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Finding brain oscillations with power dependencies in neuroimaging data.
Neuroimage. 2014 Apr 7;
Authors: Dähne S, Nikulin VV, Ramírez D, Schreier PJ, Müller KR, Haufe S
Phase synchronization among neuronal oscillations within the same frequency band has been hypothesized to be a major mechanism for communication between different brain areas. On the other hand, cross-frequency communications are more flexible allowing interactions between oscillations with different frequencies. Among such cross-frequency interactions amplitude-to-amplitude interactions are of a special interest as they show how the strength of spatial synchronization in different neuronal populations relates to each other during a given task. While, previously, amplitude-to-amplitude correlations were studied primarily on the sensor level, we present a source separation approach using spatial filters which maximize the correlation between the envelopes of brain oscillations recorded with electro-/magnetencephalography (EEG/MEG) or intracranial multichannel recordings. Our approach, which is called canonical source power correlation analysis (cSPoC), is thereby capable of extracting genuine brain oscillations solely based on their assumed coupling behavior even when the signal-to-noise ratio of the signals is low. In addition to using cSPoC for the analysis of cross-frequency interactions in the same subject, we show that it can also be utilized for studying amplitude dynamics of neuronal oscillations across subjects. We assess the performance of cSPoC in simulations as well as in three distinctively different analysis scenarios of real EEG data, each involving several subjects. In the simulations, cSPoC outperforms unsupervised state-of-art approaches. In the analysis of real EEG recordings, we demonstrate excellent unsupervised discovery of meaningful power-to-power couplings, within as well as across subjects and frequency bands.
PMID: 24721331 [PubMed - as supplied by publisher]
Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies.
J Res Med Sci. 2014 Jan;19(1):47-56
Authors: Marateb HR, Mansourian M, Adibi P, Farina D
BACKGROUND: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal-variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD).
ORDINAL-TO-INTERVAL SCALE CONVERSION EXAMPLE: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests.
RESULTS: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable.
CONCLUSION: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables.
PMID: 24672565 [PubMed - as supplied by publisher]
Limitations of the spike-triggered averaging for estimating motor unit twitch force: a theoretical analysis.
PLoS One. 2014;9(3):e92390
Authors: Negro F, Yavuz U?, Farina D
Contractile properties of human motor units provide information on the force capacity and fatigability of muscles. The spike-triggered averaging technique (STA) is a conventional method used to estimate the twitch waveform of single motor units in vivo by averaging the joint force signal. Several limitations of this technique have been previously discussed in an empirical way, using simulated and experimental data. In this study, we provide a theoretical analysis of this technique in the frequency domain and describe its intrinsic limitations. By analyzing the analytical expression of STA, first we show that a certain degree of correlation between the motor unit activities prevents an accurate estimation of the twitch force, even from relatively long recordings. Second, we show that the quality of the twitch estimates by STA is highly related to the relative variability of the inter-spike intervals of motor unit action potentials. Interestingly, if this variability is extremely high, correct estimates could be obtained even for high discharge rates. However, for physiological inter-spike interval variability and discharge rate, the technique performs with relatively low estimation accuracy and high estimation variance. Finally, we show that the selection of the triggers that are most distant from the previous and next, which is often suggested, is not an effective way for improving STA estimates and in some cases can even be detrimental. These results show the intrinsic limitations of the STA technique and provide a theoretical framework for the design of new methods for the measurement of motor unit force twitch.
PMID: 24667744 [PubMed - in process]
Learned EEG-based brain self-regulation of motor-related oscillations during application of transcranial electric brain stimulation: feasibility and limitations.
Front Behav Neurosci. 2014;8:93
Authors: Soekadar SR, Witkowski M, Cossio EG, Birbaumer N, Cohen LG
Objective: Transcranial direct current stimulation (tDCS) improves motor learning and can affect emotional processing and attention. However, it is unclear whether learned electroencephalography (EEG)-based brain-machine interface (BMI) control during tDCS is feasible, how application of transcranial electric currents during BMI control would interfere with feature-extraction of physiological brain signals and how it affects brain control performance. Here we tested this combination and evaluated stimulation-dependent artifacts across different EEG frequencies and stability of motor imagery-based BMI control. Approach: Ten healthy volunteers were invited to two BMI-sessions, each comprising two 60-trial blocks. During the trials, learned desynchronization of mu-rhythms (8-15 Hz) associated with motor imagery (MI) recorded over C4 was translated into online cursor movements on a computer screen. During block 2, either sham (session A) or anodal tDCS (session B) was applied at 1 mA with the stimulation electrode placed 1 cm anterior of C4. Main results: tDCS was associated with a significant signal power increase in the lower frequencies most evident in the signal spectrum of the EEG channel closest to the stimulation electrode. Stimulation-dependent signal power increase exhibited a decay of 12 dB per decade, leaving frequencies above 9 Hz unaffected. Analysis of BMI control performance did not indicate a difference between blocks and tDCS conditions. Conclusion: Application of tDCS during learned EEG-based self-regulation of brain oscillations above 9 Hz is feasible and safe, and might improve applicability of BMI systems.
PMID: 24672456 [PubMed]
Dynamical models of cortical circuits.
Curr Opin Neurobiol. 2014 Mar 20;25C:228-236
Authors: Wolf F, Engelken R, Puelma-Touzel M, Weidinger JD, Neef A
Cortical neurons operate within recurrent neuronal circuits. Dissecting their operation is key to understanding information processing in the cortex and requires transparent and adequate dynamical models of circuit function. Convergent evidence from experimental and theoretical studies indicates that strong feedback inhibition shapes the operating regime of cortical circuits. For circuits operating in inhibition-dominated regimes, mathematical and computational studies over the past several years achieved substantial advances in understanding response modulation and heterogeneity, emergent stimulus selectivity, inter-neuron correlations, and microstate dynamics. The latter indicate a surprisingly strong dependence of the collective circuit dynamics on the features of single neuron action potential generation. New approaches are needed to definitely characterize the cortical operating regime.
