SUMMARY We derive the joint distribution of the sequence of estimates of the parameter vector in a normal general linear model when data accumulate over a series of analyses. This sequence of estimates has a remarkably simple covariance structure, even when observations are correlated, allowing standard group sequential tests to be applied in very general settings. If variances and covariances ...

Multiple factors simultaneously affect the spiking activity of individual neurons. Determining the effects and relative importance of these factors is a challenging problem in neurophysiology. We propose a statistical framework based on the point process likelihood function to relate a neuron's spiking probability to three typical covariates: the neuron's own spiking history, concurrent ensembl...

This paper compares two habitat-suitability assessing methods, the Ecological Niche Factor Analysis (ENFA) and the Generalised Linear Model (GLM), to see how well they cope with three different scenarios. The main difference between these two analyses is that GLM is based on species presence/absence data while ENFA on presence data only. A virtual species was created and then dispatched in a ge...

There remains an open question about the usefulness and interpretation of Machine learning (MLE) approaches for discrimination spatial patterns brain images between samples or activation states. In last few decades, these have limited their operation to feature extraction linear classification tasks between-group inference. this context, statistical inference is assessed by randomly permuting i...

FMRI modelling requires flexible haemodynamic response function (HRF) modelling, with the HRF being allowed to vary spatially and between subjects. To achieve this flexibility, voxelwise parameterised HRFs have been proposed; however, inference on such models is very slow. An alternative approach is to use basis functions allowing inference to proceed in the more manageable General Linear Model...

When studying the neural responses to acupuncture with a block-designed paradigm, its temporal dynamics predicted by the general linear model (GLM) conforms to typical "on-off" variations during a limited period of the experiment manipulation. Despite a lack of direct evidence associating its psychophysiological response, numerous clinical reports suggest that acupuncture can provide pain relie...

OBJECTIVE To investigate the dynamics underlying the sustained effect of acupuncture as a possible explanation of earlier findings that acupuncture stimulation at the vision-related acupuncture point, GB37, cannot specifically change the functional MRI (fMRI) signals of the visual cortex compared with stimulation at an adjacent non-meridian point. METHODS The 'on-off' experimental design was ...

The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject's decision response to a given propositional statement based on independent component (IC) features derived from EEG and...

Functional magnetic resonance imaging (fMRI) is a technique to map the brain, anatomically as well as physiologically, which does not require any invasive analysis. In order to obtain brain activation maps, the subject under study must perform a task or be exposed to an external stimulus. At the same time a large amount of images are acquired using ultra-fast sequences through magnetic resonanc...

The success of the future exploitation Pacific polymetallic nodule deposits depends on an accurate estimation their resources, especially in small batches, scheduled for extraction short term. based only results direct seafloor sampling using box corers is burdened with a large error due to long interval and high variability abundance. Therefore, estimations should take into account bottom phot...