Gaussian process models for periodicity detection

We consider the problem of detecting and quantifying the periodic component of a function given noise-corrupted observations of a limited number of input/output tuples. Our approach is based on Gaussian process regression which provides a flexible non-parametric framework for modelling periodic data. We introduce a novel decomposition of the covariance function as the sum of periodic and aperiodic kernels. This decomposition allows for the creation of sub-models which capture the periodic nature of the signal and its complement. To quantify the periodicity of the signal, we derive a periodicity ratio which reflects the uncertainty in the fitted sub-models. Although the method can be applied to many kernels, we give a special emphasis to the Mat\'ern family, from the expression of the reproducing kernel Hilbert space inner product to the implementation of the associated periodic kernels in a Gaussian process toolkit. The proposed method is illustrated by considering the detection of periodically expressed genes in the arabidopsis genome.Comment: in PeerJ Computer Science, 201

Gaussian Processes for Big Data

We introduce stochastic variational inference for Gaussian process models. This enables the application of Gaussian process (GP) models to data sets containing millions of data points. We show how GPs can be vari- ationally decomposed to depend on a set of globally relevant inducing variables which factorize the model in the necessary manner to perform variational inference. Our ap- proach is readily extended to models with non-Gaussian likelihoods and latent variable models based around Gaussian processes. We demonstrate the approach on a simple toy problem and two real world data sets.Comment: Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

BACKGROUND: Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. RESULTS: We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. CONCLUSION: The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/

Fast Nonparametric Clustering of Structured Time-Series.

In this publication, we combine two Bayesian nonparametric models: the Gaussian Process (GP) and the Dirichlet Process (DP). Our innovation in the GP model is to introduce a variation on the GP prior which enables us to model structured time-series data, i.e., data containing groups where we wish to model inter- and intra-group variability. Our innovation in the DP model is an implementation of a new fast collapsed variational inference procedure which enables us to optimize our variational approximation significantly faster than standard VB approaches. In a biological time series application we show how our model better captures salient features of the data, leading to better consistency with existing biological classifications, while the associated inference algorithm provides a significant speed-up over EM-based variational inference

Fast Variational Inference in the Conjugate Exponential Family

We present a general method for deriving collapsed variational inference algo- rithms for probabilistic models in the conjugate exponential family. Our method unifies many existing approaches to collapsed variational inference. Our collapsed variational inference leads to a new lower bound on the marginal likelihood. We exploit the information geometry of the bound to derive much faster optimization methods based on conjugate gradients for these models. Our approach is very general and is easily applied to any model where the mean field update equations have been derived. Empirically we show significant speed-ups for probabilistic models optimized using our bound.Comment: Accepted at NIPS 201

Counteractive effects of antenatal glucocorticoid treatment on D1 receptor modulation of spatial working memory.

RATIONALE: Antenatal exposure to the glucocorticoid dexamethasone dramatically increases the number of mesencephalic dopaminergic neurons in rat offspring. However, the consequences of this expansion in midbrain dopamine (DA) neurons for behavioural processes in adulthood are poorly understood, including working memory that depends on DA transmission in the prefrontal cortex (PFC). OBJECTIVES: We therefore investigated the influence of antenatal glucocorticoid treatment (AGT) on the modulation of spatial working memory by a D1 receptor agonist and on D1 receptor binding and DA content in the PFC and striatum. METHODS: Pregnant rats received AGT on gestational days 16-19 by adding dexamethasone to their drinking water. Male offspring reared to adulthood were trained on a delayed alternation spatial working memory task and administered the partial D1 agonist SKF38393 (0.3-3 mg/kg) by systemic injection. In separate groups of control and AGT animals, D1 receptor binding and DA content were measured post-mortem in the PFC and striatum. RESULTS: SKF38393 impaired spatial working memory performance in control rats but had no effect in AGT rats. D1 binding was significantly reduced in the anterior cingulate cortex, prelimbic cortex, dorsal striatum and ventral pallidum of AGT rats compared with control animals. However, AGT had no significant effect on brain monoamine levels. CONCLUSIONS: These findings demonstrate that D1 receptors in corticostriatal circuitry down-regulate in response to AGT. This compensatory effect in D1 receptors may result from increased DA-ergic tone in AGT rats and underlie the resilience of these animals to the disruptive effects of D1 receptor activation on spatial working memory.The authors’ research is funded by the Wellcome Trust (grant number 086871/Z/08/Z), the MRC (G0701500), a joint award from the MRC (G1000183) and Wellcome Trust (093875/Z/10/ Z) in support of the Behavioral and Clinical Neuroscience Institute at Cambridge University, and an MRC strategic award to the Imperial College-Cambridge University-Manchester University (ICCAM) addiction cluster (G1000018).This is the final version of the article. It first appeared from Springer at http://dx.doi.org/10.1007/s00213-016-4405-8

