A Genetic Screen for Dihydropyridine (DHP)-Resistant Worms Reveals New Residues Required for DHP-Blockage of Mammalian Calcium Channels

Dihydropyridines (DHPs) are L-type calcium channel (Cav1) blockers prescribed to treat several diseases including hypertension. Cav1 channels normally exist in three states: a resting closed state, an open state that is triggered by membrane depolarization, followed by a non-conducting inactivated state that is triggered by the influx of calcium ions, and a rapid change in voltage. DHP binding is thought to alter the conformation of the channel, possibly by engaging a mechanism similar to voltage dependent inactivation, and locking a calcium ion in the pore, thereby blocking channel conductance. As a Cav1 channel crystal structure is lacking, the current model of DHP action has largely been achieved by investigating the role of candidate Cav1 residues in mediating DHP-sensitivity. To better understand DHP-block and identify additional Cav1 residues important for DHP-sensitivity, we screened 440,000 randomly mutated Caenorhabditis elegans genomes for worms resistant to DHP-induced growth defects. We identified 30 missense mutations in the worm Cav1 pore-forming (α1) subunit, including eleven in conserved residues known to be necessary for DHP-binding. The remaining polymorphisms are in eight conserved residues not previously associated with DHP-sensitivity. Intriguingly, all of the worm mutants that we analyzed phenotypically exhibited increased channel activity. We also created orthologous mutations in the rat α1C subunit and examined the DHP-block of current through the mutant channels in culture. Six of the seven mutant channels examined either decreased the DHP-sensitivity of the channel and/or exhibited significant residual current at DHP concentrations sufficient to block wild-type channels. Our results further support the idea that DHP-block is intimately associated with voltage dependent inactivation and underscores the utility of C. elegans as a screening tool to identify residues important for DHP interaction with mammalian Cav1 channels

Applications of Granger Causality to Magnetoencephalography Research, Short Trial Time Series Analysis, and the Study of Decision Making

Causality analysis is an approach to time series analysis that is being used increasingly to investigate neuroimaging data. The reason for its popularity is the useful perspective it provides in describing the ordered operations of various brain regions using indirectly and passively measured neurophysiological signals. Although there are numerous frameworks with which causality analysis can be performed, one concept in particular – termed Granger causality (GC) – is receiving much of the attention because of its ease of implementation and interpretability. GC makes use of the fact that a predictive relationship between the history of one signal and the future of another signal provides evidence for there being a causal relationship between the two signals, and as a result, the physical events underlying those signals. If such a relationship can be established across neural time series, causal dependencies between neural pathways can be inferred and their contribution to brain function can be studied. Several analysis frameworks exist for applying GC to neurophysiological questions but many of these frameworks have deficiencies that impede their application to large and highly multivariate neuroimaging datasets. To address some of these concerns, this study develops the theory and methods for a novel neural time series classification procedure – referred to as GC classification – based on concepts in GC analysis. Validation of this method in neuroimaging research is provided by showing that it can be applied to heterogeneous datasets, that it makes use of many parallel sources of information about causal relationships, and that it can be adapted to different types of preprocessing steps to uncover causal relationships in multivariate neural time series data. Application of this analysis method to human behavioural MEG data revealed that, during a cued button-pressing task, distinct causal relationships exist between sensory cortices and their downstream targets preceding the initiation of actions that differ by whether or not they were the result of a decision being made. These results provide evidence that the GC classification procedure is a useful and robust technique for studying causal relationships in neurophysiological time series.Ph

Distinct dynamical patterns that distinguish willed and forced actions

The neural pathways for generating willed actions have been increasingly investigated since the famous pioneering work by Benjamin Libet on the nature of free will. To better understand what differentiates the brain states underlying willed and forced behaviours, we performed a study of chosen and forced actions over a binary choice scenario. Magnetoencephalography recordings were obtained from six subjects during a simple task in which the subject presses a button with the left or right finger in response to a cue that either (1) specifies the finger with which the button should be pressed or (2) instructs the subject to press a button with a finger of their own choosing. Three independent analyses were performed to investigate the dynamical patterns of neural activity supporting willed and forced behaviours during the preparatory period preceding a button press. Each analysis offered similar findings in the temporal and spatial domains and in particular, a high accuracy in the classification of single trials was obtained around 200 ms after cue presentation with an overall average of 82%. During this period, the majority of the discriminatory power comes from differential neural processes observed bilaterally in the parietal lobes, as well as some differences in occipital and temporal lobes, suggesting a contribution of these regions to willed and forced behaviours