The simplest expression of episodic memory is the experience of familiarity, the isolated recognition that something has been encountered previously. Brain structures of the medial temporal lobe (MTL) make essential contributions to episodic memory, but the distinct contributions from each MTL structure to familiarity are debatable. Here we used specialized tests to assess recognition impairmen...

INTRODUCTION Governments throughout the world are using or considering various front-of-package (FOP) food labeling systems to provide nutrition information to consumers. Our web-based study tested consumer understanding of different FOP labeling systems. METHODS Adult participants (N = 480) were randomized to 1 of 5 groups to evaluate FOP labels: 1) no label; 2) multiple traffic light (MTL);...

Multi-task learning (MTL) has recently contributed to learning better representations in service of various NLP tasks. MTL aims at improving the performance of a primary task, by jointly training on a secondary task. This paper introduces automated tasks, which exploit the sequential nature of the input data, as secondary tasks in an MTL model. We explore next word prediction, next character pr...

We compared value recovery of a modified tree-length (MTL) logging system that measures product diameter and length using a Waratah 626 harvester head to that of a tree-length (TL) system that estimates dimensions. A field test compared the actual value cut to the maximum potential value suggested by the log bucking optimization program Assessment of Value by Individual Stems (AVIS) for 25 fell...

Multi-task learning (MTL) involves the simultaneous training of two or more related tasks over shared representations. In this work, we apply MTL to audio-visual automatic speech recognition(AV-ASR). Our primary task is to learn a mapping between audio-visual fused features and frame labels obtained from acoustic GMM/HMM model. This is combined with an auxiliary task which maps visual features ...

Multi-task learning (MTL) is considered for logistic-regression classifiers, based on a Dirichlet process (DP) formulation. A symmetric MTL (SMTL) formulation is considered in which classifiers for multiple tasks are learned jointly, with a variational Bayesian (VB) solution. We also consider an asymmetric MTL (AMTL) formulation in which the posterior density function from the SMTL model parame...

The medial temporal lobe (MTL) has been associated with declarative learning of flexible relational rules and the basal ganglia with implicit learning of stimulus-response mappings. It remains an open question of whether MTL or basal ganglia are involved when learning flexible relational contingencies without awareness. We studied learning of an explicit stimulus-response association with fMRI....

Event-related potentials (ERPs) were recorded from epileptic patients with electrodes chronically implanted in the medial temporal lobe (MTL) and other intracranial locations, and from monkeys with epidural, transcortical, and MTL electrodes. For both humans and monkeys, the eliciting events consisted of trains of auditory or visual stimuli in which a random 10-20% deviated in pitch or pattern ...

Multi-task learning (MTL) can be an effective way to improve the generalization performance of singly learning tasks if the tasks are related, especially when the amount of training data is small. Our previous work applied MTL to the joint training of triphone and trigrapheme acoustic models using deep neural networks (DNNs) for low-resource speech recognition. Significant recognition improveme...

Medial temporal lobe (MTL) function is well established as necessary for memory of facts and events. It is likely that lateral cortical regions critically guide cognitive control processes to tune in high-fidelity details that are most relevant for memory retrieval. Here, convergent results from functional and structural MRI show that retrieval of detailed episodic memory arises from lateral co...