Speech Perception under the Tent: A Domain-general Predictive Role for the Cerebellum

The role of the cerebellum in speech perception remains a mystery. Given its uniform architecture, we tested the hypothesis that it implements a domain-general predictive mechanism whose role in speech is determined by connectivity. We collated all neuroimaging studies reporting cerebellar activity in the Neurosynth database (n = 8206). From this set, we found all studies involving passive speech and sound perception (n = 72, 64% speech, 12.5% sounds, 12.5% music, and 11% tones) and speech production and articulation (n = 175). Standard and coactivation neuroimaging meta-analyses were used to compare cerebellar and associated cortical activations between passive perception and production. We found distinct regions of perception- and production-related activity in the cerebellum and regions of perception–production overlap. Each of these regions had distinct patterns of cortico-cerebellar connectivity. To test for domain-generality versus specificity, we identified all psychological and task-related terms in the Neurosynth database that predicted activity in cerebellar regions associated with passive perception and production. Regions in the cerebellum activated by speech perception were associated with domain-general terms related to prediction. One hallmark of predictive processing is metabolic savings (i.e., decreases in neural activity when events are predicted). To test the hypothesis that the cerebellum plays a predictive role in speech perception, we examined cortical activation between studies reporting cerebellar activation and those without cerebellar activation during speech perception. When the cerebellum was active during speech perception, there was far less cortical activation than when it was inactive. The results suggest that the cerebellum implements a domain-general mechanism related to prediction during speech perception

The home-forwarding mechanism to reduce the cache coherence overhead in next-generation CMPs

On the road to computer systems able to support the requirements of exascale applications, Chip Multi-Processors (CMPs) are equipped with an ever increasing number of cores interconnected through fast on-chip networks. To exploit such new architectures, the parallel software must be able to scale almost linearly with the number of cores available. To this end, the overhead introduced by the run-time system of parallel programming frameworks and by the architecture itself must be small enough in order to enable high scalability also for very fine-grained parallel programs. An approach to reduce this overhead is to use non-conventional architectural mechanisms revealing useful when certain concurrency patterns in the running application are statically or dynamically recognized. Following this idea, this paper proposes a run-time support able to reduce the effective latency of inter-thread cooperation primitives by lowering the contention on individual caches. To achieve this goal, the new home-forwarding hardware mechanism is proposed and used by our runtime in order to reduce the amount of cache-to-cache interactions generated by the cache coherence protocol. Our ideas have been emulated on the Tilera TILEPro64 CMP, showing a significant speedup improvement in some first benchmarks

The Role of Sensory Feedback in Developmental Stuttering: A Review

Developmental stuttering is a neurodevelopmental disorder that severely affects speech fluency. Multiple lines of evidence point to a role of sensory feedback in the disorder; this has led to a number of theories proposing different disruptions to the use of sensory feedback during speech motor control in people who stutter. The purpose of this review was to bring together evidence from studies using altered auditory feedback paradigms with people who stutter, in order to evaluate the predictions of these different theories. This review highlights converging evidence for particular patterns of differences in the responses of people who stutter to feedback perturbations. The implications for hypotheses on the nature of the disruption to sensorimotor control of speech in the disorder are discussed, with reference to neurocomputational models of speech control (predominantly, the DIVA model; Guenther et al., 2006; Tourville et al., 2008). While some consistent patterns are emerging from this evidence, it is clear that more work in this area is needed with developmental samples in particular, in order to tease apart differences related to symptom onset from those related to compensatory strategies that develop with experience of stuttering

