Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions.

In this work, we introduce new phenomenological neuronal models (eLIF and mAdExp) that account for energy supply and demand in the cell as well as the inactivation of spike generation how these interact with subthreshold and spiking dynamics. Including these constraints, the new models reproduce a broad range of biologically-relevant behaviors that are identified to be crucial in many neurological disorders, but were not captured by commonly used phenomenological models. Because of their low dimensionality eLIF and mAdExp open the possibility of future large-scale simulations for more realistic studies of brain circuits involved in neuronal disorders. The new models enable both more accurate modeling and the possibility to study energy-associated disorders over the whole time-course of disease progression instead of only comparing the initially healthy status with the final diseased state. These models, therefore, provide new theoretical and computational methods to assess the opportunities of early diagnostics and the potential of energy-centered approaches to improve therapies.

Fate of nitrogen in French human excreta: Current waste and agronomic opportunities for the future.

Nitrogen (N) is essential for plant growth and protein synthesis but global reactive N losses, mainly from food systems, induce strong environmental impacts. N losses after human excretion are often overlooked because, in Western societies, they partly occur as inert N2, following denitrification in wastewater treatment plants (WWTP), and losses in waters are often small compared to diffuse agricultural emissions. Yet N from human excretions could be used for crop fertilization, potentially with very high recycling rates via source separation. In this study we use unique operational data from the ∼20,000 French WWTPs to produce a N mass-balance of excretions in the French sanitation system. Even though 75 % of WWTPs' sludge is spread on crops, only 10 % of the excreted N is recycled and 50 % of N is lost to the atmosphere, mainly through WWTP nitrification-denitrification. The remaining 40 % ends up in water or in diffuse losses in the ground, of which about half is lost outside of the WWTPs' discharge system, through sewers storm water and individual autonomous systems. While WWTPs removal efficiency increased in the 2000s, it has been followed by a decade of stagnation, reaching 70 % at the national level. This national average hides regional discrepancies, from 60 to 85 % in the 6 French water agencies basins. These differences closely correlate with the classification as "N sensitive areas" and is mainly due to large WWTPs which handle most of the N load. Recycling all N in excretions could supply 10 % of domestic protein consumption in the current French food system, and up to 30 % if it is prioritized towards crop production for human consumption. Redesigning the food system (decrease of nutrient losses, more plant-based diets) could further increase this contribution.

Rich dynamics and functional organization on topographically designed neuronal networks in vitro.

Neuronal cultures are a prominent experimental tool to understand complex functional organization in neuronal assemblies. However, neurons grown on flat surfaces exhibit a strongly coherent bursting behavior with limited functionality. To approach the functional richness of naturally formed neuronal circuits, here we studied neuronal networks grown on polydimethylsiloxane (PDMS) topographical patterns shaped as either parallel tracks or square valleys. We followed the evolution of spontaneous activity in these cultures along 20 days in vitro using fluorescence calcium imaging. The networks were characterized by rich spatiotemporal activity patterns that comprised from small regions of the culture to its whole extent. Effective connectivity analysis revealed the emergence of spatially compact functional modules that were associated with both the underpinned topographical features and predominant spatiotemporal activity fronts. Our results show the capacity of spatial constraints to mold activity and functional organization, bringing new opportunities to comprehend the structure-function relationship in living neuronal circuits.

Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons.

Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show here that a sufficient condition for this network bursting is the presence of an excitatory population of oscillatory neurons which displays spike-driven adaptation. We provide an analytic model to analyze network bursts generated by coupled adaptive exponential integrate-and-fire neurons. We show that, for strong synaptic coupling, intrinsically tonic spiking neurons evolve to reach a synchronized intermittent bursting state. The presence of inhibitory neurons or plastic synapses can then modulate this dynamics in many ways but is not necessary for its appearance. Thanks to a simple self-consistent equation, our model gives an intuitive and semi-quantitative tool to understand the bursting behavior. Furthermore, it suggests that after-hyperpolarization currents are sufficient to explain bursting termination. Through a thorough mapping between the theoretical parameters and ion-channel properties, we discuss the biological mechanisms that could be involved and the relevance of the explored parameter-space. Such an insight enables us to propose experimentally-testable predictions regarding how blocking fast, medium or slow after-hyperpolarization channels would affect the firing rate and burst duration, as well as the interburst interval.