A method for delivering spatio-temporally focused energy to a dynamically adjustable target along a waveguiding structure

It is possible to exploit the frequency-dependent velocity dispersion inherent to waveguiding structures to deliver spatio-temporally focused energy to a spatial target anywhere along the longitudinal extent of a waveguide. Such focusing of energy may have application to technologies as varied as nerve stimulation or chemical etching. A waveguide signal that effects this focused energy is conceptualized and derived. The spatial location of the target acted upon by the waveguide signal is demonstrated to be dynamically adjustable with a linear filtering step. Optimal parameters for waveguide signal generation are derived in the general case, allowing for application to a cross section of homogeneous waveguides. Performance is also considered in non-ideal, absorptive media. Numerical simulations are presented that indicate agreement with analytic results, and an evaluation of possible reduction to practice is presented

Comparative Analysis of Impact Attenuation Properties from Soccer Headgear

Athletes suffering from long-term neurocognitive deficiency due to subconcussive impacts is a major concern for football and soccer players today. Football players wear helmets that can help reduce injury risks like skull fractures, and these helmets must meet standard criteria that determinines how well a functional helmet should reduce accelerations of the player’s head. Currently no standard exists for testing soccer headgear despite studies demonstrating soccer players experience similar magnitudes of impacts. In this study, a modal impact hammer was used in conjunction with a Hybrid III 50th percentile test dummy head to simulate impacts experienced by soccer players to quantify the effectiveness of headgear in attenuating head acceleration due to direct impacts. The study found one device to be functional, and able to reduce the translational acceleration for an average hit experienced by a soccer player by 20%. Devices need to be developed and common testing standards need to be established to allow for a more widespread implementation of similar devices to protect players from short and long-term injuries due to impacts

Effects of dietary protein and fiber at breakfast on appetite, ad libitum energy intake at lunch, and neural responses to visual food stimuli in overweight adults

Increasing either protein or fiber at mealtimes has relatively modest effects on ingestive behavior. Whether protein and fiber have additive or interactive effects on ingestive behavior is not known. Fifteen overweight adults (5 female, 10 male; BMI: 27.1 ± 0.2 kg/m²; aged 26 ± 1 year) consumed four breakfast meals in a randomized crossover manner (normal protein (12 g) + normal fiber (2 g), normal protein (12 g) + high fiber (8 g), high protein (25 g) + normal fiber (2 g), high protein (25 g) + high fiber (8 g)). The amount of protein and fiber consumed at breakfast did not influence postprandial appetite or ad libitum energy intake at lunch. In the fasting-state, visual food stimuli elicited significant responses in the bilateral insula and amygdala and left orbitofrontal cortex. Contrary to our hypotheses, postprandial right insula responses were lower after consuming normal protein vs. high protein breakfasts. Postprandial responses in other a priori brain regions were not significantly influenced by protein or fiber intake at breakfast. In conclusion, these data do not support increasing dietary protein and fiber at breakfast as effective strategies for modulating neural reward processing and acute ingestive behavior in overweight adults.R01 MH102224 - NIMH NIH HHS; UL1 TR001108 - NCATS NIH HHS; UL1TR001108 - NCATS NIH HH

The Compositional Nature of Verb and Argument Representations in the Human Brain

How does the human brain represent simple compositions of objects, actors,and actions? We had subjects view action sequence videos during neuroimaging (fMRI) sessions and identified lexical descriptions of those videos by decoding (SVM) the brain representations based only on their fMRI activation patterns. As a precursor to this result, we had demonstrated that we could reliably and with high probability decode action labels corresponding to one of six action videos (dig, walk, etc.), again while subjects viewed the action sequence during scanning (fMRI). This result was replicated at two different brain imaging sites with common protocols but different subjects, showing common brain areas, including areas known for episodic memory (PHG, MTL, high level visual pathways, etc.,i.e. the 'what' and 'where' systems, and TPJ, i.e. 'theory of mind'). Given these results, we were also able to successfully show a key aspect of language compositionality based on simultaneous decoding of object class and actor identity. Finally, combining these novel steps in 'brain reading' allowed us to accurately estimate brain representations supporting compositional decoding of a complex event composed of an actor, a verb, a direction, and an object.Comment: 11 pages, 6 figure

Brain structure can mediate or moderate the relationship of behavior to brain function and transcriptome. A preliminary study

Abnormalities in motor-control behavior, which have been with concussion and head acceleration events (HAE), can be quantified using virtual reality (VR) technologies. Motor-control behavior has been consistently mapped to the brain's somatomotor network (SM) using both structural (sMRI) and functional MRI (fMRI). However, no studies habe integrated HAE, motor-control behavior, sMRI and fMRI measures. Here, brain networks important for motor-control were hypothesized to show changes in tractography-based diffusion weighted imaging [difference in fractional anisotropy (dFA)] and resting-state fMRI (rs-fMRI) measures in collegiate American football players across the season, and that these measures would relate to VR-based motor-control. We firther tested if nine inflammation-related miRNAs were associated with behavior-structure-function variables. Using permutation-based mediation and moderation methods, we found that across-season dFA from the SM structural connectome (SM-dFA) mediated the relationship between across-season VR-based Sensory-motor Reactivity (dSR) and rs-fMRI SM fingerprint similarity (p = 0.007 and Teff = 47%). The interaction between dSR and SM-dFA also predicted (pF = 0.036, pbeta3 = 0.058) across-season levels of dmiRNA-30d through permutation-based moderation analysis. These results suggest (1) that motor-control is in a feedback relationship with brain structure and function, (2) behavior-structure-function can be connected to HAE, and (3) behavior-structure might predict molecular biology measures.Comment: 62 pages, 4 figures, 2 table

