NEUROTECHNIX 2015 Abstracts


Area 1 - Neurocomputing

Full Papers
Paper Nr: 1
Title:

Toward Sentient Neurotechnology - Visual Object Unity May Be Structured by and Constrain Neural Interactions

Authors:

Raymond Pavloski

Abstract: Achieving an understanding of how qualities of experience arise in concert with the operation of neural networks could produce a revolutionary advance in neurotechnology. The work reported here explores a relationship between a visual quality and neural activity that has not previously been investigated: visual object unity may emerge from and constrain neural interactions. Simulations were employed to determine if a topological signature of a unified object develops as a recurrent neural network’s activity is modulated by retinal input. Results show that differences in recurrent excitatory conductance values produced by adjacent active neurons are negligibly small, and can be described by a tolerance relation. Tolerance open balls about the vectors of conductance values produced by active neurons emerge in response to the retinal image of an object and a connected open set consisting of intersecting open balls quickly develops. Such connected open sets are invariant over fluctuations in participating neurons, demonstrate several characteristics of perception, and are hypothesized to be objective signatures of perceived object unity. Dynamical network phenomena, such as hysteresis, lead to empirical predictions that can be tested with human participants. Means of identifying objective signatures in brain activity are considered.

Paper Nr: 3
Title:

Neuronal Activity Visualization using Biologically Accurately Placed Neurons in WebGL

Authors:

Andoni Mujika, Peter Leškovský, Gorka Epelde, Roberto Alvarez and David Oyarzun

Abstract: This paper describes the design and development of a web interface used for an analysis of neural activities of the Caenorhabditis elegans (C. elegans) nematode, within the framework of the Si elegans project. The Si elegans project develops a platform, where the neural system of C. elegans is emulated in hardware and the physical worm together with the external environment is simulated in software. This platform allows for virtual execution of a variety of behavioural experiments of C. elegans. We use the herein described web interface to post-experimentally visualize the neural activity as well as the worm’s behaviour and allow for its deeper analysis. The web-page joins a 3D virtual environment with the 2D GUI in order to realistically visualize the worm and the emulated neural processes, along with additional configuration information. In the virtual environment, the locomotion of the worm is shown, including the motion of neurons. Visualizing the location of the neurons, the user can understand signal transmission among the neurons in a more intuitive way. In the 2D part, additional information about the neurons is displayed. Mainly, a grid of buttons that shows the actual spiking process of the neurons by colour changes and neuron specific voltage graphs following the potential evolution of selected neurons. We believe that this approach suits the exploration of small neuronal circuits, like is the ones of C. elegans.

Area 2 - Neuromodulation and Neural Prosthesis

Full Papers
Paper Nr: 4
Title:

In Vivo Charge Injection Limits Increased after 'Unsafe' Stimulation

Authors:

Suzan Meijs, Søren Sørensen, Kristian Rechendorff and Nico Rijkhoff

Abstract: The effect of unsafe stimulation on charge injection limits (Qinj) and pulsing capacitance (Cpulse) was investigated. Four stimulation protocols were applied: 20 mA – 200 and 400 Hz, 50 mA – 200 and 400 Hz. Increasing Qinj and Cpulse were observed for all stimulation protocols. Corrosion was not observed with any of the stimulation protocols and no tissue damage was observed for the 20 mA – 200 Hz stimulation group. This indicates that the ‘safe potential window’ may not be applicable in vivo, as no damage was done stimulating with 20 mA at 200 Hz, while damage was done using the same current at 400 Hz.

Paper Nr: 5
Title:

Increased Charge Storage Capacity of Titanium Nitride Electrodes by Deposition of Boron-doped Nanocrystalline Diamond Films

Authors:

Suzan Meijs, Matthew McDonald, Søren Sørensen, Kristian Rechendorff, Vaclav Petrak, Milos Nesladek, Nico Rijkhoff and Cristian Pablo Pennisi

Abstract: The aim of this study was to investigate the feasibility of depositing a thin layer of boron-doped nanocrystalline diamond (B-NCD) on titanium nitride (TiN) coated electrodes and the effect this has on charge injection properties. The charge storage capacity increased by applying the B-NCD film, due to the wide potential window typical for B-NCD. The impedance magnitude was higher and the pulsing capacitance lower for B-NCD compared to TiN. Due to the wide potential window, however, a higher amount of charge can be injected without reaching unsafe potentials with the B-NCD coating. The production parameters for TiN and B-NCD are critical, as they influence the pore resistance and thereby the surface area available for pulsing.

