SmartFSCV: An Artificial Intelligence Enabled Miniaturised FSCV Device Targeting Serotonin.

Goal: Dynamically monitoring serotonin in real-time within target brain regions would significantly improve the diagnostic and therapeutic approaches to a variety of neurological and psychiatric disorders. Current systems for measuring serotonin lack immediacy and portability and are bulky and expensive. Methods: We present a new miniaturised device, named SmartFSCV, designed to monitor dynamic changes of serotonin using fast-scan cyclic voltammetry (FSCV). This device outputs a precision voltage potential between -3 to +3 V, and measures current between -1.5 to +1.5 µA with nano-ampere accuracy. The device can output modifiable arbitrary waveforms for various measurements and uses an N-shaped waveform at a scan-rate of 1000 V/s for sensing serotonin. Results: Four experiments were conducted to validate SmartFSCV: static bench test, dynamic serotonin test and two artificial intelligence (AI) algorithm tests. Conclusions: These tests confirmed the ability of SmartFSCV to accurately sense and make informed decisions about the presence of serotonin using AI.

A self-stiffening compliant intracortical microprobe.

Utilising a flexible intracortical microprobe to record/stimulate neurons minimises the incompatibility between the implanted microprobe and the brain, reducing tissue damage due to the brain micromotion. Applying bio-dissolvable coating materials temporarily makes a flexible microprobe stiff to tolerate the penetration force during insertion. However, the inability to adjust the dissolving time after the microprobe contact with the cerebrospinal fluid may lead to inaccuracy in the microprobe positioning. Furthermore, since the dissolving process is irreversible, any subsequent positioning error cannot be corrected by re-stiffening the microprobe. The purpose of this study is to propose an intracortical microprobe that incorporates two compressible structures to make the microprobe both adaptive to the brain during operation and stiff during insertion. Applying a compressive force by an inserter compresses the two compressible structures completely, resulting in increasing the equivalent elastic modulus. Thus, instant switching between stiff and soft modes can be accomplished as many times as necessary to ensure high-accuracy positioning while causing minimal tissue damage. The equivalent elastic modulus of the microprobe during operation is ≈ 23 kPa, which is ≈ 42% less than the existing counterpart, resulting in ≈ 46% less maximum strain generated on the surrounding tissue under brain longitudinal motion. The self-stiffening microprobe and surrounding neural tissue are simulated during insertion and operation to confirm the efficiency of the design. Two-photon polymerisation technology is utilised to 3D print the proposed microprobe, which is experimentally validated and inserted into a lamb's brain without buckling.

A Smart Camera Trap for Detection of Endotherms and Ectotherms.

Current camera traps use passive infrared triggers; therefore, they only capture images when animals have a substantially different surface body temperature than the background. Endothermic animals, such as mammals and birds, provide adequate temperature contrast to trigger cameras, while ectothermic animals, such as amphibians, reptiles, and invertebrates, do not. Therefore, a camera trap that is capable of monitoring ectotherms can expand the capacity of ecological research on ectothermic animals. This study presents the design, development, and evaluation of a solar-powered and artificial-intelligence-assisted camera trap system with the ability to monitor both endothermic and ectothermic animals. The system is developed using a central processing unit, integrated graphics processing unit, camera, infrared light, flash drive, printed circuit board, solar panel, battery, microphone, GPS receiver, temperature/humidity sensor, light sensor, and other customized circuitry. It continuously monitors image frames using a motion detection algorithm and commences recording when a moving animal is detected during the day or night. Field trials demonstrate that this system successfully recorded a high number of animals. Lab testing using artificially generated motion demonstrated that the system successfully recorded within video frames at a high accuracy of 0.99, providing an optimized peak power consumption of 5.208 W. No water or dust entered the cases during field trials. A total of 27 cameras saved 85,870 video segments during field trials, of which 423 video segments successfully recorded ectothermic animals (reptiles, amphibians, and arthropods). This newly developed camera trap will benefit wildlife biologists, as it successfully monitors both endothermic and ectothermic animals.

Neural tissue-microelectrode interaction: Brain micromotion, electrical impedance, and flexible microelectrode insertion.

