2012 LATEST:

World Association Of Neurotechnology

(Previously World Congress of Neurotechnology)

President: Prof M Trimble (UK)
Chairman: Prof T Herdegen (DE)

In association with

Most Recent Articles Published on Neurotechnology

These articles are generated by an RSS Feed from Pubmed.  WANeurotech is not responsible for the content of any external links which may be included in the feed.

Optimal level activity of matrix metalloproteinases is critical for adult visual plasticity in the healthy and stroke-affected brain.

Elife. 2015 Nov 26;4

Authors: Pielecka-Fortuna J, Kalogeraki E, Fortuna MG, Löwel S

The ability of the adult brain to undergo plastic changes is of particular interest in medicine, especially regarding recovery from injuries or improving learning and cognition. Matrix metalloproteinases (MMPs) have been associated with juvenile experience-dependent primary visual cortex (V1) plasticity, yet little is known about their role in this process in the adult V1. Activation of MMPs is a crucial step facilitating structural changes in a healthy brain; however, upon brain injury, upregulated MMPs promote the spread of a lesion and impair recovery. To clarify these seemingly opposing outcomes of MMPs-activation, we examined the effects of MMPs-inhibition on experience-induced plasticity in healthy and stoke-affected adult mice. In healthy animals, 7-day application of MMPs-inhibitor prevented visual plasticity. Additionally, treatment with MMPs-inhibitor once but not twice following stroke rescued plasticity, normally lost under these conditions. Our data imply that a fine balance of MMPs-activity is crucial for adult visual plasticity to occur.

PMID: 26609811 [PubMed - as supplied by publisher]

The modular and integrative functional architecture of the human brain.

Proc Natl Acad Sci U S A. 2015 Nov 23;

Authors: Bertolero MA, Yeo BT, D'Esposito M

Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules' processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author-topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network's modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules' functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain's modular yet integrated implementation of cognitive functions.

PMID: 26598686 [PubMed - as supplied by publisher]

The UK Biobank.

Brain. 2015 Dec;138(Pt 12):3463-5

Authors: Matthews PM, Sudlow C

PMID: 26598488 [PubMed - in process]

Related Articles

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study.

J Vis Exp. 2015;(105)

Authors: Roche AD, Vujaklija I, Amsüss S, Sturma A, Göbel P, Farina D, Aszmann OC

Advances in robotic systems have resulted in prostheses for the upper limb that can produce multifunctional movements. However, these sophisticated systems require upper limb amputees to learn complex control schemes. Humans have the ability to learn new movements through imitation and other learning strategies. This protocol describes a structured rehabilitation method, which includes imitation, repetition, and reinforcement learning, and aims to assess if this method can improve multifunctional prosthetic control. A left below elbow amputee, with 4 years of experience in prosthetic use, took part in this case study. The prosthesis used was a Michelangelo hand with wrist rotation, and the added features of wrist flexion and extension, which allowed more combinations of hand movements. The participant's Southampton Hand Assessment Procedure score improved from 58 to 71 following structured training. This suggests that a structured training protocol of imitation, repetition and reinforcement may have a role in learning to control a new prosthetic hand. A larger clinical study is however required to support these findings.

PMID: 26575620 [PubMed - as supplied by publisher]

Related Articles

Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex.

PLoS Comput Biol. 2015 Nov;11(11):e1004602

Authors: Schottdorf M, Keil W, Coppola D, White LE, Wolf F

The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1's intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models.

PMID: 26575467 [PubMed - as supplied by publisher]

Related Articles

Real-time modulated nanoparticle separation with an ultra-large dynamic range.

Lab Chip. 2015 Nov 17;

