Journal of Neural Engineering

Papers
(The H4-Index of Journal of Neural Engineering is 36. 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 2021-06-01 to 2025-06-01.)
ArticleCitations
Neural regulation of slow waves and phasic contractions in the distal stomach: a mathematical model139
Tensor factorization approach for ERP-based assessment of schizotypy in a novel auditory oddball task on perceived family stress134
Sensor selection and miniaturization limits for detection of interictal epileptiform discharges with wearable EEG128
A message from the incoming editor100
Convolutional neural network classifies visual stimuli from cortical response recorded with wide-field imaging in mice83
Superior galvanostatic electrochemical deposition of platinum nanograss provides high performance planar microelectrodes for in vitro neural recording81
Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery70
Motor imagery with cues in virtual reality, audio and screen70
Delayed administration of interleukin-4 coacervate alleviates the neurotoxic phenotype of astrocytes and promotes functional recovery after a contusion spinal cord injury67
Identification of impulsive adolescents with a functional near infrared spectroscopy (fNIRS) based decision support system67
Source space reduction for eLORETA59
Nonlinear model predictive control of a conductance-based neuron model via data-driven forecasting54
Sensorimotor brain–computer interface performance depends on signal-to-noise ratio but not connectivity of the mu rhythm in a multiverse analysis of longitudinal data52
Decoding of cortex-wide brain activity from local recordings of neural potentials51
Low-cost and easy-fabrication lightweight drivable electrode array for multiple-regions electrophysiological recording in free-moving mice51
Modeling multiscale causal interactions between spiking and field potential signals during behavior47
Real-time modeling and feature extraction method of surface electromyography signal for hand movement classification based on oscillatory theory44
Simultaneous encoding of speed, distance, and direction in discrete reaching: an EEG study44
Wireless transmission of voltage transients from a chronically implanted neural stimulation device43
Bridging the gap between patient-specific and patient-independent seizure prediction via knowledge distillation43
Enhancement of EEG–EMG coupling detection using corticomuscular coherence with spatial–temporal optimization42
Stimulation-induced changes at the electrode–tissue interface and their influence on deep brain stimulation42
A low-cost transhumeral prosthesis operated via an ML-assisted EEG-head gesture control system41
First-in-human experience performing high-resolution cortical mapping using a novel microelectrode array containing 1024 electrodes40
A 0.53-μW/channel calibration-free spike detection IC with 98.8-%-accuracy based on stationary wavelet transforms and Teager energy operators40
5-year follow-up of a fully implanted brain–computer interface in a spinal cord injury patient40
A new attention-based 3D densely connected cross-stage-partial network for motor imagery classification in BCI39
Accuracy and precision of navigated transcranial magnetic stimulation39
A meta-learning BCI for estimating decision confidence39
Multimodal motor imagery decoding method based on temporal spatial feature alignment and fusion38
Electrochemical methods for neural interface electrodes36
Biomechanical micromotion at the neural interface modulates intracellular membrane potentials in vivo36
A high-performance brain switch based on code-modulated visual evoked potentials36
TMS-induced phase resets depend on TMS intensity and EEG phase36
Neural tracking to go: auditory attention decoding and saliency detection with mobile EEG36
Multiparametric non-linear TENS modulation to integrate intuitive sensory feedback36
TRCA-Net: using TRCA filters to boost the SSVEP classification with convolutional neural network36
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