Abstracts of the 2014 Brains, Minds, and Machines Summer School

A compilation of abstracts from the student projects of the 2014 Brains, Minds, and Machines Summer School, held at Woods Hole Marine Biological Lab, May 29 - June 12, 2014.This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216

Experimental Analysis of Dynamic Interactions between Micrometer-Scale Stainless Steel Spheres

The quasi-static interactions between macroscopic, spherical particles are well described by the Hertzian contact law. However, little is known about the interaction law at the micrometer scale, where the effects of electrostatic and hydrodynamic forces at the contact are no longer negligible. Contact dynamics at the micrometer scale have been relatively unexplored due to experimental challenges, since the particles are too small in size to be excited by actuators but too massive to be manipulated by electromagnetic fields. In this work, we experimentally study the dynamic interactions between two micrometer-scale spheres colliding in a v-shaped groove. From our experiments we determine physical parameters of interest that inform us about the force laws that apply before, during and after the collision. These parameters include the coefficient of air resistance, the coefficient of friction between the spheres and the groove, the coefficient of friction between two spheres in contact, and the coefficient of restitution

Switching state-space modeling of neural signal dynamics.

Linear parametric state-space models are a ubiquitous tool for analyzing neural time series data, providing a way to characterize the underlying brain dynamics with much greater statistical efficiency than non-parametric data analysis approaches. However, neural time series data are frequently time-varying, exhibiting rapid changes in dynamics, with transient activity that is often the key feature of interest in the data. Stationary methods can be adapted to time-varying scenarios by employing fixed-duration windows under an assumption of quasi-stationarity. But time-varying dynamics can be explicitly modeled by switching state-space models, i.e., by using a pool of state-space models with different dynamics selected by a probabilistic switching process. Unfortunately, exact solutions for state inference and parameter learning with switching state-space models are intractable. Here we revisit a switching state-space model inference approach first proposed by Ghahramani and Hinton. We provide explicit derivations for solving the inference problem iteratively after applying a variational approximation on the joint posterior of the hidden states and the switching process. We introduce a novel initialization procedure using an efficient leave-one-out strategy to compare among candidate models, which significantly improves performance compared to the existing method that relies on deterministic annealing. We then utilize this state inference solution within a generalized expectation-maximization algorithm to estimate model parameters of the switching process and the linear state-space models with dynamics potentially shared among candidate models. We perform extensive simulations under different settings to benchmark performance against existing switching inference methods and further validate the robustness of our switching inference solution outside the generative switching model class. Finally, we demonstrate the utility of our method for sleep spindle detection in real recordings, showing how switching state-space models can be used to detect and extract transient spindles from human sleep electroencephalograms in an unsupervised manner

Broadband slow-wave modulation in posterior and anterior cortex tracks distinct states of propofol-induced unconsciousness

© 2020, The Author(s). A controversy has developed in recent years over the roles of frontal and posterior cortices in mediating consciousness and unconsciousness. Disruption of posterior cortex during sleep appears to suppress the contents of dreaming, yet activation of frontal cortex appears necessary for perception and can reverse unconsciousness under anesthesia. We used anesthesia to study how regional cortical disruption, mediated by slow wave modulation of broadband activity, changes during unconsciousness in humans. We found that broadband slow-wave modulation enveloped posterior cortex when subjects initially became unconscious, but later encompassed both frontal and posterior cortex when subjects were more deeply anesthetized and likely unarousable. Our results suggest that unconsciousness under anesthesia comprises several distinct shifts in brain state that disrupt the contents of consciousness distinct from arousal and awareness of those contents

Light therapy for multiple sclerosis-associated fatigue: a randomized, controlled phase II trial

Abstract Background Bright white light therapy (LT) can improve fatigue in several disease states but has not been studied in multiple sclerosis (MS). Objective To determine whether controlled home-based LT is feasible, tolerable, and well-adhered to in MS-associated fatigue. Methods A randomized, controlled trial of twice-daily 1-h bright white LT (BWLT) (10,000 lx, active arm) versus dim red LT (DRLT) (< 300 lx, control arm) was performed. Adults with MS-associated fatigue were enrolled for 10 weeks: 2-week baseline, 4-week intervention, 4-week washout. Results 41 participants were enrolled; 35 were randomized (average age 42 years, 80% female; BWLT n = 20; DRLT n = 15). 31 were in the intention to treat analysis. The average duration of LT sessions was similar between groups (BWLT 60.9 min, DRLT 61.5 min, p = 0.70). The most commonly reported adverse event was headache. There were no events that led to discontinuation. Baseline fatigue was severe in both arms (each 53/63 points on the Fatigue Severity Scale (FSS), p = 0.92). FSS was lower following BWLT (FSS 45.8 post-LT, p = 0.04; 44.9 post-washout, p = 0.02 intra-group compared to baseline FSS) and DRLT (FSS 46.7 post-LT, p = 0.03; 43.9 post-washout, p = 0.002 intragroup compared to baseline FSS). There was no difference between BWLT and DRLT groups in the magnitude of reduction of FSS scores (p = 0.81 after LT; p = 0.77 after washout for between group comparisons). Similarly, MS quality of life metrics improved in both arms but were not significantly different between groups after LT (p = 0.22) or washout. Conclusions LT is safe, feasible, and well-tolerated in people with MS-associated fatigue. Improvement in both light spectra likely indicates a strong placebo effect for the DRLT group