Authors: Zeming KK, Thakor NV, Zhang Y, Chen CH

Nanoparticles exhibit size-dependent properties which make size-selective purification of proteins, DNA or synthetic nanoparticles essential for bio-analytics, clinical medicine, nano-plasmonics and nano-material sciences. Current purification methods of centrifugation, column chromatography and continuous-flow techniques suffer from particle aggregation, multi-stage process, complex setups and necessary nanofabrication. These increase process costs and time, reduce efficiency and limit dynamic range. Here, we achieve an unprecedented real-time nanoparticle separation (51-1500 nm) using a large-pore (2 ?m) deterministic lateral displacement (DLD) device. No external force fields or nanofabrication are required. Instead, we investigated innate long-range electrostatic influences on nanoparticles within a fluid medium at different NaCl ionic concentrations. In this study we account for the electrostatic forces beyond Debye length and showed that they cannot be assumed as negligible especially for precise nanoparticle separation methods such as DLD. Our findings have enabled us to develop a model to simultaneously quantify and modulate the electrostatic force interactions between nanoparticle and micropore. By simply controlling buffer solutions, we achieve dynamic nanoparticle size separation on a single device with a rapid response time (<20 s) and an enlarged dynamic range (>1200%), outperforming standard benchtop centrifuge systems. This novel method and model combines device simplicity, isolation precision and dynamic flexibility, opening opportunities for high-throughput applications in nano-separation for industrial and biological applications.

PMID: 26575003 [PubMed - as supplied by publisher]

Progress of Flexible Electronics in Neural Interfacing - A Self-Adaptive Non-Invasive Neural Ribbon Electrode for Small Nerves Recording.

Adv Mater. 2015 Nov 16;

Authors: Xiang Z, Yen SC, Sheshadri S, Wang J, Lee S, Liu YH, Liao LD, Thakor NV, Lee C

A novel flexible neural ribbon electrode with a self-adaptive feature is successfully implemented for various small nerves recording. As a neural interface, the selective recording capability is characterized by having reliable signal acquisitions from the sciatic nerve and its branches such as the peroneal nerve, the tibial nerve, and the sural nerve.

PMID: 26568483 [PubMed - as supplied by publisher]

Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface.

Sci Transl Med. 2015 Nov 11;7(313):313ra179

Authors: Jarosiewicz B, Sarma AA, Bacher D, Masse NY, Simeral JD, Sorice B, Oakley EM, Blabe C, Pandarinath C, Gilja V, Cash SS, Eskandar EN, Friehs G, Henderson JM, Shenoy KV, Donoghue JP, Hochberg LR

Brain-computer interfaces (BCIs) promise to restore independence for people with severe motor disabilities by translating decoded neural activity directly into the control of a computer. However, recorded neural signals are not stationary (that is, can change over time), degrading the quality of decoding. Requiring users to pause what they are doing whenever signals change to perform decoder recalibration routines is time-consuming and impractical for everyday use of BCIs. We demonstrate that signal nonstationarity in an intracortical BCI can be mitigated automatically in software, enabling long periods (hours to days) of self-paced point-and-click typing by people with tetraplegia, without degradation in neural control. Three key innovations were included in our approach: tracking the statistics of the neural activity during self-timed pauses in neural control, velocity bias correction during neural control, and periodically recalibrating the decoder using data acquired during typing by mapping neural activity to movement intentions that are inferred retrospectively based on the user's self-selected targets. These methods, which can be extended to a variety of neurally controlled applications, advance the potential for intracortical BCIs to help restore independent communication and assistive device control for people with paralysis.

PMID: 26560357 [PubMed - in process]

Altered relaxin family receptors RXFP1 and RXFP3 in the neocortex of depressed Alzheimer's disease patients.

Psychopharmacology (Berl). 2015 Nov 6;

Authors: Lee JH, Koh SQ, Guadagna S, Francis PT, Esiri MM, Chen CP, Wong PT, Dawe GS, Lai MK

RATIONALE: The G-protein-coupled relaxin family receptors RXFP1 and RXFP3 are widely expressed in the cortex and are involved in stress responses and memory and emotional processing. However, the identification of these receptors in human cortex and their status in Alzheimer's disease (AD), which is characterized by both cognitive impairments and neuropsychiatric behaviours, have not been reported.
OBJECTIVES: In this study, we characterized RXFP receptors for immunoblotting and measured RXFP1 and RXFP3 immunoreactivities in the postmortem neocortex of AD patients longitudinally assessed for depressive symptoms.
METHODS: RXFP1 and RXFP3 antibodies were characterized by immunoblotting with lysates from transfected HEK cells and preadsorption with RXFP3 peptides. Also, postmortem neocortical tissues from behaviourally assessed AD and age-matched controls were processed for immunoblotting with RXFP1 and RXFP3 antibodies.
RESULTS: Compared to controls, putative RXFP1 immunoreactivity was reduced in parietal cortex of non-depressed AD patients but unchanged in depressed patients. Furthermore, putative RXFP3 immunoreactivity was increased only in depressed AD patients. RXFP1 levels in the parietal cortex also correlated with severity of depression symptoms. In contrast, RXFP1 and RXFP3 levels did not correlate with dementia severity or ?-amyloid burden.
CONCLUSION: Alterations of RXFP1 and RXFP3 may be neurochemical markers of depression in AD, and relaxin family receptors warrant further preclinical investigations as possible therapeutic targets for neuropsychiatric symptoms in dementia.

