JNE most-cited papers 2009–10

In recent years, there has been increasing interest in using steady-state visual evoked potential (SSVEP) in brain–computer interface (BCI) systems. However, several aspects of current SSVEP-based BCI systems need improvement, specifically in relation to speed, user variation and ease of use. With these improvements in mind, this paper presents an online multi-channel SSVEP-based BCI system using a canonical correlation analysis (CCA) method for extraction of frequency information associated with the SSVEP. The key parameters, channel location, window length and the number of harmonics, are investigated using offline data, and the result used to guide the design of the online system. An SSVEP-based BCI system with six targets, which use nine channel locations in the occipital and parietal lobes, a window length of 2 s and the first harmonic, is used for online testing on 12 subjects. The results show that the proposed BCI system has a high performance, achieving an average accuracy of 95.3% and an information transfer rate of 58 ± 9.6 bit min⁻¹. The positive characteristics of the proposed system are that channel selection and parameter optimization are not required, the possible use of harmonic frequencies, low user variation and easy setup.

Brain–computer interfaces (BCIs) have attracted much attention recently, triggered by new scientific progress in understanding brain function and by impressive applications. The aim of this review is to give an overview of the various steps in the BCI cycle, i.e., the loop from the measurement of brain activity, classification of data, feedback to the subject and the effect of feedback on brain activity. In this article we will review the critical steps of the BCI cycle, the present issues and state-of-the-art results. Moreover, we will develop a vision on how recently obtained results may contribute to new insights in neurocognition and, in particular, in the neural representation of perceived stimuli, intended actions and emotions. Now is the right time to explore what can be gained by embracing real-time, online BCI and by adding it to the set of experimental tools already available to the cognitive neuroscientist. We close by pointing out some unresolved issues and present our view on how BCI could become an important new tool for probing human cognition.

Significant progress has been made in systems that interpret the electrical signals of the brain in order to control an actuator. One version of these systems senses neuronal extracellular action potentials with an array of up to 100 miniature probes inserted into the cortex. The impedance of each probe is high, so environmental electrical noise is readily coupled to the neuronal signal. To minimize this noise, an amplifier is placed close to each probe. Thus, the need has arisen for many amplifiers to be placed near the cortex. Commercially available integrated circuits do not satisfy the area, power and noise requirements of this application, so researchers have designed custom integrated-circuit amplifiers. This paper presents a comprehensive survey of the neural amplifiers described in publications prior to 2008. Methods to achieve high input impedance, low noise and a large time-constant high-pass filter are reviewed. A tutorial on the biological, electrochemical, mechanical and electromagnetic phenomena that influence amplifier design is provided. Areas for additional research, including sub-nanoampere electrolysis and chronic cortical heating, are discussed. Unresolved design concerns, including teraohm circuitry, electrical overstress and component failure, are identified.

Aligned, electrospun polymer fibers have shown considerable promise in directing regenerating axons in vitro and in vivo. However, in several studies, final electrospinning parameters are presented for producing aligned fiber scaffolds, and alignment where minimal fiber crossing occurs is not achieved. Highly aligned species are necessary for neural tissue engineering applications to ensure that axonal extension occurs through a regenerating environment efficiently. Axonal outgrowth on fibers that deviate from the natural axis of growth may delay axonal extension from one end of a scaffold to the other. Therefore, producing aligned fiber scaffolds with little fiber crossing is essential. In this study, the contributions of four electrospinning parameters (collection disk rotation speed, needle size, needle tip shape and syringe pump flow rate) were investigated thoroughly with the goal of finding parameters to obtain highly aligned electrospun fibers made from poly-L-lactic acid (PLLA). Using an 8 wt% PLLA solution in chloroform, a collection disk rotation speed of 1000 revolutions per minute (rpm), a 22 gauge, sharp-tip needle and a syringe pump rate of 2 ml h⁻¹ produced highly aligned fiber (1.2–1.6 µm in diameter) scaffolds verified using a fast Fourier transform and a fiber alignment quantification technique. Additionally, the application of an insulating sheath around the needle tip improved the rate of fiber deposition (electrospinning efficiency). Optimized scaffolds were then evaluated in vitro using embryonic stage nine (E9) chick dorsal root ganglia (DRGs) and rat Schwann cells (SCs). To demonstrate the importance of creating highly aligned scaffolds to direct neurite outgrowth, scaffolds were created that contained crossing fibers. Neurites on these scaffolds were directed down the axis of the aligned fibers, but neurites also grew along the crossed fibers. At times, these crossed fibers even stopped further axonal extension. Highly aligned PLLA fibers generated under optimized electrospinning conditions guided neurite and SC growth along the aligned fibers. Schwann cells demonstrated the bipolar phenotype seen along the fibers. Using a novel technique to determine fiber density, an increase in fiber density correlated to an increase in the number of neurites, but average neurite length was not statistically different between the two different fiber densities. Together, this work presents methods by which to produce highly aligned fiber scaffolds efficiently and techniques for assessing neurite outgrowth on different fiber scaffolds, while suggesting that crossing fibers may be detrimental in fostering efficient, directed axonal outgrowth.

