Journal of Neural Engineering (J Neural Eng)

Publisher: Institute of Physics (Great Britain), IOP Publishing

Journal description

Journal of Neural Engineering is a new forum for the interdisciplinary field of neural engineering, where neuroscientists, neurobiologists and engineers can publish their work in one periodical that bridges the gap between neuroscience and engineering. Articles will cover the field of neural engineering at the molecular, cellular and systems levels.

Current impact factor: 3.30

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 3.295
2013 Impact Factor 3.415
2012 Impact Factor 3.282
2011 Impact Factor 3.837
2010 Impact Factor 2.628
2009 Impact Factor 3.739
2008 Impact Factor 2.737

Impact factor over time

Impact factor

Additional details

5-year impact 3.74
Cited half-life 3.90
Immediacy index 0.75
Eigenfactor 0.01
Article influence 1.08
Website Journal of Neural Engineering website
Other titles Journal of neural engineering (Online), Neural engineering, JNE
ISSN 1741-2552
OCLC 54314172
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

IOP Publishing

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Pre-print on author's personal website, repository or arXiv.
    • Pre-print can not be updated after submission
    • Post-print on author's personal website immediately
    • Post-print on institutional repository, subject-based repository, PubMed Central or third party eprint servers after 12 months embargo
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged with citation
    • Must link to publisher version with DOI
    • Set statements to accompany different versions (see policy)
    • This policy is an exception to the default policies of 'IOP Publishing'
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we propose a novel method to determine the circadian variation of scalp electroencephalogram (EEG) in both individual and group levels using a correlation sum measure, quantifying self-similarity of the EEG relative energy across waking epochs. We analysed EEG recordings from central-parietal and occipito-parietal montages in nine healthy subjects undergoing a 72 h ultradian sleep-wake cycle protocol. Each waking epoch (∼1 s) of every nap opportunity was decomposed using the wavelet packet transform, and the relative energy for that epoch was calculated in the desired frequency band using the corresponding wavelet coefficients. Then, the resulting set of energy values was resampled randomly to generate different subsets with equal number of elements. The correlation sum of each subset was then calculated over a range of distance thresholds, and the average over all subsets was computed. This average value was finally scaled for each nap opportunity and considered as a new circadian measure. According to the evaluation results, a clear circadian rhythm was identified in some EEG frequency ranges, particularly in 4-8 Hz and 10-12 Hz. The correlation sum measure not only was able to disclose the circadian rhythm on the group data but also revealed significant circadian variations in most individual cases, as opposed to previous studies only reporting the circadian rhythms on a population of subjects. Compared to a naive measure based on the EEG absolute energy in the frequency band of interest, the proposed measure showed a clear superiority using both individual and group data. Results also suggested that the acrophase (i.e., the peak) of the circadian rhythm in 10-12 Hz occurs close to the core body temperature minimum. These results confirm the potential usefulness of the proposed EEG-based measure as a non-invasive circadian marker.
    Journal of Neural Engineering 10/2015; 12(5). DOI:10.1088/1741-2560/12/5/056004
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    ABSTRACT: Objective: The advancement of surface electromyogram (sEMG) recording and signal processing techniques has allowed us to characterize the recruitment properties of a substantial population of motor units (MUs) non-invasively. Here we seek to determine whether MU recruitment properties are modified in paretic muscles of hemispheric stroke survivors. Approach: Using an advanced EMG sensor array, we recorded sEMG during isometric contractions of the first dorsal interosseous muscle over a range of contraction levels, from 20% to 60% of maximum, in both paretic and contralateral muscles of stroke survivors. Using MU decomposition techniques, MU action potential amplitudes and recruitment thresholds were derived for simultaneously activated MUs in each isometric contraction. Main results: Our results show a significant disruption of recruitment organization in paretic muscles, in that the size principle describing recruitment rank order was materially distorted. MUs were recruited over a very narrow force range with increasing force output, generating a strong clustering effect, when referenced to recruitment force magnitude. Such disturbances in MU properties also correlated well with the impairment of voluntary force generation. Significance: Our findings provide direct evidence regarding MU recruitment modifications in paretic muscles of stroke survivors, and suggest that these modifications may contribute to weakness for voluntary contractions.
    Journal of Neural Engineering 09/2015; 12(6):066001. DOI:10.1088/1741-2560/12/6/066001
