A thermal spike analysis of low energy ion activated surface processes

International Nuclear Information System (INIS)

Gilmore, G.M.; Haeri, A.; Sprague, J.A.

1989-01-01

This paper reports a thermal spike analysis utilized to predict the time evolution of energy propagation through a solid resulting from energetic particle impact. An analytical solution was developed that can predict the number of surface excitations such as desorption, diffusion or chemical reaction activated by an energetic particle. The analytical solution is limited to substrates at zero Kelvin and to materials with constant thermal diffusivities. These limitations were removed by developing a computer numerical integration of the propagation of the thermal spike through the solid and the subsequent activation of surface processes

Structural Inference in the Art of Violin Making.

Science.gov (United States)

Morse-Fortier, Leonard Joseph

The "secrets" of success of early Italian violins have long been sought. Among their many efforts to reproduce the results of Stradiveri, Guarneri, and Amati, luthiers have attempted to order and match natural resonant frequencies in the free violin plates. This tap-tone plate tuning technique is simply an eigenvalue extraction scheme. In the final stages of carving, the violin maker complements considerable intuitive knowledge of violin plate structure and of modal attributes with tap-tone frequency estimates to better understand plate structure and to inform decisions about plate carving and completeness. Examining the modal attributes of violin plates, this work develops and incorporates an impulse-response scheme for modal inference, measures resonant frequencies and modeshapes for a pair of violin plates, and presents modeshapes through a unique computer visualization scheme developed specifically for this purpose. The work explores, through simple examples questions of how plate modal attributes reflect underlying structure, and questions about the so -called evolution of modeshapes and frequencies through assembly of the violin. Separately, the work develops computer code for a carved, anisotropic, plate/shell finite element. Solutions are found to the static displacement and free-vibration eigenvalue problems for an orthotropic plate, and used to verify element accuracy. Finally, a violin back plate is modelled with full consideration of plate thickness and arching. Model estimates for modal attributes compare very well against experimentally acquired values. Finally, the modal synthesis technique is applied to predicting the modal attributes of the violin top plate with ribs attached from those of the top plate alone, and with an estimate of rib mass and stiffness. This last analysis serves to verify the modal synthesis method, and to quantify its limits of applicability in attempting to solve problems with severe structural modification. Conclusions

Wood densitometry in 17th and 18th century Dutch, German, Austrian and French violins, compared to classical Cremonese and modern violins.

Science.gov (United States)

Stoel, Berend C; Borman, Terry M; de Jongh, Ronald

2012-01-01

Classical violins produced by makers such as Antonio Stradivari and Guarneri del Gesu have long been considered the epitome of the luthier's art and the expressive tool of choice for the most celebrated violinists. It has been speculated these makers had access to wood that was unique in some way and that this was responsible for their acclaimed tonal characteristics. In an attempt to discern whether the above conjecture is true, we analyzed 17 modern and classical Dutch, German, Austrian and French violins by wood densitometry using computed tomography and correlated these results with our previous study of modern and Cremonese violins; in all studying 30 instruments of the violin family. In order to make this comparison possible we developed methods to cross calibrate results from different CT manufacturers using calibration wood pieces. We found no significant differences in median densities between modern and classical violins, or between classical violins from different origins. These results suggest that it is unlikely classical Cremonese makers had access to wood with significantly different wood density characteristics than that available to contemporaneous or modern makers.

Kabalevsky, Violin Concerto in C major, Op. 48 / Robert Layton

Index Scriptorium Estoniae

Layton, Robert

1991-01-01

Uuest heliplaadist "Kabalevsky, Violin Concerto in C major, Op. 48. Khachaturian, Violin Concerto in D minor, Lydia Mordkovitch (violin). Royal Scottish National Orchestra /Neeme Järvi". Chandos MC ABTD 1519; CD CHAN 8918 (53 minutes)

Soloist evaluations of six Old Italian and six new violins

Science.gov (United States)

Fritz, Claudia; Curtin, Joseph; Poitevineau, Jacques; Borsarello, Hugues; Wollman, Indiana; Tao, Fan-Chia; Ghasarossian, Thierry

2014-01-01

Many researchers have sought explanations for the purported tonal superiority of Old Italian violins by investigating varnish and wood properties, plate tuning systems, and the spectral balance of the radiated sound. Nevertheless, the fundamental premise of tonal superiority has been investigated scientifically only once very recently, and results showed a general preference for new violins and that players were unable to reliably distinguish new violins from old. The study was, however, relatively small in terms of the number of violins tested (six), the time allotted to each player (an hour), and the size of the test space (a hotel room). In this study, 10 renowned soloists each blind-tested six Old Italian violins (including five by Stradivari) and six new during two 75-min sessions—the first in a rehearsal room, the second in a 300-seat concert hall. When asked to choose a violin to replace their own for a hypothetical concert tour, 6 of the 10 soloists chose a new instrument. A single new violin was easily the most-preferred of the 12. On average, soloists rated their favorite new violins more highly than their favorite old for playability, articulation, and projection, and at least equal to old in terms of timbre. Soloists failed to distinguish new from old at better than chance levels. These results confirm and extend those of the earlier study and present a striking challenge to near-canonical beliefs about Old Italian violins. PMID:24711376

Soloist evaluations of six Old Italian and six new violins.

Science.gov (United States)

Fritz, Claudia; Curtin, Joseph; Poitevineau, Jacques; Borsarello, Hugues; Wollman, Indiana; Tao, Fan-Chia; Ghasarossian, Thierry

2014-05-20

Many researchers have sought explanations for the purported tonal superiority of Old Italian violins by investigating varnish and wood properties, plate tuning systems, and the spectral balance of the radiated sound. Nevertheless, the fundamental premise of tonal superiority has been investigated scientifically only once very recently, and results showed a general preference for new violins and that players were unable to reliably distinguish new violins from old. The study was, however, relatively small in terms of the number of violins tested (six), the time allotted to each player (an hour), and the size of the test space (a hotel room). In this study, 10 renowned soloists each blind-tested six Old Italian violins (including five by Stradivari) and six new during two 75-min sessions--the first in a rehearsal room, the second in a 300-seat concert hall. When asked to choose a violin to replace their own for a hypothetical concert tour, 6 of the 10 soloists chose a new instrument. A single new violin was easily the most-preferred of the 12. On average, soloists rated their favorite new violins more highly than their favorite old for playability, articulation, and projection, and at least equal to old in terms of timbre. Soloists failed to distinguish new from old at better than chance levels. These results confirm and extend those of the earlier study and present a striking challenge to near-canonical beliefs about Old Italian violins.

Wood densitometry in 17th and 18th century Dutch, German, Austrian and French violins, compared to classical Cremonese and modern violins.

Directory of Open Access Journals (Sweden)

Berend C Stoel

Full Text Available Classical violins produced by makers such as Antonio Stradivari and Guarneri del Gesu have long been considered the epitome of the luthier's art and the expressive tool of choice for the most celebrated violinists. It has been speculated these makers had access to wood that was unique in some way and that this was responsible for their acclaimed tonal characteristics. In an attempt to discern whether the above conjecture is true, we analyzed 17 modern and classical Dutch, German, Austrian and French violins by wood densitometry using computed tomography and correlated these results with our previous study of modern and Cremonese violins; in all studying 30 instruments of the violin family. In order to make this comparison possible we developed methods to cross calibrate results from different CT manufacturers using calibration wood pieces. We found no significant differences in median densities between modern and classical violins, or between classical violins from different origins. These results suggest that it is unlikely classical Cremonese makers had access to wood with significantly different wood density characteristics than that available to contemporaneous or modern makers.

Bioinformatics analysis of Brucella vaccines and vaccine targets using VIOLIN.

Science.gov (United States)

He, Yongqun; Xiang, Zuoshuang

2010-09-27

Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis, one of the commonest zoonotic diseases found worldwide in humans and a variety of animal species. While several animal vaccines are available, there is no effective and safe vaccine for prevention of brucellosis in humans. VIOLIN (http://www.violinet.org) is a web-based vaccine database and analysis system that curates, stores, and analyzes published data of commercialized vaccines, and vaccines in clinical trials or in research. VIOLIN contains information for 454 vaccines or vaccine candidates for 73 pathogens. VIOLIN also contains many bioinformatics tools for vaccine data analysis, data integration, and vaccine target prediction. To demonstrate the applicability of VIOLIN for vaccine research, VIOLIN was used for bioinformatics analysis of existing Brucella vaccines and prediction of new Brucella vaccine targets. VIOLIN contains many literature mining programs (e.g., Vaxmesh) that provide in-depth analysis of Brucella vaccine literature. As a result of manual literature curation, VIOLIN contains information for 38 Brucella vaccines or vaccine candidates, 14 protective Brucella antigens, and 68 host response studies to Brucella vaccines from 97 peer-reviewed articles. These Brucella vaccines are classified in the Vaccine Ontology (VO) system and used for different ontological applications. The web-based VIOLIN vaccine target prediction program Vaxign was used to predict new Brucella vaccine targets. Vaxign identified 14 outer membrane proteins that are conserved in six virulent strains from B. abortus, B. melitensis, and B. suis that are pathogenic in humans. Of the 14 membrane proteins, two proteins (Omp2b and Omp31-1) are not present in B. ovis, a Brucella species that is not pathogenic in humans. Brucella vaccine data stored in VIOLIN were compared and analyzed using the VIOLIN query system. Bioinformatics curation and ontological representation of Brucella vaccines

SIGNIFICANT INFLUENCES OF VIOLIN EXTRACURRICULAR ACHIEVEMENT TO EMOTIONAL INTELLIGENCE

Directory of Open Access Journals (Sweden)

Nafik

2014-06-01

Full Text Available This research aims to find out (1 whether there is an influence between student’s achievements of learning violin toward their emotional intelligence, (2 whether there is a correlation between student’s achievement of learning violin and their emotional intelligence, and (3 how much contribution of student’s achievement of learning violin to their emotional intelligence. It is a qualitative research which is defined as a research method based on positivism philosophy which is used to study particular sample and population. The sample and population are drawn randomly using research instruments to collect data, and the data are analyzed statistically. This aims to examine the hypothesis defined. The finding shows that there is a significant influence between student’s achievement of learning violin and their emotional intelligence about 76.1%, while the rest of it 23.9% is influenced by other factors which are not studied in this research. It proves that learning violin influences student’s emotional intelligence very much and emotional intelligence is influential in increasing student’s achievement. From the data, it shows that most of the students participating in violin extracurricular are able to increase their learning achievement.

Imitation, genetic lineages, and time influenced the morphological evolution of the violin.

Directory of Open Access Journals (Sweden)

Daniel H Chitwood

Full Text Available Violin design has been in flux since the production of the first instruments in 16th century Italy. Numerous innovations have improved the acoustical properties and playability of violins. Yet, other attributes of the violin affect its performance less, and with fewer constraints, are potentially more sensitive to historical vagaries unrelated to quality. Although the coarse shape of violins is integral to their design, details of the body outline can vary without significantly compromising sound quality. What can violin shapes tell us about their makers and history, including the degree that luthiers have influenced each other and the evolution of complex morphologies over time? Here, I provide an analysis of morphological evolution in the violin family, sampling the body shapes of over 9,000 instruments over 400 years of history. Specific shape attributes, which discriminate instruments produced by different luthiers, strongly correlate with historical time. Linear discriminant analysis reveals luthiers who likely copied the outlines of their instruments from others, which historical accounts corroborate. Clustering of averaged violin shapes places luthiers into four major groups, demonstrating a handful of discrete shapes predominate in most instruments. Violin shapes originating from multi-generational luthier families tend to cluster together, and familial origin is a significant explanatory factor of violin shape. Together, the analysis of four centuries of violin shapes demonstrates not only the influence of history and time leading to the modern violin, but widespread imitation and the transmission of design by human relatedness.

Imitation, genetic lineages, and time influenced the morphological evolution of the violin.

Science.gov (United States)

Chitwood, Daniel H

2014-01-01

Violin design has been in flux since the production of the first instruments in 16th century Italy. Numerous innovations have improved the acoustical properties and playability of violins. Yet, other attributes of the violin affect its performance less, and with fewer constraints, are potentially more sensitive to historical vagaries unrelated to quality. Although the coarse shape of violins is integral to their design, details of the body outline can vary without significantly compromising sound quality. What can violin shapes tell us about their makers and history, including the degree that luthiers have influenced each other and the evolution of complex morphologies over time? Here, I provide an analysis of morphological evolution in the violin family, sampling the body shapes of over 9,000 instruments over 400 years of history. Specific shape attributes, which discriminate instruments produced by different luthiers, strongly correlate with historical time. Linear discriminant analysis reveals luthiers who likely copied the outlines of their instruments from others, which historical accounts corroborate. Clustering of averaged violin shapes places luthiers into four major groups, demonstrating a handful of discrete shapes predominate in most instruments. Violin shapes originating from multi-generational luthier families tend to cluster together, and familial origin is a significant explanatory factor of violin shape. Together, the analysis of four centuries of violin shapes demonstrates not only the influence of history and time leading to the modern violin, but widespread imitation and the transmission of design by human relatedness.

Updates on the web-based VIOLIN vaccine database and analysis system.

Science.gov (United States)

He, Yongqun; Racz, Rebecca; Sayers, Samantha; Lin, Yu; Todd, Thomas; Hur, Junguk; Li, Xinna; Patel, Mukti; Zhao, Boyang; Chung, Monica; Ostrow, Joseph; Sylora, Andrew; Dungarani, Priya; Ulysse, Guerlain; Kochhar, Kanika; Vidri, Boris; Strait, Kelsey; Jourdian, George W; Xiang, Zuoshuang

2014-01-01

The integrative Vaccine Investigation and Online Information Network (VIOLIN) vaccine research database and analysis system (http://www.violinet.org) curates, stores, analyses and integrates various vaccine-associated research data. Since its first publication in NAR in 2008, significant updates have been made. Starting from 211 vaccines annotated at the end of 2007, VIOLIN now includes over 3240 vaccines for 192 infectious diseases and eight noninfectious diseases (e.g. cancers and allergies). Under the umbrella of VIOLIN, >10 relatively independent programs are developed. For example, Protegen stores over 800 protective antigens experimentally proven valid for vaccine development. VirmugenDB annotated over 200 'virmugens', a term coined by us to represent those virulence factor genes that can be mutated to generate successful live attenuated vaccines. Specific patterns were identified from the genes collected in Protegen and VirmugenDB. VIOLIN also includes Vaxign, the first web-based vaccine candidate prediction program based on reverse vaccinology. VIOLIN collects and analyzes different vaccine components including vaccine adjuvants (Vaxjo) and DNA vaccine plasmids (DNAVaxDB). VIOLIN includes licensed human vaccines (Huvax) and veterinary vaccines (Vevax). The Vaccine Ontology is applied to standardize and integrate various data in VIOLIN. VIOLIN also hosts the Ontology of Vaccine Adverse Events (OVAE) that logically represents adverse events associated with licensed human vaccines.

A Research Focused on Improving Vocalisation Level on Violin Education

Science.gov (United States)

Parasiz, Gökalp

2018-01-01

The research aimed to improve vocalisation levels of music teacher's candidates on performance works for violin education moving from difficulties faced by prospective teachers. At the same time, it was aimed to provide new perspectives to violin educators. Study group was composed of six 3rd grade students studying violin education in a State…

The role of vibrato in the perception of violin quality

Science.gov (United States)

Gough, Colin E.

2003-10-01

The role of vibrato in the characterization of violin tone will be considered from both a physical acoustics and perceptual viewpoint. Musical examples of individual waveforms from violins of widely different qualities will be used to demonstrate the importance of vibrato and other temporal fluctuations in the recognition of the violin as a specific musical instrument and, by inference, of its perceived tonal quality also. Dynamic physical models will be introduced to describe the waveforms of sounds produced by the bowed string when vibrato is used. The sound produced by an individual instrument will be shown to be critically dependent on both the positions and the Q values of the acoustically important resonances excited, in addition to random noise generated by the bowing action. It will be argued that the temporal fluctuations in the sound of a violin played with vibrato are just as important as the temporal fluctuations associated with the very strong frequency-dependence of the directivity of the violin. Weinreich has emphasized the importance of the latter effect in any realistic reproduction of the sound of a violin.

Violin mode amplitude glitch monitor for the presence of excess noise on the monolithic silica suspensions of GEO 600

Energy Technology Data Exchange (ETDEWEB)

Sorazu, B; Strain, K A; Heng, I S; Kumar, R, E-mail: b.sorazu@physics.gla.ac.u [Department of Physics and Astronomy, University of Glasgow, University Avenue, Glasgow G12 8QQ (United Kingdom)

2010-08-07

Non-Gaussian features of data from gravitational wave detectors are of interest as unpredictable 'glitches' limit the sensitivity of searches for many kinds of signal. We consider events due to non-random excitations of the test masses and their suspension fibres. These events could, for example, be related to acoustic emissions in the fibres due to the presence and propagation of cracks or another type of structural perturbation, and they would generate excess noise above the Gaussian background, which matches the level expected due to thermal noise. We look for excess noise in the fundamental violin modes of the monolithic silica suspension fibres of GEO 600. We describe the algorithm used to monitor the violin mode amplitude for glitches, present our results and consider how these may be applied to advanced detectors. The conclusion of our analysis is that no excess noise above what was considered to be thermal noise was observed for several days of h(t) data analysed at the frequency of the selected violin modes.

Violin mode amplitude glitch monitor for the presence of excess noise on the monolithic silica suspensions of GEO 600

International Nuclear Information System (INIS)

Sorazu, B; Strain, K A; Heng, I S; Kumar, R

2010-01-01

Non-Gaussian features of data from gravitational wave detectors are of interest as unpredictable 'glitches' limit the sensitivity of searches for many kinds of signal. We consider events due to non-random excitations of the test masses and their suspension fibres. These events could, for example, be related to acoustic emissions in the fibres due to the presence and propagation of cracks or another type of structural perturbation, and they would generate excess noise above the Gaussian background, which matches the level expected due to thermal noise. We look for excess noise in the fundamental violin modes of the monolithic silica suspension fibres of GEO 600. We describe the algorithm used to monitor the violin mode amplitude for glitches, present our results and consider how these may be applied to advanced detectors. The conclusion of our analysis is that no excess noise above what was considered to be thermal noise was observed for several days of h(t) data analysed at the frequency of the selected violin modes.

Violin mode amplitude glitch monitor for the presence of excess noise on the monolithic silica suspensions of GEO 600

Science.gov (United States)

Sorazu, B.; Strain, K. A.; Heng, I. S.; Kumar, R.

2010-08-01

Non-Gaussian features of data from gravitational wave detectors are of interest as unpredictable 'glitches' limit the sensitivity of searches for many kinds of signal. We consider events due to non-random excitations of the test masses and their suspension fibres. These events could, for example, be related to acoustic emissions in the fibres due to the presence and propagation of cracks or another type of structural perturbation, and they would generate excess noise above the Gaussian background, which matches the level expected due to thermal noise. We look for excess noise in the fundamental violin modes of the monolithic silica suspension fibres of GEO 600. We describe the algorithm used to monitor the violin mode amplitude for glitches, present our results and consider how these may be applied to advanced detectors. The conclusion of our analysis is that no excess noise above what was considered to be thermal noise was observed for several days of h(t) data analysed at the frequency of the selected violin modes.

From Bows to Sound-Chests: Tracing the Ancestry of the Violin

Directory of Open Access Journals (Sweden)

Janelle R. Finley

2016-04-01

Full Text Available The ancestry of the violin is a subject that has been studied, researched, debated, and written about in great detail. However, despite all of the research and study, the ancestry of the violin is still not certain. This paper presents two schools of thought that propose different theories as to how the ancestry of the violin should be determined and what instruments should be included in the ancestry of the violin. The first school of thought proposes that the violin’s ancestry should be traced through the bow. The second theory proposes that the violin’s ancestry should be traced through the sound-chest of the violin. This paper also presents the different arguments for and against each theory, the importance of this topic, and the paper’s position on this topic. Research for this paper was accomplished through the use of scholarly books on the subject of the history of the violin.

Chin force in violin playing.

Science.gov (United States)

Obata, Satoshi; Kinoshita, Hiroshi

2012-06-01

Force generated between the left mandible of violinists and the chinrest of the violin was examined using a force-sensing chinrest developed in this study. A strain-gauge force sensor was built, and it was fixed between the violin's top plate and a chin cup. Fifteen professional/amateur violinists held the violin statically, played musical scales with different sound properties and sounding techniques, as well as an excerpt from a Max Bruch concerto. Peak and mean forces were evaluated for each task. In a separate experiment, lateral movement of the lower teeth due to different levels of voluntary chin force exertion was measured. Static holding forces observed were 15 and 22 N with and without the help of the left hand, respectively. Peak force increased from 16 N at soft dynamics to 20 N at strong dynamics during scales. The force further increased to 29 N with the use of vibrato technique and 35 N during shifts. Tempo and hand position did not affect the force. Playing a Bruch concerto induced a mean peak force of 52 N, ranging from 31 to 82 N among the violinists. The developed force-sensing chinrest could accurately record the generated chin force. Typical chin force to stabilize the violin during ordinary musical performance was less than 30 N, but it could momentarily exceed 50 N when technically demanding musical pieces were performed. The lateral shift of the mandible was fairly small (<0.4 mm) even with high chin-force exertion, possibly due to clenching of the molars.

A comparison of wood density between classical Cremonese and modern violins.

Directory of Open Access Journals (Sweden)

Berend C Stoel

Full Text Available Classical violins created by Cremonese masters, such as Antonio Stradivari and Giuseppe Guarneri Del Gesu, have become the benchmark to which the sound of all violins are compared in terms of their abilities of expressiveness and projection. By general consensus, no luthier since that time has been able to replicate the sound quality of these classical instruments. The vibration and sound radiation characteristics of a violin are determined by an instrument's geometry and the material properties of the wood. New test methods allow the non-destructive examination of one of the key material properties, the wood density, at the growth ring level of detail. The densities of five classical and eight modern violins were compared, using computed tomography and specially developed image-processing software. No significant differences were found between the median densities of the modern and the antique violins, however the density difference between wood grains of early and late growth was significantly smaller in the classical Cremonese violins compared with modern violins, in both the top (Spruce and back (Maple plates (p = 0.028 and 0.008, respectively. The mean density differential (SE of the top plates of the modern and classical violins was 274 (26.6 and 183 (11.7 gram/liter. For the back plates, the values were 128 (2.6 and 115 (2.0 gram/liter. These differences in density differentials may reflect similar changes in stiffness distributions, which could directly impact vibrational efficacy or indirectly modify sound radiation via altered damping characteristics. Either of these mechanisms may help explain the acoustical differences between the classical and modern violins.

Towards a Computer Assisted Violin Teaching Aid

OpenAIRE

Fitzgerald, Derry; Charles, Jane; Coyle, Eugene

2004-01-01

This paper presents a possible approach for developing a violin teaching aid based on violin pedagogy, sound analysis and comparison of beginner and good player recordings. This teaching aid is targeted at students who have difficulty listening attentively to the sounds they produce. It aims to draw their attention to the sound of a fault, offer correction and to train the user's ear to actively listen.

Modeling thermal spike driven reactions at low temperature and application to zirconium carbide radiation damage

Science.gov (United States)

Ulmer, Christopher J.; Motta, Arthur T.

2017-11-01

The development of TEM-visible damage in materials under irradiation at cryogenic temperatures cannot be explained using classical rate theory modeling with thermally activated reactions since at low temperatures thermal reaction rates are too low. Although point defect mobility approaches zero at low temperature, the thermal spikes induced by displacement cascades enable some atom mobility as it cools. In this work a model is developed to calculate "athermal" reaction rates from the atomic mobility within the irradiation-induced thermal spikes, including both displacement cascades and electronic stopping. The athermal reaction rates are added to a simple rate theory cluster dynamics model to allow for the simulation of microstructure evolution during irradiation at cryogenic temperatures. The rate theory model is applied to in-situ irradiation of ZrC and compares well at cryogenic temperatures. The results show that the addition of the thermal spike model makes it possible to rationalize microstructure evolution in the low temperature regime.

VIOLIN: vaccine investigation and online information network.

Science.gov (United States)

Xiang, Zuoshuang; Todd, Thomas; Ku, Kim P; Kovacic, Bethany L; Larson, Charles B; Chen, Fang; Hodges, Andrew P; Tian, Yuying; Olenzek, Elizabeth A; Zhao, Boyang; Colby, Lesley A; Rush, Howard G; Gilsdorf, Janet R; Jourdian, George W; He, Yongqun

2008-01-01

Vaccines are among the most efficacious and cost-effective tools for reducing morbidity and mortality caused by infectious diseases. The vaccine investigation and online information network (VIOLIN) is a web-based central resource, allowing easy curation, comparison and analysis of vaccine-related research data across various human pathogens (e.g. Haemophilus influenzae, human immunodeficiency virus (HIV) and Plasmodium falciparum) of medical importance and across humans, other natural hosts and laboratory animals. Vaccine-related peer-reviewed literature data have been downloaded into the database from PubMed and are searchable through various literature search programs. Vaccine data are also annotated, edited and submitted to the database through a web-based interactive system that integrates efficient computational literature mining and accurate manual curation. Curated information includes general microbial pathogenesis and host protective immunity, vaccine preparation and characteristics, stimulated host responses after vaccination and protection efficacy after challenge. Vaccine-related pathogen and host genes are also annotated and available for searching through customized BLAST programs. All VIOLIN data are available for download in an eXtensible Markup Language (XML)-based data exchange format. VIOLIN is expected to become a centralized source of vaccine information and to provide investigators in basic and clinical sciences with curated data and bioinformatics tools for vaccine research and development. VIOLIN is publicly available at http://www.violinet.org.

A real-time acoustic violin emulator for electric violins

OpenAIRE

GAYDECKI , Patrick

2012-01-01

International audience; A stand-alone electronic device has been developed that processes the raw electrical output produced by an electric violin, generating an output signal which, when fed to an amplifier, produces a sound that approximates closely the timbre of an acoustic or wooden instrument. The system comprises a high-impedance preamplifier, a 24-bit sigma delta codec and a digital signal processor (DSP) operating at 600 million multiplications-accumulations per second (MMACs). The de...

The Hutchins-Schelleng Violin Octet After 50 Years

Science.gov (United States)

Burns, Kevin; Maybury, Mark

Scientifically speaking, the Hutchins-Schelleng violin octet is the most interesting of all the bowed string instruments. We refer specifically to those instruments resulting from the first application of physics to the design of bowed string instruments, viz., the scientific resonance scaling process developed by John Schelleng to dimension the violin - certainly the most “successful” and mature bowed string instrument - to cover a 3½ octave range.

Dr. Franjo (Franz) Kresnik (1869-1943): a physician and a violin maker.

Science.gov (United States)

Skrobonja, Ante; Muzur, Amir

2007-01-01

Dr. Franjo (Franz) Kresnik (born Wien 1869 - died Rijeka 1943) was an excellent physician and a Central European intellectual, a bohemian mind whose two loves in life made him very special. His passions were medicine and violin making. Most of his life was spent in Susak (now a part of Rijeka, Croatia), where he worked, played music and studied the art of making stringed instruments. He visited Cremona on several occasions and studied a number of violins, drawings and tools made and used by old masters. For his profound knowledge of Cremonese violin making the Italians dubbed him "Uomo che legge violini" (The Man Who Can Read Violins). In his workshop he made fifty-two violins, two violas, two cellos and a string quartet. Some of these instruments are still played in Europe and America. The remaining violins and possessions (tools, manuscripts, drawings, literature and countless diplomas and certificates) have been kept in a memorial room at the Maritime and History Museum of the Croatian Littoral in Rijeka. In addition, a street near the Faculty of Medicine in Rijeka is named after Franjo Kresnik.

A Study on Developing Learning Strategies in Violin Education

Science.gov (United States)

Afacan, Senol; Cilden, Seyda

2018-01-01

This study was conducted for the purpose of developing a valid and reliable learning strategies scale for students receiving violin education in Departments of Music at Fine Arts High Schools. The scale was applied to 391 violin students receiving education in the 11th and 12th grades in Departments of Music at Fine Arts High Schools in the…

Perceptual studies of violin body damping and vibrato.

Science.gov (United States)

Fritz, Claudia; Woodhouse, Jim; Cheng, Felicia P-H; Cross, Ian; Blackwell, Alan F; Moore, Brian C J

2010-01-01

This work explored how the perception of violin notes is influenced by the magnitude of the applied vibrato and by the level of damping of the violin resonance modes. Damping influences the "peakiness" of the frequency response, and vibrato interacts with this peakiness by producing fluctuations in spectral content as well as in frequency and amplitude. Initially, it was shown that thresholds for detecting a change in vibrato amplitude were independent of body damping, and thresholds for detecting a change in body damping were independent of vibrato amplitude. A study of perceptual similarity using triadic comparison showed that vibrato amplitude and damping were largely perceived as independent dimensions. A series of listening tests was conducted employing synthesized, recorded, or live performance to probe perceptual responses in terms of "liveliness" and preference. The results do not support the conclusion that liveliness results from the combination of the use of vibrato and a "peaky" violin response. Judgments based on listening to single notes showed inconsistent patterns for liveliness, while preferences were highest for damping that was slightly less than for a reference (real) violin. In contrast, judgments by players based on many notes showed preference for damping close to the reference value.

Perceptual thresholds for detecting modifications applied to the acoustical properties of a violin.

Science.gov (United States)

Fritz, Claudia; Cross, Ian; Moore, Brian C J; Woodhouse, Jim

2007-12-01

This study is the first step in the psychoacoustic exploration of perceptual differences between the sounds of different violins. A method was used which enabled the same performance to be replayed on different "virtual violins," so that the relationships between acoustical characteristics of violins and perceived qualities could be explored. Recordings of real performances were made using a bridge-mounted force transducer, giving an accurate representation of the signal from the violin string. These were then played through filters corresponding to the admittance curves of different violins. Initially, limits of listener performance in detecting changes in acoustical characteristics were characterized. These consisted of shifts in frequency or increases in amplitude of single modes or frequency bands that have been proposed previously to be significant in the perception of violin sound quality. Thresholds were significantly lower for musically trained than for nontrained subjects but were not significantly affected by the violin used as a baseline. Thresholds for the musicians typically ranged from 3 to 6 dB for amplitude changes and 1.5%-20% for frequency changes. Interpretation of the results using excitation patterns showed that thresholds for the best subjects were quite well predicted by a multichannel model based on optimal processing.

Investigating the role of auditory and tactile modalities in violin quality evaluation.

Science.gov (United States)

Wollman, Indiana; Fritz, Claudia; Poitevineau, Jacques; McAdams, Stephen

2014-01-01

The role of auditory and tactile modalities involved in violin playing and evaluation was investigated in an experiment employing a blind violin evaluation task under different conditions: i) normal playing conditions, ii) playing with auditory masking, and iii) playing with vibrotactile masking. Under each condition, 20 violinists evaluated five violins according to criteria related to violin playing and sound characteristics and rated their overall quality and relative preference. Results show that both auditory and vibrotactile feedback are important in the violinists' evaluations but that their relative importance depends on the violinist, the violin and the type of evaluation (different criteria ratings or preference). In this way, the overall quality ratings were found to be accurately predicted by the rating criteria, which also proved to be perceptually relevant to violinists, but were poorly correlated with the preference ratings; this suggests that the two types of ratings (overall quality vs preference) may stem from different decision-making strategies. Furthermore, the experimental design confirmed that violinists agree more on the importance of criteria in their overall evaluation than on their actual ratings for different violins. In particular, greater agreement was found on the importance of criteria related to the sound of the violin. Nevertheless, this study reveals that there are fundamental differences in the way players interpret and evaluate each criterion, which may explain why correlating physical properties with perceptual properties has been challenging so far in the field of musical acoustics.

Nodal line optimization and its application to violin top plate design

Science.gov (United States)

Yu, Yonggyun; Jang, In Gwun; Kim, In Kyum; Kwak, Byung Man

2010-10-01

In the literature, most problems of structural vibration have been formulated to adjust a specific natural frequency: for example, to maximize the first natural frequency. In musical instruments like a violin; however, mode shapes are equally important because they are related to sound quality in the way that natural frequencies are related to the octave. The shapes of nodal lines, which represent the natural mode shapes, are generally known to have a unique feature for good violins. Among the few studies on mode shape optimization, one typical study addresses the optimization of nodal point location for reducing vibration in a one-dimensional beam structure. However, nodal line optimization, which is required in violin plate design, has not yet been considered. In this paper, the central idea of controlling the shape of the nodal lines is proposed and then applied to violin top plate design. Finite element model for a violin top plate was constructed using shell elements. Then, optimization was performed to minimize the square sum of the displacement of selected nodes located along the target nodal lines by varying the thicknesses of the top plate. We conducted nodal line optimization for the second and the fifth modes together at the same time, and the results showed that the nodal lines obtained match well with the target nodal lines. The information on plate thickness distribution from nodal line optimization would be valuable for tailored trimming of a violin top plate for the given performances.

A simple violin oscillator

Science.gov (United States)

Jones, R. T.

1976-01-01

For acoustic tests the violin is driven laterally at the bridge by a small speaker of the type commonly found in pocket transistor radios. An audio oscillator excites the tone which is picked up by a sound level meter. Gross patterns of vibration modes are obtained by the Chladni method.

Violin Pedagogy and the Physics of the Bowed String

Science.gov (United States)

McLeod, Alexander Rhodes

The paper describes the mechanics of violin tone production using non-specialist language, in order to present a scientific understanding of tone production accessible to a broad readership. As well as offering an objective understanding of tone production, this model provides a powerful tool for analyzing the technique of string playing. The interaction between the bow and the string is quite complex. Literature reviewed for this study reveals that scientific investigations have provided important insights into the mechanics of string playing, offering explanations for factors which both contribute to and limit the range of tone colours and dynamics that stringed instruments can produce. Also examined in the literature review are significant works of twentieth century violin pedagogy exploring tone production on the violin, based on the practical experience of generations of teachers and performers. Hermann von Helmholtz described the stick-slip cycle which drives the string in 1863, which replaced earlier ideas about the vibration of violin strings. Later, scientists such as John Schelleng and Lothar Cremer were able to demonstrate how the mechanics of the bow-string interaction can create different tone colours. Recent research by Anders Askenfelt, Knut Guettler, and Erwin Schoonderwaldt have continued to refine earlier research in this area. The writings of Lucien Capet, Leopold Auer, Carl Flesch, Paul Rolland, Kato Havas, Ivan Galamian, and Simon Fischer are examined and analyzed. Each author describes a different approach to tone production on the violin, representing a different understanding of the underlying mechanism. Analyzing these writings within the context of a scientific understanding of tone production makes it possible to compare these approaches more consistently, and to synthesize different concepts drawn from the diverse sources evaluated.

Nucleation of 2D nanoislands in surface thermal spikes from swift heavy ions

International Nuclear Information System (INIS)

Volkov, Alexander E.; Sorokin, Michael V.

2003-01-01

Possibility of nucleation of nanoislands in the surface thermal spikes caused by swift heavy ions or intense femptosecond laser pulses is investigated. Nanoislands may occur when the characteristic nucleation time becomes shorter than that cooling down of the thermal spot. The values of system parameters favorable for the nucleation are estimated

Some Intermediate-Level Violin Concertos.

Science.gov (United States)

Abramson, Michael

1997-01-01

Contends that many violin students attempt difficult concertos before they are technically or musically prepared. Identifies a variety of concertos at the intermediate and advanced intermediate-level for students to study and master before attempting the advanced works by Bach and Mozart. Includes concertos by Vivaldi, Leclair, Viotti, Haydn,…

Laser vibrometry measurements of vibration and sound fields of a bowed violin

Science.gov (United States)

Gren, Per; Tatar, Kourosh; Granström, Jan; Molin, N.-E.; Jansson, Erik V.

2006-04-01

Laser vibrometry measurements on a bowed violin are performed. A rotating disc apparatus, acting as a violin bow, is developed. It produces a continuous, long, repeatable, multi-frequency sound from the instrument that imitates the real bow-string interaction for a 'very long bow'. What mainly differs is that the back and forward motion of the real bow is replaced by the rotating motion with constant velocity of the disc and constant bowing force (bowing pressure). This procedure is repeatable. It is long lasting and allows laser vibrometry techniques to be used, which measure forced vibrations by bowing at all excited frequencies simultaneously. A chain of interacting parts of the played violin is studied: the string, the bridge and the plates as well as the emitted sound field. A description of the mechanics and the sound production of the bowed violin is given, i.e. the production chain from the bowed string to the produced tone.

Does the thermal spike affect low energy ion-induced interfacial mixing?

International Nuclear Information System (INIS)

Suele, P.; Menyhard, M.; Nordlund, K.

2003-01-01

Molecular dynamics simulations have been used to obtain the three-dimensional distribution of interfacial mixing and cascade defects in Ti/Pt multilayer system due to single 1 keV Ar + impact at grazing angle of incidence. The Ti/Pt system was chosen because of its relatively high heat of mixing in the binary alloy and therefore a suitable candidate for testing the effect of heat of mixing on ion-beam mixing. However, the calculated mixing profile is not sensitive to the heat of mixing. Therefore the thermal spike model of mixing is not fully supported under these irradiation conditions. Instead we found that the majority of mixing occurs after the thermal spike during the relaxation process. These conclusions are supported by liquid, vacancy as well as adatom analysis. The interfacial mixing is in various aspects anomalous in this system: the time evolution of mixing is leading to a phase delay for Ti mixing, and Pt exhibits an unexpected double peaked mixing evolution. The reasons to these effects are discussed

Method for measuring violin sound radiation based on bowed glissandi and its application to sound synthesis.

Science.gov (United States)

Perez Carrillo, Alfonso; Bonada, Jordi; Patynen, Jukka; Valimaki, Vesa

2011-08-01

This work presents a method for measuring and computing violin-body directional frequency responses, which are used for violin sound synthesis. The approach is based on a frame-weighted deconvolution of excitation and response signals. The excitation, consisting of bowed glissandi, is measured with piezoelectric transducers built into the bridge. Radiation responses are recorded in an anechoic chamber with multiple microphones placed at different angles around the violin. The proposed deconvolution algorithm computes impulse responses that, when convolved with any source signal (captured with the same transducer), produce a highly realistic violin sound very similar to that of a microphone recording. The use of motion sensors allows for tracking violin movements. Combining this information with the directional responses and using a dynamic convolution algorithm, helps to improve the listening experience by incorporating the violinist motion effect in stereo.

The thermal-spike model description of the ion-irradiated polyimide

International Nuclear Information System (INIS)

Sun Youmei; Zhang Chonghong; Zhu Zhiyong; Wang Zhiguang; Jin Yunfan; Liu Jie; Wang Ying

2004-01-01

To describe the role of electronic energy loss (dE/dX) e for chemical modification of polyimide (PI), multi-layer stacks (corresponding to different dE/dX) were irradiated by different swift heavy ions (1.158 GeV Fe 56 and 1.755 GeV Xe 136 ) under vacuum and at room temperature. Chemical changes of modified PI films were studied by Fourier transform infrared (FTIR) spectroscopy. The chain disruption rate of PI was investigated in the fluence range from 1 x 10 11 to 6 x 10 12 ions/cm 2 and a wider energy stopping power range (2.2-5.1 keV/nm for Fe 56 ions and 8.6-11.5 keV/nm for Xe 136 ions). Alkyne formation was observed over the electronic energy loss range of interest. By applying the saturated track model assumption (the damage process only occur in a cylinder of area σ), the mean degradation and alkyne formation radii in tracks were induced for Fe and Xe ion irradiation, respectively. The results were validated by the thermal-spike model. The analysis of the irradiated PI films shows that the predictions of the thermal-spike model of Szenes are in qualitative agreement with the curve shape of experimental results

Dependence of sound characteristics on the bowing position in a violin

Science.gov (United States)

Roh, YuJi; Kim, Young H.

2014-12-01

A quantitative analysis of violin sounds produced for different bowing positions over the full length of a violin string has been carried out. An automated bowing machine was employed in order to keep the bowing parameters constant. A 3-dimensional profile of the frequency spectrum was introduced in order to characterize the violin's sound. We found that the fundamental frequency did not change for different bowing positions, whereas the frequencies of the higher harmonics were different. Bowing the string at 30 mm from the bridge produced musical sounds. The middle of the string was confirmed to be a dead zone, as reported in previous works. In addition, the quarter position was also found to be a dead zone. Bowing the string 90 mm from the bridge dominantly produces a fundamental frequency of 864 Hz and its harmonics.

Measurements of effective noise temperature in fused silica fiber violin modes

Energy Technology Data Exchange (ETDEWEB)

Bilenko, I.A.; Lourie, S.L

2002-11-25

The results of measurements of the effective noise temperature in fused silica fiber violin modes are presented. In these measurements the fibers were stressed and value of the effective noise temperature was obtained by direct observation of oscillations in the fundamental violin modes of several samples. Measured values indicate that effective noise temperature does not exceed the room temperature significantly. This result is important for the design of the advanced gravitational wave antennae.

Observation of Motion of Bowed Strings and Resonant Strings in Violin Performances

Science.gov (United States)

Matsutani, Akihiro

2013-10-01

The motion of a bowed string and a resonant string of a violin were simultaneously observed for the first time. The results of the direct observation of string motion in double stops and harmonics are also presented. The importance of the resonance was experimentally demonstrated from these observations. It is suggested that players should take account of the resonance and ideal Helmholtz motion in violin performances.

REGARDING A METHOD OF PERFORMING ON THE VIOLIN IN TRADITIONAL MUSIC

Directory of Open Access Journals (Sweden)

MIRONENCO IAROSLAV

2016-06-01

Full Text Available Following a field study in the village of Lozova, Străşeni, aimed at identifying the variants of a folk song recorded by I. Mironenko from an informant living in the village of Thamaha, North Caucasus — Russia, a village inhabited by Moldovans, the musicologist discovered a fiddler who demonstrated him a specific process of executation on the violin. This method is representative of an advanced level of interpretation on the violin.

DEVELOPMENT TRENDS OF THE CONCERTO FOR VIOLIN AND ORCHESTRA IN THE EUROPEAN MUSIC AND ITS EVOLUTION IN UKRAINE

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LAPTEVA ANNA

2017-12-01

Full Text Available The paper is devoted to the evolution of the solo concerto for violin and orchestra genre in the European music since its origination till the present time. Tracing the genre development trends in almost all European countries, the author comes to the conclusion of the existence of certain regularities in the violin concerto development that are common for various national musical cultures. It enables us to reveal both individual genre peculiarities of the violin concerto and the specific features of the national cultures. Particular attention is paid to the development of the violin concerto in Ukraine.

THE INTONATIONAL ORGANIZATION IN THE VIOLIN CONCERTO MOMENTS

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CIOBANU GHENADIE

2017-06-01

Full Text Available The article examines the intonational organization of the Concerto for Violin and Symphony Orchestra „Moments”. A perspective of the analysis of the intonational system of the Concerto refers to highlighting the traditional narrative types, such as the meditative monolog, dialogue, motion etc. that are closely related to the concept and imagistic world of the work. Likewise, the personification of the soloist instrument in an instrumental concerto is determined mostly by the intonation system used by the composer in his work. The concretization of the intonations, their combination and integration into an actual system of meanings forms the musical work issues. At the same time, the intonation system reflects the ideas, images and sound collisions of the work. The „new tone” is an objectivity and constitutes the expression of a new melodic-harmonic organizational order of the sound material. The intonation of a musical work consists of the combination of specific properties generated from compositional practices. In the contemporary history of music there is a variety of individual systems of organizing the soundpitch. These specific intonation systems, however, are based on some common principles of organization. The personification of solo instrument in terms of intonation becomes an important task for a composer in the genre of concerto. A concern for the composers in the concertos for violin and orchestra refers to the methods influencing the violin intonation sonority in terms of the orchestral context in which the solo instrument is placed.

Evolution of the violin: The law of effect in action.

Science.gov (United States)

Wasserman, Edward A; Cullen, Patrick

2016-01-01

As is true for most other human inventions, the origin of the violin is unknown. What is known is that this popular and versatile instrument has notably changed over the course of several hundred years. At issue is whether those evolutionary changes in the construction of the violin are the result of premeditated, intelligent design or whether they arose through a trial-and-error process. Recent scientific evidence favors the latter account. Our perspective piece puts these recent empirical findings into a comprehensive selectionist framework. According to this view, the many things we do and make--like violins--arise from a process of variation and selection which accords with the law of effect. Contrary to popular opinion, there is neither mystique nor romance in this process; it is as fundamental and ubiquitous as the law of natural selection. As with the law of natural selection in the evolution of organisms, there is staunch resistance to the role of the law of effect in the evolution of human inventions. We conclude our piece by considering several objections to our perspective. (c) 2016 APA, all rights reserved).

