151 research outputs found
The causal role of left and right superior temporal gyri in speech perception in noise : A Transcranial Magnetic Stimulation Study
Successful perception of speech in everyday listening conditions requires effective listening strategies to overcome common acoustic distortions, such as background noise. Convergent evidence from neuroimaging and clinical studies identify activation within the temporal lobes as key to successful speech perception. However, current neurobiological models disagree on whether the left temporal lobe is sufficient for successful speech perception or whether bilateral processing is required. We addressed this issue using TMS to selectively disrupt processing in either the left or right superior temporal gyrus (STG) of healthy participants to test whether the left temporal lobe is sufficient or whether both left and right STG are essential. Participants repeated keywords from sentences presented in background noise in a speech reception threshold task while receiving online repetitive TMS separately to the left STG, right STG, or vertex or while receiving no TMS. Results show an equal drop in performance following application of TMS to either left or right STG during the task. A separate group of participants performed a visual discrimination threshold task to control for the confounding side effects of TMS. Results show no effect of TMS on the control task, supporting the notion that the results of Experiment 1 can be attributed to modulation of cortical functioning in STG rather than to side effects associated with online TMS. These results indicate that successful speech perception in everyday listening conditions requires both left and right STG and thus have ramifications for our understanding of the neural organization of spoken language processing
Photon-noise limited sensitivity in titanium nitride kinetic inductance detectors
We demonstrate photon-noise limited performance at sub-millimeter wavelengths
in feedhorn-coupled, microwave kinetic inductance detectors (MKIDs) made of a
TiN/Ti/TiN trilayer superconducting film, tuned to have a transition
temperature of 1.4~K. Micro-machining of the silicon-on-insulator wafer
backside creates a quarter-wavelength backshort optimized for efficient
coupling at 250~\micron. Using frequency read out and when viewing a variable
temperature blackbody source, we measure device noise consistent with photon
noise when the incident optical power is ~0.5~pW, corresponding to noise
equivalent powers ~3 W/. This
sensitivity makes these devices suitable for broadband photometric applications
at these wavelengths
Modulation of intra- and inter-hemispheric connectivity between primary and premotor cortex during speech perception
Primary motor (M1) areas for speech production activate during speech perception. It has been suggested that such activation may be dependent upon modulatory inputs from premotor cortex (PMv). If and how PMv differentially modulates M1 activity during perception of speech that is easy or challenging to understand, however, is unclear. This study aimed to test the link between PMv and M1 during challenging speech perception in two experiments. The first experiment investigated intra-hemispheric connectivity between left hemisphere PMv and left M1 lip area during comprehension of speech under clear and distorted listening conditions. Continuous theta burst stimulation (cTBS) was applied to left PMv in eighteen participants (aged 18–35). Post-cTBS, participants performed a sentence verification task on distorted (imprecisely articulated), and clear speech, whilst also undergoing stimulation of the lip representation in the left M1 to elicit motor evoked potentials (MEPs). In a second, separate experiment, we investigated the role of inter-hemispheric connectivity between right hemisphere PMv and left hemisphere M1 lip area. Dual-coil transcranial magnetic stimulation was applied to right PMv and left M1 lip in fifteen participants (aged 18–35). Results indicated that disruption of PMv during speech perception affects comprehension of distorted speech specifically. Furthermore, our data suggest that listening to distorted speech modulates the balance of intra- and inter-hemispheric interactions, with a larger sensorimotor network implicated during comprehension of distorted speech than when speech perception is optimal. The present results further understanding of PMv-M1 interactions during auditory-motor integration
The Grizzly, September 23, 2004
Get Down in the Lounge • USGA Amendments Cause Controversy • Wismer Rumors Exposed • Family Day is Just Around the Corner • You got SERVed! • Medulla: Soul for Your Brain • Lead the Way: UC Leadership Studies Program • Care to Dance? • Opinions: Should More Public Places Move Towards a Complete No-smoking Policy?; Tattoo or not to Tattoo? • My Summer Vacation Camping at Death Pond • The Kobe Bryant Sagahttps://digitalcommons.ursinus.edu/grizzlynews/1565/thumbnail.jp
