A Dynamic Selection Method for Reference Electrode in SSVEP-Based BCI

In SSVEP-based Brain-Computer Interface (BCI), it is very important to get an evoked EEG with a high signal to noise ratio (SNR). The SNR of SSVEP is fundamentally related to the characteristics of stimulus, such as its intensity and frequency, and it is also related to both the reference electrode and the active electrode. In the past, with SSVEP-based BCI, often the potential at ‘Cz’, the average potential at all electrodes or the average mastoid potential, were statically selected as the reference. In conjunction, a certain electrode in the occipital area was statically selected as the active electrode for all stimuli. This work proposed a dynamic selection method for the reference electrode, in which all electrodes can be looked upon as active electrodes, while an electrode which can result in the maximum sum relative-power of a specific frequency SSVEP can be confirmed dynamically and considered as the optimum reference electrode for that specific frequency stimulus. Comparing this dynamic selection method with previous methods, in which ‘Cz’, the average potential at all electrodes or the average mastoid potential were selected as the reference electrode, it is demonstrated that the SNR of SSVEP is improved significantly as is the accuracy of SSVEP detection.     

Assessing Movement Factors in Upper Limb Kinematics Decoding from EEG Signals

The past decades have seen the rapid development of upper limb kinematics decoding techniques by performing intracortical recordings of brain signals. However, the use of non-invasive approaches to perform similar decoding procedures is still in its early stages. Recent studies show that there is a correlation between electroencephalographic (EEG) signals and hand-reaching kinematic parameters. From these studies, it could be concluded that the accuracy of upper limb kinematics decoding depends, at least partially, on the characteristics of the performed movement. In this paper, we have studied upper limb movements with different speeds and trajectories in a controlled environment to analyze the influence of movement variability in the decoding performance. To that end, low frequency components of the EEG signals have been decoded with linear models to obtain the position of the volunteer’s hand during performed trajectories grasping the end effector of a planar manipulandum. The results confirm that it is possible to obtain kinematic information from low frequency EEG signals and show that decoding performance is significantly influenced by movement variability and tracking accuracy as continuous and slower movements improve the accuracy of the decoder. This is a key factor that should be taken into account in future experimental designs.     

Brain-controlled interfaces: movement restoration with neural prosthetics

Brain-controlled interfaces are devices that capture brain transmissions involved in a subject's intention to act, with the potential to restore communication and movement to those who are immobilized. Current devices record electrical activity from the scalp, on the surface of the brain, and within the cerebral cortex. These signals are being translated to command signals driving prosthetic limbs and computer displays. Somatosensory feedback is being added to this control as generated behaviors become more complex. New technology to engineer the tissue-electrode interface, electrode design, and extraction algorithms to transform the recorded signal to movement will help translate exciting laboratory demonstrations to patient practice in the near future.     

Playing 20 Questions with the Mind: Collaborative Problem Solving by Humans Using a Brain-to-Brain Interface

We present, to our knowledge, the first demonstration that a non-invasive brain-to-brain interface (BBI) can be used to allow one human to guess what is on the mind of another human through an interactive question-and-answering paradigm similar to the “20 Questions” game. As in previous non-invasive BBI studies in humans, our interface uses electroencephalography (EEG) to detect specific patterns of brain activity from one participant (the “respondent”), and transcranial magnetic stimulation (TMS) to deliver functionally-relevant information to the brain of a second participant (the “inquirer”). Our results extend previous BBI research by (1) using stimulation of the visual cortex to convey visual stimuli that are privately experienced and consciously perceived by the inquirer; (2) exploiting real-time rather than off-line communication of information from one brain to another; and (3) employing an interactive task, in which the inquirer and respondent must exchange information bi-directionally to collaboratively solve the task. The results demonstrate that using the BBI, ten participants (five inquirer-respondent pairs) can successfully identify a “mystery item” using a true/false question-answering protocol similar to the “20 Questions” game, with high levels of accuracy that are significantly greater than a control condition in which participants were connected through a sham BBI.     

