Many cognitive processes require communication between the neocortex and the hippocampus. However, coordination between large-scale cortical dynamics and hippocampal activity is not well understood, partially due to the difficulty in simultaneously recording from those regions. In the present study, we developed a flexible, insertable and transparent microelectrode array (Neuro-FITM) that enables investigation of cortical-hippocampal coordinations during hippocampal sharp-wave ripples (SWRs). Flexibility and transparency of Neuro-FITM allow simultaneous recordings of local field potentials and neural spiking from the hippocampus during wide-field calcium imaging. These experiments revealed that diverse cortical activity patterns accompanied SWRs and, in most cases, cortical activation preceded hippocampal SWRs. We demonstrated that, during SWRs, different hippocampal neural population activity was associated with distinct cortical activity patterns. These results suggest that hippocampus and large-scale cortical activity interact in a selective and diverse manner during SWRs underlying various cognitive functions. Our technology can be broadly applied to comprehensive investigations of interactions between the cortex and other subcortical structures.

Objective. Electrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain-computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions.Approach. To investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings.Main results. The mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials.Significance. These results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.

The robust application of stable mercury (Hg) isotopes for mercury source apportionment and risk assessment necessitates the understanding of mass-dependent fractionation (MDF) as a result of internal transformations within organisms. Here, we used high energy-resolution X-ray absorption near edge structure spectroscopy and isotope ratios of total mercury (δ202THg) and methylmercury (δ202MeHg) to elucidate the chemical speciation of Hg and the resultant MDF as a result of internal MeHg demethylation in waterbirds. In three waterbirds (Clark's grebe, Forster's tern, and south polar skua), between 17 and 86% of MeHg was demethylated to inorganic mercury (iHg) species primarily in the liver and kidneys as Hg-tetraselenolate [Hg(Sec)4] and minor Hg-dithiolate [Hg(SR)2] complexes. Tissular differences between δ202THg and δ202MeHg correlated linearly with %iHg [Hg(Sec)4 + Hg(SR)2] and were interpreted to reflect a kinetic isotope effect during in vivo MeHg demethylation. The product-reactant isotopic enrichment factor (ϵp/r) for the demethylation of MeHg → Hg(Sec)4 was -2.2 ± 0.1‰. δ202MeHg values were unvarying within each bird, regardless of Hg(Sec)4 abundance, indicating fast internal cycling or replenishment of MeHg relative to demethylation. Our findings document a universal selenium-dependent demethylation reaction in birds, provide new insights on the internal transformations and cycling of MeHg and Hg(Sec)4, and allow for mathematical correction of δ202THg values as a result of the MeHg → Hg(Sec)4 reaction.

Brain metastasis represents one of the most common causes of intracranial tumors in adults, and the incidence of brain metastasis continues to rise due to the increasing survival of cancer patients. Yet, the development of cystic brain metastasis remains a relatively rare occurrence. In this review, we describe the characteristics of cystic brain metastasis and evaluate the combined use of stereotactic aspiration and radiosurgery in treating large cystic brain metastasis. The results of several studies show that stereotactic radiosurgery produces comparable local tumor control and survival rates as other surgery protocols. When the size of the tumor interferes with radiosurgery, stereotactic aspiration of the metastasis should be considered to reduce the target volume as well as decreasing the chance of radiation induced necrosis and providing symptomatic relief from mass effect. The combined use of stereotactic aspiration and radiosurgery has strong implications in improving patient outcomes.

CMOS-RRAM integration holds great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise, leading to computational accuracy loss, increased energy consumption, and overhead by expensive program and verify schemes. We developed a filament-free, bulk switching RRAM technology to address these challenges. We systematically engineered a trilayer metal-oxide stack and investigated the switching characteristics of RRAM with varying thicknesses and oxygen vacancy distributions to achieve reliable bulk switching without any filament formation. We demonstrated bulk switching at megaohm regime with high current nonlinearity, up to 100 levels without compliance current. We developed a neuromorphic compute-in-memory platform and showcased edge computing by implementing a spiking neural network for an autonomous navigation/racing task. Our work addresses challenges posed by existing RRAM technologies and paves the way for neuromorphic computing at the edge under strict size, weight, and power constraints.

Human cortical organoids, three-dimensional neuronal cultures, are emerging as powerful tools to study brain development and dysfunction. However, whether organoids can functionally connect to a sensory network in vivo has yet to be demonstrated. Here, we combine transparent microelectrode arrays and two-photon imaging for longitudinal, multimodal monitoring of human cortical organoids transplanted into the retrosplenial cortex of adult mice. Two-photon imaging shows vascularization of the transplanted organoid. Visual stimuli evoke electrophysiological responses in the organoid, matching the responses from the surrounding cortex. Increases in multi-unit activity (MUA) and gamma power and phase locking of stimulus-evoked MUA with slow oscillations indicate functional integration between the organoid and the host brain. Immunostaining confirms the presence of human-mouse synapses. Implantation of transparent microelectrodes with organoids serves as a versatile in vivo platform for comprehensive evaluation of the development, maturation, and functional integration of human neuronal networks within the mouse brain.