The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.

The imaging conversion is complicated by the variation of images. An understanding of the conversion basics can be helpful for identifying the source of the error. Here we provide users with simple methods for detecting and correcting problems. This also serves as an overview for developers who wish to either develop their own tools or adapt the open source tools created by the authors.

In vivo whole-cell recordings revealed that during repeated stimulation, synaptic responses to deflection of facial whiskers rapidly adapt. Extracellular recordings in the somatosensory thalamus revealed that part of the adaptation occurs subcortically, but because cortical adaptation is stronger and recovers more slowly, cortical mechanisms must also contribute. Trains of sensory stimuli that produce profound sensory adaptation did not alter intrinsic membrane properties, including resting membrane potential, input resistance, and current-evoked firing. Synaptic input evoked via intracortical stimulation was also unchanged; however, synaptic input from the somatosensory thalamus was depressed by sensory stimulation, and this depression recovered with a time course matching that of the recovery of sensory responsiveness. These data strongly suggest that synaptic depression of thalamic input to the cortex contributes to the dynamic regulation of neuronal sensitivity during rapid changes in sensory input.

Transcripts regulated by the yeast nonsense-mediated and 5' to 3' mRNA decay pathways were identified by expression profiling of wild-type, upf1Delta, nmd2Delta, upf3Delta, dcp1Delta, and xrn1Delta cells. This analysis revealed that inactivation of Upf1p, Nmd2p, or Upf3p has identical effects on global RNA accumulation; inactivation of Dcp1p or Xrn1p exhibits both common and unique effects on global RNA accumulation but causes upregulation of only a small fraction of transcripts; and the majority of transcripts upregulated in upf/nmd strains are also upregulated to similar extents in dcp1Delta and xrn1Delta strains. Our results define the core transcripts regulated by NMD, identify several novel structural classes of NMD substrates, demonstrate that nonsense-containing mRNAs are primarily degraded by the 5' to 3' decay pathway even in the absence of functional NMD, and indicate that 3' to 5' decay, not 5' to 3' decay, may be the major mRNA decay activity in yeast cells.

The Iowa Gambling Task (IGT) is a sensitive test for the detection of decision-making impairments in several neurologic and psychiatric populations. Very few studies have employed the IGT in fMRI investigations, in part, because the task is cognitively complex. Here we report a method for exploring brain activity using fMRI during performance of the IGT. Decision-making during the IGT was associated with activity in several brain regions in a group of healthy individuals. The activated regions were consistent with the neural circuitry hypothesized to underlie somatic marker activation and decision-making. Specifically, a neural circuitry involving the dorsolateral prefrontal cortex (for working memory), the insula and posterior cingulate cortex (for representations of emotional states), the mesial orbitofrontal and ventromedial prefrontal cortex (for coupling the two previous processes), the ventral striatum and anterior cingulate/SMA (supplementary motor area) for implementing behavioral decisions was engaged. These results have implications for using the IGT to study abnormal mechanisms of decision making in a variety of clinical populations.