The Group Creativity Exercise Getting MBAs to Work and Think Effectively in Groups

This experiential exercise is designed to engage participants in a process of group creativity that helps students lead or be a part of a creative team. The challenging and tangible nature of building a room­height tower provides a heightened experience that elicits many issues and strong emotions. The exercise provides a robust platform from which the instructor can choose which of many group creativity subtopics to emphasize. In addition to exercise instructions, guidance is given on how learning goals related to creativity techniques, group development, interpersonal dynamics, and leadership—can be addressed in a debriefing discussion. Both “pre­taught” and “retrospective” teaching approaches are discussed, although a retrospective approach in which the instructor makes connections with theory during debriefing discussions is recommended. The experience of learning by doing should yield more realistic and memorable understanding of group creativity than could be accomplished with readings and/or lecture alone

Natural Variation in Biological and Simulated Central Pattern Generators

Here we analyze natural variability within two types of systems. 1, The output of the biological spinal central pattern generator for locomotion in the cat, and 2, Sets of stochastic neural networks giving an output qualitatively similar to that observed within the biological system. Fictive locomotion contains asymmetric transitions between the flexion and extension phases. The transition from extension to flexion is: 1, Always strongly phase locked; 2, Composed of overlapping extensor burst offsets and flexor burst onsets; and 3, Invariant to changes in mean cycle period. The transition from flexion to extension is: 1, Weakly phase locked within bouts containing short cycle periods, and well phase locked in bouts containing long cycle periods; 2, Offset times of flexor bursts and the onset times of extensor bursts do not overlap; and 3, Strength of phase locking depends critically upon relative timing of flexor offset and extensor onset. Stochastic neural networks that qualitatively reproducing the timing relationships observed within the biological system have outputs that depend upon both the architecture of the network as well as model neuronal type (oscillatory-non-oscillatory). Within models designed to reproduce the bi-phasic activity observed in some muscles, correlation of the bi-phasic burst is strongly influenced by model connectivity. Additionally sets of leaky integrators have burst durations, which are sometimes well correlated even though they are well separated in time. Half-center models producing alternating output are strongly influenced by the internal structure of simulated neurons. A half-center composed of a pair of leaky-integrators has transitions between phases which are always well phase locked, and overlapping. Half-centers composed of intrinsically oscillatory Morris-Lecar neurons have transitions between phases whose phase locking is parameter dependent. This parameter dependence is mainly due to changes in the timing of burst offset and burst onset. We conclude that the output of the biological central pattern generator is likely to be strongly influenced by the intrinsically oscillatory properties of its neurons. Models containing non-intrinsically oscillatory simulated neurons are unable to account for observed variability within the output of the biological system

The Group Creativity Exercise Getting MBAs to Work and Think Effectively in Groups

This experiential exercise is designed to engage participants in a process of group creativity that helps students lead or be a part of a creative team. The challenging and tangible nature of building a room­height tower provides a heightened experience that elicits many issues and strong emotions. The exercise provides a robust platform from which the instructor can choose which of many group creativity subtopics to emphasize. In addition to exercise instructions, guidance is given on how learning goals related to creativity techniques, group development, interpersonal dynamics, and leadership—can be addressed in a debriefing discussion. Both “pre­taught” and “retrospective” teaching approaches are discussed, although a retrospective approach in which the instructor makes connections with theory during debriefing discussions is recommended. The experience of learning by doing should yield more realistic and memorable understanding of group creativity than could be accomplished with readings and/or lecture alone

A Topological Deep Learning Framework for Neural Spike Decoding

The brain's spatial orientation system uses different neuron ensembles to aid in environment-based navigation. One of the ways brains encode spatial information is through grid cells, layers of decked neurons that overlay to provide environment-based navigation. These neurons fire in ensembles where several neurons fire at once to activate a single grid. We want to capture this firing structure and use it to decode grid cell data. Understanding, representing, and decoding these neural structures require models that encompass higher order connectivity than traditional graph-based models may provide. To that end, in this work, we develop a topological deep learning framework for neural spike train decoding. Our framework combines unsupervised simplicial complex discovery with the power of deep learning via a new architecture we develop herein called a simplicial convolutional recurrent neural network (SCRNN). Simplicial complexes, topological spaces that use not only vertices and edges but also higher-dimensional objects, naturally generalize graphs and capture more than just pairwise relationships. Additionally, this approach does not require prior knowledge of the neural activity beyond spike counts, which removes the need for similarity measurements. The effectiveness and versatility of the SCRNN is demonstrated on head direction data to test its performance and then applied to grid cell datasets with the task to automatically predict trajectories

Electron Affinity Calculations for Thioethers

Previous work indicated that polyphenyl thioethers possessed chemical properties, related to their electron affinities, which could allow them to function as vapor phase lubricants (VPL). Indeed, preliminary tribological tests revealed that the thioethers could function as vapor phase lubricants but not over a wide temperature and hertzian pressure range. Increasing the electron affinity of the thioethers may improve their VPL properties over this range. Adding a substituent group to the thioether will alter its electron affinity in many cases. Molecular orbital calculations were undertaken to determine the effect of five different substituent groups on the electron affinity of polyphenyl thioethers. It was found that the NO2, F, and I groups increased the thioethers electron affinity by the greatest amount. Future work will involve the addition of these groups to the thioethers followed by tribological testing to assess their VPL properties