PMID: 24658059 [PubMed - as supplied by publisher]
Moral judgment modulation by disgust is bi-directionally moderated by individual sensitivity.
Front Psychol. 2014;5:194
Authors: Ong HH, Mullette-Gillman OA, Kwok K, Lim J
Modern theories of moral judgment predict that both conscious reasoning and unconscious emotional influences affect the way people decide about right and wrong. In a series of experiments, we tested the effect of subliminal and conscious priming of disgust facial expressions on moral dilemmas. "Trolley-car"-type scenarios were used, with subjects rating how acceptable they found the utilitarian course of action to be. On average, subliminal priming of disgust facial expressions resulted in higher rates of utilitarian judgments compared to neutral facial expressions. Further, in replication, we found that individual change in moral acceptability ratings due to disgust priming was modulated by individual sensitivity to disgust, revealing a bi-directional function. Our second replication extended this result to show that the function held for both subliminally and consciously presented stimuli. Combined across these experiments, we show a reliable bi-directional function, with presentation of disgust expression primes to individuals with higher disgust sensitivity resulting in more utilitarian judgments (i.e., number-based) and presentations to individuals with lower sensitivity resulting in more deontological judgments (i.e., rules-based). Our results may reconcile previous conflicting reports of disgust modulation of moral judgment by modeling how individual sensitivity to disgust determines the direction and degree of this effect.
PMID: 24639665 [PubMed]
Task-related changes in sensorimotor integration influence the common synaptic input to motor neurones.
Acta Physiol (Oxf). 2014 Feb 7;
Authors: Laine CM, Yavuz SU, Farina D
AIM: The purpose of this investigation was to understand how visual information, when used to guide muscle activity, influences the frequency content of the neural drive to muscles and the gain of afferent feedback.
METHODS: Subjects maintained static, isometric contractions of the tibialis anterior muscle by matching a visual display of their ankle dorsiflexion force to a target set at 10% of their maximum voluntary contraction level. Two visual feedback conditions were studied. The first was a high-sensitivity feedback, in which small changes in force were of large on-screen visual magnitude. The second was a low-sensitivity feedback, in which the on-screen scaling of feedback was reduced by a factor of 10, making small force fluctuations difficult to perceive. Force tremor and Hoffmann reflex (H-reflex) amplitudes were compared between the two conditions, as well as coherence among single motor unit spike trains derived from high-density EMG recordings.
RESULTS: The high-sensitivity feedback condition was associated with lower error, larger force tremor (4-12 Hz) and larger H-reflex amplitudes relative to the low-sensitivity feedback condition. In addition, the use of high-sensitivity feedback was associated with lower 1-5 Hz coherence among pairs of motor units, but larger coherence at high frequencies (6-12, approx. 20, >30 Hz).
CONCLUSION: Alteration of visual feedback influences nearly the entire frequency spectrum of common input to motor neurones, as well the gain of afferent feedback. We speculate that task-related modulation of afferent feedback could be the origin of many of the observed changes in the neural drive to muscles.
PMID: 24620727 [PubMed - as supplied by publisher]
Decoding auditory attention to instruments in polyphonic music using single-trial EEG classification.
J Neural Eng. 2014 Mar 10;11(2):026009
Authors: Treder MS, Purwins H, Miklody D, Sturm I, Blankertz B
Objective. Polyphonic music (music consisting of several instruments playing in parallel) is an intuitive way of embedding multiple information streams. The different instruments in a musical piece form concurrent information streams that seamlessly integrate into a coherent and hedonistically appealing entity. Here, we explore polyphonic music as a novel stimulation approach for use in a brain-computer interface. Approach. In a multi-streamed oddball experiment, we had participants shift selective attention to one out of three different instruments in music audio clips. Each instrument formed an oddball stream with its own specific standard stimuli (a repetitive musical pattern) and oddballs (deviating musical pattern). Main results. Contrasting attended versus unattended instruments, ERP analysis shows subject- and instrument-specific responses including P300 and early auditory components. The attended instrument can be classified offline with a mean accuracy of 91% across 11 participants. Significance. This is a proof of concept that attention paid to a particular instrument in polyphonic music can be inferred from ongoing EEG, a finding that is potentially relevant for both brain-computer interface and music research.
PMID: 24608228 [PubMed - as supplied by publisher]
Slipping during side-step cutting: Anticipatory effects and familiarization.
Hum Mov Sci. 2014 Feb 21;
Authors: Oliveira AS, Silva PB, Lund ME, Farina D, Kersting UG
The aim of the present study was to verify whether the expectation of perturbations while performing side-step cutting manoeuvres influences lower limb EMG activity, heel kinematics and ground reaction forces. Eighteen healthy men performed two sets of 90° side-step cutting manoeuvres. In the first set, 10 unperturbed trials (Base) were performed while stepping over a moveable force platform. In the second set, subjects were informed about the random possibility of perturbations to balance throughout 32 trials, of which eight were perturbed (Pert, 10cm translation triggered at initial contact), and the others were "catch" trials (Catch). Center of mass velocity (CoMVEL), heel acceleration (HAC), ground reaction forces (GRF) and surface electromyography (EMG) from lower limb and trunk muscles were recorded for each trial. Surface EMG was analyzed prior to initial contact (PRE), during load acceptance (LA) and propulsion (PRP) periods of the stance phase. In addition, hamstrings-quadriceps co-contraction ratios (CCR) were calculated for these time-windows. The results showed no changes in CoMVEL, HAC, peak GRF and surface EMG PRE among conditions. However, during LA, there were increases in tibialis anterior EMG (30-50%) concomitant to reduced EMG for quadriceps muscles, gluteus and rectus abdominis for Catch and Pert conditions (15-40%). In addition, quadriceps EMG was still reduced during PRP (p<.05). Consequently, CCR was greater for Catch and Pert in comparison to Base (p<.05). These results suggest that there is modulation of muscle activity towards anticipating potential instability in the lower limb joints and assure safety to complete the task.
