218 research outputs found
Active Learning on Center Stage: Theater as a Tool for Medical Education
Introduction:
Knowledge and skill development related to communication must incorporate both affective and behavioral components, which are often difficult to deliver in a learning activity. Using theater techniques and principles can provide medical educators with tools to teach communication concepts.
Methods:
This 75-minute faculty development workshop presents a variety of techniques from theater and adapts them for use in medical education. Using examples related to diversity and inclusion, this session addresses general educational and theater principles, role-play, sociodrama, applied improvisation, and practical aspects of involving theater partners. The session materials include a PowerPoint presentation with facilitator notes, interactive activities to demonstrate each modality, and an evaluation. The sessions can be extended to longer formats as needed.
Results:
Forty-five participants at Learn Serve Lead 2016: The AAMC Annual Meeting attended the 75-minute session. We emailed 32 participants 5 months after the conference, and eight responded. Participants reported that their confidence level in using theater techniques as a tool for medical education increased from low-to-medium confidence presession to high confidence postsession. All survey respondents who were actively teaching said they had made changes to their teaching based on the workshop. All commented that they appreciated the active learning in the session. Many indicated they would appreciate video or other follow-up resources.
Discussion:
Principles and techniques from theater are effective tools to convey difficult-to-teach concepts related to communication. This workshop presents tools to implement activities in teaching these difficult concepts
Noise-induced dynamics in bistable systems with delay
Noise-induced dynamics of a prototypical bistable system with delayed
feedback is studied theoretically and numerically. For small noise and
magnitude of the feedback, the problem is reduced to the analysis of the
two-state model with transition rates depending on the earlier state of the
system. In this two-state approximation, we found analytical formulae for the
autocorrelation function, the power spectrum, and the linear response to a
periodic perturbation. They show very good agreement with direct numerical
simulations of the original Langevin equation. The power spectrum has a
pronounced peak at the frequency corresponding to the inverse delay time, whose
amplitude has a maximum at a certain noise level, thus demonstrating coherence
resonance. The linear response to the external periodic force also has maxima
at the frequencies corresponding to the inverse delay time and its harmonics.Comment: 4 pages, 4 figures, submitted to Physical Review Letter
Statistical-Mechanical Measure of Stochastic Spiking Coherence in A Population of Inhibitory Subthreshold Neurons
By varying the noise intensity, we study stochastic spiking coherence (i.e.,
collective coherence between noise-induced neural spikings) in an inhibitory
population of subthreshold neurons (which cannot fire spontaneously without
noise). This stochastic spiking coherence may be well visualized in the raster
plot of neural spikes. For a coherent case, partially-occupied "stripes"
(composed of spikes and indicating collective coherence) are formed in the
raster plot. This partial occupation occurs due to "stochastic spike skipping"
which is well shown in the multi-peaked interspike interval histogram. The main
purpose of our work is to quantitatively measure the degree of stochastic
spiking coherence seen in the raster plot. We introduce a new spike-based
coherence measure by considering the occupation pattern and the pacing
pattern of spikes in the stripes. In particular, the pacing degree between
spikes is determined in a statistical-mechanical way by quantifying the average
contribution of (microscopic) individual spikes to the (macroscopic)
ensemble-averaged global potential. This "statistical-mechanical" measure
is in contrast to the conventional measures such as the "thermodynamic" order
parameter (which concerns the time-averaged fluctuations of the macroscopic
global potential), the "microscopic" correlation-based measure (based on the
cross-correlation between the microscopic individual potentials), and the
measures of precise spike timing (based on the peri-stimulus time histogram).
In terms of , we quantitatively characterize the stochastic spiking
coherence, and find that reflects the degree of collective spiking
coherence seen in the raster plot very well. Hence, the
"statistical-mechanical" spike-based measure may be used usefully to
quantify the degree of stochastic spiking coherence in a statistical-mechanical
way.Comment: 16 pages, 5 figures, to appear in the J. Comput. Neurosc
Autonomous stochastic resonance in fully frustrated Josephson-junction ladders
We investigate autonomous stochastic resonance in fully frustrated
Josephson-junction ladders, which are driven by uniform constant currents. At
zero temperature large currents induce oscillations between the two ground
states, while for small currents the lattice potential forces the system to
remain in one of the two states. At finite temperatures, on the other hand,
oscillations between the two states develop even below the critical current;
the signal-to-noise ratio is found to display array-enhanced stochastic
resonance. It is suggested that such behavior may be observed experimentally
through the measurement of the staggered voltage.Comment: 6 pages, 11 figures, to be published in Phys. Rev.
Stimulus - response curves of a neuronal model for noisy subthreshold oscillations and related spike generation
We investigate the stimulus-dependent tuning properties of a noisy ionic
conductance model for intrinsic subthreshold oscillations in membrane potential
and associated spike generation. On depolarization by an applied current, the
model exhibits subthreshold oscillatory activity with occasional spike
generation when oscillations reach the spike threshold. We consider how the
amount of applied current, the noise intensity, variation of maximum
conductance values and scaling to different temperature ranges alter the
responses of the model with respect to voltage traces, interspike intervals and
their statistics and the mean spike frequency curves. We demonstrate that
subthreshold oscillatory neurons in the presence of noise can sensitively and
also selectively be tuned by stimulus-dependent variation of model parameters.Comment: 19 pages, 7 figure
Dynamical mean-field theory of spiking neuron ensembles: response to a single spike with independent noises
Dynamics of an ensemble of -unit FitzHugh-Nagumo (FN) neurons subject to
white noises has been studied by using a semi-analytical dynamical mean-field
(DMF) theory in which the original -dimensional {\it stochastic}
differential equations are replaced by 8-dimensional {\it deterministic}
differential equations expressed in terms of moments of local and global
variables. Our DMF theory, which assumes weak noises and the Gaussian
distribution of state variables, goes beyond weak couplings among constituent
neurons. By using the expression for the firing probability due to an applied
single spike, we have discussed effects of noises, synaptic couplings and the
size of the ensemble on the spike timing precision, which is shown to be
improved by increasing the size of the neuron ensemble, even when there are no
couplings among neurons. When the coupling is introduced, neurons in ensembles
respond to an input spike with a partial synchronization. DMF theory is
extended to a large cluster which can be divided into multiple sub-clusters
according to their functions. A model calculation has shown that when the noise
intensity is moderate, the spike propagation with a fairly precise timing is
possible among noisy sub-clusters with feed-forward couplings, as in the
synfire chain. Results calculated by our DMF theory are nicely compared to
those obtained by direct simulations. A comparison of DMF theory with the
conventional moment method is also discussed.Comment: 29 pages, 2 figures; augmented the text and added Appendice
Coherence Resonance and Noise-Induced Synchronization in Globally Coupled Hodgkin-Huxley Neurons
The coherence resonance (CR) of globally coupled Hodgkin-Huxley neurons is
studied. When the neurons are set in the subthreshold regime near the firing
threshold, the additive noise induces limit cycles. The coherence of the system
is optimized by the noise. A bell-shaped curve is found for the peak height of
power spectra of the spike train, being significantly different from a
monotonic behavior for the single neuron. The coupling of the network can
enhance CR in two different ways. In particular, when the coupling is strong
enough, the synchronization of the system is induced and optimized by the
noise. This synchronization leads to a high and wide plateau in the local
measure of coherence curve. The local-noise-induced limit cycle can evolve to a
refined spatiotemporal order through the dynamical optimization among the
autonomous oscillation of an individual neuron, the coupling of the network,
and the local noise.Comment: five pages, five figure
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