Comparative Study of SSVEP- and P300-Based Models for the Telepresence Control of Humanoid Robots

In this paper, we evaluate the control performance of SSVEP (steady-state visual evoked potential)- and P300-based models using Cerebot—a mind-controlled humanoid robot platform. Seven subjects with diverse experience participated in experiments concerning the open-loop and closed-loop control of a humanoid robot via brain signals. The visual stimuli of both the SSVEP- and P300- based models were implemented on a LCD computer monitor with a refresh frequency of 60 Hz. Considering the operation safety, we set the classification accuracy of a model over 90.0% as the most important mandatory for the telepresence control of the humanoid robot. The open-loop experiments demonstrated that the SSVEP model with at most four stimulus targets achieved the average accurate rate about 90%, whereas the P300 model with the six or more stimulus targets under five repetitions per trial was able to achieve the accurate rates over 90.0%. Therefore, the four SSVEP stimuli were used to control four types of robot behavior; while the six P300 stimuli were chosen to control six types of robot behavior. Both of the 4-class SSVEP and 6-class P300 models achieved the average success rates of 90.3% and 91.3%, the average response times of 3.65 s and 6.6 s, and the average information transfer rates (ITR) of 24.7 bits/min 18.8 bits/min, respectively. The closed-loop experiments addressed the telepresence control of the robot; the objective was to cause the robot to walk along a white lane marked in an office environment using live video feedback. Comparative studies reveal that the SSVEP model yielded faster response to the subject’s mental activity with less reliance on channel selection, whereas the P300 model was found to be suitable for more classifiable targets and required less training. To conclude, we discuss the existing SSVEP and P300 models for the control of humanoid robots, including the models proposed in this paper.     

Long-Term Safety of Repeated Blood-Brain Barrier Opening via Focused Ultrasound with Microbubbles in Non-Human Primates Performing a Cognitive Task

Focused Ultrasound (FUS) coupled with intravenous administration of microbubbles (MB) is a non-invasive technique that has been shown to reliably open (increase the permeability of) the blood-brain barrier (BBB) in multiple in vivo models including non-human primates (NHP). This procedure has shown promise for clinical and basic science applications, yet the safety and potential neurological effects of long term application in NHP requires further investigation under parameters shown to be efficacious in that species (500kHz, 200–400 kPa, 4–5μm MB, 2 minute sonication). In this study, we repeatedly opened the BBB in the caudate and putamen regions of the basal ganglia of 4 NHP using FUS with systemically-administered MB over 4–20 months. We assessed the safety of the FUS with MB procedure using MRI to detect edema or hemorrhaging in the brain. Contrast enhanced T1-weighted MRI sequences showed a 98% success rate for openings in the targeted regions. T2-weighted and SWI sequences indicated a lack edema in the majority of the cases. We investigated potential neurological effects of the FUS with MB procedure through quantitative cognitive testing of’ visual, cognitive, motivational, and motor function using a random dot motion task with reward magnitude bias presented on a touchpanel display. Reaction times during the task significantly increased on the day of the FUS with MB procedure. This increase returned to baseline within 4–5 days after the procedure. Visual motion discrimination thresholds were unaffected. Our results indicate FUS with MB can be a safe method for repeated opening of the BBB at the basal ganglia in NHP for up to 20 months without any long-term negative physiological or neurological effects with the parameters used.     

The prion-like domain of Fused in Sarcoma is phosphorylated by multiple kinases affecting liquid- and solid-phase transitions

Fused in Sarcoma (FUS) is a ubiquitously expressed protein that can phase-separate from nucleoplasm and cytoplasm into distinct liquid-droplet structures. It is predominantly nuclear and most of its functions are related to RNA and DNA metabolism. Excessive persistence of FUS within cytoplasmic phase-separated assemblies is implicated in the diseases amyotrophic lateral sclerosis and frontotemporal dementia. Phosphorylation of FUS’s prion-like domain (PrLD) by nuclear phosphatidylinositol 3-kinase-related kinase (PIKK)-family kinases following DNA damage was previously shown to alter FUS’s liquid-phase and solid-phase transitions in cell models and in vitro. However, proteomic data suggest that FUS’s PrLD is phosphorylated at numerous additional sites, and it is unknown if other non-PIKK and nonnuclear kinases might be influencing FUS’s phase transitions. Here we evaluate disease mutations and stress conditions that increase FUS accumulation into cytoplasmic phase-separated structures. We observed that cytoplasmic liquid-phase structures contain FUS phosphorylated at novel sites, which occurred independent of PIKK-family kinases. We engineered phosphomimetic substitutions within FUS’s PrLD and observed that mimicking a few phosphorylation sites strongly inhibited FUS solid-phase aggregation, while minimally altering liquid-phase condensation. These effects occurred independent of the exact location of the phosphomimetic substitutions, suggesting that modulation of PrLD phosphorylation may offer therapeutic strategies that are specific for solid-phase aggregation observed in disease.     

