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Future brain–computer interfaces will require local and highly individualized signal processing of fully integrated electronic circuits within the nervous system and other living tissue. New devices will need to be developed that can receive data from a sensor array, process these data into meaningful information, and translate that information into a format that can be interpreted by living systems. Here, the first example of interfacing a hardware‐based pattern classifier with a biological nerve is reported. The classifier implements the Widrow–Hoff learning algorithm on an array of evolvable organic electrochemical transistors (EOECTs). The EOECTs' channel conductance is modulated in situ by electropolymerizing the semiconductor material within the channel, allowing for low voltage operation, high reproducibility, and an improvement in state retention by two orders of magnitude over state‐of‐the‐art OECT devices. The organic classifier is interfaced with a biological nerve using an organic electrochemical spiking neuron to translate the classifier's output to a simulated action potential. The latter is then used to stimulate muscle contraction selectively based on the input pattern, thus paving the way for the development of adaptive neural interfaces for closed‐loop therapeutic systems. [ABSTRACT FROM AUTHOR]

Electrical signals are fundamental to key biological events such as brain activity, heartbeat, or vital hormone secretion. Their capture and analysis provide insight into cell or organ physiology and a number of bioelectronic medical devices aim to improve signal acquisition. Organic electrochemical transistors (OECT) have proven their capacity to capture neuronal and cardiac signals with high fidelity and amplification. Vertical PEDOT:PSS‐based OECTs (vOECTs) further enhance signal amplification and device density but have not been characterized in biological applications. An electronic board with individually tuneable transistor biases overcomes fabrication induced heterogeneity in device metrics and allows quantitative biological experiments. Careful exploration of vOECT electric parameters defines voltage biases compatible with reliable transistor function in biological experiments and provides useful maximal transconductance values without influencing cellular signal generation or propagation. This permits successful application in monitoring micro‐organs of prime importance in diabetes, the endocrine pancreatic islets, which are known for their far smaller signal amplitudes as compared to neurons or heart cells. Moreover, vOECTs capture their single‐cell action potentials and multicellular slow potentials reflecting micro‐organ organizations as well as their modulation by the physiological stimulator glucose. This opens the possibility to use OECTs in new biomedical fields well beyond their classical applications. [ABSTRACT FROM AUTHOR]

There is increasing demand for direct in situ metabolite monitoring from cell cultures and in vivo using implantable devices. Electrochemical biosensors are commonly preferred due to their low‐cost, high sensitivity, and low complexity. Metabolite detection, however, in cultured cells or sensitive tissue is rarely shown. Commonly, glucose sensing occurs indirectly by measuring the concentration of hydrogen peroxide, which is a by‐product of the conversion of glucose by glucose oxidase. However, continuous production of hydrogen peroxide in cell media with high glucose is toxic to adjacent cells or tissue. This challenge is overcome through a novel, stacked enzyme configuration. A primary enzyme is used to provide analyte sensitivity, along with a secondary enzyme which converts H2O2 back to O2. The secondary enzyme is functionalized as the outermost layer of the device. Thus, production of H2O2 remains local to the sensor and its concentration in the extracellular environment does not increase. This "biostack" is integrated with organic electrochemical transistors to demonstrate sensors that monitor glucose concentration in cell cultures in situ. The "biostack" renders the sensors nontoxic for cells and provides highly sensitive and stable detection of metabolites. [ABSTRACT FROM AUTHOR]

Abstract: Organic semiconductors can be employed as the active layer in accumulation mode organic electrochemical transistors (OECTs), where redox stability in aqueous electrolytes is important for long‐term recordings of biological events. It is observed that alkoxy‐benzo[1,2‐b:4,5‐b′]dithiophene (BDT) copolymers can be extremely unstable when they are oxidized in aqueous solutions. The redox stability of these copolymers can be improved by molecular design of the copolymer where it is observed that the electron rich comonomer 3,3′‐dimethoxy‐2,2′‐bithiophene (MeOT2) lowers the oxidation potential and also stabilizes positive charges through delocalization and resonance effects. For copolymers where the comonomers do not have the same ability to stabilize positive charges, irreversible redox reactions are observed with the formation of quinone structures, being detrimental to performance of the materials in OECTs. Charge distribution along the copolymer from density functional theory calculations is seen to be an important factor in the stability of the charged copolymer. As a result of the stabilizing effect of the comonomer, a highly stable OECT performance is observed with transconductances in the mS range. The analysis of the decomposition pathway also raises questions about the general stability of the alkoxy‐BDT unit, which is heavily used in donor–acceptor copolymers in the field of photovoltaics. [ABSTRACT FROM AUTHOR]