Observable Flow Experience in a Two-Year-Old Japanese Child's Violin Playing

Science.gov (United States)

Akutsu, Taichi

2018-01-01

This study investigated the flow experience of Jiro, a 2-year-old Japanese boy, regarding his violin playing in a social context. In this study, Jiro's violin playing was videotaped at home and during musical sessions for young children and families, guided by the author as a violinist-teacher-researcher. The method adopted a single case study…

First results from the 'Violin-Mode' tests on an advanced LIGO suspension at MIT

International Nuclear Information System (INIS)

Lockerbie, N A; Tokmakov, K V; Carbone, L; Shapiro, B; Bell, A; Strain, K A

2011-01-01

This paper describes the first results from 'Violin-Mode' measurements made on the four suspension fibres of a fully suspended 40 kg test mass. These measurements were made at the LIGO lab, Gravitational Wave Observatory test facility, at MIT. Here, an aluminium-alloy (dummy) test mass, simulating an advanced LIGO (Laser Interferometer Gravitational Wave Observatory) test mass/mirror, had been suspended in air from a test suspension by four fused-silica suspension fibres, each measuring 400 μm in diameter x 600 mm long. Violin-Mode measurements were made on these highly tensioned fibres by retrofitting a prototype system of four novel shadow sensors to the test suspension, one per fibre, these sensors having, collectively, a displacement sensitivity of (6.9 ± 1.3) x 10 -11 m (rms) Hz -1/2 , at 500 Hz, over a measuring span of ±0.1 mm. Violin-Mode fundamental resonances were detected in all four fibres: with frequencies ∼ 485 Hz when the test mass was supported lightly from below, and at ∼500 Hz when it was fully suspended. In the latter case the Violin-Mode detection took place whilst the test mass, together with its suspension fibres, was undergoing relatively large-amplitude 'pendulum-mode' motion, at ∼0.6 Hz. This motion was measured to have a peak-peak amplitude at one of the suspension fibres of up to ∼140 μm (35 μm, rms) the shadow sensors each having subsidiary outputs for monitoring such low-frequency, large amplitude, motion. Under fully suspended conditions, a calibrated Violin-Mode 'free-oscillation' amplitude of 430 ± 20 picometres, rms, was measured at 500.875 Hz, in the same suspension fibre which was found to be undergoing, simultaneously, the ∼140 μm peak-peak motion. Over the bandwidth monitored (dc to 3.2 kHz), Violin-Mode harmonics up to the sixth were recorded in an evoked response. It was concluded that the prototype system had demonstrated amply its practical viability as a detector of Violin-Mode resonances in the test

Thermal Management of Transient Power Spikes in Electronics - Phase Change Energy Storage or Copper Heat Sinks?

OpenAIRE

Krishnan, S.; Garimella, S V

2004-01-01

A transient thermal analysis is performed to investigate thermal control of power semiconductors using phase change materials, and to compare the performance of this approach to that of copper heat sinks. Both the melting of the phase change material under a transient power spike input, as well as the resolidification process, are considered. Phase change materials of different kinds (paraffin waxes and metallic alloys) are considered, with and without the use of thermal conductivity enhancer...

COMPOSITION PECULIARITIES IN THE SONATA C-MOLL FOR VIOLIN AND PIANO BY KONSTANTIN ROMANOV

Directory of Open Access Journals (Sweden)

ŢIRCUNOVA SVETLANA

2015-06-01

Full Text Available The author analyzes the Sonata for Violin and Piano by Konstantin Romanov written in Chisinau in 1920s. This is one of the first works known in national music in the genre of sonata for violin, written on the territory of the Republic of Moldova. The work is considered in terms of its musical form built in the classical traditions.

The evolution of air resonance power efficiency in the violin and its ancestors.

Science.gov (United States)

Nia, Hadi T; Jain, Ankita D; Liu, Yuming; Alam, Mohammad-Reza; Barnas, Roman; Makris, Nicholas C

2015-03-08

The fact that acoustic radiation from a violin at air-cavity resonance is monopolar and can be determined by pure volume change is used to help explain related aspects of violin design evolution. By determining the acoustic conductance of arbitrarily shaped sound holes, it is found that air flow at the perimeter rather than the broader sound-hole area dominates acoustic conductance, and coupling between compressible air within the violin and its elastic structure lowers the Helmholtz resonance frequency from that found for a corresponding rigid instrument by roughly a semitone. As a result of the former, it is found that as sound-hole geometry of the violin's ancestors slowly evolved over centuries from simple circles to complex f-holes, the ratio of inefficient, acoustically inactive to total sound-hole area was decimated, roughly doubling air-resonance power efficiency. F-hole length then slowly increased by roughly 30% across two centuries in the renowned workshops of Amati, Stradivari and Guarneri, favouring instruments with higher air-resonance power, through a corresponding power increase of roughly 60%. By evolution-rate analysis, these changes are found to be consistent with mutations arising within the range of accidental replication fluctuations from craftsmanship limitations with subsequent selection favouring instruments with higher air-resonance power.

Investigation of Near-Surface Defects Induced by Spike Rapid Thermal Annealing in c-SILICON Solar Cells

Science.gov (United States)

Liu, Guodong; Ren, Pan; Zhang, Dayong; Wang, Weiping; Li, Jianfeng

2016-01-01

The defects induced by a spike rapid thermal annealing (RTA) process in crystalline silicon (c-Si) solar cells were investigated by the photoluminescence (PL) technique and the transmission electron microscopy (TEM), respectively. Dislocation defects were found to form in the near-surface junction region of the monocrystalline Si solar cell after a spike RTA process was performed at 1100∘C. Photo J-V characteristics were measured on the Si solar cell before and after the spike RTA treatments to reveal the effects of defects on the Si cell performances. In addition, the Silvaco device simulation program was used to study the effects of defects density on the cell performances by fitting the experimental data of RTA-treated cells. The results demonstrate that there was an obvious degradation in the Si solar cell performances when the defect density after the spike RTA treatment was above 1×1013cm-3.

Structural acoustics model of the violin radiativity profile.

Science.gov (United States)

Bissinger, George

2008-12-01

Violin radiativity profiles are dominated by the Helmholtz-like A0 cavity mode ( approximately 280 Hz), first corpus bending modes B1(-) and B1(+) ( approximately 500 Hz), and BH and bridge-filter peaks ( approximately 2.4 kHz and approximately 3.5 kHz, respectively), with falloff above approximately 4 kHz. The B1 modes-dependent on two low-lying free-plate modes--are proposed to excite A0 via coupling to B1-driven in-phase f-hole volume flows. VIOCADEAS data show that A0 radiativity increases primarily as A0-B1(-) frequency difference decreases, consistent with Meinel's 1937 experiment for too-thick/too-thin plate thicknesses, plus sound post removal and violin octet baritone results. The vibration-->acoustic energy filter, F(RAD), computed from shape-material-independent radiation and total damping, peaks at the critical frequency f(crit), estimated from a free-plate mode by analogy to flat-plate bending. Experimentally, f(crit) decreased as this plate mode (and B1(+)) frequency increased. Simulations show that increasing plate thicknesses lowers f(crit), reduces F(RAD), and moves the spectral balance toward lower frequencies. Incorporating string-->corpus filters (including bridge versus bridge-island impedances) provides a model for overall violin radiativity. This model-with B1 and A0-B1 couplings, and f(crit) (computed from a free-plate mode important to B1) strongly affecting the lowest and highest parts of the radiativity profile-substantiates prior empirical B1--sound quality linkages.

Assessment of sensorimotor cortical representation asymmetries and motor skills in violin players.

Science.gov (United States)

Schwenkreis, Peter; El Tom, Susan; Ragert, Patrick; Pleger, Burkhard; Tegenthoff, Martin; Dinse, Hubert R

2007-12-01

As a model for use-dependent plasticity, the brains of professional musicians have been extensively studied to examine structural and functional adaptation to unique requirements of skilled performance. Here we provide a combination of data on motor performance and hand representation in the primary motor and somatosensory cortex of professional violin players, with the aim of assessing possible behavioural consequences of sensorimotor cortical asymmetries. We studied 15 healthy right-handed professional violin players and 35 healthy nonmusician controls. Motor and somatosensory cortex asymmetry was assessed by recording the motor output map after transcranial magnetic stimulation from a small hand muscle, and by dipole source localization of somatosensory evoked potentials after electrical stimulation of the median and ulnar nerves. Motor performance was examined using a series of standardized motor tasks covering different aspects of hand function. Violin players showed a significant right-larger-than-left asymmetry of the motor and somatosensory cortex, whereas nonmusician controls showed no significant interhemispheric difference. The amount of asymmetry in the motor and somatosensory cortices of musicians was significantly correlated. At the behavioural level, motor performance did not significantly differ between musicians and nonmusicians. The results support a use-dependent enlargement of the left hand representation in the sensorimotor cortex of violin players. However, these cortical asymmetries were not paralleled by accompanying altered asymmetries at a behavioural level, suggesting that the reorganisation might be task-specific and does not lead to improved motor abilities in general.

First results from the ‘Violin-Mode’ tests on an advanced LIGO suspension at MIT

Science.gov (United States)

Lockerbie, N. A.; Carbone, L.; Shapiro, B.; Tokmakov, K. V.; Bell, A.; Strain, K. A.

2011-12-01

This paper describes the first results from ‘Violin-Mode’ measurements made on the four suspension fibres of a fully suspended 40 kg test mass. These measurements were made at the LIGO lab, Gravitational Wave Observatory test facility, at MIT. Here, an aluminium-alloy (dummy) test mass, simulating an advanced LIGO (Laser Interferometer Gravitational Wave Observatory) test mass/mirror, had been suspended in air from a test suspension by four fused-silica suspension fibres, each measuring 400 µm in diameter × 600 mm long. Violin-Mode measurements were made on these highly tensioned fibres by retrofitting a prototype system of four novel shadow sensors to the test suspension, one per fibre, these sensors having, collectively, a displacement sensitivity of (6.9 ± 1.3) × 10-11 m (rms) Hz-1/2, at 500 Hz, over a measuring span of ±0.1 mm. Violin-Mode fundamental resonances were detected in all four fibres: with frequencies ˜ 485 Hz when the test mass was supported lightly from below, and at ˜500 Hz when it was fully suspended. In the latter case the Violin-Mode detection took place whilst the test mass, together with its suspension fibres, was undergoing relatively large-amplitude ‘pendulum-mode’ motion, at ˜0.6 Hz. This motion was measured to have a peak-peak amplitude at one of the suspension fibres of up to ˜140 µm (35 µm, rms)—the shadow sensors each having subsidiary outputs for monitoring such low-frequency, large amplitude, motion. Under fully suspended conditions, a calibrated Violin-Mode ‘free-oscillation’ amplitude of 430 ± 20 picometres, rms, was measured at 500.875 Hz, in the same suspension fibre which was found to be undergoing, simultaneously, the ˜140 µm peak-peak motion. Over the bandwidth monitored (dc to 3.2 kHz), Violin-Mode harmonics up to the sixth were recorded in an evoked response. It was concluded that the prototype system had demonstrated amply its practical viability as a detector of Violin-Mode resonances in the

Studying friction while playing the violin: exploring the stick-slip phenomenon.

Science.gov (United States)

Casado, Santiago

2017-01-01

Controlling the stick-slip friction phenomenon is of major importance for many familiar situations. This effect originates from the periodic rupture of junctions created between two rubbing surfaces due to the increasing shear stress at the interface. It is ultimately responsible for the behavior of many braking systems, earthquakes, and unpleasant squeaky sounds caused by the scratching of two surfaces. In the case of a musical bow-stringed instrument, stick-slip is controlled in order to provide well-tuned notes at different intensities. A trained ear is able to distinguish slight sound variations caused by small friction differences. Hence, a violin can be regarded as a perfect benchmark to explore the stick-slip effect at the mesoscale. Two violin bow hairs were studied, a natural horse tail used in a professional philharmonic orchestra, and a synthetic one used with a violin for beginners. Atomic force microscopy characterization revealed clear differences when comparing the surfaces of both bow hairs, suggesting that a structure having peaks and a roughness similar to that of the string to which both bow hairs rubbed permits a better control of the stick-slip phenomenon.

Studying friction while playing the violin: exploring the stick–slip phenomenon

Directory of Open Access Journals (Sweden)

Santiago Casado

2017-01-01

Full Text Available Controlling the stick–slip friction phenomenon is of major importance for many familiar situations. This effect originates from the periodic rupture of junctions created between two rubbing surfaces due to the increasing shear stress at the interface. It is ultimately responsible for the behavior of many braking systems, earthquakes, and unpleasant squeaky sounds caused by the scratching of two surfaces. In the case of a musical bow-stringed instrument, stick–slip is controlled in order to provide well-tuned notes at different intensities. A trained ear is able to distinguish slight sound variations caused by small friction differences. Hence, a violin can be regarded as a perfect benchmark to explore the stick–slip effect at the mesoscale. Two violin bow hairs were studied, a natural horse tail used in a professional philharmonic orchestra, and a synthetic one used with a violin for beginners. Atomic force microscopy characterization revealed clear differences when comparing the surfaces of both bow hairs, suggesting that a structure having peaks and a roughness similar to that of the string to which both bow hairs rubbed permits a better control of the stick–slip phenomenon.

Perceived Articulation Uniformity between Trumpet and Violin Performances

Science.gov (United States)

Cooper, Shelly C.; Hamann, Donald L.

2010-01-01

Directors strive for a unified sound throughout their wind and orchestra ensembles. Articulation affects sound uniformity among winds and strings. This baseline study examined whether a trumpet player could better match a violin player's articulation, as perceived by participants listening to a recording of two performances, when: (a) performing…

Enhacing spectral sintesis techniques with performance gestures using the violin as a case study

OpenAIRE

Pérez Carrillo, Alfonso Antonio

2009-01-01

In this work we investigate new sound synthesis techniques for imitating musical instruments using the violin as a case study. It is a multidisciplinary research, covering several fields such as spectral modeling, machine learning, analysis of musical gestures or musical acoustics. It addresses sound production with a very empirical approach, based on the analysis of performance gestures as well as on the measurement of acoustical properties of the violin. Based on the characteristics of the ...

Assessment of cervical range of motion, cervical core strength and scapular dyskinesia in violin players.

Science.gov (United States)

Tawde, Pooja; Dabadghav, Rachana; Bedekar, Nilima; Shyam, Ashok; Sancheti, Parag

2016-12-01

Playing the violin can lead to asymmetric postures which can affect the cervical range of motion, cervical core strength and scapular stability. The objective of the study was to assess the cervical range of motion, cervical core strength and scapular dyskinesia in violin players and non-players of the same age group. An inclinometer was used to assess the cervical range of motion, pressure biofeedback was used to assess cervical core strength and scapular dyskinesia was also assessed in 30 professional violin players (18-40 years) compared with 30 age-matched non-players. Analysis was done using an unpaired t test. Significant change was seen with respect to extension (p = 0.051), cervical core strength (p = 0.005), right (Rt) superior angle 0° (p = 0.004), Rt superior angle 45° (p = 0.015) and Rt inferior angle 90° (p = 0.013). This study shows a significant difference in extension range of motion and cervical core strength of violin players. Also, there was scapular dyskinesia seen at 0° and 45° right-side superior angle of the scapula and 90° right-side inferior angle of the scapula.

Double spike methodology for uranium determination by thermal ionisation mass spectrometry: separation and purification of 234U

International Nuclear Information System (INIS)

Shah, P.M.; Saxena, M.K.; Sanjai Kumar; Aggarwal, S.K.; Jain, H.C.

1995-01-01

With an objective to prepare double spike of 233 U+ 234 U for determination of uranium concentration by Isotopic Dilution Thermal Ionisation Mass Spectrometry (ID-TIMS), 234 U was separated and purified from aged 238 Pu sample (15 years old) using several ion exchange and solvent extraction procedures. Final product containing 95% and 5% alpha activities of 234 and 238 Pu, respectively, which translates into 99.998 atom% of 234 U and 0.002 atom% of 238 Pu was found suitable for double spike. (author). 1 ref

Reverse engineering the structural and acoustic behavior of a stradivari violin

Science.gov (United States)

Pyrkosz, Michael

There is a tremendous amount of mystery that surrounds the instruments of Antonio Stradivari. There have been many studies done in the past, but no one completely understands exactly how he made his instruments, or why they are still considered the best in the world. This project is designed to develop an engineering model of one of Stradivari's violins that will accurately simulate the structural and acoustic behavior of the instrument. It also hopes to shine some light on what makes the instruments of Stradivari unique when compared to other violins. It will focus on geometry and material properties, utilizing several modern engineering tools, including CT scanning, experimental modal analysis, finite element analysis, correlation techniques, and acoustic synthesis.

Is the thermal-spike model consistent with experimentally determined electron temperature?

International Nuclear Information System (INIS)

Ajryan, Eh.A.; Fedorov, A.V.; Kostenko, B.F.

2000-01-01

Carbon K-Auger electron spectra from amorphous carbon foils induced by fast heavy ions are theoretically investigated. The high-energy tail of the Auger structure showing a clear projectile charge dependence is analyzed within the thermal-spike model framework as well as in the frame of another model taking into account some kinetic features of the process. A poor comparison results between theoretically and experimentally determined temperatures are suggested to be due to an improper account of double electron excitations or due to shake-up processes which leave the system in a more energetic initial state than a statically screened core hole

Special Issue: Every picture tells a story: Pupil representations of learning the violin

Directory of Open Access Journals (Sweden)

Andrea Creech

2006-06-01

Full Text Available Abstract: The influence on learning outcomes of interpersonal interaction amongst teachers, pupils and parents is the subject of an inquiry that took this researcher on a voyage from the qualitative to the quantitative side of the “methodological divide”, and back again. This paper presents findings from first phase of the research, which included a quantitative survey to examine how learning and teaching experience for violin pupils was influenced by the interpersonal dynamics of responsiveness and control, within pupilparent and pupil-teacher relationships. As part of the survey pupils were asked to draw pictures of their violin lessons. It was thought that the pictures might reveal pupils’ perceptions of their experience of learning an instrument and that the pictures would add depth to the quantitative scales that measured interpersonal mechanisms and pupil outcomes. The pictures were subjected to content analysis and coded accordingly. These codes were matched with pupil artists’ scores for control and responsiveness, as well as with their scores for outcomes that included enjoyment of music, personal satisfaction, self esteem, self efficacy, friendship, motivation and musical attainment. Analysis of variance was computed in order to test the null hypotheses that a pupil-teacher-parent interpersonal behaviour (control and responsiveness was not represented in their pictures and b pupil outcomes were not reflected in their depictions of violin lessons. This paper presents the results of this analysis, thus addressing the question of whether the pictures could be accepted as telling a credible and coherent story about pupils’ perceptions of learning the violin.

Liquid Metal Machine Triggered Violin-Like Wire Oscillator.

Science.gov (United States)

Yuan, Bin; Wang, Lei; Yang, Xiaohu; Ding, Yujie; Tan, Sicong; Yi, Liting; He, Zhizhu; Liu, Jing

2016-10-01

The first ever oscillation phenomenon of a copper wire embraced inside a self-powered liquid metal machine is discovered. When contacting a copper wire to liquid metal machine, it would be swallowed inside and then reciprocally moves back and forth, just like a violin bow. Such oscillation could be easily regulated by touching a steel needle on the liquid metal surface.

Fiddler's neck: Chin rest-associated irritant contact dermatitis and allergic contact dermatitis in a violin player.

Science.gov (United States)

Caero, Jennifer E; Cohen, Philip R

2012-09-15

Fiddler's neck refers to an irritant contact dermatitis on the submandibular neck of violin and viola players and an allergic contact dermatitis to nickel from the bracket attaching the violin to the chin rest on the violinist's supraclavicular neck. A 26-year-old woman developed submandibular and supraclavicular left neck lesions corresponding to the locations of the chin rest and bracket that was attached to her violin that held it against her neck when she played. Substitution of a composite chin rest, which did not contain nickel, and the short-term application of a low potency topical corticosteroid cream, resulted in complete resolution of the allergic contact dermatitis supraclavicular neck lesion. The irritant contact dermatitis submandibular neck lesion persisted. In conclusion, violin players are predisposed to developing irritant contact dermatitis or allergic contact dermatitis from the chin rest. We respectfully suggest that the submandibular neck lesions from contact with the chin rest be referred to as 'fiddler's neck - type 1,' whereas the supraclavicular neck lesions resulting from contact of the bracket holding the chin rest in place be called 'fiddler's neck - type 2.' A composite chin rest should be considered in patients with a preceding history of allergic contact dermatitis to nickel.

A thermal spike model of the amorphization of insulators by high-energy heavy-ion irradiation

International Nuclear Information System (INIS)

Szenes, G.

1995-01-01

Recently, experimental data on magnetic insulators irradiated with swift heavy ions were analyzed by a new thermal spike model and good quantitative agreement was achieved. Analytical expressions were given for the evolution of latent tracks with the electronic stopping power S e of bombarding ions and a relation between the thermal properties of the target and the threshold value of S e was proposed and proved experimentally. In the present paper, after a brief review of the model, the temperature dependence of latent track formation is discussed and the predictions of the model are compared with the available experimental results

Annealing effect of thermal spike in MgO thin film prepared by cathodic vacuum arc deposition

Energy Technology Data Exchange (ETDEWEB)

Zhu, Daoyun, E-mail: zhudy@gdut.edu.cn [Experiment Teaching Department, Guangdong University of Technology, Guangzhou 510006 (China); State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275 (China); Zhao, Shoubai [School of Physics and Electronic Engineering, Guangzhou University, Guangzhou 510400 (China); Zheng, Changxi; Chen, Dihu [State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275 (China); He, Zhenhui, E-mail: stshzh@mail.sysu.edu.cn [State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics and Engineering, Sun Yat-sen University, Guangzhou 510275 (China)

2013-12-16

MgO films were prepared by using pulsed cathodic vacuum arc deposition technique. The substrate bias voltage was in the range of −150 to −750 V. Film structure was investigated by X-ray diffraction (XRD). The annealing effect of thermal spike produced by the impacting of energetic ions was analyzed. The calculated results showed that the lifetime of a thermal spike generated by an energetic ion with the energy of 150 eV was less than one picosecond and it was sufficient to allow Mg{sup 2+} or O{sup 2-} to move one bond length to satisfy the intrinsic stress relief in the affected volume. The MgO(200) lattice spacings of the films deposited at different bias voltages were all larger than the ideal value of 2.1056 Å. As the bias amplitude increased the lattice spacing decreased, which indicated that the compressive stress in the film was partially relieved with increasing impacting ion energy. The stress relief also could be reflected from the film orientation with bias voltage. The biaxial elastic modulus for MgO(100), MgO(110) and MgO(111) planes were calculated and they were M{sub (100)} = 199 GPa, M{sub (110)} = 335 GPa and M{sub (111)} = 340 GPa, respectively. The M values indicated that the preferred orientation will be MgO(200) due to the minimum energy configuration when the lattice strain was large. It was confirmed by the XRD results in our experiments. - Highlights: • MgO thin films with preferred orientation were obtained by CVAD technique. • Annealing effect of a thermal spike in MgO film was discussed. • Lattice spacing of MgO film decreased with the increase of bias voltage. • Film preferred orientation changed from (200) to (220) as the bias voltage increased.

Comparison of electromyographic activity and range of neck motion in violin students with and without neck pain during playing.

Science.gov (United States)

Park, Kyue-nam; Kwon, Oh-yun; Ha, Sung-min; Kim, Su-jung; Choi, Hyun-jung; Weon, Jong-hyuck

2012-12-01

Neck pain is common in violin students during a musical performance. The purpose of this study was to compare electromyographic (EMG) activity in superficial neck muscles with neck motion when playing the violin as well as neck range of motion (ROM) at rest, between violin students with and without neck pain. Nine violin students with neck pain and nine age- and gender-matched subjects without neck pain were recruited. Muscle activity of the bilateral upper trapezius, sternocleidomastoid, and superficial cervical extensor muscles was measured using surface EMG. Kinematic data on neck motion while playing and active neck ROM were also measured using a three-dimensional motion analysis system. Independent t-tests were used to compare EMG activity with kinematic data between groups. These analyses revealed that while playing, both the angle of left lateral bending and leftward rotation of the cervical spine were significantly greater in the neck pain group than among those without neck pain. Similarly, EMG activity of the left upper trapezius, both cervical extensors, and both sternocleidomastoid muscles were significantly greater in the neck pain group. The active ROM of left axial rotation was significantly lower in the neck pain group. These results suggest that an asymmetric playing posture and the associated increased muscle activity as well as decreased neck axial rotation may contribute to neck pain in violin students.

Multi-scale approach to radiation damage induced by ion beams: complex DNA damage and effects of thermal spikes

International Nuclear Information System (INIS)

Surdutovich, E.; Yakubovich, A.V.; Solov'yov, A.V.; Surdutovich, E.; Yakubovich, A.V.; Solov'yov, A.V.

2010-01-01

We present the latest advances of the multi-scale approach to radiation damage caused by irradiation of a tissue with energetic ions and report the calculations of complex DNA damage and the effects of thermal spikes on biomolecules. The multi-scale approach aims to quantify the most important physical, chemical, and biological phenomena taking place during and following irradiation with ions and provide a better means for clinically-necessary calculations with adequate accuracy. We suggest a way of quantifying the complex clustered damage, one of the most important features of the radiation damage caused by ions. This quantification allows the studying of how the clusterization of DNA lesions affects the lethality of damage. We discuss the first results of molecular dynamics simulations of ubiquitin in the environment of thermal spikes, predicted to occur in tissue for a short time after an ion's passage in the vicinity of the ions' tracks. (authors)

Damping and tuning of the fibre violin modes in monolithic silica suspensions

International Nuclear Information System (INIS)

Gossler, S; Cagnoli, G; Crooks, D R M; Lueck, H; Rowan, S; Smith, J R; Strain, K A; Hough, J; Danzmann, K

2004-01-01

High Q mirror suspensions are a key element of the advanced interferometric gravitational-wave detectors. In December 2002 the last of the final interferometer optics of GEO 600 were monolithically suspended, using fused silica fibres. The violin modes of the suspension fibres can have Q greater than 10 8 and can therefore interfere with the interferometer length control servo. Hence, the violin modes need to be damped, without degrading the pendulum Q itself. Furthermore, the frequency spread of the fibres used has to be small to allow for high Q notch filtering in the length control servo. The requirements for the violin modes of the two GEO 600 inboard suspensions are Q 6 for the fundamental and Q 6 for the first harmonic mode, respectively. The frequency spread should not exceed 10% within one mode. To accomplish that, two sections of the fibres were coated with amorphous Teflon. By applying the coating, the Q of the relevant modes can be degraded to the desired values and furthermore, the frequencies of these modes can be tuned almost independently with a good accuracy over a wide range. After welding the fibres in the monolithic suspension, a corrective coating was applied to some fibres, to compensate for the frequency spread due to the tension spread of the four fibres within a suspension. We present the method and the results achieved

Numerical simulation on current spike behaviour of JT-60U disruptive plasmas

International Nuclear Information System (INIS)

Takei, N; Nakamura, Y; Tsutsui, H; Yoshino, R; Kawano, Y; Ozeki, T; Tobita, K; Tsuji-Iio, S; Shimada, R; Jardin, S C

2004-01-01

Characteristics and underlying mechanisms for plasma current spikes, which have been frequently observed during the thermal quench of JT-60U disruptions, were investigated through tokamak simulation code simulations including the passive shell effects of the vacuum vessel. Positive shear and reversed shear (PS and RS) plasmas were shown to have various current spike features in the experiments, e.g. an impulsive increase in the plasma current (positive spike) in the majority of thermal quenches, and a sudden decrease (negative spike), that has been excluded from past consideration, as an exception. It was first clarified that the shell effects, which become significant especially at a strong pressure drop due to the thermal quench of high β p plasmas, play an important role in the current spike in accordance with the initial relation of the radial location between the plasma equilibria and the vacuum vessel. As a consequence, a negative current spike may appear at thermal quench when the plasma is positioned further out from the geometric centre of the vacuum vessel. It was also pointed out that a further lowering in the internal inductance, in contradiction to previous interpretation in the past, is a plausible candidate for the mechanism for positive current spikes observed even in RS plasmas. The new interpretation enables us to reason out the whole character of current spikes of JT-60U disruptions

Resonance wood [Picea abies (L.) Karst.]--evaluation and prediction of violin makers' quality-grading.

Science.gov (United States)

Buksnowitz, Christoph; Teischinger, Alfred; Müller, Ulrich; Pahler, Andreas; Evans, Robert

2007-04-01

The definition of quality in the field of resonance wood for musical instrument making has attracted considerable interest over decades but has remained incomplete. The current work compares the traditional knowledge and practical experience of violin makers with a material-science approach to objectively characterize the properties of resonance wood. Norway spruce [Picea abies (L.) Karst.] has earned a very high reputation for the construction of resonance tops of stringed instruments and resonance boards of keyboard instruments, and was therefore chosen as the focus of the investigation. The samples were obtained from numerous renowned resonance wood regions in the European Alps and cover the whole range of available qualities. A set of acoustical, anatomical, mechanical and optical material properties was measured on each sample. These measurements were compared with subjective quality grading by violin makers, who estimated the acoustical, optical and overall suitability for violin making. Multiple linear regression models were applied to evaluate the predictability of the subjective grading using the measured material characteristics as predictors. The results show that luthiers are able to estimate wood quality related to visible features, but predictions of mechanical and acoustical properties proved to be very poor.

Spider Silk Violin Strings with a Unique Packing Structure Generate a Soft and Profound Timbre

Science.gov (United States)

Osaki, Shigeyoshi

2012-04-01

We overcome the difficulties in pulling long draglines from spiders, twist bundles of dragline filaments, and succeed in preparing violin strings. The twisting is found to change the cross section shapes of filaments from circular to polygonal and to optimize the packing structure with no openings among filaments providing mechanically strong and elastic strings. The spider string signal peaks of overtones for the violin are relatively large at high frequencies, generating a soft and profound timbre. Such a preferable timbre is considered to be due to the unique polygonal packing structure which provides valuable knowledge for developing new types of materials.

Coordination in fast repetitive violin-bowing patterns.

Science.gov (United States)

Schoonderwaldt, Erwin; Altenmüller, Eckart

2014-01-01

We present a study of coordination behavior in complex violin-bowing patterns involving simultaneous bow changes (reversal of bowing direction) and string crossings (changing from one string to another). Twenty-two violinists (8 advanced amateurs, 8 students with violin as major subject, and 6 elite professionals) participated in the experiment. We investigated the influence of a variety of performance conditions (specific bowing patterns, dynamic level, tempo, and transposition) and level of expertise on coordination behavior (a.o., relative phase and amplitude) and stability. It was found that the general coordination behavior was highly consistent, characterized by a systematic phase lead of bow inclination over bow velocity of about 15° (i.e., string crossings were consistently timed earlier than bow changes). Within similar conditions, a high individual consistency was found, whereas the inter-individual agreement was considerably less. Furthermore, systematic influences of performance conditions on coordination behavior and stability were found, which could be partly explained in terms of particular performance constraints. Concerning level of expertise, only subtle differences were found, the student and professional groups (higher level of expertise) showing a slightly higher stability than the amateur group (lower level of expertise). The general coordination behavior as observed in the current study showed a high agreement with perceptual preferences reported in an earlier study to similar bowing patterns, implying that complex bowing trajectories for an important part emerge from auditory-motor interaction.

Coordination in fast repetitive violin-bowing patterns.

Directory of Open Access Journals (Sweden)

Erwin Schoonderwaldt

Full Text Available We present a study of coordination behavior in complex violin-bowing patterns involving simultaneous bow changes (reversal of bowing direction and string crossings (changing from one string to another. Twenty-two violinists (8 advanced amateurs, 8 students with violin as major subject, and 6 elite professionals participated in the experiment. We investigated the influence of a variety of performance conditions (specific bowing patterns, dynamic level, tempo, and transposition and level of expertise on coordination behavior (a.o., relative phase and amplitude and stability. It was found that the general coordination behavior was highly consistent, characterized by a systematic phase lead of bow inclination over bow velocity of about 15° (i.e., string crossings were consistently timed earlier than bow changes. Within similar conditions, a high individual consistency was found, whereas the inter-individual agreement was considerably less. Furthermore, systematic influences of performance conditions on coordination behavior and stability were found, which could be partly explained in terms of particular performance constraints. Concerning level of expertise, only subtle differences were found, the student and professional groups (higher level of expertise showing a slightly higher stability than the amateur group (lower level of expertise. The general coordination behavior as observed in the current study showed a high agreement with perceptual preferences reported in an earlier study to similar bowing patterns, implying that complex bowing trajectories for an important part emerge from auditory-motor interaction.

In situ multi-element analyses by energy-dispersive X-ray fluorescence on varnishes of historical violins

Energy Technology Data Exchange (ETDEWEB)

Echard, Jean-Philippe [Laboratoire de recherche et de restauration, Musee de la musique, Cite de la musique, 221, avenue Jean-Jaures, 75019 Paris (France)]. E-mail: jpechard@cite-musique.fr

2004-10-08

Varnishes of Italian violins and other historical stringed instruments have been analyzed by energy-dispersive X-ray fluorescence (EDXRF). The instruments whose varnishes were to be analyzed were chosen from the collection kept in Musee de la Musique in Paris. Direct analyses were performed on instrument varnishes, without any sampling and non-destructively, showing inorganic elements such as lead, mercury and iron that could be related to siccatives or pigments. Analytical results and their comparison with old formulae or traditional recipes of violin varnishes, as with the few previous analytical results, will be discussed.

In situ multi-element analyses by energy-dispersive X-ray fluorescence on varnishes of historical violins

International Nuclear Information System (INIS)

Echard, Jean-Philippe

2004-01-01

Varnishes of Italian violins and other historical stringed instruments have been analyzed by energy-dispersive X-ray fluorescence (EDXRF). The instruments whose varnishes were to be analyzed were chosen from the collection kept in Musee de la Musique in Paris. Direct analyses were performed on instrument varnishes, without any sampling and non-destructively, showing inorganic elements such as lead, mercury and iron that could be related to siccatives or pigments. Analytical results and their comparison with old formulae or traditional recipes of violin varnishes, as with the few previous analytical results, will be discussed

Full-field vibration measurements of the violin using digital stroboscopic holographic interferometry and electromagnetic stimulation of the strings

Science.gov (United States)

Keersmaekers, Lissa; Keustermans, William; De Greef, Daniël; Dirckx, Joris J. J.

2016-06-01

We developed a setup in which the strings of the violin are driven electromagnetically, and the resulting vibration of the instrument is measured with digital stroboscopic holography. A 250mW single mode green laser beam is chopped using an acousto-optic modulator, generating illumination pulses of 2% of the vibration period. The phase of the illumination pulse is controlled by a programmable function generator so that digital holograms can be recorded on a number of subsequent time positions within the vibration phase. From these recordings, the out of plane motion as a function of time is reconstructed in full field. We show results of full-field vibration amplitude and vibration phase maps, and time resolved full-field deformations of the violin back plane. Time resolved measurements show in detail how the deformation of the violin plane changes as a function of time at different frequencies. We found very different behavior under acoustic stimulation of the instrument and when using electromagnetic stimulation of a string. The aim of the work it to gather data which can be used in power flow calculations to study how the energy of the strings is conducted to the body of the violin and eventually is radiated as sound.

Full-field vibration measurements of the violin using digital stroboscopic holographic interferometry and electromagnetic stimulation of the strings

International Nuclear Information System (INIS)

Keersmaekers, Lissa; Keustermans, William; De Greef, Daniël; Dirckx, Joris J. J.

2016-01-01

We developed a setup in which the strings of the violin are driven electromagnetically, and the resulting vibration of the instrument is measured with digital stroboscopic holography. A 250 mW single mode green laser beam is chopped using an acousto-optic modulator, generating illumination pulses of 2% of the vibration period. The phase of the illumination pulse is controlled by a programmable function generator so that digital holograms can be recorded on a number of subsequent time positions within the vibration phase. From these recordings, the out of plane motion as a function of time is reconstructed in full field. We show results of full-field vibration amplitude and vibration phase maps, and time resolved full-field deformations of the violin back plane. Time resolved measurements show in detail how the deformation of the violin plane changes as a function of time at different frequencies. We found very different behavior under acoustic stimulation of the instrument and when using electromagnetic stimulation of a string. The aim of the work it to gather data which can be used in power flow calculations to study how the energy of the strings is conducted to the body of the violin and eventually is radiated as sound.

Full-field vibration measurements of the violin using digital stroboscopic holographic interferometry and electromagnetic stimulation of the strings

Energy Technology Data Exchange (ETDEWEB)

Keersmaekers, Lissa; Keustermans, William, E-mail: william.keustermans@uantwerpen.be; De Greef, Daniël; Dirckx, Joris J. J. [University of Antwerp, Laboratory of Biophysics and Biomedical Physics, Groenenborgerlaan 171, 2020 Antwerp (Belgium)

2016-06-28

We developed a setup in which the strings of the violin are driven electromagnetically, and the resulting vibration of the instrument is measured with digital stroboscopic holography. A 250 mW single mode green laser beam is chopped using an acousto-optic modulator, generating illumination pulses of 2% of the vibration period. The phase of the illumination pulse is controlled by a programmable function generator so that digital holograms can be recorded on a number of subsequent time positions within the vibration phase. From these recordings, the out of plane motion as a function of time is reconstructed in full field. We show results of full-field vibration amplitude and vibration phase maps, and time resolved full-field deformations of the violin back plane. Time resolved measurements show in detail how the deformation of the violin plane changes as a function of time at different frequencies. We found very different behavior under acoustic stimulation of the instrument and when using electromagnetic stimulation of a string. The aim of the work it to gather data which can be used in power flow calculations to study how the energy of the strings is conducted to the body of the violin and eventually is radiated as sound.

Damping and tuning of the fibre violin modes in monolithic silica suspensions

Energy Technology Data Exchange (ETDEWEB)

Gossler, S [Max-Planck-Institute for Gravitational Physics (Albert-Einstein-Institute) and University of Hannover, Callinstr 38, D-30167 Hannover (Germany); Cagnoli, G [Department of Physics and Astronomy, Institute for Gravitational Research, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Crooks, D R M [Department of Physics and Astronomy, Institute for Gravitational Research, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Lueck, H [Max-Planck-Institute for Gravitational Physics (Albert-Einstein-Institute) and University of Hannover, Callinstr 38, D-30167 Hannover (Germany); Rowan, S [Department of Physics and Astronomy, Institute for Gravitational Research, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Smith, J R [Max-Planck-Institute for Gravitational Physics (Albert-Einstein-Institute) and University of Hannover, Callinstr 38, D-30167 Hannover (Germany); Strain, K A [Department of Physics and Astronomy, Institute for Gravitational Research, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Hough, J [Department of Physics and Astronomy, Institute for Gravitational Research, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Danzmann, K [Max-Planck-Institute for Gravitational Physics (Albert-Einstein-Institute) and University of Hannover, Callinstr 38, D-30167 Hannover (Germany)

2004-03-07

High Q mirror suspensions are a key element of the advanced interferometric gravitational-wave detectors. In December 2002 the last of the final interferometer optics of GEO 600 were monolithically suspended, using fused silica fibres. The violin modes of the suspension fibres can have Q greater than 10{sup 8} and can therefore interfere with the interferometer length control servo. Hence, the violin modes need to be damped, without degrading the pendulum Q itself. Furthermore, the frequency spread of the fibres used has to be small to allow for high Q notch filtering in the length control servo. The requirements for the violin modes of the two GEO 600 inboard suspensions are Q < 3 x 10{sup 6} for the fundamental and Q < 2 x 10{sup 6} for the first harmonic mode, respectively. The frequency spread should not exceed 10% within one mode. To accomplish that, two sections of the fibres were coated with amorphous Teflon. By applying the coating, the Q of the relevant modes can be degraded to the desired values and furthermore, the frequencies of these modes can be tuned almost independently with a good accuracy over a wide range. After welding the fibres in the monolithic suspension, a corrective coating was applied to some fibres, to compensate for the frequency spread due to the tension spread of the four fibres within a suspension. We present the method and the results achieved.

Load-cell based characterization system for a "Violin-Mode" shadow-sensor in advanced LIGO suspensions

Science.gov (United States)

Lockerbie, N. A.; Tokmakov, K. V.

2016-07-01

The background to this work was a prototype shadow sensor, which was designed for retro-fitting to an advanced LIGO (Laser Interferometer Gravitational wave Observatory) test-mass/mirror suspension, in which 40 kg test-mass/mirrors are each suspended by four approximately 600 mm long by 0.4 mm diameter fused-silica suspension fibres. The shadow sensor comprised a LED source of Near InfraRed (NIR) radiation and a rectangular silicon photodiode detector, which, together, were to bracket the fibre under test. The aim was to detect transverse Violin-Mode resonances in the suspension fibres. Part of the testing procedure involved tensioning a silica fibre sample and translating it transversely through the illuminating NIR beam, so as to measure the DC responsivity of the detection system to fibre displacement. However, an equally important part of the procedure, reported here, was to keep the fibre under test stationary within the beam, whilst trying to detect low-level AC Violin-Mode resonances excited on the fibre, in order to confirm the primary function of the sensor. Therefore, a tensioning system, incorporating a load-cell readout, was built into the test fibre's holder. The fibre then was excited by a signal generator, audio power amplifier, and distant loudspeaker, and clear resonances were detected. A theory for the expected fundamental resonant frequency as a function of fibre tension was developed and is reported here, and this theory was found to match closely with the detected resonant frequencies as they varied with tension. Consequently, the resonances seen were identified as being proper Violin-Mode fundamental resonances of the fibre, and the operation of the Violin-Mode detection system was validated.

A Comparison of First and Third Position Approaches to Violin Instruction

Science.gov (United States)

Cowden, Robert L.

1972-01-01

Purpose of this study was to determine by means of a performance scale whether there would be a significant difference between the intonational and rhythmic achievement of fourth-grade students who began violin study in the first position and fourth-grade students who began in the third position. (Author/CB)

In situ multi-element analyses by energy-dispersive X-ray fluorescence on varnishes of historical violins

Science.gov (United States)

Echard, Jean-Philippe

2004-10-01

Varnishes of Italian violins and other historical stringed instruments have been analyzed by energy-dispersive X-ray fluorescence (EDXRF). The instruments whose varnishes were to be analyzed were chosen from the collection kept in Musée de la Musique in Paris. Direct analyses were performed on instrument varnishes, without any sampling and non-destructively, showing inorganic elements such as lead, mercury and iron that could be related to siccatives or pigments. Analytical results and their comparison with old formulae or traditional recipes of violin varnishes, as with the few previous analytical results, will be discussed.

Strings on a Violin: Location Dependence of Frequency Tuning in Active Dendrites.

Science.gov (United States)

Das, Anindita; Rathour, Rahul K; Narayanan, Rishikesh

2017-01-01

Strings on a violin are tuned to generate distinct sound frequencies in a manner that is firmly dependent on finger location along the fingerboard. Sound frequencies emerging from different violins could be very different based on their architecture, the nature of strings and their tuning. Analogously, active neuronal dendrites, dendrites endowed with active channel conductances, are tuned to distinct input frequencies in a manner that is dependent on the dendritic location of the synaptic inputs. Further, disparate channel expression profiles and differences in morphological characteristics could result in dendrites on different neurons of the same subtype tuned to distinct frequency ranges. Alternately, similar location-dependence along dendritic structures could be achieved through disparate combinations of channel profiles and morphological characteristics, leading to degeneracy in active dendritic spectral tuning. Akin to strings on a violin being tuned to different frequencies than those on a viola or a cello, different neuronal subtypes exhibit distinct channel profiles and disparate morphological characteristics endowing each neuronal subtype with unique location-dependent frequency selectivity. Finally, similar to the tunability of musical instruments to elicit distinct location-dependent sounds, neuronal frequency selectivity and its location-dependence are tunable through activity-dependent plasticity of ion channels and morphology. In this morceau, we explore the origins of neuronal frequency selectivity, and survey the literature on the mechanisms behind the emergence of location-dependence in distinct forms of frequency tuning. As a coda to this composition, we present some future directions for this exciting convergence of biophysical mechanisms that endow a neuron with frequency multiplexing capabilities.

The acoustics of the violin: a review

International Nuclear Information System (INIS)

Woodhouse, Jim

2014-01-01

To understand the design and function of the violin requires investigation of a range of scientific questions. This paper presents a review: the relevant physics covers the nonlinear vibration of a bowed string, the vibration of the instrument body, and the consequent sound radiation. Questions of discrimination and preference by listeners and players require additional studies using the techniques of experimental psychology, and these are also touched on in the paper. To address the concerns of players and makers of instruments requires study of the interaction of all these factors, coming together in the concept of ‘playability’ of an instrument. (review article)

The acoustics of the violin: a review

Science.gov (United States)

Woodhouse, Jim

2014-11-01

To understand the design and function of the violin requires investigation of a range of scientific questions. This paper presents a review: the relevant physics covers the nonlinear vibration of a bowed string, the vibration of the instrument body, and the consequent sound radiation. Questions of discrimination and preference by listeners and players require additional studies using the techniques of experimental psychology, and these are also touched on in the paper. To address the concerns of players and makers of instruments requires study of the interaction of all these factors, coming together in the concept of ‘playability’ of an instrument.

Perceived Pitch of Violin and Cello Vibrato Tones among Music Majors

Science.gov (United States)

Geringer, John M.; MacLeod, Rebecca B.; Allen, Michael L.

2010-01-01

The purpose of this study was to investigate the perceived pitch of string vibrato tones. The authors used recordings of acoustic instruments (cello and violin) to provide both vibrato stimulus tones and the nonvibrato tones that listeners adjusted to match the perceived pitch of the vibrato stimuli. We were interested especially in whether there…

Violin f-hole contribution to far-field radiation via patch near-field acoustical holography.