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    ABSTRACT: Objective: Current approaches in neurofeedback/brain-computer interface research often focus on identifying, on a subject-by-subject basis, the neural regions that are best suited for self-driven modulation. It is known that the hMT+/V5 complex, an early visual cortical region, is recruited during explicit and implicit motion imagery, in addition to real motion perception. This study tests the feasibility of training healthy volunteers to regulate the level of activation in their hMT+/V5 complex using real-time fMRI neurofeedback and visual motion imagery strategies. Approach: We functionally localized the hMT+/V5 complex to further use as a target region for neurofeedback. An uniform strategy based on motion imagery was used to guide subjects to neuromodulate hMT+/V5. Main results: We found that 15/20 participants achieved successful neurofeedback. This modulation led to the recruitment of a specific network as further assessed by psychophysiological interaction analysis. This specific circuit, including hMT+/V5, putative V6 and medial cerebellum was activated for successful neurofeedback runs. The putamen and anterior insula were recruited for both successful and non-successful runs. Significance: Our findings indicate that hMT+/V5 is a region that can be modulated by focused imagery and that a specific cortico-cerebellar circuit is recruited during visual motion imagery leading to successful neurofeedback. These findings contribute to the debate on the relative potential of extrinsic (sensory) versus intrinsic (default-mode) brain regions in the clinical application of neurofeedback paradigms. This novel circuit might be a good target for future neurofeedback approaches that aim, for example, the training of focused attention in disorders such as ADHD.
    Journal of Neural Engineering 09/2015; 12(6):066003. DOI:10.1088/1741-2560/12/6/066003
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    ABSTRACT: Objective: Prefrontal hemodynamic responses are observed during performance of motor tasks. Using a dance video game (DVG), a complex motor task that requires temporally accurate footsteps with given visual and auditory cues, we investigated whether 20 h of DVG training modified hemodynamic responses of the prefrontal cortex in six healthy young adults. Approach: Fronto-temporal activity during actual DVG play was measured using functional near-infrared spectroscopy (fNIRS) pre- and post-training. To evaluate the training-induced changes in the time-courses of fNIRS signals, we employed a regression analysis using the task-specific template fNIRS signals that were generated from alternate well-trained and/or novice DVG players. The HRF was also separately incorporated as a template to construct an alternate regression model. Change in coefficients for template functions at pre- and post- training were determined and compared among different models. Main results: Training significantly increased the motor performance using the number of temporally accurate steps in the DVG as criteria. The mean oxygenated hemoglobin (ΔoxyHb) waveform changed from an activation above baseline pattern to that of a below baseline pattern. Participants showed significantly decreased coefficients for regressors of the ΔoxyHb response of novice players and HRF. The model using ΔoxyHb responses from both well-trained and novice players of DVG as templates showed the best fit for the ΔoxyHb responses of the participants at both pre- and post-training when analyzed with Akaike information criteria. Significance: These results suggest that the coefficients for the template ΔoxyHb responses of the novice players are sensitive indicators of motor learning during the initial stage of training and thus clinically useful to determine the improvement in motor performance when patients are engaged in a specific rehabilitation program.
    Journal of Neural Engineering 09/2015; 12(6):066004. DOI:10.1088/1741-2560/12/6/066004
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    ABSTRACT: Objective. Speech intelligibility with existing multichannel cochlear implants (CIs) is thought to be limited by poor spatial selectivity and interactions between CI channels caused by overlapping activation with monopolar (MP) stimulation. Our previous studies have shown that focused multipolar (FMP) and tripolar (TP) stimulation produce more restricted neural activation in the inferior colliculus (IC), compared to MP stimulation. Approach. This study explored interactions in the IC produced by simultaneous stimulation of two CI channels. We recorded multi-unit neural activity in the IC of anaesthetized cats with normal and severely degenerated spiral ganglion neuron populations in response to FMP, TP and MP stimulation from a 14 channel CI. Stimuli were applied to a ‘fixed’ CI channel, chosen toward the middle of the cochlear electrode array, and the effects of simultaneously stimulating a more apical ‘test’ CI channel were measured as a function of spatial separation between the two stimulation channels and stimulus level of the fixed channel. Channel interactions were quantified by changes in neural responses and IC threshold (i.e., threshold shift) elicited by simultaneous stimulation of two CI channels, compared to stimulation of the test channel alone. Main results. Channel interactions were significantly lower for FMP and TP than for MP stimulation (p Significance. The present study demonstrates how the degree of channel interactions in a CI can be controlled using stimulation configurations such as FMP and TP; such knowledge is essential in enhancing CI function in complex acoustic environments.
    Journal of Neural Engineering 09/2015; 12(6):066005. DOI:10.1088/1741-2560/12/6/066005