PMID: 26542729 [PubMed - as supplied by publisher]

A Spiking Neural Network in sEMG Feature Extraction.

Sensors (Basel). 2015;15(11):27894-27904

Authors: Lobov S, Mironov V, Kastalskiy I, Kazantsev V

We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control.

PMID: 26540060 [PubMed - as supplied by publisher]

Related Articles

Stress activates the nucleus incertus and modulates plasticity in the hippocampo-medial prefrontal cortical pathway.

Brain Res Bull. 2015 Oct 31;

Authors: Rajkumar R, Wu Y, Farooq U, Tan WH, Dawe GS

The nucleus incertus (NI) is a small brainstem cluster of neurons presumed to play a role in stress responses. We show that swim stress (normal water: 30min and cold water: 20min) and elevation stress robustly induced c-Fos expression in the NI and significantly suppressed long term potentiation (LTP) in the hippocampo-medial prefrontal cortical (HP-mPFC) pathway. To examine whether activation of CRF1 receptors in the NI plays a role in the suppression of HP-mPFC LTP, antalarmin, a specific CRF1 receptor antagonist, was infused directly into the NI either before presentation of (1) elevation stress or (2) high frequency stimulation. As predicted, the intra-NI infusion of antalarmin reversed the elevation stress-induced suppression of LTP in the HP-mPFC pathway. This short report suggests that the CRF1 receptor system in the NI contributes to stress-related impairment in the plasticity of HP-mPFC pathway. The findings suggest that the NI-HP-mPFC is a stress responsive circuit in the rodent brain.

PMID: 26529052 [PubMed - as supplied by publisher]

Related Articles

Benchmarking neuromorphic vision: lessons learnt from computer vision.

Front Neurosci. 2015;9:374

Authors: Tan C, Lallee S, Orchard G

Neuromorphic Vision sensors have improved greatly since the first silicon retina was presented almost three decades ago. They have recently matured to the point where they are commercially available and can be operated by laymen. However, despite improved availability of sensors, there remains a lack of good datasets, while algorithms for processing spike-based visual data are still in their infancy. On the other hand, frame-based computer vision algorithms are far more mature, thanks in part to widely accepted datasets which allow direct comparison between algorithms and encourage competition. We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer vision. Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation of Neuromorphic Vision benchmarks and challenges. We also discuss the unique challenges faced when benchmarking Neuromorphic Vision algorithms, particularly when attempting to provide direct comparison with frame-based computer vision.

PMID: 26528120 [PubMed]

Related Articles

Sociology of Low Expectations: Recalibration as Innovation Work in Biomedicine.

Sci Technol Human Values. 2015 Nov;40(6):998-1021

Authors: Gardner J, Samuel G, Williams C

Social scientists have drawn attention to the role of hype and optimistic visions of the future in providing momentum to biomedical innovation projects by encouraging innovation alliances. In this article, we show how less optimistic, uncertain, and modest visions of the future can also provide innovation projects with momentum. Scholars have highlighted the need for clinicians to carefully manage the expectations of their prospective patients. Using the example of a pioneering clinical team providing deep brain stimulation to children and young people with movement disorders, we show how clinicians confront this requirement by drawing on their professional knowledge and clinical expertise to construct visions of the future with their prospective patients; visions which are personalized, modest, and tainted with uncertainty. We refer to this vision-constructing work as recalibration, and we argue that recalibration enables clinicians to manage the tension between the highly optimistic and hyped visions of the future that surround novel biomedical interventions, and the exigencies of delivering those interventions in a clinical setting. Drawing on work from science and technology studies, we suggest that recalibration enrolls patients in an innovation alliance by creating a shared understanding of how the "effectiveness" of an innovation shall be judged.

PMID: 26527846 [PubMed - as supplied by publisher]

Related Articles

Evaluating more naturalistic outcome measures: A 1-year smartphone study in multiple sclerosis.

