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Graphene-based biosensors can be produced in a scalable manner at reasonable cost, and they show significant promise for sensitive detection of small molecules and biomarkers such as proteins, single strand nucleic acids, and drug targets. Here, we describe an approach that enables a limit of detection of ~1 aM for a ssDNA target without amplification. We also show that a sensor based on a short (20mer) probe complementary to a portion of a longer (100mer) target provides enhanced sensitivity and saturation signal level. Finally, we show that graphene-based DNA biosensors can be repeatedly recycled with consistent sensor responses by melting off bound target strands. These results show the potential utility of this technology in nucleic acid detection for disease diagnostics.

Hippocampal seizures are a defining feature of mesial temporal lobe epilepsy (MTLE). Area CA1 of the hippocampus is commonly implicated in the generation of seizures, which may occur because of the activity of endogenous cell populations or of inputs from other regions within the hippocampal formation. Simultaneously observing activity at the cellular and network scalesin vivoremains challenging. Here, we present a novel technology for simultaneous electrophysiology and multicellular calcium imaging of CA1 pyramidal cells (PCs) in mice enabled by a transparent graphene-based microelectrode array (Gr MEA). We examine PC firing at seizure onset, oscillatory coupling, and the dynamics of the seizure traveling wave as seizures evolve. Finally, we couple features derived from both modalities to predict the speed of the traveling wave using bootstrap aggregated regression trees. Analysis of the most important features in the regression trees suggests a transition among states in the evolution of hippocampal seizures.

Neurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution., Driscoll, Rosch et al. design transparent graphene-based surface probes to achieve simultaneous electrophysiological recording and calcium imaging of epileptic seizures in mice. This method could be used to investigate circuit dynamics during seizure onset and evolution with high temporal and spatial resolution.

Neurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution.