Dynamic causal modelling shows a prominent role of local inhibition in alpha power modulation in higher visual cortex

During resting-state EEG recordings, alpha activity is more prominent over the posterior cortex in eyes-closed (EC) conditions compared to eyes-open (EO). In this study, we characterized the difference in spectra between EO and EC conditions using dynamic causal modelling. Specifically, we investigated the role of intrinsic and extrinsic connectivity-within the visual cortex-in generating EC-EO alpha power differences over posterior electrodes. The primary visual cortex (V1) and the bilateral middle temporal visual areas (V5) were equipped with bidirectional extrinsic connections using a canonical microcircuit. The states of four intrinsically coupled subpopulations-within each occipital source-were also modelled. Using Bayesian model selection, we tested whether modulations of the intrinsic connections in V1, V5 or extrinsic connections (or a combination thereof) provided the best evidence for the data. In addition, using parametric empirical Bayes (PEB), we estimated group averages under the winning model. Bayesian model selection showed that the winning model contained both extrinsic connectivity modulations, as well as intrinsic connectivity modulations in all sources. The PEB analysis revealed increased extrinsic connectivity during EC. Overall, we found a reduction in the inhibitory intrinsic connections during EC. The results suggest that the intrinsic modulations in V5 played the most important role in producing EC-EO alpha differences, suggesting an intrinsic disinhibition in higher order visual cortex, during EC resting state

Making Muscle Elastic: The Structural Basis of Myomesin Stretching

The muscle M-band protein myomesin comprises a 36-nm long filament made of repetitive immunoglobulin–helix modules that can stretch to 2.5-fold this length, demonstrating substantial molecular elasticity

Peripheral contributions to resting state brain dynamics

The correlational structure of brain activity dynamics in the absence of stimuli or behavior is often taken to reveal intrinsic properties of neural function. To test the limits of this assumption, we analyzed peripheral contributions to resting state activity measured by fMRI in unanesthetized, chemically immobilized male rats that emulate human neuroimaging conditions. We find that perturbation of somatosensory input channels modifies correlation strengths that relate somatosensory areas both to one another and to higher-order brain regions, despite the absence of ostensible stimuli or movements. Resting state effects are mediated by the same peripheral and thalamic structures that relay responses to overt sensory stimuli. The impact of basal peripheral input is reduced in a rat model of autism, which displays both lower somatosensory functional connectivity and insensitivity to vibrissa inactivation. These results demonstrate the influence of extrinsic influences on resting state brain phenotypes in health and disease

Solution-Based Structural Analysis of the Decaheme Cytochrome, MtrA, by Small-Angle X-ray Scattering and Analytical Ultracentrifugation

The potential exploitation of metal-reducing bacteria as a means for environmental cleanup or alternative fuel is an exciting prospect; however, the cellular processes that would allow for these applications need to be better understood. MtrA is a periplasmic decaheme c-type cytochrome from Shewanella oneidensis involved in the reduction of extracellular iron oxides and therefore is a critical element in Shewanella ability to engage in extracellular charge transfer. As a relatively small 333-residue protein, the heme content is surprisingly high. MtrA is believed to obtain electrons from the inner membrane-bound quinol oxidoreductase, CymA, and shuttle them across the outer membrane to MtrC, another decaheme cytochrome that directly interacts with insoluble metal oxides. How MtrA is able to perform this task is a question of interest. Here through the use of two solution-based techniques, small-angle X-ray scattering (SAXS) and analytical ultracentrifugation (AUC), we present the first structural analysis of MtrA. Our results establish that between 0.5 and 4 mg/mL, MtrA exists as a monomeric protein that is shaped like an extended molecular “wire” with a maximum protein dimension (D[subscript max]) of 104 Å and a rod-like aspect ratio of 2.2 to 2.5. This study contributes to a greater understanding of how MtrA fulfills its role in the redox processes that must occur before electrons reach the outside of the cell.National Science Foundation (U.S.). (0546323)National Institutes of Health (U.S.) (Grant Number F32GM904862)Howard Hughes Medical Institute. InvestigatorNational Science Foundation (U.S.) (Award DMR- 0936384

Cortical Resonance Frequencies Emerge from Network Size and Connectivity

Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emergent property of the networks that interconnect them. Using a network model of loosely-coupled Wilson-Cowan oscillators to simulate a patch of cortical sheet, we demonstrate that the size of the activated network is inversely related to its resonance frequency. Further analysis of the parameter space indicated that the number of excitatory and inhibitory connections, as well as the average transmission delay between units, determined the resonance frequency. The model predicted that if an activated network within the visual cortex increased in size, the resonance frequency of the network would decrease. We tested this prediction experimentally using the steady-state visual evoked potential where we stimulated the visual cortex with different size stimuli at a range of driving frequencies. We demonstrate that the frequency corresponding to peak steady-state response inversely correlated with the size of the network. We conclude that although individual neurons possess resonance properties, oscillatory activity at the macroscopic level is strongly influenced by network interactions, and that the steady-state response can be used to investigate functional networks