A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation of parameters in the diffusion tensor model, and also to a simple partial volume model of diffusion. In both cases the parameters of interest include parameters defining local fiber direction. A technique is then presented for using these density functions to estimate global connectivity (i.e., the probability of the existence of a connection through the data field, between any two distant points), allowing for the quantification of belief in tractography results. This technique is then applied to the estimation of the cortical connectivity of the human thalamus. The resulting connectivity distributions correspond well with predictions from invasive tracer methods in nonhuman primate. Key words: diffusion-weighted MRI; probability density functions Uncertainty and its representation have an important role to play in any situation where the goal is to infer useful information from noisy data. In diffusion-weighted MRI (DW-MRI) scientists attempt to infer information about, for example, diffusion anisotropy or underlying fiber tract direction, by fitting models of the diffusion and measurement processes to DW-MRI data (e.g., Refs. 1,2). In this scheme there is uncertainty caused both by the noise and artifacts present in any MR scan, but also by the incomplete modeling of the diffusion signal. That is, the true diffusion signal is more complicated than we choose to model. This additional complexity in the diffusion signal appears as residuals when we fit a simple model to the data, causing additional uncertainty in the model parameters. All of the uncertainty in these parameters may be represented in the form of probability density functions (pdfs). This article is essentially divided into two parts, dealing separately with uncertainty at the local and global levels. In the first part, we describe a technique for estimating the pdfs on all parameters in any local model of diffusion. We will show results derived from two simple models of the diffusion process within a voxel: The diffusion tensor model which assumes a local 3D Gaussian diffusion profile, and a simple partial volume model of local diffusion, which assumes that a fraction of diffusion is along a single dominant direction, and that the remainder is isotropic. We will then make suggestions for the extension to more complete models of the diffusion process which are able to account for one, or more, distribution of fiber directions within the voxel. In all of these models, the use of Bayesian techniques allows for the application of prior constraints on parameters in the model where such constraints are sensible. For example, in the fitting of the diffusion tensor model, the eigenvalues of the diffusion tensor are constrained to be positive.The distributions on parameters in a diffusion model are of great significance when making inference on the basis of these param...

The experience of pain is subjectively different from the fear and anxiety caused by threats of pain. Functional magnetic resonance imaging in healthy humans was applied to dissociate neural activation patterns associated with acute pain and its anticipation. Expectation of pain activated sites within the medial frontal lobe, insular cortex, and cerebellum distinct from, but close to, locations mediating pain experience itself. Anticipation of pain can in its own right cause mood changes and behavioral adaptations that exacerbate the suffering experienced by chronic pain patients. Selective manipulations of activity at these sites may offer therapeutic possibilities for treating chronic pain.

Current clinical and experimental literature strongly supports the phenomenon of reduced pain perception whilst attention is distracted away from noxious stimuli. This study used functional MRI to elucidate the underlying neural systems and mechanisms involved. An analogue of the Stroop task, the counting Stroop, was used as a cognitive distraction task whilst subjects received intermittent painful thermal stimuli. Pain intensity scores were significantly reduced when subjects took part in the more cognitively demanding interference task of the counting Stroop than in the less demanding neutral task. When subjects were distracted during painful stimulation, brain areas associated with the affective division of the anterior cingulate cortex (ACC) and orbitofrontal regions showed increased activation. In contrast, many areas of the pain matrix (i.e. thalamus, insula, cognitive division of the ACC) displayed reduced activation, supporting the behavioural results of reduced pain perception.

