RESUMO
Realizing the full potential of organoids and assembloids to model neural development and disease will require improved methods for long-term, minimally invasive recording of electrical activity. Current technologies, such as patch clamp, penetrating microelectrodes, planar electrode arrays and substrate-attached flexible electrodes, do not allow chronic recording of organoids in suspension, which is necessary to preserve architecture. Inspired by kirigami art, we developed flexible electronics that transition from a two-dimensional to a three-dimensional basket-like configuration with either spiral or honeycomb patterns to accommodate the long-term culture of organoids in suspension. Here we show that this platform, named kirigami electronics (KiriE), integrates with and enables chronic recording of cortical organoids for up to 120 days while preserving their morphology, cytoarchitecture and cell composition. We demonstrate integration of KiriE with optogenetic and pharmacological manipulation and modeling phenotypes related to a genetic disease. Moreover, KiriE can capture corticostriatal connectivity in assembloids following optogenetic stimulation. Thus, KiriE will enable investigation of disease and activity patterns underlying nervous system assembly.
RESUMO
Organoids and assembloids have emerged as a promising platform to model aspects of nervous system development. Longterm, minimally-invasive recordings in these multi-cellular systems are essential for developing disease models. Current technologies, such as patch-clamp, penetrating microelectrodes, planar electrode arrays and substrate-attached flexible electrodes, do not, however, allow chronic recording of organoids in suspension, which is necessary to preserve their architecture. Inspired by the art of kirigami, we developed flexible electronics that transition from a 2D pattern to a 3D basketlike configuration to accommodate the long-term culture of organoids in suspension. This platform, named kirigami electronics (KiriE), integrates with and enables chronic recording of cortical organoids while preserving morphology, cytoarchitecture, and cell composition. KiriE can be integrated with optogenetic and pharmacological stimulation and model disease. Moreover, KiriE can capture activity in cortico-striatal assembloids. Moving forward, KiriE could reveal disease phenotypes and activity patterns underlying the assembly of the nervous system.
RESUMO
Current trend in neurosciences is to use naturalistic stimuli, such as cinema, class-room biology or video gaming, aiming to understand the brain functions during ecologically valid conditions. Naturalistic stimuli recruit complex and overlapping cognitive, emotional and sensory brain processes. Brain oscillations form underlying mechanisms for such processes, and further, these processes can be modified by expertise. Human cortical functions are often analyzed with linear methods despite brain as a biological system is highly nonlinear. This study applies a relatively robust nonlinear method, Higuchi fractal dimension (HFD), to classify cortical functions of math experts and novices when they solve long and complex math demonstrations in an EEG laboratory. Brain imaging data, which is collected over a long time span during naturalistic stimuli, enables the application of data-driven analyses. Therefore, we also explore the neural signature of math expertise with machine learning algorithms. There is a need for novel methodologies in analyzing naturalistic data because formulation of theories of the brain functions in the real world based on reductionist and simplified study designs is both challenging and questionable. Data-driven intelligent approaches may be helpful in developing and testing new theories on complex brain functions. Our results clarify the different neural signature, analyzed by HFD, of math experts and novices during complex math and suggest machine learning as a promising data-driven approach to understand the brain processes in expertise and mathematical cognition.