Neurol Neuroimmunol Neuroinflamm. 2015 Dec;2(6):e162

Authors: Bove R, White CC, Giovannoni G, Glanz B, Golubchikov V, Hujol J, Jennings C, Langdon D, Lee M, Legedza A, Paskavitz J, Prasad S, Richert J, Robbins A, Roberts S, Weiner H, Ramachandran R, Botfield M, De Jager PL

OBJECTIVE: In this cohort of individuals with and without multiple sclerosis (MS), we illustrate some of the novel approaches that smartphones provide to monitor patients with chronic neurologic disorders in their natural setting.
METHODS: Thirty-eight participant pairs (MS and cohabitant) aged 18-55 years participated in the study. Each participant received an Android HTC Sensation 4G smartphone containing a custom application suite of 19 tests capturing participant performance and patient-reported outcomes (PROs). Over 1 year, participants were prompted daily to complete one assigned test.
RESULTS: A total of 22 patients with MS and 17 cohabitants completed the entire study. Among patients with MS, low scores on PROs relating to mental and visual function were associated with dropout (p < 0.05). We illustrate several novel features of a smartphone platform. First, fluctuations in MS outcomes (e.g., fatigue) were assessed against an individual's ambient environment by linking responses to meteorological data. Second, both response accuracy and speed for the Ishihara color vision test were captured, highlighting the benefits of both active and passive data collection. Third, a new trait, a person-specific learning curve in neuropsychological testing, was identified using spline analysis. Finally, averaging repeated measures over the study yielded the most robust correlation matrix of the different outcome measures.
CONCLUSIONS: We report the feasibility of, and barriers to, deploying a smartphone platform to gather useful passive and active performance data at high frequency in an unstructured manner in the field. A smartphone platform may therefore enable large-scale naturalistic studies of patients with MS or other neurologic diseases.

PMID: 26516627 [PubMed]

Related Articles

Sensing Cardiac Electrical Activity With a Cardiac Myocyte--Targeted Optogenetic Voltage Indicator.

Circ Res. 2015 Aug 14;117(5):401-12

Authors: Chang Liao ML, de Boer TP, Mutoh H, Raad N, Richter C, Wagner E, Downie BR, Unsöld B, Arooj I, Streckfuss-Bömeke K, Döker S, Luther S, Guan K, Wagner S, Lehnart SE, Maier LS, Stühmer W, Wettwer E, van Veen T, Morlock MM, Knöpfel T, Zimmermann WH

RATIONALE: Monitoring and controlling cardiac myocyte activity with optogenetic tools offer exciting possibilities for fundamental and translational cardiovascular research. Genetically encoded voltage indicators may be particularly attractive for minimal invasive and repeated assessments of cardiac excitation from the cellular to the whole heart level.
OBJECTIVE: To test the hypothesis that cardiac myocyte-targeted voltage-sensitive fluorescence protein 2.3 (VSFP2.3) can be exploited as optogenetic tool for the monitoring of electric activity in isolated cardiac myocytes and the whole heart as well as function and maturity in induced pluripotent stem cell-derived cardiac myocytes.
METHODS AND RESULTS: We first generated mice with cardiac myocyte-restricted expression of VSFP2.3 and demonstrated distinct localization of VSFP2.3 at the t-tubulus/junctional sarcoplasmic reticulum microdomain without any signs for associated pathologies (assessed by echocardiography, RNA-sequencing, and patch clamping). Optically recorded VSFP2.3 signals correlated well with membrane voltage measured simultaneously by patch clamping. The use of VSFP2.3 for human action potential recordings was confirmed by simulation of immature and mature action potentials in murine VSFP2.3 cardiac myocytes. Optical cardiograms could be monitored in whole hearts ex vivo and minimally invasively in vivo via fiber optics at physiological heart rate (10 Hz) and under pacing-induced arrhythmia. Finally, we reprogrammed tail-tip fibroblasts from transgenic mice and used the VSFP2.3 sensor for benchmarking functional and structural maturation in induced pluripotent stem cell-derived cardiac myocytes.
CONCLUSIONS: We introduce a novel transgenic voltage-sensor model as a new method in cardiovascular research and provide proof of concept for its use in optogenetic sensing of physiological and pathological excitation in mature and immature cardiac myocytes in vitro and in vivo.

PMID: 26078285 [PubMed - indexed for MEDLINE]

Related Articles

Jaw tremor as a physiological biomarker of bruxism.

