Optimizing cognitive neuroscience experiments for separating event- related fMRI BOLD responses in non-randomized alternating designs.

Functional magnetic resonance imaging (fMRI) has revolutionized human brain research. But there exists a fundamental mismatch between the rapid time course of neural events and the sluggish nature of the fMRI blood oxygen level-dependent (BOLD) signal, which presents special challenges for cognitive neuroscience research. This limitation in the temporal resolution of fMRI puts constraints on the information about brain function that can be obtained with fMRI and also presents methodological challenges. Most notably, when using fMRI to measure neural events occurring closely in time, the BOLD signals may temporally overlap one another. This overlap problem may be exacerbated in complex experimental paradigms (stimuli and tasks) that are designed to manipulate and isolate specific cognitive-neural processes involved in perception, cognition, and action. Optimization strategies to deconvolve overlapping BOLD signals have proven effective in providing separate estimates of BOLD signals from temporally overlapping brain activity, but there remains reduced efficacy of such approaches in many cases. For example, when stimulus events necessarily follow a non-random order, like in trial-by-trial cued attention or working memory paradigms. Our goal is to provide guidance to improve the efficiency with which the underlying responses evoked by one event type can be detected, estimated, and distinguished from other events in designs common in cognitive neuroscience research. We pursue this goal using simulations that model the nonlinear and transient properties of fMRI signals, and which use more realistic models of noise. Our simulations manipulated: (i) Inter-Stimulus-Interval (ISI), (ii) proportion of so-called null events, and (iii) nonlinearities in the BOLD signal due to both cognitive and design parameters. We offer a theoretical framework along with a python toolbox called deconvolve to provide guidance on the optimal design parameters that will be of particular utility when using non-random, alternating event sequences in experimental designs. In addition, though, we also highlight the challenges and limitations in simultaneously optimizing both detection and estimation efficiency of BOLD signals in these common, but complex, cognitive neuroscience designs.

The effects of magnesium and ammonium additions on phosphate recovery from greenhouse wastewater.

Phosphorus recovery from greenhouse wastewater, using precipitation-crystallization, was conducted under three levels of calcium concentration, 304 mg/L (7.6 mmol/L), 384 mg/L (9.6 mmol/L), and 480 mg/L (12 mmol/L), and also with additions of ammonium and magnesium into the wastewater. Jar test results confirmed high phosphate removal, with more than 90% of the removal achieved with a pH as low as 7.7. Under the low calcium concentration, ammonium addition affected the chemical reactions at pH lower than 8.0, where struvite was produced; when the pH was raised to 8.8, other calcium compounds dominated the precipitation. Under the medium calcium concentration, ammonium and magnesium addition helped struvite precipitation in the low pH range. Hydroxyapatite (HAP) was the main product. Under the high calcium concentration, ammonium addition showed no effects on the precipitation.

Phosphate recovery from greenhouse wastewater.

A study was conducted to investigate the suitability of phosphate recovery from greenhouse wastewaters by using precipitation/crystallization process. More than 90% of the phosphate could be removed from the greenhouse wastewater. Various calcium phosphate salts were obtained in the process; hydroxyapatite [Ca5(PO4)3OH] could be the main product from the precipitates. Phosphate removal was affected by the presence of magnesium ion in wastewaters. An increase of magnesium concentrations in wastewaters decreased phosphate removal rates. The chemical contents of precipitates in terms of calcium, magnesium and phosphate were affected by calcium to magnesium molar ratio. Higher calcium contents were obtained at wastewaters with high calcium to magnesium molar ratio. An addition of magnesium did not affect the potassium contents in the precipitates. K-struvite, MgKPO4 x 6H2O, was not the major product in the precipitate, even with addition of a large quantity of magnesium.