Nerve injury can lead to mechanical hypersensitivity in both humans and animal models, such that innocuous touch produces pain. Recent functional studies have demonstrated a critical role for descending pain-facilitating influences from the rostral ventromedial medulla (RVM) in neuropathic pain, but the underlying mechanisms and properties of the relevant neurons within the RVM are essentially ...

The paper investigates the application of a recently introduced learning technique, called the relevance vector machine (RVM) to construct a block-adaptive kernel-based nonlinear multiuser detector (MUD) for direct-sequence code-division multiple-access (DS-CDMA) signals transmitted through multipath channels. It is demonstrated that the RVM MUD can closely match the performance of the optimal ...

To resolve the online detection difficulty of some important state variables in fermentation process with traditional instruments, a soft sensing modeling method based on relevance vector machine (RVM) with a hybrid kernel function is presented. Based on the characteristic analysis of two commonly-used kernel functions, that is, local Gaussian kernel function and global polynomial kernel functi...

In this research, a comparison of the relevance vector machine (RVM), least square support vector machine (LSSVM) and the radial basis function neural network (RBFNN) for evaporation duct estimation are presented. The parabolic equation model is adopted as the forward propagation model, and which is used to establish the training database between the radar sea clutter power and the evaporation ...

The Condensation and the Wavelet Approximated Reduced Vector Machine (W-RVM) approach are joined by the core idea to spend only as much as necessary effort for easy to discriminate regions (Condensation) and measurement locations (W-RVM) of the feature space, but most for regions and locations with high statistical likelihood to contain the object of interest. We unify both approaches by adapti...

The objective and automated monitoring of depression using behavioral signals is confounded by the wide clinical profile of this commonly occurring mood disorder. This paper introduces Relevance Vector Machines, a novel method for predicting clinical depression scores from paralinguistic cues. It highlights many of the advantages RVM can offer depression prediction; sparsity, implicit noise cha...

PURPOSE To determine whether combining structural (optical coherence tomography, OCT) and functional (standard automated perimetry, SAP) measurements as input for machine learning classifiers (MLCs; relevance vector machine, RVM; and subspace mixture of Gaussians, SSMoG) improves diagnostic accuracy for detecting glaucomatous eyes compared with using each measurement method alone. METHODS Six...

In recent years there is an increasing interest for analytical methods that learn patterns over large-scale data distributed over Peer-to-Peer (P2P) networks and support applications. Mining patterns in such distributed and dynamic environment is a challenging task, because centralization of data is not feasible. In this paper, we have proposed a distributed classification technique based on Re...

BACKGROUND Our previous studies have shown that complete Freund's adjuvant (CFA)-induced masseter inflammation and microinjection of the pro-inflammatory cytokine interleukin-1β (IL-1β) into the subnucleus interpolaris/subnucleus caudalis transition zone of the spinal trigeminal nucleus (Vi/Vc) can induce contralateral orofacial hyperalgesia in rat models. We have also shown that contralateral ...

Many analgesic drugs, including μ-opioids, cannabinoids, and the novel nonopioid analgesic improgan, produce antinociception by actions in the rostral ventromedial medulla (RVM). There they activate pain-inhibiting neurons, termed "OFF-cells," defined by a nociceptive reflex-related pause in activity. Based on recent functional evidence that neuronal P450 epoxygenases are important for the cent...