Clin Neurophysiol. 2015 Sep;126(9):1746-53

Authors: Laine CM, Yavuz ?U, D'Amico JM, Gorassini MA, Türker KS, Farina D

OBJECTIVE: To determine if sleep bruxism is associated with abnormal physiological tremor of the jaw during a visually-guided bite force control task.
METHODS: Healthy participants and patients with sleep bruxism were given visual feedback of their bite force and asked to trace triangular target trajectories (duration=20s, peak force <35% maximum voluntary force). Bite force control was quantified in terms of the power spectra of force fluctuations, masseter EMG activity, and force-to-EMG coherence.
RESULTS: Patients had greater jaw force tremor at ?8 Hz relative to controls, along with increased masseter EMG activity and force-to-EMG coherence in the same frequency range. Patients also showed lower force-to-EMG coherence at low frequencies (<3 Hz), but greater coherence at high frequencies (20-40 Hz). Finally, patients had greater 6-10 Hz force tremor during periods of descending vs. ascending force, while controls showed no difference in tremor with respect to force dynamics.
CONCLUSION: Patients with bruxism have abnormal jaw tremor when engaged in a visually-guided bite force task.
SIGNIFICANCE: Measurement of jaw tremor may aid in the detection/evaluation of bruxism. In light of previous literature, our results also suggest that bruxism is marked by abnormal or mishandled peripheral feedback from the teeth.

PMID: 25533275 [PubMed - indexed for MEDLINE]

A Gaze Independent Brain-Computer Interface Based on Visual Stimulation through Closed Eyelids.

Sci Rep. 2015;5:15890

Authors: Hwang HJ, Ferreria VY, Ulrich D, Kilic T, Chatziliadis X, Blankertz B, Treder M

A classical brain-computer interface (BCI) based on visual event-related potentials (ERPs) is of limited application value for paralyzed patients with severe oculomotor impairments. In this study, we introduce a novel gaze independent BCI paradigm that can be potentially used for such end-users because visual stimuli are administered on closed eyelids. The paradigm involved verbally presented questions with 3 possible answers. Online BCI experiments were conducted with twelve healthy subjects, where they selected one option by attending to one of three different visual stimuli. It was confirmed that typical cognitive ERPs can be evidently modulated by the attention of a target stimulus in eyes-closed and gaze independent condition, and further classified with high accuracy during online operation (74.58% ±?17.85 s.d.; chance level 33.33%), demonstrating the effectiveness of the proposed novel visual ERP paradigm. Also, stimulus-specific eye movements observed during stimulation were verified as reflex responses to light stimuli, and they did not contribute to classification. To the best of our knowledge, this study is the first to show the possibility of using a gaze independent visual ERP paradigm in an eyes-closed condition, thereby providing another communication option for severely locked-in patients suffering from complex ocular dysfunctions.

PMID: 26510583 [PubMed - in process]

Multi-Variate EEG Analysis as a Novel Tool to Examine Brain Responses to Naturalistic Music Stimuli.

PLoS One. 2015;10(10):e0141281

Authors: Sturm I, Dähne S, Blankertz B, Curio G

Note onsets in music are acoustic landmarks providing auditory cues that underlie the perception of more complex phenomena such as beat, rhythm, and meter. For naturalistic ongoing sounds a detailed view on the neural representation of onset structure is hard to obtain, since, typically, stimulus-related EEG signatures are derived by averaging a high number of identical stimulus presentations. Here, we propose a novel multivariate regression-based method extracting onset-related brain responses from the ongoing EEG. We analyse EEG recordings of nine subjects who passively listened to stimuli from various sound categories encompassing simple tone sequences, full-length romantic piano pieces and natural (non-music) soundscapes. The regression approach reduces the 61-channel EEG to one time course optimally reflecting note onsets. The neural signatures derived by this procedure indeed resemble canonical onset-related ERPs, such as the N1-P2 complex. This EEG projection was then utilized to determine the Cortico-Acoustic Correlation (CACor), a measure of synchronization between EEG signal and stimulus. We demonstrate that a significant CACor (i) can be detected in an individual listener's EEG of a single presentation of a full-length complex naturalistic music stimulus, and (ii) it co-varies with the stimuli's average magnitudes of sharpness, spectral centroid, and rhythmic complexity. In particular, the subset of stimuli eliciting a strong CACor also produces strongly coordinated tension ratings obtained from an independent listener group in a separate behavioral experiment. Thus musical features that lead to a marked physiological reflection of tone onsets also contribute to perceived tension in music.