Submicron-Bubble-Enhanced Focused Ultrasound for Blood–Brain Barrier Disruption and Improved CNS Drug Delivery

The use of focused ultrasound (FUS) with microbubbles has been proven to induce transient blood–brain barrier opening (BBB-opening). However, FUS-induced inertial cavitation of microbubbles can also result in erythrocyte extravasations. Here we investigated whether induction of submicron bubbles to oscillate at their resonant frequency would reduce inertial cavitation during BBB-opening and thereby eliminate erythrocyte extravasations in a rat brain model. FUS was delivered with acoustic pressures of 0.1–4.5 MPa using either in-house manufactured submicron bubbles or standard SonoVue microbubbles. Wideband and subharmonic emissions from bubbles were used to quantify inertial and stable cavitation, respectively. Erythrocyte extravasations were evaluated by in vivo post-treatment magnetic resonance susceptibility-weighted imaging, and finally by histological confirmation. We found that excitation of submicron bubbles with resonant frequency-matched FUS (10 MHz) can greatly limit inertial cavitation while enhancing stable cavitation. The BBB-opening was mainly caused by stable cavitation, whereas the erythrocyte extravasation was closely correlated with inertial cavitation. Our technique allows extensive reduction of inertial cavitation to induce safe BBB-opening. Furthermore, the safety issue of BBB-opening was not compromised by prolonging FUS exposure time, and the local drug concentrations in the brain tissues were significantly improved to 60 times (BCNU; 18.6 µg versus 0.3 µg) by using chemotherapeutic agent-loaded submicron bubbles with FUS. This study provides important information towards the goal of successfully translating FUS brain drug delivery into clinical use.     

LASSO based stimulus frequency recognition model for SSVEP BCIs

Steady-state visual evoked potential (SSVEP) has been increasingly used for the study of brain–computer interface (BCI). How to recognize SSVEP with shorter time and lower error rate is one of the key points to develop a more efficient SSVEP-based BCI. To achieve this goal, we make use of the sparsity constraint of the least absolute shrinkage and selection operator (LASSO) for the extraction of more discriminative features of SSVEP, and then we propose a LASSO model using the linear regression between electroencephalogram (EEG) recordings and the standard square-wave signals of different frequencies to recognize SSVEP without the training stage. In this study, we verified the proposed LASSO model offline with the EEG data of nine healthy subjects in contrast to canonical correlation analysis (CCA). In the experiment, when a shorter time window was used, we found that the LASSO model yielded better performance in extracting robust and detectable features of SSVEP, and the information transfer rate obtained by the LASSO model was significantly higher than that of the CCA. Our proposed method can assist to reduce the recording time without sacrificing the classification accuracy and is promising for a high-speed SSVEP-based BCI.     

Brain-Computer Interface Controlled Cyborg: Establishing a Functional Information Transfer Pathway from Human Brain to Cockroach Brain

An all-chain-wireless brain-to-brain system (BTBS), which enabled motion control of a cyborg cockroach via human brain, was developed in this work. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) was used in this system for recognizing human motion intention and an optimization algorithm was proposed in SSVEP to improve online performance of the BCI. The cyborg cockroach was developed by surgically integrating a portable microstimulator that could generate invasive electrical nerve stimulation. Through Bluetooth communication, specific electrical pulse trains could be triggered from the microstimulator by BCI commands and were sent through the antenna nerve to stimulate the brain of cockroach. Serial experiments were designed and conducted to test overall performance of the BTBS with six human subjects and three cockroaches. The experimental results showed that the online classification accuracy of three-mode BCI increased from 72.86% to 78.56% by 5.70% using the optimization algorithm and the mean response accuracy of the cyborgs using this system reached 89.5%. Moreover, the results also showed that the cyborg could be navigated by the human brain to complete walking along an S-shape track with the success rate of about 20%, suggesting the proposed BTBS established a feasible functional information transfer pathway from the human brain to the cockroach brain.     