Science.gov (United States)

Bissinger, George; Williams, Earl G; Valdivia, Nicolas

2007-06-01

The violin radiates either from dual ports (f-holes) or via surface motion of the corpus (top+ribs+back), with no clear delineation between these sources. Combining "patch" near-field acoustical holography over just the f-hole region of a violin with far-field radiativity measurements over a sphere, it was possible to separate f-hole from surface motion contributions to the total radiation of the corpus below 2.6 kHz. A0, the Helmholtz-like lowest cavity resonance, radiated essentially entirely through the f-holes as expected while A1, the first longitudinal cavity mode with a node at the f-holes, had no significant f-hole radiation. The observed A1 radiation comes from an indirect radiation mechanism, induced corpus motion approximately mirroring the cavity pressure profile seen for violinlike bowed string instruments across a wide range of sizes. The first estimates of the fraction of radiation from the f-holes F(f) indicate that some low frequency corpus modes thought to radiate only via surface motion (notably the first corpus bending modes) had significant radiation through the f-holes, in agreement with net volume changes estimated from experimental modal analysis. F(f) generally trended lower with increasing frequency, following corpus mobility decreases. The f-hole directivity (top/back radiativity ratio) was generally higher than whole-violin directivity.

Learning to play the violin: motor control by freezing, not freeing degrees of freedom.

Science.gov (United States)

Konczak, Jürgen; Vander Velden, Heidi; Jaeger, Lukas

2009-05-01

Playing a violin requires precise patterns of limb coordination that are acquired over years of practice. In the present study, the authors investigated how motion at proximal arm joints influenced the precision of bow movements in novice learners and experts. The authors evaluated the performances of 11 children (4-12 years old), 3 beginning-to-advanced level adult players, and 2 adult concert violinists, using a musical work that all had mastered as their first violin piece. The authors found that learning to play the violin was not associated with a release or freeing of joint degrees of freedom. Instead, learning was characterized by an experience-dependent suppression of sagittal shoulder motion, as documented by an observed reduction in joint angular amplitude. This reduction in the amplitude of shoulder flexion-extension correlated highly with a decrease of bow-movement variability. The remaining mechanical degrees of freedom at the elbow and shoulder showed patterns of neither suppression nor freeing. Only violinists with more than 700 practice hr achieved sagittal shoulder range of motion comparable to experts. The findings imply that restricting joint amplitude at selected joint degrees of freedom, while leaving other degrees of freedom unconstrained, constitutes an appropriate strategy for learning complex, high-precision motor patterns in children and adults. The findings also highlight that mastering even seemingly simple bowing movements constitutes a prolonged learning process.

Load-cell based characterization system for a “Violin-Mode” shadow-sensor in advanced LIGO suspensions

Energy Technology Data Exchange (ETDEWEB)

Lockerbie, N. A.; Tokmakov, K. V. [SUPA (Scottish Universities Physics Alliance) Department of Physics, University of Strathclyde, 107 Rottenrow, Glasgow G4 0NG (United Kingdom)

2016-07-15

The background to this work was a prototype shadow sensor, which was designed for retro-fitting to an advanced LIGO (Laser Interferometer Gravitational wave Observatory) test-mass/mirror suspension, in which 40 kg test-mass/mirrors are each suspended by four approximately 600 mm long by 0.4 mm diameter fused-silica suspension fibres. The shadow sensor comprised a LED source of Near InfraRed (NIR) radiation and a rectangular silicon photodiode detector, which, together, were to bracket the fibre under test. The aim was to detect transverse Violin-Mode resonances in the suspension fibres. Part of the testing procedure involved tensioning a silica fibre sample and translating it transversely through the illuminating NIR beam, so as to measure the DC responsivity of the detection system to fibre displacement. However, an equally important part of the procedure, reported here, was to keep the fibre under test stationary within the beam, whilst trying to detect low-level AC Violin-Mode resonances excited on the fibre, in order to confirm the primary function of the sensor. Therefore, a tensioning system, incorporating a load-cell readout, was built into the test fibre’s holder. The fibre then was excited by a signal generator, audio power amplifier, and distant loudspeaker, and clear resonances were detected. A theory for the expected fundamental resonant frequency as a function of fibre tension was developed and is reported here, and this theory was found to match closely with the detected resonant frequencies as they varied with tension. Consequently, the resonances seen were identified as being proper Violin-Mode fundamental resonances of the fibre, and the operation of the Violin-Mode detection system was validated.

Load-cell based characterization system for a “Violin-Mode” shadow-sensor in advanced LIGO suspensions

International Nuclear Information System (INIS)

Lockerbie, N. A.; Tokmakov, K. V.

2016-01-01

The background to this work was a prototype shadow sensor, which was designed for retro-fitting to an advanced LIGO (Laser Interferometer Gravitational wave Observatory) test-mass/mirror suspension, in which 40 kg test-mass/mirrors are each suspended by four approximately 600 mm long by 0.4 mm diameter fused-silica suspension fibres. The shadow sensor comprised a LED source of Near InfraRed (NIR) radiation and a rectangular silicon photodiode detector, which, together, were to bracket the fibre under test. The aim was to detect transverse Violin-Mode resonances in the suspension fibres. Part of the testing procedure involved tensioning a silica fibre sample and translating it transversely through the illuminating NIR beam, so as to measure the DC responsivity of the detection system to fibre displacement. However, an equally important part of the procedure, reported here, was to keep the fibre under test stationary within the beam, whilst trying to detect low-level AC Violin-Mode resonances excited on the fibre, in order to confirm the primary function of the sensor. Therefore, a tensioning system, incorporating a load-cell readout, was built into the test fibre’s holder. The fibre then was excited by a signal generator, audio power amplifier, and distant loudspeaker, and clear resonances were detected. A theory for the expected fundamental resonant frequency as a function of fibre tension was developed and is reported here, and this theory was found to match closely with the detected resonant frequencies as they varied with tension. Consequently, the resonances seen were identified as being proper Violin-Mode fundamental resonances of the fibre, and the operation of the Violin-Mode detection system was validated.

Structural changes in cuticles on violin bow hair caused by wear.

Science.gov (United States)

Yamamoto, Tomoko; Sugiyama, Shigeru

2010-01-01

A bow with horse tail hair is used to play the violin. New and worn-out bow hairs were observed by atomic force microscopy. The cuticles of the new bow hair were already damaged by bleach and delipidation, however the worn-out bow hairs were much more damaged and broken off by force, which relates to wearing out.

Understanding the Learning Style of Pre-School Children Learning the Violin

Science.gov (United States)

Calissendorff, Maria

2006-01-01

The aim of the study was to acquire a deeper understanding of how small children learn an instrument in the presence of their parents. It is qualitative in nature and concerned six pre-school children (five years old) who were learning the violin together and where their parents were present at the lessons. All the children's homes were visited…

Microanalysis of old violin varnishes by total-reflection X-ray fluorescence

Science.gov (United States)

von Bohlen, Alex; Meyer, Friedrich

1997-07-01

Total reflection X-ray fluorescence was used to characterize elements (with Z>13) contained in varnishes applied by prominent violin makers during the last five centuries. Direct analyses of small flakes with masses varnish. Higher amounts of Fe, As and Pb were found in old products, Mn, Co, Cu, Zn and Pb were used in more recent varnishes.

On the Relationship between Technique and Style: The Case of the Violin

Science.gov (United States)

Johansson, Mats

2015-01-01

This article examines the formative interaction between instrumental technique and musical style by analysing different approaches to the violin/fiddle. It is argued that technique is constitutive of style and that musical concepts are intimately related to the accumulated experience of sensations associated with handling the instrument in a…

Effects of Articulation Styles on Perception of Modulated Tempos in Violin Excerpts

Science.gov (United States)

Geringer, John M.; Madsen, Clifford K.; Macleod, Rebecca B.

2007-01-01

We investigated effects of legato, staccato and pizzicato articulation styles on the perception of modulated tempos. Seventy-two music majors served as participants. Two solo violin excerpts were chosen with contrasting rhythmic rates and were recorded in all three articulation styles. Examples were presented to listeners in three conditions of…

Constructing a "Fast Protocol" for Middle School Beginner Violin Classes in Japan

Science.gov (United States)

Akutsu, Taichi

2018-01-01

This study aimed to investigate the process of constructing a "fast-protocol" for violin instruction. Since learning string instruments has not been common, and because there are limited hours for music in Japanese schools, the author, a violinist, collaborated with the general music teacher at a middle school in the Tokyo metropolitan…

The Conservation of Rhythm in Suzuki Violin Students: A Task Validation Study.

Science.gov (United States)

Nelson, David J.

1984-01-01

Twenty Suzuki violin students between four and eight years old were individually administered an author-designed rhythmic task and a series of standardized tasks that measured area and length conservation. The students' prior training was found to be less of a factor in rhythmic conservation than were age and area-length conservation. (Author/RM)

Development of a Computer-Based Visualised Quantitative Learning System for Playing Violin Vibrato

Science.gov (United States)

Ho, Tracy Kwei-Liang; Lin, Huann-shyang; Chen, Ching-Kong; Tsai, Jih-Long

2015-01-01

Traditional methods of teaching music are largely subjective, with the lack of objectivity being particularly challenging for violin students learning vibrato because of the existence of conflicting theories. By using a computer-based analysis method, this study found that maintaining temporal coincidence between the intensity peak and the target…

Awake Surgery for a Violin Player: Monitoring Motor and Music Performance, A Case Report.

Science.gov (United States)

Piai, Vitória; Vos, Sandra H; Idelberger, Reinhard; Gans, Pauline; Doorduin, Jonne; Ter Laan, Mark

2018-02-27

We report the case of a professional violin player who underwent an awake craniotomy to resect a tumor in the left supplementary motor area, an area involved in motor planning. A careful pre- and intraoperative monitoring plan for music performance and complex motor function was established that could be used in combination with cortical stimulation. The patient suffered an epileptic seizure during cortical stimulation. The monitoring of complex motor and musical functions was implemented with the patient playing the violin while the resection was performed. Almost complete resection was achieved with no notable postoperative deficits contributing to functional impairment. The multidisciplinary approach, involving neurosurgery, neuropsychology, anesthesiology, and clinical neurophysiology, allowed us to successfully cope with the theoretical and practical challenges associated with tailored care for a professional musician. The music and motor monitoring plan is reported in detail to enable other sites to reproduce and adapt it accordingly.

Unraveling mysteries of personal performance style; biomechanics of left-hand position changes (shifting) in violin performance.

Science.gov (United States)

Visentin, Peter; Li, Shiming; Tardif, Guillaume; Shan, Gongbing

2015-01-01

Instrumental music performance ranks among the most complex of learned human behaviors, requiring development of highly nuanced powers of sensory and neural discrimination, intricate motor skills, and adaptive abilities in a temporal activity. Teaching, learning and performing on the violin generally occur within musico-cultural parameters most often transmitted through aural traditions that include both verbal instruction and performance modeling. In most parts of the world, violin is taught in a manner virtually indistinguishable from that used 200 years ago. The current study uses methods from movement science to examine the "how" and "what" of left-hand position changes (shifting), a movement skill essential during violin performance. In doing so, it begins a discussion of artistic individualization in terms of anthropometry, the performer-instrument interface, and the strategic use of motor behaviors. Results based on 540 shifting samples, a case series of 6 professional-level violinists, showed that some elements of the skill were individualized in surprising ways while others were explainable by anthropometry, ergonomics and entrainment. Remarkably, results demonstrated each violinist to have developed an individualized pacing for shifts, a feature that should influence timing effects and prove foundational to aesthetic outcomes during performance. Such results underpin the potential for scientific methodologies to unravel mysteries of performance that are associated with a performer's personal artistic style.

Unraveling mysteries of personal performance style; biomechanics of left-hand position changes (shifting in violin performance

Directory of Open Access Journals (Sweden)

Peter Visentin

2015-10-01

Full Text Available Instrumental music performance ranks among the most complex of learned human behaviors, requiring development of highly nuanced powers of sensory and neural discrimination, intricate motor skills, and adaptive abilities in a temporal activity. Teaching, learning and performing on the violin generally occur within musico-cultural parameters most often transmitted through aural traditions that include both verbal instruction and performance modeling. In most parts of the world, violin is taught in a manner virtually indistinguishable from that used 200 years ago. The current study uses methods from movement science to examine the “how” and “what” of left-hand position changes (shifting, a movement skill essential during violin performance. In doing so, it begins a discussion of artistic individualization in terms of anthropometry, the performer-instrument interface, and the strategic use of motor behaviors. Results based on 540 shifting samples, a case series of 6 professional-level violinists, showed that some elements of the skill were individualized in surprising ways while others were explainable by anthropometry, ergonomics and entrainment. Remarkably, results demonstrated each violinist to have developed an individualized pacing for shifts, a feature that should influence timing effects and prove foundational to aesthetic outcomes during performance. Such results underpin the potential for scientific methodologies to unravel mysteries of performance that are associated with a performer’s personal artistic style.

Parental Involvement in the Musical Education of Violin Students: Suzuki and "Traditional" Approaches Compared

Science.gov (United States)

Bugeja, Clare

2009-01-01

This article investigates parental involvement in the musical education of violin students and the changing role of the parents' across the learning process. Two contexts were compared, one emphasising the Suzuki methodology and the other a "traditional" approach. Students learning "traditionally" are typically taught note reading from the…

[Deep venous thrombosis of the upper limb in a violin player: The "bow syndrome"].

Science.gov (United States)

Sanson, H; Gautier, V; Stansal, A; Sfeir, D; Franceschi, C; Priollet, P

2016-12-01

Exercise-induced thrombosis is a rare cause of deep venous thrombosis (DVT) of the upper limb and usually affects young subjects without comorbid conditions. The diagnosis may be challenging. A 23-year-old female right-handed French teacher and amateur violin player presented with edema of the root of the right arm associated with erythrocyanosis of the extremity and collateral circulation of the shoulder. History taking revealed oral contraception and recent change in violin playing habits. D-dimers were negative. A second duplex-Doppler was required before visualization of a DVT in the right subclavian vein. The patient was given low-molecular-weight heparin alone, followed by rivaroxaban. The outcome was very favorable at 48h. The patient was seen at 4 months and had not had a recurrent episode. The diagnosis of DVT of the upper limb is basically clinical. There is a clinical probability score for the introduction of anticoagulation even if the duplex-Doppler fails to visualize DVT, a situation that can occur due to the clavicular superposition in this region. Exercise-induced DVT should be suspected in patients with minimally intense but repeated exercise (hyper-abduction), e.g. as here playing the violin. Anticoagulation is the treatment of choice. The role for surgery and pharmacomechanical strategies remains to be defined. Exercise-induced thrombosis (Paget-Schroetter syndrome) should be suspected in young patients free of any comorbidity who develop a thrombosis of the upper limb. Studies comparing different therapeutic options would be useful to achieve more homogeneous management practices despite the heterogeneous clinical presentations. Copyright © 2016. Published by Elsevier Masson SAS.

Experimental Demonstration on Air Cavity Mode of Violin Using Holed Sheets of Paper

Science.gov (United States)

Matsutani, Akihiro

2018-01-01

The fundamental air cavity mode (A0) of a violin was investigated from the viewpoint of its dependence on the opening area and shape by using holed sheets of paper. The dependences of the frequency response of the A0 cavity mode on the shape, opening area, and orientation of the openings were observed. It was also demonstrated that the change of…

Anton Stepanovich Arensky : Violin Concerto in A minor, Op.54

OpenAIRE

Vojtovicova, Maria

2017-01-01

I have chosen Anton Stepanovich Arensky and his Violin Concerto in A minor as an object of my practical and theoretical final project in Metropolia University of Applied Sciences for a very simple reason and that is, I believe he and his concert never got the attention they deserve. In the beginning of the thesis I go briefly through Arensky’s life and his entire work as there is not a lot known of him and we have very limited sources of information due to his short life and lack of inte...

Connecting science and the musical arts in teaching tone quality: Integrating Helmholtz motion and master violin teachers' pedagogies

Science.gov (United States)

Collins, Cheri D.

Is it possible for students to achieve better tone quality from even their factory-made violins? All violins, regardless of cost, have a common capacity for good tone in certain frequencies. These signature modes outline the first position range of a violin (196-600 hertz). To activate this basic capacity of all violins, the string must fully vibrate. To accomplish this the bow must be pulled across the string with enough pressure (relative to its speed and contact point) for the horsehairs to catch. This friction permits the string to vibrate in Helmholtz Motion, which produces a corner that travels along the edge of the string between the bridge and the nut. Creating this corner is the most fundamental technique for achieving good tone. The findings of celebrated scientists Ernest Chladni, Hermann von Helmholtz, and John Schelleng will be discussed and the tone-production pedagogy of master teachers Carl Flesch, Ivan Galamian, Robert Gerle, and Simon Fischer will be investigated. Important connections between the insights of these scientists and master teachers are evident. Integrating science and art can provide teachers with a better understanding of the characteristics of good tone. This can help their students achieve the best possible sound from their instruments. In the private studio the master teacher may not use the words "Helmholtz Motion." Yet through modeling and listening students are able to understand and create a quality tone. Music teachers without experience in string performance may be assigned to teach strings in classroom and ensembles settings. As a result modeling good tone is not always possible. However, all teachers and conductors can understand the fundamental behavior of string vibration and adapt their instruction strategies towards student success. Better tonal quality for any string instrument is ultimately achieved. Mastery and use of the Helmholtz Motion benefits teachers and students alike. Simple practice exercises for teaching

Thermal spike model interpretation of sputtering yield data for Bi thin films irradiated by MeV {sup 84}Kr{sup 15+} ions

Energy Technology Data Exchange (ETDEWEB)

Mammeri, S. [Centre de Recherche Nucléaire d’Alger, B.P. 399, 02 Bd. Frantz Fanon, Alger-gare, Algiers (Algeria); Ouichaoui, S., E-mail: souichaoui@gmail.com [Université des Sciences et de la Technologie H. Boumediene (USTHB), Faculté de Physique, Laboratoire SNIRM, B.P. 32, El-Alia, 16111 Bab Ezzouar, Algiers (Algeria); Ammi, H. [Centre de Recherche Nucléaire d’Alger, B.P. 399, 02 Bd. Frantz Fanon, Alger-gare, Algiers (Algeria); Pineda-Vargas, C.A. [iThemba LABS, National Research Foundation, P.O. Box 722, Somerset West 7129 (South Africa); Faculty of Health and Wellness Sciences, CPUT, P.O. Box 1906, Bellville 7535 (South Africa); Dib, A. [Centre de Recherche Nucléaire d’Alger, B.P. 399, 02 Bd. Frantz Fanon, Alger-gare, Algiers (Algeria); Msimanga, M. [iThemba LABS, National Research Foundation, P. Bag 11, Wits 2050, Johannesburg (South Africa); Department of Physics, Tshwane University of Technology, P. Bag X680, Pretoria 001 (South Africa)

2015-07-01

A modified thermal spike model initially proposed to account for defect formation in metals within the high heavy ion energy regime is adapted for describing the sputtering of Bi thin films under MeV Kr ions. Surface temperature profiles for both the electronic and atomic subsystems have been carefully evaluated versus the radial distance and time with introducing appropriate values of the Bi target electronic stopping power for multi-charged Kr{sup 15+} heavy ions as well as different target physical proprieties like specific heats and thermal conductivities. Then, the total sputtering yields of the irradiated Bi thin films have been determined from a spatiotemporal integration of the local atomic evaporation rate. Besides, an expected non negligible contribution of elastic nuclear collisions to the Bi target sputtering yields and ion-induced surface effects has also been considered in our calculation. Finally, the latter thermal spike model allowed us to derive numerical sputtering yields in satisfactorily agreement with existing experimental data both over the low and high heavy ion energy regions, respectively, dominated by elastic nuclear collisions and inelastic electronic collisions, in particular with our data taken recently for Bi thin films irradiated by 27.5 MeV Kr{sup 15+} heavy ions. An overall consistency of our model calculation with the predictions of sputtering yield theoretical models within the target nuclear stopping power regime was also pointed out.

Characterisation of varnishes used in violins by pyrolysis-gas chromatography/mass spectrometry.

Science.gov (United States)

Chiavari, Giuseppe; Montalbani, Simona; Otero, Vanessa

2008-12-01

The correct characterisation and a detailed knowledge of the materials originally used in violin varnishes, like natural resins, is crucial for the conservation in museums and for a suitable restoration technique. The study presented here reports on the potential of pyrolysis (Py) coupled with gas chromatography (GC) and mass spectrometry (MS) for the identification of chemical markers of each resin; this technique is very sensitive and selective, it needs a small quantity of sample and does not require chemical treatments. To improve the chromatographic behaviour of polar compounds the derivatising agent tetramethylammonium hydroxide (TMAH) in combination with pyrolysis has been used, in the so-called TMAH thermochemolysis or thermally assisted hydrolysis and methylation (THM), or more simply pyrolysis-methylation. The natural resins studied were colophony, sandarac, manila copal, elemi, amber and benzoin, mainly composed of terpenic compounds, with the exception of the latter, composed of aromatic compounds. Many compounds were identified; in particular, methyl esters of resinous acids that, individually or in a group, can be used as chemical markers. However, through this technique it was not possible to distinguish between the sandarac and manila copal resins because their chromatographic behaviour is very similar. Finally, the procedure applied has been employed in the characterisation of original varnish samples.

O violino violado: o entremear das vozes esquecidas das rabecas e de "outros violinos" The fiddled violin: the clamor of forgotten voices from the Brazilian rabecas and "other violins"

Directory of Open Access Journals (Sweden)

Luiz Henrique Fiaminghi

2009-01-01

Full Text Available A representação do violino como instrumento musical hegemônico é um fato incontestável se considerarmos sua presença nos mais diversos âmbitos das práticas da música ocidental. As últimas décadas presenciaram, porém, a emergência de algumas vozes dissonantes: as práticas interpretativas historicamente informadas (Historically Informed Performance ou HIP redescobriram o violino barroco e todo o seu aparato técnico; no Brasil, a rabeca mostrou suas potencialidades, não mais somente nas mãos de ardorosos defensores da cultura popular, mas de músicos em busca de novas sonoridades. Tomando como exemplo a intersecção do popular e erudito contido nas peças para rabeca escritas por José Eduardo Gramani, pretende-se aqui, sobretudo, mais do que apresentar respostas definitivas, abrir novas questões relacionadas ao ensino do violino no mundo contemporâneo, a partir da inserção de instrumentos esquecidos pela história oficial. Neste sentido, reflete alguns dos aspectos defendidos por Walter Benjamin em Sobre o conceito de história, e traz para a pauta das discussões sobre interpretação musical a questão da padronização imposta pela indústria cultural.The representation of the violin as a hegemonic musical instrument is an undisputed fact, regarding its presence within the widest scope of Western musical performance. The last decades have witnessed, however, the emergency of some dissonant voices: the Historically Informed Performance (HIP practice has rediscovered the baroque violin and all its technical apparatus; the Brazilian fiddle rabeca claimed to be heard through its own voice, despite the neglectful approach from the mainstream scholars and musicians. Departing from the intersection between popular and erudite culture that characterizes most of Brazilian José Eduardo Gramani’s music written for rabeca, this article raises reflections about violin teaching in a multi-cultural society, according to the concepts

Estimation of violin bowing features from Audio recordings with Convolutional Networks

DEFF Research Database (Denmark)

Perez-Carillo, Alfonso; Purwins, Hendrik

The acquisition of musical gestures and particularly of instrument controls from a musical performance is a field of increasing interest with applications in many research areas. In the last years, the development of novel sensing technologies has allowed the fine measurement of such controls...... and low-cost of the acquisition and its nonintrusive nature. The main challenge is designing robust detection algorithms to be as accurate as the direct approaches. In this paper, we present an indirect acquisition method to estimate violin bowing controls from audio signal analysis based on training...

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

Science.gov (United States)

Zenke, Friedemann; Ganguli, Surya

2018-04-13

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

Design & Evaluation of an Accessible Hybrid Violin Platform

DEFF Research Database (Denmark)

Overholt, Daniel; Gelineck, Steven

2014-01-01

We introduce and describe the initial evaluation of a new accessible (easily replicable) augmented violin prototype. Our research is focused on the user experience when playing such hybrid physical- digital instruments, and exploration of novel interactive performance techniques. The goal of wider...... platform accessibility for players and other researchers is approached via a simple ‘do-it-yourself’ design described herein. All hardware and software elements are open- source, and the build process requires minimal electronics skills. Cost has also been kept to a minimum where possible. Our initial...... that incorporates orientation/gesture sensors as well, with the resulting sound amplified and rendered via small speakers mounted directly to the instrument. The platform combines all necessary elements for digitally-mediated interactive performance; the need for a traditional computer only arises when developing...

Attention and Perseverance Behaviors of PreSchool Children Enrolled in Suzuki Violin Lessons and Other Activities.

Science.gov (United States)

Scott, Laurie

1992-01-01

Reports on a study of attention span and persevering behaviors of preschool children. Finds the Suzuki Method of violin instruction is associated with longer attention spans and more persevering behaviors than creative movement instruction or other preschool programs. Concludes that teachers prefer the Suzuki Method's approach to other forms of…

Spiking neural network for recognizing spatiotemporal sequences of spikes

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2004-01-01

Sensory neurons in many brain areas spike with precise timing to stimuli with temporal structures, and encode temporally complex stimuli into spatiotemporal spikes. How the downstream neurons read out such neural code is an important unsolved problem. In this paper, we describe a decoding scheme using a spiking recurrent neural network. The network consists of excitatory neurons that form a synfire chain, and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition, respectively. The network signals recognition of a specific spatiotemporal sequence when the last excitatory neuron down the synfire chain spikes, which happens if and only if that sequence was present in the input spike stream. The recognition scheme is invariant to variations in the intervals between input spikes within some range. The computation of the network can be mapped into that of a finite state machine. Our network provides a simple way to decode spatiotemporal spikes with diverse types of neurons

Cognitive Levels Regarding Articulation Marks among Violin Students in Department of Music Education in Gazi University

Science.gov (United States)

Taninmis, Gamze Elif

2016-01-01

The purpose of this study is to determine violin students' cognitive levels about articulation marks in Department of Music Education, Fine Arts Education, Gazi Faculty of Education, Gazi University (GUGEF), and to identify the variables on which the cognitive levels vary. It is a descriptive research considering the study purpose, method and…

THE SONATA FOR VIOLIN AND PIANO BY VIOREL MUNTEANU IN THE INTERPRETATIVE CONCEPTION OF NATIVE MUSICIANS

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STOLEARCIUC XENIA

2016-06-01

Full Text Available Signed in 1974, the Sonata for violin and piano by Viorel Munteanu continues the Enescu tradition and distinguishes itself by an original musical language, that alongside of the form sobriety, places this opus among the most representative examples of Romanian chamber instrumental music of the second half of the 20th century. Special attention is given to the exploration of the source of folklore and the Byzantine influence that generate the intonational-thematic structure of the whole work and relate it to the opuses of Moldovan music. Thus, the abundance of sound symbols and specific elements of the „pastoral” space reveals essential aspects of the interpretative conception of the native musicians. This composition was premiered in Chisinau within the framework of the 25th edition of the International Festival The Days of New Music. In the present article the author wants to pay her respects to the late violinist Angela Molodojan who performed with remarkable artistry, originality and musical refinement the violin part in the above-mentioned creation.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

Science.gov (United States)

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

iSpike: a spiking neural interface for the iCub robot

International Nuclear Information System (INIS)

Gamez, D; Fidjeland, A K; Lazdins, E

2012-01-01

This paper presents iSpike: a C++ library that interfaces between spiking neural network simulators and the iCub humanoid robot. It uses a biologically inspired approach to convert the robot’s sensory information into spikes that are passed to the neural network simulator, and it decodes output spikes from the network into motor signals that are sent to control the robot. Applications of iSpike range from embodied models of the brain to the development of intelligent robots using biologically inspired spiking neural networks. iSpike is an open source library that is available for free download under the terms of the GPL. (paper)

Padrões físicos inadequados na performance musical de estudantes de violino Inadequate physical patterns in musical performance of violin students

Directory of Open Access Journals (Sweden)

Carolina Valverde Alves

2012-12-01

Full Text Available O presente artigo, uma exposição resumida da dissertação de mestrado (2008, discute a observação e avaliação dos problemas corporais que permeiam a prática de seis estudantes de violino do curso de Graduação da Escola de Música da UFMG. Dados foram colhidos através de observação, filmes e fotos de seis alunos de violino em quatro situações diferentes de performance no contexto do curso, além de avaliações fisioterápicas realizadas no consultório de Fisioterapia da pesquisadora. Estes dados foram apresentados a um painel composto por quatro observadores da área da saúde e da música. A análise destes dados revela que os seis alunos de violino apresentaram padrões físicos inadequados que poderiam prejudicar sua saúde e, consequentemente, sua performance. Além disso, foi conduzida uma pesquisa bibliográfica envolvendo estudos relacionados à Anatomia, Biomecânica e Cinesiologia. Esperamos que este artigo possa chamar a atenção dos violinistas e professores de violino para a importância de uma consciência corporal durante a performance do instrumento, que vise mais simetria e relaxamento das regiões corporais envolvidas no ato de tocar o violino.This article, a summary of the Master thesis (2008, discusses the observation and evaluation of physical problems presented by six Bachelors students of the Music School of UFMG (Brazil, in their violin practice. Data was collected through observation, films and photos of six violin students at four different situations of performance in the context of their program, besides the physiotherapeutic assessments held in the office of the physiotherapist researcher. This data was then submitted to a panel composed of four observers, health and music specialists. The analysis of this data reveals that the six violin students showed inappropriate physical patterns that could jeopardize their performance as well as their health. Also, a bibliographic survey related to the Anatomy

An AC modulated near infrared gain calibration system for a "Violin-Mode" transimpedance amplifier, intended for advanced LIGO suspensions

Science.gov (United States)

Lockerbie, N. A.; Tokmakov, K. V.

2016-07-01

The background to this work was a prototype shadow sensor, which was designed for retro-fitting to an advanced LIGO (Laser Interferometer Gravitational wave Observatory) test-mass/mirror suspension, in which a 40 kg test-mass/mirror is suspended by four approximately 600 mm long by 0.4 mm diameter fused-silica suspension fibres. The shadow sensor comprised a LED source of Near InfraRed (NIR) radiation, and a "tall-thin" rectangular silicon photodiode detector, which together were to bracket the fibre under test. The photodiode was positioned so as to be sensitive (primarily) to transverse "Violin-Mode" vibrations of such a fibre, via the oscillatory movement of the shadow cast by the fibre, as this moved across the face of the detector. In this prototype shadow sensing system the photodiode was interfaced to a purpose-built transimpedance amplifier, this having both AC and DC outputs. A quasi-static calibration was made of the sensor's DC responsivity, i.e., incremental rate of change of output voltage versus fibre position, by slowly scanning a fused-silica fibre sample transversely through the illuminating beam. The work reported here concerns the determination of the sensor's more important AC (Violin-Mode) responsivity. Recognition of the correspondence between direct AC modulation of the source, and actual Violin-Mode signals, and of the transformative role of the AC/DC gain ratio for the amplifier, at any modulation frequency, f, resulted in the construction of the AC/DC calibration source described here. A method for determining in practice the transimpedance AC/DC gain ratio of the photodiode and amplifier, using this source, is illustrated by a specific numerical example, and the gain ratio for the prototype sensing system is reported over the frequency range 1 Hz-300 kHz. In fact, a maximum DC responsivity of 1.26 kV.m-1 was measured using the prototype photodiode sensor and amplifier discussed here. Therefore, the measured AC/DC transimpedance gain ratio

An AC modulated near infrared gain calibration system for a "Violin-Mode" transimpedance amplifier, intended for advanced LIGO suspensions.

Science.gov (United States)

Lockerbie, N A; Tokmakov, K V

2016-07-01

The background to this work was a prototype shadow sensor, which was designed for retro-fitting to an advanced LIGO (Laser Interferometer Gravitational wave Observatory) test-mass/mirror suspension, in which a 40 kg test-mass/mirror is suspended by four approximately 600 mm long by 0.4 mm diameter fused-silica suspension fibres. The shadow sensor comprised a LED source of Near InfraRed (NIR) radiation, and a "tall-thin" rectangular silicon photodiode detector, which together were to bracket the fibre under test. The photodiode was positioned so as to be sensitive (primarily) to transverse "Violin-Mode" vibrations of such a fibre, via the oscillatory movement of the shadow cast by the fibre, as this moved across the face of the detector. In this prototype shadow sensing system the photodiode was interfaced to a purpose-built transimpedance amplifier, this having both AC and DC outputs. A quasi-static calibration was made of the sensor's DC responsivity, i.e., incremental rate of change of output voltage versus fibre position, by slowly scanning a fused-silica fibre sample transversely through the illuminating beam. The work reported here concerns the determination of the sensor's more important AC (Violin-Mode) responsivity. Recognition of the correspondence between direct AC modulation of the source, and actual Violin-Mode signals, and of the transformative role of the AC/DC gain ratio for the amplifier, at any modulation frequency, f, resulted in the construction of the AC/DC calibration source described here. A method for determining in practice the transimpedance AC/DC gain ratio of the photodiode and amplifier, using this source, is illustrated by a specific numerical example, and the gain ratio for the prototype sensing system is reported over the frequency range 1 Hz-300 kHz. In fact, a maximum DC responsivity of 1.26 kV.m(-1) was measured using the prototype photodiode sensor and amplifier discussed here. Therefore, the measured AC/DC transimpedance gain

A source of illumination for low-noise ‘Violin-Mode’ shadow sensors, intended for use in interferometric gravitational wave detectors

International Nuclear Information System (INIS)

Lockerbie, N A; Tokmakov, K V; Strain, K A

2014-01-01

A low-noise source of illumination is described for shadow sensors having a displacement sensitivity of (69  ±  13) picometres (rms)/√Hz, at 500 Hz, over a measuring span of ±0.1 mm. These sensors were designed to detect ‘Violin-Mode’ resonances in the suspension fibres of the test-masses/mirrors for the Advanced LIGO (Laser Interferometer Gravitational wave Observatory) gravitational wave detectors. The source of illumination (emitter) described here used a single column of 8 × miniature near infrared LEDs (λ = 890 nm). These emitters cast the shadows of 400 μm diameter fused silica suspension fibres onto their complementary shadow-displacement detectors, located at a distance of 74 fibre diameters (29.6 mm) behind the axes of the fibres themselves. Violin-Mode vibrations of each fibre were sensed as differential ac photocurrents in the corresponding ‘split-photodiode’ detector. This paper describes the design, construction, noise analysis, and measures that were taken in the conception of the emitters, in order to produce high-contrast shadows at such distant detectors. In this way it proved possible to obtain, simultaneously, a very high transfer sensitivity to Violin-Mode vibration of the fibres, and a very low level of detection noise—close to the fundamental shot noise limit—whilst remaining within the constraints of this simple design of emitter. The shadow detector is described in an accompanying paper. (paper)

A source of illumination for low-noise ‘Violin-Mode’ shadow sensors, intended for use in interferometric gravitational wave detectors

Science.gov (United States)

Lockerbie, N. A.; Tokmakov, K. V.; Strain, K. A.

2014-12-01

A low-noise source of illumination is described for shadow sensors having a displacement sensitivity of (69  ±  13) picometres (rms)/√Hz, at 500 Hz, over a measuring span of ±0.1 mm. These sensors were designed to detect ‘Violin-Mode’ resonances in the suspension fibres of the test-masses/mirrors for the Advanced LIGO (Laser Interferometer Gravitational wave Observatory) gravitational wave detectors. The source of illumination (emitter) described here used a single column of 8 × miniature near infrared LEDs (λ = 890 nm). These emitters cast the shadows of 400 μm diameter fused silica suspension fibres onto their complementary shadow-displacement detectors, located at a distance of 74 fibre diameters (29.6 mm) behind the axes of the fibres themselves. Violin-Mode vibrations of each fibre were sensed as differential ac photocurrents in the corresponding ‘split-photodiode’ detector. This paper describes the design, construction, noise analysis, and measures that were taken in the conception of the emitters, in order to produce high-contrast shadows at such distant detectors. In this way it proved possible to obtain, simultaneously, a very high transfer sensitivity to Violin-Mode vibration of the fibres, and a very low level of detection noise—close to the fundamental shot noise limit—whilst remaining within the constraints of this simple design of emitter. The shadow detector is described in an accompanying paper.

Analysis of High-Density Surface EMG and Finger Pressure in the Left Forearm of Violin Players: A Feasibility Study.

Science.gov (United States)

Cattarello, Paolo; Merletti, Roberto; Petracca, Francesco

2017-09-01

Wrist and finger flexor muscles of the left hand were evaluated using high-density surface EMG (HDsEMG) in 17 violin players. Pressure sensors also were mounted below the second string of the violin to evaluate, simultaneously, finger pressure. Electrode grid size was 110x70 mm (12x8 electrodes with interelectrode distance=10 mm and Ø=3 mm). The study objective was to observe the activation patterns of these muscles while the violinists sequentially played four notes--SI (B), DO# (C#), RE (D), MI (E)--at 2 bows/s (one bow up in 0.5 s and one down in 0.5 s) and 4 bows/s on the second string, while producing a constant (CONST) or ramp (RAMP) sound volume. HDsEMG images obtained while playing the notes were compared with those obtained during isometric radial or ulnar flexion of the wrist or fingers. Two image descriptors provided information on image differences. Results showed that the technique was reliable and provided reliable signals, and that recognizably different sEMG images could be associated with the four notes tested, despite the variability within and between subjects playing the same note. sEMG activity of the left hand muscles and pressure on the string in the RAMP task were strongly affected in some individuals by the sound volume (controlled by the right hand) and much less in other individuals. These findings question whether there is an individual or generally optimal way of pressing violin strings with the left hand. The answer to this question might substantially modify the teaching of string instruments.

Training spiking neural networks to associate spatio-temporal input-output spike patterns

OpenAIRE

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

2013-01-01

In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

An intercomparison experiment on isotope dilution thermal ionisation mass spectrometry using plutonium-239 spike for the determination of plutonium concentration in dissolver solution of irradiated fuel

International Nuclear Information System (INIS)

Aggarwal, S.K.; Shah, P.M.; Saxena, M.K.; Jain, H.C.; Gurba, P.B.; Babbar, R.K.; Udagatti, S.V.; Moorthy, A.D.; Singh, R.K.; Bajpai, D.D.

1996-01-01

Determination of plutonium concentration in the dissolver solution of irradiated fuel is one of the key measurements in the nuclear fuel cycle. This report presents the results of an intercomparison experiment performed between Fuel Chemistry Division (FCD) at BARC and PREFRE, Tarapur for determining plutonium concentration in dissolver solution of irradiated fuel using 239 Pu spike in isotope dilution thermal ionisation mass spectrometry (ID-TIMS). The 239 Pu spike method was previously established at FCD as viable alternative to the imported enriched 242 Pu or 244 Pu; the spike used internationally for plutonium concentration determination by IDMS in dissolver solution of irradiated fuel. Precision and accuracy achievable for determining plutonium concentration are compared under the laboratory and the plant conditions using 239 Pu spike in IDMS. For this purpose, two different dissolver solutions with 240 Pu/ 239 Pu atom ratios of about 0.3 and 0.07 corresponding, respectively, to high and low burn-up fuels, were used. The results of the intercomparison experiment demonstrate that there is no difference in the precision values obtained under the laboratory and the plant conditions; with mean precision values of better than 0.2%. Further, the plutonium concentration values determined by the two laboratories agreed within 0.3%. This exercise, therefore, demonstrates that ID-TIMS method using 239 Pu spike can be used for determining plutonium concentration in dissolver solution of irradiated fuel, under the plant conditions. 7 refs., 8 tabs

Spike persistence and normalization in benign epilepsy with centrotemporal spikes - Implications for management.

Science.gov (United States)

Kim, Hunmin; Kim, Soo Yeon; Lim, Byung Chan; Hwang, Hee; Chae, Jong-Hee; Choi, Jieun; Kim, Ki Joong; Dlugos, Dennis J

2018-05-10

This study was performed 1) to determine the timing of spike normalization in patients with benign epilepsy with centrotemporal spikes (BECTS); 2) to identify relationships between age of seizure onset, age of spike normalization, years of spike persistence and treatment; and 3) to assess final outcomes between groups of patients with or without spikes at the time of medication tapering. Retrospective analysis of BECTS patients confirmed by clinical data, including age of onset, seizure semiology and serial electroencephalography (EEG) from diagnosis to remission. Age at spike normalization, years of spike persistence, and time of treatment onset to spike normalization were assessed. Final seizure and EEG outcome were compared between the groups with or without spikes at the time of AED tapering. One hundred and thirty-four patients were included. Mean age at seizure onset was 7.52 ± 2.11 years. Mean age at spike normalization was 11.89 ± 2.11 (range: 6.3-16.8) years. Mean time of treatment onset to spike normalization was 4.11 ± 2.13 (range: 0.24-10.08) years. Younger age of seizure onset was correlated with longer duration of spike persistence (r = -0.41, p < 0.001). In treated patients, spikes persisted for 4.1 ± 1.95 years, compared with 2.9 ± 1.97 years in untreated patients. No patients had recurrent seizures after AED was discontinued, regardless of the presence/absence of spikes at time of AED tapering. Years of spike persistence was longer in early onset BECTS patients. Treatment with AEDs did not shorten years of spike persistence. Persistence of spikes at time of treatment withdrawal was not associated with seizure recurrence. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

An AC modulated near infrared gain calibration system for a “Violin-Mode” transimpedance amplifier, intended for advanced LIGO suspensions

International Nuclear Information System (INIS)

Lockerbie, N. A.; Tokmakov, K. V.

2016-01-01

The background to this work was a prototype shadow sensor, which was designed for retro-fitting to an advanced LIGO (Laser Interferometer Gravitational wave Observatory) test-mass/mirror suspension, in which a 40 kg test-mass/mirror is suspended by four approximately 600 mm long by 0.4 mm diameter fused-silica suspension fibres. The shadow sensor comprised a LED source of Near InfraRed (NIR) radiation, and a “tall-thin” rectangular silicon photodiode detector, which together were to bracket the fibre under test. The photodiode was positioned so as to be sensitive (primarily) to transverse “Violin-Mode” vibrations of such a fibre, via the oscillatory movement of the shadow cast by the fibre, as this moved across the face of the detector. In this prototype shadow sensing system the photodiode was interfaced to a purpose-built transimpedance amplifier, this having both AC and DC outputs. A quasi-static calibration was made of the sensor’s DC responsivity, i.e., incremental rate of change of output voltage versus fibre position, by slowly scanning a fused-silica fibre sample transversely through the illuminating beam. The work reported here concerns the determination of the sensor’s more important AC (Violin-Mode) responsivity. Recognition of the correspondence between direct AC modulation of the source, and actual Violin-Mode signals, and of the transformative role of the AC/DC gain ratio for the amplifier, at any modulation frequency, f, resulted in the construction of the AC/DC calibration source described here. A method for determining in practice the transimpedance AC/DC gain ratio of the photodiode and amplifier, using this source, is illustrated by a specific numerical example, and the gain ratio for the prototype sensing system is reported over the frequency range 1 Hz–300 kHz. In fact, a maximum DC responsivity of 1.26 kV.m"−"1 was measured using the prototype photodiode sensor and amplifier discussed here. Therefore, the measured AC

An AC modulated near infrared gain calibration system for a “Violin-Mode” transimpedance amplifier, intended for advanced LIGO suspensions

Energy Technology Data Exchange (ETDEWEB)

Lockerbie, N. A.; Tokmakov, K. V. [SUPA (Scottish Universities Physics Alliance) Department of Physics, University of Strathclyde, 107 Rottenrow, Glasgow G4 0NG (United Kingdom)

2016-07-15

The background to this work was a prototype shadow sensor, which was designed for retro-fitting to an advanced LIGO (Laser Interferometer Gravitational wave Observatory) test-mass/mirror suspension, in which a 40 kg test-mass/mirror is suspended by four approximately 600 mm long by 0.4 mm diameter fused-silica suspension fibres. The shadow sensor comprised a LED source of Near InfraRed (NIR) radiation, and a “tall-thin” rectangular silicon photodiode detector, which together were to bracket the fibre under test. The photodiode was positioned so as to be sensitive (primarily) to transverse “Violin-Mode” vibrations of such a fibre, via the oscillatory movement of the shadow cast by the fibre, as this moved across the face of the detector. In this prototype shadow sensing system the photodiode was interfaced to a purpose-built transimpedance amplifier, this having both AC and DC outputs. A quasi-static calibration was made of the sensor’s DC responsivity, i.e., incremental rate of change of output voltage versus fibre position, by slowly scanning a fused-silica fibre sample transversely through the illuminating beam. The work reported here concerns the determination of the sensor’s more important AC (Violin-Mode) responsivity. Recognition of the correspondence between direct AC modulation of the source, and actual Violin-Mode signals, and of the transformative role of the AC/DC gain ratio for the amplifier, at any modulation frequency, f, resulted in the construction of the AC/DC calibration source described here. A method for determining in practice the transimpedance AC/DC gain ratio of the photodiode and amplifier, using this source, is illustrated by a specific numerical example, and the gain ratio for the prototype sensing system is reported over the frequency range 1 Hz–300 kHz. In fact, a maximum DC responsivity of 1.26 kV.m{sup −1} was measured using the prototype photodiode sensor and amplifier discussed here. Therefore, the measured AC

Violin Bridge Mobility Analysis under In-Plane Excitation

Directory of Open Access Journals (Sweden)

Cheng-Zhong Zhang

2013-11-01

Full Text Available The vibration of a violin bridge is a dynamic contact vibration with two interfaces: strings-bridge, and bridge feet-top plate. In this paper, the mobility of an isolated bridge under in-plane excitation is explored using finite element modeling based on the contact vibration model. Numerical results show that the dynamic contact stiffness in the two contact interfaces has a great impact on the bridge mobility. A main resonance peak is observed in the frequency range of 2–3 kHz in the frequency response of the isolated bridge when the contact stiffness is smaller than a critical threshold. The main resonance peak frequency is affected by the contact stiffness as well. In order to verify the numerical findings, a novel experimental system is then designed on the basis of a piezoelectric dynamometer for bridge mobility analysis. Experimental results confirm the impact of the dynamic contact stiffness on the bridge mobility.