PMID: 26510120 [PubMed - as supplied by publisher]

From phenotypic chaos to neurobiological order.

Nat Neurosci. 2015 Oct 27;18(11):1532-1534

Authors: Holmes AJ, Yeo BT

PMID: 26505560 [PubMed - as supplied by publisher]

Notched Environmental Sounds: A New Hearing Aid Supported Tinnitus Treatment Evaluated in 20 Patients.

Clin Otolaryngol. 2015 Oct 27;

Authors: Strauss DJ, Corona-Strauss FI, Seidler H, Haab L, Hannemann R

There is converging evidence in that the suppression of neural hyperactivity by lateral inhibition using tailor-made notch filtering is a promising approach to support tinnitus treatments. We evaluated a new notched environmental sound technology for the first time as hearing aid supported tinnitus treatment in 20 tinnitus patients. This technology employs a notch filter which abruptly filters out environmental sounds in behind-the-ear hearing aids at the tinnitus frequency. We evaluated this new approach using a double-blind pre-/post therapy evaluation in 20 tinnitus patients (10 controls, 10 patients with notched environmental sound) using a widely accepted psychometric instrument and objective electroencephalographic means. The subjective and objective results show that tailor-made notch filtering in hearing aids might support tinnitus treatments. This article is protected by copyright. All rights reserved.

PMID: 26505162 [PubMed - as supplied by publisher]

The Promise of Neurotechnology in Clinical Translational Science.

Clin Psychol Sci. 2015 Sep;3(5):797-815

Authors: White SW, Richey JA, Gracanin D, Bell MA, LaConte S, Coffman M, Trubanova A, Kim I

Neurotechnology is broadly defined as a set of devices used to understand neural processes and applications that can potentially facilitate the brain's ability to repair itself. In the past decade, an increasingly explicit understanding of basic biological mechanisms of brain-related illnesses has produced applications that allow a direct yet noninvasive method to index and manipulate the functioning of the human nervous system. Clinical scientists are poised to apply this technology to assess, treat, and better understand complex socioemotional processes that underlie many forms of psychopathology. In this review, we describe the potential benefits and hurdles, both technical and methodological, of neurotechnology in the context of clinical dysfunction. We also offer a framework for developing and evaluating neurotechnologies that is intended to expedite progress at the nexus of clinical science and neural interface designs by providing a comprehensive vocabulary to describe the necessary features of neurotechnology in the clinic.

PMID: 26504676 [PubMed - as supplied by publisher]

Reduced Hemispheric Asymmetry of Brain Anatomical Networks Is Linked to Schizophrenia: A Connectome Study.

Cereb Cortex. 2015 Oct 26;

Authors: Sun Y, Chen Y, Collinson SL, Bezerianos A, Sim K

Despite convergent evidence indicating a variety of regional abnormalities of hemispheric asymmetry in schizophrenia, patterns of wider neural network asymmetry remain to be determined. In this study, we investigated alterations in hemispheric white matter topology in schizophrenia and their association with clinical manifestations of the illness. Weighted hemispheric brain anatomical networks were constructed for each of 116 right-handed patients with schizophrenia and 66 matched healthy participants. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that although small-world properties were preserved in the hemispheric network, a significant hemispheric-independent deficit of global integration was found in schizophrenia. Furthermore, a significant group-by-hemisphere interaction was revealed in the characteristic path length and global efficiency, attributing to significantly reduced hemispheric asymmetry of global integration in patients compared with healthy controls. Specifically, we found reduced asymmetric nodal efficiency in several frontal regions and the hippocampus. Finally, the abnormal hemispheric asymmetry of brain anatomical network topology was associated with clinical features (duration of illness and psychotic psychopathology) in patients. Our findings provide new insights into lateralized nature of hemispheric dysconnectivity and highlight the potential for using brain network measures of hemispheric asymmetry as neural biomarkers for schizophrenia and its clinical features.

PMID: 26503264 [PubMed - as supplied by publisher]

Neurogenesis paradoxically decreases both pattern separation and memory interference.