Does surgeon sex and anthropometry matter for tool usability in traditional laparoscopic surgery? A systematic review and meta-analysis

Copyright © The Author(s) 2023 Introduction: Hand size, strength, and stature all impact a surgeon’s ability to perform Traditional Laparoscopic Surgery (TLS) comfortably and effectively. This is due to limitations in instrument and operating room design. This article aims to review performance, pain, and tool usability data based on biological sex and anthropometry. Methods: PubMed, Embase, and Cochrane databases were searched in May 2023. Retrieved articles were screened based on whether a full-text, English article was available in which original results were stratified by biological sex or physical proportions. Article quality was discussed using the Mixed Methods Appraisal Tool (MMAT). Data were summarized in three main themes: task performance, physical discomfort, and tool usability and fit. Task completion times, pain prevalence, and grip style results between male and female surgeons formed three meta-analyses. Results: A total of 1354 articles were sourced, and 54 were deemed suitable for inclusion. The collated results showed that female participants, predominantly novices, took 2.6–30.1 s longer to perform standardized laparoscopic tasks. Female surgeons reported pain at double the frequency of their male colleagues. Female surgeons and those with a smaller glove size were consistently more likely to report difficulty and require modified (potentially suboptimal) grip techniques with standard laparoscopic tools. Conclusions: The pain and stress reported by female or small-handed surgeons when using laparoscopic tools demonstrates the need for currently available instrument handles, including robotic hand controls, to become more size-inclusive. However, this study is limited by reporting bias and inconsistencies; furthermore, most data was collected in a simulated environment. Additional research into how anthropometric tool design impacts the live operating performance of experienced female surgeons would further inform this area of investigation.Open Access funding enabled and organized by CAUL and its Member Institutions. This review was commissioned and funded by CMR Surgical Ltd

Dis-Locations: Mapping the Banlieue

Representations of the French suburbs in contemporary French film have, since the late 1980s, identified an apparent generic specificity that is linked closely to this location. I will explore the narrative tropes of alienation and exclusion—as dislocations—which have dominated the filmic representation of banlieue spaces and their populations before examining examples in which the realignment of sociocultural topographies and film space foregrounds the question of whether representations of the banlieue remain inherently and generically connected to realist discourses dominated by spatial representation of exclusions, or whether the over-determined spaces of the banlieue can act as décor, as setting and wider spatial frame. I will then focus on the presence and function of banlieue spaces and narratives in two recent French films—Girlhood/Bande de filles (Céline Sciamma 2014) and Palme d’or winner Dheepan (Jacques Audiard 2015)—suggesting that the banlieue continues to provide a complex site that both asserts socio-economic specificities and serves as a stylized setting through which to foreground other negotiations of territory and agency

Visualizing sound emission of elephant vocalizations: evidence for two rumble production types

Recent comparative data reveal that formant frequencies are cues to body size in animals, due to a close relationship between formant frequency spacing, vocal tract length and overall body size. Accordingly, intriguing morphological adaptations to elongate the vocal tract in order to lower formants occur in several species, with the size exaggeration hypothesis being proposed to justify most of these observations. While the elephant trunk is strongly implicated to account for the low formants of elephant rumbles, it is unknown whether elephants emit these vocalizations exclusively through the trunk, or whether the mouth is also involved in rumble production. In this study we used a sound visualization method (an acoustic camera) to record rumbles of five captive African elephants during spatial separation and subsequent bonding situations. Our results showed that the female elephants in our analysis produced two distinct types of rumble vocalizations based on vocal path differences: a nasally- and an orally-emitted rumble. Interestingly, nasal rumbles predominated during contact calling, whereas oral rumbles were mainly produced in bonding situations. In addition, nasal and oral rumbles varied considerably in their acoustic structure. In particular, the values of the first two formants reflected the estimated lengths of the vocal paths, corresponding to a vocal tract length of around 2 meters for nasal, and around 0.7 meters for oral rumbles. These results suggest that African elephants may be switching vocal paths to actively vary vocal tract length (with considerable variation in formants) according to context, and call for further research investigating the function of formant modulation in elephant vocalizations. Furthermore, by confirming the use of the elephant trunk in long distance rumble production, our findings provide an explanation for the extremely low formants in these calls, and may also indicate that formant lowering functions to increase call propagation distances in this species'