Structured Parallel Programming and Cache Coherence in Multicore Architectures

It is clear that multicore processors have become the building blocks of today’s high-performance computing platforms. The advent of massively parallel single-chip microprocessors further emphasizes the gap that exists between parallel architectures and parallel programming maturity. Our research group, starting from the experiences on distributed and shared memory multiprocessor, was one of the first to propose a Structured Parallel Programming approach to bridge this gap. In this scenario, one of the biggest problems is that an application’s performance is often affected by the sharing pattern of data and its impact on Cache Coherence. Currently multicore platforms rely on hardware or automatic cache coherence techniques that allow programmers to develop programs without taking into account the problem. It is well known that standard coherency protocols are inefficient for certain data communication patterns and these inefficiencies will be amplified by the increased core number and the complex memory hierarchies. Following a structured parallelism approach, our methodology to attack these problems is based on two interrelated issues: structured parallelism paradigms and cost models (or performance models). Evaluating the performance of a program, although widely studied, is still an open problem in the research community and, notably, specific cost models to de- scribe multicores are missing. For this reason in this thesis, we define an abstract model for cache coherent architectures, which is able to capture the essential elements and the qualitative behaviors of multicore-based systems. Furthermore, we show how this abstract model combined with well known performance modelling techniques, such as analytical modelling (e.g., queueing models and stochastic process algebras) or simulations, provide an application- and architecture-dependent cost model to predict structured parallel applications performances. Starting out from the behavior and performance predictability of structured parallelism schemes, in this thesis we address the issue of cache coherence in multicore architectures, following an algorithm-dependent approach, a particular kind of software cache coherence solution characterized by explicit cache management strategies, which are specific of the algorithm to be executed. Notably, we ensure parallel correctness by exploiting architecture-specific mechanisms and by defining proper data structures in order to “emulate” cache coherence solutions in an efficient way for each computation. Algorithm-dependent cache coherence can be efficiently implemented at the support level of structured parallelism paradigms, with absolute transparency with respect to the application programmer. Moreover, by using the cost model, in this thesis we study and compare different algorithm-dependent implementations, such as those based on automatic cache coherence with respect to an original, non-automatic and lock-free solution based on interprocessor communications. Notably, with this latter implementation, in some cases, we are able to reduce the number of memory accesses, cache transfers and synchronizations and increasing computation parallelism with respect to the use of automatic cache coherence. Current architectures do not usually allow disabling automatic cache coherence. However, the emergence of many-core architectures somewhat changed the scenario, so that some architectures, such as the Tilera TilePro64, allow to control and disable the automatic cache coherence facilities. For this reason, in this thesis we finally apply our methodology to TilePro64 platform in order provide a further validation of the results obtained by our cost model

Modello dei costi delle tecniche di cache coherence nelle architetture multiprocessor

In questa tesi viene affrontato il problema della Cache Coherence nelle architetture multiprocessor. Dopo aver introdotto le principali tecniche messe a disposizione dal livello hardware-firmware di questi sistemi e i principali protocolli di cache coherence sviluppati per la risoluzione di questo problema, vengono descritte le due principali strategie di implementazione. Da una parte abbiamo la soluzione snoopy-based che fa uso di un bus come punto di centralizzazione a livello firmware, dall’altra la soluzione adottata nei sistemi a più alto grado di parallelismo basata sul concetto di directory. Una soluzione alternativa è l’approccio algorithm-dependent che permette di affrontare la risoluzione del problema della cache coherence nella progettazione del supporto della mutua esclusione. Nella tesi è stato sviluppato un modello dei costi che usa come punto di partenza la valutazione delle prestazioni delle architetture multiprocessor basata sulla teoria delle code. Il modello presentato permette di valutare l’impatto che questi due approcci hanno sulle prestazioni dei programmi paralleli, mettendo in evidenza come l’approccio algorithm-dependent riesca a minimizzare il numero di trasferimenti di blocchi di cache e di comunicazioni interprocessor rispetto alle soluzioni automatiche

Cerebellar tDCS Dissociates the Timing of Perceptual Decisions from Perceptual Change in Speech