How Thoughts Give Rise to Action - Conscious Motor Intention Increases the Excitability of Target-Specific Motor Circuits

The present study shows evidence for conscious motor intention in motor preparation prior to movement execution. We demonstrate that conscious motor intention of directed movement, combined with minimally supra-threshold transcranial magnetic stimulation (TMS) of the motor cortex, determines the direction and the force of resulting movements, whilst a lack of intention results in weak and omni-directed muscle activation. We investigated changes of consciously intended goal directed movements by analyzing amplitudes of motor-evoked potentials of the forearm muscle, flexor carpi radialis (FCR), and extensor carpi radialis (ECR), induced by transcranial magnetic stimulation over the right motor cortex and their motor outcome. Right-handed subjects were asked to develop a strong intention to move their left wrist (flexion or extension), without any overt motor output at the wrist, prior to brain stimulation. Our analyses of hand acceleration and electromyography showed that during the strong motor intention of wrist flexion movement, it evoked motor potential responses that were significantly larger in the FCR muscle than in the ECR, whilst the opposite was true for an extension movement. The acceleration data on flexion/extension corresponded to this finding. Under no-intention conditions again, which served as a reference for motor evoked potentials, brain stimulation resulted in undirected and minimally simultaneous extension/flexion innervation and virtually no movement. These results indicate that conscious intentions govern motor function, which in turn shows that a neuronal activation representing an “intention network” in the human brain pre-exists, and that it functionally represents target specific motor circuits. Until today, it was unclear whether conscious motor intention exists prior to movement, or whether the brain constructs such an intention after movement initiation. Our study gives evidence that motor intentions become aware before any motor execution.     

A Direct Brain-to-Brain Interface in Humans

We describe the first direct brain-to-brain interface in humans and present results from experiments involving six different subjects. Our non-invasive interface, demonstrated originally in August 2013, combines electroencephalography (EEG) for recording brain signals with transcranial magnetic stimulation (TMS) for delivering information to the brain. We illustrate our method using a visuomotor task in which two humans must cooperate through direct brain-to-brain communication to achieve a desired goal in a computer game. The brain-to-brain interface detects motor imagery in EEG signals recorded from one subject (the “sender”) and transmits this information over the internet to the motor cortex region of a second subject (the “receiver”). This allows the sender to cause a desired motor response in the receiver (a press on a touchpad) via TMS. We quantify the performance of the brain-to-brain interface in terms of the amount of information transmitted as well as the accuracies attained in (1) decoding the sender’s signals, (2) generating a motor response from the receiver upon stimulation, and (3) achieving the overall goal in the cooperative visuomotor task. Our results provide evidence for a rudimentary form of direct information transmission from one human brain to another using non-invasive means.     

On the Quantification of SSVEP Frequency Responses in Human EEG in Realistic BCI Conditions

This article concerns one of the most important problems of brain-computer interfaces (BCI) based on Steady State Visual Evoked Potentials (SSVEP), that is the selection of the a-priori most suitable frequencies for stimulation. Previous works related to this problem were done either with measuring systems that have little in common with actual BCI systems (e.g., single flashing LED) or were presented on a small number of subjects, or the tested frequency range did not cover a broad spectrum. Their results indicate a strong SSVEP response around 10 Hz, in the range 13–25 Hz, and at high frequencies in the band of 40–60 Hz. In the case of BCI interfaces, stimulation with frequencies from various ranges are used. The frequencies are often adapted for each user separately. The selection of these frequencies, however, was not yet justified in quantitative group-level study with proper statistical account for inter-subject variability. The aim of this study is to determine the SSVEP response curve, that is, the magnitude of the evoked signal as a function of frequency. The SSVEP response was induced in conditions as close as possible to the actual BCI system, using a wide range of frequencies (5–30 Hz, in step of 1 Hz). The data were obtained for 10 subjects. SSVEP curves for individual subjects and the population curve was determined. Statistical analysis were conducted both on the level of individual subjects and for the group. The main result of the study is the identification of the optimal range of frequencies, which is 12–18 Hz, for the registration of SSVEP phenomena. The applied criterion of optimality was: to find the largest contiguous range of frequencies yielding the strong and constant-level SSVEP response.     

The graph theoretical analysis of the SSVEP harmonic response networks

Steady-state visually evoked potentials (SSVEP) have been widely used in the neural engineering and cognitive neuroscience researches. Previous studies have indicated that the SSVEP fundamental frequency responses are correlated with the topological properties of the functional networks entrained by the periodic stimuli. Given the different spatial and functional roles of the fundamental frequency and harmonic responses, in this study we further investigated the relation between the harmonic responses and the corresponding functional networks, using the graph theoretical analysis. We found that the second harmonic responses were positively correlated to the mean functional connectivity, clustering coefficient, and global and local efficiencies, while negatively correlated with the characteristic path lengths of the corresponding networks. In addition, similar pattern occurred with the lowest stimulus frequency (6.25 Hz) at the third harmonic responses. These findings demonstrate that more efficient brain networks are related to larger SSVEP responses. Furthermore, we showed that the main connection pattern of the SSVEP harmonic response networks originates from the interactions between the frontal and parietal–occipital regions. Overall, this study may bring new insights into the understanding of the brain mechanisms underlying SSVEP.     

