Advancing electronics to interact with tissue necessitates meeting material constraints in electrochemical, electrical, and mechanical domains simultaneously. Clinical bioelectrodes with established electrochemical functionalities are rigid and mechanically mismatched with tissue. Whereas conductive materials with tissue-like softness and stretchability are demonstrated, when applied to electrochemically probe tissue, their performance is distorted by strain and corrosion. We devise a layered architectural composite design that couples strain-induced cracked films with a strain-isolated out-of-plane conductive pathway and in-plane nanowire networks to eliminate strain effects on device electrochemical performance. Accordingly, we developed a library of stretchable, highly conductive, and strain-insensitive bioelectrodes featuring clinically established brittle interfacial materials (iridium-oxide, gold, platinum, and carbon). We paired these bioelectrodes with different electrochemical probing methods (amperometry, voltammetry, and potentiometry) and demonstrated strain-insensitive sensing of multiple biomarkers and in vivo neuromodulation.

SIP30 (SNAP25 interacting protein of 30) is a SNAP25 interaction protein of 30 kDa that functions in neurotransmitter release. Using a chronic constriction injury (CCI) model of neuropathic pain, we profiled gene expression in the rat spinal cord and brain and identifiedsip30, which was upregulated after CCI. Here, we show that CCI induced a bilateral increase of SIP30 in the rostral anterior cingulate cortex (rACC), a key brain region that has been implicated in pain affect. We put rats in a chamber with one half painted white (light area) and the other half painted black (dark area), and measured neuropathic pain-evoked place escape/avoidance paradigm (PEAP) to quantify the level of negative emotion evoked by painful stimuli using a Von Frey hair. Inhibition of CCI-mediated induction of SIP30 by intra-rACC injection of shRNA targeting the ratsip30gene reduced PEAP. Interestingly, knockdown of SIP30 did not affect CCI-induced evoked pain such as heat hyperalgesia and mechanical allodynia. Neither did it affect general learning and memory. CCI-induced upregulation of SIP30 was correlated with activation of ERK, PKA, and CREB in the rACC. Intra-rACC administration of PKA or ERK inhibitors suppressed CCI-induced SIP30 upregulation and blocked the induction of PEAP. Additionally, knockdown of SIP30 suppressed the frequency of mEPSCs and increased paired-pulse ratios in rACC slices and decreased extracellular glutamate concentrations. Together, our results highlight SIP30 as a target of PKA and ERK in the rACC to mediate neuropathic pain-evoked negative emotion via modulation of glutamate release and excitatory synaptic transmission.

Respiration is produced and controlled by well-characterized brain stem nuclei, but the contributions of spinal circuits to respiratory control and modulation remain under investigation. Many respiratory studies are conducted in in vitro preparations (e.g., brain stem slice) obtained from neonatal rodents. While informative, these studies do not fully recapitulate the complex afferent and efferent neural circuits that are likely to be involved in eupnea (i.e., quiet breathing). To begin to investigate spinal contributions to respiration, we electrically stimulated the cervical spinal cord during unassisted respiration in anesthetized, intact mice. Specifically, we used epidermal electrical stimulation at 20 Hz and varied current intensity to map changes in respiration. Stimulating at 1.5 mA at cervical level 3 (C3) consistently caused a significant increase in respiratory frequency compared with prestimulation baseline and when compared with sham stimulations. The increase in respiratory frequency persisted for several minutes after epidural stimulation ceased. There was no change in tidal volume, and the estimated minute ventilation was increased as a consequence of the increase in respiratory frequency. Sigh frequency also increased during epidural stimulation at C3. Neither the increase in respiratory frequency nor the increase in sighing were observed after stimulation at other dorsal cervical levels. These findings suggest that the spinal circuits involved in the modulation of eupnea and sighing may be preferentially activated by specific endogenous inputs. Moreover, the cervical spinal cord may play a role in respiratory modulation that affects both eupneic respiration and sigh production in intact, adult mice.

Recent studies suggest that epidural stimulation of the spinal cord could increase the motor pattern both in motor and sensory complete spinal cord injury (SCI) patients. However, choosing the optimal epidural stimulation variables, such as the frequency, intensity, and location of the stimulation, significantly affects maximal motor functionality. This paper presents a novel technique using machine learning methods to predict the functionality of a SCI patient after epidural stimulation. Additionally, we suggest a committee-based active learning method to reduce the number of clinical experiments required through exploring the stimulation configuration space more efficiently. This paper also introduces a novel method to dynamically weight the results of different experiments based on neural networks to create an optimal estimate of the quantity of interest. The proposed method for the prediction of stimulation outcomes is evaluated based on various accuracy measures such as mean absolute error, standard deviation, and correlation coefficient. The results show that the proposed method can be used to reliably predict the outcome of epidural stimulation on maximum voluntary contraction force with the prediction error of about 15%.