Violin bridge mobility analysis under in-plane excitation.

Science.gov (United States)

Zhang, Cheng-Zhong; Zhang, Guang-Ming; Ye, Bang-Yan; Liang, Li-Dong

2013-11-08

The vibration of a violin bridge is a dynamic contact vibration with two interfaces: strings-bridge, and bridge feet-top plate. In this paper, the mobility of an isolated bridge under in-plane excitation is explored using finite element modeling based on the contact vibration model. Numerical results show that the dynamic contact stiffness in the two contact interfaces has a great impact on the bridge mobility. A main resonance peak is observed in the frequency range of 2-3 kHz in the frequency response of the isolated bridge when the contact stiffness is smaller than a critical threshold. The main resonance peak frequency is affected by the contact stiffness as well. In order to verify the numerical findings, a novel experimental system is then designed on the basis of a piezoelectric dynamometer for bridge mobility analysis. Experimental results confirm the impact of the dynamic contact stiffness on the bridge mobility.

Influences of Dynamic Level and Pitch Register on the Vibrato Rates and Widths of Violin and Viola Players

Science.gov (United States)

MacLeod, Rebecca B.

2008-01-01

The purpose of this study was to investigate possible influences of pitch register and dynamic level on vibrato rates and widths of university and high school violin and viola players. Analysis showed that pitch register significantly affected the vibrato rates and widths of the performers. Musicians vibrated 0.32 Hz faster and approximately 26…

Spatial distribution of surface EMG on trapezius and lumbar muscles of violin and cello players in single note playing.

Science.gov (United States)

Afsharipour, Babak; Petracca, Francesco; Gasparini, Mauro; Merletti, Roberto

2016-12-01

Musicians activate their muscles in different patterns, depending on their posture, the instrument being played, and their experience level. Bipolar surface electrodes have been used in the past to monitor such activity, but this method is highly sensitive to the location of the electrode pair. In this work, the spatial distribution of surface EMG (sEMG) of the right trapezius and right and left erector spinae muscles were studied in 16 violin players and 11 cello players. Musicians played their instrument one string at a time in sitting position with/without backrest support. A 64 sEMG electrode (16×4) grid, 10mm inter-electrode distance (IED), was placed over the middle and lower trapezius (MT and LT) of the bowing arm. Two 16×2 electrode grids (IED=10mm) were placed on the left and right erector spinae muscles. Subjects played each of the four strings of the instrument either in large (1bow/s) or detaché tip/tail (8bows/s) bowing in two sessions (two days). In each of two days, measurements were repeated after half an hour of exercise to see the effect of exercise on the muscle activity and signal stability. A "muscle activity index" (MAI) was defined as the spatial average of the segmented active region of the RMS map. Spatial maps were automatically segmented using the watershed algorithm and thresholding. Results showed that, for violin players, sliding the bow upward from the tip toward the tail results in a higher MAI for the trapezius muscle than a downward bow. On the contrary, in cello players, higher MAI is produced in the tail to tip movement. For both instruments, an increasing MAI in the trapezius was observed as the string position became increasingly lateral, from string 1 (most medial) toward string 4 (most lateral). Half an hour of performance did not cause significant differences between the signal quality and the MAI values measured before and after the exercise. The MAI of the left and right erector spinae was smaller in the case of

The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex

DEFF Research Database (Denmark)

Forsberg, Lars E.; Bonde, Lars H.; Harvey, Michael A.

2016-01-01

and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states......Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from...... visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary...

Span: spike pattern association neuron for learning spatio-temporal spike patterns.

Science.gov (United States)

Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

2012-08-01

Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

Deep Spiking Networks

NARCIS (Netherlands)

O'Connor, P.; Welling, M.

2016-01-01

We introduce an algorithm to do backpropagation on a spiking network. Our network is "spiking" in the sense that our neurons accumulate their activation into a potential over time, and only send out a signal (a "spike") when this potential crosses a threshold and the neuron is reset. Neurons only

The Violin Concerto in D Major RV Anh. 8 and several other issues concerning František Jiránek (1698–1778)

Czech Academy of Sciences Publication Activity Database

Kapsa, Václav

2014-01-01

Roč. 14, č. 1 (2014), s. 15-43 ISSN 1594-0012 Institutional support: RVO:68378076 Keywords : 18th century instrumental music * violin concerto * Antonio Vivaldi * attribution * authenticity Subject RIV: AL - Art, Architecture, Cultural Heritage

Decoding spikes in a spiking neuronal network

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [Department of Informatics, University of Sussex, Brighton BN1 9QH (United Kingdom); Ding, Mingzhou [Department of Mathematics, Florida Atlantic University, Boca Raton, FL 33431 (United States)

2004-06-04

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs.

Decoding spikes in a spiking neuronal network

International Nuclear Information System (INIS)

Feng Jianfeng; Ding, Mingzhou

2004-01-01

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs

The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes.

Science.gov (United States)

Burroughs, Amelia; Wise, Andrew K; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y; Lang, Eric J; Apps, Richard; Cerminara, Nadia L

2017-01-01

Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes. Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets. The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear. We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number. This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition

The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex

Science.gov (United States)

Forsberg, Lars E.; Bonde, Lars H.; Harvey, Michael A.; Roland, Per E.

2016-01-01

Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states were slow, frequently changing direction. In single trials, sharp as well as smooth and slow transients transform the trajectories to be outward directed, fast and crossing the threshold to become evoked. Although the speeds of the evolution of the evoked states differ, the same domain of the state space is explored indicating uniformity of the evoked states. All evoked states return to the spontaneous evoked spiking state as in a typical mono-stable dynamical system. In single trials, neither the original spiking rates, nor the temporal evolution in state space could distinguish simple visual scenes. PMID:27582693

Automatic EEG spike detection.

Science.gov (United States)

Harner, Richard

2009-10-01

Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach. Expert-selected spike parameters were the first and still most widely used for AESD. Thresholds for amplitude, duration, sharpness, rise-time, fall-time, after-coming slow waves, background frequency, and more have been used. It is still unclear which of these wave parameters are essential, beyond peak-peak amplitude and duration. Wavelet parameters are very appropriate to AESD but need to be combined with other parameters to achieve desired levels of spike detection efficiency. Artificial Neural Network (ANN) and expert-system methods may have reached peak efficiency. Support Vector Machine (SVM) technology focuses on outliers rather than centroids of spike and nonspike data clusters and should improve AESD efficiency. An exemplary spike/nonspike database is suggested as a tool for assessing parameters and methods for AESD and is available in CSV or Matlab formats from the author at brainvue@gmail.com. Exploratory Data Analysis (EDA) is presented as a graphic method for finding better spike parameters and for the step-wise evaluation of the spike detection process.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

Science.gov (United States)

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

Gas chromatography/mass spectrometry characterization of historical varnishes of ancient Italian lutes and violin.

Science.gov (United States)

Echard, J P; Benoit, C; Peris-Vicente, J; Malecki, V; Gimeno-Adelantado, J V; Vaiedelich, S

2007-02-12

The organic constituents of historical vanishes from two ancient Italian lutes and a Stradivari violin, kept in the Musée de la musique in Paris, have been characterized using gas chromatography-mass spectrometry. Results have been compared with the chromatograms and mass spectra of recent as well as old naturally aged reference materials. The three historical varnishes analyzed have been shown to be oil varnishes, probably mixtures of linseed oil with resins. Identification of diterpenoids and triterpenoids compounds, and of the resins that may have been ingredients of the varnishes, are discussed in this paper.

Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting.

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Werner, Thilo; Vianello, Elisa; Bichler, Olivier; Garbin, Daniele; Cattaert, Daniel; Yvert, Blaise; De Salvo, Barbara; Perniola, Luca

2016-01-01

In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM) as easy to program and low energy (Spike Timing Dependent Plasticity. Real spiking data have been recorded both intra- and extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

Automatic spike sorting using tuning information.

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Ventura, Valérie

2009-09-01

Current spike sorting methods focus on clustering neurons' characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes' identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only.

Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus.

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Wennberg, Richard; Cheyne, Douglas

2014-05-01

To assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus. MSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions. MSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3 Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering. MSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability. MSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Decoding spatiotemporal spike sequences via the finite state automata dynamics of spiking neural networks

International Nuclear Information System (INIS)

Jin, Dezhe Z

2008-01-01

Temporally complex stimuli are encoded into spatiotemporal spike sequences of neurons in many sensory areas. Here, we describe how downstream neurons with dendritic bistable plateau potentials can be connected to decode such spike sequences. Driven by feedforward inputs from the sensory neurons and controlled by feedforward inhibition and lateral excitation, the neurons transit between UP and DOWN states of the membrane potentials. The neurons spike only in the UP states. A decoding neuron spikes at the end of an input to signal the recognition of specific spike sequences. The transition dynamics is equivalent to that of a finite state automaton. A connection rule for the networks guarantees that any finite state automaton can be mapped into the transition dynamics, demonstrating the equivalence in computational power between the networks and finite state automata. The decoding mechanism is capable of recognizing an arbitrary number of spatiotemporal spike sequences, and is insensitive to the variations of the spike timings in the sequences

Extraction of bowing parameters from violin performance combining motion capture and sensors.

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Schoonderwaldt, E; Demoucron, M

2009-11-01

A method is described for measurement of a complete set of bowing parameters in violin performance. Optical motion capture was combined with sensors for accurate measurement of the main bowing parameters (bow position, bow velocity, bow acceleration, bow-bridge distance, and bow force) as well as secondary control parameters (skewness, inclination, and tilt of the bow). In addition, other performance features (moments of on/off in bow-string contact, string played, and bowing direction) were extracted. Detailed descriptions of the calculations of the bowing parameters, features, and calibrations are given. The described system is capable of measuring all bowing parameters without disturbing the player, allowing for detailed studies of musically relevant aspects of bow control and coordination of bowing parameters in bowed-string instrument performance.

Application of cross-correlated delay shift rule in spiking neural networks for interictal spike detection.

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Lilin Guo; Zhenzhong Wang; Cabrerizo, Mercedes; Adjouadi, Malek

2016-08-01

This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classify spike patterns. The objective of this study was to evaluate the feasibility of using the CCDS rule to automate the detection of interictal spikes in electroencephalogram (EEG) data on patients with epilepsy. Encoding is the initial yet essential step for spiking neurons to process EEG patterns. A new encoding method is utilized to convert the EEG signal into spike patterns. The simulation results show that the proposed algorithm identified 69 spikes out of 82 spikes, or 84% detection rate, which is quite high considering the subtleties of interictal spikes and the tediousness of monitoring long EEG records. This CCDS rule is also benchmarked by ReSuMe on the same task.

Spike rate and spike timing contributions to coding taste quality information in rat periphery

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Vernon eLawhern

2011-05-01

Full Text Available There is emerging evidence that individual sensory neurons in the rodent brain rely on temporal features of the discharge pattern to code differences in taste quality information. In contrast, in-vestigations of individual sensory neurons in the periphery have focused on analysis of spike rate and mostly disregarded spike timing as a taste quality coding mechanism. The purpose of this work was to determine the contribution of spike timing to taste quality coding by rat geniculate ganglion neurons using computational methods that have been applied successfully in other sys-tems. We recorded the discharge patterns of narrowly-tuned and broadly-tuned neurons in the rat geniculate ganglion to representatives of the five basic taste qualities. We used mutual in-formation to determine significant responses and the van Rossum metric to characterize their temporal features. While our findings show that spike timing contributes a significant part of the message, spike rate contributes the largest portion of the message relayed by afferent neurons from rat fungiform taste buds to the brain. Thus, spike rate and spike timing together are more effective than spike rate alone in coding stimulus quality information to a single basic taste in the periphery for both narrowly-tuned specialist and broadly-tuned generalist neurons.

Impact of spike train autostructure on probability distribution of joint spike events.

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Pipa, Gordon; Grün, Sonja; van Vreeswijk, Carl

2013-05-01

The discussion whether temporally coordinated spiking activity really exists and whether it is relevant has been heated over the past few years. To investigate this issue, several approaches have been taken to determine whether synchronized events occur significantly above chance, that is, whether they occur more often than expected if the neurons fire independently. Most investigations ignore or destroy the autostructure of the spiking activity of individual cells or assume Poissonian spiking as a model. Such methods that ignore the autostructure can significantly bias the coincidence statistics. Here, we study the influence of the autostructure on the probability distribution of coincident spiking events between tuples of mutually independent non-Poisson renewal processes. In particular, we consider two types of renewal processes that were suggested as appropriate models of experimental spike trains: a gamma and a log-normal process. For a gamma process, we characterize the shape of the distribution analytically with the Fano factor (FFc). In addition, we perform Monte Carlo estimations to derive the full shape of the distribution and the probability for false positives if a different process type is assumed as was actually present. We also determine how manipulations of such spike trains, here dithering, used for the generation of surrogate data change the distribution of coincident events and influence the significance estimation. We find, first, that the width of the coincidence count distribution and its FFc depend critically and in a nontrivial way on the detailed properties of the structure of the spike trains as characterized by the coefficient of variation CV. Second, the dependence of the FFc on the CV is complex and mostly nonmonotonic. Third, spike dithering, even if as small as a fraction of the interspike interval, can falsify the inference on coordinated firing.

Nicotine-Mediated ADP to Spike Transition: Double Spiking in Septal Neurons.

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Kodirov, Sodikdjon A; Wehrmeister, Michael; Colom, Luis

2016-04-01

The majority of neurons in lateral septum (LS) are electrically silent at resting membrane potential. Nicotine transiently excites a subset of neurons and occasionally leads to long lasting bursting activity upon longer applications. We have observed simultaneous changes in frequencies and amplitudes of spontaneous action potentials (AP) in the presence of nicotine. During the prolonged exposure, nicotine increased numbers of spikes within a burst. One of the hallmarks of nicotine effects was the occurrences of double spikes (known also as bursting). Alignment of 51 spontaneous spikes, triggered upon continuous application of nicotine, revealed that the slope of after-depolarizing potential gradually increased (1.4 vs. 3 mV/ms) and neuron fired the second AP, termed as double spiking. A transition from a single AP to double spikes increased the amplitude of after-hyperpolarizing potential. The amplitude of the second (premature) AP was smaller compared to the first one, and this correlation persisted in regard to their duration (half-width). A similar bursting activity in the presence of nicotine, to our knowledge, has not been reported previously in the septal structure in general and in LS in particular.

Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Institute of Scientific and Technical Information of China (English)

Lin Chen; Yong Deng; Weihua Luo; Zhen Wang; Shaoqun Zeng

2009-01-01

Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with phys-iological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgrnent. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.

Information transmission with spiking Bayesian neurons

International Nuclear Information System (INIS)

Lochmann, Timm; Deneve, Sophie

2008-01-01

Spike trains of cortical neurons resulting from repeatedpresentations of a stimulus are variable and exhibit Poisson-like statistics. Many models of neural coding therefore assumed that sensory information is contained in instantaneous firing rates, not spike times. Here, we ask how much information about time-varying stimuli can be transmitted by spiking neurons with such input and output variability. In particular, does this variability imply spike generation to be intrinsically stochastic? We consider a model neuron that estimates optimally the current state of a time-varying binary variable (e.g. presence of a stimulus) by integrating incoming spikes. The unit signals its current estimate to other units with spikes whenever the estimate increased by a fixed amount. As shown previously, this computation results in integrate and fire dynamics with Poisson-like output spike trains. This output variability is entirely due to the stochastic input rather than noisy spike generation. As a result such a deterministic neuron can transmit most of the information about the time varying stimulus. This contrasts with a standard model of sensory neurons, the linear-nonlinear Poisson (LNP) model which assumes that most variability in output spike trains is due to stochastic spike generation. Although it yields the same firing statistics, we found that such noisy firing results in the loss of most information. Finally, we use this framework to compare potential effects of top-down attention versus bottom-up saliency on information transfer with spiking neurons

Barbed micro-spikes for micro-scale biopsy

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Byun, Sangwon; Lim, Jung-Min; Paik, Seung-Joon; Lee, Ahra; Koo, Kyo-in; Park, Sunkil; Park, Jaehong; Choi, Byoung-Doo; Seo, Jong Mo; Kim, Kyung-ah; Chung, Hum; Song, Si Young; Jeon, Doyoung; Cho, Dongil

2005-06-01

Single-crystal silicon planar micro-spikes with protruding barbs are developed for micro-scale biopsy and the feasibility of using the micro-spike as a micro-scale biopsy tool is evaluated for the first time. The fabrication process utilizes a deep silicon etch to define the micro-spike outline, resulting in protruding barbs of various shapes. Shanks of the fabricated micro-spikes are 3 mm long, 100 µm thick and 250 µm wide. Barbs protruding from micro-spike shanks facilitate the biopsy procedure by tearing off and retaining samples from target tissues. Micro-spikes with barbs successfully extracted tissue samples from the small intestines of the anesthetized pig, whereas micro-spikes without barbs failed to obtain a biopsy sample. Parylene coating can be applied to improve the biocompatibility of the micro-spike without deteriorating the biopsy function of the micro-spike. In addition, to show that the biopsy with the micro-spike can be applied to tissue analysis, samples obtained by micro-spikes were examined using immunofluorescent staining. Nuclei and F-actin of cells which are extracted by the micro-spike from a transwell were clearly visualized by immunofluorescent staining.

Bayesian population decoding of spiking neurons.

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Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias

2009-01-01

The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

Bayesian population decoding of spiking neurons

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Sebastian Gerwinn

2009-10-01

Full Text Available The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a `spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

Heterogeneity of Purkinje cell simple spike-complex spike interactions: zebrin- and non-zebrin-related variations.

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Tang, Tianyu; Xiao, Jianqiang; Suh, Colleen Y; Burroughs, Amelia; Cerminara, Nadia L; Jia, Linjia; Marshall, Sarah P; Wise, Andrew K; Apps, Richard; Sugihara, Izumi; Lang, Eric J

2017-08-01

Cerebellar Purkinje cells (PCs) generate two types of action potentials, simple and complex spikes. Although they are generated by distinct mechanisms, interactions between the two spike types exist. Zebrin staining produces alternating positive and negative stripes of PCs across most of the cerebellar cortex. Thus, here we compared simple spike-complex spike interactions both within and across zebrin populations. Simple spike activity undergoes a complex modulation preceding and following a complex spike. The amplitudes of the pre- and post-complex spike modulation phases were correlated across PCs. On average, the modulation was larger for PCs in zebrin positive regions. Correlations between aspects of the complex spike waveform and simple spike activity were found, some of which varied between zebrin positive and negative PCs. The implications of the results are discussed with regard to hypotheses that complex spikes are triggered by rises in simple spike activity for either motor learning or homeostatic functions. Purkinje cells (PCs) generate two types of action potentials, called simple and complex spikes (SSs and CSs). We first investigated the CS-associated modulation of SS activity and its relationship to the zebrin status of the PC. The modulation pattern consisted of a pre-CS rise in SS activity, and then, following the CS, a pause, a rebound, and finally a late inhibition of SS activity for both zebrin positive (Z+) and negative (Z-) cells, though the amplitudes of the phases were larger in Z+ cells. Moreover, the amplitudes of the pre-CS rise with the late inhibitory phase of the modulation were correlated across PCs. In contrast, correlations between modulation phases across CSs of individual PCs were generally weak. Next, the relationship between CS spikelets and SS activity was investigated. The number of spikelets/CS correlated with the average SS firing rate only for Z+ cells. In contrast, correlations across CSs between spikelet numbers and the

Improved SpikeProp for Using Particle Swarm Optimization

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Falah Y. H. Ahmed

2013-01-01

Full Text Available A spiking neurons network encodes information in the timing of individual spike times. A novel supervised learning rule for SpikeProp is derived to overcome the discontinuities introduced by the spiking thresholding. This algorithm is based on an error-backpropagation learning rule suited for supervised learning of spiking neurons that use exact spike time coding. The SpikeProp is able to demonstrate the spiking neurons that can perform complex nonlinear classification in fast temporal coding. This study proposes enhancements of SpikeProp learning algorithm for supervised training of spiking networks which can deal with complex patterns. The proposed methods include the SpikeProp particle swarm optimization (PSO and angle driven dependency learning rate. These methods are presented to SpikeProp network for multilayer learning enhancement and weights optimization. Input and output patterns are encoded as spike trains of precisely timed spikes, and the network learns to transform the input trains into target output trains. With these enhancements, our proposed methods outperformed other conventional neural network architectures.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

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Qiang Yu

Full Text Available A new learning rule (Precise-Spike-Driven (PSD Synaptic Plasticity is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

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Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

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Daniel ede Santos-Sierra

2015-11-01

Full Text Available Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions cite{Pyragas}, where the slave neuron is able to anticipate in time the behaviour of the master one. In this paper we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI, one of the main features of the neural response associated to the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.

Science.gov (United States)

de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A; Navas, Adrian; Villacorta-Atienza, Jose A

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

Coronavirus spike-receptor interactions

NARCIS (Netherlands)

Mou, H.

2015-01-01

Coronaviruses cause important diseases in humans and animals. Coronavirus infection starts with the virus binding with its spike proteins to molecules present on the surface of host cells that act as receptors. This spike-receptor interaction is highly specific and determines the virus’ cell, tissue

Spike-based population coding and working memory.

Directory of Open Access Journals (Sweden)

Martin Boerlin

2011-02-01

Full Text Available Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.

Consensus-Based Sorting of Neuronal Spike Waveforms.

Science.gov (United States)

Fournier, Julien; Mueller, Christian M; Shein-Idelson, Mark; Hemberger, Mike; Laurent, Gilles

2016-01-01

Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be checked against independently obtained "ground truth" data. In most spike-sorting algorithms in use today, the optimality of a clustering solution is assessed relative to some assumption on the distribution of the spike shapes associated with a particular single unit (e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual validation. When the spatiotemporal waveforms of spikes from different cells overlap, the decision as to whether two spikes should be assigned to the same source can be quite subjective, if it is not based on reliable quantitative measures. We propose a new approach, whereby spike clusters are identified from the most consensual partition across an ensemble of clustering solutions. Using the variability of the clustering solutions across successive iterations of the same clustering algorithm (template matching based on K-means clusters), we estimate the probability of spikes being clustered together and identify groups of spikes that are not statistically distinguishable from one another. Thus, we identify spikes that are most likely to be clustered together and therefore correspond to consistent spike clusters. This method has the potential advantage that it does not rely on any model of the spike shapes. It also provides estimates of the proportion of misclassified spikes for each of the identified clusters. We tested our algorithm on several datasets for which there exists a ground truth (simultaneous intracellular data), and show that it performs close to the optimum reached by a support vector machine trained on the ground truth. We also show that the estimated rate of misclassification matches the proportion of misclassified spikes measured from the ground truth data.

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

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Huys, Raoul; Jirsa, Viktor K.; Darokhan, Ziauddin; Valentiniene, Sonata; Roland, Per E.

2016-01-01

Neurons in the primary visual cortex spontaneously spike even when there are no visual stimuli. It is unknown whether the spiking evoked by visual stimuli is just a modification of the spontaneous ongoing cortical spiking dynamics or whether the spontaneous spiking state disappears and is replaced by evoked spiking. This study of laminar recordings of spontaneous spiking and visually evoked spiking of neurons in the ferret primary visual cortex shows that the spiking dynamics does not change: the spontaneous spiking as well as evoked spiking is controlled by a stable and persisting fixed point attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization is that it avoids the need for a system reorganization following visual stimulation, and impedes the transition of spontaneous spiking to evoked spiking and the propagation of spontaneous spiking from layer 4 to layers 2–3. PMID:26778982

Spatially resolved element analysis of historical violin varnishes by use of muPIXE.

Science.gov (United States)

von Bohlen, Alex; Röhrs, Stefan; Salomon, Joseph

2007-02-01

External muPIXE has been used for characterisation of small samples of varnish from historical violins, and pieces of varnished wood from historical and modern stringed instruments. To obtain spatially resolved information about the distribution of elements across the varnish layers single-spot analysis, line-scans, and area-mapping were performed. Local resolution of approximately 20 mum was obtained from the 3 MeV, 1 nA proton micro-probe. Results from simultaneous multi-element determination of Na, Mg, Al, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Br, Rb, Sr, Ag, Cd, Sn, Ba, and Pb in historical varnishes are presented. Semi-quantitative evaluation of line-scans recorded on diverse historical varnishes is reported. The applied method is discussed in detail and the results obtained are critically reviewed and compared with those in the literature.

Spike voltage topography in temporal lobe epilepsy.

Science.gov (United States)

Asadi-Pooya, Ali A; Asadollahi, Marjan; Shimamoto, Shoichi; Lorenzo, Matthew; Sperling, Michael R

2016-07-15

We investigated the voltage topography of interictal spikes in patients with temporal lobe epilepsy (TLE) to see whether topography was related to etiology for TLE. Adults with TLE, who had epilepsy surgery for drug-resistant seizures from 2011 until 2014 at Jefferson Comprehensive Epilepsy Center were selected. Two groups of patients were studied: patients with mesial temporal sclerosis (MTS) on MRI and those with other MRI findings. The voltage topography maps of the interictal spikes at the peak were created using BESA software. We classified the interictal spikes as polar, basal, lateral, or others. Thirty-four patients were studied, from which the characteristics of 340 spikes were investigated. The most common type of spike orientation was others (186 spikes; 54.7%), followed by lateral (146; 42.9%), polar (5; 1.5%), and basal (3; 0.9%). Characteristics of the voltage topography maps of the spikes between the two groups of patients were somewhat different. Five spikes in patients with MTS had polar orientation, but none of the spikes in patients with other MRI findings had polar orientation (odds ratio=6.98, 95% confidence interval=0.38 to 127.38; p=0.07). Scalp topographic mapping of interictal spikes has the potential to offer different information than visual inspection alone. The present results do not allow an immediate clinical application of our findings; however, detecting a polar spike in a patient with TLE may increase the possibility of mesial temporal sclerosis as the underlying etiology. Copyright © 2016 Elsevier B.V. All rights reserved.

Multineuronal Spike Sequences Repeat with Millisecond Precision

Directory of Open Access Journals (Sweden)

Koki eMatsumoto

2013-06-01

Full Text Available Cortical microcircuits are nonrandomly wired by neurons. As a natural consequence, spikes emitted by microcircuits are also nonrandomly patterned in time and space. One of the prominent spike organizations is a repetition of fixed patterns of spike series across multiple neurons. However, several questions remain unsolved, including how precisely spike sequences repeat, how the sequences are spatially organized, how many neurons participate in sequences, and how different sequences are functionally linked. To address these questions, we monitored spontaneous spikes of hippocampal CA3 neurons ex vivo using a high-speed functional multineuron calcium imaging technique that allowed us to monitor spikes with millisecond resolution and to record the location of spiking and nonspiking neurons. Multineuronal spike sequences were overrepresented in spontaneous activity compared to the statistical chance level. Approximately 75% of neurons participated in at least one sequence during our observation period. The participants were sparsely dispersed and did not show specific spatial organization. The number of sequences relative to the chance level decreased when larger time frames were used to detect sequences. Thus, sequences were precise at the millisecond level. Sequences often shared common spikes with other sequences; parts of sequences were subsequently relayed by following sequences, generating complex chains of multiple sequences.

A frequency-based characterization of spiccato bowing in violin performance.

Science.gov (United States)

Shan, Gongbing; Visentin, Peter; Wooldridge, Luke; Wang, Changdong; Connolly, Dennis

2007-12-01

Performance of instrumental music requires high precision and the automisation of motor control to free the performer to focus on the artistic outcome. To acquire this high skill, training is experience-based, involves one-on-one instruction, and requires long hours of repetitive practice. This approach is consistent with a traditional model of vocational apprenticeship. Practice habits and long hours associated with training have been identified as sometimes contributing to high rates of vocational injury among musicians. This study explores violin performance, identifying generalizable perceptual markers to bridge the gap between science and experience in pedagogical methodology. Kinematic data were collected using 3-D motion capture. Dynamic modeling was used to specify internal loads. Eleven professional-level musicians were tested, ranging in age from 21 to 47 years (M = 36 yr., SD = 6). The study identified several motor-learning markers, speed-dependent motor control phases (increasing effort, optimization, and approaching physiological limits), string-dependent motor control, and an unexpected sympathetic resonance between the two arms, notwithstanding their very different functions. This study suggests that instrumental performance could be aided by identifying markers related to musical outcomes, performers' perceptions, and motor skill acquisition.

Spiking Neural P Systems with Communication on Request.

Science.gov (United States)

Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante

2017-12-01

Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

Self-control with spiking and non-spiking neural networks playing games.

Science.gov (United States)

Christodoulou, Chris; Banfield, Gaye; Cleanthous, Aristodemos

2010-01-01

Self-control can be defined as choosing a large delayed reward over a small immediate reward, while precommitment is the making of a choice with the specific aim of denying oneself future choices. Humans recognise that they have self-control problems and attempt to overcome them by applying precommitment. Problems in exercising self-control, suggest a conflict between cognition and motivation, which has been linked to competition between higher and lower brain functions (representing the frontal lobes and the limbic system respectively). This premise of an internal process conflict, lead to a behavioural model being proposed, based on which, we implemented a computational model for studying and explaining self-control through precommitment behaviour. Our model consists of two neural networks, initially non-spiking and then spiking ones, representing the higher and lower brain systems viewed as cooperating for the benefit of the organism. The non-spiking neural networks are of simple feed forward multilayer type with reinforcement learning, one with selective bootstrap weight update rule, which is seen as myopic, representing the lower brain and the other with the temporal difference weight update rule, which is seen as far-sighted, representing the higher brain. The spiking neural networks are implemented with leaky integrate-and-fire neurons with learning based on stochastic synaptic transmission. The differentiating element between the two brain centres in this implementation is based on the memory of past actions determined by an eligibility trace time constant. As the structure of the self-control problem can be likened to the Iterated Prisoner's Dilemma (IPD) game in that cooperation is to defection what self-control is to impulsiveness or what compromising is to insisting, we implemented the neural networks as two players, learning simultaneously but independently, competing in the IPD game. With a technique resembling the precommitment effect, whereby the

Memristors Empower Spiking Neurons With Stochasticity

KAUST Repository

Al-Shedivat, Maruan

2015-06-01

Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

Ion backscattering and X-ray investigations of violin varnish and wood

International Nuclear Information System (INIS)

Sigurd, D.; Tove, P.A.; Petersson, S.

1980-01-01

The use of Rutherford backscattering (RBS) of ions (i.e. α-particles) and excitation of characteristic X-rays by protons, for determining the elemental composition of the top layers of violin varnish and wood is described. The amount of elements such as C, O, Si, S, Ca, Cu, Fe, Ni, Zn, Pb has been measured, on the varnished and unvarnished sides of wood samples from old instrument makers such as A. Stradivari, G. Guarneri del Gesu, Santo Serafin, C. Tononi etc. Differences in both the shape of the RBS spectra and in the presence of different elements are found and discussed. The use of X-ray excitation by ions (i.e. protons) helps in assessing the presence of the different elements. X-ray investigations can be done with instruments in air while RBS (at least in the presently used form) has to be performed in a vacuum chamber. Apart from offering an aid in determining the materials and procedures which were used in fabricating acoustically excellent instruments, the method could be of value for identifying their authenticity. (orig.)

Ion backscattering and x-ray investigations of violin varnish and wood

Science.gov (United States)

Arne Tove, Per; Sigurd, Dag; Petersson, Sture

1980-01-01

The use of Rutherford backscattering (RBS) of ions (i.e. α-particles) and excitation of characteristic X-rays by protons, for determining the elemental composition of the top layers of violin varnish and wood is described. The amount of elements such as C, O, Si, S, Ca, Cu, Fe, Ni, Zn, Pb has been measured, on the varnished and unvarnished sides of wood samples from old instrument makers such as A. Stradivari, G. Guarneri del Gesu, Santo Serafin, C. Tononi etc. Differences in both the shape of the RBS spectra and in the presence of different elements are found and discussed. The use of X-ray excitation by ions (i.e. protons) helps in assessing the presence of the different elements. X-ray investigations can be done with instruments in air while RBS (at least in the presently used form) has to be performed in a vacuum chamber. Apart from offering an aid in determining the materials and procedures which were used in fabricating acoustically excellent instruments, the method could be of value for identifying their authenticity.

Non-orthogonally transitive G2 spike solution

International Nuclear Information System (INIS)

Lim, Woei Chet

2015-01-01

We generalize the orthogonally transitive (OT) G 2 spike solution to the non-OT G 2 case. This is achieved by applying Geroch’s transformation on a Kasner seed. The new solution contains two more parameters than the OT G 2 spike solution. Unlike the OT G 2 spike solution, the new solution always resolves its spike. (fast track communication)

Wavelet analysis of epileptic spikes

Science.gov (United States)

Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-05-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

Wavelet analysis of epileptic spikes

CERN Document Server

Latka, M; Kozik, A; West, B J; Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-01-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

Local flow measurements at the inlet spike tip of a Mach 3 supersonic cruise airplane

Science.gov (United States)

Johnson, H. J.; Montoya, E. J.

1973-01-01

The flow field at the left inlet spike tip of a YF-12A airplane was examined using at 26 deg included angle conical flow sensor to obtain measurements at free-stream Mach numbers from 1.6 to 3.0. Local flow angularity, Mach number, impact pressure, and mass flow were determined and compared with free-stream values. Local flow changes occurred at the same time as free-stream changes. The local flow usually approached the spike centerline from the upper outboard side because of spike cant and toe-in. Free-stream Mach number influenced the local flow angularity; as Mach number increased above 2.2, local angle of attack increased and local sideslip angle decreased. Local Mach number was generally 3 percent less than free-stream Mach number. Impact-pressure ratio and mass flow ratio increased as free-stream Mach number increased above 2.2, indicating a beneficial forebody compression effect. No degradation of the spike tip instrumentation was observed after more than 40 flights in the high-speed thermal environment encountered by the airplane. The sensor is rugged, simple, and sensitive to small flow changes. It can provide accurate imputs necessary to control an inlet.

Three dimensional motion capture applied to violin playing: A study on feasibility and characterization of the motor strategy.

Science.gov (United States)

Ancillao, Andrea; Savastano, Bernardo; Galli, Manuela; Albertini, Giorgio

2017-10-01

Playing string instruments requires advanced motor skills and a long training that is often spent in uncomfortable postures that may lead to injuries or musculoskeletal disorders. Thus, it is interesting to objectively characterize the motor strategy adopted by the players. In this work, we implemented a method for the quantitative analysis of the motor performance of a violin player. The proposed protocol takes advantage of an optoelectronic system and some infra-red reflecting markers in order to track player's motion. The method was tested on a professional violin player performing a legato bowing task. The biomechanical strategy of the upper limb and bow positioning were described by means of quantitative parameters and motion profiles. Measured quantities were: bow trajectory, angles, tracks, velocity, acceleration and jerk. A good repeatability of the bowing motion (CV < 2%) and high smoothness (jerk < 5 m/s 3 ) were observed. Motion profiles of shoulder, elbow and wrist were repeatable (CV < 7%) and comparable to the curves observed in other studies. Jerk and acceleration profiles demonstrated high smoothness in the ascending and descending phases of bowing. High variability was instead observed for the neck angle (CV ∼56%). "Quantitative" measurements, instead of "qualitative" observation, can support the diagnosis of motor disorders and the accurate evaluation of musicians' skills. The proposed protocol is a powerful tool for the description of musician's performance, that may be useful to document improvements in playing abilities and to adjust training strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

Motor control by precisely timed spike patterns

DEFF Research Database (Denmark)

Srivastava, Kyle H; Holmes, Caroline M; Vellema, Michiel

2017-01-01

whether the information in spike timing actually plays a role in brain function. By examining the activity of individual motor units (the muscle fibers innervated by a single motor neuron) and manipulating patterns of activation of these neurons, we provide both correlative and causal evidence......A fundamental problem in neuroscience is understanding how sequences of action potentials ("spikes") encode information about sensory signals and motor outputs. Although traditional theories assume that this information is conveyed by the total number of spikes fired within a specified time...... interval (spike rate), recent studies have shown that additional information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear...

Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering.

Science.gov (United States)

Hullman, Jessica; Resnick, Paul; Adar, Eytan

2015-01-01

Many visual depictions of probability distributions, such as error bars, are difficult for users to accurately interpret. We present and study an alternative representation, Hypothetical Outcome Plots (HOPs), that animates a finite set of individual draws. In contrast to the statistical background required to interpret many static representations of distributions, HOPs require relatively little background knowledge to interpret. Instead, HOPs enables viewers to infer properties of the distribution using mental processes like counting and integration. We conducted an experiment comparing HOPs to error bars and violin plots. With HOPs, people made much more accurate judgments about plots of two and three quantities. Accuracy was similar with all three representations for most questions about distributions of a single quantity.

Evidence for inhomogeneous thermal sources of two spike events of 1978, May 5 and December 4

International Nuclear Information System (INIS)

Wiehl, H.J.; Desai, U.

1982-09-01

Two short duration single spike events of 1978 May 5 and December 4 exhibit similar time profiles in the microwave and hard X-ray ranges, indicating emission from compact sources. Microwave spectral observations exhibit inhomogeneieties present in the source parameters. The existence of fine time structures in the microwave time profiles at 10.4 GHz from Berne are interpreted as a signature of the dynamics of a disturbance travelling through the souce at the ion-sound speed. Stereoscopic observations with the hard X-ray detector on the solar orbiter, Helios-2, and the Berne microwave antennae do not indicate any time lag or differences in the time profiles during the impulsive phase. This is taken as evidence for the absence of directionality of emission making beam models unlikely for short duration single spike events

Generalized activity equations for spiking neural network dynamics

Directory of Open Access Journals (Sweden)

Michael A Buice

2013-11-01

Full Text Available Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales - the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances.

Thin walled Nb tubes for suspending test masses in interferometric gravitational wave detectors

Energy Technology Data Exchange (ETDEWEB)

Lee, B.H. [School of Physics, University of Western Australia, Crawley 6009, WA (Australia)]. E-mail: bhl@physics.uwa.edu.au; Ju, L. [School of Physics, University of Western Australia, Crawley 6009, WA (Australia); Blair, D.G. [School of Physics, University of Western Australia, Crawley 6009, WA (Australia)

2006-02-13

In a previous Letter, we have shown that the use of orthogonal ribbons could provide a better mirror suspension technique in interferometric gravitational wave antennas. One of the key improvements presented by the orthogonal ribbon is the reduction in the number of violin string modes in the direction of the laser. We have considered more elaborate geometries in recent simulations and obtained a suspension that provides further reduction in the number of violin string modes in the direction of the laser, as well as in the direction orthogonal to the laser. This thin walled niobium tube suspension exhibits a reduction in the number of violin modes to 5 in each direction up to a frequency of 5 kHz. Furthermore, the violin mode thermal noise peaks can be reduced in amplitude by 30 dB.

Thin walled Nb tubes for suspending test masses in interferometric gravitational wave detectors

International Nuclear Information System (INIS)

Lee, B.H.; Ju, L.; Blair, D.G.

2006-01-01

In a previous Letter, we have shown that the use of orthogonal ribbons could provide a better mirror suspension technique in interferometric gravitational wave antennas. One of the key improvements presented by the orthogonal ribbon is the reduction in the number of violin string modes in the direction of the laser. We have considered more elaborate geometries in recent simulations and obtained a suspension that provides further reduction in the number of violin string modes in the direction of the laser, as well as in the direction orthogonal to the laser. This thin walled niobium tube suspension exhibits a reduction in the number of violin modes to 5 in each direction up to a frequency of 5 kHz. Furthermore, the violin mode thermal noise peaks can be reduced in amplitude by 30 dB

Epileptiform spike detection via convolutional neural networks

DEFF Research Database (Denmark)

Johansen, Alexander Rosenberg; Jin, Jing; Maszczyk, Tomasz

2016-01-01

The EEG of epileptic patients often contains sharp waveforms called "spikes", occurring between seizures. Detecting such spikes is crucial for diagnosing epilepsy. In this paper, we develop a convolutional neural network (CNN) for detecting spikes in EEG of epileptic patients in an automated...

Statistical properties of superimposed stationary spike trains.

Science.gov (United States)

Deger, Moritz; Helias, Moritz; Boucsein, Clemens; Rotter, Stefan

2012-06-01

The Poisson process is an often employed model for the activity of neuronal populations. It is known, though, that superpositions of realistic, non- Poisson spike trains are not in general Poisson processes, not even for large numbers of superimposed processes. Here we construct superimposed spike trains from intracellular in vivo recordings from rat neocortex neurons and compare their statistics to specific point process models. The constructed superimposed spike trains reveal strong deviations from the Poisson model. We find that superpositions of model spike trains that take the effective refractoriness of the neurons into account yield a much better description. A minimal model of this kind is the Poisson process with dead-time (PPD). For this process, and for superpositions thereof, we obtain analytical expressions for some second-order statistical quantities-like the count variability, inter-spike interval (ISI) variability and ISI correlations-and demonstrate the match with the in vivo data. We conclude that effective refractoriness is the key property that shapes the statistical properties of the superposition spike trains. We present new, efficient algorithms to generate superpositions of PPDs and of gamma processes that can be used to provide more realistic background input in simulations of networks of spiking neurons. Using these generators, we show in simulations that neurons which receive superimposed spike trains as input are highly sensitive for the statistical effects induced by neuronal refractoriness.

Learning Universal Computations with Spikes

Science.gov (United States)

Thalmeier, Dominik; Uhlmann, Marvin; Kappen, Hilbert J.; Memmesheimer, Raoul-Martin

2016-01-01

Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require previous building of intrinsic world models. Here we show how spiking neural networks may solve these different tasks. Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing. The networks contain dendritic or synaptic nonlinearities and have a constrained connectivity. We then combine such networks with learning rules for outputs or recurrent connections. We show that this allows to learn even difficult benchmark tasks such as the self-sustained generation of desired low-dimensional chaotic dynamics or memory-dependent computations. Furthermore, we show how spiking networks can build models of external world systems and use the acquired knowledge to control them. PMID:27309381

Spiking Neurons for Analysis of Patterns

Science.gov (United States)

Huntsberger, Terrance

2008-01-01

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological

The Omega-Infinity Limit of Single Spikes

CERN Document Server

Axenides, Minos; Linardopoulos, Georgios

A new infinite-size limit of strings in RxS2 is presented. The limit is obtained from single spike strings by letting their angular velocity omega become infinite. We derive the energy-momenta relation of omega-infinity single spikes as their linear velocity v-->1 and their angular momentum J-->1. Generally, the v-->1, J-->1 limit of single spikes is singular and has to be excluded from the spectrum and be studied separately. We discover that the dispersion relation of omega-infinity single spikes contains logarithms in the limit J-->1. This result is somewhat surprising, since the logarithmic behavior in the string spectra is typically associated with their motion in non-compact spaces such as AdS. Omega-infinity single spikes seem to completely cover the surface of the 2-sphere they occupy, so that they may essentially be viewed as some sort of "brany strings". A proof of the sphere-filling property of omega-infinity single spikes is given in the appendix.

Stress-Induced Impairment of a Working Memory Task: Role of Spiking Rate and Spiking History Predicted Discharge

Science.gov (United States)

Devilbiss, David M.; Jenison, Rick L.; Berridge, Craig W.