It is common clinical experience that anxiety about pain can exacerbate the pain sensation. Using event-related functional magnetic resonance imaging (FMRI), we compared activation responses to noxious thermal stimulation while perceived pain intensity was manipulated by changes in either physical intensity or induced anxiety. One visual signal, which reliably predicted noxious stimulation of moderate intensity, came to evoke low anxiety about the impending pain. Another visual signal was followed by the same, moderate-intensity stimulation on most of the trials, but occasionally by discriminably stronger noxious stimuli, and came to evoke higher anxiety. We found that the entorhinal cortex of the hippocampal formation responded differentially to identical noxious stimuli, dependent on whether the perceived pain intensity was enhanced by pain-relevant anxiety. During this emotional pain modulation, entorhinal responses predicted activity in closely connected, affective (perigenual cingulate), and intensity coding (midinsula) areas. Our finding suggests that accurate preparatory information during medical and dental procedures alleviates pain by disengaging the hippocampus. It supports the proposal that during anxiety, the hippocampal formation amplifies aversive events to prime behavioral responses that are adaptive to the worst possible outcome.

Pain is an unpleasant sensory and emotional experience usually triggered by stimulation of peripheral nerves and often associated with actual or potential tissue damage. It is well known that pain perception for patients and normal subjects can be modulated by psychological factors, such as attention, stress, and arousal. Our understanding of how this modulation occurs at a neuroanatomical level is poor. Here we neuroanatomically defined a key area in the network of brain regions active in response to pain that is modulated by attention to the painful stimulus. High-resolution functional magnetic resonance imaging was used to define brain activation to painful heat stimulation applied to the hand of nine normal subjects within the periaqueductal gray region. Subjects were asked to either focus on or distract themselves from the painful stimuli, which were cued using colored lights. During the distraction condition, subjects rated the pain intensity as significantly lower compared with when they attended to the stimulus. Activation in the periaqueductal gray was significantly increased during the distraction condition, and the total increase in activation was predictive of changes in perceived intensity. This provides direct evidence supporting the notion that the periaqueductal gray is a site for higher cortical control of pain modulation in humans.

Functional magnetic resonance image (fMRI) experiments rely on the ability to detect subtle signal changes in magnetic resonance image time series. Any areas of signal change that correlate with the neurological stimulus can then be identified and compared with a corresponding high-resolution anatomical scan. This report reviews some of the several artefacts that are frequently present in fMRI data, degrading their quality and hence their interpretation. In particular, the effects of magnetic field inhomogeneities are described, both on echo planar imaging (EPI) data and on spiral imaging data. The modulation of these distortions as the subject moves in the magnet is described. The effects of gradient coil nonlinearities and EPI ghost correction schemes are also discussed.

Although there has been much investigation of brain pathways involved in pain, little is known about the brain mechanisms involved in processing somatosensory stimuli which feel pleasant. Employing fMRI it was shown that pleasant touch to the hand with velvet produced stronger activation of the orbitofrontal cortex than affectively neutral touch of the hand with wood. In contrast, the affectively neutral but more intense touch produced more activation of the primary somatosensory cortex than the pleasant stimulus. This indicates that part of the orbitofrontal cortex is concerned with representing the positively affective aspects of somatosensory stimuli, and in further experiments it was shown that this orbitofrontal area is different from that activated by taste and smell. The finding that three different primary or unlearned types of reinforcer (touch, taste, and smell) are represented in the orbitofrontal cortex helps to provide a firm foundation for understanding the neural basis of emotions, which can be understood in terms of states elicited by stimuli which are rewarding or punishing.

Limited understanding of infant pain has led to its lack of recognition in clinical practice. While the network of brain regions that encode the affective and sensory aspects of adult pain are well described, the brain structures involved in infant nociceptive processing are less well known, meaning little can be inferred about the nature of the infant pain experience. Using fMRI we identified the network of brain regions that are active following acute noxious stimulation in newborn infants, and compared the activity to that observed in adults. Significant infant brain activity was observed in 18 of the 20 active adult brain regions but not in the infant amygdala or orbitofrontal cortex. Brain regions that encode sensory and affective components of pain are active in infants, suggesting that the infant pain experience closely resembles that seen in adults. This highlights the importance of developing effective pain management strategies in this vulnerable population.DOI: http://dx.doi.org/10.7554/eLife.06356.001