SRI International
-
Optogenetic Manipulation of Activity and Temporally Controlled Cell-Specific Ablation Reveal a Role for MCH Neurons in Sleep/Wake Regulation
To determine the physiological role of MCH neurons, newly developed transgenic mouse strains that enable manipulation of the activity and fate of MCH neurons in vivo were generated using the recently developed knockin-mediated enhanced gene expression by improved tetracycline-controlled gene induction system.
-
The Adaptor Protein SAP Regulates Type II NKT-Cell Development, Cytokine Production, and Cytotoxicity against Lymphoma
Here, using a type II NKT-cell TCR transgenic mouse model, we demonstrated that CD1d-expressing hematopoietic cells, but not thymic epithelial cells, meditate efficient selection of type II NKT cells.
-
Coordinated Ionospheric Observations Indicating Coupling between Preonset Flow Bursts and Waves That Lead to Substorm Onset
A critical, long-standing problem in substorm research is identification of the sequence of events leading to substorm expansion phase onset.
-
Conditional Ablation of Orexin/Hypocretin Neurons: A New Mouse Model for the Study of Narcolepsy and Orexin System Function
The sleep disorder narcolepsy results from loss of hypothalamic orexin/hypocretin neurons. Although narcolepsy onset is usually postpubertal, current mouse models involve loss of either orexin peptides or orexin neurons from birth. To create a model of orexin/hypocretin deficiency with closer fidelity to human narcolepsy, diphtheria toxin A (DTA) was expressed in orexin neurons under control…
-
GABAB Agonism Promotes Sleep and Reduces Cataplexy in Murine Narcolepsy
We evaluated the effects of chronic administration of GHB and the GABA B agonist R -baclofen ( R -BAC) on arousal state and cataplexy in two models of narcolepsy: orexin/ataxin-3 (Atax) and orexin/tTA; TetO diphtheria toxin mice (DTA).
-
ASR Error Detection Using Recurrent Neural Network Language Model and Complementary ASR
Our goal is to locate errors in an utterance so that the dialogue manager can pose appropriate clarification questions to the users.
-
An Autoencoder with Bilingual Sparse Features for Improved Statistical Machine Translation
We propose a natural autoencoder that maps all the discrete and overlapping sparse features for each SCFG rule into a continuous vector, so that the information encoded in sparse feature vectors becomes a dense vector that may enjoy more samples during training and avoid overfitting.
-
Computationally-Efficient Endpointing Features for Natural Spoken Interaction with Personal-Assistant Systems
We elicit personal-assistant speech using a recognizer with a dramatically increased endpoint threshold, and find frequent non-final pauses. Based on the new data, we develop low-cost acoustic features to discriminate non-final from final pauses.
-
Dissociation of Preparatory Attention and Response Monitoring Maturation During Adolescence
The objective was to assess development of EEG markers of these strategies and their role in both preparatory attention (contingent negative variation, CNV) and response monitoring (Error Related Negativity, ERN, and Correct Related Negativity, CRN).
-
A Novel Scheme for Speaker Recognition Using a Phonetically-Aware Deep Neural Network
We propose a novel framework for speaker recognition in which extraction of sufficient statistics for the state-of-the-art i-vector model is driven by a deep neural network (DNN) trained for automatic speech recognition (ASR).
-
Synchrony of Anterior Cingulate Cortex and Insular-Striatal Activation Predicts Ambiguity Aversion in Individuals with Low Impulsivity
To test how dACC functional network connectivity would be modulated by uncertainty and differ between individuals, 24 healthy participants underwent functional MRI in 3 sequential runs: 1 resting-state and 2 decision-making task runs. Individuals with lower nonplanning impulsiveness made greater use of a Pass option and avoided uncertain ambiguous situations.
-
Towards Quantifying the Completeness of BDI Goals
We sketch a pragmatic but principled mechanism for quantifying the level of completeness of goals in a Belief-Desire-Intention–like agent.