Insertion of a microelectrode into the brain to record/stimulate neurons damages neural tissue and blood vessels and initiates the brain's wound healing response. Due to the large difference between the stiffness of neural tissue and microelectrode, brain micromotion also leads to neural tissue damage and associated local immune response. Over time, following implantation, the brain's response to the tissue damage can result in microelectrode failure. Reducing the microelectrode's cross-sectional dimensions to single-digit microns or using soft materials with elastic modulus close to that of the neural tissue are effective methods to alleviate the neural tissue damage and enhance microelectrode longevity. However, the increase in electrical impedance of the microelectrode caused by reducing the microelectrode contact site's dimensions can decrease the signal-to-noise ratio. Most importantly, the reduced dimensions also lead to a reduction in the critical buckling force, which increases the microelectrode's propensity to buckling during insertion. After discussing brain micromotion, the main source of neural tissue damage, surface modification of the microelectrode contact site is reviewed as a key method for addressing the increase in electrical impedance issue. The review then focuses on recent approaches to aiding insertion of flexible microelectrodes into the brain, including bending stiffness modification, effective length reduction, and application of a magnetic field to pull the electrode. An understanding of the advantages and drawbacks of the developed strategies offers a guide for dealing with the buckling phenomenon during implantation.

An FSCV Deep Neural Network: Development, Pruning, and Acceleration on an FPGA.

Fast-scan cyclic voltammetry (FSCV) is an electrochemical technique for measuring rapid changes in the extracellular concentration of neurotransmitters within the brain. Due to its fast scan rate and large output-data size, the current analysis of the FSCV data is often conducted on a computer external to the FSCV device. Moreover, the analysis is semi-automated and requires a good understanding of the characteristics of the underlying chemistry to interpret, making it unsuitable for real-time implementation on low-resource FSCV devices. This paper presents a hardware-software co-design approach for the analysis of FSCV data. Firstly, a deep neural network (DNN) is developed to predict the concentration of a dopamine solution and identify the data recording electrode. Secondly, the DNN is pruned to decrease its computation complexity, and a custom overlay is developed to implement the pruned DNN on a low-resource FPGA-based platform. The pruned DNN attains a recognition accuracy of 97.2% with a compression ratio of 3.18. When the DNN overlay is implemented on a PYNQ-Z2 platform, it achieves the execution time of 13 ms and power consumption of 1.479 W on the entire PYNQ-Z2 board. This study demonstrates the possibility of operating the DNN for FSCV data analysis on portable FPGA-based platforms.

Miniature Resistance Measurement Device for Structural Health Monitoring of Reinforced Concrete Infrastructure.

A vast amount of civil infrastructure is constructed using reinforced concrete, which can be susceptible to corrosion, posing significant risks. Corrosion of reinforced concrete has various causes, with chloride ingress known to be a major contributor. Monitoring this chloride ingress would allow for preventative maintenance to be less intrusive at a lower cost. Currently, chloride sensing methods are bulky and expensive, leaving the majority of concrete infrastructures unmonitored. This paper presents the design and fabrication of a miniature, low-cost device that can be embedded into concrete at various locations and depths. The device measures localized concrete resistance, correlating to the chloride ingress in the concrete using equations listed in this paper, and calculated results from two experiments are presented. The device benefits from a four-probe architecture, injecting a fixed frequency AC waveform across its outer electrodes within the cement block. Voltage across the internal electrodes is measured with a microcontroller and converted to a resistance value, communicated serially to an external computer. A final test showcases the ability of the device for three-dimensional mass deployment.

TinyFSCV: FSCV for the Masses.

The ability to monitor neurochemical dynamics in target brain regions with a high degree of temporal resolution has assisted researchers in investigating the pathogenesis, and pathophysiology of a variety of neurological and psychiatric disorders. Current systems for neurochemical monitoring are bulky or expensive, limiting widespread exploration of this research field and preventing large-scale parallel experimentation. In this paper, we present a new miniaturized research platform, the TinyFSCV system, which can be used to monitor dynamic changes in neurochemicals through Fast-Scan Cyclic Voltammetry (FSCV). This system contains a precision voltage output circuit that can accurately output potentials between -0.55 to 2 V and scan a connected electrochemical cell at up to 400 V/s, the required speed to sense most neurochemicals with FSCV. In addition, the device includes precision current measurement circuity with a measurement range of -115 to [Formula: see text] capable of taking measurements at up to 56 KS/s. Four experiments are conducted to demonstrate the capability of the system. These consisted of: static bench tests, static ferrocene tests, and static and dynamic dopamine tests. These experiments demonstrate the ability of the miniaturized platform to accurately sense and measure neurochemicals. Ultimately, the TinyFSCV system is a platform that can enable large-scale, low-cost parallel experimentation to take place in the field of neurochemical monitoring. In addition, this device will increase the accessibility of neurochemical sensing, providing advanced tools and techniques to more researchers, and facilitating widespread exploration of the field of neurodynamics.