Neuroimaging studies suggest that the cerebellum might play a role in both speech perception and speech perceptual learning. However, it remains unclear what this role is: does the cerebellum directly contribute to the perceptual decision? Or does it contribute to the timing of perceptual decisions? To test this, we applied transcranial direct current stimulation (tDCS) to the right cerebellum during a speech perception task. Participants experienced a series of speech perceptual tests designed to measure and then manipulate their perception of a phonetic contrast. One group received cerebellar tDCS during speech perceptual learning and a different group received "sham" tDCS during the same task. Both groups showed similar learning-related changes in speech perception that transferred to a different phonetic contrast. For both trained and untrained speech perceptual decisions, cerebellar tDCS significantly increased the time it took participants to indicate their decisions with a keyboard press. The results suggest that cerebellar tDCS disrupted the timing of perceptual decisions, while leaving the eventual decision unaltered. In support of this conclusion, we use the drift diffusion model to decompose the data into processes that determine the outcome of perceptual decision-making and those that do not. The modeling suggests that cerebellar tDCS disrupted processes unrelated to decision-making. Taken together, the empirical data and modeling demonstrate that right cerebellar tDCS dissociates the timing of perceptual decisions from perceptual change. The results provide initial evidence in healthy humans that the cerebellum critically contributes to speech timing in the perceptual domain

Reorganization of the Neurobiology of Language After Sentence Overlearning

It is assumed that there are a static set of “language regions” in the brain. Yet, language comprehension engages regions well beyond these, and patients regularly produce familiar “formulaic” expressions when language regions are severely damaged. These suggest that the neurobiology of language is not fixed but varies with experiences, like the extent of word sequence learning. We hypothesized that perceiving overlearned sentences is supported by speech production and not putative language regions. Participants underwent 2 sessions of behavioral testing and functional magnetic resonance imaging (fMRI). During the intervening 15 days, they repeated 2 sentences 30 times each, twice a day. In both fMRI sessions, they “passively” listened to those sentences, novel sentences, and produced sentences. Behaviorally, evidence for overlearning included a 2.1-s decrease in reaction times to predict the final word in overlearned sentences. This corresponded to the recruitment of sensorimotor regions involved in sentence production, inactivation of temporal and inferior frontal regions involved in novel sentence listening, and a 45% change in global network organization. Thus, there was a profound whole-brain reorganization following sentence overlearning, out of “language” and into sensorimotor regions. The latter are generally preserved in aphasia and Alzheimer’s disease, perhaps explaining residual abilities with formulaic expressions in both

How is precision regulated in maintaining trunk posture?

Precision of limb control is associated with increased joint stiffness caused by antagonistic co-activation. The aim of this study was to examine whether this strategy also applies to precision of trunk postural control. To this end, thirteen subjects performed static postural tasks, aiming at a target object with a cursor that responded to 2D trunk angles. By manipulating target dimensions, different levels of precision were imposed in the frontal and sagittal planes. Trunk angle and electromyography (EMG) of abdominal and back muscles were recorded. Repeated measures ANOVAs revealed significant effects of target dimensions on kinematic variability in both movement planes. Specifically, standard deviation (SD) of trunk angle decreased significantly when target size in the same direction decreased, regardless of the precision demands in the other direction. Thus, precision control of trunk posture was directionally specific. However, no consistent effect of precision demands was found on trunk muscle activity, when averaged over time series. Therefore, it was concluded that stiffness regulation by antagonistic co-activation was not used to meet increased precision demands in trunk postural control. Instead, results from additional analyses suggest that precision of trunk angle was controlled in a feedback mode

Compensation for Changing Motor Uncertainty

When movement outcome differs consistently from the intended movement, errors are used to correct subsequent movements (e.g., adaptation to displacing prisms or force fields) by updating an internal model of motor and/or sensory systems. Here, we examine changes to an internal model of the motor system under changes in the variance structure of movement errors lacking an overall bias. We introduced a horizontal visuomotor perturbation to change the statistical distribution of movement errors anisotropically, while monetary gains/losses were awarded based on movement outcomes. We derive predictions for simulated movement planners, each differing in its internal model of the motor system. We find that humans optimally respond to the overall change in error magnitude, but ignore the anisotropy of the error distribution. Through comparison with simulated movement planners, we found that aimpoints corresponded quantitatively to an ideal movement planner that updates a strictly isotropic (circular) internal model of the error distribution. Aimpoints were planned in a manner that ignored the direction-dependence of error magnitudes, despite the continuous availability of unambiguous information regarding the anisotropic distribution of actual motor errors