The Grizzly, November 18, 2004
Student Reactions to Sigma Pi • President Strassburger\u27s Letter to the Collegeville Community • Poe on Poe Recommended for Theater Festival Nomination • Ursinus College Dance Company Concert Debuts this Week • Men and Women for Feminism: Review of From the Belly • Review: What did the Moon See? • Major Highlight: Business and Economics • Opinions: Welcome to Dubya\u27s Fun World; The Wismer Incident: Issues of Food and Money; What\u27s Real About Reality TV • Success Does not Equal Playoff Contention for the Men\u27s Rugby Team • Wrestling Team Puts Yet Another Beating on its Oppositionhttps://digitalcommons.ursinus.edu/grizzlynews/1572/thumbnail.jp
The Grizzly, October 7, 2004
Ursinus Students Help in the Fight Against Cancer • New Sports Bar Opening Near Campus • Sigma Who? Students try to Bring National Fraternity to Campus • Did you Watch the Presidential Debates? • Spotlight on Alpha Sigma Nu • Ursinus Political Campaign • From Ursinus to the Publishing House: An Interview with Dr. Schroeder • Opinions: Political Campaign Ads: Too Negative or the Price we Pay for Living in a Democracy?; Why not the Guillotine?; Curbside Pickup: A Classier Alternative to Fast Food; Wismer Worries; Passing Time with Haikus • Ursinus Cross Country 2004 Kicks-off • Field Hockey Comes out Strong in 2004 Seasonhttps://digitalcommons.ursinus.edu/grizzlynews/1567/thumbnail.jp
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
Load imbalance pervasively exists in distributed deep learning training
systems, either caused by the inherent imbalance in learned tasks or by the
system itself. Traditional synchronous Stochastic Gradient Descent (SGD)
achieves good accuracy for a wide variety of tasks, but relies on global
synchronization to accumulate the gradients at every training step. In this
paper, we propose eager-SGD, which relaxes the global synchronization for
decentralized accumulation. To implement eager-SGD, we propose to use two
partial collectives: solo and majority. With solo allreduce, the faster
processes contribute their gradients eagerly without waiting for the slower
processes, whereas with majority allreduce, at least half of the participants
must contribute gradients before continuing, all without using a central
parameter server. We theoretically prove the convergence of the algorithms and
describe the partial collectives in detail. Experimental results on
load-imbalanced environments (CIFAR-10, ImageNet, and UCF101 datasets) show
that eager-SGD achieves 1.27x speedup over the state-of-the-art synchronous
SGD, without losing accuracy.Comment: Published in Proceedings of the 25th ACM SIGPLAN Symposium on
Principles and Practice of Parallel Programming (PPoPP'20), pp. 45-61. 202
SparCML: High-Performance Sparse Communication for Machine Learning
Applying machine learning techniques to the quickly growing data in science
and industry requires highly-scalable algorithms. Large datasets are most
commonly processed "data parallel" distributed across many nodes. Each node's
contribution to the overall gradient is summed using a global allreduce. This
allreduce is the single communication and thus scalability bottleneck for most
machine learning workloads. We observe that frequently, many gradient values
are (close to) zero, leading to sparse of sparsifyable communications. To
exploit this insight, we analyze, design, and implement a set of
communication-efficient protocols for sparse input data, in conjunction with
efficient machine learning algorithms which can leverage these primitives. Our
communication protocols generalize standard collective operations, by allowing
processes to contribute arbitrary sparse input data vectors. Our generic
communication library, SparCML, extends MPI to support additional features,
such as non-blocking (asynchronous) operations and low-precision data
representations. As such, SparCML and its techniques will form the basis of
future highly-scalable machine learning frameworks
The Grizzly, November 11, 2004
USGA Passes Sigma Pi • Two Students Wear Questionable Costumes • Lonnie Graham is the Spark • Ursinus Proposes Possible Plans for Honor Code • The Benefits for a Professor on Sabbatical • Effects of Election Still Resonate in Ursinus Community • Do Ursinus Students Make use of Proximity to Philadelphia? • Opinions: Is Online Dating a Safe Alternative for Meeting People or a Risky Plea of Desperation?; All is not Lost for Liberals • Field Hockey Team Wins Centennial Conference Title • It\u27s All Over for Three Women Soccer Players • The Collegeville Cursehttps://digitalcommons.ursinus.edu/grizzlynews/1571/thumbnail.jp
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