Accurate QRS detection is an important first step for the analysis of heart rate variability. Algorithms based on the differentiated ECG are computationally efficient and hence ideal for real-time analysis of large datasets. Here, we analyze traditional first-derivative based squaring function (Hamilton-Tompkins) and Hilbert transform-based methods for QRS detection and their modifications with improved detection thresholds. On a standard ECG dataset, the Hamilton-Tompkins algorithm had the highest detection accuracy (99.68% sensitivity, 99.63% positive predictivity) but also the largest time error. The modified Hamilton-Tompkins algorithm as well as the Hilbert transform-based algorithms had comparable, though slightly lower, accuracy; yet these automated algorithms present an advantage for real-time applications by avoiding human intervention in threshold determination. The high accuracy of the Hilbert transform-based method compared to detection with the second derivative of the ECG is ascribable to its inherently uniform magnitude spectrum. For all algorithms, detection errors occurred mainly in beats with decreased signal slope, such as wide arrhythmic beats or attenuated beats. For best performance, a combination of the squaring function and Hilbert transform-based algorithms can be applied such that differences in detection will point to abnormalities in the signal that can be further analyzed.

Neuropsychiatric disorders are a leading source of disability and require novel treatments that target mechanisms of disease. As such disorders are thought to result from aberrant neuronal circuit activity, neuromodulation approaches are of increasing interest given their potential for manipulating circuits directly. Low intensity transcranial electrical stimulation (tES) with direct currents (transcranial direct current stimulation, tDCS) or alternating currents (transcranial alternating current stimulation, tACS) represent novel, safe, well-tolerated, and relatively inexpensive putative treatment modalities. This report seeks to promote the science, technology and effective clinical applications of these modalities, identify research challenges, and suggest approaches for addressing these needs in order to achieve rigorous, reproducible findings that can advance clinical treatment. The National Institute of Mental Health (NIMH) convened a workshop in September 2016 that brought together experts in basic and human neuroscience, electrical stimulation biophysics and devices, and clinical trial methods to examine the physiological mechanisms underlying tDCS/tACS, technologies and technical strategies for optimizing stimulation protocols, and the state of the science with respect to therapeutic applications and trial designs. Advances in understanding mechanisms, methodological and technological improvements (e.g., electronics, computational models to facilitate proper dosing), and improved clinical trial designs are poised to advance rigorous, reproducible therapeutic applications of these techniques. A number of challenges were identified and meeting participants made recommendations made to address them. These recommendations align with requirements in NIMH funding opportunity announcements to, among other needs, define dosimetry, demonstrate dose/response relationships, implement rigorous blinded trial designs, employ computational modeling, and demonstrate target engagement when testing stimulation-based interventions for the treatment of mental disorders.

We present the first computational study comparing the electric field induced by various electroconvulsive therapy (ECT) and magnetic seizure therapy (MST) paradigms. Four ECT electrode configurations (bilateral, bifrontal, right unilateral, and focal electrically administered seizure therapy) and three MST coil configurations (circular, cap, and double cone) were modeled. The model incorporated a modality-specific neural activation threshold. ECT (0.3 ms pulse width) and MST induced the maximum electric field of 2.1-2.5 V cm⁻¹ and 1.1-2.2 V cm⁻¹ in the brain, corresponding to 6.2-7.2 times and 1.2-2.3 times the neural activation threshold, respectively. The MST electric field is more confined to the superficial cortex compared to ECT. The brain volume stimulated was much larger with ECT (up to 100%) than with MST (up to 8.2%). MST with the double-cone coil was the most focal, and bilateral ECT was the least focal. Our results suggest a possible biophysical explanation of the reduced side effects of MST compared to ECT. Our results also indicate that the conventional ECT pulse amplitude (800-900 mA) is much higher than necessary for seizure induction. Reducing the ECT pulse amplitude should be explored as a potential means of diminishing side effects.

This Technical Report describes new methods of transcranial magnetic stimulation (TMS) in non-human primates. By combining single neuron recording with a modified TMS coil with focused stimulation in alert macaques, the authors show that this method can reduce stimulation artifact and allow investigation into the neuronal mechanisms of TMS. Transcranial magnetic stimulation (TMS) is a widely used, noninvasive method for stimulating nervous tissue, yet its mechanisms of effect are poorly understood. Here we report new methods for studying the influence of TMS on single neurons in the brain of alert non-human primates. We designed a TMS coil that focuses its effect near the tip of a recording electrode and recording electronics that enable direct acquisition of neuronal signals at the site of peak stimulus strength minimally perturbed by stimulation artifact in awake monkeys (Macaca mulatta). We recorded action potentials within ∼1 ms after 0.4-ms TMS pulses and observed changes in activity that differed significantly for active stimulation as compared with sham stimulation. This methodology is compatible with standard equipment in primate laboratories, allowing easy implementation. Application of these tools will facilitate the refinement of next generation TMS devices, experiments and treatment protocols.