Gesture analysis for physics education researchers

Systematic observations of student gestures can not only fill in gaps in students' verbal expressions, but can also offer valuable information about student ideas, including their source, their novelty to the speaker, and their construction in real time. This paper provides a review of the research in gesture analysis that is most relevant to physics education researchers and illustrates gesture analysis for the purpose of better understanding student thinking about physics.Comment: 14 page

The Large Aperture GRB Observatory

The Large Aperture GRB Observatory (LAGO) is aiming at the detection of the high energy (around 100 GeV) component of Gamma Ray Bursts, using the single particle technique in arrays of Water Cherenkov Detectors (WCD) in high mountain sites (Chacaltaya, Bolivia, 5300 m a.s.l., Pico Espejo, Venezuela, 4750 m a.s.l., Sierra Negra, Mexico, 4650 m a.s.l). WCD at high altitude offer a unique possibility of detecting low gamma fluxes in the 10 GeV - 1 TeV range. The status of the Observatory and data collected from 2007 to date will be presented.Comment: 4 pages, proceeding of 31st ICRC 200

Water Cherenkov Detectors response to a Gamma Ray Burst in the Large Aperture GRB Observatory

In order to characterise the behaviour of Water Cherenkov Detectors (WCD) under a sudden increase of 1 GeV - 1 TeV background photons from a Gamma Ray Burst (GRB), simulations were conducted and compared to data acquired by the WCD of the Large Aperture GRB Observatory (LAGO). The LAGO operates arrays of WCD at high altitude to detect GRBs using the single particle technique. The LAGO sensitivity to GRBs is derived from the reported simulations of the gamma initiated particle showers in the atmosphere and the WCD response to secondaries.Comment: 5 pages, proceeding of the 31st ICRC 200

Emergence of Microglia Bearing Senescence Markers During Paralysis Progression in a Rat Model of Inherited ALS

Age is a recognized risk factor for amyotrophic lateral sclerosis (ALS), a paralytic disease characterized by progressive loss of motor neurons and neuroinflammation. A hallmark of aging is the accumulation of senescent cells. Yet, the pathogenic role of cellular senescence in ALS remains poorly understood. In rats bearing the ALS-linked SOD1(G93A) mutation, microgliosis contribute to motor neuron death, and its pharmacologic downregulation results in increased survival. Here, we have explored whether gliosis and motor neuron loss were associated with cellular senescence in the spinal cord during paralysis progression. In the lumbar spinal cord of symptomatic SOD1(G93A) rats, numerous cells displayed nuclear p16(INK4a) as well as loss of nuclear Lamin B1 expression, two recognized senescence-associated markers. The number of p16(INK4a)-positive nuclei increased by four-fold while Lamin B1-negative nuclei increased by 1,2-fold, respect to non-transgenic or asymptomatic transgenic rats. p16(INK4a)-positive nuclei and Lamin B1-negative nuclei were typically localized in a subset of hypertrophic Iba1-positive microglia, occasionally exhibiting nuclear giant multinucleated cell aggregates and abnormal nuclear morphology. Next, we analyzed senescence markers in cell cultures of microglia obtained from the spinal cord of symptomatic SOD1(G93A) rats. Although microglia actively proliferated in cultures, a subset of them developed senescence markers after few days in vitro and subsequent passages. Senescent SOD1(G93A) microglia in culture conditions were characterized by large and flat morphology, senescence-associated beta-Galactosidase (SA-beta-Gal) activity as well as positive labeling for p16(INK4a), p53, matrix metalloproteinase-1 (MMP-1) and nitrotyrosine, suggesting a senescent-associated secretory phenotype (SASP). Remarkably, in the degenerating lumbar spinal cord other cell types, including ChAT-positive motor neurons and GFAP-expressing astrocytes, also displayed nuclear p16(INK4a) staining. These results suggest that cellular senescence is closely associated with inflammation and motor neuron loss occurring after paralysis onset in SOD1(G93A) rats. The emergence of senescent cells could mediate key pathogenic mechanisms in ALS

