Journal of Neural Engineering

Papers
(The H4-Index of Journal of Neural Engineering is 33. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-09-01 to 2025-09-01.)
ArticleCitations
Neural regulation of slow waves and phasic contractions in the distal stomach: a mathematical model159
Tensor factorization approach for ERP-based assessment of schizotypy in a novel auditory oddball task on perceived family stress141
A message from the incoming editor112
Motor imagery with cues in virtual reality, audio and screen81
Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery74
Identification of impulsive adolescents with a functional near infrared spectroscopy (fNIRS) based decision support system73
Nonlinear model predictive control of a conductance-based neuron model via data-driven forecasting65
Low-cost and easy-fabrication lightweight drivable electrode array for multiple-regions electrophysiological recording in free-moving mice64
Decoding of cortex-wide brain activity from local recordings of neural potentials55
Modeling multiscale causal interactions between spiking and field potential signals during behavior50
Simultaneous encoding of speed, distance, and direction in discrete reaching: an EEG study49
Wireless transmission of voltage transients from a chronically implanted neural stimulation device49
Bridging the gap between patient-specific and patient-independent seizure prediction via knowledge distillation46
A 0.53-μW/channel calibration-free spike detection IC with 98.8-%-accuracy based on stationary wavelet transforms and Teager energy operators45
Enhancement of EEG–EMG coupling detection using corticomuscular coherence with spatial–temporal optimization45
A meta-learning BCI for estimating decision confidence44
Sensorimotor brain–computer interface performance depends on signal-to-noise ratio but not connectivity of the mu rhythm in a multiverse analysis of longitudinal data44
Convolutional neural network classifies visual stimuli from cortical response recorded with wide-field imaging in mice43
A finite element method framework to model extracellular neural stimulation42
Multimodal motor imagery decoding method based on temporal spatial feature alignment and fusion41
TMS-induced phase resets depend on TMS intensity and EEG phase40
Decoding cortical responses from visual input using an endovascular brain–computer interface38
Multiparametric non-linear TENS modulation to integrate intuitive sensory feedback37
A systematic evaluation of Euclidean alignment with deep learning for EEG decoding37
Performance of optically pumped magnetometer magnetoencephalography: validation in large samples and multiple tasks37
Evaluating the clinical benefit of brain-computer interfaces for control of a personal computer35
First-in-human experience performing high-resolution cortical mapping using a novel microelectrode array containing 1024 electrodes35
Neural tracking to go: auditory attention decoding and saliency detection with mobile EEG34
A high-performance brain switch based on code-modulated visual evoked potentials34
5-year follow-up of a fully implanted brain–computer interface in a spinal cord injury patient34
Accuracy and precision of navigated transcranial magnetic stimulation34
Stimulation-induced changes at the electrode–tissue interface and their influence on deep brain stimulation34
Source space reduction for eLORETA34
Polyvinyl alcohol/polyacrylamide double-network hydrogel-based semi-dry electrodes for robust electroencephalography recording at hairy scalp for noninvasive brain–computer interfaces33
End-to-end learning of safe stimulation parameters for cortical neuroprosthetic vision33
Fascicles split or merge every ∼560 microns within the human cervical vagus nerve33
Electrochemical methods for neural interface electrodes33
Bayesian optimization of cortical neuroprosthetic vision using perceptual feedback33
A new attention-based 3D densely connected cross-stage-partial network for motor imagery classification in BCI33
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