We present a micromachined 252-channel ECoG (electrocorticogram)-electrode array, which is made of a thin polyimide foil substrate enclosing sputtered platinum electrode sites and conductor paths. The array subtends an area of approximately 35 mm by 60 mm and is designed to cover large parts of a hemisphere of a macaque monkey's cortex. Eight omnetics connectors are directly soldered to the foil. This leads to a compact assembly size which enables a chronic implantation of the array and allows free movements of the animal between the recording sessions. The electrode sites are 1 mm in diameter and were characterized by electrochemical impedance spectroscopy. At 1 kHz, the electrode impedances vary between 1.5 kΩ and 5 kΩ. The yield of functioning electrodes in three assembled devices is 99.5%. After implantation of a device with 100% working electrodes, standard electrocorticographic signals can be obtained from every electrode. The response to visual stimuli can be measured with electrodes lying on the visual cortex. After an implantation time of 4.5 months, all electrodes are still working and no decline in signal quality could be observed.

Neural stimulation with high spatial and temporal precision is desirable both for studying the real-time dynamics of neural networks and for prospective clinical treatment of neurological diseases. Optical stimulation of genetically targeted neurons expressing the light sensitive channel protein Channelrhodopsin (ChR2) has recently been reported as a means for millisecond temporal control of neuronal spiking activities with cell-type selectivity. This offers the prospect of enabling local delivery of optical stimulation and the simultaneous monitoring of the neural activity by electrophysiological means, both in the vicinity of and distant to the stimulation site. We report here a novel dual-modality hybrid device, which consists of a tapered coaxial optical waveguide ('optrode') integrated into a 100 element intra-cortical multi-electrode recording array. We first demonstrate the dual optical delivery and electrical recording capability of the single optrode in in vitro preparations of mouse retina, photo-stimulating the native retinal photoreceptors while recording light-responsive activities from ganglion cells. The dual-modality array device was then used in ChR2 transfected mouse brain slices. Specifically, epileptiform events were reliably optically triggered by the optrode and their spatiotemporal patterns were simultaneously recorded by the multi-electrode array.

Brain–computer interface (BCI) systems do not work for all users. This article introduces a novel combination of tasks that could inspire BCI systems that are more accurate than conventional BCIs, especially for users who cannot attain accuracy adequate for effective communication. Subjects performed tasks typically used in two BCI approaches, namely event-related desynchronization (ERD) and steady state visual evoked potential (SSVEP), both individually and in a 'hybrid' condition that combines both tasks. Electroencephalographic (EEG) data were recorded across three conditions. Subjects imagined moving the left or right hand (ERD), focused on one of the two oscillating visual stimuli (SSVEP), and then simultaneously performed both tasks. Accuracy and subjective measures were assessed. Offline analyses suggested that half of the subjects did not produce brain patterns that could be accurately discriminated in response to at least one of the two tasks. If these subjects produced comparable EEG patterns when trying to use a BCI, these subjects would not be able to communicate effectively because the BCI would make too many errors. Results also showed that switching to a different task used in BCIs could improve accuracy in some of these users. Switching to a hybrid approach eliminated this problem completely, and subjects generally did not consider the hybrid condition more difficult. Results validate this hybrid approach and suggest that subjects who cannot use a BCI should consider switching to a different BCI approach, especially a hybrid BCI. Subjects proficient with both approaches might combine them to increase information throughput by improving accuracy, reducing selection time, and/or increasing the number of possible commands.

We reveal the presence of refractory and overlap effects in the event-related potentials in visual P300 speller datasets, and we show their negative impact on the performance of the system. This finding has important implications for how to encode the letters that can be selected for communication. However, we show that such effects are dependent on stimulus parameters: an alternative stimulus type based on apparent motion suffers less from the refractory effects and leads to an improved letter prediction performance.

Near-infrared spectroscopy (NIRS) has recently been identified as a safe, portable and relatively low-cost signal acquisition tool for non-invasive brain–computer interface (BCI) development. The ultimate goal of BCI research is for the user to be able to communicate functional intent directly through thoughts. In this paper we propose an NIRS-BCI paradigm based on directly decoding neural correlates of decision making, specifically subjective preference evaluation. Nine subjects were asked to mentally evaluate two possible drinks and decide which they preferred. Frequency domain near-infrared spectroscopy was used to image each subject's prefrontal cortex during the task. Using mean signal amplitudes as features and linear discriminant analysis, we were able to decode which drink was preferred on a single-trial basis with an average accuracy of 80%.

Neuronal network output in the cortex as a function of synapse density during development has not been explicitly determined. Synaptic scaling in cortical brain networks seems to alter excitatory and inhibitory synaptic inputs to produce a representative rate of synaptic output. Here, we cultured rat hippocampal neurons over a three-week period to correlate synapse density with the increase in spontaneous spiking activity. We followed the network development as synapse formation and spike rate in two serum-free media optimized for either (a) neuron survival (Neurobasal/B27) or (b) spike rate (NbActiv4). We found that while synaptophysin synapse density increased linearly with development, spike rates increased exponentially in developing neuronal networks. Synaptic receptor components NR1, GluR1 and GABA-A also increase linearly but with more excitatory receptors than inhibitory. These results suggest that the brain's information processing capability gains more from increasing connectivity of the processing units than increasing processing units, much as Internet information flow increases much faster than the linear number of nodes and connections.