Understanding Hidden Memories of Recurrent Neural Networks

Recurrent neural networks (RNNs) have been successfully applied to various natural language processing (NLP) tasks and achieved better results than conventional methods. However, the lack of understanding of the mechanisms behind their effectiveness limits further improvements on their architectures. In this paper, we present a visual analytics method for understanding and comparing RNN models for NLP tasks. We propose a technique to explain the function of individual hidden state units based on their expected response to input texts. We then co-cluster hidden state units and words based on the expected response and visualize co-clustering results as memory chips and word clouds to provide more structured knowledge on RNNs' hidden states. We also propose a glyph-based sequence visualization based on aggregate information to analyze the behavior of an RNN's hidden state at the sentence-level. The usability and effectiveness of our method are demonstrated through case studies and reviews from domain experts.Comment: Published at IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017

Supraspinal characterization of the thermal grill illusion with fMRI.

BackgroundSimultaneous presentation of non-noxious warm (40°C) and cold (20°C) stimuli in an interlacing fashion results in a transient hot burning noxious sensation (matched at 46°C) known as the thermal grill (TG) illusion. Functional magnetic resonance imaging and psychophysical assessments were utilized to compare the supraspinal events related to the spatial summation effect of three TG presentations: 20°C/20°C (G2020), 20°C/40°C (G2040) and 40°C/40°C (G4040) with corresponding matched thermode stimuli: 20°C (P20), 46°C (P46) and 40°C (P40) and hot pain (HP) stimuli.ResultsFor G2040, the hot burning sensation was only noted during the initial off-line assessment. In comparison to P40, G4040 resulted in an equally enhanced response from all supraspinal regions associated with both pain sensory/discriminatory and noxious modulatory response. In comparison to P20, G2020 presentation resulted in a much earlier diminished/sedative response leading to a statistically significantly (P < 0.01) higher degree of deactivation in modulatory supraspinal areas activated by G4040. Granger Causality Analysis showed that while thalamic activation in HP may cast activation inference in all hot pain related somatosensory, affective and modulatory areas, similar activation in G2040 and G2020 resulted in deactivation inference in the corresponding areas.ConclusionsIn short, the transient TG sensation is caused by a dissociated state derived from non-noxious warm and cold spatial summation interaction. The observed central dissociated state may share some parallels in certain chronic neuropathic pain states

Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

Will this work for Susan? Challenges for delivering usable and useful generic linked data browsers

While we witness an explosion of exploration tools for simple datasets on Web 2.0 designed for use by ordinary citizens, the goal of a usable interface for supporting navigation and sense-making over arbitrary linked data has remained elusive. The purpose of this paper is to analyse why - what makes exploring linked data so hard? Through a user-centered use case scenario, we work through requirements for sense making with data to extract functional requirements and to compare these against our tools to see what challenges emerge to deliver a useful, usable knowledge building experience with linked data. We present presentation layer and heterogeneous data integration challenges and offer practical considerations for moving forward to effective linked data sensemaking tools

LFP beta amplitude is predictive of mesoscopic spatio-temporal phase patterns

Beta oscillations observed in motor cortical local field potentials (LFPs) recorded on separate electrodes of a multi-electrode array have been shown to exhibit non-zero phase shifts that organize into a planar wave propagation. Here, we generalize this concept by introducing additional classes of patterns that fully describe the spatial organization of beta oscillations. During a delayed reach-to-grasp task in monkey primary motor and dorsal premotor cortices we distinguish planar, synchronized, random, circular, and radial phase patterns. We observe that specific patterns correlate with the beta amplitude (envelope). In particular, wave propagation accelerates with growing amplitude, and culminates at maximum amplitude in a synchronized pattern. Furthermore, the occurrence probability of a particular pattern is modulated with behavioral epochs: Planar waves and synchronized patterns are more present during movement preparation where beta amplitudes are large, whereas random phase patterns are dominant during movement execution where beta amplitudes are small