2012-01-01

Stress, pervasive in society, contributes to over half of all work place accidents a year and over time can contribute to a variety of psychiatric disorders including depression, schizophrenia, and post-traumatic stress disorder. Stress impairs higher cognitive processes, dependent on the prefrontal cortex (PFC) and that involve maintenance and integration of information over extended periods, including working memory and attention. Substantial evidence has demonstrated a relationship between patterns of PFC neuron spiking activity (action-potential discharge) and components of delayed-response tasks used to probe PFC-dependent cognitive function in rats and monkeys. During delay periods of these tasks, persistent spiking activity is posited to be essential for the maintenance of information for working memory and attention. However, the degree to which stress-induced impairment in PFC-dependent cognition involves changes in task-related spiking rates or the ability for PFC neurons to retain information over time remains unknown. In the current study, spiking activity was recorded from the medial PFC of rats performing a delayed-response task of working memory during acute noise stress (93 db). Spike history-predicted discharge (SHPD) for PFC neurons was quantified as a measure of the degree to which ongoing neuronal discharge can be predicted by past spiking activity and reflects the degree to which past information is retained by these neurons over time. We found that PFC neuron discharge is predicted by their past spiking patterns for nearly one second. Acute stress impaired SHPD, selectively during delay intervals of the task, and simultaneously impaired task performance. Despite the reduction in delay-related SHPD, stress increased delay-related spiking rates. These findings suggest that neural codes utilizing SHPD within PFC networks likely reflects an additional important neurophysiological mechanism for maintenance of past information over time. Stress

Spikes and matter inhomogeneities in massless scalar field models

International Nuclear Information System (INIS)

Coley, A A; Lim, W C

2016-01-01

We shall discuss the general relativistic generation of spikes in a massless scalar field or stiff perfect fluid model. We first investigate orthogonally transitive (OT) G 2 stiff fluid spike models both heuristically and numerically, and give a new exact OT G 2 stiff fluid spike solution. We then present a new two-parameter family of non-OT G 2 stiff fluid spike solutions, obtained by the generalization of non-OT G 2 vacuum spike solutions to the stiff fluid case by applying Geroch’s transformation on a Jacobs seed. The dynamics of these new stiff fluid spike solutions is qualitatively different from that of the vacuum spike solutions in that the matter (stiff fluid) feels the spike directly and the stiff fluid spike solution can end up with a permanent spike. We then derive the evolution equations of non-OT G 2 stiff fluid models, including a second perfect fluid, in full generality, and briefly discuss some of their qualitative properties and their potential numerical analysis. Finally, we discuss how a fluid, and especially a stiff fluid or massless scalar field, affects the physics of the generation of spikes. (paper)

Spiking neural P systems with multiple channels.

Science.gov (United States)

Peng, Hong; Yang, Jinyu; Wang, Jun; Wang, Tao; Sun, Zhang; Song, Xiaoxiao; Luo, Xiaohui; Huang, Xiangnian

2017-11-01

Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computing systems inspired from the neurophysiological behavior of biological spiking neurons. In this paper, we investigate a new variant of SNP systems in which each neuron has one or more synaptic channels, called spiking neural P systems with multiple channels (SNP-MC systems, in short). The spiking rules with channel label are introduced to handle the firing mechanism of neurons, where the channel labels indicate synaptic channels of transmitting the generated spikes. The computation power of SNP-MC systems is investigated. Specifically, we prove that SNP-MC systems are Turing universal as both number generating and number accepting devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Measurement of isotope abundance variations in nature by gravimetric spiking isotope dilution analysis (GS-IDA).

Science.gov (United States)

Chew, Gina; Walczyk, Thomas

2013-04-02

Subtle variations in the isotopic composition of elements carry unique information about physical and chemical processes in nature and are now exploited widely in diverse areas of research. Reliable measurement of natural isotope abundance variations is among the biggest challenges in inorganic mass spectrometry as they are highly sensitive to methodological bias. For decades, double spiking of the sample with a mix of two stable isotopes has been considered the reference technique for measuring such variations both by multicollector-inductively coupled plasma mass spectrometry (MC-ICPMS) and multicollector-thermal ionization mass spectrometry (MC-TIMS). However, this technique can only be applied to elements having at least four stable isotopes. Here we present a novel approach that requires measurement of three isotope signals only and which is more robust than the conventional double spiking technique. This became possible by gravimetric mixing of the sample with an isotopic spike in different proportions and by applying principles of isotope dilution for data analysis (GS-IDA). The potential and principle use of the technique is demonstrated for Mg in human urine using MC-TIMS for isotopic analysis. Mg is an element inaccessible to double spiking methods as it consists of three stable isotopes only and shows great potential for metabolically induced isotope effects waiting to be explored.

Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering.

Directory of Open Access Journals (Sweden)

Jessica Hullman

Full Text Available Many visual depictions of probability distributions, such as error bars, are difficult for users to accurately interpret. We present and study an alternative representation, Hypothetical Outcome Plots (HOPs, that animates a finite set of individual draws. In contrast to the statistical background required to interpret many static representations of distributions, HOPs require relatively little background knowledge to interpret. Instead, HOPs enables viewers to infer properties of the distribution using mental processes like counting and integration. We conducted an experiment comparing HOPs to error bars and violin plots. With HOPs, people made much more accurate judgments about plots of two and three quantities. Accuracy was similar with all three representations for most questions about distributions of a single quantity.

Measurement of the delta34S value in methionine by double spike multi-collector thermal ionization mass spectrometry using Carius tube digestion.

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Mann, Jacqueline L; Kelly, W Robert

2010-09-15

Methionine is an essential amino acid and is the primary source of sulfur for humans. Using the double spike ((33)S-(36)S) multi-collector thermal ionization mass spectrometry (MC-TIMS) technique, three sample bottles of a methionine material obtained from the Institute for Reference Materials and Measurements have been measured for delta(34)S and sulfur concentration. The mean delta(34)S value, relative to Vienna Canyon Diablo Troilite (VCDT), determined was 10.34 +/- 0.11 per thousand (n = 9) with the uncertainty reported as expanded uncertainties (U). These delta(34)S measurements include a correction for blank which has been previously ignored in studies of sulfur isotopic composition. The sulfur concentrations for the three bottles range from 56 to 88 microg/g. The isotope composition and concentration results demonstrate the high accuracy and precision of the DS-MC-TIMS technique for measuring sulfur in methionine.

Left hand finger force in violin playing: tempo, loudness, and finger differences.

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Kinoshita, Hiroshi; Obata, Satoshi

2009-07-01

A three-dimensional force transducer was installed in the neck of a violin under the A string at the D5 position in order to study the force with which the violinist clamps the string against the fingerboard under normal playing conditions. Violinists performed repetitive sequences of open A- and fingered D-tones using the ring finger at tempi of 1, 2, 4, 8, and 16 notes/s at mezzo-forte. At selected tempi, the effects of dynamic level and the use of different fingers were investigated as well. The force profiles were clearly dependent on tempo and dynamic level. At slow tempi, the force profiles were characterized by an initial pulse followed by a level force to the end of the finger contact period. At tempi higher than 2 Hz, only pulsed profiles were observed. The peak force exceeded 4.5 N at 1 and 2 Hz and decreased to 1.7 N at 16 Hz. All force and impulse values were lower at softer dynamic levels, and when using the ring or little finger compared to the index finger.

A multi-technique chemical characterization of a Stradivari decorated violin top plate

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Malagodi, M.; Canevari, C.; Bonizzoni, L.; Galli, A.; Maspero, F.; Martini, M.

2013-08-01

This paper focuses on the characterization of the materials of a violin top plate made by Antonio Stradivari (17th century), with different diagnostic techniques and with an integrated and non-destructive analytical methodology to study surface coatings and decorations. The UV-induced visible fluorescence, optical digital microscopy, ED-XRF associated with micro-FTIR spectroscopy analysis, and dendrochronology were performed. The investigations were aimed to identify the presence of original varnish layers and to characterize the composition of the decorations, either the inlaid purflings or the composite false-inlay strip between them. Several results were achieved: (i) evidence of the absence of varnish layers on the surface as a result of extended and inappropriate restoring; (ii) identification of the dye used for the black layers of the purflings; (iii) characterization of the black matrix and the white elements of the decoration. Furthermore, a dendrochronological dating was performed. A copy of the top plate was realized with materials similar to those identified on the Stradivari original; the same analyses performed on the original model were carried out on the same areas of the copy.

Geomagnetic spikes on the core-mantle boundary

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Davies, C. J.; Constable, C.

2017-12-01

Extreme variations of Earth's magnetic field occurred in the Levantine region around 1000 BC, where the field intensity rose and fell by a factor of 2-3 over a short time and confined spatial region. There is presently no coherent link between this intensity spike and the generating processes in Earth's liquid core. Here we test the attribution of a surface spike to a flux patch visible on the core-mantle boundary (CMB), calculating geometric and energetic bounds on resulting surface geomagnetic features. We show that the Levantine intensity high must span at least 60 degrees in longitude. Models providing the best trade-off between matching surface spike intensity, minimizing L1 and L2 misfit to the available data and satisfying core energy constraints produce CMB spikes 8-22 degrees wide with peak values of O(100) mT. We propose that the Levantine spike grew in place before migrating northward and westward, contributing to the growth of the axial dipole field seen in Holocene field models. Estimates of Ohmic dissipation suggest that diffusive processes, which are often neglected, likely govern the ultimate decay of geomagnetic spikes. Using these results, we search for the presence of spike-like features in geodynamo simulations.

Bursts generate a non-reducible spike-pattern code

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Hugo G Eyherabide

2009-05-01

Full Text Available On the single-neuron level, precisely timed spikes can either constitute firing-rate codes or spike-pattern codes that utilize the relative timing between consecutive spikes. There has been little experimental support for the hypothesis that such temporal patterns contribute substantially to information transmission. Using grasshopper auditory receptors as a model system, we show that correlations between spikes can be used to represent behaviorally relevant stimuli. The correlations reflect the inner structure of the spike train: a succession of burst-like patterns. We demonstrate that bursts with different spike counts encode different stimulus features, such that about 20% of the transmitted information corresponds to discriminating between different features, and the remaining 80% is used to allocate these features in time. In this spike-pattern code, the "what" and the "when" of the stimuli are encoded in the duration of each burst and the time of burst onset, respectively. Given the ubiquity of burst firing, we expect similar findings also for other neural systems.

Stochastic Variational Learning in Recurrent Spiking Networks

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Danilo eJimenez Rezende

2014-04-01

Full Text Available The ability to learn and perform statistical inference with biologically plausible recurrent network of spiking neurons is an important step towards understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators conveying information about ``novelty on a statistically rigorous ground.Simulations show that our model is able to learn bothstationary and non-stationary patterns of spike trains.We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

Stochastic variational learning in recurrent spiking networks.

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Jimenez Rezende, Danilo; Gerstner, Wulfram

2014-01-01

The ability to learn and perform statistical inference with biologically plausible recurrent networks of spiking neurons is an important step toward understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators) conveying information about "novelty" on a statistically rigorous ground. Simulations show that our model is able to learn both stationary and non-stationary patterns of spike trains. We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

Determination of (187)Os in molybdenite by ICP-MS with neutron-induced (186)Os and (188)Os spikes.

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Qu, W; Du, A; Zhao, D

2001-10-31

The article describes a method for the determination of (187)Os in molybdenite by isotope dilution inductively coupled plasma-mass spectrometry (ID-ICP-MS) with neutron-induced (186)Os and (188)Os spike. The spike used in the present work was prepared in line with the principle by which artificial nuclides are produced in a nuclear reaction. The concentration and isotopic composition of osmium in the prepared spike were evaluated accurately with the isotope dilution method, using negative thermal ion mass spectrometry (N-TIMS). The advantage of this method is that using (186)Os and (188)Os double spikes can effectively compensate for the mass discrimination effects of ICP-MS. Thus, the common correction practice for mass bias in the isotope dilution method with a single spike is unnecessary. In addition, the method enables one to reduce the determined error arising from instrumental instability. The precision for the (187)Os/((186)Os+(188)Os) ratio was approximately 2% (2sigma, RSD), but in the case of (187)Os/(186)Os, (187)Os/(188)Os and (186)Os/(188)Os, precision ranged from 2.0 to 8% (2sigma, RSD). The results for (187)Os concentration in a molybdenite sample determined with this method showed good agreement with reference values.

A thermal modelling of displacement cascades in uranium dioxide

Energy Technology Data Exchange (ETDEWEB)

Martin, G., E-mail: guillaume.martin@cea.fr [CEA – DEN/DEC/SESC/LLCC, Bât. 352, 13108 Saint-Paul-Lez-Durance Cedex (France); Garcia, P.; Sabathier, C. [CEA – DEN/DEC/SESC/LLCC, Bât. 352, 13108 Saint-Paul-Lez-Durance Cedex (France); Devynck, F.; Krack, M. [Laboratory for Reactor Physics and Systems Behaviour, Paul Scherrer Institute, CH-5232 Villigen PSI (Switzerland); Maillard, S. [CEA – DEN/DEC/SESC/LLCC, Bât. 352, 13108 Saint-Paul-Lez-Durance Cedex (France)

2014-05-01

The space and time dependent temperature distribution was studied in uranium dioxide during displacement cascades simulated by classical molecular dynamics (MD). The energy for each simulated radiation event ranged between 0.2 keV and 20 keV in cells at initial temperatures of 700 K or 1400 K. Spheres into which atomic velocities were rescaled (thermal spikes) have also been simulated by MD to simulate the thermal excitation induced by displacement cascades. Equipartition of energy was shown to occur in displacement cascades, half of the kinetic energy of the primary knock-on atom being converted after a few tenths of picoseconds into potential energy. The kinetic and potential parts of the system energy are however subjected to little variations during dedicated thermal spike simulations. This is probably due to the velocity rescaling process, which impacts a large number of atoms in this case and would drive the system away from a dynamical equilibrium. This result makes questionable MD simulations of thermal spikes carried out up to now (early 2014). The thermal history of cascades was compared to the heat equation solution of a punctual thermal excitation in UO{sub 2}. The maximum volume brought to a temperature above the melting temperature during the simulated cascade events is well reproduced by this simple model. This volume eventually constitutes a relevant estimate of the volume affected by a displacement cascade in UO{sub 2}. This definition of the cascade volume could also make sense in other materials, like iron.

Inferring oscillatory modulation in neural spike trains.

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Arai, Kensuke; Kass, Robert E

2017-10-01

Oscillations are observed at various frequency bands in continuous-valued neural recordings like the electroencephalogram (EEG) and local field potential (LFP) in bulk brain matter, and analysis of spike-field coherence reveals that spiking of single neurons often occurs at certain phases of the global oscillation. Oscillatory modulation has been examined in relation to continuous-valued oscillatory signals, and independently from the spike train alone, but behavior or stimulus triggered firing-rate modulation, spiking sparseness, presence of slow modulation not locked to stimuli and irregular oscillations with large variability in oscillatory periods, present challenges to searching for temporal structures present in the spike train. In order to study oscillatory modulation in real data collected under a variety of experimental conditions, we describe a flexible point-process framework we call the Latent Oscillatory Spike Train (LOST) model to decompose the instantaneous firing rate in biologically and behaviorally relevant factors: spiking refractoriness, event-locked firing rate non-stationarity, and trial-to-trial variability accounted for by baseline offset and a stochastic oscillatory modulation. We also extend the LOST model to accommodate changes in the modulatory structure over the duration of the experiment, and thereby discover trial-to-trial variability in the spike-field coherence of a rat primary motor cortical neuron to the LFP theta rhythm. Because LOST incorporates a latent stochastic auto-regressive term, LOST is able to detect oscillations when the firing rate is low, the modulation is weak, and when the modulating oscillation has a broad spectral peak.

The motor system plays the violin: a musical metaphor inferred from the oscillatory activity of the α-motoneuron pools during locomotion.

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Chiovetto, Enrico

2011-04-01

Despite substantial advances in the field, particularly resulting from physiological studies in animals, the neural mechanisms underlying the generation of many motor behaviors in humans remain unclear. A recent study (Cappellini G et al. J Neurophysiol 104: 3064-3073, 2010) sheds more light on this topic. Like the string of a violin, the α-motoneuron pools in the spinal cord during locomotion show continuous and oscillatory patterns of activation. In this report, the implications and relevance of this finding are discussed in a general framework that includes neurophysiology, optimal control theory, and robotics.

The local field potential reflects surplus spike synchrony

DEFF Research Database (Denmark)

Denker, Michael; Roux, Sébastien; Lindén, Henrik

2011-01-01

While oscillations of the local field potential (LFP) are commonly attributed to the synchronization of neuronal firing rate on the same time scale, their relationship to coincident spiking in the millisecond range is unknown. Here, we present experimental evidence to reconcile the notions...... of synchrony at the level of spiking and at the mesoscopic scale. We demonstrate that only in time intervals of significant spike synchrony that cannot be explained on the basis of firing rates, coincident spikes are better phase locked to the LFP than predicted by the locking of the individual spikes....... This effect is enhanced in periods of large LFP amplitudes. A quantitative model explains the LFP dynamics by the orchestrated spiking activity in neuronal groups that contribute the observed surplus synchrony. From the correlation analysis, we infer that neurons participate in different constellations...

Supervised Learning Based on Temporal Coding in Spiking Neural Networks.

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Mostafa, Hesham

2017-08-01

Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input-output relation is differentiable almost everywhere. Moreover, this relation is piecewise linear after a transformation of variables. Methods for training ANNs thus carry directly to the training of such spiking networks as we show when training on the permutation invariant MNIST task. In contrast to rate-based spiking networks that are often used to approximate the behavior of ANNs, the networks we present spike much more sparsely and their behavior cannot be directly approximated by conventional ANNs. Our results highlight a new approach for controlling the behavior of spiking networks with realistic temporal dynamics, opening up the potential for using these networks to process spike patterns with complex temporal information.

Linking investment spikes and productivity growth

NARCIS (Netherlands)

Geylani, P.C.; Stefanou, S.E.

2013-01-01

We investigate the relationship between productivity growth and investment spikes using Census Bureau’s plant-level dataset for the U.S. food manufacturing industry. There are differences in productivity growth and investment spike patterns across different sub-industries and food manufacturing

A new supervised learning algorithm for spiking neurons.

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Xu, Yan; Zeng, Xiaoqin; Zhong, Shuiming

2013-06-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the running process of the neuron through adjusting synaptic weights, which can be regarded as a classification problem. Based on this idea, this letter proposes a new supervised learning method for spiking neurons with temporal encoding; it first transforms the supervised learning into a classification problem and then solves the problem by using the perceptron learning rule. The experiment results show that the proposed method has higher learning accuracy and efficiency over the existing learning methods, so it is more powerful for solving complex and real-time problems.

Solving constraint satisfaction problems with networks of spiking neurons

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Zeno eJonke

2016-03-01

Full Text Available Network of neurons in the brain apply – unlike processors in our current generation ofcomputer hardware – an event-based processing strategy, where short pulses (spikes areemitted sparsely by neurons to signal the occurrence of an event at a particular point intime. Such spike-based computations promise to be substantially more power-efficient thantraditional clocked processing schemes. However it turned out to be surprisingly difficult todesign networks of spiking neurons that can solve difficult computational problems on the levelof single spikes (rather than rates of spikes. We present here a new method for designingnetworks of spiking neurons via an energy function. Furthermore we show how the energyfunction of a network of stochastically firing neurons can be shaped in a quite transparentmanner by composing the networks of simple stereotypical network motifs. We show that thisdesign approach enables networks of spiking neurons to produce approximate solutions todifficult (NP-hard constraint satisfaction problems from the domains of planning/optimizationand verification/logical inference. The resulting networks employ noise as a computationalresource. Nevertheless the timing of spikes (rather than just spike rates plays an essential rolein their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines and Gibbs sampling.

Surfing a spike wave down the ventral stream.

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VanRullen, Rufin; Thorpe, Simon J

2002-10-01

Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the absolute or relative timing of spikes in spike trains. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of one such code and its relevance for visual processing. In a unified framework where the relation between stimulus saliency and spike relative timing plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure: the most salient information is represented by the first spikes over the population. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i). the selectivity of the cortical neurons, (ii). lateral interactions and (iii). top-down attentional influences from higher order cortical areas. The resulting model could account for the remarkable efficiency and rapidity of processing observed in the primate visual system.

AMORE Mo-99 Spike Test Results

Energy Technology Data Exchange (ETDEWEB)

Youker, Amanda J. [Argonne National Lab. (ANL), Argonne, IL (United States); Krebs, John F. [Argonne National Lab. (ANL), Argonne, IL (United States); Quigley, Kevin J. [Argonne National Lab. (ANL), Argonne, IL (United States); Byrnes, James P. [Argonne National Lab. (ANL), Argonne, IL (United States); Rotsch, David A [Argonne National Lab. (ANL), Argonne, IL (United States); Brossard, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States); Wesolowski, Kenneth [Argonne National Lab. (ANL), Argonne, IL (United States); Alford, Kurt [Argonne National Lab. (ANL), Argonne, IL (United States); Chemerisov, Sergey [Argonne National Lab. (ANL), Argonne, IL (United States); Vandegrift, George F. [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-09-27

With funding from the National Nuclear Security Administrations Material Management and Minimization Office, Argonne National Laboratory (Argonne) is providing technical assistance to help accelerate the U.S. production of Mo-99 using a non-highly enriched uranium (non-HEU) source. A potential Mo-99 production pathway is by accelerator-initiated fissioning in a subcritical uranyl sulfate solution containing low enriched uranium (LEU). As part of the Argonne development effort, we are undertaking the AMORE (Argonne Molybdenum Research Experiment) project, which is essentially a pilot facility for all phases of Mo-99 production, recovery, and purification. Production of Mo-99 and other fission products in the subcritical target solution is initiated by putting an electron beam on a depleted uranium (DU) target; the fast neutrons produced in the DU target are thermalized and lead to fissioning of U-235. At the end of irradiation, Mo is recovered from the target solution and separated from uranium and most of the fission products by using a titania column. The Mo is stripped from the column with an alkaline solution. After acidification of the Mo product solution from the recovery column, the Mo is concentrated (and further purified) in a second titania column. The strip solution from the concentration column is then purified with the LEU Modified Cintichem process. A full description of the process can be found elsewhere [1–3]. The initial commissioning steps for the AMORE project include performing a Mo-99 spike test with pH 1 sulfuric acid in the target vessel without a beam on the target to demonstrate the initial Mo separation-and-recovery process, followed by the concentration column process. All glovebox operations were tested with cold solutions prior to performing the Mo-99 spike tests. Two Mo-99 spike tests with pH 1 sulfuric acid have been performed to date. Figure 1 shows the flow diagram for the remotely operated Mo-recovery system for the AMORE project

Three dimensional mathematical modeling of violin plate surfaces: An approach based on an ensemble of contour lines.

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Piantadosi, Steven

2017-01-01

This paper presents an approach to describing the three dimensional shape of a violin plate in mathematical form. The shape description begins with standard contour lines and ends with an equation for a surface in three dimensional space. The traditional specification of cross sectional arching is unnecessary. Advantages of this approach are that it employs simple and universal description of plate geometry and yields a complete, smoothed, precise mathematical equation of the plate that is suitable for modern three dimensional production. It is quite general and suitable for both exterior and interior plate surfaces, yielding the ability to control thicknesses along with shape. This method can produce mathematical descriptions with tolerances easily less than 0.001 millimeters suitable for modern computerized numerical control carving and hand finishing.

Spike timing precision of neuronal circuits.

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Kilinc, Deniz; Demir, Alper

2018-04-17

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

Causal Inference and Explaining Away in a Spiking Network

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Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

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Fernando Perez-Peña

2013-11-01

Full Text Available In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM. All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6 and power requirements (3.4 W to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6. It also evidences the suitable use of AER as a communication protocol between processing and actuation.

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

Science.gov (United States)

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-01-01

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation. PMID:24264330

Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

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Zedong Bi

2016-08-01

Full Text Available Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded, by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy.

Joint Probability-Based Neuronal Spike Train Classification

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Yan Chen

2009-01-01

Full Text Available Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs. The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.

Fitting neuron models to spike trains

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Cyrille eRossant

2011-02-01

Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

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Pietro Quaglio

2017-05-01

Full Text Available Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs. STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons. In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST. We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE analysis.

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

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Schwemmer, Michael A; Fairhall, Adrienne L; Denéve, Sophie; Shea-Brown, Eric T

2015-07-15

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation. We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks

A Simple Deep Learning Method for Neuronal Spike Sorting

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Yang, Kai; Wu, Haifeng; Zeng, Yu

2017-10-01

Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

The player and the bowed string: coordination of bowing parameters in violin and viola performance.

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Schoonderwaldt, E

2009-11-01

An experiment was conducted with four violin and viola players, measuring their bowing performance using an optical motion capture system and sensors on the bow. The measurements allowed for a detailed analysis of the use and coordination of the main bowing parameters bow velocity, bow force, and bow-bridge distance. An analysis of bowing strategies in detache playing of notes of three durations (0.2, 2, and 4 s) at three dynamic levels (pp, mf, and f) on all four strings is presented, focusing on the "steady" part of the notes. The results revealed clear trends in the coordinated variations of the bowing parameters depending on the constraints of the task, reflecting a common behavior as well as individual strategies. Furthermore, there were clear indications that the players adapted the bowing parameters to the physical properties of the string and the instrument, respecting the limits of the playable control parameter space.

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.

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Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang

2016-01-01

Network of neurons in the brain apply-unlike processors in our current generation of computer hardware-an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines) and Gibbs sampling.

Recent progress in multi-electrode spike sorting methods.

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Lefebvre, Baptiste; Yger, Pierre; Marre, Olivier

2016-11-01

In recent years, arrays of extracellular electrodes have been developed and manufactured to record simultaneously from hundreds of electrodes packed with a high density. These recordings should allow neuroscientists to reconstruct the individual activity of the neurons spiking in the vicinity of these electrodes, with the help of signal processing algorithms. Algorithms need to solve a source separation problem, also known as spike sorting. However, these new devices challenge the classical way to do spike sorting. Here we review different methods that have been developed to sort spikes from these large-scale recordings. We describe the common properties of these algorithms, as well as their main differences. Finally, we outline the issues that remain to be solved by future spike sorting algorithms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multineuron spike train analysis with R-convolution linear combination kernel.

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Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially polluted soil

DEFF Research Database (Denmark)

Ottosen, Lisbeth M.; Lepkova, Katarina; Kubal, Martin

2006-01-01

Electrokinetic remediation methods for removal of heavy metals from polluted soils have been subjected for quite intense research during the past years since these methods are well suitable for fine-grained soils where other remediation methods fail. Electrodialytic remediation is an electrokinetic...... remediation method which is based on applying an electric DC field and the use of ion exchange membranes that ensures the main transport of heavy metals to be out of the pollutes soil. An experimental investigation was made with electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially...... polluted soil under the same operational conditions (constant current density 0.2 mA/cm2 and duration 28 days). The results of the present paper show that caution must be taken when generalising results obtained in spiked kaolinite to remediation of industrially polluted soils, as it was shown...

Toxicity of nickel-spiked freshwater sediments to benthic invertebrates-Spiking methodology, species sensitivity, and nickel bioavailability

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Besser, John M.; Brumbaugh, William G.; Kemble, Nile E.; Ivey, Chris D.; Kunz, James L.; Ingersoll, Christopher G.; Rudel, David

2011-01-01

This report summarizes data from studies of the toxicity and bioavailability of nickel in nickel-spiked freshwater sediments. The goal of these studies was to generate toxicity and chemistry data to support development of broadly applicable sediment quality guidelines for nickel. The studies were conducted as three tasks, which are presented here as three chapters: Task 1, Development of methods for preparation and toxicity testing of nickel-spiked freshwater sediments; Task 2, Sensitivity of benthic invertebrates to toxicity of nickel-spiked freshwater sediments; and Task 3, Effect of sediment characteristics on nickel bioavailability. Appendices with additional methodological details and raw chemistry and toxicity data for the three tasks are available online at http://pubs.usgs.gov/sir/2011/5225/downloads/.

Playing a 3-Stringed Violin: Innovation via the Joint Evolution of People, Process, and Knowledge Management System

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Cooper, Lynne P.

2010-01-01

Users continuously evaluate the value and performance of their Knowledge Management Systems (KMS). As suggested by a punctuated socio-technical system process model, today's success can quickly become tomorrow's failure should the KMS fail to meet evolving needs and expectations. The more deeply a tool is embedded in the actual work process, the more vulnerable it is to emergent changes and perturbations. This paper uses the metaphor of a "3-stringed violin" to explore how differing levels of user knowledge about tools and processes can lead to system perturbations and how the active involvement of other actors can dampen the impact of perturbations, i.e., help the system survive the operational equivalent of a broken string. Recommendations suggest ways to increase system resiliency and contribute to incremental innovation.

ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms.

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Hagen, Espen; Ness, Torbjørn V; Khosrowshahi, Amir; Sørensen, Christina; Fyhn, Marianne; Hafting, Torkel; Franke, Felix; Einevoll, Gaute T

2015-04-30

New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times. We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy. ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval. ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers. ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Use of Linkage Technique in Johannes Brahms’ op. 78 and Leopoldo Miguéz’s op.14 Violin Sonatas

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Desirée Johanna Mesquita Mayr

2016-11-01

Full Text Available This paper specifically addresses linkage, a characteristically Brahmsian technique employed in the formation of musical ideas through the gradual transformation of precedent elements, being considered an indicator in the use of developing variation. After a detailed review of the literature encompassing definitions, classification and exemplification considering works of three theorists (FRISCH, 1984. SMITH, 2007. RAHN, 2015, an original proposal for a typology of linkage is presented. We compare a special occurrence of linkage in Brahms’ Violin Sonata, op. 78 to two similar occurrences in Leopoldo Miguéz’s sonata op. 14, a work of the same genre.. The results reinforce the hypothesis that Miguéz had employed organic constructive processes in his piece.

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

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Huys, Raoul; Jirsa, Viktor K; Darokhan, Ziauddin

2016-01-01

attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization...

Multichannel interictal spike activity detection using time-frequency entropy measure.

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Thanaraj, Palani; Parvathavarthini, B

2017-06-01

Localization of interictal spikes is an important clinical step in the pre-surgical assessment of pharmacoresistant epileptic patients. The manual selection of interictal spike periods is cumbersome and involves a considerable amount of analysis workload for the physician. The primary focus of this paper is to automate the detection of interictal spikes for clinical applications in epilepsy localization. The epilepsy localization procedure involves detection of spikes in a multichannel EEG epoch. Therefore, a multichannel Time-Frequency (T-F) entropy measure is proposed to extract features related to the interictal spike activity. Least squares support vector machine is used to train the proposed feature to classify the EEG epochs as either normal or interictal spike period. The proposed T-F entropy measure, when validated with epilepsy dataset of 15 patients, shows an interictal spike classification accuracy of 91.20%, sensitivity of 100% and specificity of 84.23%. Moreover, the area under the curve of Receiver Operating Characteristics plot of 0.9339 shows the superior classification performance of the proposed T-F entropy measure. The results of this paper show a good spike detection accuracy without any prior information about the spike morphology.

Training Deep Spiking Neural Networks Using Backpropagation.

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Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

2016-01-01

Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

Spike Code Flow in Cultured Neuronal Networks.

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Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

2016-01-01

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Grain price spikes and beggar-thy-neighbor policy responses

DEFF Research Database (Denmark)

Jensen, Hans Grinsted; Anderson, Kym

2017-01-01

When prices spike in international grain markets, national governments often reduce the extent to which that spike affects their domestic food markets. Those actions exacerbate the price spike and international welfare transfer associated with that terms of trade change. Several recent analyses...

Spike sorting for polytrodes: a divide and conquer approach

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Nicholas V. Swindale

2014-02-01

Full Text Available In order to determine patterns of neural activity, spike signals recorded by extracellular electrodes have to be clustered (sorted with the aim of ensuring that each cluster represents all the spikes generated by an individual neuron. Many methods for spike sorting have been proposed but few are easily applicable to recordings from polytrodes which may have 16 or more recording sites. As with tetrodes, these are spaced sufficiently closely that signals from single neurons will usually be recorded on several adjacent sites. Although this offers a better chance of distinguishing neurons with similarly shaped spikes, sorting is difficult in such cases because of the high dimensionality of the space in which the signals must be classified. This report details a method for spike sorting based on a divide and conquer approach. Clusters are initially formed by assigning each event to the channel on which it is largest. Each channel-based cluster is then sub-divided into as many distinct clusters as possible. These are then recombined on the basis of pairwise tests into a final set of clusters. Pairwise tests are also performed to establish how distinct each cluster is from the others. A modified gradient ascent clustering (GAC algorithm is used to do the clustering. The method can sort spikes with minimal user input in times comparable to real time for recordings lasting up to 45 minutes. Our results illustrate some of the difficulties inherent in spike sorting, including changes in spike shape over time. We show that some physiologically distinct units may have very similar spike shapes. We show that RMS measures of spike shape similarity are not sensitive enough to discriminate clusters that can otherwise be separated by principal components analysis. Hence spike sorting based on least-squares matching to templates may be unreliable. Our methods should be applicable to tetrodes and scaleable to larger multi-electrode arrays (MEAs.

Deciphering neuronal population codes for acute thermal pain

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Chen, Zhe; Zhang, Qiaosheng; Phuong Sieu Tong, Ai; Manders, Toby R.; Wang, Jing

2017-06-01

Objective. Pain is defined as an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage. Current pain research mostly focuses on molecular and synaptic changes at the spinal and peripheral levels. However, a complete understanding of pain mechanisms requires the physiological study of the neocortex. Our goal is to apply a neural decoding approach to read out the onset of acute thermal pain signals, which can be used for brain-machine interface. Approach. We used micro wire arrays to record ensemble neuronal activities from the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC) in freely behaving rats. We further investigated neural codes for acute thermal pain at both single-cell and population levels. To detect the onset of acute thermal pain signals, we developed a novel latent state-space framework to decipher the sorted or unsorted S1 and ACC ensemble spike activities, which reveal information about the onset of pain signals. Main results. The state space analysis allows us to uncover a latent state process that drives the observed ensemble spike activity, and to further detect the ‘neuronal threshold’ for acute thermal pain on a single-trial basis. Our method achieved good detection performance in sensitivity and specificity. In addition, our results suggested that an optimal strategy for detecting the onset of acute thermal pain signals may be based on combined evidence from S1 and ACC population codes. Significance. Our study is the first to detect the onset of acute pain signals based on neuronal ensemble spike activity. It is important from a mechanistic viewpoint as it relates to the significance of S1 and ACC activities in the regulation of the acute pain onset.

Introduction to spiking neural networks: Information processing, learning and applications.

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Ponulak, Filip; Kasinski, Andrzej

2011-01-01

The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

Neuronal spike sorting based on radial basis function neural networks

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Taghavi Kani M

2011-02-01

Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.

Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation.

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Doron, Guy; von Heimendahl, Moritz; Schlattmann, Peter; Houweling, Arthur R; Brecht, Michael

2014-02-05

The action potential activity of single cortical neurons can evoke measurable sensory effects, but it is not known how spiking parameters and neuronal subtypes affect the evoked sensations. Here, we examined the effects of spike train irregularity, spike frequency, and spike number on the detectability of single-neuron stimulation in rat somatosensory cortex. For regular-spiking, putative excitatory neurons, detectability increased with spike train irregularity and decreasing spike frequencies but was not affected by spike number. Stimulation of single, fast-spiking, putative inhibitory neurons led to a larger sensory effect compared to regular-spiking neurons, and the effect size depended only on spike irregularity. An ideal-observer analysis suggests that, under our experimental conditions, rats were using integration windows of a few hundred milliseconds or more. Our data imply that the behaving animal is sensitive to single neurons' spikes and even to their temporal patterning. Copyright © 2014 Elsevier Inc. All rights reserved.

Error-backpropagation in temporally encoded networks of spiking neurons

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractFor a network of spiking neurons that encodes information in the timing of individual spike-times, we derive a supervised learning rule, emph{SpikeProp, akin to traditional error-backpropagation and show how to overcome the discontinuities introduced by thresholding. With this algorithm,

Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. I: Spike Generating Models on Converging Motifs

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Zedong eBi

2016-02-01

Full Text Available In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis. Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e. synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons. Neurons (including the post-synaptic neuron in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1 synchronous firing and burstiness tend to increase DiffV, (2 heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3 heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our

Mimickers of generalized spike and wave discharges.

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Azzam, Raed; Bhatt, Amar B

2014-06-01

Overinterpretation of benign EEG variants is a common problem that can lead to the misdiagnosis of epilepsy. We review four normal patterns that mimic generalized spike and wave discharges: phantom spike-and-wave, hyperventilation hypersynchrony, hypnagogic/ hypnopompic hypersynchrony, and mitten patterns.

A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

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Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

2017-05-01

This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

Unsupervised spike sorting based on discriminative subspace learning.

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Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Multiplexed Spike Coding and Adaptation in the Thalamus

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Rebecca A. Mease

2017-05-01

Full Text Available High-frequency “burst” clusters of spikes are a generic output pattern of many neurons. While bursting is a ubiquitous computational feature of different nervous systems across animal species, the encoding of synaptic inputs by bursts is not well understood. We find that bursting neurons in the rodent thalamus employ “multiplexing” to differentially encode low- and high-frequency stimulus features associated with either T-type calcium “low-threshold” or fast sodium spiking events, respectively, and these events adapt differently. Thus, thalamic bursts encode disparate information in three channels: (1 burst size, (2 burst onset time, and (3 precise spike timing within bursts. Strikingly, this latter “intraburst” encoding channel shows millisecond-level feature selectivity and adapts across statistical contexts to maintain stable information encoded per spike. Consequently, calcium events both encode low-frequency stimuli and, in parallel, gate a transient window for high-frequency, adaptive stimulus encoding by sodium spike timing, allowing bursts to efficiently convey fine-scale temporal information.

Implementing Signature Neural Networks with Spiking Neurons.

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Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence

Effect of heavy metals on pH buffering capacity and solubility of Ca, Mg, K, and P in non-spiked and heavy metal-spiked soils.

Science.gov (United States)

Najafi, Sarvenaz; Jalali, Mohsen

2016-06-01

In many parts of the world, soil acidification and heavy metal contamination has become a serious concern due to the adverse effects on chemical properties of soil and crop yield. The aim of this study was to investigate the effect of pH (in the range of 1 to 3 units above and below the native pH of soils) on calcium (Ca), magnesium (Mg), potassium (K), and phosphorus (P) solubility in non-spiked and heavy metal-spiked soil samples. Spiked samples were prepared by cadmium (Cd), copper (Cu), nickel (Ni), and zinc (Zn) as chloride salts and incubating soils for 40 days. The pH buffering capacity (pHBC) of each sample was determined by plotting the amount of H(+) or OH(-) added (mmol kg(-1)) versus the related pH value. The pHBC of soils ranged from 47.1 to 1302.5 mmol kg(-1) for non-spiked samples and from 45.0 to 1187.4 mmol kg(-1) for spiked soil samples. The pHBC values were higher in soil 2 (non-spiked and spiked) which had higher calcium carbonate content. The results indicated the presence of heavy metals in soils generally decreased the solution pH and pHBC values in spiked samples. In general, solubility of Ca, Mg, and K decreased with increasing equilibrium pH of non-spiked and spiked soil samples. In the case of P, increasing the pH to about 7, decreased the solubility in all soils but further increase of pH from 7, enhanced P solubility. The solubility trends and values for Ca, Mg, and K did not differed significantly in non-spiked and spiked samples. But in the case of P, a reduction in solubility was observed in heavy metal-spiked soils. The information obtained in this study can be useful to make better estimation of the effects of soil pollutants on anion and cation solubility from agricultural and environmental viewpoints.

The Mutation Frequency in Different Spike Categories in Barley

DEFF Research Database (Denmark)

Frydenberg, O.; Doll, Hans; Sandfær, J.

1964-01-01

After gamma irradiation of barley seeds, a comparison has been made between the chlorophyll-mutant frequencies in X1 spikes that had multicellular bud meristems in the seeds at the time of treatment (denoted as pre-formed spikes) and X1 spikes having no recognizable meristems at the time...

Orthobunyavirus ultrastructure and the curious tripodal glycoprotein spike.

Directory of Open Access Journals (Sweden)

Thomas A Bowden

Full Text Available The genus Orthobunyavirus within the family Bunyaviridae constitutes an expanding group of emerging viruses, which threaten human and animal health. Despite the medical importance, little is known about orthobunyavirus structure, a prerequisite for understanding virus assembly and entry. Here, using electron cryo-tomography, we report the ultrastructure of Bunyamwera virus, the prototypic member of this genus. Whilst Bunyamwera virions are pleomorphic in shape, they display a locally ordered lattice of glycoprotein spikes. Each spike protrudes 18 nm from the viral membrane and becomes disordered upon introduction to an acidic environment. Using sub-tomogram averaging, we derived a three-dimensional model of the trimeric pre-fusion glycoprotein spike to 3-nm resolution. The glycoprotein spike consists mainly of the putative class-II fusion glycoprotein and exhibits a unique tripod-like arrangement. Protein-protein contacts between neighbouring spikes occur at membrane-proximal regions and intra-spike contacts at membrane-distal regions. This trimeric assembly deviates from previously observed fusion glycoprotein arrangements, suggesting a greater than anticipated repertoire of viral fusion glycoprotein oligomerization. Our study provides evidence of a pH-dependent conformational change that occurs during orthobunyaviral entry into host cells and a blueprint for the structure of this group of emerging pathogens.

Independent component analysis separates spikes of different origin in the EEG.

Science.gov (United States)

Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

2006-02-01

Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

Spiking and bursting patterns of fractional-order Izhikevich model

Science.gov (United States)

Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

Spike Bursts from an Excitable Optical System

Science.gov (United States)

Rios Leite, Jose R.; Rosero, Edison J.; Barbosa, Wendson A. S.; Tredicce, Jorge R.

Diode Lasers with double optical feedback are shown to present power drop spikes with statistical distribution controllable by the ratio of the two feedback times. The average time between spikes and the variance within long time series are studied. The system is shown to be excitable and present bursting of spikes created with specific feedback time ratios and strength. A rate equation model, extending the Lang-Kobayashi single feedback for semiconductor lasers proves to match the experimental observations. Potential applications to construct network to mimic neural systems having controlled bursting properties in each unit will be discussed. Brazilian Agency CNPQ.

Spike Code Flow in Cultured Neuronal Networks

Directory of Open Access Journals (Sweden)

Shinichi Tamura

2016-01-01

Full Text Available We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Orthogonal ribbons for suspending test masses in interferometric gravitational wave detectors

International Nuclear Information System (INIS)

Lee, B.H.; Ju, L.; Blair, D.G.

2005-01-01

We show that a simple modification of proposed ribbon suspensions for laser interferometric gravitational wave detectors can substantially reduce the amplitude of violin modes at the expense of a small deterioration of suspension thermal noise. Using low loss fused silica, large amplitude peaks which cause dynamic range problems can be reduced by 21 dB. The total number of horizontal longitudinal direction violin modes below 5 kHz is reduced to less than half that expected with conventional ribbon suspensions

Orthogonal ribbons for suspending test masses in interferometric gravitational wave detectors

Energy Technology Data Exchange (ETDEWEB)

Lee, B.H. [School of Physics, University of Western Australia, Crawley 6009, WA (Australia)]. E-mail: bhl@physics.uwa.edu.au; Ju, L. [School of Physics, University of Western Australia, Crawley 6009, WA (Australia); Blair, D.G. [School of Physics, University of Western Australia, Crawley 6009, WA (Australia)

2005-05-23

We show that a simple modification of proposed ribbon suspensions for laser interferometric gravitational wave detectors can substantially reduce the amplitude of violin modes at the expense of a small deterioration of suspension thermal noise. Using low loss fused silica, large amplitude peaks which cause dynamic range problems can be reduced by 21 dB. The total number of horizontal longitudinal direction violin modes below 5 kHz is reduced to less than half that expected with conventional ribbon suspensions.

Comparison of Classifier Architectures for Online Neural Spike Sorting.

Science.gov (United States)

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

Automatic fitting of spiking neuron models to electrophysiological recordings

Directory of Open Access Journals (Sweden)

Cyrille Rossant

2010-03-01

Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

Scaling of spiking and humping in keyhole welding

Energy Technology Data Exchange (ETDEWEB)

Wei, P S; Chuang, K C [Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan (China); DebRoy, T [Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA 16802 (United States); Ku, J S, E-mail: pswei@mail.nsysu.edu.tw, E-mail: cielo.zhuang@gmail.com, E-mail: rtd1@psu.edu, E-mail: jsku@mail.nsysu.edu.tw [Institute of Materials Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan (China)

2011-06-22

Spiking, rippling and humping seriously reduce the strength of welds. The effects of beam focusing, volatile alloying element concentration and welding velocity on spiking, coarse rippling and humping in keyhole mode electron-beam welding are examined through scale analysis. Although these defects have been studied in the past, the mechanisms for their formation are not fully understood. This work relates the average amplitudes of spikes to fusion zone depth for the welding of Al 6061, SS 304 and carbon steel, and Al 5083. The scale analysis introduces welding and melting efficiencies and an appropriate power distribution to account for the focusing effects, and the energy which is reflected and escapes through the keyhole opening to the surroundings. The frequency of humping and spiking can also be predicted from the scale analysis. The analysis also reveals the interrelation between coarse rippling and humping. The data and the mechanistic findings reported in this study are useful for understanding and preventing spiking and humping during keyhole mode electron and laser beam welding.

A metric space approach to the information capacity of spike trains

OpenAIRE

HOUGHTON, CONOR JAMES; GILLESPIE, JAMES

2010-01-01

PUBLISHED Classical information theory can be either discrete or continuous, corresponding to discrete or continuous random variables. However, although spike times in a spike train are described by continuous variables, the information content is usually calculated using discrete information theory. This is because the number of spikes, and hence, the number of variables, varies from spike train to spike train, making the continuous theory difficult to apply.It is possible to avoid ...