PMID: 24565168 [PubMed - as supplied by publisher]
Inducible and titratable silencing of Caenorhabditis elegans neurons in vivo with histamine-gated chloride channels.
Proc Natl Acad Sci U S A. 2014 Feb 18;111(7):2770-5
Authors: Pokala N, Liu Q, Gordus A, Bargmann CI
Recent progress in neuroscience has been facilitated by tools for neuronal activation and inactivation that are orthogonal to endogenous signaling systems. We describe here a chemical-genetic approach for inducible silencing of Caenorhabditis elegans neurons in intact animals, using the histamine-gated chloride channel HisCl1 from Drosophila and exogenous histamine. Administering histamine to freely moving C. elegans that express HisCl1 transgenes in neurons leads to rapid and potent inhibition of neural activity within minutes, as assessed by behavior, functional calcium imaging, and electrophysiology of neurons expressing HisCl1. C. elegans does not use histamine as an endogenous neurotransmitter, and exogenous histamine has little apparent effect on wild-type C. elegans behavior. HisCl1-histamine silencing of sensory neurons, interneurons, and motor neurons leads to behavioral effects matching their known functions. In addition, the HisCl1-histamine system can be used to titrate the level of neural activity, revealing quantitative relationships between neural activity and behavioral output. We use these methods to dissect escape circuits, define interneurons that regulate locomotion speed (AVA, AIB) and escape-related omega turns (AIB), and demonstrate graded control of reversal length by AVA interneurons and DA/VA motor neurons. The histamine-HisCl1 system is effective, robust, compatible with standard behavioral assays, and easily combined with optogenetic tools, properties that should make it a useful addition to C. elegans neurotechnology.
PMID: 24550306 [PubMed - in process]
Exploiting the self-similarity in ERP images by nonlocal means for single-trial denoising.
IEEE Trans Neural Syst Rehabil Eng. 2013 Jul;21(4):576-83
Authors: Strauss DJ, Teuber T, Steidl G, Corona-Strauss FI
Event related potentials (ERPs) represent a noninvasive and widely available means to analyze neural correlates of sensory and cognitive processing. Recent developments in neural and cognitive engineering proposed completely new application fields of this well-established measurement technique when using an advanced single-trial processing. We have recently shown that 2-D diffusion filtering methods from image processing can be used for the denoising of ERP single-trials in matrix representations, also called ERP images. In contrast to conventional 1-D transient ERP denoising techniques, the 2-D restoration of ERP images allows for an integration of regularities over multiple stimulations into the denoising process. Advanced anisotropic image restoration methods may require directional information for the ERP denoising process. This is especially true if there is a lack of a priori knowledge about possible traces in ERP images. However due to the use of event related experimental paradigms, ERP images are characterized by a high degree of self-similarity over the individual trials. In this paper, we propose the simple and easy to apply nonlocal means method for ERP image denoising in order to exploit this self-similarity rather than focusing on the edge-based extraction of directional information. Using measured and simulated ERP data, we compare our method to conventional approaches in ERP denoising. It is concluded that the self-similarity in ERP images can be exploited for single-trial ERP denoising by the proposed approach. This method might be promising for a variety of evoked and event-related potential applications, including nonstationary paradigms such as changing exogeneous stimulus characteristics or endogenous states during the experiment. As presented, the proposed approach is for the a posteriori denoising of single-trial sequences.
PMID: 23060344 [PubMed - indexed for MEDLINE]
Time to address the problems at the neural interface.
J Neural Eng. 2014 Feb 6;11(2):020201
Authors: Durand DM, Ghovanloo M, Krames E
Neural engineers have made significant, if not remarkable, progress in interfacing with the nervous system in the last ten years. In particular, neuromodulation of the brain has generated significant therapeutic benefits [1-5]. EEG electrodes can be used to communicate with patients with locked-in syndrome . In the central nervous system (CNS), electrode arrays placed directly over or within the cortex can record neural signals related to the intent of the subject or patient [7, 8]. A similar technology has allowed paralyzed patients to control an otherwise normal skeletal system with brain signals [9, 10]. This technology has significant potential to restore function in these and other patients with neural disorders such as stroke . Although there are several multichannel arrays described in the literature, the workhorse for these cortical interfaces has been the Utah array . This 100-channel electrode array has been used in most studies on animals and humans since the 1990s and is commercially available. This array and other similar microelectrode arrays can record neural signals with high quality (high signal-to-noise ratio), but these signals fade and disappear after a few months and therefore the current technology is not reliable for extended periods of time. Therefore, despite these major advances in communicating with the brain, clinical translation cannot be implemented. The reasons for this failure are not known but clearly involve the interface between the electrode and the neural tissue. The Defense Advanced Research Project Agency (DARPA) as well as other federal funding agencies such as the National Science Foundation (NSF) and the National Institutes of Health have provided significant financial support to investigate this problem without much success. A recent funding program from DARPA was designed to establish the failure modes in order to generate a reliable neural interface technology and again was unsuccessful at producing a robust interface with the CNS. In 2013, two symposia were held independently to discuss this problem: one was held at the International Neuromodulation Society's 11th World Congress in Berlin and supported by the International Neuromodulation Society(1) and the other at the 6th International Neural Engineering conference in San Diego(2) and was supported by the NSF. Clearly, the neuromodulation and the neural engineering communities are keen to solve this problem. Experts from the field were assembled to discuss the problems and potential solutions. Although many important