Front Syst Neurosci. 2015;9:136

Authors: Finnegan R, Becker S

The hippocampus has been the focus of memory research for decades. While the functional role of this structure is not fully understood, it is widely recognized as being vital for rapid yet accurate encoding and retrieval of associative memories. Since the discovery of adult hippocampal neurogenesis in the dentate gyrus by Altman and Das in the 1960's, many theories and models have been put forward to explain the functional role it plays in learning and memory. These models postulate different ways in which new neurons are introduced into the dentate gyrus and their functional importance for learning and memory. Few if any previous models have incorporated the unique properties of young adult-born dentate granule cells and the developmental trajectory. In this paper, we propose a novel computational model of the dentate gyrus that incorporates the developmental trajectory of the adult-born dentate granule cells, including changes in synaptic plasticity, connectivity, excitability and lateral inhibition, using a modified version of the Restricted Boltzmann machine. Our results show superior performance on memory reconstruction tasks for both recent and distally learned items, when the unique characteristics of young dentate granule cells are taken into account. Even though the hyperexcitability of the young neurons generates more overlapping neural codes, reducing pattern separation, the unique properties of the young neurons nonetheless contribute to reducing retroactive and proactive interference, at both short and long time scales. The sparse connectivity is particularly important for generating distinct memory traces for highly overlapping patterns that are learned within the same context.

PMID: 26500511 [PubMed - as supplied by publisher]

Related Articles

Electromyographic adjustments during continuous and intermittent incremental fatiguing cycling.

Scand J Med Sci Sports. 2015 Oct 23;

Authors: Martinez-Valdes E, Guzman-Venegas RA, Silvestre RA, Macdonald JH, Falla D, Araneda OF, Haichelis D

We studied the sensitivity of electromyographic (EMG) variables to load and muscle fatigue during continuous and intermittent incremental cycling. Fifteen men attended three laboratory sessions. Visit 1: lactate threshold, peak power output, and VO2max . Visits 2 and 3: Continuous (more fatiguing) and intermittent (less fatiguing) incremental cycling protocols [20%, 40%, 60%, 80% and 100% of peak power output (PPO)]. During both protocols, multichannel EMG signals were recorded from vastus lateralis: muscle fiber conduction velocity (MFCV), instantaneous mean frequency (iMNF), and absolute and normalized root mean square (RMS) were analyzed. MFCV differed between protocols (P?<?0.001), and only increased consistently with power output during intermittent cycling. RMS parameters were similar between protocols, and increased linearly with power output. However, only normalized RMS was higher during the more fatiguing 100% PPO stage of the continuous protocol [continuous-intermittent mean difference (95% CI): 45.1 (8.5% to 81.7%)]. On the contrary, iMNF was insensitive to load changes and muscle fatigue (P?=?0.14). Despite similar power outputs, continuous and intermittent cycling influenced MFCV and normalized RMS differently. Only normalized RMS was sensitive to both increases in power output (in both protocols) and muscle fatigue, and thus is the most suitable EMG parameter to monitor changes in muscle activation during cycling.

PMID: 26493490 [PubMed - as supplied by publisher]

On testing neural network models.

Nat Rev Neurosci. 2015 Oct 21;

Authors: Yuste R

PMID: 26486185 [PubMed - as supplied by publisher]

Mapping entrained brain oscillations during transcranial alternating current stimulation (tACS).

Neuroimage. 2015 Oct 17;

Authors: Witkowski M, Cossio EG, Chander BS, Braun C, Birbaumer N, Robinson SE, Soekadar SR

Transcranial alternating current stimulation (tACS), a non-invasive and well-tolerated form of electric brain stimulation, can influence perception, memory, as well as motor and cognitive function. While the exact underlying neurophysiological mechanisms are unknown, the effects of tACS are mainly attributed to frequency-specific entrainment of endogenous brain oscillations in brain areas close to the stimulation electrodes, and modulation of spike timing dependent plasticity reflected in gamma band oscillatory responses. tACS-related electromagnetic stimulator artifacts, however, impede investigation of these neurophysiological mechanisms. Here we introduce a novel approach combining amplitude-modulated tACS during whole-head magnetoencephalography (MEG) allowing for artifact-free source reconstruction and precise mapping of entrained brain oscillations underneath the stimulator electrodes. Using this approach, we show that reliable reconstruction of neuromagnetic low- and high-frequency oscillations including high gamma band activity in stimulated cortical areas is feasible opening a new window to unveil the mechanisms underlying the effects of stimulation protocols that entrain brain oscillatory activity.