Development of a miniature device for emerging deep brain stimulation paradigms.

Deep brain stimulation (DBS) is a neuromodulatory approach for treatment of several neurological and psychiatric disorders. A new focus on optimising the waveforms used for stimulation is emerging regarding the mechanism of DBS treatment. Many existing DBS devices offer only a limited set of predefined waveforms, mainly rectangular, and hence are inapt for exploring the emerging paradigm. Advances in clinical DBS are moving towards incorporating new stimulation parameters, yet we remain limited in our capacity to test these in animal models, arguably a critical first step. Accordingly, there is a need for the development of new miniature, low-power devices to enable investigation into the new DBS paradigms in preclinical settings. The ideal device would allow for flexibility in the stimulation waveforms, while remaining suitable for chronic, tetherless, biphasic deep brain stimulation. In this work, we elucidate several key parameters in a DBS system, identify gaps in existing solutions, and propose a new device to support preclinical DBS. The device allows for a high degree of flexibility in the output waveform with easily altered shape, frequency, pulse-width and amplitude. The device is suitable for both traditional and modern stimulation schemes, including those using non-rectangular waveforms, as well as delayed feedback schemes. The device incorporates active charge balancing to ensure safe operation, and allows for simple production of custom biphasic waveforms. This custom waveform output is unique in the field of preclinical DBS devices, and could be advantageous in performing future DBS studies investigating new treatment paradigms. This tetherless device can be easily and comfortably carried by an animal in a back-mountable configuration. The results of in-vitro tests are presented and discussed.

Surface nanogrooving of carbon microtubes.

Extrusion processing of carbon tubes can be problematic due to their poor interfacial interactions with polymeric matrices. Surface chemical modification of carbon tubes can be utilized to create bonding sites to form networks with polymer chains. However, chemical reactions resulting in intermolecular primary bonding limit processability of extrudate, since they cause unstable rheological behaviour, and thus decrease the stock holding time, which is determinative in extrusion. This study presents a method for the synthesis of carbon microtubes with physically modified surface area to improve the filler and matrix interfacial interactions. The key concept is the formation of a nanogrooved topography, through acoustic cavitation on the surface of processing fibres. The effect of nanogrooving on roughness parameters is described, along with the role of surface modified carbon tubes on rheological behaviour, homogeneity, and coherency of extrudate. The measurements showed that nanogrooving increases the surface area of carbon microtubes, as a result, die swelling of the extrudate is reduced. Furthermore, after solidification, the mechanical strength of composite is reinforced due to stronger interactions between nanogrooved carbon tubes and polymer matrix.

An investigation into closed-loop treatment of neurological disorders based on sensing mitochondrial dysfunction.

Dynamic feedback based closed-loop medical devices offer a number of advantages for treatment of heterogeneous neurological conditions. Closed-loop devices integrate a level of neurobiological feedback, which allows for real-time adjustments to be made with the overarching aim of improving treatment efficacy and minimizing risks for adverse events. One target which has not been extensively explored as a potential feedback component in closed-loop therapies is mitochondrial function. Several neurodegenerative and psychiatric disorders including Parkinson's disease, Major Depressive disorder and Bipolar disorder have been linked to perturbations in the mitochondrial respiratory chain. This paper investigates the potential to monitor this mitochondrial function as a method of feedback for closed-loop neuromodulation treatments. A generic model of the closed-loop treatment is developed to describe the high-level functions of any system designed to control neural function based on mitochondrial response to stimulation, simplifying comparison and future meta-analysis. This model has four key functional components including: a sensor, signal manipulator, controller and effector. Each of these components are described and several potential technologies for each are investigated. While some of these candidate technologies are quite mature, there are still technological gaps remaining. The field of closed-loop medical devices is rapidly evolving, and whilst there is a lot of interest in this area, widespread adoption has not yet been achieved due to several remaining technological hurdles. However, the significant therapeutic benefits offered by this technology mean that this will be an active area for research for years to come.