Area 3 - Neural Rehabilitation

Full Papers
Paper Nr: 12
Title:

Brain-Computer Interface and Functional Electrical Stimulation for Neurorehabilitation of Hand in Sub-acute Tetraplegic Patients - Functional and Neurological Outcomes

Authors:

Bethel C. A. Osuagwu, Leslie Wallace, Matthew Fraser and Aleksandra Vuckovic

Abstract: The aim of this paper is to compare neurological and functional outcomes between two groups of subacute hospitalised patients with incomplete tetraplegia receiving two experimental therapies. Seven patients received 20 sessions of Brain Computer Interface (BCI) controlled Functional Electrical Stimulation (FES) while five patients received 20 sessions of passive FES. The treatment assessment measures were EEG during movement attempt, Somatosensory evoked potential (SSEP) of the ulnar and median nerve and the range of movement of both wrists. Patients in both groups initially had intense cortical activity during a movement attempt, which was wide-spread, not restricted to the sensory-motor cortex. Following the treatment, cortical activity restored towards the activity in able-bodied people in BCI-FES group only. SSEP also returned in 3 patients in BCI-FES group while in FES group no changes were noticed. The range of movement improved in both groups and results are inconclusive due to the small number of participants. This study confirms the feasibility of prolonged BCI-FES therapy in a hospital setting. The results indicate better neurological recovery in BCI-FES group. Larger and longer studies are required to assess the potential advantage of BCI-FES on functional recovery.

Area 4 - NeuroSensing and Diagnosis

Full Papers
Paper Nr: 13
Title:

Comparison of Data Selection Strategies for Online Support Vector Machine Classification

Authors:

Mario Michael Krell, Nils Wilshusen, Andrei Cristian Ignat and Su Kyoung Kim

Abstract: It is often the case that practical applications of support vector machines (SVMs) require the capability to perform online learning under limited availability of computational resources. Enabling SVMs for online learning can be done through several strategies. One group thereof manipulates the training data and limits its size. We aim to summarize these existing approaches and compare them, firstly, on several synthetic datasets with different shifts and, secondly, on electroencephalographic (EEG) data. During the manipulation, class imbalance can occur across the training data and it might even happen that all samples of one class are removed. In order to deal with this potential issue, we suggest and compare three balancing criteria.

Paper Nr: 15
Title:

raxDAWN: Circumventing Overfitting of the Adaptive xDAWN

Authors:

Mario Michael Krell, Hendrik Wöhrle and Anett Seeland

Abstract: The xDAWN algorithm is a well-established spatial filter which was developed to enhance the signal quality of brain-computer interfaces for the detection of event-related potentials. Recently, an adaptive version has been introduced. Here, we present an improved version that incorporates regularization to reduce the influence of noise and avoid overfitting. We show that regularization improves the performance significantly for up to 4%, when little data is available as it is the case when the brain-computer interface should be used without or with a very short prior calibration session.

Area 5 - Neural Rehabilitation

Full Papers
Paper Nr: 16
Title:

A Wearable Bracelet Device for Promoting Arm Use in Stroke Patients

Authors:

Belén Rubio Ballester, Alica Lathe, Esther Duarte, Armin Duff and Paul F. M. J. Verschure

Abstract: After stroke, many patients experience hemiparesis or weakness on one side of the body. In order to compensate for this lack of motor function, they tend to overuse their non-affected limb. This so called learned non-use may be one of the most relevant contributors to functional loss after post-stroke hospital discharge. We hypothesize that frequent exposure to movement related feedback through a wearable bracelet device may 1) increase the patient’s intrinsic motivation for using the paretic limb, and 2) counteract learned non-use, therefore inducing motor recovery. First, to validate the accelerometers-based measurement of arm use, we recruited 10 right-handed volunteers without neurological impairments. Second, we explored the acceptability and clinical impact of a low-cost wearable system on 4 chronic stroke patients with hemiparesis. Our results suggest that frequent exposure to direct feedback about arm use promotes the integration of the paretic limb in the performance of instrumental activities of daily living (iADLs). In addition, results from questionnaires revealed that the use of wearable devices may influence positively the patient’s intrinsic motivation for using the affected arm. To the best of our knowledge, this is the first study suggesting the benefits of wearable-based feedback as an intervention tool for counteracting learned non-use.

