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Graphene active sensors have demonstrated promising capabilities for the detection of electrophysiological signals in the brain. Their functional properties, together with their flexibility as well as their expected stability and biocompatibility have raised them as a promising building block for large-scale sensing neural interfaces. However, in order to provide reliable tools for neuroscience and biomedical engineering applications, the maturity of this technology must be thoroughly studied. Here, we evaluate the performance of 64-channel graphene sensor arrays in terms of homogeneity, sensitivity and stability using a wireless, quasi-commercial headstage and demonstrate the biocompatibility of epicortical graphene chronic implants. Furthermore, to illustrate the potential of the technology to detect cortical signals from infra-slow to high-gamma frequency bands, we perform proof-of-concept long-term wireless recording in a freely behaving rodent. Our work demonstrates the maturity of the graphene-based technology, which represents a promising candidate for chronic, wide frequency band neural sensing interfaces., This work has been funded by the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 732032 (BrainCom) and Graphene Flagship Grant Agreements No. 785219 (GrapheneCore2) and 881603 (GrapheneCore3). The ICN2 is supported by the Severo Ochoa Centres of Excellence program, funded by the Spanish Research Agency (AEI, grant no. SEV-2017-0706), and by the CERCA Program/Generalitat de Catalunya. R.G.C. is supported by the International Ph.D Program La Caixa-Severo Ochoa (Programa Internacional de Becas “la Caixa”-Severo Ochoa). This work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS “NANBIOSIS”, more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN) at the IMB-CNM. This work is within the project FIS2017-85787-R funded by the “Ministerio de Ciencia, Innovación y Universidades” of Spain, the “Agencia Estatal de Investigación (AEI)”, and the “Fondo Europeo de Desarrollo Regional (FEDER/UE)”. A.S. and G.S. were also supported by Bundesministerium für Bildung und Forschung [grant number 01GQ0440]. R.G.C. acknowledges that this work has been done in the framework of the Ph.D in Electrical and Telecommunication Engineering at the Universitat Autònoma de Barcelona.

Recording infraslow brain signals (, This work was funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 696656 (Graphene Flagship) and no. 732032 (BrainCom). This work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MINECO and the ICTS ‘NANBIOSIS’, more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN) at the IMB-CNM. E.M.C. acknowledges that this work has been done in the framework of the PhD in Electrical and Telecommunication Engineering at the Universitat Autònoma de Barcelona. E..C. thanks the Spanish Ministerio de Economía y Competitividad for the Juan de la Cierva postdoctoral grant IJCI-2015–25201. T. Durduran acknowledges support from Fundació CELLEX Barcelona, Ministerio de Economía y Competitividad /FEDER (PHOTODEMENTIA, DPI2015–64358-C2–1-R), the “Severo Ochoa” Programme for Centres of Excellence in R&D (SEV-2015–0522) and the Obra Social “la Caixa” Foundation (LlumMedBcn). M.V.S.V. acknowledges support from MINECO BFU2017-85048-R. ICN2 is supported by the Severo Ochoa programme fromSpanish MINECO (grant no. SEV-2017-0706).