Spin controlled atom-ion inelastic collisions

The control of the ultracold collisions between neutral atoms is an extensive and successful field of study. The tools developed allow for ultracold chemical reactions to be managed using magnetic fields, light fields and spin-state manipulation of the colliding particles among other methods. The control of chemical reactions in ultracold atom-ion collisions is a young and growing field of research. Recently, the collision energy and the ion electronic state were used to control atom-ion interactions. Here, we demonstrate spin-controlled atom-ion inelastic processes. In our experiment, both spin-exchange and charge-exchange reactions are controlled in an ultracold Rb-Sr$^+$ mixture by the atomic spin state. We prepare a cloud of atoms in a single hyperfine spin-state. Spin-exchange collisions between atoms and ion subsequently polarize the ion spin. Electron transfer is only allowed for (RbSr)$^+$ colliding in the singlet manifold. Initializing the atoms in various spin states affects the overlap of the collision wavefunction with the singlet molecular manifold and therefore also the reaction rate. We experimentally show that by preparing the atoms in different spin states one can vary the charge-exchange rate in agreement with theoretical predictions

Expression of the neuroprotective slow Wallerian degeneration (WldS) gene in non-neuronal tissues

<p>Abstract</p> <p>Background</p> <p>The slow Wallerian Degeneration (<it>Wld</it>^<it>S</it>) gene specifically protects axonal and synaptic compartments of neurons from a wide variety of degeneration-inducing stimuli, including; traumatic injury, Parkinson's disease, demyelinating neuropathies, some forms of motor neuron disease and global cerebral ischemia. The <it>Wld</it>^{<it>S </it>}gene encodes a novel Ube4b-Nmnat1 chimeric protein (Wld^Sprotein) that is responsible for conferring the neuroprotective phenotype. How the chimeric Wld^Sprotein confers neuroprotection remains controversial, but several studies have shown that expression in neurons <it>in vivo </it>and <it>in vitro </it>modifies key cellular pathways, including; NAD biosynthesis, ubiquitination, the mitochondrial proteome, cell cycle status and cell stress. Whether similar changes are induced in non-neuronal tissue and organs at a basal level <it>in vivo </it>remains to be determined. This may be of particular importance for the development and application of neuroprotective therapeutic strategies based around <it>Wld</it>^<it>S</it>-mediated pathways designed for use in human patients.</p> <p>Results</p> <p>We have undertaken a detailed analysis of non-neuronal <it>Wld</it>^{<it>S </it>}expression in <it>Wld</it>^{<it>S </it>}mice, alongside gravimetric and histological analyses, to examine the influence of <it>Wld</it>^{<it>S </it>}expression in non-neuronal tissues. We show that expression of <it>Wld</it>^{<it>S </it>}RNA and protein are not restricted to neuronal tissue, but that the relative RNA and protein expression levels rarely correlate in these non-neuronal tissues. We show that <it>Wld</it>^{<it>S </it>}mice have normal body weight and growth characteristics as well as gravimetrically and histologically normal organs, regardless of Wld^Sprotein levels. Finally, we demonstrate that previously reported <it>Wld</it>^<it>S</it>-induced changes in cell cycle and cell stress status are neuronal-specific, not recapitulated in non-neuronal tissues at a basal level.</p> <p>Conclusions</p> <p>We conclude that expression of Wld^Sprotein has no adverse effects on non-neuronal tissue at a basal level <it>in vivo</it>, supporting the possibility of its safe use in future therapeutic strategies targeting axonal and/or synaptic compartments in patients with neurodegenerative disease. Future experiments determining whether Wld^Sprotein can modify responses to injury in non-neuronal tissue are now required.</p

Impact of Neuronal Membrane Damage on the Local Field Potential in a Large-Scale Simulation of Cerebral Cortex

Within multiscale brain dynamics, the structure–function relationship between cellular changes at a lower scale and coordinated oscillations at a higher scale is not well understood. This relationship may be particularly relevant for understanding functional impairments after a mild traumatic brain injury (mTBI) when current neuroimaging methods do not reveal morphological changes to the brain common in moderate to severe TBI such as diffuse axonal injury or gray matter lesions. Here, we created a physiology-based model of cerebral cortex using a publicly released modeling framework (GEneral NEural SImulation System) to explore the possibility that performance deficits characteristic of blast-induced mTBI may reflect dysfunctional, local network activity influenced by microscale neuronal damage at the cellular level. We operationalized microscale damage to neurons as the formation of pores on the neuronal membrane based on research using blast paradigms, and in our model, pores were simulated by a change in membrane conductance. We then tracked changes in simulated electrical activity. Our model contained 585 simulated neurons, comprised of 14 types of cortical and thalamic neurons each with its own compartmental morphology and electrophysiological properties. Comparing the functional activity of neurons before and after simulated damage, we found that simulated pores in the membrane reduced both action potential generation and local field potential (LFP) power in the 1–40 Hz range of the power spectrum. Furthermore, the location of damage modulated the strength of these effects: pore formation on simulated axons reduced LFP power more strongly than did pore formation on the soma and the dendrites. These results indicate that even small amounts of cellular damage can negatively impact functional activity of larger scale oscillations, and our findings suggest that multiscale modeling provides a promising avenue to elucidate these relationships