia, spasticity, and eventually seizures. Multiple bihemispheric foci of calcification in the brain were seen on computed tomography scan, with magnetic resonance imaging (MRI) showing relatively symmetrical areas of enhancement in the brain corresponding mostly to the areas of calcification. Cerebrospinal fluid analysis and 2 brain biopsy specimens showed no evidence of an infectious, inflammatory, or malignant process. Despite being treated empirically with high-dose corticosteroids, the patient continued to deteriorate, with the family deciding for hospice care. The final autopsy diagnosis and the approach to the clinical data are discussed.

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm.

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

Ionic mechanism underlying optimal stimuli for neuronal excitation: role of Na+ channel inactivation.

The ionic mechanism underlying optimal stimulus shapes that induce a neuron to fire an action potential, or spike, is relevant to understanding optimal information transmission and therapeutic stimulation in the nervous system. Here we analyze for the first time the ionic basis for stimulus optimality in the Hodgkin and Huxley model and for eliciting a spike in squid giant axons, the preparation for which the model was devised. The experimentally determined stimulus is a smoothly varying biphasic current waveform having a relatively long and shallow hyperpolarizing phase followed by a depolarizing phase of briefer duration. The hyperpolarizing phase removes a small degree of the resting level of Na(+) channel inactivation. This result together with the subsequent depolarizing phase provides a signal that is energetically more efficient for eliciting spikes than rectangular current pulses. Sodium channel inactivation is the only variable that is changed during the stimulus waveform, other than the membrane potential, V. The activation variables for Na(+) and K(+) channels are unchanged throughout the stimulus. This result demonstrates how an optimal stimulus waveform relates to ionic dynamics and may have implications for energy efficiency of neural excitation in many systems including the mammalian brain.

Optimal stimulus shapes for neuronal excitation.

An important problem in neuronal computation is to discern how features of stimuli control the timing of action potentials. One aspect of this problem is to determine how an action potential, or spike, can be elicited with the least energy cost, e.g., a minimal amount of applied current. Here we show in the Hodgkin & Huxley model of the action potential and in experiments on squid giant axons that: 1) spike generation in a neuron can be highly discriminatory for stimulus shape and 2) the optimal stimulus shape is dependent upon inputs to the neuron. We show how polarity and time course of post-synaptic currents determine which of these optimal stimulus shapes best excites the neuron. These results are obtained mathematically using the calculus of variations and experimentally using a stochastic search methodology. Our findings reveal a surprising complexity of computation at the single cell level that may be relevant for understanding optimization of signaling in neurons and neuronal networks.

A simple modification of the Hodgkin and Huxley equations explains type 3 excitability in squid giant axons.

The Hodgkin and Huxley (HH) model predicts sustained repetitive firing of nerve action potentials for a suprathreshold depolarizing current pulse for as long as the pulse is applied (type 2 excitability). Squid giant axons, the preparation for which the model was intended, fire only once at the beginning of the pulse (type 3 behaviour). This discrepancy between the theory and experiments can be removed by modifying a single parameter in the HH equations for the K+ current as determined from the analysis in this paper. K+ currents in general have been described by IK=gK(V-EK), where gK is the membrane's K+ current conductance and EK is the K+ Nernst potential. However, IK has a nonlinear dependence on (V-EK) well described by the Goldman-Hodgkin-Katz equation that determines the voltage dependence of gK. This experimental finding is the basis for the modification in the HH equations describing type 3 behaviour. Our analysis may have broad significance given the use of IK=gK(V-EK) to describe K+ currents in a wide variety of biological preparations.