Nucleotide pyrophosphatase employs a P-loop-like motif to enhance catalytic power and NDP/NTP discrimination.

We investigated the potential (d)NDP/(d)NTP discrimination mechanisms in nucleotide pyrophosphatases. Here, we report that dUTPase, an essential nucleotide pyrophosphatase, uses a C-terminal P-loop-like sequence in a unique mechanism for substrate discrimination and efficient hydrolysis. Our spectroscopy and transient kinetics results on human dUTPase mutants combined with previous structural studies indicate that (i) H-bond interactions between the γ-phosphate and the P-loop-like motif V promote the catalytically competent conformation of the reaction center at the α-phosphate group; (ii) these interactions accelerate the chemical step of the kinetic cycle and that (iii) hydrolysis occurs very slowly or not at all in the absence of the γ-phosphate--motif V interactions, i.e., in dUDP, dUDP.BeFx, or in the motif V-deleted mutant. The physiological role of dUTPase is to set cellular dUTPdTTP ratios and prevent injurious uracil incorporation into DNA. Based upon comparison with related pyrophosphate generating (d)NTPases, we propose that the unusual use of a P-loop-like motif enables dUTPases to achieve efficient catalysis of dUTP hydrolysis and efficient discrimination against dUDP at the same time. These specifics might have been advantageous on the appearance of uracil-DNA repair. The similarities and differences between dUTPase motif V and the P-loop (or Walker A sequence) commonly featured by ATP- and GTPases offer insight into functional adaptation to various nucleotide hydrolysis tasks.

Social Cognition and Interaction Training (SCIT) for inpatients with schizophrenia spectrum disorders: preliminary findings.

Individuals with schizophrenia exhibit consistent deficits in social cognition such as emotion perception, attributional style, and theory of mind, which may be targets of psychosocial treatments. Previous intervention studies have typically focused on only one aspect of social cognition and have not assessed generalization of treatment to improvements in social functioning. This paper describes preliminary data from a new group-based treatment, Social Cognition and Interaction Training (SCIT), aimed at improving social cognition in schizophrenia. Eighteen inpatients with schizophrenia spectrum disorders completed SCIT and were compared with 10 inpatients who completed a coping skills group. Participants were assessed at pre-test and post-test on measures of emotion and social perception, theory of mind, attributional style (e.g., blame, hostility, and aggression), cognitive flexibility, and social relationships. We also collected data on the frequency of aggressive incidents on the treatment ward. The results showed that compared to the control group, SCIT participants improved on all of the social cognitive measures and showed better self-reported social relationships and fewer aggressive incidents on the treatment unit at post-test. Importantly, this change was independent of changes in clinical symptoms over time and supports the unique role of SCIT in improving social cognitive deficits in schizophrenia.

The conviction of delusional beliefs scale: reliability and validity.

This study reports on the development of a new measure of delusional belief conviction, the Conviction of Delusional Beliefs Scale (CDBS). Most of the current scales in use assess belief conviction with a single item and primarily reflect the cognitive aspects of conviction. The CDBS represents an improvement over existing scales in that it contains a larger number of test items that can be subjected to psychometric examination. In addition, the CDBS also broadens the concept of belief conviction by incorporating cognitive, emotional, and behavioral items. In the present study, fifty participants with delusions completed the CDBS along with measures of delusional ideation, psychiatric symptomatology, insight, and reading ability. The CDBS showed very good levels of internal consistency and test-retest stability over a six-week period. All of the CDBS items loaded highly on a unitary factor of belief conviction. The CDBS positively correlated with four measures of belief conviction thereby reflecting the convergent validity of the scale. The CDBS was unrelated to other dimensions of delusional ideation, psychiatric symptomatology, insight, and reading ability, which supported the discriminant validity of the scale. The CDBS appears to be a reliable and valid measure of delusional belief conviction that could be used in clinical and research settings.

Informed consent in schizophrenia: the use of cues in the assessment of understanding.

The purpose of this study was to determine if providing cues could facilitate participant understanding for consent form information. Understanding scores were measured in a group of participants diagnosed with schizophrenia and a control group using cued recognition and uncued recall methods. When understanding was measured with uncued methods, persons with schizophrenia showed lower scores compared to the control group. However, when cues were provided, there was no difference between the two groups on understanding scores, and persons with schizophrenia showed normal levels of understanding. The results suggest that cued methods may be a better alternative to measure participant understanding.