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    ABSTRACT: Objective: Although electrode size should be miniaturized to provide higher selectivity for neural signal recording and to avoid tissue damage, small sized electrodes induce high impedance, which decreases recording quality. In this work, the electrode surface was modified to increase the effective surface area to lower the electrode impedance and to improve the neural signal detection quality by optimizing plasma conditions. Approach: A tetrafluoromethane (CF4) plasma was used to increase the effective surface area of gold electrode sites of polyimide-based neural probes. In vitro electrode impedance and in vivo neural signal recording and stimulation were characterized. Main results: For 15 μm diameter (dia.) electrode size, the average surface roughness could be increased from 1.7 to 22 nm after plasma treatment, and the electrode impedance was decreased by 98%. Averaged background noise power in the range of 1 to 1000 Hz was decreased to -106 dB after the 30 μm dia. electrodes were plasma modified-lower than the noise level of -86 dB without plasma treatment. Neural probes with plasma-modified electrode sites of 15 and 30 μm dia. were implanted to the anterior cingulate cortex (ACC) region for acute recording of spontaneous and electrical evoked local field potential (LFP) of neural signals. Spontaneous LFP recorded in vivo by the plasma-modified electrodes of 30 μm dia. was two times higher compared to electrodes without treatment. For a stimulation current of 400 μA, electrically evoked LFP recorded by the plasma-modified electrodes was seven times higher than those without plasma exposure. Significance: A controllable technology was developed to increase the effective surface area of electrodes using a CF4 plasma. Plasma-modified electrodes improved the quality of the neural probe recording and more sensitive to record spontaneous and evoked LFP in the ACC region.
    Journal of Neural Engineering 09/2015; 12(5):056018. DOI:10.1088/1741-2560/12/5/056018
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    ABSTRACT: Swallowing and swallowing disorders have garnered continuing interest over the past several decades. Electroencephalography (EEG) is an inexpensive and non-invasive procedure with very high temporal resolution which enables analysis of short and fast swallowing events, as well as an analysis of the organizational and behavioral aspects of cortical motor preparation, swallowing execution and swallowing regulation. EEG is a powerful technique which can be used alone or in combination with other techniques for monitoring swallowing, detection of swallowing motor imagery for diagnostic or biofeedback purposes, or to modulate and measure the effects of swallowing rehabilitation. This paper provides a review of the existing literature which has deployed EEG in the investigation of oropharyngeal swallowing, smell, taste and texture related to swallowing, cortical pre-motor activation in swallowing, and swallowing motor imagery detection. Furthermore, this paper provides a brief review of the different modalities of brain imaging techniques used to study swallowing brain activities, as well as the EEG components of interest for studies on swallowing and on swallowing motor imagery. Lastly, this paper provides directions for future swallowing investigations using EEG.
    Journal of Neural Engineering 09/2015; 12(5):051001. DOI:10.1088/1741-2560/12/5/051001
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    ABSTRACT: Objective: In the last decade, multiple brain areas have been investigated with respect to their decoding capability of continuous arm or hand movements. So far, these studies have mainly focused on motor or premotor areas like M1 and F5. However, there is accumulating evidence that anterior intraparietal area (AIP) in the parietal cortex also contains information about continuous movement. Approach: In this study, we decoded 27 degrees of freedom representing complete hand and arm kinematics during a delayed grasping task from simultaneously recorded activity in areas M1, F5, and AIP of two macaque monkeys (Macaca mulatta). Main results: We found that all three areas provided decoding performances that lay significantly above chance. In particular, M1 yielded highest decoding accuracy followed by F5 and AIP. Furthermore, we provide support for the notion that AIP does not only code categorical visual features of objects to be grasped, but also contains a substantial amount of temporal kinematic information. Significance: This fact could be utilized in future developments of neural interfaces restoring hand and arm movements.
    Journal of Neural Engineering 09/2015; 12(5):056016. DOI:10.1088/1741-2560/12/5/056016
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    ABSTRACT: The dexterous manipulation of objects depends heavily on somatosensory signals from the limb. The development of anthropomorphic robotic arms and of algorithms to decode intended movements from neuronal signals has stimulated the need to restore somatosensation for use in upper-limb neuroprostheses. Without touch and proprioception, patients have difficulty controlling prosthetic limbs to a level that justifies the required invasive surgery. Intracortical microstimulation (ICMS) through chronically implanted electrode arrays has the potential to provide rich and intuitive sensory feedback. This approach to sensory restoration requires, however, that the evoked sensations remain stable over time. To investigate the stability of ICMS-evoked sensations, we measured the ability of non-human primates to detect ICMS over experimental sessions that spanned years. We found that the performance of the animals remained highly stable over time, even when they were tested with electrodes that had experienced extensive stimulation. Given the stability of the sensations that it evokes, ICMS may thus be a viable approach for sensory restoration.
    Journal of Neural Engineering 08/2015; 12(5):056010. DOI:10.1088/1741-2560/12/5/056010