Clustering predicts memory performance in networks of spiking and non-spiking neurons

Directory of Open Access Journals (Sweden)

Weiliang eChen

2011-03-01

Full Text Available The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks. We also show that the clustering of the network, measured by Clustering Coefficient, has a strong linear correlation to the performance of associative memory. This result is important since a purely static measure of network connectivity appears to determine an important dynamic property of the network.

Voltage-spike analysis for a free-running parallel inverter

Science.gov (United States)

Lee, F. C. Y.; Wilson, T. G.

1974-01-01

Unwanted and sometimes damaging high-amplitude voltage spikes occur during each half cycle in many transistor saturable-core inverters at the moment when the core saturates and the transistors switch. The analysis shows that spikes are an intrinsic characteristic of certain types of inverters even with negligible leakage inductance and purely resistive load. The small but unavoidable after-saturation inductance of the saturable-core transformer plays an essential role in creating these undesired thigh-voltage spikes. State-plane analysis provides insight into the complex interaction between core and transistors, and shows the circuit parameters upon which the magnitude of these spikes depends.

Automated spike preparation system for Isotope Dilution Mass Spectrometry (IDMS)

International Nuclear Information System (INIS)

Maxwell, S.L. III; Clark, J.P.

1990-01-01

Isotope Dilution Mass Spectrometry (IDMS) is a method frequently employed to measure dissolved, irradiated nuclear materials. A known quantity of a unique isotope of the element to be measured (referred to as the ''spike'') is added to the solution containing the analyte. The resulting solution is chemically purified then analyzed by mass spectrometry. By measuring the magnitude of the response for each isotope and the response for the ''unique spike'' then relating this to the known quantity of the ''spike'', the quantity of the nuclear material can be determined. An automated spike preparation system was developed at the Savannah River Site (SRS) to dispense spikes for use in IDMS analytical methods. Prior to this development, technicians weighed each individual spike manually to achieve the accuracy required. This procedure was time-consuming and subjected the master stock solution to evaporation. The new system employs a high precision SMI Model 300 Unipump dispenser interfaced with an electronic balance and a portable Epson HX-20 notebook computer to automate spike preparation

Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

Directory of Open Access Journals (Sweden)

Bertrand Fontaine

2014-04-01

Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

An Overview of Bayesian Methods for Neural Spike Train Analysis

Directory of Open Access Journals (Sweden)

Zhe Chen

2013-01-01

Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

An Unsupervised Online Spike-Sorting Framework.

Science.gov (United States)

Knieling, Simeon; Sridharan, Kousik S; Belardinelli, Paolo; Naros, Georgios; Weiss, Daniel; Mormann, Florian; Gharabaghi, Alireza

2016-08-01

Extracellular neuronal microelectrode recordings can include action potentials from multiple neurons. To separate spikes from different neurons, they can be sorted according to their shape, a procedure referred to as spike-sorting. Several algorithms have been reported to solve this task. However, when clustering outcomes are unsatisfactory, most of them are difficult to adjust to achieve the desired results. We present an online spike-sorting framework that uses feature normalization and weighting to maximize the distinctiveness between different spike shapes. Furthermore, multiple criteria are applied to either facilitate or prevent cluster fusion, thereby enabling experimenters to fine-tune the sorting process. We compare our method to established unsupervised offline (Wave_Clus (WC)) and online (OSort (OS)) algorithms by examining their performance in sorting various test datasets using two different scoring systems (AMI and the Adamos metric). Furthermore, we evaluate sorting capabilities on intra-operative recordings using established quality metrics. Compared to WC and OS, our algorithm achieved comparable or higher scores on average and produced more convincing sorting results for intra-operative datasets. Thus, the presented framework is suitable for both online and offline analysis and could substantially improve the quality of microelectrode-based data evaluation for research and clinical application.

Emergent dynamics of spiking neurons with fluctuating threshold

Science.gov (United States)

Bhattacharjee, Anindita; Das, M. K.

2017-05-01

Role of fluctuating threshold on neuronal dynamics is investigated. The threshold function is assumed to follow a normal probability distribution. Standard deviation of inter-spike interval of the response is computed as an indicator of irregularity in spike emission. It has been observed that, the irregularity in spiking is more if the threshold variation is more. A significant change in modal characteristics of Inter Spike Intervals (ISI) is seen to occur as a function of fluctuation parameter. Investigation is further carried out for coupled system of neurons. Cooperative dynamics of coupled neurons are discussed in view of synchronization. Total and partial synchronization regimes are depicted with the help of contour plots of synchrony measure under various conditions. Results of this investigation may provide a basis for exploring the complexities of neural communication and brain functioning.

Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: a simulation study

International Nuclear Information System (INIS)

Shimazaki, Hideaki

2013-01-01

Neurons in cortical circuits exhibit coordinated spiking activity, and can produce correlated synchronous spikes during behavior and cognition. We recently developed a method for estimating the dynamics of correlated ensemble activity by combining a model of simultaneous neuronal interactions (e.g., a spin-glass model) with a state-space method (Shimazaki et al. 2012 PLoS Comput Biol 8 e1002385). This method allows us to estimate stimulus-evoked dynamics of neuronal interactions which is reproducible in repeated trials under identical experimental conditions. However, the method may not be suitable for detecting stimulus responses if the neuronal dynamics exhibits significant variability across trials. In addition, the previous model does not include effects of past spiking activity of the neurons on the current state of ensemble activity. In this study, we develop a parametric method for simultaneously estimating the stimulus and spike-history effects on the ensemble activity from single-trial data even if the neurons exhibit dynamics that is largely unrelated to these effects. For this goal, we model ensemble neuronal activity as a latent process and include the stimulus and spike-history effects as exogenous inputs to the latent process. We develop an expectation-maximization algorithm that simultaneously achieves estimation of the latent process, stimulus responses, and spike-history effects. The proposed method is useful to analyze an interaction of internal cortical states and sensory evoked activity

The electric potential of tripolar spikes

Energy Technology Data Exchange (ETDEWEB)

Nocera, L. [Theoretical Plasma Physics, IPCF-CNR, Via Moruzzi 1, I-56124 Pisa (Italy)

2010-02-22

We present an analytical formula for the waveform of the electric potential associated with a tripolar spike in a plasma. This formula is based on the construction and on the subsequent solution of a differential equation for the waveform. We work out this equation as a direct consequence of the morphological and functional properties of the observed waveform, without making any reference to the velocity distributions of the electrons and of the ions which sustain the spike. In the approximation of small potential amplitudes, we solve this equation by quadrature. In particular, in the second order approximation, the solution of this equation is given in terms of elementary functions. This analytical solution is able to reproduce the potential waveforms associated with electron holes, ion holes, monotonic and nonmonotonic double layers and tripolar spikes, in excellent agreement with observations.

The electric potential of tripolar spikes

International Nuclear Information System (INIS)

Nocera, L.

2010-01-01

We present an analytical formula for the waveform of the electric potential associated with a tripolar spike in a plasma. This formula is based on the construction and on the subsequent solution of a differential equation for the waveform. We work out this equation as a direct consequence of the morphological and functional properties of the observed waveform, without making any reference to the velocity distributions of the electrons and of the ions which sustain the spike. In the approximation of small potential amplitudes, we solve this equation by quadrature. In particular, in the second order approximation, the solution of this equation is given in terms of elementary functions. This analytical solution is able to reproduce the potential waveforms associated with electron holes, ion holes, monotonic and nonmonotonic double layers and tripolar spikes, in excellent agreement with observations.

Noisy Spiking in Visual Area V2 of Amblyopic Monkeys.

Science.gov (United States)

Wang, Ye; Zhang, Bin; Tao, Xiaofeng; Wensveen, Janice M; Smith, Earl L; Chino, Yuzo M

2017-01-25

Interocular decorrelation of input signals in developing visual cortex can cause impaired binocular vision and amblyopia. Although increased intrinsic noise is thought to be responsible for a range of perceptual deficits in amblyopic humans, the neural basis for the elevated perceptual noise in amblyopic primates is not known. Here, we tested the idea that perceptual noise is linked to the neuronal spiking noise (variability) resulting from developmental alterations in cortical circuitry. To assess spiking noise, we analyzed the contrast-dependent dynamics of spike counts and spiking irregularity by calculating the square of the coefficient of variation in interspike intervals (CV 2 ) and the trial-to-trial fluctuations in spiking, or mean matched Fano factor (m-FF) in visual area V2 of monkeys reared with chronic monocular defocus. In amblyopic neurons, the contrast versus response functions and the spike count dynamics exhibited significant deviations from comparable data for normal monkeys. The CV 2 was pronounced in amblyopic neurons for high-contrast stimuli and the m-FF was abnormally high in amblyopic neurons for low-contrast gratings. The spike count, CV 2 , and m-FF of spontaneous activity were also elevated in amblyopic neurons. These contrast-dependent spiking irregularities were correlated with the level of binocular suppression in these V2 neurons and with the severity of perceptual loss for individual monkeys. Our results suggest that the developmental alterations in normalization mechanisms resulting from early binocular suppression can explain much of these contrast-dependent spiking abnormalities in V2 neurons and the perceptual performance of our amblyopic monkeys. Amblyopia is a common developmental vision disorder in humans. Despite the extensive animal studies on how amblyopia emerges, we know surprisingly little about the neural basis of amblyopia in humans and nonhuman primates. Although the vision of amblyopic humans is often described as

Pb isotope analysis of ng size samples by TIMS equipped with a 1013 Ω resistor using a 207Pb-204Pb double spike

NARCIS (Netherlands)

Klaver, M.; Smeets, R.J.; Koornneef, J.M.; Davies, G.R.; Vroon, P.Z.

2016-01-01

The use of the double spike technique to correct for instrumental mass fractionation has yielded high precision results for lead isotope measurements by thermal ionisation mass spectrometry (TIMS), but the applicability to ng size Pb samples is hampered by the small size of the

Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons.

Science.gov (United States)

Grewe, Jan; Kruscha, Alexandra; Lindner, Benjamin; Benda, Jan

2017-03-07

Synchronous activity in populations of neurons potentially encodes special stimulus features. Selective readout of either synchronous or asynchronous activity allows formation of two streams of information processing. Theoretical work predicts that such a synchrony code is a fundamental feature of populations of spiking neurons if they operate in specific noise and stimulus regimes. Here we experimentally test the theoretical predictions by quantifying and comparing neuronal response properties in tuberous and ampullary electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus These related systems show similar levels of synchronous activity, but only in the more irregularly firing tuberous afferents a synchrony code is established, whereas in the more regularly firing ampullary afferents it is not. The mere existence of synchronous activity is thus not sufficient for a synchrony code. Single-cell features such as the irregularity of spiking and the frequency dependence of the neuron's transfer function determine whether synchronous spikes possess a distinct meaning for the encoding of time-dependent signals.

Voltage spikes in Nb3Sn and NbTi strands

International Nuclear Information System (INIS)

Bordini, B.; Ambrosio, G.; Barzi, E.; Carcagno, R.; Feher, S.; Kashikhin, V.V.; Lamm, M.J.; Orris, D.; Tartaglia, M.; Tompkins, J.C.; Turrioni, D.; Yamada, R.; Zlobin, A.V.; Fermilab

2005-01-01

As part of the High Field Magnet program at Fermilab several NbTi and Nb 3 Sn strands were tested with particular emphasis on the study of voltage spikes and their relationship to superconductor instabilities. The voltage spikes were detected under various experimental conditions using voltage-current (V-I) and voltage-field (V-H) methods. Two types of spikes, designated ''magnetization'' and ''transport current'' spikes, have been identified. Their origin is most likely related to magnetization flux jump and transport current redistribution, respectively. Many of the signals observed appear to be a combination of these two types of spikes; the combination of these two instability mechanisms should play a dominant role in determining the minimum quench current

A supervised learning rule for classification of spatiotemporal spike patterns.

Science.gov (United States)

Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

2016-08-01

This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'.

Science.gov (United States)

Swindale, Nicholas V; Mitelut, Catalin; Murphy, Timothy H; Spacek, Martin A

2017-02-10

Few stand-alone software applications are available for sorting spikes from recordings made with multi-electrode arrays. Ideally, an application should be user friendly with a graphical user interface, able to read data files in a variety of formats, and provide users with a flexible set of tools giving them the ability to detect and sort extracellular voltage waveforms from different units with some degree of reliability. Previously published spike sorting methods are now available in a software program, SpikeSorter, intended to provide electrophysiologists with a complete set of tools for sorting, starting from raw recorded data file and ending with the export of sorted spikes times. Procedures are automated to the extent this is currently possible. The article explains and illustrates the use of the program. A representative data file is opened, extracellular traces are filtered, events are detected and then clustered. A number of problems that commonly occur during sorting are illustrated, including the artefactual over-splitting of units due to the tendency of some units to fire spikes in pairs where the second spike is significantly smaller than the first, and over-splitting caused by slow variation in spike height over time encountered in some units. The accuracy of SpikeSorter's performance has been tested with surrogate ground truth data and found to be comparable to that of other algorithms in current development.

A Markovian event-based framework for stochastic spiking neural networks.

Science.gov (United States)

Touboul, Jonathan D; Faugeras, Olivier D

2011-11-01

In spiking neural networks, the information is conveyed by the spike times, that depend on the intrinsic dynamics of each neuron, the input they receive and on the connections between neurons. In this article we study the Markovian nature of the sequence of spike times in stochastic neural networks, and in particular the ability to deduce from a spike train the next spike time, and therefore produce a description of the network activity only based on the spike times regardless of the membrane potential process. To study this question in a rigorous manner, we introduce and study an event-based description of networks of noisy integrate-and-fire neurons, i.e. that is based on the computation of the spike times. We show that the firing times of the neurons in the networks constitute a Markov chain, whose transition probability is related to the probability distribution of the interspike interval of the neurons in the network. In the cases where the Markovian model can be developed, the transition probability is explicitly derived in such classical cases of neural networks as the linear integrate-and-fire neuron models with excitatory and inhibitory interactions, for different types of synapses, possibly featuring noisy synaptic integration, transmission delays and absolute and relative refractory period. This covers most of the cases that have been investigated in the event-based description of spiking deterministic neural networks.

Fast convergence of spike sequences to periodic patterns in recurrent networks

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2002-01-01

The dynamical attractors are thought to underlie many biological functions of recurrent neural networks. Here we show that stable periodic spike sequences with precise timings are the attractors of the spiking dynamics of recurrent neural networks with global inhibition. Almost all spike sequences converge within a finite number of transient spikes to these attractors. The convergence is fast, especially when the global inhibition is strong. These results support the possibility that precise spatiotemporal sequences of spikes are useful for information encoding and processing in biological neural networks

Noise-enhanced coding in phasic neuron spike trains.

Science.gov (United States)

Ly, Cheng; Doiron, Brent

2017-01-01

The stochastic nature of neuronal response has lead to conjectures about the impact of input fluctuations on the neural coding. For the most part, low pass membrane integration and spike threshold dynamics have been the primary features assumed in the transfer from synaptic input to output spiking. Phasic neurons are a common, but understudied, neuron class that are characterized by a subthreshold negative feedback that suppresses spike train responses to low frequency signals. Past work has shown that when a low frequency signal is accompanied by moderate intensity broadband noise, phasic neurons spike trains are well locked to the signal. We extend these results with a simple, reduced model of phasic activity that demonstrates that a non-Markovian spike train structure caused by the negative feedback produces a noise-enhanced coding. Further, this enhancement is sensitive to the timescales, as opposed to the intensity, of a driving signal. Reduced hazard function models show that noise-enhanced phasic codes are both novel and separate from classical stochastic resonance reported in non-phasic neurons. The general features of our theory suggest that noise-enhanced codes in excitable systems with subthreshold negative feedback are a particularly rich framework to study.

Financial time series prediction using spiking neural networks.

Science.gov (United States)

Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

2014-01-01

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.

Genes with a spike expression are clustered in chromosome (sub)bands and spike (sub)bands have a powerful prognostic value in patients with multiple myeloma

Science.gov (United States)

Kassambara, Alboukadel; Hose, Dirk; Moreaux, Jérôme; Walker, Brian A.; Protopopov, Alexei; Reme, Thierry; Pellestor, Franck; Pantesco, Véronique; Jauch, Anna; Morgan, Gareth; Goldschmidt, Hartmut; Klein, Bernard

2012-01-01

Background Genetic abnormalities are common in patients with multiple myeloma, and may deregulate gene products involved in tumor survival, proliferation, metabolism and drug resistance. In particular, translocations may result in a high expression of targeted genes (termed spike expression) in tumor cells. We identified spike genes in multiple myeloma cells of patients with newly-diagnosed myeloma and investigated their prognostic value. Design and Methods Genes with a spike expression in multiple myeloma cells were picked up using box plot probe set signal distribution and two selection filters. Results In a cohort of 206 newly diagnosed patients with multiple myeloma, 2587 genes/expressed sequence tags with a spike expression were identified. Some spike genes were associated with some transcription factors such as MAF or MMSET and with known recurrent translocations as expected. Spike genes were not associated with increased DNA copy number and for a majority of them, involved unknown mechanisms. Of spiked genes, 36.7% clustered significantly in 149 out of 862 documented chromosome (sub)bands, of which 53 had prognostic value (35 bad, 18 good). Their prognostic value was summarized with a spike band score that delineated 23.8% of patients with a poor median overall survival (27.4 months versus not reached, Pband score was independent of other gene expression profiling-based risk scores, t(4;14), or del17p in an independent validation cohort of 345 patients. Conclusions We present a new approach to identify spike genes and their relationship to patients’ survival. PMID:22102711

Predictive coding of dynamical variables in balanced spiking networks.

Science.gov (United States)

Boerlin, Martin; Machens, Christian K; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

A method for decoding the neurophysiological spike-response transform.

Science.gov (United States)

Stern, Estee; García-Crescioni, Keyla; Miller, Mark W; Peskin, Charles S; Brezina, Vladimir

2009-11-15

Many physiological responses elicited by neuronal spikes-intracellular calcium transients, synaptic potentials, muscle contractions-are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions-the elementary response kernel and additional kernels or functions that describe the dependence on previous history-that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the "synaptic decoding" approach of Sen et al. (1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms.

A spiking neuron circuit based on a carbon nanotube transistor

International Nuclear Information System (INIS)

Chen, C-L; Kim, K; Truong, Q; Shen, A; Li, Z; Chen, Y

2012-01-01

A spiking neuron circuit based on a carbon nanotube (CNT) transistor is presented in this paper. The spiking neuron circuit has a crossbar architecture in which the transistor gates are connected to its row electrodes and the transistor sources are connected to its column electrodes. An electrochemical cell is incorporated in the gate of the transistor by sandwiching a hydrogen-doped poly(ethylene glycol)methyl ether (PEG) electrolyte between the CNT channel and the top gate electrode. An input spike applied to the gate triggers a dynamic drift of the hydrogen ions in the PEG electrolyte, resulting in a post-synaptic current (PSC) through the CNT channel. Spikes input into the rows trigger PSCs through multiple CNT transistors, and PSCs cumulate in the columns and integrate into a ‘soma’ circuit to trigger output spikes based on an integrate-and-fire mechanism. The spiking neuron circuit can potentially emulate biological neuron networks and their intelligent functions. (paper)

An online supervised learning method based on gradient descent for spiking neurons.

Science.gov (United States)

Xu, Yan; Yang, Jing; Zhong, Shuiming

2017-09-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

A ‘Violin-Mode’ shadow sensor for interferometric gravitational wave detectors

Science.gov (United States)

Lockerbie, N. A.; Tokmakov, K. V.

2014-12-01

This paper describes a system of four novel shadow detectors having, collectively, a displacement sensitivity of (69  ±  13) picometres (rms) / √Hz, at 500 Hz, over a measuring span of ±0.1 mm. The detectors were designed to monitor the vibrations of the 600 mm long, 400 μm diameter, silica suspension fibres of the mirrors for the Advanced LIGO (Laser Interferometer Gravitational wave Observatory) gravitational wave detectors, at the resonances of the so-called Violin Modes (VM). The VM detection system described here had a target sensitivity of 100 pm (rms)/ √Hz at 500 Hz, together with, ultimately, a required detection span of ±0.1 mm about the mean position of each fibre—in order to compensate for potential slow drift over time of fibre position, due to mechanical relaxation. The full sensor system, comprising emitters (sources of illumination) and shadow detectors, therefore met these specifications. Using these sensors, VM resonances having amplitudes of 1.2 nm (rms) were detected in the suspension fibres of an Advanced LIGO dummy test-mass. The VM bandwidth of the sensor, determined by its transimpedance amplifier, was 226 Hz-8.93 kHz at the -3 dB points. This paper focuses mainly on the detector side of the shadow sensors. The emitters are described in an accompanying paper.

A ‘Violin-Mode’ shadow sensor for interferometric gravitational wave detectors

International Nuclear Information System (INIS)

Lockerbie, N A; Tokmakov, K V

2014-01-01

This paper describes a system of four novel shadow detectors having, collectively, a displacement sensitivity of (69  ±  13) picometres (rms) / √Hz, at 500 Hz, over a measuring span of ±0.1 mm. The detectors were designed to monitor the vibrations of the 600 mm long, 400 μm diameter, silica suspension fibres of the mirrors for the Advanced LIGO (Laser Interferometer Gravitational wave Observatory) gravitational wave detectors, at the resonances of the so-called Violin Modes (VM). The VM detection system described here had a target sensitivity of 100 pm (rms)/ √Hz at 500 Hz, together with, ultimately, a required detection span of ±0.1 mm about the mean position of each fibre—in order to compensate for potential slow drift over time of fibre position, due to mechanical relaxation. The full sensor system, comprising emitters (sources of illumination) and shadow detectors, therefore met these specifications. Using these sensors, VM resonances having amplitudes of 1.2 nm (rms) were detected in the suspension fibres of an Advanced LIGO dummy test-mass. The VM bandwidth of the sensor, determined by its transimpedance amplifier, was 226 Hz–8.93 kHz at the −3 dB points. This paper focuses mainly on the detector side of the shadow sensors. The emitters are described in an accompanying paper. (paper)

Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

Science.gov (United States)

Kazantsev, V B; Asatryan, S Yu

2011-09-01

Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

Voltage spikes in Nb3Sn and NbTi strands

Energy Technology Data Exchange (ETDEWEB)

Bordini, B.; Ambrosio, G.; Barzi, E.; Carcagno, R.; Feher, S.; Kashikhin, V.V.; Lamm, M.J.; Orris, D.; Tartaglia, M.; Tompkins, J.C.; Turrioni, D.; Yamada, R.; Zlobin,; /Fermilab

2005-09-01

As part of the High Field Magnet program at Fermilab several NbTi and Nb{sub 3}Sn strands were tested with particular emphasis on the study of voltage spikes and their relationship to superconductor instabilities. The voltage spikes were detected under various experimental conditions using voltage-current (V-I) and voltage-field (V-H) methods. Two types of spikes, designated ''magnetization'' and ''transport current'' spikes, have been identified. Their origin is most likely related to magnetization flux jump and transport current redistribution, respectively. Many of the signals observed appear to be a combination of these two types of spikes; the combination of these two instability mechanisms should play a dominant role in determining the minimum quench current.

Pressurized water reactor iodine spiking behavior under power transient conditions

International Nuclear Information System (INIS)

Ho, J.C.

1992-01-01

The most accepted theory explaining the cause of pressurized water reactor iodine spiking is steam formation and condensation in damaged fuel rods. The phase transformation of the primary coolant from water to steam and back again is believed to cause the iodine spiking phenomenon. But due to the complex nature of the phenomenon, a comprehensive model of the behavior has not yet been successfully developed. This paper presents a new model based on an empirical approach, which gives a first-order estimation of the peak iodine spiking magnitude. Based on the proposed iodine spiking model, it is apparent that it is feasible to derive a correlation using the plant operating data base to monitor and control the peak iodine spiking magnitude

On the Use of 233U-236U Double-Spike for TIMS Measurements of Uranium Isotopes: A Simulation Study

International Nuclear Information System (INIS)

Williams, R W

2004-01-01

Synthetic ion beams with instantaneous and temporal characteristics appropriate to thermal ionization mass spectrometry (TIMS) were mathematically generated and analyzed to determine the effects of using a mixed 233 U- 236 U spike (double-spike) in the analysis of uranium isotopes. The instantaneous beam characteristics are the intensities (e.g., counts per second) modeled with a Poisson distribution plus a component of random noise that simulates the detection processes. Several beam intensity and mass fractionation vs. time functions were modeled to simulate a range of sample sizes and the commonly employed methods of data collection. These beam profiles were also generated with different noise levels, and signal-to-noise vs. analytical precision diagrams are presented. Modeling focused on natural uranium, where 238 U/ 235 U = 137.88, and on the ability of a given method to determine precisely and accurately small variations in this ratio. Practical limits on precision were determined to be 20-30 ppm, which is consistent with precision seen for other elements by state-of-the-art TIMS. The TIMS total evaporation method was compared directly with the double-spike method. While similar analytical precisions are obtained with either method, the double-spike method of correcting for analytical bias gives more accurate results. The results of a total evaporation analysis will deviate from true by more than the analytical precision if as little as 0.05% of the signal is not integrated, whereas the accuracy and precision of the double-spiked analyses are always linked

THE OLD PROVENÇAL BALLATAS FOR VOICE AND VIOLIN BY SNEJANA PISLARI: ISSUES OF FORMATION

Directory of Open Access Journals (Sweden)

COADĂ TATIANA

2017-06-01

Full Text Available The article offers a detailed analysis of one of the most interesting examples of domestic chamber vocal music of the end of the twentieth century — „The Old Provençal Ballatas” by S. Pislari on G. Faydit’s verses. Special attention is paid to the genre and stylistic features of the works, revealing the identity of the musical language. The main place is given to the issues of formamodelling in the „Old Provençal Ballata”, fact that is due to the innovative attitude of the composer to working with the poetic text. Written in disused colloquial dialect, it determines the choice of the basic means of musical expression — melody, harmony, texture. An important distinction of the work is the composition of its performers as well, a female voice and the violin, both are monophonic by their nature. The dialogical texture of the composition combines the features of contrast polyphony and heterophony, which further contributes to the individualization of the composer’s intent.

Contamination spike simulation and measurement in a clean metal vapor laser

International Nuclear Information System (INIS)

Lin, C.E.; Yang, C.Y.

1990-01-01

This paper describes a new method for the generation of contamination-induced voltage spikes in a clean metal vapor laser. The method facilitates the study of the characteristics of this troublesome phenomenon in laser systems. Analysis of these artificially generated dirt spikes shows that the breakdown time of the laser tube is increased when these spike appear. The concept of a Townsend discharge is used to identify the parameter which changes the breakdown time of the discharges. The residual ionization control method is proposed to generate dirt spikes in a clean laser. Experimental results show that a wide range of dirt spike magnitudes can be obtained by using the proposed method. The method provides easy and accurate control of the magnitude of the dirt spike, and the laser tube does not become polluted. Results based on the measurements can be used in actual laser systems to monitor the appearance of dirt spikes and thus avoid the danger of thyratron failure

Spike and burst coding in thalamocortical relay cells.

Directory of Open Access Journals (Sweden)

Fleur Zeldenrust

2018-02-01

Full Text Available Mammalian thalamocortical relay (TCR neurons switch their firing activity between a tonic spiking and a bursting regime. In a combined experimental and computational study, we investigated the features in the input signal that single spikes and bursts in the output spike train represent and how this code is influenced by the membrane voltage state of the neuron. Identical frozen Gaussian noise current traces were injected into TCR neurons in rat brain slices as well as in a validated three-compartment TCR model cell. The resulting membrane voltage traces and spike trains were analyzed by calculating the coherence and impedance. Reverse correlation techniques gave the Event-Triggered Average (ETA and the Event-Triggered Covariance (ETC. This demonstrated that the feature selectivity started relatively long before the events (up to 300 ms and showed a clear distinction between spikes (selective for fluctuations and bursts (selective for integration. The model cell was fine-tuned to mimic the frozen noise initiated spike and burst responses to within experimental accuracy, especially for the mixed mode regimes. The information content carried by the various types of events in the signal as well as by the whole signal was calculated. Bursts phase-lock to and transfer information at lower frequencies than single spikes. On depolarization the neuron transits smoothly from the predominantly bursting regime to a spiking regime, in which it is more sensitive to high-frequency fluctuations. The model was then used to elucidate properties that could not be assessed experimentally, in particular the role of two important subthreshold voltage-dependent currents: the low threshold activated calcium current (IT and the cyclic nucleotide modulated h current (Ih. The ETAs of those currents and their underlying activation/inactivation states not only explained the state dependence of the firing regime but also the long-lasting concerted dynamic action of the two

Stochastic optimal control of single neuron spike trains

DEFF Research Database (Denmark)

Iolov, Alexandre; Ditlevsen, Susanne; Longtin, Andrë

2014-01-01

stimulation of a neuron to achieve a target spike train under the physiological constraint to not damage tissue. Approach. We pose a stochastic optimal control problem to precisely specify the spike times in a leaky integrate-and-fire (LIF) model of a neuron with noise assumed to be of intrinsic or synaptic...... origin. In particular, we allow for the noise to be of arbitrary intensity. The optimal control problem is solved using dynamic programming when the controller has access to the voltage (closed-loop control), and using a maximum principle for the transition density when the controller only has access...... to the spike times (open-loop control). Main results. We have developed a stochastic optimal control algorithm to obtain precise spike times. It is applicable in both the supra-threshold and sub-threshold regimes, under open-loop and closed-loop conditions and with an arbitrary noise intensity; the accuracy...

Anticipating Activity in Social Media Spikes

OpenAIRE

Higham, Desmond J.; Grindrod, Peter; Mantzaris, Alexander V.; Otley, Amanda; Laflin, Peter

2014-01-01

We propose a novel mathematical model for the activity of microbloggers during an external, event-driven spike. The model leads to a testable prediction of who would become most active if a spike were to take place. This type of information is of great interest to commercial organisations, governments and charities, as it identifies key players who can be targeted with information in real time when the network is most receptive. The model takes account of the fact that dynamic interactions ev...

Multimodal imaging of spike propagation: a technical case report.

Science.gov (United States)

Tanaka, N; Grant, P E; Suzuki, N; Madsen, J R; Bergin, A M; Hämäläinen, M S; Stufflebeam, S M

2012-06-01

We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.

Graphene-based filament material for thermal ionization

Energy Technology Data Exchange (ETDEWEB)

Hewitt, J. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Shick, C. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Siegfried, M. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2017-09-19

The use of graphene oxide materials for thermal ionization mass spectrometry analysis of plutonium and uranium has been investigated. Filament made from graphene oxide slurries have been 3-D printed. A method for attaching these filaments to commercial thermal ionization post assemblies has been devised. Resistive heating of the graphene based filaments under high vacuum showed stable operation in excess of 4 hours. Plutonium ion production has been observed in an initial set of filaments spiked with the Pu 128 Certified Reference Material.

The Analysis and Suppression of the spike noise in vibrator record

Science.gov (United States)

Jia, H.; Jiang, T.; Xu, X.; Ge, L.; Lin, J.; Yang, Z.

2013-12-01

During the seismic exploration with vibrator, seismic recording systems have often been affected by random spike noise in the background, which leads to strong data distortions as a result of the cross-correlation processing of the vibrator method. Partial or total loss of the desired seismic information is possible if no automatic spike reduction is available in the field prior to correlation of the field record. Generally speaking, original record of vibrator is uncorrelated data, in which the signal is non-wavelet form. In order to obtain the seismic record similar to explosive source, the signal of uncorrelated data needs to use the correlation algorithm to compress into wavelet form. The correlation process results in that the interference of spike in correlated data is not only being suppressed, but also being expanded. So the spike noise suppression of vibrator is indispensable. According to numerical simulation results, the effect of spike in the vibrator record is mainly affected by the amplitude and proportional points in the uncorrelated record. When the spike noise ratio in uncorrelated record reaches 1.5% and the average amplitude exceeds 200, it will make the SNR(signal-to-noise ratio) of the correlated record lower than 0dB, so that it is difficult to separate the signal. While the amplitude and ratio is determined by the intensity of background noise. Therefore, when the noise level is strong, in order to improve SNR of the seismic data, the uncorrelated record of vibrator need to take necessary steps to suppress spike noise. For the sake of reducing the influence of the spike noise, we need to make the detection and suppression of spike noise process for the uncorrelated record. Because vibrator works by inputting sweep signal into the underground long time, ideally, the peak and valley values of each trace have little change. On the basis of the peak and valley values, we can get a reference amplitude value. Then the spike can be detected and

Cytoplasmic tail of coronavirus spike protein has intracellular

Indian Academy of Sciences (India)

https://www.ias.ac.in/article/fulltext/jbsc/042/02/0231-0244. Keywords. Coronavirus spike protein trafficking; cytoplasmic tail signal; endoplasmic reticulum–Golgi intermediate complex; lysosome. Abstract. Intracellular trafficking and localization studies of spike protein from SARS and OC43 showed that SARS spikeprotein is ...

A novel automated spike sorting algorithm with adaptable feature extraction.

Science.gov (United States)

Bestel, Robert; Daus, Andreas W; Thielemann, Christiane

2012-10-15

To study the electrophysiological properties of neuronal networks, in vitro studies based on microelectrode arrays have become a viable tool for analysis. Although in constant progress, a challenging task still remains in this area: the development of an efficient spike sorting algorithm that allows an accurate signal analysis at the single-cell level. Most sorting algorithms currently available only extract a specific feature type, such as the principal components or Wavelet coefficients of the measured spike signals in order to separate different spike shapes generated by different neurons. However, due to the great variety in the obtained spike shapes, the derivation of an optimal feature set is still a very complex issue that current algorithms struggle with. To address this problem, we propose a novel algorithm that (i) extracts a variety of geometric, Wavelet and principal component-based features and (ii) automatically derives a feature subset, most suitable for sorting an individual set of spike signals. Thus, there is a new approach that evaluates the probability distribution of the obtained spike features and consequently determines the candidates most suitable for the actual spike sorting. These candidates can be formed into an individually adjusted set of spike features, allowing a separation of the various shapes present in the obtained neuronal signal by a subsequent expectation maximisation clustering algorithm. Test results with simulated data files and data obtained from chick embryonic neurons cultured on microelectrode arrays showed an excellent classification result, indicating the superior performance of the described algorithm approach. Copyright © 2012 Elsevier B.V. All rights reserved.

SPIKY: a graphical user interface for monitoring spike train synchrony.

Science.gov (United States)

Kreuz, Thomas; Mulansky, Mario; Bozanic, Nebojsa

2015-05-01

Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels. Copyright © 2015 the American Physiological Society.

Femtosecond laser fabricated spike structures for selective control of cellular behavior.

Science.gov (United States)

Schlie, Sabrina; Fadeeva, Elena; Koch, Jürgen; Ngezahayo, Anaclet; Chichkov, Boris N

2010-09-01

In this study we investigate the potential of femtosecond laser generated micrometer sized spike structures as functional surfaces for selective cell controlling. The spike dimensions as well as the average spike to spike distance can be easily tuned by varying the process parameters. Moreover, negative replications in soft materials such as silicone elastomer can be produced. This allows tailoring of wetting properties of the spike structures and their negative replicas representing a reduced surface contact area. Furthermore, we investigated material effects on cellular behavior. By comparing human fibroblasts and SH-SY5Y neuroblastoma cells we found that the influence of the material was cell specific. The cells not only changed their morphology, but also the cell growth was affected. Whereas, neuroblastoma cells proliferated at the same rate on the spike structures as on the control surfaces, the proliferation of fibroblasts was reduced by the spike structures. These effects can result from the cell specific adhesion patterns as shown in this work. These findings show a possibility to design defined surface microstructures, which could control cellular behavior in a cell specific manner.

Google Searches for "Cheap Cigarettes" Spike at Tax Increases: Evidence from an Algorithm to Detect Spikes in Time Series Data.

Science.gov (United States)

Caputi, Theodore L

2018-05-03

Online cigarette dealers have lower prices than brick-and-mortar retailers and advertise tax-free status.1-8 Previous studies show smokers search out these online alternatives at the time of a cigarette tax increase.9,10 However, these studies rely upon researchers' decision to consider a specific date and preclude the possibility that researchers focus on the wrong date. The purpose of this study is to introduce an unbiased methodology to the field of observing search patterns and to use this methodology to determine whether smokers search Google for "cheap cigarettes" at cigarette tax increases and, if so, whether the increased level of searches persists. Publicly available data from Google Trends is used to observe standardized search volumes for the term, "cheap cigarettes". Seasonal Hybrid Extreme Studentized Deviate and E-Divisive with Means tests were performed to observe spikes and mean level shifts in search volume. Of the twelve cigarette tax increases studied, ten showed spikes in searches for "cheap cigarettes" within two weeks of the tax increase. However, the mean level shifts did not occur for any cigarette tax increase. Searches for "cheap cigarettes" spike around the time of a cigarette tax increase, but the mean level of searches does not shift in response to a tax increase. The SHESD and EDM tests are unbiased methodologies that can be used to identify spikes and mean level shifts in time series data without an a priori date to be studied. SHESD and EDM affirm spikes in interest are related to tax increases. • Applies improved statistical techniques (SHESD and EDM) to Google search data related to cigarettes, reducing bias and increasing power • Contributes to the body of evidence that state and federal tax increases are associated with spikes in searches for cheap cigarettes and may be good dates for increased online health messaging related to tobacco.

Spike-timing theory of working memory.

Directory of Open Access Journals (Sweden)

Botond Szatmáry

Full Text Available Working memory (WM is the part of the brain's memory system that provides temporary storage and manipulation of information necessary for cognition. Although WM has limited capacity at any given time, it has vast memory content in the sense that it acts on the brain's nearly infinite repertoire of lifetime long-term memories. Using simulations, we show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. Here, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatiotemporal spike-timing patterns, called polychronous patterns; and synapses forming such polychronous neuronal groups (PNGs are subject to associative synaptic plasticity in the form of both long-term and short-term spike-timing dependent plasticity. While long-term potentiation is essential in PNG formation, we show how short-term plasticity can temporarily strengthen the synapses of selected PNGs and lead to an increase in the spontaneous reactivation rate of these PNGs. This increased reactivation rate, consistent with in vivo recordings during WM tasks, results in high interspike interval variability and irregular, yet systematically changing, elevated firing rate profiles within the neurons of the selected PNGs. Additionally, our theory explains the relationship between such slowly changing firing rates and precisely timed spikes, and it reveals a novel relationship between WM and the perception of time on the order of seconds.

Dual roles for spike signaling in cortical neural populations

Directory of Open Access Journals (Sweden)

Dana eBallard

2011-06-01

Full Text Available A prominent feature of signaling in cortical neurons is that of randomness in the action potential. The output of a typical pyramidal cell can be well fit with a Poisson model, and variations in the Poisson rate repeatedly have been shown to be correlated with stimuli. However while the rate provides a very useful characterization of neural spike data, it may not be the most fundamental description of the signaling code. Recent data showing γ frequency range multi-cell action potential correlations, together with spike timing dependent plasticity, are spurring a re-examination of the classical model, since precise timing codes imply that the generation of spikes is essentially deterministic. Could the observed Poisson randomness and timing determinism reflect two separate modes of communication, or do they somehow derive from a single process? We investigate in a timing-based model whether the apparent incompatibility between these probabilistic and deterministic observations may be resolved by examining how spikes could be used in the underlying neural circuits. The crucial component of this model draws on dual roles for spike signaling. In learning receptive fields from ensembles of inputs, spikes need to behave probabilistically, whereas for fast signaling of individual stimuli, the spikes need to behave deterministically. Our simulations show that this combination is possible if deterministic signals using γ latency coding are probabilistically routed through different members of a cortical cell population at different times. This model exhibits standard features characteristic of Poisson models such as orientation tuning post-stimulus histograms and exponential interval histograms. In addition it makes testable predictions that follow from the γ latency coding.

Measures of spike train synchrony for data with multiple time scales

NARCIS (Netherlands)

Satuvuori, Eero; Mulansky, Mario; Bozanic, Nebojsa; Malvestio, Irene; Zeldenrust, Fleur; Lenk, Kerstin; Kreuz, Thomas

2017-01-01

Background Measures of spike train synchrony are widely used in both experimental and computational neuroscience. Time-scale independent and parameter-free measures, such as the ISI-distance, the SPIKE-distance and SPIKE-synchronization, are preferable to time scale parametric measures, since by

A novel unsupervised spike sorting algorithm for intracranial EEG.

Science.gov (United States)

Yadav, R; Shah, A K; Loeb, J A; Swamy, M N S; Agarwal, R

2011-01-01

This paper presents a novel, unsupervised spike classification algorithm for intracranial EEG. The method combines template matching and principal component analysis (PCA) for building a dynamic patient-specific codebook without a priori knowledge of the spike waveforms. The problem of misclassification due to overlapping classes is resolved by identifying similar classes in the codebook using hierarchical clustering. Cluster quality is visually assessed by projecting inter- and intra-clusters onto a 3D plot. Intracranial EEG from 5 patients was utilized to optimize the algorithm. The resulting codebook retains 82.1% of the detected spikes in non-overlapping and disjoint clusters. Initial results suggest a definite role of this method for both rapid review and quantitation of interictal spikes that could enhance both clinical treatment and research studies on epileptic patients.

No WIMP mini-spikes in dwarf spheroidal galaxies

NARCIS (Netherlands)

Wanders, M.; Bertone, G.; Volonteri, M.; Weniger, C.

2015-01-01

The formation of black holes inevitably affects the distribution of dark and baryonic matter in their vicinity, leading to an enhancement of the dark matter density, called spike, and if dark matter is made of WIMPs, to a strong enhancement of the dark matter annihilation rate. Spikes at the center

The Mechanisms of Repetitive Spike Generation in an Axonless Retinal Interneuron

Directory of Open Access Journals (Sweden)

Mark S. Cembrowski

2012-02-01

Full Text Available Several types of retinal interneurons exhibit spikes but lack axons. One such neuron is the AII amacrine cell, in which spikes recorded at the soma exhibit small amplitudes (5 ms. Here, we used electrophysiological recordings and computational analysis to examine the mechanisms underlying this atypical spiking. We found that somatic spikes likely represent large, brief action potential-like events initiated in a single, electrotonically distal dendritic compartment. In this same compartment, spiking undergoes slow modulation, likely by an M-type K conductance. The structural correlate of this compartment is a thin neurite that extends from the primary dendritic tree: local application of TTX to this neurite, or excision of it, eliminates spiking. Thus, the physiology of the axonless AII is much more complex than would be anticipated from morphological descriptions and somatic recordings; in particular, the AII possesses a single dendritic structure that controls its firing pattern.

Building functional networks of spiking model neurons.

Science.gov (United States)

Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

2016-03-01

Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

Spike morphology in blast-wave-driven instability experiments

International Nuclear Information System (INIS)

Kuranz, C. C.; Drake, R. P.; Grosskopf, M. J.; Fryxell, B.; Budde, A.; Hansen, J. F.; Miles, A. R.; Plewa, T.; Hearn, N.; Knauer, J.

2010-01-01

The laboratory experiments described in the present paper observe the blast-wave-driven Rayleigh-Taylor instability with three-dimensional (3D) initial conditions. About 5 kJ of energy from the Omega laser creates conditions similar to those of the He-H interface during the explosion phase of a supernova. The experimental target is a 150 μm thick plastic disk followed by a low-density foam. The plastic piece has an embedded, 3D perturbation. The basic structure of the pattern is two orthogonal sine waves where each sine wave has an amplitude of 2.5 μm and a wavelength of 71 μm. In some experiments, an additional wavelength is added to explore the interaction of modes. In experiments with 3D initial conditions the spike morphology differs from what has been observed in other Rayleigh-Taylor experiments and simulations. Under certain conditions, experimental radiographs show some mass extending from the interface to the shock front. Current simulations show neither the spike morphology nor the spike penetration observed in the experiments. The amount of mass reaching the shock front is analyzed and potential causes for the spike morphology and the spikes reaching the shock are discussed. One such hypothesis is that these phenomena may be caused by magnetic pressure, generated by an azimuthal magnetic field produced by the plasma dynamics.

Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks

NARCIS (Netherlands)

D. Zambrano (Davide); S.M. Bohte (Sander)

2016-01-01

textabstractBiological neurons communicate with a sparing exchange of pulses - spikes. It is an open question how real spiking neurons produce the kind of powerful neural computation that is possible with deep artificial neural networks, using only so very few spikes to communicate. Building on

Characterizing neural activities evoked by manual acupuncture through spiking irregularity measures

International Nuclear Information System (INIS)

Xue Ming; Wang Jiang; Deng Bin; Wei Xi-Le; Yu Hai-Tao; Chen Ying-Yuan

2013-01-01

The neural system characterizes information in external stimulations by different spiking patterns. In order to examine how neural spiking patterns are related to acupuncture manipulations, experiments are designed in such a way that different types of manual acupuncture (MA) manipulations are taken at the ‘Zusanli’ point of experimental rats, and the induced electrical signals in the spinal dorsal root ganglion are detected and recorded. The interspike interval (ISI) statistical histogram is fitted by the gamma distribution, which has two parameters: one is the time-dependent firing rate and the other is a shape parameter characterizing the spiking irregularities. The shape parameter is the measure of spiking irregularities and can be used to identify the type of MA manipulations. The coefficient of variation is mostly used to measure the spike time irregularity, but it overestimates the irregularity in the case of pronounced firing rate changes. However, experiments show that each acupuncture manipulation will lead to changes in the firing rate. So we combine four relatively rate-independent measures to study the irregularity of spike trains evoked by different types of MA manipulations. Results suggest that the MA manipulations possess unique spiking statistics and characteristics and can be distinguished according to the spiking irregularity measures. These studies have offered new insights into the coding processes and information transfer of acupuncture. (interdisciplinary physics and related areas of science and technology)

Coincidence Detection Using Spiking Neurons with Application to Face Recognition

Directory of Open Access Journals (Sweden)

Fadhlan Kamaruzaman

2015-01-01

Full Text Available We elucidate the practical implementation of Spiking Neural Network (SNN as local ensembles of classifiers. Synaptic time constant τs is used as learning parameter in representing the variations learned from a set of training data at classifier level. This classifier uses coincidence detection (CD strategy trained in supervised manner using a novel supervised learning method called τs Prediction which adjusts the precise timing of output spikes towards the desired spike timing through iterative adaptation of τs. This paper also discusses the approximation of spike timing in Spike Response Model (SRM for the purpose of coincidence detection. This process significantly speeds up the whole process of learning and classification. Performance evaluations with face datasets such as AR, FERET, JAFFE, and CK+ datasets show that the proposed method delivers better face classification performance than the network trained with Supervised Synaptic-Time Dependent Plasticity (STDP. We also found that the proposed method delivers better classification accuracy than k nearest neighbor, ensembles of kNN, and Support Vector Machines. Evaluation on several types of spike codings also reveals that latency coding delivers the best result for face classification as well as for classification of other multivariate datasets.

Adaptive coupling optimized spiking coherence and synchronization in Newman-Watts neuronal networks.

Science.gov (United States)

Gong, Yubing; Xu, Bo; Wu, Ya'nan

2013-09-01

In this paper, we have numerically studied the effect of adaptive coupling on the temporal coherence and synchronization of spiking activity in Newman-Watts Hodgkin-Huxley neuronal networks. It is found that random shortcuts can enhance the spiking synchronization more rapidly when the increment speed of adaptive coupling is increased and can optimize the temporal coherence of spikes only when the increment speed of adaptive coupling is appropriate. It is also found that adaptive coupling strength can enhance the synchronization of spikes and can optimize the temporal coherence of spikes when random shortcuts are appropriate. These results show that adaptive coupling has a big influence on random shortcuts related spiking activity and can enhance and optimize the temporal coherence and synchronization of spiking activity of the network. These findings can help better understand the roles of adaptive coupling for improving the information processing and transmission in neural systems.

A matched-filter algorithm to detect amperometric spikes resulting from quantal secretion.

Science.gov (United States)

Balaji Ramachandran, Supriya; Gillis, Kevin D

2018-01-01

Electrochemical microelectrodes located immediately adjacent to the cell surface can detect spikes of amperometric current during exocytosis as the transmitter released from a single vesicle is oxidized on the electrode surface. Automated techniques to detect spikes are needed in order to quantify the spike rate as a measure of the rate of exocytosis. We have developed a Matched Filter (MF) detection algorithm that scans the data set with a library of prototype spike templates while performing a least-squares fit to determine the amplitude and standard error. The ratio of the fit amplitude to the standard error constitutes a criterion score that is assigned for each time point and for each template. A spike is detected when the criterion score exceeds a threshold and the highest-scoring template and the time of peak score is identified. The search for the next spike commences only after the score falls below a second, lower threshold to reduce false positives. The approach was extended to detect spikes with double-exponential decays with the sum of two templates. Receiver Operating Characteristic plots (ROCs) demonstrate that the algorithm detects >95% of manually identified spikes with a false-positive rate of ∼2%. ROCs demonstrate that the MF algorithm performs better than algorithms that detect spikes based on a derivative-threshold approach. The MF approach performs well and leads into approaches to identify spike parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

A 244Pu spike reference material CBNM IRM-042A

International Nuclear Information System (INIS)

Verbruggen, A.; Gallet, M.; Hendrickx, F.; Bievre, P. de

1991-01-01

An highly enriched 244 Pu isotopic reference material (CBNM IRM-042a) has been prepared and certified for 244 Pu isotope concentration. The certified value of (2.257 7 ± 0.004 4).10 18 atoms 242 Pu.kg -1 of solution has been established by isotope dilution mass spectrometry. The plutonium isotopic composition has been determined by thermal ionization mass spectrometry and calibration of these measurements by means of synthetic 242 Pu/ 239 Pu mixtures. The isotopic reference material is supplied in a sealed glass ampoule containing approximately 10 g of a 5M nitric acid solution at an approximate concentration of 1 μg Pu per g solution. This isotopic reference material is part of a systematic CBNM programme to supply spike isotopic reference materials of various isotopes at different concentrations

Spike sorting based upon machine learning algorithms (SOMA).

Science.gov (United States)

Horton, P M; Nicol, A U; Kendrick, K M; Feng, J F

2007-02-15

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would only identify a known number of clusters. Our extra techniques automatically identify the number of clusters within the dataset, and their sizes, thereby reducing the chance of misclassification. We also discuss a new pre-processing technique, which transforms the data into a higher dimensional feature space revealing separable clusters. Using principal component analysis (PCA) alone may not achieve this. Our new approach appends the features acquired using PCA with features describing the geometric shapes that constitute a spike waveform. To validate our new spike sorting approach, we have applied it to multi-electrode array datasets acquired from the rat olfactory bulb, and from the sheep infero-temporal cortex, and using simulated data. The SOMA sofware is available at http://www.sussex.ac.uk/Users/pmh20/spikes.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

Science.gov (United States)

Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

Inherently stochastic spiking neurons for probabilistic neural computation

KAUST Repository

Al-Shedivat, Maruan

2015-04-01

Neuromorphic engineering aims to design hardware that efficiently mimics neural circuitry and provides the means for emulating and studying neural systems. In this paper, we propose a new memristor-based neuron circuit that uniquely complements the scope of neuron implementations and follows the stochastic spike response model (SRM), which plays a cornerstone role in spike-based probabilistic algorithms. We demonstrate that the switching of the memristor is akin to the stochastic firing of the SRM. Our analysis and simulations show that the proposed neuron circuit satisfies a neural computability condition that enables probabilistic neural sampling and spike-based Bayesian learning and inference. Our findings constitute an important step towards memristive, scalable and efficient stochastic neuromorphic platforms. © 2015 IEEE.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

Directory of Open Access Journals (Sweden)

Christian Albers

Full Text Available Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP. Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious and strong (teacher spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

Science.gov (United States)

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Correlations decrease with propagation of spiking activity in the mouse barrel cortex

Directory of Open Access Journals (Sweden)

Gayathri Nattar Ranganathan

2011-05-01

Full Text Available Propagation of suprathreshold spiking activity through neuronal populations is important for the function of the central nervous system. Neural correlations have an impact on cortical function particularly on the signaling of information and propagation of spiking activity. Therefore we measured the change in correlations as suprathreshold spiking activity propagated between recurrent neuronal networks of the mammalian cerebral cortex. Using optical methods we recorded spiking activity from large samples of neurons from two neural populations simultaneously. The results indicate that correlations decreased as spiking activity propagated from layer 4 to layer 2/3 in the rodent barrel cortex.

Absolute Ca Isotopic Measurement Using an Improved Double Spike Technique

Directory of Open Access Journals (Sweden)

Jason Jiun-San Shen

2009-01-01

Full Text Available A new vector analytical method has been developed in order to obtain the true isotopic composition of the 42Ca-48Ca double spike. This is achieved by using two different sample-spike mixtures combined with the double spike and natural Ca data. Be cause the natural sample (two mixtures and the spike should all lie on a single mixing line, we are able to con strain the true isotopic composition of our double spike using this new approach. Once the isotopic composition of the Ca double spike is established, we are able to obtain the true Ca isotopic composition of the NIST Ca standard SRM915a, 40Ca/44Ca = 46.537 ± 2 (2sm, n = 55, 42Ca/44Ca = 0.31031 ± 1, 43Ca/44Ca = 0.06474 ± 1, and 48Ca/44Ca = 0.08956 ± 1. De spite an off set of 1.3% in 40Ca/44Ca between our result and the previously re ported value (Russell et al. 1978, our data indicate an off set of 1.89__in 40Ca/44Ca between SRM915a and seawater, entirely consistent with the published results.

The Nature of Power Spikes: a regime-switch approach

NARCIS (Netherlands)

C.M. de Jong (Cyriel)

2005-01-01

textabstractDue to its non-storable nature, electricity is a commodity with probably the most volatile spot prices, exemplified by occasional spikes. Appropriate pricing, portfolio, and risk management models have to incorporate these characteristics, and the spikes in particular. We investigate the

Transcriptome Analysis for Abnormal Spike Development of the Wheat Mutant dms.

Science.gov (United States)

Zhu, Xin-Xin; Li, Qiao-Yun; Shen, Chun-Cai; Duan, Zong-Biao; Yu, Dong-Yan; Niu, Ji-Shan; Ni, Yong-Jing; Jiang, Yu-Mei

2016-01-01

Wheat (Triticum aestivum L.) spike development is the foundation for grain yield. We obtained a novel wheat mutant, dms, characterized as dwarf, multi-pistil and sterility. Although the genetic changes are not clear, the heredity of traits suggests that a recessive gene locus controls the two traits of multi-pistil and sterility in self-pollinating populations of the medium plants (M), such that the dwarf genotype (D) and tall genotype (T) in the progeny of the mutant are ideal lines for studies regarding wheat spike development. The objective of this study was to explore the molecular basis for spike abnormalities of dwarf genotype. Four unigene libraries were assembled by sequencing the mRNAs of the super-bulked differentiating spikes and stem tips of the D and T plants. Using integrative analysis, we identified 419 genes highly expressed in spikes, including nine typical homeotic genes of the MADS-box family and the genes TaAP2, TaFL and TaDL. We also identified 143 genes that were significantly different between young spikes of T and D, and 26 genes that were putatively involved in spike differentiation. The result showed that the expression levels of TaAP1-2, TaAP2, and other genes involved in the majority of biological processes such as transcription, translation, cell division, photosynthesis, carbohydrate transport and metabolism, and energy production and conversion were significantly lower in D than in T. We identified a set of genes related to wheat floral organ differentiation, including typical homeotic genes. Our results showed that the major causal factors resulting in the spike abnormalities of dms were the lower expression homeotic genes, hormonal imbalance, repressed biological processes, and deficiency of construction materials and energy. We performed a series of studies on the homeotic genes, however the other three causal factors for spike abnormal phenotype of dms need further study.

Melting of Au and Al in nanometer Fe/Au and Fe/Al multilayers under swift heavy ions: A thermal spike study

International Nuclear Information System (INIS)

Chettah, A.; Wang, Z.G.; Kac, M.; Kucal, H.; Meftah, A.; Toulemonde, M.

2006-01-01

Knowing that Fe is sensitive to swift heavy ion irradiations whereas Au and Al are not, the behavior of nanometric metallic multilayer systems, like [Fe(3 nm)/Au(x)] y and [Fe(3 nm)/Al(x)] y with x ranging between 1 and 10 nm, were studied within the inelastic thermal spike model. In addition to the usual cylindrical geometry of energy dissipation perpendicular to the ion projectile direction, the heat transport along the ion path was implemented in the electronic and atomic sub-systems. The simulations were performed using three different values of linear energy transfer corresponding to 3 MeV/u of 208 Pb, 132 Xe and 84 Kr ions. For the Fe/Au system, evidence of appearance of a molten phase was found in the entire Au layer, provided the Au thickness is less than 7 nm and 3 nm for Pb and Xe ions, respectively. For the Fe/Al(x) system irradiated with Pb ions, the Al layers with a thickness less than 4 nm melt along the entire ion track. Surprisingly, the Fe layer does not melt if the Al thickness is larger than 2 nm, although the deposited energy surpasses the electronic stopping power threshold of track formation in Fe. For Kr ions melting does not occur in any of the multilayer systems

Axonal propagation of simple and complex spikes in cerebellar Purkinje neurons.

Science.gov (United States)

Khaliq, Zayd M; Raman, Indira M

2005-01-12

In cerebellar Purkinje neurons, the reliability of propagation of high-frequency simple spikes and spikelets of complex spikes is likely to regulate inhibition of Purkinje target neurons. To test the extent to which a one-to-one correspondence exists between somatic and axonal spikes, we made dual somatic and axonal recordings from Purkinje neurons in mouse cerebellar slices. Somatic action potentials were recorded with a whole-cell pipette, and the corresponding axonal signals were recorded extracellularly with a loose-patch pipette. Propagation of spontaneous and evoked simple spikes was highly reliable. At somatic firing rates of approximately 200 spikes/sec, 375 Hz during somatic hyperpolarizations that silenced spontaneous firing to approximately 150 Hz during spontaneous activity. The probability of propagation of individual spikelets could be described quantitatively as a saturating function of spikelet amplitude, rate of rise, or preceding interspike interval. The results suggest that ion channels of Purkinje axons are adapted to produce extremely short refractory periods and that brief bursts of forward-propagating action potentials generated by complex spikes may contribute transiently to inhibition of postsynaptic neurons.

The chronotron: a neuron that learns to fire temporally precise spike patterns.

Directory of Open Access Journals (Sweden)

Răzvan V Florian

Full Text Available In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons, one that provides high memory capacity (E-learning, and one that has a higher biological plausibility (I-learning. With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm.

Climate Change Effect on Thermal Power Cooling in the U.S.

Science.gov (United States)

Maintaining reasonable surface-water temperatures is paramount for aquatic ecosystem health. Thermal pollution from power plant effluent can result in unnatural river temperature spikes locally, as well as cause damaging breaches to river temperature. The threat of a nonstationar...

Accelerated spike resampling for accurate multiple testing controls.

Science.gov (United States)

Harrison, Matthew T

2013-02-01

Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity.

Science.gov (United States)

D'Souza, Prashanth; Liu, Shih-Chii; Hahnloser, Richard H R

2010-03-09

It is widely believed that sensory and motor processing in the brain is based on simple computational primitives rooted in cellular and synaptic physiology. However, many gaps remain in our understanding of the connections between neural computations and biophysical properties of neurons. Here, we show that synaptic spike-time-dependent plasticity (STDP) combined with spike-frequency adaptation (SFA) in a single neuron together approximate the well-known perceptron learning rule. Our calculations and integrate-and-fire simulations reveal that delayed inputs to a neuron endowed with STDP and SFA precisely instruct neural responses to earlier arriving inputs. We demonstrate this mechanism on a developmental example of auditory map formation guided by visual inputs, as observed in the external nucleus of the inferior colliculus (ICX) of barn owls. The interplay of SFA and STDP in model ICX neurons precisely transfers the tuning curve from the visual modality onto the auditory modality, demonstrating a useful computation for multimodal and sensory-guided processing.

Real-time computing platform for spiking neurons (RT-spike).

Science.gov (United States)

Ros, Eduardo; Ortigosa, Eva M; Agís, Rodrigo; Carrillo, Richard; Arnold, Michael

2006-07-01

A computing platform is described for simulating arbitrary networks of spiking neurons in real time. A hybrid computing scheme is adopted that uses both software and hardware components to manage the tradeoff between flexibility and computational power; the neuron model is implemented in hardware and the network model and the learning are implemented in software. The incremental transition of the software components into hardware is supported. We focus on a spike response model (SRM) for a neuron where the synapses are modeled as input-driven conductances. The temporal dynamics of the synaptic integration process are modeled with a synaptic time constant that results in a gradual injection of charge. This type of model is computationally expensive and is not easily amenable to existing software-based event-driven approaches. As an alternative we have designed an efficient time-based computing architecture in hardware, where the different stages of the neuron model are processed in parallel. Further improvements occur by computing multiple neurons in parallel using multiple processing units. This design is tested using reconfigurable hardware and its scalability and performance evaluated. Our overall goal is to investigate biologically realistic models for the real-time control of robots operating within closed action-perception loops, and so we evaluate the performance of the system on simulating a model of the cerebellum where the emulation of the temporal dynamics of the synaptic integration process is important.

High-precision measurements of seawater Pb isotope compositions by double spike thermal ionization mass spectrometry.

Science.gov (United States)

Paul, Maxence; Bridgestock, Luke; Rehkämper, Mark; van DeFlierdt, Tina; Weiss, Dominik

2015-03-10

A new method for the determination of seawater Pb isotope compositions and concentrations was developed, which combines and optimizes previously published protocols for the separation and isotopic analysis of this element. For isotopic analysis, the procedure involves initial separation of Pb from 1 to 2L of seawater by co-precipitation with Mg hydroxide and further purification by a two stage anion exchange procedure. The Pb isotope measurements are subsequently carried out by thermal ionization mass spectrometry using a (207)Pb-(204)Pb double spike for correction of instrumental mass fractionation. These methods are associated with a total procedural Pb blank of 28±21 pg (1sd) and typical Pb recoveries of 40-60%. The Pb concentrations are determined by isotope dilution (ID) on 50 mL of seawater, using a simplified version of above methods. Analyses of multiple aliquots of six seawater samples yield a reproducibility of about ±1 to ±10% (1sd) for Pb concentrations of between 7 and 50 pmol/kg, where precision was primarily limited by the uncertainty of the blank correction (12±4 pg; 1sd). For the Pb isotope analyses, typical reproducibilities (±2sd) of 700-1500 ppm and 1000-2000 ppm were achieved for (207)Pb/(206)Pb, (208)Pb/(206)Pb and (206)Pb/(204)Pb, (207)Pb/(204)Pb, (208)Pb/(204)Pb, respectively. These results are superior to literature data that were obtained using plasma source mass spectrometry and they are at least a factor of five more precise for ratios involving the minor (204)Pb isotope. Both Pb concentration and isotope data, furthermore, show good agreement with published results for two seawater intercomparison samples of the GEOTRACES program. Finally, the new methods were applied to a seawater depth profile from the eastern South Atlantic. Both Pb contents and isotope compositions display a smooth evolution with depth, and no obvious outliers. Compared to previous Pb isotope data for seawater, the (206)Pb/(204)Pb ratios are well correlated

SPAN: spike pattern association neuron for learning spatio-temporal sequences

OpenAIRE

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

2012-01-01

Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the prec...

Impact of substance P on the correlation of spike train evoked by electro acupuncture

International Nuclear Information System (INIS)

Jin, Chen; Zhang, Xuan; Wang, Jiang; Guo, Yi; Zhao, Xue; Guo, Yong-Ming

2016-01-01

Highlights: • We analyze spike trains induced by EA before and after inhibiting SP in PC6 area. • Inhibiting SP leads to an increase of spiking rate of median nerve. • SP may modulate membrane potential to affect the spiking rate. • SP has an influence on long-range correlation of spike train evoked by EA. • SP play an important role in EA-induced neural spiking and encoding. - Abstract: Substance P (SP) participates in the neural signal transmission evoked by electro-acupuncture (EA). This paper investigates the impact of SP on the correlation of spike train in the median nerve evoked by EA at 'Neiguan' acupoint (PC6). It shows that the spiking rate and interspike interval (ISI) distribution change obviously after inhibiting SP. This variation of spiking activity indicates that SP affects the temporal structure of spike train through modulating the action potential on median nerve filaments. Furtherly, the correlation coefficient and scaling exponent are considered to measure the correlation of spike train. Scaled Windowed Variance (SWV) method is applied to calculate scaling exponent which quantifies the long-range correlation of the neural electrical signals. It is found that the correlation coefficients of ISI increase after inhibiting SP released. In addition, the scaling exponents of neuronal spike train have significant differences between before and after inhibiting SP. These findings demonstrate that SP has an influence on the long-range correlation of spike train. Our results indicate that SP may play an important role in EA-induced neural spiking and encoding.

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

Science.gov (United States)

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

The transfer function of neuron spike.

Science.gov (United States)

Palmieri, Igor; Monteiro, Luiz H A; Miranda, Maria D

2015-08-01

The mathematical modeling of neuronal signals is a relevant problem in neuroscience. The complexity of the neuron behavior, however, makes this problem a particularly difficult task. Here, we propose a discrete-time linear time-invariant (LTI) model with a rational function in order to represent the neuronal spike detected by an electrode located in the surroundings of the nerve cell. The model is presented as a cascade association of two subsystems: one that generates an action potential from an input stimulus, and one that represents the medium between the cell and the electrode. The suggested approach employs system identification and signal processing concepts, and is dissociated from any considerations about the biophysical processes of the neuronal cell, providing a low-complexity alternative to model the neuronal spike. The model is validated by using in vivo experimental readings of intracellular and extracellular signals. A computational simulation of the model is presented in order to assess its proximity to the neuronal signal and to observe the variability of the estimated parameters. The implications of the results are discussed in the context of spike sorting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cochlear spike synchronization and neuron coincidence detection model

Science.gov (United States)

Bader, Rolf

2018-02-01

Coincidence detection of a spike pattern fed from the cochlea into a single neuron is investigated using a physical Finite-Difference model of the cochlea and a physiologically motivated neuron model. Previous studies have shown experimental evidence of increased spike synchronization in the nucleus cochlearis and the trapezoid body [Joris et al., J. Neurophysiol. 71(3), 1022-1036 and 1037-1051 (1994)] and models show tone partial phase synchronization at the transition from mechanical waves on the basilar membrane into spike patterns [Ch. F. Babbs, J. Biophys. 2011, 435135]. Still the traveling speed of waves on the basilar membrane cause a frequency-dependent time delay of simultaneously incoming sound wavefronts up to 10 ms. The present model shows nearly perfect synchronization of multiple spike inputs as neuron outputs with interspike intervals (ISI) at the periodicity of the incoming sound for frequencies from about 30 to 300 Hz for two different amounts of afferent nerve fiber neuron inputs. Coincidence detection serves here as a fusion of multiple inputs into one single event enhancing pitch periodicity detection for low frequencies, impulse detection, or increased sound or speech intelligibility due to dereverberation.

The variational spiked oscillator

International Nuclear Information System (INIS)

Aguilera-Navarro, V.C.; Ullah, N.

1992-08-01

A variational analysis of the spiked harmonic oscillator Hamiltonian -d 2 / d x 2 + x 2 + δ/ x 5/2 , δ > 0, is reported in this work. A trial function satisfying Dirichlet boundary conditions is suggested. The results are excellent for a large range of values of the coupling parameter. (author)

Trace element ink spiking for signature authentication

International Nuclear Information System (INIS)

Hatzistavros, V.S.; Kallithrakas-Kontos, N.G.

2008-01-01

Signature authentication is a critical question in forensic document examination. Last years the evolution of personal computers made signature copying a quite easy task, so the development of new ways for signature authentication is crucial. In the present work a commercial ink was spiked with many trace elements in various concentrations. Inorganic and organometallic ink soluble compounds were used as spiking agents, whilst ink retained its initial properties. The spiked inks were used for paper writing and the documents were analyzed by a non destructive method, the energy dispersive X-ray fluorescence. The thin target model was proved right for quantitative analysis and a very good linear relationship of the intensity (X-ray signal) against concentration was estimated for all used elements. Intensity ratios between different elements in the same ink gave very stable results, independent on the writing alterations. The impact of time both to written document and prepared inks was also investigated. (author)

A Novel and Simple Spike Sorting Implementation.

Science.gov (United States)

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2017-04-01

Monitoring the activity of multiple, individual neurons that fire spikes in the vicinity of an electrode, namely perform a Spike Sorting (SS) procedure, comprises one of the most important tools for contemporary neuroscience in order to reverse-engineer the brain. As recording electrodes' technology rabidly evolves by integrating thousands of electrodes in a confined spatial setting, the algorithms that are used to monitor individual neurons from recorded signals have to become even more reliable and computationally efficient. In this work, we propose a novel framework of the SS approach in which a single-step processing of the raw (unfiltered) extracellular signal is sufficient for both the detection and sorting of the activity of individual neurons. Despite its simplicity, the proposed approach exhibits comparable performance with state-of-the-art approaches, especially for spike detection in noisy signals, and paves the way for a new family of SS algorithms with the potential for multi-recording, fast, on-chip implementations.

A Fully Automated Approach to Spike Sorting.

Science.gov (United States)

Chung, Jason E; Magland, Jeremy F; Barnett, Alex H; Tolosa, Vanessa M; Tooker, Angela C; Lee, Kye Y; Shah, Kedar G; Felix, Sarah H; Frank, Loren M; Greengard, Leslie F

2017-09-13

Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible. Copyright © 2017 Elsevier Inc. All rights reserved.

A case-control study of wicket spikes using video-EEG monitoring.

Science.gov (United States)

Vallabhaneni, Maya; Baldassari, Laura E; Scribner, James T; Cho, Yong Won; Motamedi, Gholam K

2013-01-01

To investigate clinical characteristics associated with wicket spikes in patients undergoing long-term video-EEG monitoring. A case-control study was performed in 479 patients undergoing video-EEG monitoring, with 3 age- (±3 years) and gender-matched controls per patient with wicket spikes. Logistic regression was utilized to investigate the association between wicket spikes and other factors, including conditions that have been previously associated with wicket spikes. Wicket spikes were recorded in 48 patients. There was a significantly higher prevalence of dizziness/vertigo (p=0.002), headaches (p=0.005), migraine (p=0.015), and seizures (p=0.016) in patients with wickets. The majority of patients with wicket spikes did not exhibit epileptiform activity on EEG; however, patients with history of seizures were more likely to have wickets (p=0.017). There was no significant difference in the prevalence of psychogenic non-epileptic seizures between the groups. Wickets were more common on the left, during sleep, and more likely to be first recorded on day 1-2 of monitoring. Patients with wicket spikes are more likely to have dizziness/vertigo, headaches, migraine, and seizures. Patients with history of seizures are more likely to have wickets. The prevalence of psychogenic non-epileptic seizures is not significantly higher in patients with wickets. Copyright © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.

Science.gov (United States)

Koyama, Shinsuke

2015-07-01

We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

Science.gov (United States)

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.

Science.gov (United States)

Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen

2016-01-01

The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper.

Isotope and Patient Age Predict for PSA Spikes After Permanent Prostate Brachytherapy

International Nuclear Information System (INIS)

Bostancic, Chelsea; Merrick, Gregory S.; Butler, Wayne M.; Wallner, Kent E.; Allen, Zachariah; Galbreath, Robert; Lief, Jonathan; Gutman, Sarah E.

2007-01-01

Purpose: To evaluate prostate-specific antigen (PSA) spikes after permanent prostate brachytherapy in low-risk patients. Methods and Materials: The study population consisted of 164 prostate cancer patients who were part of a prospective randomized trial comparing 103 Pd and 125 I for low-risk disease. Of the 164 patients, 61 (37.2%) received short-course androgen deprivation therapy. The median follow-up was 5.4 years. On average, 11.1 post-treatment PSA measurements were obtained per patient. Biochemical disease-free survival was defined as a PSA level of ≤0.40 ng/mL after nadir. A PSA spike was defined as an increase of ≥0.2 ng/mL, followed by a durable decline to prespike levels. Multiple parameters were evaluated as predictors for a PSA spike. Results: Of the 164 patients, 44 (26.9%) developed a PSA spike. Of the 46 hormone-naive 125 I patients and 57 hormone-naive 103 Pd patients, 21 (45.7%) and 8 (14.0%) developed a PSA spike. In the hormone-naive patients, the mean time between implantation and the spike was 22.6 months and 18.7 months for 125 I and 103 Pd, respectively. In patients receiving neoadjuvant androgen deprivation therapy, the incidence of spikes was comparable between isotopes ( 125 I 28.1% and 103 Pd 20.7%). The incidence of spikes was substantially different in patients 125 I and/or <65 years of age. Differences in isotope-related spikes are most pronounced in hormone-naive patients

Boobs, Boxing, and Bombs: Problematizing the Entertainment of Spike TV

OpenAIRE

Walton, Gerald; Potvin, L.

2009-01-01

Spike is the only television network in North America “for men.” Its motto, “Get more action,” is suggestive of pursuits of various forms of violence. We conceptualize Spike not as trivial entertainment, but rather as a form of pop culture that erodes the gains of feminists who have challenged the prevalence of normalized hegemonic masculinity (HM). Our paper highlights themes of Spike content, and connects those themes to the literature on HM. Moreover, we validate the identities and lives ...

Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning.

Science.gov (United States)

Kuroda, S; Yamamoto, K; Miyamoto, H; Doya, K; Kawat, M

2001-03-01

Mean firing rates (MFRs), with analogue values, have thus far been used as information carriers of neurons in most brain theories of learning. However, the neurons transmit the signal by spikes, which are discrete events. The climbing fibers (CFs), which are known to be essential for cerebellar motor learning, fire at the ultra-low firing rates (around 1 Hz), and it is not yet understood theoretically how high-frequency information can be conveyed and how learning of smooth and fast movements can be achieved. Here we address whether cerebellar learning can be achieved by CF spikes instead of conventional MFR in an eye movement task, such as the ocular following response (OFR), and an arm movement task. There are two major afferents into cerebellar Purkinje cells: parallel fiber (PF) and CF, and the synaptic weights between PFs and Purkinje cells have been shown to be modulated by the stimulation of both types of fiber. The modulation of the synaptic weights is regulated by the cerebellar synaptic plasticity. In this study we simulated cerebellar learning using CF signals as spikes instead of conventional MFR. To generate the spikes we used the following four spike generation models: (1) a Poisson model in which the spike interval probability follows a Poisson distribution, (2) a gamma model in which the spike interval probability follows the gamma distribution, (3) a max model in which a spike is generated when a synaptic input reaches maximum, and (4) a threshold model in which a spike is generated when the input crosses a certain small threshold. We found that, in an OFR task with a constant visual velocity, learning was successful with stochastic models, such as Poisson and gamma models, but not in the deterministic models, such as max and threshold models. In an OFR with a stepwise velocity change and an arm movement task, learning could be achieved only in the Poisson model. In addition, for efficient cerebellar learning, the distribution of CF spike

Computational investigations of blunt body drag-reduction spikes in hypersonic flows

International Nuclear Information System (INIS)

Kamran, N.; Zahir, S.; Khan, M.A.

2003-01-01

Drag is an important parameter in the designing of high-speed vehicles. Such vehicles include hypervelocity projectiles, reentry modules, and hypersonic aircrafts. Therefore, there exists an active or passive technique to reduce drag due to the high pressures at nosetip region of the vehicle. Drag can be reduced by attaching a forward facing spike on the nose of the vehicle. The present study reviews and deals with the CFD analysis made on a standard blunt body to reduce aerodynamic drag due to the attachment of forward facing spikes for High-Speed vehicles. Different spike lengths have been examined to study the forebody flowfield. The investigation concludes that spikes are an effective way to reduce the aerodynamic drag due to reduced dynamic pressure on the nose caused by the separated flow on the spikes. With the accomplishment of confidence on computational data, study was extended in hypersonic Mach range with a drag prediction accuracy of ± 10%. In the present work, viscous fluid dynamics studies were performed for a complete freestream Mach number range of 5.0, 6.0, 7.0 and 8.0 for different spike lengths and zero degree angle of attack. (author)

Transient reduction in theta power caused by interictal spikes in human temporal lobe epilepsy.

Science.gov (United States)

Manling Ge; Jundan Guo; Yangyang Xing; Zhiguo Feng; Weide Lu; Xinxin Ma; Yuehua Geng; Xin Zhang

2017-07-01

The inhibitory impacts of spikes on LFP theta rhythms(4-8Hz) are investigated around sporadic spikes(SSs) based on intracerebral EEG of 4 REM sleep patients with temporal lobe epilepsy(TLE) under the pre-surgical monitoring. Sequential interictal spikes in both genesis area and extended propagation pathway are collected, that, SSs genesis only in anterior hippocampus(aH)(possible propagation pathway in Entorhinal cortex(EC)), only in EC(possible propagation pathway in aH), and in both aH and EC synchronously. Instantaneous theta power was estimated by using Gabor wavelet transform, and theta power level was estimated by averaged over time and frequency before SSs(350ms pre-spike) and after SSs(350ms post-spike). The inhibitory effect around spikes was evaluated by the ratio of theta power level difference between pre-spike and post-spike to pre-spike theta power level. The findings were that theta power level was reduced across SSs, and the effects were more sever in the case of SSs in both aH and EC synchronously than either SSs only in EC or SSs only in aH. It is concluded that interictal spikes impair LFP theta rhythms transiently and directly. The work suggests that the reduction of theta power after the interictal spike might be an evaluation indicator of damage of epilepsy to human cognitive rhythms.

From quantum mechanics to finance: Microfoundations for jumps, spikes and high volatility phases in diffusion price processes

Science.gov (United States)

Henkel, Christof

2017-03-01

We present an agent behavior based microscopic model that induces jumps, spikes and high volatility phases in the price process of a traded asset. We transfer dynamics of thermally activated jumps of an unexcited/excited two state system discussed in the context of quantum mechanics to agent socio-economic behavior and provide microfoundations. After we link the endogenous agent behavior to price dynamics we establish the circumstances under which the dynamics converge to an Itô-diffusion price processes in the large market limit.

Spectral components of cytosolic [Ca2+] spiking in neurons

DEFF Research Database (Denmark)

Kardos, J; Szilágyi, N; Juhász, G

1998-01-01

. Delayed complex responses of large [Ca2+]c spiking observed in cells from a different set of cultures were synthesized by a set of frequencies within the range 0.018-0.117 Hz. Differential frequency patterns are suggested as characteristics of the [Ca2+]c spiking responses of neurons under different...

Unsupervised clustering with spiking neurons by sparse temporal coding and multi-layer RBF networks

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractWe demonstrate that spiking neural networks encoding information in spike times are capable of computing and learning clusters from realistic data. We show how a spiking neural network based on spike-time coding and Hebbian learning can successfully perform unsupervised clustering on

Spike-timing-based computation in sound localization.

Directory of Open Access Journals (Sweden)

Dan F M Goodman

2010-11-01

Full Text Available Spike timing is precise in the auditory system and it has been argued that it conveys information about auditory stimuli, in particular about the location of a sound source. However, beyond simple time differences, the way in which neurons might extract this information is unclear and the potential computational advantages are unknown. The computational difficulty of this task for an animal is to locate the source of an unexpected sound from two monaural signals that are highly dependent on the unknown source signal. In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. The model was able to accurately estimate the location of previously unknown sounds in both azimuth and elevation (including front/back discrimination in a known acoustic environment. We found that multiple representations of different acoustic environments could coexist as sets of overlapping neural assemblies which could be associated with spatial locations by Hebbian learning. The model demonstrates the computational relevance of relative spike timing to extract spatial information about sources independently of the source signal.

Neural Spike Train Synchronisation Indices: Definitions, Interpretations and Applications.

Science.gov (United States)

Halliday, D M; Rosenberg, J R

2017-04-24

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second order cumulant. The simulations used a paired motoneurone model and a paired regular spiking cortical neurone model. The sampling variability of spike trains generated under identical conditions from the paired motoneurone model varied from 50% { 160% of the estimated value. On theoretical grounds, and on the basis of simulated data a rate dependence is present in all synchronization indices. The application of coherence and pooled coherence estimates to the issue of synchronization indices is considered. This alternative frequency domain approach allows an arbitrary number of spike train pairs to be evaluated for statistically significant differences, and combined into a single population measure. The pooled coherence framework allows pooled time domain measures to be derived, application of this to the simulated data is illustrated. Data from the cortical neurone model is generated over a wide range of firing rates (1 - 250 spikes/sec). The pooled coherence framework correctly characterizes the sampling variability as not significant over this wide operating range. The broader applicability of this approach to multi electrode array data is briefly discussed.

Visualizing spikes in source-space

DEFF Research Database (Denmark)

Beniczky, Sándor; Duez, Lene; Scherg, Michael

2016-01-01

OBJECTIVE: Reviewing magnetoencephalography (MEG) recordings is time-consuming: signals from the 306 MEG-sensors are typically reviewed divided into six arrays of 51 sensors each, thus browsing each recording six times in order to evaluate all signals. A novel method of reconstructing the MEG...... signals in source-space was developed using a source-montage of 29 brain-regions and two spatial components to remove magnetocardiographic (MKG) artefacts. Our objective was to evaluate the accuracy of reviewing MEG in source-space. METHODS: In 60 consecutive patients with epilepsy, we prospectively...... evaluated the accuracy of reviewing the MEG signals in source-space as compared to the classical method of reviewing them in sensor-space. RESULTS: All 46 spike-clusters identified in sensor-space were also identified in source-space. Two additional spike-clusters were identified in source-space. As 29...

Temporal Correlations and Neural Spike Train Entropy

International Nuclear Information System (INIS)

Schultz, Simon R.; Panzeri, Stefano

2001-01-01

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a 'brute force' approach

Channel noise effects on first spike latency of a stochastic Hodgkin-Huxley neuron

Science.gov (United States)

Maisel, Brenton; Lindenberg, Katja

2017-02-01

While it is widely accepted that information is encoded in neurons via action potentials or spikes, it is far less understood what specific features of spiking contain encoded information. Experimental evidence has suggested that the timing of the first spike may be an energy-efficient coding mechanism that contains more neural information than subsequent spikes. Therefore, the biophysical features of neurons that underlie response latency are of considerable interest. Here we examine the effects of channel noise on the first spike latency of a Hodgkin-Huxley neuron receiving random input from many other neurons. Because the principal feature of a Hodgkin-Huxley neuron is the stochastic opening and closing of channels, the fluctuations in the number of open channels lead to fluctuations in the membrane voltage and modify the timing of the first spike. Our results show that when a neuron has a larger number of channels, (i) the occurrence of the first spike is delayed and (ii) the variation in the first spike timing is greater. We also show that the mean, median, and interquartile range of first spike latency can be accurately predicted from a simple linear regression by knowing only the number of channels in the neuron and the rate at which presynaptic neurons fire, but the standard deviation (i.e., neuronal jitter) cannot be predicted using only this information. We then compare our results to another commonly used stochastic Hodgkin-Huxley model and show that the more commonly used model overstates the first spike latency but can predict the standard deviation of first spike latencies accurately. We end by suggesting a more suitable definition for the neuronal jitter based upon our simulations and comparison of the two models.

Transformation-invariant visual representations in self-organizing spiking neural networks.

Science.gov (United States)

Evans, Benjamin D; Stringer, Simon M

2012-01-01

The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Transform-invariant visual representations in self-organizing spiking neural networks

Directory of Open Access Journals (Sweden)

Benjamin eEvans

2012-07-01

Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

Science.gov (United States)

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.

Directory of Open Access Journals (Sweden)

Laureline Logiaco

2015-08-01

Full Text Available The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70-200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys' behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.

Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.

Science.gov (United States)

Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

2015-08-01

The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70-200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys' behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.

A memristive spiking neuron with firing rate coding

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Marina eIgnatov

2015-10-01

Full Text Available Perception, decisions, and sensations are all encoded into trains of action potentials in the brain. The relation between stimulus strength and all-or-nothing spiking of neurons is widely believed to be the basis of this coding. This initiated the development of spiking neuron models; one of today's most powerful conceptual tool for the analysis and emulation of neural dynamics. The success of electronic circuit models and their physical realization within silicon field-effect transistor circuits lead to elegant technical approaches. Recently, the spectrum of electronic devices for neural computing has been extended by memristive devices, mainly used to emulate static synaptic functionality. Their capabilities for emulations of neural activity were recently demonstrated using a memristive neuristor circuit, while a memristive neuron circuit has so far been elusive. Here, a spiking neuron model is experimentally realized in a compact circuit comprising memristive and memcapacitive devices based on the strongly correlated electron material vanadium dioxide (VO2 and on the chemical electromigration cell Ag/TiO2-x/Al. The circuit can emulate dynamical spiking patterns in response to an external stimulus including adaptation, which is at the heart of firing rate coding as first observed by E.D. Adrian in 1926.

Spike Neural Models Part II: Abstract Neural Models

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Johnson, Melissa G.

2018-02-01

Full Text Available Neurons are complex cells that require a lot of time and resources to model completely. In spiking neural networks (SNN though, not all that complexity is required. Therefore simple, abstract models are often used. These models save time, use less computer resources, and are easier to understand. This tutorial presents two such models: Izhikevich's model, which is biologically realistic in the resulting spike trains but not in the parameters, and the Leaky Integrate and Fire (LIF model which is not biologically realistic but does quickly and easily integrate input to produce spikes. Izhikevich's model is based on Hodgkin-Huxley's model but simplified such that it uses only two differentiation equations and four parameters to produce various realistic spike patterns. LIF is based on a standard electrical circuit and contains one equation. Either of these two models, or any of the many other models in literature can be used in a SNN. Choosing a neural model is an important task that depends on the goal of the research and the resources available. Once a model is chosen, network decisions such as connectivity, delay, and sparseness, need to be made. Understanding neural models and how they are incorporated into the network is the first step in creating a SNN.

Interspike Interval Based Filtering of Directional Selective Retinal Ganglion Cells Spike Trains

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Aurel Vasile Martiniuc

2012-01-01

Full Text Available The information regarding visual stimulus is encoded in spike trains at the output of retina by retinal ganglion cells (RGCs. Among these, the directional selective cells (DSRGC are signaling the direction of stimulus motion. DSRGCs' spike trains show accentuated periods of short interspike intervals (ISIs framed by periods of isolated spikes. Here we use two types of visual stimulus, white noise and drifting bars, and show that short ISI spikes of DSRGCs spike trains are more often correlated to their preferred stimulus feature (that is, the direction of stimulus motion and carry more information than longer ISI spikes. Firstly, our results show that correlation between stimulus and recorded neuronal response is best at short ISI spiking activity and decrease as ISI becomes larger. We then used grating bars stimulus and found that as ISI becomes shorter the directional selectivity is better and information rates are higher. Interestingly, for the less encountered type of DSRGC, known as ON-DSRGC, short ISI distribution and information rates revealed consistent differences when compared with the other directional selective cell type, the ON-OFF DSRGC. However, these findings suggest that ISI-based temporal filtering integrates a mechanism for visual information processing at the output of retina toward higher stages within early visual system.

Structured chaos shapes spike-response noise entropy in balanced neural networks

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Guillaume eLajoie

2014-10-01

Full Text Available Large networks of sparsely coupled, excitatory and inhibitory cells occur throughout the brain. For many models of these networks, a striking feature is that their dynamics are chaotic and thus, are sensitive to small perturbations. How does this chaos manifest in the neural code? Specifically, how variable are the spike patterns that such a network produces in response to an input signal? To answer this, we derive a bound for a general measure of variability -- spike-train entropy. This leads to important insights on the variability of multi-cell spike pattern distributions in large recurrent networks of spiking neurons responding to fluctuating inputs. The analysis is based on results from random dynamical systems theory and is complemented by detailed numerical simulations. We find that the spike pattern entropy is an order of magnitude lower than what would be extrapolated from single cells. This holds despite the fact that network coupling becomes vanishingly sparse as network size grows -- a phenomenon that depends on ``extensive chaos, as previously discovered for balanced networks without stimulus drive. Moreover, we show how spike pattern entropy is controlled by temporal features of the inputs. Our findings provide insight into how neural networks may encode stimuli in the presence of inherently chaotic dynamics.

A step-wise steerable source of illumination for low-noise "Violin-Mode" shadow sensors, intended for use in interferometric gravitational wave detectors

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Lockerbie, N. A.; Tokmakov, K. V.

2016-01-01

A steerable low-noise source of illumination is described for shadow-sensors having a displacement sensitivity of ˜100 pm (rms)/√Hz, at 500 Hz, over a measuring span of at least ±0.5 mm. These sensors were designed to detect lateral "Violin-Mode" resonances in the highly tensioned fused-silica suspension fibres of the test-masses/mirrors for the Advanced Laser Interferometer Gravitational Wave Observatory gravitational wave detectors. The shadow sensors—one intended for each of the four fibres in a suspension—comprised a source of Near InfraRed (NIR) radiation (emitter) and a differential shadow-displacement sensor (detector), these bracketing the fibre under test. The suspension fibres themselves were approximately 600 mm long by 0.4 mm in diameter, and when illuminated from the side, they cast narrow, vertical, shadows onto their respective detectors—these being located at an effective distance of 50 fibre diameters behind the axes of the fibres themselves. The emitter described here was designed to compensate for a significant degree of mechanical drift or creep over time in the mean position of its suspension fibre. This was achieved by employing five adjacent columns of 8 × miniature NIR LEDs (Light Emitting Diodes, λ = 890 nm), with one column being activated at a time. When used in conjunction with a "reverse Galilean" telescope, the LED sources allowed the collimated beam from the emitter to be steered azimuthally in fine angular increments (0.65°), causing the fibre's shadow to move laterally, in a step-wise manner, across the plane of its facing detector. Each step in shadow position was approximately 0.23 mm in size, and this allowed the fibre's shadow to be re-centred, so as to bridge once again both elements of its photodiode detector—even if the fibre was off-centred by as much as ±0.5 mm. Re-centring allowed Violin-Mode vibrations of the fibre to be sensed once again as differential AC photocurrents, these flowing in anti-phase in the

Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

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Sailamul, Pachaya; Jang, Jaeson; Paik, Se-Bum

2017-12-01

Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

Prevalence and Associated Factors of Playing-Related Musculoskeletal Disorders in Brazilian Violin Players.