Farmers’ Intentions to Implement Foot and Mouth Disease Control Measures in Ethiopia

The objectives of this study were to explore farmers’ intentions to implement foot and mouth disease (FMD) control in Ethiopia, and to identify perceptions about the disease and its control measures that influence these intentions using the Health Belief Model (HBM) framework. Data were collected using questionnaires from 293 farmers in three different production systems. The influence of perceptions on the intentions to implement control measures were analyzed using binary logistic regression. The effect of socio-demographic and husbandry variables on perceptions that were found to significantly influence the intentions were analyzed using ordinal logistic regression. Almost all farmers (99%) intended to implement FMD vaccination free of charge. The majority of farmers in the pastoral (94%) and market oriented (92%) systems also had the intention to implement vaccination with charge but only 42% of the crop-livestock mixed farmers had the intention to do so. Only 2% of pastoral and 18% of crop-livestock mixed farmers had the intention to implement herd isolation and animal movement restriction continuously. These proportions increased to 11% for pastoral and 50% for crop-livestock mixed farmers when the measure is applied only during an outbreak. The majority of farmers in the market oriented system (>80%) had the intention to implement herd isolation and animal movement restriction measure, both continuously and during an outbreak. Among the HBM perception constructs, perceived barrier was found to be the only significant predictor of the intention to implement vaccination. Perceived susceptibility, perceived benefit and perceived barrier were the significant predictors of the intention for herd isolation and animal movement restriction measure. In turn, the predicting perceived barrier on vaccination control varied significantly with the production system and the age of farmers. The significant HBM perception predictors on herd isolation and animal movement restriction control were significantly influenced only by the type of production system. The results of this study indicate that farmers’ intentions to apply FMD control measures are variable among production systems, an insight which is relevant in the development of future control programs. Promotion programs aimed at increasing farmers’ motivation to participate in FMD control by charged vaccination or animal movement restriction should give attention to the perceived barriers influencing the intentions to apply these measures.     

Simultaneous Detection of P300 and Steady-State Visually Evoked Potentials for Hybrid Brain-Computer Interface

Objective

We study the feasibility of a hybrid Brain-Computer Interface (BCI) combining simultaneous visual oddball and Steady-State Visually Evoked Potential (SSVEP) paradigms, where both types of stimuli are superimposed on a computer screen. Potentially, such a combination could result in a system being able to operate faster than a purely P300-based BCI and encode more targets than a purely SSVEP-based BCI.

Approach

We analyse the interactions between the brain responses of the two paradigms, and assess the possibility to detect simultaneously the brain activity evoked by both paradigms, in a series of 3 experiments where EEG data are analysed offline.

Main Results

Despite differences in the shape of the P300 response between pure oddball and hybrid condition, we observe that the classification accuracy of this P300 response is not affected by the SSVEP stimulation. We do not observe either any effect of the oddball stimulation on the power of the SSVEP response in the frequency of stimulation. Finally results from the last experiment show the possibility of detecting both types of brain responses simultaneously and suggest not only the feasibility of such hybrid BCI but also a gain over pure oddball- and pure SSVEP-based BCIs in terms of communication rate.     

In vivo imaging of endogenous neural stem cells in the adult brain

The discovery of endogenous neural stem cells (eNSCs) in the adult mammalian brain with their ability to self-renew and differentiate into functional neurons, astrocytes and oligodendrocytes has raised the hope for novel therapies of neurological diseases. Experimentally, those eNSCs can be mobilized in vivo, enhancing regeneration and accelerating functional recovery after, e.g., focal cerebral ischemia, thus constituting a most promising approach in stem cell research. In order to translate those current experimental approaches into a clinical setting in the future, non-invasive imaging methods are required to monitor eNSC activation in a longitudinal and intra-individual manner. As yet, imaging protocols to assess eNSC mobilization non-invasively in the live brain remain scarce, but considerable progress has been made in this field in recent years. This review summarizes and discusses the current imaging modalities suitable to monitor eNSCs in individual experimental animals over time, including optical imaging, magnetic resonance tomography and-spectroscopy, as well as positron emission tomography (PET). Special emphasis is put on the potential of each imaging method for a possible clinical translation, and on the specificity of the signal obtained. PET-imaging with the radiotracer 3’-deoxy-3’-[¹⁸F]fluoro-L-thymidine in particular constitutes a modality with excellent potential for clinical translation but low specificity; however, concomitant imaging of neuroinflammation is feasible and increases its specificity. The non-invasive imaging strategies presented here allow for the exploitation of novel treatment strategies based upon the regenerative potential of eNSCs, and will help to facilitate a translation into the clinical setting.     