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    ABSTRACT: We have developed an asynchronous brain-machine interface (BMI)-based lower limb exoskeleton control system based on steady-state visual evoked potentials (SSVEPs). By decoding electroencephalography signals in real-time, users are able to walk forward, turn right, turn left, sit, and stand while wearing the exoskeleton. SSVEP stimulation is implemented with a visual stimulation unit, consisting of five light emitting diodes fixed to the exoskeleton. A canonical correlation analysis (CCA) method for the extraction of frequency information associated with the SSVEP was used in combination with k-nearest neighbors. Overall, 11 healthy subjects participated in the experiment to evaluate performance. To achieve the best classification, CCA was first calibrated in an offline experiment. In the subsequent online experiment, our results exhibit accuracies of 91.3 ± 5.73%, a response time of 3.28 ± 1.82 s, an information transfer rate of 32.9 ± 9.13 bits/min, and a completion time of 1100 ± 154.92 s for the experimental parcour studied. The ability to achieve such high quality BMI control indicates that an SSVEP-based lower limb exoskeleton for gait assistance is becoming feasible.
    Journal of Neural Engineering 08/2015; 12(5):056009. DOI:10.1088/1741-2560/12/5/056009
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    ABSTRACT: People with disabilities may control devices such as a computer or a wheelchair by means of a brain-computer interface (BCI). BCI based on steady-state visual evoked potentials (SSVEP) requires visual stimulation of the user. However, this SSVEP-based BCI suffers from the 'Midas touch effect', i.e., the BCI can detect an SSVEP even when the user is not gazing at the stimulus. Then, these incorrect detections deteriorate the performance of the system, especially in asynchronous BCI because ongoing EEG is classified. In this paper, a novel transitory response of the attention-level of the user is reported. It was used to develop a hybrid BCI (hBCI). Three methods are proposed to detect the attention-level of the user. They are based on the alpha rhythm and theta/beta rate. The proposed hBCI scheme is presented along with these methods. Hence, the hBCI sends a command only when the user is at a high-level of attention, or in other words, when the user is really focused on the task being performed. The hBCI was tested over two different EEG datasets. The performance of the hybrid approach is superior to the standard one. Improvements of 20% in accuracy and 10 bits min(-1) are reported. Moreover, the attention-level is extracted from the same EEG channels used in SSVEP detection and this way, no extra hardware is needed. A transitory response of EEG signal is used to develop the attention-SSVEP hBCI which is capable of reducing the Midas touch effect.
    Journal of Neural Engineering 08/2015; 12(5):056007. DOI:10.1088/1741-2560/12/5/056007
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    ABSTRACT: This work deals with studying and improving the insulation lifetime of polyimide-insulated thin film neural implants, or related polyimide-based medical implants. The evolution of the leak impedance of insulated conductors was investigated in saline water at 40 °C. The fabrication process as commonly found in literature for polyimide/platinum/polyimide microelectrode arrays was compared with three possible improvements: one based on lowering the curing temperature of the lower layer, one based on chemical activation and one based on an additional plasma activation step. The lower curing temperature process was found to yield a 7.5-fold improved lifetime compared with the state of the art process. Also, the leak impedances found after soak testing are an order of magnitude higher compared to the standard process. By improving the lifetime and insulation impedance of polyimide insulation with one order of magnitude, this work increases the applicability of polyimide in chronic thin film neural implants considerably.
    Journal of Neural Engineering 08/2015; 12(5):054001. DOI:10.1088/1741-2560/12/5/054001
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    ABSTRACT: Ketamine is a widely used drug with clinical and research applications, and also known to be used as a recreational drug. Ketamine produces conspicuous changes in the electrocorticographic (ECoG) signals observed both in humans and rodents. In rodents, the intracranial ECoG displays a high-frequency oscillation (HFO) which power is modulated nonlinearly by ketamine dose. Despite the widespread use of ketamine there is no model description of the relationship between the pharmacokinetic-pharmacodynamics (PK-PDs) of ketamine and the observed HFO power. In the present study, we developed a PK-PD model based on estimated ketamine concentration, its known pharmacological actions, and observed ECoG effects. The main pharmacological action of ketamine is antagonism of the NMDA receptor (NMDAR), which in rodents is accompanied by an HFO observed in the ECoG. At high doses, however, ketamine also acts at non-NMDAR sites, produces loss of consciousness, and the transient disappearance of the HFO. We propose a two-compartment PK model that represents the concentration of ketamine, and a PD model based in opposing effects of the NMDAR and non-NMDAR actions on the HFO power. We recorded ECoG from the cortex of rats after two doses of ketamine, and extracted the HFO power from the ECoG spectrograms. We fit the PK-PD model to the time course of the HFO power, and showed that the model reproduces the dose-dependent profile of the HFO power. The model provides good fits even in the presence of high variability in HFO power across animals. As expected, the model does not provide good fits to the HFO power after dosing the pure NMDAR antagonist MK-801. Our study provides a simple model to relate the observed electrophysiological effects of ketamine to its actions at the molecular level at different concentrations. This will improve the study of ketamine and rodent models of schizophrenia to better understand the wide and divergent range of effects that ketamine has.
    Journal of Neural Engineering 08/2015; 12(5):056006. DOI:10.1088/1741-2560/12/5/056006