Bayesian inversion of synthetic AVO data to assess fluid and shale content in sand-shale media

Reservoir characterization of sand-shale sequences has always challenged geoscientists due to the presence of anisotropy in the form of shale lenses or shale layers. Water saturation and volume of shale are among the fundamental reservoir properties of interest for sand-shale intervals, and relate to the amount of fluid content and accumulating potentials of such media. This paper suggests an integrated workflow using synthetic data for the characterization of shaley-sand media based on anisotropic rock physics (T-matrix approximation) and seismic reflectivity modelling. A Bayesian inversion scheme for estimating reservoir parameters from amplitude vs. offset (AVO) data was used to obtain the information about uncertainties as well as their most likely values. The results from our workflow give reliable estimates of water saturation from AVO data at small uncertainties, provided background sand porosity values and isotropic overburden properties are known. For volume of shale, the proposed workflow provides reasonable estimates even when larger uncertainties are present in AVO data

Selective Attention Increases Both Gain and Feature Selectivity of the Human Auditory Cortex

Background. An experienced car mechanic can often deduce what’s wrong with a car by carefully listening to the sound of the ailing engine, despite the presence of multiple sources of noise. Indeed, the ability to select task-relevant sounds for awareness, whilst ignoring irrelevant ones, constitutes one of the most fundamental of human faculties, but the underlying neural mechanisms have remained elusive. While most of the literature explains the neural basis of selective attention by means of an increase in neural gain, a number of papers propose enhancement in neural selectivity as an alternative or a complementary mechanism. Methodology/Principal Findings. Here, to address the question whether pure gain increase alone can explain auditory selective attention in humans, we quantified the auditory cortex frequency selectivity in 20 healthy subjects by masking 1000-Hz tones by continuous noise masker with parametrically varying frequency notches around the tone frequency (i.e., a notched-noise masker). The task of the subjects was, in different conditions, to selectively attend to either occasionally occurring slight increments in tone frequency (1020 Hz), tones of slightly longer duration, or ignore the sounds. In line with previous studies, in the ignore condition, the global field power (GFP) of event-related brain responses at 100 ms from the stimulus onset to the 1000-Hz tones was suppressed as a function of the narrowing of the notch width. During the selective attention conditions, the suppressant effect of the noise notch width on GFP was decreased, but as a function significantly different from a multiplicative one expected on the basis of simple gain model of selective attention. Conclusions/Significance. Our results suggest that auditory selective attention in humans cannot be explained by a gai

Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments

Deficient NRG1-ERBB signaling alters social approach: relevance to genetic mouse models of schizophrenia

Growth factor Neuregulin 1 (NRG1) plays an essential role in development and organization of the cerebral cortex. NRG1 and its receptors, ERBB3 and ERBB4, have been implicated in genetic susceptibility for schizophrenia. Disease symptoms include asociality and altered social interaction. To investigate the role of NRG1-ERBB signaling in social behavior, mice heterozygous for an Nrg1 null allele (Nrg1+/−), and mice with conditional ablation of Erbb3 or Erbb4 in the central nervous system, were evaluated for sociability and social novelty preference in a three-chambered choice task. Results showed that deficiencies in NRG1 or ERBB3 significantly enhanced sociability. All of the mutant groups demonstrated a lack of social novelty preference, in contrast to their respective wild-type controls. Effects of NRG1, ERBB3, or ERBB4 deficiency on social behavior could not be attributed to general changes in anxiety-like behavior, activity, or loss of olfactory ability. Nrg1+/− pups did not exhibit changes in isolation-induced ultrasonic vocalizations, a measure of emotional reactivity. Overall, these findings provide evidence that social behavior is mediated by NRG1-ERBB signaling

The Natural Statistics of Audiovisual Speech

Humans, like other animals, are exposed to a continuous stream of signals, which are dynamic, multimodal, extended, and time varying in nature. This complex input space must be transduced and sampled by our sensory systems and transmitted to the brain where it can guide the selection of appropriate actions. To simplify this process, it's been suggested that the brain exploits statistical regularities in the stimulus space. Tests of this idea have largely been confined to unimodal signals and natural scenes. One important class of multisensory signals for which a quantitative input space characterization is unavailable is human speech. We do not understand what signals our brain has to actively piece together from an audiovisual speech stream to arrive at a percept versus what is already embedded in the signal structure of the stream itself. In essence, we do not have a clear understanding of the natural statistics of audiovisual speech. In the present study, we identified the following major statistical features of audiovisual speech. First, we observed robust correlations and close temporal correspondence between the area of the mouth opening and the acoustic envelope. Second, we found the strongest correlation between the area of the mouth opening and vocal tract resonances. Third, we observed that both area of the mouth opening and the voice envelope are temporally modulated in the 2–7 Hz frequency range. Finally, we show that the timing of mouth movements relative to the onset of the voice is consistently between 100 and 300 ms. We interpret these data in the context of recent neural theories of speech which suggest that speech communication is a reciprocally coupled, multisensory event, whereby the outputs of the signaler are matched to the neural processes of the receiver

Drug discovery in ophthalmology: past success, present challenges, and future opportunities

BACKGROUND: Drug discovery has undergone major transformations in the last century, progressing from the recognition and refinement of natural products with therapeutic benefit, to the systematic screening of molecular libraries on whole organisms or cell lines and more recently to a more target-based approach driven by greater knowledge of the physiological and pathological pathways involved. Despite this evolution increasing challenges within the drug discovery industry are causing escalating rates of failure of development pipelines. DISCUSSION: We review the challenges facing the drug discovery industry, and discuss what attempts are being made to increase the productivity of drug development, including a refocusing on the study of the basic biology of the disease, and an embracing of the concept of ‘translational research’. We consider what ophthalmic drug discovery can learn from the sector in general and discuss strategies to overcome the present limitations. This includes advances in the understanding of the pathogenesis of disease; improvements in animal models of human disease; improvements in ophthalmic drug delivery and attempts at patient stratification within clinical trials. SUMMARY: As we look to the future, we argue that investment in ophthalmic drug development must continue to cover the whole translational spectrum (from ‘bench to bedside and back again’) with recognition that both biological discovery and clinical understanding will drive drug discovery, providing safe and effective therapies for ocular disease

Advancing schizophrenia drug discovery : optimizing rodent models to bridge the translational gap

Although our knowledge of the pathophysiology of schizophrenia has increased, treatments for this devastating illness remain inadequate. Here, we critically assess rodent models and behavioural end points used in schizophrenia drug discovery and discuss why these have not led to improved treatments. We provide a perspective on how new models, based on recent advances in the understanding of the genetics and neural circuitry underlying schizophrenia, can bridge the translational gap and lead to the development of more effective drugs. We conclude that previous serendipitous approaches should be replaced with rational strategies for drug discovery in integrated preclinical and clinical programmes. Validation of drug targets in disease-based models that are integrated with translationally relevant end point assessments will reduce the current attrition rate in schizophrenia drug discovery and ultimately lead to therapies that tackle the disease process

Auditory event-related potentials

Auditory event related potentials are electric potentials (AERP, AEP) and magnetic fields (AEF) generated by the synchronous activity of large neural populations in the brain, which are time-locked to some actual or expected sound event