Paper Nr: 17
Title:

Commonalities of Motor Performance Metrics are Revealed by Predictive Oscillatory EEG Components

Authors:

M. Tangermann, J. Reis and A. Meinel

Abstract: The power of oscillatory components of the electroencephalogram (EEG) can be predictive for the single-trial performance score of an upcoming task. State-of-the-art machine learning methods allow to extract such predictive subspace components even from noisy multichannel EEG recordings. In the context of an isometric hand motor rehabilitation task, we analyse EEG data of n=20 normally aged subjects. Predictive oscillatory EEG subspaces were derived with a spatial filtering method (source power comodulation, SPoC), and the transfer of these subspaces between five performance metrics but within data of single subjects was investigated. Findings suggest, that on the grand average of 20 subjects, informative SPoC subspace components were extracted, which could be shared between a set of three metrics describing the duration of subtasks and jerk characteristics of the force trajectories. Transfer to any other of the remaining four metrics was not possible above chance level for a metric describing the reaction time and a metric assessing the length of the force trajectory. Furthermore we show, that these transfer results are in line with the structure of cross-correlations between the performance metrics.

Short Papers
Paper Nr: 6
Title:

A Poll Oriented Classifier for Affective Brain Computer Interfaces

Authors:

Daniela Iacoviello, Naixia Pagnani, Andrea Petracca, Matteo Spezialetti and Giuseppe Placidi

Abstract: Affective Computing and Brain Computer Interface (BCI) are two innovative and rapidly growing fields of research. Affective Computing aims at equipping machines with the human capabilities of observe, understand and express affecting features; BCI aims at discovering novel communication channels and protocols, through the monitoring of the brain activity. Emotion recognition plays a central role in both these research fields. In this work we present an EEG poll based classification algorithm for self-induced emotional states used for BCI. We tested the approach using three emotions: the disgust produced by remembering an unpleasant odor (a stink), the pleasantness induced by the memory of a fragrance and a relaxing state. Preliminary experimental results are also reported.

Area 6 - NeuroSensing and Diagnosis

Short Papers
Paper Nr: 7
Title:

Encoding of Movement in Local Field Potentials from the Wall of Motor Cortical Lesions in Rats

Authors:

Ioana Nica, Marjolijn Deprez, Frederik Ceyssens, Kris van Kuyck, Robert Puers, Bart Nuttin and Jean-Marie Aerts

Abstract: Cortical lesions can severely impact normal motor function and a better understanding of the neural electrical activity at the level of the lesion can help optimize current rehabilitation techniques. Here, we study local field potentials (LFPs) recorded from within the cavity wall of cortical lesions, induced in the forelimb area of the rat motor cortex. We report prominent theta and gamma oscillatory activity, on data collected from three rats. We show that these oscillations are strongly linked to movement intervals, in an open-field experimental setup that required neither learning nor reward. These results should be extended into a further investigation to test the hypothesis that LFPs can help parametrize the animal's state of impairment.

Area 7 - Neurocomputing

Short Papers
Paper Nr: 8
Title:

Detection of Internal and External Events in Spiking Neural Networks

Authors:

Sergey Lobov, Victor Kazantsev and Valeri Makarov

Abstract: Networks of spiking neurons implemented in-silico can closely mimic in-vivo neural networks and brain functions. However, their use for hybrid computations remains rather limited. In this work we report two successful cases of development of spiking neural networks for controlling mobile robots. In the first case a neural network drives a toy robot. We show that thus obtained neuroanimat is capable of synchronizing the network activity with external sensory stimuli. Then, the robot produces basic animal behaviors. In the second example we employ spiking neurons in a human-robot interface. The interface is based on a bracelet with electromyographic sensors and recognizes nine hand gestures. The recognized gestures are sent to the robot as motor commands. Our results show that all users after few trials manage to control the robot remotely. We note that in both cases besides neural networks there are no additional external algorithms employed for the decision-making.

Area 8 - NeuroSensing and Diagnosis

Short Papers
Paper Nr: 10
Title:

Fast Automated Interictal Spike Detection in iEEG/ECoG Recordings - Using Optimized Memory Access

Authors:

Filip Kesner, Jan Cimbalnik, Irena Dolezalova, Milan Brazdil and Lukáš Sekanina

Abstract: MOTIVATION Interictal spikes have been established as an important biomarker in surface EEG and intracranial iEEG recordings for some time (Staley et al., 2011). Spikes are used for clinical practice and research of epilepsy, ADHD and also in other areas (Barkmeier et al.,2012a). Although the gold standard for interictal spike detection has been and still mainly is manual evaluation, it has been shown that higher consistency of results can be achieved by automated detection algorithm (Barkmeier et al., 2012b). Detection algorithms can save enormous amount of work for reviewers and provide a faster data analysis for research or even clinical practice. OBJECTIVES Computational efficiency is not so important when recordings are processed from only a few channels and a real-time detection is not necessary. Example of those would be recordings from rodents (Ovchinnikov et al., 2010). However, when processing intracranial recordings from humans, in as much as 150 channels with 5 kHz sampling rate, which are in average 30 minutes long, computational time requirements gain a great deal of importance. While several terabytes (just our institution) of such recordings are available for processing, a detection algorithm has to be designed to allow fast offline processing of intracranial recordings or even a real-time detection over at least hundreds of channels simultaneously. In order to process large signal data, the memory access is often crucial bottleneck for CPU processing, which puts high requirements on effective cache utilization, to reduce the access to a slow main memory. The goal of this paper is to propose an efficient spike detection algorithm, particularly, the first level detector.