points were raised, few emerged as key issues. (1) The ability to access remotely and reliably internal neural signals . Although some of the technological problems have already been solved, this ability to access neural signals is still a significant problem since reliable and robust transcutaneous telemetry systems with large numbers of signals, each with wide bandwidth, are not readily available to researchers. (2) A translation strategy taking basic research to the clinic . The lack of understanding of the biological response to implanted constructs and the inability to monitor the sites and match the mechanical properties of the probe to the neural tissue properties continue to be an unsolved problem. In addition, the low levels of collaboration among neuroscientists, clinicians, patients and other stakeholders throughout different phases of research and development were considered to be significant impediments to progress. (3) Fundamental tools development procedures for neural interfacing . There are many laboratories testing various devices with different sets of criteria, but there is no consensus on the failure modes. The reliability, robustness of metrics and testing standards for such devices have not been established, either in academia or in industry. To start addressing this problem, the FDA has established a laboratory to test the reliability of some neural devices. Although the discussion was mostly centered on interfacing with the CNS, it has recently become clear that the peripheral nervous system (PNS) could be an important target for interfacing, perhaps even more accessible for interfacing than the CNS. A recent initiative called Bioelectronic Medicines(3) is a step in that direction. A recent summit held in New York was organized to investigate novel and disruptive neural technologies to interface specifically with the PNS in order to restore health and biological function to organs. With significant interest in neurotechnology for neural interfacing (see footnotes 1, 2 and 3) and uncovering new ways to treat, prevent and cure brain disorders (President Obama's brain initiative(4)), it seems clear that the problems at the interface will not remain unsolved for long. Finding solutions to the problem at the neural interface for interacting with the nervous system (PNS and CNS) is crucial for understanding and restoring brain function. This would in turn have a significant impact on health care and quality of life for patients with neural disorders. References  Follett K A et al 2010 Pallidal versus subthalamic deep-brain stimulation for Parkinson's disease New Engl. J. Med. 362 2077-91  Holtzheimer P E et al 2012 Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression Arch. Gen. Psychiatry 69 150  Carron R, Chabardes S and Hammond C 2012 Mechanisms of action of high-frequency deep brain stimulation. A review of the literature and current concepts NeuroChirurgie 58 209-17  Vidailhet M et al 2005 Bilateral deep-brain stimulation of the globus pallidus in primary generalized dystonia New Engl. J. Med. 352 459-67  Theodore W H and Fisher R S 2004 Brain stimulation for epilepsy Lancet Neurol. 3 111-8  Kübler A, Kotchoubey B, Kaiser J, Wolpaw J R and Birbaumer N 2001 Brain-computer communication: unlocking the locked Psychol. Bull. 127 358-75  Schalk G, Miller K J, Anderson N R, Wilson J A, Smyth M D, Ojemann J G, Moran D W, Wolpaw J R and Leuthardt E C 2008 Two-dimensional movement control using electrocorticographic signals in humans J. Neural Eng. 5 75  Serruya M D, Hatsopoulos N G, Paninski L, Fellows M R and Donoghue J P 2002 Brain-machine interface: instant neural control of a movement signal Nature 416 141-2  Hochberg L R, Serruya M D, Friehs G M, Mukand J A, Saleh M, Caplan A H, Branner A, Chen D, Penn R D and Donoghue J P 2006 Neuronal ensemble control of prosthetic devices by a human with tetraplegia Nature 442 164-71  Collinger J L et al 2013 High-performance neuroprosthetic control by an individual with tetraplegia Lancet 381 557-64  Leuthardt E C, Schalk G, Wolpaw J R, Ojemann J G and Moran D W 2004 A brain-computer interface using electrocorticographic signals in humans J. Neural Eng. 1 63  Maynard E M, Nordhausen C T and Normann R A 1997 The Utah intracortical electrode array: a recording structure for potential brain-computer interfaces Electroencephalogr. Clin. Neurophysiol. 102 228-39 (1) www.neuromodulation.com/8-june-2013 (2) http://neuro.embs.org/wp-content/uploads/sites/2/2013/05/SymposiumAdvert1.pdf (3) www.gsk.com/explore-gsk/how-we-do-r-and-d/bioelectronics.html (4) www.whitehouse.gov/share/brain-initiative.
PMID: 24503546 [PubMed - as supplied by publisher]
Reduced task-induced variations in the distribution of activity across back muscle regions in individuals with low back pain.
Pain. 2014 Feb 3;
Authors: Falla D, Gizzi L, Tschapek M, Erlenwein J, Petzke F
This study investigated change in the distribution of lumbar erector spinae muscle activity and pressure pain sensitivity across the low back in individuals with low back pain (LBP) and healthy controls. Surface electromyographic (EMG) signals were recorded from multiple locations over the lumbar erector spinae muscle with a 13×5 grid of electrodes from 19 people with chronic non-specific LBP and 17 control subjects as they performed a repetitive lifting task. The EMG root mean square (RMS) was computed for each location of the grid to form a map of the EMG amplitude distribution. Pressure pain thresholds (PPT) were recorded before and after the lifting task over a similar area of the back. For the control subjects, the EMG RMS progressively increased more in the caudal region of the lumbar erector spinae during the repetitive task resulting in a shift in the distribution of muscle activity. In contrast, the distribution of muscle activity remained unaltered in the LBP group despite an overall increase in EMG amplitude. PPT was lower in the LBP group after completion of the repetitive task compared to baseline (average across all locations: pre: 268.0±165.9kPa; post: 242.0±166.7kPa) whereas no change in PPT over time was observed for the control group (320.1±162.1kPa; post: 322.0±179.5kPa). The results demonstrate that LBP alters the normal adaptation of lumbar erector spinae muscle activity to exercise which occurs in the presence of exercise-induced hyperalgesia. Reduced variability of muscle activity may have important implications for the provocation and recurrence of LBP due to repetitive tasks.
PMID: 24502841 [PubMed - as supplied by publisher]
A hybrid intelligent system for diagnosing microalbuminuria in type 2 diabetes patients without having to measure urinary albumin.