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Kochem, Frederico B; Silva, Julio G

2017-03-01

To investigate the prevalence of playing-related musculoskeletal disorders (PRMD) and associated factors among violinists from the state of Rio de Janeiro, Brazil. This cross-sectional study included 106 violinists from eight cities in the state of Rio de Janeiro. Sociodemographic and musical characteristic data, pain symptoms, and upper-limb functionality were collected using the DASH and the Standardized Nordic Questionnaires. The associations between musculoskeletal complaints and possible predictors were analyzed by binary logistic regression. Of the 106 surveyed violin players, 86.8% reported at least one painful area in the last 12 months and 77.4% in the last week. These symptoms were responsible for the temporary interruption of musical activity in 8.1% of musicians. More than 50% of violinists showed dysfunctional upper limbs according to the DASH optional module. Women were more likely to develop musculoskeletal disorders (OR 4.4, CI 1.9-10.0, p<0.001). In addition, older musicians were more likely to report pain in the last 7 days (OR 3.3, CI 5.1-10.97; p=0.04) and also had higher scores on the DASH (OR 1.8, CI 1.1-3.1; p=0.01). Other factors associated with the development of PRMD were body mass index, practice hours per week, and final DASH score. Violinists living and working in the state of Rio de Janeiro have a high prevalence of PRMD, especially women and older musicians.

Routes to Chaos Induced by a Discontinuous Resetting Process in a Hybrid Spiking Neuron Model.

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Nobukawa, Sou; Nishimura, Haruhiko; Yamanishi, Teruya

2018-01-10

Several hybrid spiking neuron models combining continuous spike generation mechanisms and discontinuous resetting processes following spiking have been proposed. The Izhikevich neuron model, for example, can reproduce many spiking patterns. This model clearly possesses various types of bifurcations and routes to chaos under the effect of a state-dependent jump in the resetting process. In this study, we focus further on the relation between chaotic behaviour and the state-dependent jump, approaching the subject by comparing spiking neuron model versions with and without the resetting process. We first adopt a continuous two-dimensional spiking neuron model in which the orbit in the spiking state does not exhibit divergent behaviour. We then insert the resetting process into the model. An evaluation using the Lyapunov exponent with a saltation matrix and a characteristic multiplier of the Poincar'e map reveals that two types of chaotic behaviour (i.e. bursting chaotic spikes and near-period-two chaotic spikes) are induced by the resetting process. In addition, we confirm that this chaotic bursting state is generated from the periodic spiking state because of the slow- and fast-scale dynamics that arise when jumping to the hyperpolarization and depolarization regions, respectively.

Should spikes on post-resection ECoG guide pediatric epilepsy surgery?

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Greiner, Hansel M; Horn, Paul S; Tenney, Jeffrey R; Arya, Ravindra; Jain, Sejal V; Holland, Katherine D; Leach, James L; Miles, Lili; Rose, Douglas F; Fujiwara, Hisako; Mangano, Francesco T

2016-05-01

There is wide variation in clinical practice regarding the role of electrocorticography immediately after resection (post-resection ECoG) for pediatric epilepsy surgery. Results can guide further resection of potentially epileptogenic tissue. We hypothesized that post-resection ECoG spiking represents a biomarker of the epileptogenic zone and predicts seizure outcome in children undergoing epilepsy surgery. We retrospectively identified 124 children with post-resection ECoG performed on the margins of resection. ECoG records were scored in a blinded fashion based on presence of frequent spiking. For patients identified as having additional resection based on clinical post-resection ECoG interpretation, these "second-look" ECoG results were re-reviewed for ongoing discharges or completeness of resection. Frequent spike populations were grouped using a standard scoring system into three ranges: 0.1-0.5Hz, 0.5-1Hz, >1Hz. Seizure outcomes were determined at minimum 12-month followup. Of 124 patients who met inclusion criteria, 60 (48%) had an identified spike population on post-resection ECoG. Thirty (50%) of these had further resection based on clinical interpretation. Overall, good outcome (ILAE 1) was seen in 56/124 (45%). Completeness of resection of spiking (absence of spiking on initial post-resection ECoG or resolution of spiking after further resection) showed a trend toward good outcome (OR 2.03, p=0.099). Patients with completeness of resection had good outcome in 41/80 (51%) of cases; patients with continued spikes had good outcome in 15/44 (35%) of cases. Post-resection ECoG identifies residual epileptogenic tissue in a significant number of children. Lower frequency or absence of discharges on initial recording showed a trend toward good outcome. Completeness of resection demonstrated on final ECoG recording did not show a significant difference in outcome. This suggests that post-resection discharges represent a prognostic marker rather than a remediable

Evoking prescribed spike times in stochastic neurons

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Doose, Jens; Lindner, Benjamin

2017-09-01

Single cell stimulation in vivo is a powerful tool to investigate the properties of single neurons and their functionality in neural networks. We present a method to determine a cell-specific stimulus that reliably evokes a prescribed spike train with high temporal precision of action potentials. We test the performance of this stimulus in simulations for two different stochastic neuron models. For a broad range of parameters and a neuron firing with intermediate firing rates (20-40 Hz) the reliability in evoking the prescribed spike train is close to its theoretical maximum that is mainly determined by the level of intrinsic noise.

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

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Oliynyk Andriy

2012-08-01

Full Text Available Abstract Background Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Results Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting, which is designed to optimize: (i fast and accurate detection, (ii offline sorting and (iii online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com using LabVIEW (National Instruments, USA. We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering.

Science.gov (United States)

Oliynyk, Andriy; Bonifazzi, Claudio; Montani, Fernando; Fadiga, Luciano

2012-08-08

Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike

The influence of single bursts vs. single spikes at excitatory dendrodendritic synapses

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Masurkar, Arjun V.; Chen, Wei R.

2015-01-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in-vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC–interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, vs. single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. PMID:22277089

Nonlinear evolution of single spike in Richtmyer-Meshkov instability

International Nuclear Information System (INIS)

Fukuda, Y.; Nishihara, K.; Wouchuk, J.G.

2000-01-01

Nonlinear evolution of single spike structure and vortex in the Richtmyer-Meshkov instability is investigated with the use of a two-dimensional hydrodynamic code. It is shown that singularity appears in the vorticity left by transmitted and reflected shocks at a corrugated interface. This singularity results in opposite sign of vorticity along the interface that causes double spiral structure of the spike. (authors)

Comparison of spike-sorting algorithms for future hardware implementation.

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Gibson, Sarah; Judy, Jack W; Markovic, Dejan

2008-01-01

Applications such as brain-machine interfaces require hardware spike sorting in order to (1) obtain single-unit activity and (2) perform data reduction for wireless transmission of data. Such systems must be low-power, low-area, high-accuracy, automatic, and able to operate in real time. Several detection and feature extraction algorithms for spike sorting are described briefly and evaluated in terms of accuracy versus computational complexity. The nonlinear energy operator method is chosen as the optimal spike detection algorithm, being most robust over noise and relatively simple. The discrete derivatives method [1] is chosen as the optimal feature extraction method, maintaining high accuracy across SNRs with a complexity orders of magnitude less than that of traditional methods such as PCA.

Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

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Yu, T; Sejnowski, T J; Cauwenberghs, G

2011-10-01

We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

Memristors Empower Spiking Neurons With Stochasticity

KAUST Repository

Al-Shedivat, Maruan; Naous, Rawan; Cauwenberghs, Gert; Salama, Khaled N.

2015-01-01

Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning

Development of on-off spiking in superior paraolivary nucleus neurons of the mouse

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Felix, Richard A.; Vonderschen, Katrin; Berrebi, Albert S.

2013-01-01

The superior paraolivary nucleus (SPON) is a prominent cell group in the auditory brain stem that has been increasingly implicated in representing temporal sound structure. Although SPON neurons selectively respond to acoustic signals important for sound periodicity, the underlying physiological specializations enabling these responses are poorly understood. We used in vitro and in vivo recordings to investigate how SPON neurons develop intrinsic cellular properties that make them well suited for encoding temporal sound features. In addition to their hallmark rebound spiking at the stimulus offset, SPON neurons were characterized by spiking patterns termed onset, adapting, and burst in response to depolarizing stimuli in vitro. Cells with burst spiking had some morphological differences compared with other SPON neurons and were localized to the dorsolateral region of the nucleus. Both membrane and spiking properties underwent strong developmental regulation, becoming more temporally precise with age for both onset and offset spiking. Single-unit recordings obtained in young mice demonstrated that SPON neurons respond with temporally precise onset spiking upon tone stimulation in vivo, in addition to the typical offset spiking. Taken together, the results of the present study demonstrate that SPON neurons develop sharp on-off spiking, which may confer sensitivity to sound amplitude modulations or abrupt sound transients. These findings are consistent with the proposed involvement of the SPON in the processing of temporal sound structure, relevant for encoding communication cues. PMID:23515791

Theory of thermal sputtering

International Nuclear Information System (INIS)

Kelly, R.

1977-01-01

An energetic ion which is incident on a solid target causes a momentary temperature increase in the impact region, i.e., a so-called thermal spike occurs. Such spikes are capable of causing (or supplementing) disordering, precipitation, crystallization, electronic excitation, stoichiometry change, desorption, and sputtering, it being the contribution to sputtering that is considered here. The approach used is compatible with modern damage-distribution theory. Thus the temperature profile left by the incident ion is taken as a three-dimensional Gaussian with parameters appropriate to power-law scattering, and is used as the initial condition for solving the heat-conduction equation. Let us write this solution as T = T(t, y), where t is time and y is a dimension parallel to the target surface. The vaporization flux from a solid surface is taken as pnsup(1/2)(2π 2 >kT)sup(-1/2), where p, the equilibrium pressure of a vapor species containing n atoms, can be written as p 0 exp(-L/T), p 0 and L are constants largely independent of temperature, and 2 > is the mean mass per atom of target. An equation for the thermal sputtering coefficient is given: after integration the final result takes the form: Ssub(thermal)=pnsup(1/2)[2π 2 >k(Tsub(infinity)+cΔT 0 )]sup(-1/2)πlambda 2 tsub(eff.)atoms/ion, where Tsub(infinity) is the macroscopic target temperature, cΔT 0 is the maximum temperature increase at x = y = 0, p is to be evaluated at T = Tsub(infinity) + cΔT 0 , lambda is the mean atomic spacing of the target, and tsub(eff.) is a quantity with units of time. (author)

Spikes and memory in (Nord Pool) electricity price spot prices

DEFF Research Database (Denmark)

Proietti, Tomasso; Haldrup, Niels; Knapik, Oskar

Electricity spot prices are subject to transitory sharp movements commonly referred to as spikes. The paper aims at assessing their effects on model based inferences and predictions, with reference to the Nord Pool power exchange. We identify a spike as a price value which deviates substantially...

Neural spike sorting using iterative ICA and a deflation-based approach.

Science.gov (United States)

Tiganj, Z; Mboup, M

2012-12-01

We propose a spike sorting method for multi-channel recordings. When applied in neural recordings, the performance of the independent component analysis (ICA) algorithm is known to be limited, since the number of recording sites is much lower than the number of neurons. The proposed method uses an iterative application of ICA and a deflation technique in two nested loops. In each iteration of the external loop, the spiking activity of one neuron is singled out and then deflated from the recordings. The internal loop implements a sequence of ICA and sorting for removing the noise and all the spikes that are not fired by the targeted neuron. Then a final step is appended to the two nested loops in order to separate simultaneously fired spikes. We solve this problem by taking all possible pairs of the sorted neurons and apply ICA only on the segments of the signal during which at least one of the neurons in a given pair was active. We validate the performance of the proposed method on simulated recordings, but also on a specific type of real recordings: simultaneous extracellular-intracellular. We quantify the sorting results on the extracellular recordings for the spikes that come from the neurons recorded intracellularly. The results suggest that the proposed solution significantly improves the performance of ICA in spike sorting.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

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Jan Hahne

2017-05-01

Full Text Available Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

Science.gov (United States)

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Superficial dorsal horn neurons with double spike activity in the rat.

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Rojas-Piloni, Gerardo; Dickenson, Anthony H; Condés-Lara, Miguel

2007-05-29

Superficial dorsal horn neurons promote the transfer of nociceptive information from the periphery to supraspinal structures. The membrane and discharge properties of spinal cord neurons can alter the reliability of peripheral signals. In this paper, we analyze the location and response properties of a particular class of dorsal horn neurons that exhibits double spike discharge with a very short interspike interval (2.01+/-0.11 ms). These neurons receive nociceptive C-fiber input and are located in laminae I-II. Double spikes are generated spontaneously or by depolarizing current injection (interval of 2.37+/-0.22). Cells presenting double spike (interval 2.28+/-0.11) increased the firing rate by electrical noxious stimulation, as well as, in the first minutes after carrageenan injection into their receptive field. Carrageenan is a polysaccharide soluble in water and it is used for producing an experimental model of semi-chronic pain. In the present study carrageenan also produces an increase in the interval between double spikes and then, reduced their occurrence after 5-10 min. The results suggest that double spikes are due to intrinsic membrane properties and that their frequency is related to C-fiber nociceptive activity. The present work shows evidence that double spikes in superficial spinal cord neurones are related to the nociceptive stimulation, and they are possibly part of an acute pain-control mechanism.

Activity-Dependent Plasticity of Spike Pauses in Cerebellar Purkinje Cells

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Giorgio Grasselli

2016-03-01

Full Text Available The plasticity of intrinsic excitability has been described in several types of neurons, but the significance of non-synaptic mechanisms in brain plasticity and learning remains elusive. Cerebellar Purkinje cells are inhibitory neurons that spontaneously fire action potentials at high frequencies and regulate activity in their target cells in the cerebellar nuclei by generating a characteristic spike burst-pause sequence upon synaptic activation. Using patch-clamp recordings from mouse Purkinje cells, we find that depolarization-triggered intrinsic plasticity enhances spike firing and shortens the duration of spike pauses. Pause plasticity is absent from mice lacking SK2-type potassium channels (SK2−/− mice and in occlusion experiments using the SK channel blocker apamin, while apamin wash-in mimics pause reduction. Our findings demonstrate that spike pauses can be regulated through an activity-dependent, exclusively non-synaptic, SK2 channel-dependent mechanism and suggest that pause plasticity—by altering the Purkinje cell output—may be crucial to cerebellar information storage and learning.

Higher Order Spike Synchrony in Prefrontal Cortex during visual memory

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Gordon ePipa

2011-06-01

Full Text Available Precise temporal synchrony of spike firing has been postulated as an important neuronal mechanism for signal integration and the induction of plasticity in neocortex. As prefrontal cortex plays an important role in organizing memory and executive functions, the convergence of multiple visual pathways onto PFC predicts that neurons should preferentially synchronize their spiking when stimulus information is processed. Furthermore, synchronous spike firing should intensify if memory processes require the induction of neuronal plasticity, even if this is only for short-term. Here we show with multiple simultaneously recorded units in ventral prefrontal cortex that neurons participate in 3 ms precise synchronous discharges distributed across multiple sites separated by at least 500 µm. The frequency of synchronous firing is modulated by behavioral performance and is specific for the memorized visual stimuli. In particular, during the memory period in which activity is not stimulus driven, larger groups of up to 7 sites exhibit performance dependent modulation of their spike synchronization.

Timing intervals using population synchrony and spike timing dependent plasticity

Directory of Open Access Journals (Sweden)

Wei Xu

2016-12-01

Full Text Available We present a computational model by which ensembles of regularly spiking neurons can encode different time intervals through synchronous firing. We show that a neuron responding to a large population of convergent inputs has the potential to learn to produce an appropriately-timed output via spike-time dependent plasticity. We explain why temporal variability of this population synchrony increases with increasing time intervals. We also show that the scalar property of timing and its violation at short intervals can be explained by the spike-wise accumulation of jitter in the inter-spike intervals of timing neurons. We explore how the challenge of encoding longer time intervals can be overcome and conclude that this may involve a switch to a different population of neurons with lower firing rate, with the added effect of producing an earlier bias in response. Experimental data on human timing performance show features in agreement with the model’s output.

Spike-adding in parabolic bursters: The role of folded-saddle canards

Science.gov (United States)

Desroches, Mathieu; Krupa, Martin; Rodrigues, Serafim

2016-09-01

The present work develops a new approach to studying parabolic bursting, and also proposes a novel four-dimensional canonical and polynomial-based parabolic burster. In addition to this new polynomial system, we also consider the conductance-based model of the Aplysia R15 neuron known as the Plant model, and a reduction of this prototypical biophysical parabolic burster to three variables, including one phase variable, namely the Baer-Rinzel-Carillo (BRC) phase model. Revisiting these models from the perspective of slow-fast dynamics reveals that the number of spikes per burst may vary upon parameter changes, however the spike-adding process occurs in an explosive fashion that involves special solutions called canards. This spike-adding canard explosion phenomenon is analysed by using tools from geometric singular perturbation theory in tandem with numerical bifurcation techniques. We find that the bifurcation structure persists across all considered systems, that is, spikes within the burst are incremented via the crossing of an excitability threshold given by a particular type of canard orbit, namely the true canard of a folded-saddle singularity. However there can be a difference in the spike-adding transitions in parameter space from one case to another, according to whether the process is continuous or discontinuous, which depends upon the geometry of the folded-saddle canard. Using these findings, we construct a new polynomial approximation of the Plant model, which retains all the key elements for parabolic bursting, including the spike-adding transitions mediated by folded-saddle canards. Finally, we briefly investigate the presence of spike-adding via canards in planar phase models of parabolic bursting, namely the theta model by Ermentrout and Kopell.

Fast computation with spikes in a recurrent neural network

International Nuclear Information System (INIS)

Jin, Dezhe Z.; Seung, H. Sebastian

2002-01-01

Neural networks with recurrent connections are sometimes regarded as too slow at computation to serve as models of the brain. Here we analytically study a counterexample, a network consisting of N integrate-and-fire neurons with self excitation, all-to-all inhibition, instantaneous synaptic coupling, and constant external driving inputs. When the inhibition and/or excitation are large enough, the network performs a winner-take-all computation for all possible external inputs and initial states of the network. The computation is done very quickly: As soon as the winner spikes once, the computation is completed since no other neurons will spike. For some initial states, the winner is the first neuron to spike, and the computation is done at the first spike of the network. In general, there are M potential winners, corresponding to the top M external inputs. When the external inputs are close in magnitude, M tends to be larger. If M>1, the selection of the actual winner is strongly influenced by the initial states. If a special relation between the excitation and inhibition is satisfied, the network always selects the neuron with the maximum external input as the winner

Computing with Spiking Neuron Networks

NARCIS (Netherlands)

H. Paugam-Moisy; S.M. Bohte (Sander); G. Rozenberg; T.H.W. Baeck (Thomas); J.N. Kok (Joost)

2012-01-01

htmlabstractAbstract Spiking Neuron Networks (SNNs) are often referred to as the 3rd gener- ation of neural networks. Highly inspired from natural computing in the brain and recent advances in neurosciences, they derive their strength and interest from an ac- curate modeling of synaptic interactions

Code-specific learning rules improve action selection by populations of spiking neurons.

Science.gov (United States)

Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

2014-08-01

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

Knowledge extraction from evolving spiking neural networks with rank order population coding.

Science.gov (United States)

Soltic, Snjezana; Kasabov, Nikola

2010-12-01

This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

Mapping cortical mesoscopic networks of single spiking cortical or sub-cortical neurons.

Science.gov (United States)

Xiao, Dongsheng; Vanni, Matthieu P; Mitelut, Catalin C; Chan, Allen W; LeDue, Jeffrey M; Xie, Yicheng; Chen, Andrew Cn; Swindale, Nicholas V; Murphy, Timothy H

2017-02-04

Understanding the basis of brain function requires knowledge of cortical operations over wide-spatial scales, but also within the context of single neurons. In vivo, wide-field GCaMP imaging and sub-cortical/cortical cellular electrophysiology were used in mice to investigate relationships between spontaneous single neuron spiking and mesoscopic cortical activity. We make use of a rich set of cortical activity motifs that are present in spontaneous activity in anesthetized and awake animals. A mesoscale spike-triggered averaging procedure allowed the identification of motifs that are preferentially linked to individual spiking neurons by employing genetically targeted indicators of neuronal activity. Thalamic neurons predicted and reported specific cycles of wide-scale cortical inhibition/excitation. In contrast, spike-triggered maps derived from single cortical neurons yielded spatio-temporal maps expected for regional cortical consensus function. This approach can define network relationships between any point source of neuronal spiking and mesoscale cortical maps.

A unified approach to linking experimental, statistical and computational analysis of spike train data.

Directory of Open Access Journals (Sweden)

Liang Meng

Full Text Available A fundamental issue in neuroscience is how to identify the multiple biophysical mechanisms through which neurons generate observed patterns of spiking activity. In previous work, we proposed a method for linking observed patterns of spiking activity to specific biophysical mechanisms based on a state space modeling framework and a sequential Monte Carlo, or particle filter, estimation algorithm. We have shown, in simulation, that this approach is able to identify a space of simple biophysical models that were consistent with observed spiking data (and included the model that generated the data, but have yet to demonstrate the application of the method to identify realistic currents from real spike train data. Here, we apply the particle filter to spiking data recorded from rat layer V cortical neurons, and correctly identify the dynamics of an slow, intrinsic current. The underlying intrinsic current is successfully identified in four distinct neurons, even though the cells exhibit two distinct classes of spiking activity: regular spiking and bursting. This approach--linking statistical, computational, and experimental neuroscience--provides an effective technique to constrain detailed biophysical models to specific mechanisms consistent with observed spike train data.

Relationship between focal penicillin spikes and cortical spindles in the cerveau isolé cat.

Science.gov (United States)

McLachlan, R S; Kaibara, M; Girvin, J P

1983-01-01

Using the unanesthetized, cerveau isolé preparation in the cat, the association between artificially induced penicillin (PCN) spikes and spontaneously occurring electrocorticographic (ECoG) spindles was investigated. Spikes were elicited by surface application of small pledgets of PCN. After the application of PCN, there was a decrease in spindle amplitude but no change in frequency, duration, or spindle wave frequency in the area of the focus. Examination of the times of occurrence of the spikes and spindles disclosed that in the majority of cases, within a few minutes of the initiation of the foci, there was very high simultaneity, usually 100% between the occurrences of these two events. Examination of the times of occurrence of the spikes within the ECoG spindles failed to disclose any compelling evidence which would favor either the hypothesis that spikes "trigger" spindles or the hypothesis that spindles predispose to focal spikes. Thus, whether spikes trigger spindles, or spikes simply occur in a nonspecific manner during the occurrence of the spindle, or whether it is a combination of both these explanations, must remain an open question on the basis of the data available.

Poisson-Like Spiking in Circuits with Probabilistic Synapses

Science.gov (United States)

Moreno-Bote, Rubén

2014-01-01

Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex. PMID:25032705

On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses.

Science.gov (United States)

Song, Tao; Xu, Jinbang; Pan, Linqiang

2015-12-01

Spiking neural P systems with rules on synapses are a new variant of spiking neural P systems. In the systems, the neuron contains only spikes, while the spiking/forgetting rules are moved on the synapses. It was obtained that such system with 30 neurons (using extended spiking rules) or with 39 neurons (using standard spiking rules) is Turing universal. In this work, this number is improved to 6. Specifically, we construct a Turing universal spiking neural P system with rules on synapses having 6 neurons, which can generate any set of Turing computable natural numbers. As well, it is obtained that spiking neural P system with rules on synapses having less than two neurons are not Turing universal: i) such systems having one neuron can characterize the family of finite sets of natural numbers; ii) the family of sets of numbers generated by the systems having two neurons is included in the family of semi-linear sets of natural numbers.

Which spike train distance is most suitable for distinguishing rate and temporal coding?

Science.gov (United States)

Satuvuori, Eero; Kreuz, Thomas

2018-04-01

It is commonly assumed in neuronal coding that repeated presentations of a stimulus to a coding neuron elicit similar responses. One common way to assess similarity are spike train distances. These can be divided into spike-resolved, such as the Victor-Purpura and the van Rossum distance, and time-resolved, e.g. the ISI-, the SPIKE- and the RI-SPIKE-distance. We use independent steady-rate Poisson processes as surrogates for spike trains with fixed rate and no timing information to address two basic questions: How does the sensitivity of the different spike train distances to temporal coding depend on the rates of the two processes and how do the distances deal with very low rates? Spike-resolved distances always contain rate information even for parameters indicating time coding. This is an issue for reasonably high rates but beneficial for very low rates. In contrast, the operational range for detecting time coding of time-resolved distances is superior at normal rates, but these measures produce artefacts at very low rates. The RI-SPIKE-distance is the only measure that is sensitive to timing information only. While our results on rate-dependent expectation values for the spike-resolved distances agree with Chicharro et al. (2011), we here go one step further and specifically investigate applicability for very low rates. The most appropriate measure depends on the rates of the data being analysed. Accordingly, we summarize our results in one table that allows an easy selection of the preferred measure for any kind of data. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Basalt FRP Spike Repairing of Wood Beams

Directory of Open Access Journals (Sweden)

Luca Righetti

2015-08-01

Full Text Available This article describes aspects within an experimental program aimed at improving the structural performance of cracked solid fir-wood beams repaired with Basalt Fiber Reinforced Polymer (BFRP spikes. Fir wood is characterized by its low density, low compression strength, and high level of defects, and it is likely to distort when dried and tends to fail under tension due to the presence of cracks, knots, or grain deviation. The proposed repair technique consists of the insertion of BFRP spikes into timber beams to restore the continuity of cracked sections. The experimental efforts deal with the evaluation of the bending strength and deformation properties of 24 timber beams. An artificially simulated cracking was produced by cutting the wood beams in half or notching. The obtained results for the repaired beams were compared with those of solid undamaged and damaged beams, and increases of beam capacity, bending strength and of modulus of elasticity, and analysis of failure modes was discussed. For notched beams, the application of the BFRP spikes was able to restore the original bending capacity of undamaged beams, while only a small part of the original capacity was recovered for beams that were cut in half.

Diallel analysis to study the genetic makeup of spike and yield ...

African Journals Online (AJOL)

African Journal of Biotechnology ... Five wheat genotypes were crossed in complete diallel fashion for gene ... by pursuing pedigree method while heterosis can be exploited for spike length, grain weight per spike and grain yield per plant.

The influence of single bursts versus single spikes at excitatory dendrodendritic synapses.

Science.gov (United States)

Masurkar, Arjun V; Chen, Wei R

2012-02-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC -interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, versus single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Coherent and intermittent ensemble oscillations emerge from networks of irregular spiking neurons.

Science.gov (United States)

Hoseini, Mahmood S; Wessel, Ralf

2016-01-01

Local field potential (LFP) recordings from spatially distant cortical circuits reveal episodes of coherent gamma oscillations that are intermittent, and of variable peak frequency and duration. Concurrently, single neuron spiking remains largely irregular and of low rate. The underlying potential mechanisms of this emergent network activity have long been debated. Here we reproduce such intermittent ensemble oscillations in a model network, consisting of excitatory and inhibitory model neurons with the characteristics of regular-spiking (RS) pyramidal neurons, and fast-spiking (FS) and low-threshold spiking (LTS) interneurons. We find that fluctuations in the external inputs trigger reciprocally connected and irregularly spiking RS and FS neurons in episodes of ensemble oscillations, which are terminated by the recruitment of the LTS population with concurrent accumulation of inhibitory conductance in both RS and FS neurons. The model qualitatively reproduces experimentally observed phase drift, oscillation episode duration distributions, variation in the peak frequency, and the concurrent irregular single-neuron spiking at low rate. Furthermore, consistent with previous experimental studies using optogenetic manipulation, periodic activation of FS, but not RS, model neurons causes enhancement of gamma oscillations. In addition, increasing the coupling between two model networks from low to high reveals a transition from independent intermittent oscillations to coherent intermittent oscillations. In conclusion, the model network suggests biologically plausible mechanisms for the generation of episodes of coherent intermittent ensemble oscillations with irregular spiking neurons in cortical circuits. Copyright © 2016 the American Physiological Society.

Delphine Letort, The Spike Lee Brand: A Study of Documentary Filmmaking

OpenAIRE

Lipson, David

2017-01-01

Spike Lee is known the world over for films like She’s Gotta Have It (1986), School Daze (1988), Do the Right Thing (1989), etc. This association with fiction films is so strong that one could mistakenly think that Delphine Letort’s book The Spike Lee Brand: A Study of Documentary Filmmaking would explore the connection between these fiction films and the documentary genre. However, the first pages of the book clearly indicate that it will focus on Spike Lee the documentary filmmaker. Making ...

Character recognition from trajectory by recurrent spiking neural networks.

Science.gov (United States)

Jiangrong Shen; Kang Lin; Yueming Wang; Gang Pan

2017-07-01

Spiking neural networks are biologically plausible and power-efficient on neuromorphic hardware, while recurrent neural networks have been proven to be efficient on time series data. However, how to use the recurrent property to improve the performance of spiking neural networks is still a problem. This paper proposes a recurrent spiking neural network for character recognition using trajectories. In the network, a new encoding method is designed, in which varying time ranges of input streams are used in different recurrent layers. This is able to improve the generalization ability of our model compared with general encoding methods. The experiments are conducted on four groups of the character data set from University of Edinburgh. The results show that our method can achieve a higher average recognition accuracy than existing methods.

Modulation of the spike activity of neocortex neurons during a conditioned reflex.

Science.gov (United States)

Storozhuk, V M; Sanzharovskii, A V; Sachenko, V V; Busel, B I

2000-01-01

Experiments were conducted on cats to study the effects of iontophoretic application of glutamate and a number of modulators on the spike activity of neurons in the sensorimotor cortex during a conditioned reflex. These studies showed that glutamate, as well as exerting a direct influence on neuron spike activity, also had a delayed facilitatory action lasting 10-20 min after iontophoresis was finished. Adrenomimetics were found to have a double modulatory effect on intracortical glutamate connections: inhibitory and facilitatory effects were mediated by beta1 and beta2 adrenoceptors respectively. Although dopamine, like glutamate, facilitated neuron spike activity during the period of application, the simultaneous facilitatory actions of glutamate and L-DOPA were accompanied by occlusion of spike activity, and simultaneous application of glutamate and haloperidol suppressed spike activity associated with the conditioned reflex response. Facilitation thus appears to show a significant level of dependence on metabotropic glutamate receptors which, like dopamine receptors, are linked to the intracellular medium via Gi proteins.

Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.

Directory of Open Access Journals (Sweden)

Naoki Hiratani

2015-04-01

Full Text Available The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory.

Platinum stable isotope ratio measurements by double-spike multiple collector ICPMS

DEFF Research Database (Denmark)

Creech, John; Baker, Joel; Handler, Monica

2013-01-01

We present a new technique for the precise determination of platinum (Pt) stable isotope ratios by multiple-collector inductively coupled plasma mass spectrometry (MC-ICPMS) using two different Pt double-spikes ( Pt-Pt and Pt-Pt). Results are expressed relative to the IRMM-010 Pt isotope standard......) can be obtained on Pt stable isotope ratios with either double-spike. Elemental doping tests reveal that double-spike corrected Pt stable isotope ratios are insensitive to the presence of relatively high (up to 10%) levels of matrix elements, although the Pt-Pt double-spike is affected by an isobaric...... = 7.308%) results in a redefined Pt atomic weight of 195.08395 ± 0.00068. Using our technique we have measured small, reproducible and statistically significant offsets in Pt stable isotope ratios between different Pt element standards and the IRMM-010 standard, which potentially indicates...

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

Science.gov (United States)

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na(+) and K(+) currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.

Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

Directory of Open Access Journals (Sweden)

Emre eNeftci

2014-01-01

Full Text Available Restricted Boltzmann Machines (RBMs and Deep Belief Networks have been demonstrated to perform efficiently in variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The reverberating activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP carries out the weight updates in an online, asynchronous fashion.We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

Event-driven contrastive divergence for spiking neuromorphic systems.

Science.gov (United States)

Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

2013-01-01

Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

Science.gov (United States)

Sengupta, Abhronil; Banerjee, Aparajita; Roy, Kaushik

2016-12-01

Over the past decade, spiking neural networks (SNNs) have emerged as one of the popular architectures to emulate the brain. In SNNs, information is temporally encoded and communication between neurons is accomplished by means of spikes. In such networks, spike-timing-dependent plasticity mechanisms require the online programing of synapses based on the temporal information of spikes transmitted by spiking neurons. In this work, we propose a spintronic synapse with decoupled spike-transmission and programing-current paths. The spintronic synapse consists of a ferromagnet-heavy-metal heterostructure where the programing current through the heavy metal generates spin-orbit torque to modulate the device conductance. Low programing energy and fast programing times demonstrate the efficacy of the proposed device as a nanoelectronic synapse. We perform a simulation study based on an experimentally benchmarked device-simulation framework to demonstrate the interfacing of such spintronic synapses with CMOS neurons and learning circuits operating in the transistor subthreshold region to form a network of spiking neurons that can be utilized for pattern-recognition problems.

A 16-Channel Nonparametric Spike Detection ASIC Based on EC-PC Decomposition.

Science.gov (United States)

Wu, Tong; Xu, Jian; Lian, Yong; Khalili, Azam; Rastegarnia, Amir; Guan, Cuntai; Yang, Zhi

2016-02-01

In extracellular neural recording experiments, detecting neural spikes is an important step for reliable information decoding. A successful implementation in integrated circuits can achieve substantial data volume reduction, potentially enabling a wireless operation and closed-loop system. In this paper, we report a 16-channel neural spike detection chip based on a customized spike detection method named as exponential component-polynomial component (EC-PC) algorithm. This algorithm features a reliable prediction of spikes by applying a probability threshold. The chip takes raw data as input and outputs three data streams simultaneously: field potentials, band-pass filtered neural data, and spiking probability maps. The algorithm parameters are on-chip configured automatically based on input data, which avoids manual parameter tuning. The chip has been tested with both in vivo experiments for functional verification and bench-top experiments for quantitative performance assessment. The system has a total power consumption of 1.36 mW and occupies an area of 6.71 mm (2) for 16 channels. When tested on synthesized datasets with spikes and noise segments extracted from in vivo preparations and scaled according to required precisions, the chip outperforms other detectors. A credit card sized prototype board is developed to provide power and data management through a USB port.

Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization.

Science.gov (United States)

Kulkarni, Shruti R; Rajendran, Bipin

2018-07-01

We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse biological spike rates below 300Hz achieves a classification accuracy of 98.17% on the MNIST test database with four times fewer parameters compared to the state-of-the-art. We present several insights from extensive numerical experiments regarding optimization of learning parameters and network configuration to improve its accuracy. We also describe a number of strategies to optimize the SNN for implementation in memory and energy constrained hardware, including approximations in computing the neuronal dynamics and reduced precision in storing the synaptic weights. Experiments reveal that even with 3-bit synaptic weights, the classification accuracy of the designed SNN does not degrade beyond 1% as compared to the floating-point baseline. Further, the proposed SNN, which is trained based on the precise spike timing information outperforms an equivalent non-spiking artificial neural network (ANN) trained using back propagation, especially at low bit precision. Thus, our study shows the potential for realizing efficient neuromorphic systems that use spike based information encoding and learning for real-world applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

Inference of neuronal network spike dynamics and topology from calcium imaging data

Directory of Open Access Journals (Sweden)

Henry eLütcke

2013-12-01

Full Text Available Two-photon calcium imaging enables functional analysis of neuronal circuits by inferring action potential (AP occurrence ('spike trains' from cellular fluorescence signals. It remains unclear how experimental parameters such as signal-to-noise ratio (SNR and acquisition rate affect spike inference and whether additional information about network structure can be extracted. Here we present a simulation framework for quantitatively assessing how well spike dynamics and network topology can be inferred from noisy calcium imaging data. For simulated AP-evoked calcium transients in neocortical pyramidal cells, we analyzed the quality of spike inference as a function of SNR and data acquisition rate using a recently introduced peeling algorithm. Given experimentally attainable values of SNR and acquisition rate, neural spike trains could be reconstructed accurately and with up to millisecond precision. We then applied statistical neuronal network models to explore how remaining uncertainties in spike inference affect estimates of network connectivity and topological features of network organization. We define the experimental conditions suitable for inferring whether the network has a scale-free structure and determine how well hub neurons can be identified. Our findings provide a benchmark for future calcium imaging studies that aim to reliably infer neuronal network properties.

Noise influence on spike activation in a Hindmarsh–Rose small-world neural network

International Nuclear Information System (INIS)

Zhe, Sun; Micheletto, Ruggero

2016-01-01

We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh−Rose (H−R) neural networks. (paper)

Noise influence on spike activation in a Hindmarsh-Rose small-world neural network

Science.gov (United States)

Zhe, Sun; Micheletto, Ruggero

2016-07-01

We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh-Rose (H-R) neural networks.

Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

Science.gov (United States)

Gardner, Brian; Sporea, Ioana; Grüning, André

2015-12-01

Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we examine how multilayered networks of spiking neurons can learn to encode for input patterns using a fully temporal coding scheme. To this end, we introduce a new supervised learning rule, MultilayerSpiker, that can train spiking networks containing hidden layer neurons to perform transformations between spatiotemporal input and output spike patterns. The performance of the proposed learning rule is demonstrated in terms of the number of pattern mappings it can learn, the complexity of network structures it can be used on, and its classification accuracy when using multispike-based encodings. In particular, the learning rule displays robustness against input noise and can generalize well on an example data set. Our approach contributes to both a systematic understanding of how computations might take place in the nervous system and a learning rule that displays strong technical capability.

Frequency of Rolandic Spikes in ADHD

Directory of Open Access Journals (Sweden)

J Gordon Millichap

2003-10-01

Full Text Available The frequency of rolandic spikes in nonepileptic children with attention deficit hyperactivity disorder (ADHD was compared with a control group of normal school-aged children in a study at the University of Frankfurt, Germany.

Origin of frontal lobe spikes in the early onset benign occipital lobe epilepsy (Panayiotopoulos syndrome).

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Leal, Alberto J R; Ferreira, José C; Dias, Ana I; Calado, Eulália

2008-09-01

Early onset benign occipital lobe epilepsy (Panayiotopoulos syndrome [PS]) is a common and easily recognizable epilepsy. Interictal EEG spike activity is often multifocal but most frequently localized in the occipital lobes. The origin and clinical significance of the extra-occipital spikes remain poorly understood. Three patients with the PS and interictal EEG spikes with frontal lobe topography were studied using high-resolution EEG. Independent component analysis (ICA) was used to decompose the spikes in components with distinct temporal dynamics. The components were mapped in the scalp with a spline-laplacian algorithm. The change in scalp potential topography from spike onset to peak, suggests the contribution of several intracranial generators, with different kinetics of activation and significant overlap. ICA was able to separate the major contributors to frontal spikes and consistently revealed an early activating group of components over the occipital areas in all the patients. The local origin of these early potentials was established by the spline-laplacian montage. Frontal spikes in PS are consistently associated with early and unilateral occipital lobe activation, suggesting a postero-anterior spike propagation. Frontal spikes in the PS represent a secondary activation triggered by occipital interictal discharges and do not represent an independent focus.

The coronavirus spike protein : mechanisms of membrane fusion and virion incorporation

NARCIS (Netherlands)

Bosch, B.J.

2004-01-01

The coronavirus spike protein is a membrane-anchored glycoprotein responsible for virus-cell attachment and membrane fusion, prerequisites for a successful virus infection. In this thesis, two aspects are described regarding the molecular biology of the coronavirus spike protein: its membrane fusion

Remifentanil-induced spike activity as a diagnostic tool in epilepsy surgery

DEFF Research Database (Denmark)

Gronlykke, L.; Knudsen, M.L.; Hogenhaven, H.

2008-01-01

. Electrocorticography (ECoG) recordings were performed on the intraventricular hippocampus and from the anterior inferior temporal and lateral neocortex before and after a 300 microg intravenous bolus of remifentanil. Spike activity was quantified as spike-count per minute. RESULTS: A significant increase (P

Tritium uptake in rainbow trout (Oncorhynchus mykiss): HTO and OBT-spiked feed exposures simultaneously

International Nuclear Information System (INIS)

Kim, S.B.; Shultz, C.; Stuart, M.; Festarini, A.

2015-01-01

There is currently considerable interest in organically bound tritium (OBT) formation in edible fish. The major questions revolve around whether or not tritium can accumulate in fish after being released into aquatic environments. Since OBT formation rates in large, edible fish are poorly understood, rainbow trout (Oncorhynchus mykiss) studies, where fish were simultaneously exposed to tritiated water (HTO) and OBT-spiked feed over 130 days, were conducted to evaluate tritium uptake. The measured HTO activity concentrations in fish tissue confirmed that HTO in fish tissue equilibrates quickly with HTO in tank water. The data obtained also confirmed that OBT uptake is faster when fish are ingesting OBT-spiked feed compared to when fish are living in tritiated water (and consuming non-OBT-spiked feed). The difference between the two exposure types is such that the groups exposed to tritiated water and OBT-spiked feed simultaneously were showing the same uptake rates as OBT-spiked feed only exposures. Contrary to what was expected, the rate of OBT uptake (from OBT-spiked feed) seemed to be higher in slow growing fish compared to fast growing fish. Another observation from these studies was that OBT activity concentrations in all organs (viscera) had a tendency to be higher than OBT activity concentrations measured in fish flesh. - Highlights: • Edible size of rainbow trout (Oncorhynchus mykiss) were simultaneously exposed to tritiated water (HTO) and OBT-spiked feed over 130 days. • OBT uptake is faster when fish are ingesting OBT-spiked feed compared to when fish are living in tritiated water (and consuming non-OBT-spiked feed). • The rate of OBT uptake (from OBT-spiked feed) seemed to be higher in slow growing fish compared to fast growing fish

EFFECTS OF DIFFERENT GROWING CONDITIONS ON THE MORPHOLOGICAL FEATURES OF THE SPIKE OF HEXAPLOID TRITICALE

Directory of Open Access Journals (Sweden)

K. U. Kurkiev

2016-01-01

Full Text Available Aim. The aim is to study the effect of different environmental conditions on the morphological traits of the spike of hexaploid triticale varieties.Methods. We analyzed 507 samples of triticale of various eco-geographical origins, in different years of study and at different seeding times. To investigate the influence of environmental conditions on the phenotypic expression of the studied traits we held a comparative analysis of the spike of two years and, in addition, of spring triticale during winter and spring crops. Analysis on the features was carried out on the main spikes. We studied the following morphological characteristics of the spike: length, number of spikelets and density.Results and discussion. The study of differences in individual variety samples showed that more than 60% triticale samples had significant differences in the length of the spike, depending on the weather conditions of the year – with the winter crops number of spikelets per spike was significantly higher than with the spring crops. A comparative analysis of the impact of the weather conditions of the year on triticale showed that significant differences in the density of the spike were observed in less than 30%.Conclusion. Study of the influence of conditions of the year and sowing dates on the main features of the spike of triticale showed that the density of the spike is the least affected by the external environment. The length of the spikes and the number of spikelets per spike differed significantly when growing in a various conditions.

A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.

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Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

Capturing spike variability in noisy Izhikevich neurons using point process generalized linear models

DEFF Research Database (Denmark)

Østergaard, Jacob; Kramer, Mark A.; Eden, Uri T.

2018-01-01

current. We then fit these spike train datawith a statistical model (a generalized linear model, GLM, with multiplicative influences of past spiking). For different levels of noise, we show how the GLM captures both the deterministic features of the Izhikevich neuron and the variability driven...... by the noise. We conclude that the GLM captures essential features of the simulated spike trains, but for near-deterministic spike trains, goodness-of-fit analyses reveal that the model does not fit very well in a statistical sense; the essential random part of the GLM is not captured....... are separately applied; understanding the relationships between these modeling approaches remains an area of active research. In this letter, we examine this relationship using simulation. To do so, we first generate spike train data from a well-known dynamical model, the Izhikevich neuron, with a noisy input...

Spike sorting using locality preserving projection with gap statistics and landmark-based spectral clustering.

Science.gov (United States)

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2014-12-30

Understanding neural functions requires knowledge from analysing electrophysiological data. The process of assigning spikes of a multichannel signal into clusters, called spike sorting, is one of the important problems in such analysis. There have been various automated spike sorting techniques with both advantages and disadvantages regarding accuracy and computational costs. Therefore, developing spike sorting methods that are highly accurate and computationally inexpensive is always a challenge in the biomedical engineering practice. An automatic unsupervised spike sorting method is proposed in this paper. The method uses features extracted by the locality preserving projection (LPP) algorithm. These features afterwards serve as inputs for the landmark-based spectral clustering (LSC) method. Gap statistics (GS) is employed to evaluate the number of clusters before the LSC can be performed. The proposed LPP-LSC is highly accurate and computationally inexpensive spike sorting approach. LPP spike features are very discriminative; thereby boost the performance of clustering methods. Furthermore, the LSC method exhibits its efficiency when integrated with the cluster evaluator GS. The proposed method's accuracy is approximately 13% superior to that of the benchmark combination between wavelet transformation and superparamagnetic clustering (WT-SPC). Additionally, LPP-LSC computing time is six times less than that of the WT-SPC. LPP-LSC obviously demonstrates a win-win spike sorting solution meeting both accuracy and computational cost criteria. LPP and LSC are linear algorithms that help reduce computational burden and thus their combination can be applied into real-time spike analysis. Copyright © 2014 Elsevier B.V. All rights reserved.