Breaking the trade-off: rainforest bats maximize bandwidth and repetition rate of echolocation calls as they approach prey

Both mammals and birds experience a performance trade-off between producing vocalizations with high bandwidths and at high repetition rate. Echolocating bats drastically increase repetition rate from 2–20 calls s⁻¹ up to about 170 calls s⁻¹ prior to intercepting airborne prey in order to accurately track prey movement. In turn, bandwidth drops to about 10–30 kHz for the calls of this ‘final buzz’. We have now discovered that Southeast Asian rainforest bats (in the vespertilionid subfamilies Kerivoulinae and Murininae) are able to maintain high call bandwidths at very high repetition rates throughout approach to prey. Five species of Kerivoula and Phoniscus produced call bandwidths of between 78 and 170 kHz at repetition rates of 140–200 calls s⁻¹ and two of Murina at 80 calls s⁻¹. The ‘typical’ and distinct drop in call frequency was present in none of the seven species. This stands in striking contrast to our present view of echolocation during approach to prey in insectivorous bats, which was established largely based on European and American members of the same bat family, the Vespertilionidae. Buzz calls of Kerivoula pellucida had mean bandwidths of 170 kHz and attained maximum starting frequencies of 250 kHz which makes them the most broadband and most highly pitched tonal animal vocalization known to date. We suggest that the extreme vocal performance of the Kerivoulinae and Murininae evolved as an adaptation to echolocating and tracking arthropods in the dense rainforest understorey.     

Association of GRM7 Variants with Different Phenotype Patterns of Age-Related Hearing Impairment in an Elderly Male Han Chinese Population

Several single nucleotide polymorphisms (SNPs) of the Glutamate metabotrophic receptor 7 gene (GRM7) have recently been identified by the genome-wide association study (GWAS) as potentially playing a role in susceptibility to age-related hearing impairment (ARHI), however this has not been validated in the Han Chinese population. The aim of this study was to determine if these SNPs are also associated with ARHI in an elderly male Han Chinese population. In this case-control candidate genes association study, a total of 982 men with ARHI and 324 normal-hearing controls subjects were studied. Using K-means cluster analysis, four audiogram shape subtypes of ARHI were identified in the case group: ‘‘flat shape (FL)’’, ‘‘sloping shape (SL)’’, ‘‘2-4 kHz abrupt loss (AL) shape’’ and ‘‘8 kHz dip (8D) shape’’. Results suggested that the SNP rs11928865 (A>T) of GRM7 was significantly associated with ARHI after adjusting for non-genetic factors (p= 0.000472, OR= 1.599, 95%CI= 1.229~2.081). Furthermore, frequency of TT genotype (rs11928865) were significant higher in the SL subgroup and AL subgroup with compared to controls group (p= 9.41E-05, OR= 1.945, 95%CI= 1.393~2.715; p= 0.000109, OR= 1.915, 95%CI= 1.378~2.661 adjusted, respectively) after Bonferroni correction. However, there wasn’t significant difference in the frequency of the TT genotype between cases in the FL subgroup or the 8D subgroup with when compared with controls. Results of the current study suggest that, in an elderly male Han Chinese population, GRM7 SNP rs11928865 (TT) occurs more frequently in ARHI patients with SL and AL phenotype patterns.     

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

We have developed an open software platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution and testing on multiple Graphics Processing Units (GPUs). Neurokernel provides a programming model that capitalizes upon the structural organization of the fly brain into a fixed number of functional modules to distinguish between these modules’ local information processing capabilities and the connectivity patterns that link them. By defining mandatory communication interfaces that specify how data is transmitted between models of each of these modules regardless of their internal design, Neurokernel explicitly enables multiple researchers to collaboratively model the fruit fly’s entire brain by integration of their independently developed models of its constituent processing units. We demonstrate the power of Neurokernel’s model integration by combining independently developed models of the retina and lamina neuropils in the fly’s visual system and by demonstrating their neuroinformation processing capability. We also illustrate Neurokernel’s ability to take advantage of direct GPU-to-GPU data transfers with benchmarks that demonstrate scaling of Neurokernel’s communication performance both over the number of interface ports exposed by an emulation’s constituent modules and the total number of modules comprised by an emulation.