Comput Biol Med. 2014 Feb;45:34-42
Authors: Marateb HR, Mansourian M, Faghihimani E, Amini M, Farina D
Microalbuminuria (MA) is an independent predictor of cardiovascular and renal disease, development of overt nephropathy, and cardiovascular mortality in patients with type 2 diabetes. Detecting MA is an important screening tool to identify people with high risk of cardiovascular and kidney disease. The gold standard to detect MA is measuring 24-h urine albumin excretion. A new method for MA diagnosis is presented in this manuscript which uses clinical parameters usually monitored in type 2 diabetic patients without the need of an additional measurement of urinary albumin. We designed an expert-based fuzzy MA classifier in which rule induction was performed by particle swarm optimization. A variety of classifiers was tested. Additionally, multiple logistic regression was used for statistical feature extraction. The significant features were age, diabetic duration, body mass index and HbA1C (the average level of blood sugar over the previous 3 months, which is routinely checked every 3 months for diabetic patients). The resulting classifier was tested on a sample size of 200 patients with type 2 diabetes in a cross-sectional study. The performance of the proposed classifier was assessed using (repeated) holdout and 10-fold cross-validation. The minimum sensitivity, specificity, precision and accuracy of the proposed fuzzy classifier system with feature extraction were 95%, 85%, 84% and 92%, respectively. The proposed hybrid intelligent system outperformed other tested classifiers and showed "almost perfect agreement" with the gold standard. This algorithm is a promising new tool for screening MA in type-2 diabetic patients.
PMID: 24480161 [PubMed - in process]
Can retinal ganglion cell dipoles seed iso-orientation domains in the visual cortex?
PLoS One. 2014;9(1):e86139
Authors: Schottdorf M, Eglen SJ, Wolf F, Keil W
It has been argued that the emergence of roughly periodic orientation preference maps (OPMs) in the primary visual cortex (V1) of carnivores and primates can be explained by a so-called statistical connectivity model. This model assumes that input to V1 neurons is dominated by feed-forward projections originating from a small set of retinal ganglion cells (RGCs). The typical spacing between adjacent cortical orientation columns preferring the same orientation then arises via Moiré-Interference between hexagonal ON/OFF RGC mosaics. While this Moiré-Interference critically depends on long-range hexagonal order within the RGC mosaics, a recent statistical analysis of RGC receptive field positions found no evidence for such long-range positional order. Hexagonal order may be only one of several ways to obtain spatially repetitive OPMs in the statistical connectivity model. Here, we investigate a more general requirement on the spatial structure of RGC mosaics that can seed the emergence of spatially repetitive cortical OPMs, namely that angular correlations between so-called RGC dipoles exhibit a spatial structure similar to that of OPM autocorrelation functions. Both in cat beta cell mosaics as well as primate parasol receptive field mosaics we find that RGC dipole angles are spatially uncorrelated. To help assess the level of these correlations, we introduce a novel point process that generates mosaics with realistic nearest neighbor statistics and a tunable degree of spatial correlations of dipole angles. Using this process, we show that given the size of available data sets, the presence of even weak angular correlations in the data is very unlikely. We conclude that the layout of ON/OFF ganglion cell mosaics lacks the spatial structure necessary to seed iso-orientation domains in the primary visual cortex.
PMID: 24475081 [PubMed - in process]
Functional cortical connectivity analysis of mental fatigue unmasks hemispheric asymmetry and changes in small-world networks.
Brain Cogn. 2014 Jan 21;85C:220-230
Authors: Sun Y, Lim J, Kwok K, Bezerianos A
Changes in functional connectivity across mental states can provide richer information about human cognition than simpler univariate approaches. Here, we applied a graph theoretical approach to analyze such changes in the lower alpha (8-10Hz) band of EEG data from 26 subjects undergoing a mentally-demanding test of sustained attention: the Psychomotor Vigilance Test. Behavior and connectivity maps were compared between the first and last 5min of the task. Reaction times were significantly slower in the final minutes of the task, showing a clear time-on-task effect. A significant increase was observed in weighted characteristic path length, a measure of the efficiency of information transfer within the cortical network. This increase was correlated with reaction time change. Functional connectivity patterns were also estimated on the cortical surface via source localization of cortical activities in 26 predefined regions of interest. Increased characteristic path length was revealed, providing further support for the presence of a reshaped global topology in cortical connectivity networks under fatigue state. Additional analysis showed an asymmetrical pattern of connectivity (right>left) in fronto-parietal regions associated with sustained attention, supporting the right-lateralization of this function. Interestingly, in the fatigue state, significance decreases were observed in left, but not right fronto-parietal connectivity. Our results indicate that functional network organization can change over relatively short time scales with mental fatigue, and that decreased connectivity has a meaningful relationship with individual difference in behavior and performance.
PMID: 24463002 [PubMed - as supplied by publisher]
A role for sorting nexin 27 in AMPA receptor trafficking.
Nat Commun. 2014 Jan 24;5:3176
Authors: Loo LS, Tang N, Al-Haddawi M, Stewart Dawe G, Hong W
Sorting nexin 27 (SNX27), a PDZ domain-containing endosomal protein, was recently shown to modulate glutamate receptor recycling in Down's syndrome. However, the precise molecular role of SNX27 in GluA1 trafficking is unclear. Here we report that SNX27 is enriched in dendrites and spines, along with recycling endosomes. Significantly, the mobilization of SNX27 along with recycling endosomes into spines was observed. Mechanistically, SNX27 interacts with K-ras GTPase via the RA domain; and following chemical LTP stimuli, K-ras is recruited to SNX27-enriched endosomes through a Ca(2+)/CaM-dependent mechanism, which in turn drives the synaptic delivery of homomeric GluA1 receptors. Impairment of SNX27 prevents LTP and associated trafficking of AMPARs. These results demonstrate a role for SNX27 in neuronal plasticity, provide a molecular explanation for the K-ras signal during LTP and identify SNX27 as the PDZ-containing molecular linker that couples the plasticity stimuli to the delivery of postsynaptic cargo.
PMID: 24458027 [PubMed - in process]
Neural correlates of task-related changes in physiological tremor.
