Alertness fluctuations when performing a task modulate cortical evoked responses to transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) has been widely used in human cognitive neuroscience to examine the causal role of distinct cortical areas in perceptual, cognitive and motor functions. However, it is widely acknowledged that the effects of focal cortical stimulation can vary substantially between participants and even from trial to trial within individuals. Recent work from resting state functional magnetic resonance imaging (fMRI) studies has suggested that spontaneous fluctuations in alertness over a testing session can modulate the neural dynamics of cortical processing, even when participants remain awake and responsive to the task at hand. Here we investigated the extent to which spontaneous fluctuations in alertness during wake-to-sleep transition can account for the variability in neurophysiological responses to TMS. We combined single-pulse TMS with neural recording via electroencephalography (EEG) to quantify changes in motor and cortical reactivity with fluctuating levels of alertness defined objectively on the basis of ongoing brain activity. We observed rapid, non-linear changes in TMS-evoked responses with decreasing levels of alertness, even while participants remained responsive in the behavioural task. Specifically, we found that the amplitude of motor evoked potentials peaked during periods of EEG flattening, whereas TMS-evoked potentials increased and remained stable during EEG flattening and the subsequent occurrence of theta ripples that indicate the onset of NREM stage 1 sleep. Our findings suggest a rapid and complex reorganization of active neural networks in response to spontaneous fluctuations of alertness over relatively short periods of behavioural testing during wake-to-sleep transition

Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions.

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies

Detecting Awareness in the Vegetative State: Electroencephalographic Evidence for Attempted Movements to Command

Patients in the Vegetative State (VS) do not produce overt motor behavior to command and are therefore considered to be unaware of themselves and of their environments. However, we recently showed that high-density electroencephalography (EEG) can be used to detect covert command-following in some VS patients. Due to its portability and inexpensiveness, EEG assessments of awareness have the potential to contribute to a standard clinical protocol, thus improving diagnostic accuracy. However, this technique requires refinement and optimization if it is to be used widely as a clinical tool. We asked a patient who had been repeatedly diagnosed as VS for 12-years to try to move his left and right hands, between periods of rest, while EEG was recorded from four scalp electrodes. We identified appropriate and statistically reliable modulations of sensorimotor beta rhythms following commands to try to move, which could be significantly classified at a single-trial level. These reliable effects indicate that the patient attempted to follow the commands, and was therefore aware, but was unable to execute an overtly discernable action. The cognitive demands of this novel task are lower than those used previously and, crucially, allow for awareness to be determined on the basis of a 20-minute EEG recording made with only four electrodes. This approach makes EEG assessments of awareness clinically viable, and therefore has potential for inclusion in a standard assessment of awareness in the VS

Genome-Wide Association Data Reveal a Global Map of Genetic Interactions among Protein Complexes

This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex