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Determining the magnitude and origins of nitrogen (N) deposition in the open ocean is vital for understanding how anthropogenic activities influence oceanic biogeochemical cycles. Excess N in the North Pacific Ocean(NPO) is suggested to reflect recent anthropogenic atmospheric deposition from the Asian continent, changes in nutrient dynamics due to marine N-fixation, and/or lateral transport of nutrients. We investigate the impact of anthropogenic and marine sources on reactive N deposition in the NPO, with a focus on ammonium (NH4+), an important bioavailable nutrient, using aerosol samples (n =108) collected off the coast of China (Changdao Island). This study site is used as a proxy for continental emissions that can be exported and subsequently deposited to the ocean. The NH4+concentration of aerosol samples varied seasonally (p < 0.05), with a higher average value in winter (2.8 ±1.1 μg/m3) and spring (1.9 ±0.8 μg/m3) compared to autumn (0.7 ±0.6 μg/m3) and summer (1.4 ±0.4 μg/m3). The isotopic composition of aerosol NH4+ varied seasonally, with higher averages in spring (13.3 ±7.9‰) and summer (15.6 ±6.2‰) compared to autumn (3.2 ±2.5 ‰) and winter (3.8 ±11.4‰). These seasonal patterns in the isotopic composition of NH4+ are investigated based on correlations of aerosol chemical species, seasonal shifts in transport patterns, partitioning of ammonia/ammonium between the gas and particle phase, and continental versus marine sources of ammonia. We find that anthropogenic activities, mainly agricultural practices (e.g., volatilization, fertilizer, animal husbandry), are the primary sources of NH4+ deposited to the NPO. 

Abstract Understanding the brain requires understanding neurons’ functional responses to the circuit architecture shaping them. Here we introduce the MICrONS functional connectomics dataset with dense calcium imaging of around 75,000 neurons in primary visual cortex (VISp) and higher visual areas (VISrl, VISal and VISlm) in an awake mouse that is viewing natural and synthetic stimuli. These data are co-registered with an electron microscopy reconstruction containing more than 200,000 cells and 0.5 billion synapses. Proofreading of a subset of neurons yielded reconstructions that include complete dendritic trees as well the local and inter-areal axonal projections that map up to thousands of cell-to-cell connections per neuron. Released as an open-access resource, this dataset includes the tools for data retrieval and analysis^1,2. Accompanying studies describe its use for comprehensive characterization of cell types^3–6, a synaptic level connectivity diagram of a cortical column⁴, and uncovering cell-type-specific inhibitory connectivity that can be linked to gene expression data^4,7. Functionally, we identify new computational principles of how information is integrated across visual space⁸, characterize novel types of neuronal invariances⁹and bring structure and function together to uncover a general principle for connectivity between excitatory neurons within and across areas^10,11. 

Summary The neocortex is one of the most critical structures that makes us human, and it is involved in a variety of cognitive functions from perception to sensory integration and motor control. Composed of repeated modules, or microcircuits, the neocortex relies on distinct cell types as its fundamental building blocks. Despite significant progress in characterizing these cell types^1–5, an understanding of the complete synaptic partners associated with individual excitatory cell types remain elusive. Here, we investigate the connectivity of arguably the most well recognized and studied excitatory neuron in the neocortex: the thick tufted layer 5 pyramidal cell^6–10also known as extra telencephalic (ET)¹¹neurons. Although the synaptic interactions of ET neurons have been extensively explored, a comprehensive characterization of their local connectivity remains lacking. To address this knowledge gap, we leveraged a 1 mm³electron microscopic (EM) dataset. We found that ET neurons primarily establish connections with inhibitory cells in their immediate vicinity. However, when they extend their axons to other cortical regions, they tend to connect more with excitatory cells. We also find that the inhibitory cells targeted by ET neurons are a specific group of cell types, and they preferentially inhibit ET cells. Finally, we observed that the most common excitatory targets of ET neurons are layer 5 IT neurons and layer 6 pyramidal cells, whereas synapses with other ET neurons are not as common. These findings challenge current views of the connectivity of ET neurons and suggest a circuit design that involves local competition among ET neurons and collaboration with other types of excitatory cells. Our results also highlight a specific circuit pattern where a subclass of excitatory cells forms a network with specific inhibitory cell types, offering a framework for exploring the connectivity of other types of excitatory cells.