Biology subjects

Kuzum, D.

Publications and source records attributed to Kuzum, D..

4 recordsLinked to original sources

bioRxiv2022

Multimodal monitoring of human cortical organoids implanted in mice using transparent graphene microelectrodes reveal functional connection between organoid and mouse visual cortex

Human cortical organoids, three-dimensional neuronal cell cultures derived from human induced pluripotent stem cells, have recently emerged as promising models of human brain development and dysfunction. Transplantation of human brain organoids into the mouse brain has been shown to be a successful in vivo model providing vascularization for long term chronic experiments. However, chronic functional connectivity and responses evoked by external sensory stimuli has yet to be demonstrated, due to limitations of chronic recording technologies. Here, we develop an experimental paradigm based on transparent graphene microelectrode arrays and two-photon imaging for longitudinal, multimodal monitoring of human organoids transplanted in the mouse cortex. The transparency of graphene microelectrodes permits visual and optical inspection of the transplanted organoid and the surrounding cortex throughout the chronic experiments where local field potentials and multi-unit activity (MUA) are recorded during spontaneous activity and visual stimuli. These experiments reveal that visual stimuli evoke electrophysiological responses in the organoid, matching the responses from the surrounding cortex. Increases in the power of the gamma and MUA bands as well as phase locking of MUA events to slow oscillations evoked by visual stimuli suggest functional connectivity established between the human and mouse tissue. Optical imaging through the transparent microelectrodes shows vascularization of the organoids. Postmortem histological analysis exhibits morphological integration and synaptic connectivity with surrounding mouse cortex as well as migration of organoid cells into the surrounding cortex. This novel combination of stem cell and neural recording technologies could serve as a unique platform for comprehensive evaluation of organoids as models of brain development and dysfunction and as personalized neural prosthetics to restore lost, degenerated, or damaged brain regions.

neuroscience↗

bioRxiv2021

E-Cannula reveals anatomical diversity in sharp-wave ripples as a driver for the recruitment of distinct hippocampal assemblies

The hippocampus plays a critical role in spatial navigation and episodic memory. However, research on in vivo hippocampal activity dynamics has mostly relied on single modalities such as electrical recordings or optical imaging, with respectively limited spatial and temporal resolution. This technical difficulty greatly impedes multi-level investigations into network state-related changes in cellular activity. To overcome these limitations, we developed the E-Cannula integrating fully transparent graphene microelectrodes with imaging-cannula. The E-Cannula enables the simultaneous electrical recording and two-photon calcium imaging from the exact same population of neurons across an anatomically extended region of the mouse hippocampal CA1 stably across several days. These large-scale simultaneous optical and electrical recordings showed that local hippocampal sharp wave ripples (SWRs) are associated with synchronous calcium events involving large neural populations in CA1. We show that SWRs exhibit spatiotemporal wave patterns along multiple axes in 2D space with different spatial extents (local or global) and temporal propagation modes (stationary or travelling). Notably, distinct SWR wave patterns were associated with, and decoded from, the selective recruitment of orthogonal CA1 cell assemblies. These results suggest that the diversity in the anatomical progression of SWRs may serve as a mechanism for the selective activation of the unique hippocampal cell assemblies extensively implicated in the encoding of distinct memories. Through these results we demonstrate the utility of the E-Cannula as a versatile neurotechnology with the potential for future integration with other optical components such as green lenses, fibers or prisms enabling the multi-modal investigation of cross-time scale population-level neural dynamics across brain regions.

neuroscience↗

bioRxiv2021

Decoding of cortex-wide brain activity from local recordings of neural potentials

ObjectiveElectrical 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. ApproachTo 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 resultsThe 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. SignificanceThese 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.

neuroscience↗

bioRxiv2018

A biophysical computational model for memory trace transfer from hippocampus to neocortex

The hippocampus plays important roles in memory formation and retrieval through sharp-wave-ripples. Recent studies have shown that certain neuron populations in the prefrontal cortex exhibit coordinated reactivations during awake ripple events. Also, the reactivation seems stronger during initial awake learning. These experimental findings suggest that the awake ripple is an important biomarker, through which the hippocampus interacts with the neocortex to assist the memory formation and retrieval. However, the computational mechanisms of this ripple based hippocampal-cortical coordination are still not clear. In this work, we build a biophysical model that includes both CA1 and layer V networks of the prefrontal cortex to investigate the possible mechanisms, by which the memory traces in the hippocampus can be transferred to prefrontal cortex. We first show that the local field potentials generated in the hippocampus and prefrontal cortex exhibit ripple range activities that are consistent with the recent experimental studies. Then, we find that the sequence information stored in the hippocampus can be successfully transferred to the prefrontal cortex recurrent networks through spike-timing dependent plasticity (STDP) and sequence replays. Further, we investigate the mechanisms of memory retrieval in the PFC network. Our findings suggest that the stored memory traces in the prefrontal cortex network can be retrieved through two different mechanisms, namely the cell-specific input and non-specific spontaneous background noise. Finally, we show that more SWRs and an optimal background noise level will both contribute to better sequence reactivations in the PFC network during memory retrieval. Our study presents a possible explanation for the memory trace transfer from the hippocampus to the neocortex through ripple coupling in awake states and reports two different mechanisms by which the stored memory traces can be successfully retrieved.\n\nAuthor SummaryThe hippocampal-cortical interactions have been found to be important for learning and memory. Recent experimental work reports interesting coordinations between the hippocampus and neocortex during ripple events in quiet awake states. Investigating this phenomena is critical for a deeper understanding of the mechanisms by which hippocampus contributes to the long-term memory formation in the neocortex. To this end, we build a biophysical computational model for both the hippocampal CA1 and prefrontal cortex networks. We demonstrate that under STDP rule and sequential inputs, the memory traces initially stored in the hippocampus can be transferred to the neocortex through the ripple events. The stored memory traces in the PFC network can be reactivated by two different mechanisms, namely the cell-specific inputs and non-specific background noises. Our study suggests that both the ripple event numbers and the level of background noises jointly determine the quality of memory retrieval during reactivation.

neuroscience↗