Algebraic approach to spike-time neural codes in the hippocampus.

Although temporal coding through spike-time patterns has long been of interest in neuroscience, the specific structures that could be useful for spike-time codes remain highly unclear. Here, we introduce an analytical approach, using techniques from discrete mathematics, to study spike-time codes. As an initial example, we focus on the phenomenon of "phase precession" in the rodent hippocampus. During navigation and learning on a physical track, specific cells in a rodent's brain form a highly structured pattern relative to the oscillation of population activity in this region. Studies of phase precession largely focus on its role in precisely ordering spike times for synaptic plasticity, as the role of phase precession in memory formation is well established. Comparatively less attention has been paid to the fact that phase precession represents one of the best candidates for a spike-time neural code. The precise nature of this code remains an open question. Here, we derive an analytical expression for a function mapping points in physical space to complex-valued spikes by representing individual spike times as complex numbers. The properties of this function make explicit a specific relationship between past and future in spike patterns of the hippocampus. Importantly, this mathematical approach generalizes beyond the specific phenomenon studied here, providing a technique to study the neural codes within precise spike-time sequences found during sensory coding and motor behavior. We then introduce a spike-based decoding algorithm, based on this function, that successfully decodes a simulated animal's trajectory using only the animal's initial position and a pattern of spike times. This decoder is robust to noise in spike times and works on a timescale almost an order of magnitude shorter than typically used with decoders that work on average firing rate. These results illustrate the utility of a discrete approach, based on the structure and symmetries in spike patterns across finite sets of cells, to provide insight into the structure and function of neural systems.

Quantification of energy and cost reduction from decreasing dissolved oxygen levels in full-scale water resource recovery facilities.

Aeration systems often lack the efficiency to maintain a desired residual dissolved oxygen (DO) concentration in the tank in part because little consideration is given to the dynamic daily and seasonal loading conditions. Although advanced aeration controllers exist, the majority of plants have DO set points typically based on common practice and literature values rather than site-specific conditions, which can result in DO set points higher than those necessary to meet treatment objectives. DO set point reduction strategies have primarily been proposed through either static or dynamic simulations. In this study, the substantial improvements associated with DO set point reduction are demonstrated at full scale. A yearlong characterization of full-scale aeration dynamics captured the effect of diurnal and seasonal fluctuations on oxygen transfer and energy demand and so facilitated the estimation of the potential savings of DO reduction strategies. Full-scale validation provided direct evidence of DO reduction strategies inducing an overall enhancement of oxygen transfer efficiency along the different bioreactors, while confirming that energy savings as high as 20% were feasible. This study quantifies the influence of oxygen transfer efficiency on operating choices and site-specific conditions (control strategy, loading conditions, and influent flow variability). PRACTITIONER POINTS: We quantified the energy reduction and cost savings associated with a DO reduction in an aeration tank. For each 0.2 mg/L of DO decreased, the average power demand reduction per unit water treated exceeded 17%. Field measurements of dynamic alpha values eliminate the uncertainty in estimating aeration energy and cost savings from DO variations.

Oxygen transfer and plant-wide energy assessment of primary screening in WRRFs.

Primary screening is gaining interest as a method to achieve removal performances comparable to primary clarification while reducing the footprint and increasing operational elasticity. Aeration efficiency indicators in a pilot sequential batch reactor (SBR) and a full scale water resource recovery facility (WRRF) were investigated after the implementation of rotating belt filters/screens (RBF). To compare the impact between screened (350 µm) and nonscreened primary influent, two identical treatment lines were monitored using off-gas and respirometric measurements. The study provides the first result on improved oxygen transfer efficiency due to primary screening. Consistent aeration efficiency improvements of 27% and 20% between screened and nonscreened were obtained at pilot and full scale, respectively. Changes in aeration efficiency and carbon redirection were integrated into a set of models to investigate the primary screening impact on the WRRF energy balance. While the plant-wide assessment for different scenarios improved the energy balance up to 15%, a detailed comparative analysis between various treatment schemes gained insight into the advantages and limitations of the energetic sustainability of primary screening. PRACTITIONER POINTS: Aeration efficiency improved 27% at pilot scale Aeration efficiency improved 20% at full scale. Use of primary screening can improve the energy balance up to 15 Assessment of advantages and limitations of primary screening.