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Journal of Neuroscience Methods

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https://www.readbyqxmd.com/read/27914975/techniques-for-chronic-monitoring-of-brain-activity-in-freely-moving-sheep-using-wireless-longitudinal-eeg-recording
#1
N Perentos, A U Nicol, A Q Martins, J E Stewart, P Taylor, A J Morton
BACKGROUND: Large mammals with complex central nervous systems offer new possibilities for translational research into basic brain function. Techniques for monitoring brain activity in large mammals, however, are not as well developed as they are in rodents. NEW METHOD: We have developed a method for chronic monitoring of electroencephalographic (EEG) activity in unrestrained sheep. We describe the methods for behavioural training prior to implantation, surgical procedures for implantation, a protocol for reliable anaesthesia and recovery, methods for EEG data collection, as well as data pertaining to suitability and longevity of different types of electrodes...
November 30, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27913211/sgrasp-a-graph-based-method-for-the-derivation-of-subject-specific-functional-parcellations-of-the-brain
#2
N Honnorat, T D Satterthwaite, R E Gur, R C Gur, C Davatzikos
BACKGROUND: Resting-state fMRI (rs-fMRI) has emerged as a prominent tool for the study of functional connectivity. The identification of the regions associated with the different brain functions has received significant interest. However, most of the studies conducted so far have focused on the definition of a common set of regions, valid for an entire population. The variation of the functional regions within a population has rarely been accounted for. New Method: In this paper, we propose sGraSP, a graph-based approach for the derivation of subject-specific functional parcellations...
November 29, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27899319/cost-effective-raspberry-pi-based-radio-frequency-identification-tagging-of-mice-suitable-for-automated-in-vivo-imaging
#3
Federico Bolaños, Jeff M LeDue, Timothy H Murphy
BACKGROUND: Automation of animal experimentation improves consistency, reduces potential for error while decreasing animal stress and increasing well-being. Radio frequency identification (RFID) tagging can identify individual mice in group housing environments enabling animal-specific tracking of physiological parameters. NEW METHOD: We describe a simple protocol to radio frequency identification (RFID) tag and detect mice. RFID tags were injected sub-cutaneously after brief isoflurane anesthesia and do not require surgical steps such as suturing or incisions...
November 27, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27894783/comparison-of-speed-vacuum-method-and-heat-drying-method-to-measure-brain-water-content-of-small-brain-samples
#4
Anne Sebastiani, Tobias Hirnet, Antje Jahn-Eimermacher, Serge C Thal
BACKGROUND: A reliable measurement of brain water content (wet-to-dry ratio) is an important prerequisite for conducting research on mechanisms of brain edema formation. The conventionally used oven-drying method suffers from several limitations, especially in small samples. A technically demanding and time-consuming alternative is freeze-drying. NEW METHOD: Centrifugal vacuum concentrators (e.g. SpeedVac/speed-vacuum drying) are a combination of vacuum-drying and centrifugation, used to reduce the boiling temperature...
November 25, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27894782/transitioning-eeg-experiments-away-from-the-laboratory-using-a-raspberry-pi-2
#5
Jonathan W P Kuziek, Axita Shienh, Kyle E Mathewson
BACKGROUND: Electroencephalography (EEG) experiments are typically performed in controlled laboratory settings to minimise noise and produce reliable measurements. These controlled conditions also reduce the applicability of the obtained results to more varied environments and may limit their relevance to everyday situations. NEW METHOD: Advances in computer portability may increase the mobility and applicability of EEG results while decreasing costs. In this experiment we show that stimulus presentation using a Raspberry Pi 2 computer provides a low cost, reliable alternative to a traditional desktop PC in the administration of EEG experimental tasks...
November 25, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27887969/flexible-head-casts-for-high-spatial-precision-meg
#6
Sofie S Meyer, James Bonaiuto, Mark Lim, Holly Rossiter, Sheena Waters, David Bradbury, Sven Bestmann, Matthew Brookes, Martina F Callaghan, Nikolaus Weiskopf, Gareth R Barnes
BACKGROUND: In combination with magnetoencephalographic (MEG) data, accurate knowledge of the brain's structure and location provide a principled way of reconstructing neural activity with high temporal resolution. However, measuring the brain's location is compromised by head movement during scanning, and by fiducial-based co-registration with magnetic resonance imaging (MRI) data. The uncertainty from these two factors introduces errors into the forward model and limit the spatial resolution of the data...
