A long short-term memory network for vessel reconstruction based on laser doppler flowmetry via a steerable needle

Hemorrhage is one risk of percutaneous intervention in the brain that can be life-threatening. Steerable needles can avoid blood vessels thanks to their ability to follow curvilinear paths, although knowledge of vessel pose is required. To achieve this, we present the deployment of laser Doppler flowmetry (LDF) sensors as an in-situ vessel detection method for steerable needles. Since the perfusion value from an LDF system does not provide positional information directly, we propose the use of a machine learning technique based on a Long Short-term Memory (LSTM) network to perform vessel reconstruction online. Firstly, the LSTM is used to predict the diameter and position of an approaching vessel based on successive measurements of a single LDF probe. Secondly, a "no-go" area is predicted based on the measurement from four LDF probes embedded within a steerable needle, which accounts for the full vessel pose. The network was trained using simulation data and tested on experimental data, with 75 % diameter prediction accuracy and 0.27 mm positional Root Mean Square (RMS) Error for the single probe network, and 77 % vessel volume overlap for the 4-probe setup

Musicians have better memory than nonmusicians: A meta-analysis

Background Several studies have found that musicians perform better than nonmusicians in memory tasks, but this is not always the case, and the strength of this apparent advantage is unknown. Here, we conducted a meta-analysis with the aim of clarifying whether musicians perform better than nonmusicians in memory tasks. Methods Education Source; PEP (WEB)\u2014Psychoanalytic Electronic Publishing; Psychology and Behavioral Science (EBSCO); PsycINFO (Ovid); PubMed; ScienceDirect\u2014AllBooks Content (Elsevier API); SCOPUS (Elsevier API); SocINDEX with Full Text (EBSCO) and Google Scholar were searched for eligible studies. The selected studies involved two groups of participants: young adult musicians and nonmusicians. All the studies included memory tasks (loading long-term, short-term or working memory) that contained tonal, verbal or visuospatial stimuli. Three meta-analyses were run separately for long-term memory, short-term memory and working memory. Results We collected 29 studies, including 53 memory tasks. The results showed that musicians performed better than nonmusicians in terms of long-term memory, g = .29, 95% CI (.08\u2013.51), short-term memory, g = .57, 95% CI (.41\u2013.73), and working memory, g = .56, 95% CI (.33\u2013.80). To further explore the data, we included a moderator (the type of stimulus presented, i.e., tonal, verbal or visuospatial), which was found to influence the effect size for short-term and working memory, but not for long-term memory. In terms of short-term and working memory, the musicians\u2019 advantage was large with tonal stimuli, moderate with verbal stimuli, and small or null with visuospatial stimuli. Conclusions The three meta-analyses revealed a small effect size for long-term memory, and a medium effect size for short-term and working memory, suggesting that musicians perform better than nonmusicians in memory tasks. Moreover, the effect of the moderator suggested that, the type of stimuli influences this advantage

Lipreading with Long Short-Term Memory

Lipreading, i.e. speech recognition from visual-only recordings of a speaker's face, can be achieved with a processing pipeline based solely on neural networks, yielding significantly better accuracy than conventional methods. Feed-forward and recurrent neural network layers (namely Long Short-Term Memory; LSTM) are stacked to form a single structure which is trained by back-propagating error gradients through all the layers. The performance of such a stacked network was experimentally evaluated and compared to a standard Support Vector Machine classifier using conventional computer vision features (Eigenlips and Histograms of Oriented Gradients). The evaluation was performed on data from 19 speakers of the publicly available GRID corpus. With 51 different words to classify, we report a best word accuracy on held-out evaluation speakers of 79.6% using the end-to-end neural network-based solution (11.6% improvement over the best feature-based solution evaluated).Comment: Accepted for publication at ICASSP 201

Self-rated everyday prospective memory abilities of cigarette smokers and non-smokers: a web based study

The present study examined self-ratings of two aspects of everyday memory performance: long-term prospective memory—measured by the prospective memory questionnaire (PMQ), and everyday memory—measured by the everyday memory questionnaire (EMQ). Use of other substances was also measured and used as covariates in the study. To ensure confidentiality and to expand the numbers used in previous studies, an Internet study was carried out and data from 763 participants was gathered. After controlling for other drug use and strategy use, the data from the PMQ revealed that smokers reported a greater number of long-term prospective memory errors than non-smokers. There were also differences between light and heavier smokers in long-term prospective memory, suggesting that nicotine may have a dose-dependent impact upon long-term prospective memory performance. There was also a significant ANOVA group effect on the EMQ, although the trend for more memory errors amongst the heavier smokers was statistically only borderline (p = .057). These findings suggest there are selective memory deficits associated with smoking and that long-term prospective memory deficits should be added to the growing list of problems associated with cigarette use

Some shortcomings of long-term working memory

Within the framework of their long-term working memory theory, Ericsson and Kintsch (1995) propose that experts rapidly store information in long-term memory through two mechanisms: elaboration of long-term memory patterns and schemas and use of retrieval structures. They use chess players’ memory as one of their most compelling sources of empirical evidence. In this paper, I show that evidence from chess memory, far from supporting their theory, limits its generality. Evidence from other domains reviewed by Ericsson and Kintsch, such as medical expertise, is not as strong as claimed, and sometimes contradicts the theory outright. I argue that Ericsson and Kintsch’s concept of retrieval structure conflates three different types of memory structures that possess quite different properties. One of these types of structures—generic, general-purpose retrieval structures—has a narrower use than proposed by Ericsson and Kintsch: it applies only in domains where there is a conscious, deliberate intent by individuals to improve their memory. Other mechanisms, including specific retrieval structures, exist that permit a rapid encoding into long-term memory under other circumstances