Data processing techniques impact quantification of cortico-cortical evoked potentials.

BACKGROUND: Cortico-cortical evoked potentials (CCEPs) are a common tool for probing effective connectivity in intracranial human electrophysiology. As with all human electrophysiology data, CCEP data are highly susceptible to noise. To address noise, filters and re-referencing are often applied to CCEP data, but different processing strategies are used from study to study. NEW METHOD: We systematically compare how common average re-referencing and filtering CCEP data impacts quantification. RESULTS: We show that common average re-referencing and filters, particularly filters that cut out more frequencies, can significantly impact the quantification of CCEP magnitude and morphology. We identify that high cutoff high pass filters (> 0.5 Hz), low cutoff low pass filters (< 200 Hz), and common average re-referencing impact quantification across subjects. However, we also demonstrate that the presence of noise may impact CCEP quantification, and preprocessing is necessary to mitigate this. We show that filtering is more effective than re-referencing or averaging across trials for reducing most common types of noise. COMPARISON WITH EXISTING METHODS: These results suggest that existing CCEP processing methods must be applied with care to maximize noise reduction and minimize changes to the data. We do not test every available processing strategy; rather we demonstrate that processing can influence the results of CCEP studies. We emphasize the importance of reporting all processing methods, particularly re-referencing methods. CONCLUSIONS: We propose a general framework for choosing an appropriate processing pipeline for CCEP data, taking into consideration the noise levels of a specific dataset. We suggest that minimal gentle filtering is preferable.

Metabolism of a New Dipeptide Neuroprotector in Rats.

Metabolism of a new neuroprotector GZK-111 (N-phenylacetylglycyl-L-proline ethyl ester) in rat blood plasma was studied by HPLC-mass spectrometry. Four biotransformation products were identified. It is concluded that the main ways of GZK-111 biotransformation are hydrolysis of the ester bond by esterases followed by degradation of the resulting metabolite, as well as reactions leading to the formation of phenylacetic acid and cycloprolylglycine that exhibits neuropsychotropic activity.

Preclinical Pharmacokinetics of GZK-111, a Dipeptide with Neuroprotective Activity.

We studied the pharmacokinetics of GZK-111 (N-phenylacetyl-glycyl-L-proline ethyl ether), a compound with neuroprotective activity, and its metabolite CPG (cyclo-L-prolylglycine) in rat blood plasma after single intravenous and intragastric administration in a dose of 20 mg/kg. It was found that the parent drug undergoes intensive biotransformation; its metabolite CPG persists in the circulation more than twice as long as GZK-111 and its plasma concentrations were higher by 50-70 times than the concentrations of the parent compound.

HCN Channel Phosphorylation Sites Mapped by Mass Spectrometry in Human Epilepsy Patients and in an Animal Model of Temporal Lobe Epilepsy.

Because hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channels modulate the excitability of cortical and hippocampal principal neurons, these channels play a key role in the hyperexcitability that occurs during the development of epilepsy after a brain insult, or epileptogenesis. In epileptic rats generated by pilocarpine-induced status epilepticus, HCN channel activity is downregulated by two main mechanisms: a hyperpolarizing shift in gating and a decrease in amplitude of the current mediated by HCN channels, Ih. Because these mechanisms are modulated by various phosphorylation signaling pathways, we hypothesized that phosphorylation changes occur at individual HCN channel amino acid residues (phosphosites) during epileptogenesis. We collected CA1 hippocampal tissue from male Sprague Dawley rats made epileptic by pilocarpine-induced status epilepticus, and age-matched naïve controls. We also included resected human brain tissue containing epileptogenic zones (EZs) where seizures arise for comparison to our chronically epileptic rats. After enrichment for HCN1 and HCN2 isoforms by immunoprecipitation and trypsin in-gel digestion, the samples were analyzed by mass spectrometry. We identified numerous phosphosites from HCN1 and HCN2 channels, representing a novel survey of phosphorylation sites within HCN channels. We found high levels of HCN channel phosphosite homology between humans and rats. We also identified a novel HCN1 channel phosphosite S791, which underwent significantly increased phosphorylation during the chronic epilepsy stage. Heterologous expression of a phosphomimetic mutant, S791D, replicated a hyperpolarizing shift in Ih gating seen in neurons from chronically epileptic rats. These results show that HCN1 channel phosphorylation is altered in epilepsy and may be of pathogenic importance.

Fully implanted adaptive deep brain stimulation in freely moving essential tremor patients.

OBJECTIVE: Deep brain stimulation (DBS) is a safe and established treatment for essential tremor (ET) and several other movement disorders. One approach to improving DBS therapy is adaptive DBS (aDBS), in which stimulation parameters are modulated in real time based on biofeedback from either external or implanted sensors. Previously tested systems have fallen short of translational applicability due to the requirement for patients to continuously wear the necessary sensors or processing devices, as well as privacy and security concerns. APPROACH: We designed and implemented a translation-ready training data collection system for fully implanted aDBS. Two patients chronically implanted with electrocorticography strips over the hand portion of M1 and DBS probes in the ipsilateral ventral intermediate nucleus of the thalamus for treatment of ET were recruited for this study. Training was conducted using a translation-ready distributed training procedure, allowing a substantially higher degree of control over data collection than previous works. A linear classifier was trained using this system, biased towards activating stimulation in accordance with clinical considerations. MAIN RESULTS: The clinically relevant average false negative rate, defined as fraction of time during which stimulation dropped below [Formula: see text] clinical levels during movement epochs, was 0.036. Tremor suppression, calculated through analysis of gyroscope data, was 33.2% more effective on average with aDBS than with continuous DBS. During a period of free movement with aDBS, one patient reported a slight paresthesia; patients noticed no difference in treatment efficacy between systems. SIGNIFICANCE: Here is presented the first translation-ready training procedure for a fully embedded aDBS control system for MDs and one of the first examples of such a system in ET, adding to the consensus that fully implanted aDBS systems are sufficiently mature for broader deployment in treatment of movement disorders.

Signal recovery from stimulation artifacts in intracranial recordings with dictionary learning.

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.

[An assessment of the helminthiasis situation in Belorussia by the dynamics of the mean multiyear indices of population morbidity]. / Otsenka situatsii po gel'mintozam v Belorussii po dinamike srednemnogoletnikh pokazatelei zabolevaemosti naseleniia.

The study of population morbidity with helminthiasis prevalence in Byelorussia has revealed 11 nosological entities and has established that in 99.9% these were cases of ascariasis, trichocephaliasis and enterobiasis. In 1981-1989 dynamics of ascariasis and trichocephaliasis morbidity was characterized by a marked tendency towards its decrease, while there was a tendency towards moderate growth in enterobiasis morbidity. The values of the (intensive) rates of helminthiasis morbidity during the examination of hundreds of thousands people does not considerably depend on the fluctuations of the number of persons examined on the presence of helminths. To elaborate systems for epidemiologic surveys of helminthiasis it is necessary to increase the volume and improve the quality of information on the morbidity rates.