November 22, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27867012/a-robust-sparse-modeling-framework-for-estimating-schizophrenia-biomarkers-from-fmri
#7
Keith Dillon, Vince Calhoun, Yu-Ping Wang
BACKGROUND: Our goal is to identify the brain regions most relevant to mental illness using neuroimaging. State of the art machine learning methods commonly suffer from repeatability difficulties in this application, particularly when using large and heterogeneous populations for samples. NEW METHOD: We revisit both dimensionality reduction and sparse modeling, and recast them in a common optimization-based framework. This allows us to combine the benefits of both types of methods in an approach which we call unambiguous components...
November 17, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27856276/the-complex-hierarchical-topology-of-eeg-functional-connectivity
#8
Keith Smith, Javier Escudero
BACKGROUND: Understanding the complex hierarchical topology of functional brain networks is a key aspect of functional connectivity research. Such topics are obscured by the widespread use of sparse binary network models which are fundamentally different to the complete weighted networks derived from functional connectivity. NEW METHODS: We introduce two techniques to probe the hierarchical complexity of topologies. Firstly, a new metric to measure hierarchical complexity; secondly, a Weighted Complex Hierarchy (WCH) model...
November 14, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27856275/rnaseq-profiling-of-primary-microglia-and-astrocyte-cultures-in-near-term-ovine-fetus-a-glial-in-vivo-in-vitro-multi-hit-paradigm-in-large-mammalian-brain
#9
M Cortes, M Cao, H L Liu, P Burns, C Moore, G Fecteau, A Desrochers, L B Barreiro, J P Antel, M G Frasch
BACKGROUND: The chronically instrumented fetal sheep is a widely used animal model to study fetal brain development in health and disease, but no methods exist yet to interrogate dedicated brain cell populations to identify their molecular and genomic phenotype. For example, the molecular mechanisms whereby microglia or astrocytes contribute to inflammation in the brain remain incompletely understood. NEW METHOD: Here we present a protocol to derive primary pure microglial or astrocyte cultures from near-term fetal sheep brain, after the animals have been chronically instrumented and studied in vivo...
November 14, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27856274/improved-assessment-of-sensorimotor-gating-in-animal-models-relevant-to-asd-a-data-modelling-approach-to-quantify-prepulse-inhibition-of-the-acoustic-startle-reflex
#10
Stéphanie Degroote, Darel Hunting, Larissa Takser
BACKGROUND: The PrePulse Inhibition (PPI) of the acoustic startle reflex is a neurobehavioral test frequently used in neurodevelopmental studies. Most PPI studies have used rodent models of schizophrenia; however, the currently used data analysis method does not take into account the variability present in autistic preclinical models. NEW METHOD: We propose a new data modelling approach for PPI data obtained from animals exposed to valproic acid or endocrine disruptors, using mixed modeling; and a new calculation of inhibition of the acoustic startle, which takes into account the habituation phenomenon...
November 14, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27851906/magpy-a-python-toolbox-for-controlling-magstim-transcranial-magnetic-stimulators
#11
Nicolas A McNair
BACKGROUND: To date, transcranial magnetic stimulation (TMS) studies manipulating stimulation parameters have largely used blocked paradigms. However, altering these parameters on a trial-by-trial basis in Magstim stimulators is complicated by the need to send regular (1Hz) commands to the stimulator. Additionally, effecting such control interferes with the ability to send TMS pulses or simultaneously present stimuli with high-temporal precision. NEW METHOD: This manuscript presents the MagPy toolbox, a Python software package that provides full control over Magstim stimulators via the serial port...
November 13, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27845151/data-fusion-for-paroxysmal-events-classification-from-eeg
#12
Evangelia Pippa, Evangelia I Zacharaki, Michael Koutroumanidis, Vasileios Megalooikonomou
BACKGROUND: Spatiotemporal analysis of electroencephalography is commonly used for classification of events since it allows capturing dependencies across channels. The significant increase of feature vector dimensionality however introduce noise and thus it does not allow the classification models to be trained using a limited number of samples usually available in clinical studies. NEW METHOD: Thus, we investigate the classification of epileptic and non-epileptic events based on temporal and spectral analysis through the application of three different fusion schemes for the combination of information across channels...
November 11, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27845150/the-extraction-of-motion-onset-vep-bci-features-based-on-deep-learning-and-compressed-sensing
#13
Teng Ma, Hui Li, Hao Yang, Xulin Lv, Peiyang Li, Tiejun Liu, Dezhong Yao, Peng Xu
BACKGROUND: Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong background EEG activities, and an effective approach is needed to extract the corresponding mVEP features to perform task recognition for BCI control. NEW METHOD: In the current study, we combine deep learning with compressed sensing to mine discriminative mVEP information to improve the mVEP BCI performance...