J Neurophysiol. 2013 Jul;110(1):170-6
Authors: Laine CM, Negro F, Farina D
Appropriate control of muscle contraction requires integration of command signals with sensory feedback. Sensorimotor integration is often studied under conditions in which muscle force is controlled with visual feedback. While it is known that alteration of visual feedback can influence task performance, the underlying changes in neural drive to the muscles are not well understood. In this study, we characterize the frequency content of force fluctuations and neural drive when production of muscle force is target guided versus self guided. In the self-guided condition, subjects performed isometric contractions of the first dorsal interosseous (FDI) muscle while slowly and randomly varying their force level. Subjects received visual feedback of their own force in order to keep contractions between 6% and 10% of maximum voluntary contraction (MVC). In the target-guided condition, subjects used a display of their previously generated force as a target to track over time. During target tracking, force tremor increased significantly in the 3-5 and 7-9 Hz ranges, compared with self-guided contractions. The underlying changes in neural drive were assessed by coherence analysis of FDI motor unit activity. During target-guided force production, pairs of simultaneously recorded motor units showed less coherent activity in the 3-5 Hz frequency range but greater coherence in the 7-9 Hz range than in the self-guided contractions. These results show that the frequency content of common synaptic input to motoneurons is altered when force production is visually guided. We propose that a change in stretch-reflex gain could provide a potential mechanism for the observed changes in force tremor and motor unit coherence.
PMID: 23596333 [PubMed - indexed for MEDLINE]
Deliver us from evil? The temptation, realities, and neuroethico-legal issues of employing assessment neurotechnologies in public safety initiatives.
Theor Med Bioeth. 2014 Jan 20;
Authors: Giordano J, Kulkarni A, Farwell J
In light of the recent events of terrorism and publicized cases of mass slayings and serial killings, there have been calls from the public and policy-makers alike for neuroscience and neurotechnology (neuroS/T) to be employed to intervene in ways that define and assess, if not prevent, such wanton acts of aggression and violence. Ongoing advancements in assessment neuroS/T have enabled heretofore unparalleled capabilities to evaluate the structure and function of the brain, yet each and all are constrained by certain technical and practical limitations. In this paper, we present an overview of the capabilities and constraints of current assessment neuroS/T, address neuro-ethical and legal issues fostered by the use and potential misuse of these approaches, and discuss how neuroethics may inform science and the law to guide right and sound applications of neuroS/T to "deliver us from evil" while not being led into temptations of ampliative claims and inapt use.
PMID: 24442931 [PubMed - as supplied by publisher]
Modes and regulation of endocytic membrane retrieval in mouse auditory hair cells.
J Neurosci. 2014 Jan 15;34(3):705-16
Authors: Neef J, Jung S, Wong AB, Reuter K, Pangrsic T, Chakrabarti R, Kügler S, Lenz C, Nouvian R, Boumil RM, Frankel WN, Wichmann C, Moser T
Synaptic vesicle recycling sustains high rates of neurotransmission at the ribbon-type active zones (AZs) of mouse auditory inner hair cells (IHCs), but its modes and molecular regulation are poorly understood. Electron microscopy indicated the presence of clathrin-mediated endocytosis (CME) and bulk endocytosis. The endocytic proteins dynamin, clathrin, and amphiphysin are expressed and broadly distributed in IHCs. We used confocal vglut1-pHluorin imaging and membrane capacitance (Cm) measurements to study the spatial organization and dynamics of IHC exocytosis and endocytosis. Viral gene transfer expressed vglut1-pHluorin in IHCs and targeted it to synaptic vesicles. The intravesicular pH was ?6.5, supporting only a modest increase of vglut1-pHluorin fluorescence during exocytosis and pH neutralization. Ca(2+) influx triggered an exocytic increase of vglut1-pHluorin fluorescence at the AZs, around which it remained for several seconds. The endocytic Cm decline proceeded with constant rate (linear component) after exocytosis of the readily releasable pool (RRP). When exocytosis exceeded three to four RRP equivalents, IHCs additionally recruited a faster Cm decline (exponential component) that increased with the amount of preceding exocytosis and likely reflects bulk endocytosis. The dynamin inhibitor Dyngo-4a and the clathrin blocker pitstop 2 selectively impaired the linear component of endocytic Cm decline. A missense mutation of dynamin 1 (fitful) inhibited endocytosis to a similar extent as Dyngo-4a. We propose that IHCs use dynamin-dependent endocytosis via CME to support vesicle cycling during mild stimulation but recruit bulk endocytosis to balance massive exocytosis.
PMID: 24431429 [PubMed - in process]
Flavoprotein autofluorescence imaging of visual system activity in zebra finches and mice.
PLoS One. 2014;9(1):e85225
Authors: Michael N, Bischof HJ, Löwel S
Large-scale brain activity patterns can be visualized by optical imaging of intrinsic signals (OIS) based on activity-dependent changes in the blood oxygenation level. Another method, flavoprotein autofluorescence imaging (AFI), exploits the mitochondrial flavoprotein autofluorescence, which is enhanced during neuronal activity. In birds, topographic mapping of visual space has been shown in the visual wulst, the avian homologue of the mammalian visual cortex by using OIS. We here applied the AFI method to visualize topographic maps in the visual wulst because with OIS, which depends on blood flow changes, blood vessel artifacts often obscure brain activity maps. We then compared both techniques quantitatively in zebra finches and in C57Bl/6J mice using the same setup and stimulation conditions. In addition to experiments with craniotomized animals, we also examined mice with intact skull (in zebra finches, intact skull imaging is not feasible probably due to the skull construction). In craniotomized animals, retinotopic maps were obtained by both methods in both species. Using AFI, artifacts caused by blood vessels were generally reduced, the magnitude of neuronal activity significantly higher and the retinotopic map quality better than that obtained by OIS in both zebra finches and mice. In contrast, our measurements in non-craniotomized mice did not reveal any quantitative differences between the two methods. Our results thus suggest that AFI is the method of choice for investigations of visual processing in zebra finches. In mice, however, if researchers decide to use the advantages of imaging through the intact skull, they will not be able to exploit the higher signals obtainable by the AFI-method.
PMID: 24400130 [PubMed - in process]
EEG alpha activity is associated with individual differences in post-break improvement.
Neuroimage. 2013 Aug 1;76:81-9
Authors: Lim J, Quevenco FC, Kwok K
Continuous EEG activity has been used increasingly as a marker of mental and cognitive states, with previous work linking particular neural patterns to conditions of arousal or fatigue. This approach is more commonly used to assess task-related, as opposed to resting-state activity. In this study, we recorded the EEG of 31 healthy individuals as they performed two sessions of a 65-minute auditory oddball task, one with, and one without a 5-minute break opportunity. Over the course of the task, reaction times, as well as EEG power in theta and lower alpha bands increased in both conditions, but did not differ significantly between conditions. Over the period of the break, delta and theta EEG activity decreased significantly in comparison with activity in the equivalent period in the no-break condition. Individual differences in response to the break were observed, with approximately half the subjects showing an improvement, and half showing a decline. These individual differences were correlated both with decreases in theta activity, as well as resting upper alpha power during the period of the break. Our results suggest that tonic EEG activity during resting periods is meaningfully related to behavioral change between individuals based on physiological or psychological factors that remain to be explored.
PMID: 23523810 [PubMed - indexed for MEDLINE]
How do we recognise who is speaking?
Front Biosci (Schol Ed). 2014;6:92-109
Authors: Mathias SR, von Kriegstein K
The human brain effortlessly extracts a wealth of information from natural speech, which allows the listener to both understand the speech message and recognise who is speaking. This article reviews behavioural and neuroscientific work that has attempted to characterise how listeners achieve speaker recognition. Behavioural studies suggest that the action of a speaker's glottal folds and the overall length of their vocal tract carry important voice-quality information. Although these cues are useful for discriminating and recognising speakers under certain circumstances, listeners may use virtually any systematic feature for recognition. Neuroscientific studies have revealed that speaker recognition relies upon a predominantly right-lateralised network of brain regions. Specifically, the posterior parts of superior temporal sulcus appear to perform some of the acoustical analyses necessary for the perception of speaker and message, whilst anterior portions may play a more abstract role in perceiving speaker identity. This voice-processing network is supported by direct, early connections to non-auditory regions, such as the visual face-sensitive area in the fusiform gyrus, which may serve to optimize person recognition.
PMID: 24389264 [PubMed - in process]
What do clinicians need from a rehabilitation treatment taxonomy? An alternate approach for describing treatment content versus process.
Arch Phys Med Rehabil. 2014 Jan;95(1 Suppl):S74-6
Authors: Fasoli SE, Chen CC
Clinician feedback and thought processes about treatment classification and description will aid development of the rehabilitation treatment taxonomy (RTT) presented in this supplement. Here, we discuss comparisons between the proposed RTT and an inductive practice-based evidence (PBE) model used to describe rehabilitation treatments. Interviews with clinicians well versed with PBE highlight the complexity of rehabilitation treatments, and bring to light potential advantages and challenges of a deductive, theory-driven classification to uncover the black box of rehabilitation.
PMID: 24370328 [PubMed - in process]
A non-parametric Bayesian approach for clustering and tracking non-stationarities of neural spikes.
J Neurosci Methods. 2013 Dec 12;
Authors: Shalchyan V, Farina D
-Background Neural spikes from multiple neurons recorded in a multi-unit signal are usually separated by clustering. Drifts in the position of the recording electrode relative to the neurons over time cause gradual changes in the position and shapes of the clusters, challenging the clustering task. By dividing the data into short time intervals, Bayesian tracking of the clusters based on Gaussian cluster model has been previously proposed. However, the Gaussian cluster model is often not verified for neural spikes. -New Method We present a Bayesian clustering approach that makes no assumptions on the distribution of the clusters and use kernel-based density estimation of the clusters in every time interval as a prior for Bayesian classification of the data in the subsequent time interval. -Comparison with Existing Methods The proposed method was tested and compared to Gaussian model-based approach for cluster tracking by using both simulated and experimental datasets. -Results The results showed that the proposed non-parametric kernel-based density estimation of the clusters outperformed the sequential Gaussian model fitting in both simulated and experimental data tests. -Conclusions Using Non-parametric kernel density-based clustering that makes no assumptions on the distribution of the clusters enhances the ability of tracking cluster non-stationarity over time with respect to the Gaussian cluster modeling approach.
PMID: 24333470 [PubMed - as supplied by publisher]
Neurovascular coupling: in vivo optical techniques for functional brain imaging.
Biomed Eng Online. 2013;12:38
Authors: Liao LD, Tsytsarev V, Delgado-Martínez I, Li ML, Erzurumlu R, Vipin A, Orellana J, Lin YR, Lai HY, Chen YY, Thakor NV
Optical imaging techniques reflect different biochemical processes in the brain, which is closely related with neural activity. Scientists and clinicians employ a variety of optical imaging technologies to visualize and study the relationship between neurons, glial cells and blood vessels. In this paper, we present an overview of the current optical approaches used for the in vivo imaging of neurovascular coupling events in small animal models. These techniques include 2-photon microscopy, laser speckle contrast imaging (LSCI), voltage-sensitive dye imaging (VSDi), functional photoacoustic microscopy (fPAM), functional near-infrared spectroscopy imaging (fNIRS) and multimodal imaging techniques. The basic principles of each technique are described in detail, followed by examples of current applications from cutting-edge studies of cerebral neurovascular coupling functions and metabolic. Moreover, we provide a glimpse of the possible ways in which these techniques might be translated to human studies for clinical investigations of pathophysiology and disease. In vivo optical imaging techniques continue to expand and evolve, allowing us to discover fundamental basis of neurovascular coupling roles in cerebral physiology and pathophysiology.
PMID: 23631798 [PubMed - indexed for MEDLINE]
Identification of common synaptic inputs to motor neurons from the rectified electromyogram.