PMID: 26481671 [PubMed - as supplied by publisher]

A National Network of Neurotechnology Centers for the BRAIN Initiative.

Neuron. 2015 Oct 14;

Authors: Alivisatos AP, Chun M, Church GM, Greenspan RJ, Roukes ML, Yuste R

We propose the creation of a national network of neurotechnology centers to enhance and accelerate the BRAIN Initiative and optimally leverage the effort and creativity of individual laboratories involved in it. As "brain observatories," these centers could provide the critical interdisciplinary environment both for realizing ambitious and complex technologies and for providing individual investigators with access to them.

PMID: 26481036 [PubMed - as supplied by publisher]

Related Articles

Novel insights into the interplay between ventral neck muscles in individuals with whiplash-associated disorders.

Sci Rep. 2015;5:15289

Authors: Peterson G, Nilsson D, Trygg J, Falla D, Dedering Å, Wallman T, Peolsson A

Chronic whiplash-associated disorder (WAD) is common after whiplash injury, with considerable personal, social, and economic burden. Despite decades of research, factors responsible for continuing pain and disability are largely unknown, and diagnostic tools are lacking. Here, we report a novel model of mechanical ventral neck muscle function recorded from non-invasive, real-time, ultrasound measurements. We calculated the deformation area and deformation rate in 23 individuals with persistent WAD and compared them to 23 sex- and age-matched controls. Multivariate statistics were used to analyse interactions between ventral neck muscles, revealing different interplay between muscles in individuals with WAD and healthy controls. Although the cause and effect relation cannot be established from this data, for the first time, we reveal a novel method capable of detecting different neck muscle interplay in people with WAD. This non-invasive method stands to make a major breakthrough in the assessment and diagnosis of people following a whiplash trauma.

PMID: 26472599 [PubMed - in process]

Related Articles

Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data.

PLoS Comput Biol. 2015 Oct;11(10):e1004464

Authors: Soudry D, Keshri S, Stinson P, Oh MH, Iyengar G, Paninski L

Inferring connectivity in neuronal networks remains a key challenge in statistical neuroscience. The "common input" problem presents a major roadblock: it is difficult to reliably distinguish causal connections between pairs of observed neurons versus correlations induced by common input from unobserved neurons. Available techniques allow us to simultaneously record, with sufficient temporal resolution, only a small fraction of the network. Consequently, naive connectivity estimators that neglect these common input effects are highly biased. This work proposes a "shotgun" experimental design, in which we observe multiple sub-networks briefly, in a serial manner. Thus, while the full network cannot be observed simultaneously at any given time, we may be able to observe much larger subsets of the network over the course of the entire experiment, thus ameliorating the common input problem. Using a generalized linear model for a spiking recurrent neural network, we develop a scalable approximate expected loglikelihood-based Bayesian method to perform network inference given this type of data, in which only a small fraction of the network is observed in each time bin. We demonstrate in simulation that the shotgun experimental design can eliminate the biases induced by common input effects. Networks with thousands of neurons, in which only a small fraction of the neurons is observed in each time bin, can be quickly and accurately estimated, achieving orders of magnitude speed up over previous approaches.

PMID: 26465147 [PubMed - in process]

Related Articles

The new nanophysiology: regulation of ionic flow in neuronal subcompartments.

Nat Rev Neurosci. 2015 Oct 14;

Authors: Holcman D, Yuste R

Cable theory and the Goldman-Hodgkin-Huxley-Katz models for the propagation of ions and voltage within a neuron have provided a theoretical foundation for electrophysiology and been responsible for many cornerstone advances in neuroscience. However, these theories break down when they are applied to small neuronal compartments, such as dendritic spines, synaptic terminals or small neuronal processes, because they assume spatial and ionic homogeneity. Here we discuss a broader theory that uses the Poisson-Nernst-Planck (PNP) approximation and electrodiffusion to more accurately model the constraints that neuronal nanostructures place on electrical current flow. This extension of traditional cable theory could advance our understanding of the physiology of neuronal nanocompartments.

PMID: 26462753 [PubMed - as supplied by publisher]

Page Last Updated : 02-12-2013

Keep me updated

A value is required.
A value is required.
A value is required.Invalid format.
A value is required.

Your privacy is important to us



Website Design by: MGF.net