Area 9 - Neural Rehabilitation

Short Papers
Paper Nr: 11
Title:

ADS 1299-based Open Hardware Amplifier from OpenBCI.com: Signal Quality for EEG Registration and SSVEP-based BCI

Authors:

M. Zieleniewska, A. Chabuda, M. Biesaga, R. Kus and P. Durka

Abstract: This paper presents the comparison of EEG signals recorded using an ADS-1299 Open Hardware EEG amplifier from the openbci.com project and a reference commercial top-class amplifier from TMSi.com. The signals were recorded simultaneously from one subject. Behavioural conditions included classical eyes open/eyes closed resting state EEG as well as SSVEP stimulation with several frequencies. We present the spectra of the same time epochs extracted from both signals, recorded from a closely spaced electrodes during the resting state condition. As for the SSVEP, we assess the quality of the signal by a measure of discrimination of stimulation frequencies used in a real SSVEP-based BCI from the openbci.pl system.

Area 10 - Neuromodulation and Neural Prosthesis

Short Papers
Paper Nr: 14
Title:

Transcutaneous Spinal Direct Current Stimulation - Modelling the Electric Field Distribution in the Cervical Spinal Cord

Authors:

S. R. Fernandes, R. Salvador, C. Wenger, M. de Carvalho and P. C. Miranda

Abstract: Exploratory studies in humans demonstrated that transcutaneous spinal direct current stimulation (tsDCS) has neuromodulatory effects on spinal motor circuitry. There is only one computational study published that presents the electric field and current density distributions during tsDCS applied on the thoracic spine region, using realistic human models based on high-resolution MRI. The main objective of the present study was to perform a finite element analysis of the electric field distribution in tsDCS in the cervical spine region, in order to infer the possible neuromodulatory effects on cervical spine circuitry. The electrode configuration considered in the study followed the experimental setup used in literature, with the target electrode placed over the C6-T1 spinous processes and the return electrode placed over the right deltoid muscle. The electric field distribution in the cervical spinal cord presented higher magnitude values in the upper region of the spinal segments C5 to T1, corresponding to the braquial plexus and related to upper limb neurologic function. These values are consistent with results obtained in previous modelling studies in transcranial direct current stimulation (tDCS) considering experimental setups of clinical studies that resulted in modulation of the motor cortex. This may indicate that the electric field magnitude maximum values presented could be sufficient for occurrence of neuromodulatory effects in the cervical spinal circuitry related to upper limb function. Cervical tsDCS can, therefore, be a promising non-invasive clinical tool for neuronal circuitry modulation in the cervical spinal cord. Defining accurate models that predict the physical effects of tsDCS on spinal neurons may be a powerful tool to develop clinical applications focused on specific neurologic patient needs.

Area 11 - Neural Rehabilitation

Short Papers
Paper Nr: 18
Title:

Hysteresis in the Perception of Visual Unity - Confirmation of a Neural Network Model Prediction

Authors:

Ian Bright and Raymond Pavloski

Abstract: In response to a simulated retinal image of an object, the recurrent input to a richly connected artificial neural network organizes into a connected open set (COS) of ionic conductance values, which models the continuity and unity of a visual object. As the density of light dots on a dark background increases and then decreases, a COS appears at a density that is higher than that at which it disappears (hysteresis). This experiment tested the hypothesis that humans will show hysteresis similar to that of the simulation. In addition, the effect of dot lightness on the perception of a unified visual object was also tested.

Area 12 - NeuroSensing and Diagnosis

Short Papers
Paper Nr: 19
Title:

Novel Ultra-long Term EEG Monitoring System - A Possible Enabler of BCI Technologies

Authors:

Jonas Duun-Henriksen and Sirin W. Gangstad

Abstract: Various groups have recently sketched the future within portable EEG equipment. They agree that small, portable and convenient systems for instant and continuous EEG monitoring are essential. We therefore present a novel subcutaneous monitoring system developed for unobtrusive, continuous, ultra-long term EEG applications. Evidence of high signal quality is provided for two patients monitored continuously night and day for a 1 month period.