We report a fabrication process for coating neural probes with an ultrafast degrading polymer to create consistent and reproducible devices for neural tissue insertion. The rigid polymer coating acts as a probe insertion aid, but resorbs within hours post-implantation. Despite the feasibility for short term neural recordings from currently available neural prosthetic devices, most of these devices suffer from long term gliosis, which isolates the probes from adjacent neurons, increasing the recording impedance and stimulation threshold. The size and stiffness of implanted probes have been identified as critical factors that lead to this long term gliosis. Smaller, more flexible probes that match the mechanical properties of brain tissue could allow better long term integration by limiting the mechanical disruption of the surrounding tissue during and after probe insertion, while being flexible enough to deform with the tissue during brain movement. However, these small flexible probes inherently lack the mechanical strength to penetrate the brain on their own. In this work, we have developed a micromolding method for coating a non-functional miniaturized SU-8 probe with an ultrafast degrading tyrosine-derived polycarbonate (E5005(2K)). Coated, non-functionalized probes of varying dimensions were reproducibly fabricated with high yields. The polymer erosion/degradation profiles of the probes were characterized in vitro. The probes were also mechanically characterized in ex vivo brain tissue models by measuring buckling and insertion forces during probe insertion. The results demonstrate the ability to produce polymer coated probes of consistent quality for future in vivo use, for example to study the effects of different design parameters that may affect tissue response during long term chronic intra-cortical microelectrode neural recordings.

Despite deep brain stimulation’s positive early results in psychiatric disorders, well-designed clinical trials have yielded inconsistent clinical outcomes. One path to more reliable benefit is closed-loop therapy: stimulation that is automatically adjusted by a device or algorithm in response to changes in the patient’s electrical brain activity. These interventions may provide more precise and patient-specific treatments. In this article, we first introduce the available closed-loop neuromodulation platforms, which have shown clinical efficacy in epilepsy and strong early results in movement disorders. We discuss the strengths and limitations of these devices in the context of psychiatric illness. We then describe emerging technologies to address these limitations, including pre-clinical developments such as wireless deep neurostimulation and genetically targeted neuromodulation. Finally, we discuss ongoing challenges and limitations for closed-loop psychiatric brain stimulation development, most notably the difficulty of identifying meaningful biomarkers for titration. We consider this in the recently-released Research Domain Criteria (RDoC) framework and describe how neuromodulation and RDoC are jointly very well suited to address the problem of treatment-resistant illness.

Cross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate examples of CFC during a seizure and in response to electrical stimuli.

Neural oscillations enable communication between brain regions. Closed-loop brain stimulation attempts to modify this activity by stimulation locked to the phase of concurrent neural oscillations. If successful, this may be a major step forward for clinical brain stimulation therapies. The challenge for effective phase-locked systems is accurately calculating the phase of a source oscillation in real time. The basic operations of filtering the source signal to a frequency band of interest and extracting its phase cannot be performed in real time without distortion. We present a method for continuously estimating phase that reduces this distortion by using an autoregressive model to predict the future of a filtered signal before passing it though the Hilbert transform. This method outperforms published approaches on real data and is available as a reusable open-source module. We also examine the challenge of compensating for the filter phase response and outline promising directions of future study.

Single-unit recording neural probes have significant advantages towards improving signal-to-noise ratio and specificity for signal acquisition in brain-to-computer interface devices. Long-term effectiveness is unfortunately limited by the chronic injury response, which has been linked to the mechanical mismatch between rigid probes and compliant brain tissue. Small, flexible microelectrodes may overcome this limitation, but insertion of these probes without buckling requires supporting elements such as a stiff coating with a biodegradable polymer. For these coated probes, there is a design trade-off between the potential for successful insertion into brain tissue and the degree of trauma generated by the insertion. The objective of this study was to develop and validate a finite element model (FEM) to simulate insertion of coated neural probes of varying dimensions and material properties into brain tissue. Simulations were performed to predict the buckling and insertion forces during insertion of coated probes into a tissue phantom with material properties of brain. The simulations were validated with parallel experimental studies where probes were inserted into agarose tissue phantom, ex vivo chick embryonic brain tissue, and ex vivo rat brain tissue. Experiments were performed with uncoated copper wire and both uncoated and coated SU-8 photoresist and Parylene C probes. Model predictions were found to strongly agree with experimental results (<10% error). The ratio of the predicted buckling force-to-predicted insertion force, where a value greater than one would ideally be expected to result in successful insertion, was plotted against the actual success rate from experiments. A sigmoidal relationship was observed, with a ratio of 1.35 corresponding to equal probability of insertion and failure, and a ratio of 3.5 corresponding to a 100% success rate. This ratio was dubbed the “safety factor”, as it indicated the degree to which the coating should be over-designed to ensure successful insertion. Probability color maps were generated to visually compare the influence of design parameters. Statistical metrics derived from the color maps and multi-variable regression analysis confirmed that coating thickness and probe length were the most important features in influencing insertion potential. The model also revealed the effects of manufacturing flaws on insertion potential.

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These results suggest that: (1) the degree of mechanical trauma at device implantation and mechanical mismatches at the probe-tissue interface affect long term gliosis; (2) smaller, more flexible probes may minimize the glial response to provide improved tissue biocompatibility when used for chronic neural signal recording; and (3) some degree of glial scarring did not significantly affect neuronal distribution around the probe.

Objective. Neurostimulation technologies are important for studying neural circuits and the connections that underlie neurological and psychiatric disorders. However, current methods come with limitations such as the restraint on movement imposed by the wires delivering stimulation. The objective of this study was to assess whether the e-Particle (EP), a novel wireless neurostimulator, could sufficiently stimulate the brain to modify behavior without these limitations. Approach. Rats were implanted with the EP and a commercially available stimulating electrode. Animals received rewarding brain stimulation, and performance in a conditioned place preference (CPP) task was measured. To ensure stimulation-induced neuronal activation, immediate early gene c-fos expression was also measured. Main results. The EP was validated in a commonly used CPP task by demonstrating that (1) wireless stimulation via the EP induced preference behavior that was comparable to that induced by standard wired electrodes and (2) neuronal activation was observed in projection targets of the stimulation site. Significance. The EP may help achieve a better understanding of existing brain stimulation methods while overcoming their limitations. Validation of the EP in a behavioral model suggests that the benefits of this technology may extend to other areas of animal research and potentially to human clinical applications.