Information theoretic evaluation of a noiseband-based cochlear implant simulator

Noise-band vocoders are often used to simulate the signal processing algorithms used in cochlear implants (CIs), producing acoustic stimuli that may be presented to normal hearing (NH) subjects. Such evaluations may obviate the heterogeneity of CI user populations, achieving greater experimental control than when testing on CI subjects. However, it remains an open question whether advancements in algorithms developed on NH subjects using a simulator will necessarily improve performance in CI users. This study assessed the similarity in vowel identification of CI subjects and NH subjects using an 8-channel noise-band vocoder simulator configured to match input and output frequencies or to mimic output after a basalward shift of input frequencies. Under each stimulus condition, NH subjects performed the task both with and without feedback/training. Similarity of NH subjects to CI users was evaluated using correct identification rates and information theoretic approaches. Feedback/training produced higher rates of correct identification, as expected, but also resulted in error patterns that were closer to those of the CI users. Further evaluation remains necessary to determine how patterns of confusion at the token level are affected by the various parameters in CI simulators, providing insight into how a true CI simulation may be developed to facilitate more rapid prototyping and testing of novel CI signal processing and electrical stimulation strategies

Accumulation of high magnitude acceleration events predicts cerebrovascular reactivity changes in female high school soccer athletes

Mitigating the effects of repetitive exposure to head trauma has become a major concern for the general population, given the growing body of evidence that even asymptomatic exposure to head accelerations is linked with increased risk for negative life outcomes and that risk increases as exposure is prolonged over many years. Among women's sports, soccer currently exhibits the highest growth in participation and reports the largest number of mild traumatic brain injuries annually, making female soccer athletes a relevant population in assessing the effects of repetitive exposure to head trauma. Cerebrovascular biomarkers may be useful in assessing the effects of repetitive head trauma, as these are thought to contribute directly to neurocognitive symptoms associated with mild traumatic brain injury. Here we use fMRI paired with a hypercapnic breath hold task along with monitoring of head acceleration events, to assess the relationship between cerebrovascular brain changes and exposure to repetitive head trauma over a season of play in female high school soccer athletes. We identified longitudinal changes in cerebrovascular reactivity that were significantly associated with prolonged accumulation to high magnitude (> 75th percentile) head acceleration events. Findings argue for active monitoring of athletes during periods of exposure to head acceleration events, illustrate the importance of collecting baseline (i.e., pre-exposure) measurements, and suggest modeling as a means of guiding policy to mitigate the effects of repetitive head trauma

Sub-concussive Hit Characteristics Predict Deviant Brain Metabolism in Football Athletes

Magnetic resonance spectroscopy and helmet telemetry were used to monitor the neural metabolic response to repetitive head collisions in 25 high school American football athletes. Specific hit characteristics were determined highly predictive of metabolic alterations, suggesting that sub-concussive blows can produce biochemical changes and potentially lead to neurological problems

The Compositional Nature of Event Representations in the Human Brain

How does the human brain represent simple compositions of constituents: actors, verbs, objects, directions, and locations? Subjects viewed videos during neuroimaging (fMRI) sessions from which sentential descriptions of those videos were identified by decoding the brain representations based only on their fMRI activation patterns. Constituents (e.g., fold and shirt) were independently decoded from a single presentation. Independent constituent classification was then compared to joint classification of aggregate concepts (e.g., fold-shirt); results were similar as measured by accuracy and correlation. The brain regions used for independent constituent classification are largely disjoint and largely cover those used for joint classification. This allows recovery of sentential descriptions of stimulus videos by composing the results of the independent constituent classifiers. Furthermore, classifiers trained on the words one set of subjects think of when watching a video can recognise sentences a different subject thinks of when watching a different video

Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions

We had human subjects perform a one-out-of-six class action recognition task from video stimuli while undergoing functional magnetic resonance imaging (fMRI). Support-vector machines (SVMs) were trained on the recovered brain scans to classify actions observed during imaging, yielding average classification accuracy of 69.73% when tested on scans from the same subject and of 34.80% when tested on scans from different subjects. An apples-to-apples comparison was performed with all publicly available software that implements state-of-the-art action recognition on the same video corpus with the same cross-validation regimen and same partitioning into training and test sets, yielding classification accuracies between 31.25% and 52.34%. This indicates that one can read people’s minds better than state-of-the-art computer-vision methods can perform action recognition.This work was supported, in part, by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 1231216. AB, DPB, NS, and JMS were supported, in part, by Army Research Laboratory (ARL) Cooperative Agreement W911NF-10-2-0060, AB, in part, by the Center forBrains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216, WC, CX, and JJC, in part, by ARL Cooperative Agreement W911NF-10-2-0062 and NSF CAREER grant IIS-0845282, CDF, in part, by NSF grant CNS-0855157, CH and SJH, in part, by the McDonnell Foundation, and BAP, in part, by Science Foundation Ireland grant 09/IN.1/I2637