Speech Communication

Contains reports on five research projects.C.J. Lebel FellowshipNational Institutes of Health (Grant 5 T32 NSO7040)National Institutes of Health (Grant 5 R01 NS04332)National Institutes of Health (Grant 5 R01 NS21183)National Institutes of Health (Grant 5 P01 NS13126)National Institutes of Health (Grant 1 PO1-NS23734)National Science Foundation (Grant BNS 8418733)U.S. Navy - Naval Electronic Systems Command (Contract N00039-85-C-0254)U.S. Navy - Naval Electronic Systems Command (Contract N00039-85-C-0341)U.S. Navy - Naval Electronic Systems Command (Contract N00039-85-C-0290)National Institutes of Health (Grant RO1-NS21183), subcontract with Boston UniversityNational Institutes of Health (Grant 1 PO1-NS23734), subcontract with the Massachusetts Eye and Ear Infirmar

Speech Communication

Contains table of contents for Part IV, table of contents for Section 1 and reports on five research projects.Apple Computer, Inc.C.J. Lebel FellowshipNational Institutes of Health (Grant T32-NS07040)National Institutes of Health (Grant R01-NS04332)National Institutes of Health (Grant R01-NS21183)National Institutes of Health (Grant P01-NS23734)U.S. Navy / Naval Electronic Systems Command (Contract N00039-85-C-0254)U.S. Navy - Office of Naval Research (Contract N00014-82-K-0727

Observing capture with a colloidal model membrane channel.

Funder: Royal Society; doi: http://dx.doi.org/10.13039/501100000288Funder: National Physical Laboratory; doi: http://dx.doi.org/10.13039/501100007851Funder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266We use video microscopy to study the full capture process for colloidal particles transported through microfluidic channels by a pressure-driven flow. In particular, we obtain trajectories for particles as they move from the bulk into confinement, using these to map in detail the spatial velocity and concentration fields for a range of different flow velocities. Importantly, by changing the height profiles of our microfluidic devices, we consider systems for which flow profiles in the channel are the same, but flow fields in the reservoir differ with respect to the quasi-2D monolayer of particles. We find that velocity fields and profiles show qualitative agreement with numerical computations of pressure-driven fluid flow through the systems in the absence of particles, implying that in the regimes studied here particle-particle interactions do not strongly perturb the flow. Analysis of the particle flux through the channel indicates that changing the reservoir geometry leads to a change between long-range attraction of the particles to the pore and diffusion-to-capture-like behaviour, with concentration fields that show qualitative changes based on device geometry. Our results not only provide insight into design considerations for microfluidic devices, but also a foundation for experimental elucidation of the concept of a capture radius. This long standing problem plays a key role in transport models for biological channels and nanopore sensors

Resting-State Directional Connectivity and Anxiety and Depression Symptoms in Adult Cannabis Users

Background Anxiety and depression symptoms are common among cannabis users and could be a risk factor for cannabis use (CU) disorder. Thus, it is critical to understand the neuronal circuits underlying the associations between CU and these symptoms. Alterations in resting-state functional connectivity within and/or between the default mode network and salience network have been reported in CU, anxiety, and depressive disorders and thus could be a mechanism underlying the associations between CU disorder and anxiety/depression symptoms. Methods Using resting-state functional magnetic resonance imaging, effective connectivities (ECs) among 9 major nodes from the default mode network and salience network were measured using dynamic causal modeling in 2 datasets: the Human Connectome Project (28 CU participants and 28 matched non–drug-using control participants) and a local CU study (21 CU participants and 21 matched non–drug-using control participants) in separate and parallel analyses. Results Relative to the control participants, right amygdala to left amygdala, anterior cingulate cortex to left amygdala, and medial prefrontal cortex to right insula ECs were greater, and left insula to left amygdala EC was smaller in the CU group. Each of these ECs showed a reliable linear relationship with at least one of the anxiety/depression measures. Most findings on the right amygdala to left amygdala EC were common to both datasets. Conclusions Right amygdala to left amygdala and anterior cingulate cortex to left amygdala ECs may be related to the close associations between CU and anxiety/depression symptoms. The findings on the medial prefrontal cortex to right insula and left insula to left amygdala ECs may reflect a compensatory mechanism

Resting-state directional connectivity and anxiety and depression symptoms in adult cannabis users

BACKGROUND: Anxiety and depression symptoms are common among cannabis users and could be a risk factor for cannabis use (CU) disorder. Thus, it is critical to understand the neuronal circuits underlying the associations between CU and these symptoms. Alterations in resting-state functional connectivity within and/or between the default mode network and salience network have been reported in CU, anxiety, and depressive disorders and thus could be a mechanism underlying the associations between CU disorder and anxiety/depression symptoms. METHODS: Using resting-state functional magnetic resonance imaging, effective connectivities (ECs) among 9 major nodes from the default mode network and salience network were measured using dynamic causal modeling in 2 datasets: the Human Connectome Project (28 CU participants and 28 matched non-drug-using control participants) and a local CU study (21 CU participants and 21 matched non-drug-using control participants) in separate and parallel analyses. RESULTS: Relative to the control participants, right amygdala to left amygdala, anterior cingulate cortex to left amygdala, and medial prefrontal cortex to right insula ECs were greater, and left insula to left amygdala EC was smaller in the CU group. Each of these ECs showed a reliable linear relationship with at least one of the anxiety/depression measures. Most findings on the right amygdala to left amygdala EC were common to both datasets. CONCLUSIONS: Right amygdala to left amygdala and anterior cingulate cortex to left amygdala ECs may be related to the close associations between CU and anxiety/depression symptoms. The findings on the medial prefrontal cortex to right insula and left insula to left amygdala ECs may reflect a compensatory mechanism