November 11, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27840146/computerized-spiral-analysis-using-the-ipad
#14
Jonathan A Sisti, Brandon Christophe, Audrey Rakovich Seville, Andrew L A Garton, Vivek P Gupta, Alexander J Bandin, Qiping Yu, Seth L Pullman
BACKGROUND: Digital analysis of writing and drawing has become a valuable research and clinical tool for the study of upper limb motor dysfunction in patients with essential tremor, Parkinson's disease, dystonia, and related disorders. We developed a validated method of computerized spiral analysis of hand-drawn Archimedean spirals that provides insight into movement dynamics beyond subjective visual assessment using a Wacom graphics tablet. While the Wacom tablet method provides robust data, more widely available mobile technology platforms exist...
November 10, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27836729/discovering-recurring-patterns-in-electrophysiological-recordings
#15
Bart Gips, Ali Bahramisharif, Eric Lowet, Mark J Roberts, Peter de Weerd, Ole Jensen, Jan van der Eerden
BACKGROUND: Fourier-based techniques are used abundantly in the analysis of electrophysiological data. However, these techniques are of limited value when the signal of interest is non-sinusoidal or non-periodic. NEW METHOD: We present sliding window matching (SWM): a new data-driven method for discovering recurring temporal patterns in electrophysiological data. SWM is effective in detecting recurring but unknown patterns even when they appear non-periodically...
November 8, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27832957/the-physio-toolbox-for-modeling-physiological-noise-in-fmri-data
#16
Lars Kasper, Steffen Bollmann, Andreea O Diaconescu, Chloe Hutton, Jakob Heinzle, Sandra Iglesias, Tobias U Hauser, Miriam Sebold, Zina-Mary Manjaly, Klaas P Pruessmann, Klaas E Stephan
BACKGROUND: Physiological noise is one of the major confounds for fMRI. A common class of correction methods model noise from peripheral measures, such as ECGs or pneumatic belts. However, physiological noise correction has not emerged as a standard preprocessing step for fMRI data yet due to: (1) the varying data quality of physiological recordings, (2) non-standardized peripheral data formats and (3) the lack of full automatization of processing and modeling physiology, required for large-cohort studies...
November 8, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27826091/detectability-of-granger-causality-for-subsampled-continuous-time-neurophysiological-processes
#17
Lionel Barnett, Anil K Seth
BACKGROUND: Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. NEW METHOD: We present a theoretical analysis of the effects of subsampling on Granger-causal inference...
November 5, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27794451/total-variation-for-the-analysis-of-event-related-potentials
#18
Alexander Klein, Wolfgang Skrandies
BACKGROUND: Event-related potential waveforms are often analysed in the time-domain for changes of striking morphological features, like amplitudes or latencies of extrema, at the expense of missing less obvious changes in overall morphology. NEW METHOD: The measure of total variation can capture a variety of changes in curve morphology. We show analytical examples, and the application to two sets of EEG data (n1=41, n2=19) difficult to analyse with more traditional methods...
October 26, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27771307/nerve-excitability-in-the-rat-forelimb-a-technique-to-improve-translational-utility
#19
Ria Arnold, Mihai Moldovan, Mette Romer Rosberg, Arun V Krishnan, Renee Morris, Christian Krarup
BACKGROUND: Nerve excitability testing by threshold-tracking is the only available method to study axonal ion channel function and membrane potential in the clinical setting. The measures are, however, indirect and the interpretation of neuropathic changes remains challenging. The same multiple measures of axonal excitability were adapted to further explore the pathophysiological changes in rodent disease models under pharmacologic and genetic manipulations. These studies are typically limited to the investigation of the "long nerves" such as the tail or the tibial nerves...
October 19, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27769876/seizure-specific-wavelet-seizlet-design-for-epileptic-seizure-detection-using-correntropy-ellipse-features-based-on-seizure-modulus-maximas-patterns
#20
Morteza Behnam, Hossein Pourghassem
BACKGROUND: EEG signal analysis of pediatric patients plays vital role for making a decision to intervene in presurgical stages. NEW METHOD: In this paper, an offline seizure detection algorithm based on definition of a seizure-specific wavelet (Seizlet) is presented. After designing the Seizlet, by forming cone of influence map of the EEG signal, four types of layouts are analytically designed that are called Seizure Modulus Maximas Patterns (SMMP). By mapping CorrEntropy Induced Metric (CIM) series, four structural features based on least square estimation of fitted non-tilt conic ellipse are extracted that are called CorrEntropy Ellipse Features (CEF)...
October 18, 2016: Journal of Neuroscience Methods
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