The Timing of the Cognitive Cycle

We propose that human cognition consists of cascading cycles of recurring brain events. Each cognitive cycle senses the current situation, interprets it with reference to ongoing goals, and then selects an internal or external action in response. While most aspects of the cognitive cycle are unconscious, each cycle also yields a momentary “ignition” of conscious broadcasting. Neuroscientists have independently proposed ideas similar to the cognitive cycle, the fundamental hypothesis of the LIDA model of cognition. High-level cognition, such as deliberation, planning, etc., is typically enabled by multiple cognitive cycles. In this paper we describe a timing model LIDA's cognitive cycle. Based on empirical and simulation data we propose that an initial phase of perception (stimulus recognition) occurs 80–100 ms from stimulus onset under optimal conditions. It is followed by a conscious episode (broadcast) 200–280 ms after stimulus onset, and an action selection phase 60–110 ms from the start of the conscious phase. One cognitive cycle would therefore take 260–390 ms. The LIDA timing model is consistent with brain evidence indicating a fundamental role for a theta-gamma wave, spreading forward from sensory cortices to rostral corticothalamic regions. This posteriofrontal theta-gamma wave may be experienced as a conscious perceptual event starting at 200–280 ms post stimulus. The action selection component of the cycle is proposed to involve frontal, striatal and cerebellar regions. Thus the cycle is inherently recurrent, as the anatomy of the thalamocortical system suggests. The LIDA model fits a large body of cognitive and neuroscientific evidence. Finally, we describe two LIDA-based software agents: the LIDA Reaction Time agent that simulates human performance in a simple reaction time task, and the LIDA Allport agent which models phenomenal simultaneity within timeframes comparable to human subjects. While there are many models of reaction time performance, these results fall naturally out of a biologically and computationally plausible cognitive architecture

Stochastic Resonance Modulates Neural Synchronization within and between Cortical Sources

Neural synchronization is a mechanism whereby functionally specific brain regions establish transient networks for perception, cognition, and action. Direct addition of weak noise (fast random fluctuations) to various neural systems enhances synchronization through the mechanism of stochastic resonance (SR). Moreover, SR also occurs in human perception, cognition, and action. Perception, cognition, and action are closely correlated with, and may depend upon, synchronized oscillations within specialized brain networks. We tested the hypothesis that SR-mediated neural synchronization occurs within and between functionally relevant brain areas and thus could be responsible for behavioral SR. We measured the 40-Hz transient response of the human auditory cortex to brief pure tones. This response arises when the ongoing, random-phase, 40-Hz activity of a group of tuned neurons in the auditory cortex becomes synchronized in response to the onset of an above-threshold sound at its “preferred” frequency. We presented a stream of near-threshold standard sounds in various levels of added broadband noise and measured subjects' 40-Hz response to the standards in a deviant-detection paradigm using high-density EEG. We used independent component analysis and dipole fitting to locate neural sources of the 40-Hz response in bilateral auditory cortex, left posterior cingulate cortex and left superior frontal gyrus. We found that added noise enhanced the 40-Hz response in all these areas. Moreover, added noise also increased the synchronization between these regions in alpha and gamma frequency bands both during and after the 40-Hz response. Our results demonstrate neural SR in several functionally specific brain regions, including areas not traditionally thought to contribute to the auditory 40-Hz transient response. In addition, we demonstrated SR in the synchronization between these brain regions. Thus, both intra- and inter-regional synchronization of neural activity are facilitated by the addition of moderate amounts of random noise. Because the noise levels in the brain fluctuate with arousal system activity, particularly across sleep-wake cycles, optimal neural noise levels, and thus SR, could be involved in optimizing the formation of task-relevant brain networks at several scales under normal conditions

Independent EEG Sources Are Dipolar

Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition ‘dipolarity’ defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison)

Good vibrations, bad vibrations: Oscillatory brain activity in the attentional blink

The attentional blink (AB) is a deficit in reporting the second (T2) of two targets (T1, T2) when presented in close temporal succession and within a stream of distractor stimuli. The AB has received a great deal of attention in the past two decades because it allows to study the mechanisms that influence the rate and depth of information processing in various setups and therefore provides an elegant way to study correlates of conscious perception in supra-threshold stimuli. Recently evidence has accumulated suggesting that oscillatory signals play a significant role in temporally coordinating information between brain areas. This review focuses on studies looking into oscillatory brain activity in the AB. The results of these studies indicate that the AB is related to modulations in oscillatory brain activity in the theta, alpha, beta, and gamma frequency bands. These modulations are sometimes restricted to a circumscribed brain area but more frequently include several brain regions. They occur before targets are presented as well as after the presentation of the targets. We will argue that the complexity of the findings supports the idea that the AB is not the result of a processing impairment in one particular process or brain area, but the consequence of a dynamic interplay between several processes and/or parts of a neural network