J Physiol. 2013 May 15;591(Pt 10):2403-18
Authors: Farina D, Negro F, Jiang N
Oscillatory common inputs of cortical or peripheral origin can be identified from the motor neuron output with coherence analysis. Linear transmission is possible despite the motor neuron non-linearity because the same input is sent commonly to several neurons. Because of the linear transmission, common input components to motor neurons can be investigated from the surface EMG, for example by EEG-EMG or EMG-EMG coherence. In these studies, there is an open debate on the utility and appropriateness of EMG rectification. The present study addresses this issue using an analytical, simulation and experimental approach. The main novel theoretical contribution that we report is that the spectra of both the rectified and the raw EMG contain input spectral components to motor neurons. However, they differ by the contribution of amplitude cancellation which influences the rectified EMG spectrum when extracting common oscillatory inputs. Therefore, the degree of amplitude cancellation has an impact on the effectiveness of EMG rectification in extracting input spectral peaks. The theoretical predictions were exactly confirmed by realistic simulations of a pool of motor neurons innervating a muscle in a cylindrical volume conductor of EMG generation and by experiments conducted on the first dorsal interosseous and the abductor pollicis brevis muscles of seven healthy subjects during pinching. It was concluded that when the contraction level is relatively low, EMG rectification may be preferable for identifying common inputs to motor neurons, especially when the energy of the action potentials in the low frequency range is low. Nonetheless, different levels of cancellation across conditions influence the relative estimates of the degree of linear transmission of oscillatory inputs to motor neurons when using the rectified EMG.
PMID: 23507877 [PubMed - indexed for MEDLINE]
The role of actigraphy in the assessment of primary insomnia: a retrospective study.
Sleep Med. 2013 Nov 15;
Authors: Natale V, Léger D, Martoni M, Bayon V, Erbacci A
OBJECTIVE: The aim of our study was to evaluate quantitative actigraphic criteria obtained using the Actiwatch device (AW64; Cambridge Neurotechnology Ltd., Cambridge, UK) to differentiate participants with insomnia from normal sleepers.
METHODS: In our retrospective study, we recovered 493 actigraphic records from two sleep measure databases of patients with insomnia (n=151) and one of normal sleepers (n=342). We considered the following actigraphic sleep parameters: time in bed (TIB), sleep-onset latency (SOL), total sleep time (TST), wake after sleep onset (WASO), sleep efficiency (SE), number of awakenings (NWAK), terminal wakefulness (TWAK), fragmentation index (FI), and mean motor activity (MA). We also considered two actigraphic circadian indexes: interdaily stability and intradaily variability. Using the Youden index, we calculated the quantitative actigraphic criteria that performed best for each actigraphic sleep parameter. Finally, we created receiver operating characteristic curves to test the accuracy of each criterion identified.
RESULTS: All sleep parameters except TST and TWAK differentiated the two groups of participants, allowing calculation of quantitative actigraphic criteria. There were no differences in the circadian indices.
CONCLUSIONS: The quantitative actigraphic criteria obtained in our study were not the same as those obtained previously with a different device, suggesting the need to adopt shared technical solutions for actigraphy.
PMID: 24325809 [PubMed - as supplied by publisher]
Comparison of 7 versus 14 days wrist actigraphy monitoring in a sleep disorders clinic population.
Chronobiol Int. 2013 Dec 4;
Authors: Briscoe S, Hardy E, Pengo MF, Kosky C, Williams AJ, Hart N, Steier J
Wrist actigraphy is a valid measure to assess sleep and circadian rhythm abnormalities. It is listed in the diagnostic criteria for sleep disorders where single night polysomnography is insufficient (ICSD-2). However, an optimal recording time remains unclear. We hypothesised that seven days would provide sufficient data for analysis, similar to recordings for 14 days. We analysed three consecutive years of actigraphy data obtained within a tertiary sleep referral centre. Data were recorded continuously for two weeks using an AW4 actiwatch (Cambridge NeuroTechnology, Cambridge, UK; Mini Mitter Co, Sunriver, OR). Parameters, including sleep efficiency (SE), sleep latency (SL), sleep fragmentation index (SFI), total sleep time (TST) and wake after sleep onset (WASO) were analysed using GraphPad Prism (Version 5.02, GraphPad Software Inc, San Diego, CA) and classified into week one, week two and an overall average for the duration of 14 days. In addition, two experienced consultants working in the sleep laboratory compared the results of week one versus week two independently, visually analysing the data for circadian rhythmicity and fragmentation of the pattern, allowing calculation of the intraclass correlation coefficient (ICC), ?. The actigraphies of 239 patients (51.9% male; age 42 (16) years) were analysed. There was no difference in SE, SL, SFI or WASO between week one, week two and 14 days average recording. A small difference was found between TST week one (399.9 minutes, 95% CI 389.9-409.9 minutes) and TST week two (388.7 minutes, 95% CI 378.3-399.1 minutes), but not between TST for 14 days average recording (394.3 minutes, 95% CI 384.7-403.9 minutes) and either week. Independent scorers achieved a good agreement in the rhythmicity of the sleep pattern (ICC ? 0.734, p?<?0.001) and a low agreement for the fragmentation of the pattern (ICC ? 0.380, p?<?0.001). One week of wrist actigraphy recording provides similar data to two week actigraphies, despite subtle differences between the weeks. One week wrist actigraphy could be recommended as standard compared to longer recordings to maximise efficiency of the clinical service. Further studies are required to validate our results in specific clinical subgroups.
PMID: 24304408 [PubMed - as supplied by publisher]
Brain-machine interface (BMI) - application to neurological disorders.
Rinsho Shinkeigaku. 2013;53(11):962-5
Authors: Yoshimine T, Yanagisawa T, Hirata M
Brain-machine interface (BMI) is a new technology to receive input from the brain which is translated to operate a computer or other external device in real time. After significant progress during the recent 10 years, this technology is now very close to the clinical use to restore neural functions of patients with severe neurologic impairment. This technology is also a strong tool to investigate the mode of neuro-signal processing in the brain and to understand the mechanism of neural dysfunction which leads to the development of novel neurotechnology for the treatment of various sorts of neurological disorders.
PMID: 24291847 [PubMed - in process]