Efficient simulation scheme for spiking neural networks

Nearly all neuronal information processing and inter¬neuronal communication in the brain involves action potentials, or spikes, which drive the short-term synaptic dynamics of neurons, but also their long-term dynamics, via synaptic plasticity. In many brain structures, action potential activity is considered to be sparse. This sparseness of activity has been exploited to reduce the computational cost of large-scale network simulations, through the development of "event-driven" simulation schemes. However, existing event-driven simulations schemes use extremely simplified neuronal models. Here, we design, implement and evaluate critically an event-driven algorithm (EDLUT) that uses pre-calculated lookup tables to characterize synaptic and neuronal dynamics. This approach enables the use of more complex (and realistic) neuronal models or data in representing the neurons, while retaining the advantage of high-speed simulation. We demonstrate the method's application for neurons containing exponential synaptic conductances, thereby implementing shunting inhibition, a phenomenon that is critical to cellular computation. We also introduce an improved two-stage event-queue algorithm, which allows the simulations to scale efficiently to highly-connected networks with arbitrary propagation delays. Finally, the scheme readily accommodates implementation of synaptic plasticity mechanisms that depend upon spike timing, enabling future simulations to explore issues of long-term learning and adaptation in large-scale networks

Advances in Reinforcement Learning

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic

Diffusion tensor imaging and resting state functional connectivity as advanced imaging biomarkers of outcome in infants with hypoxic-ischaemic encephalopathy treated with hypothermia

Therapeutic hypothermia confers significant benefit in term neonates with hypoxic-ischaemic encephalopathy (HIE). However, despite the treatment nearly half of the infants develop an unfavourable outcome. Intensive bench-based and early phase clinical research is focused on identifying treatments that augment hypothermic neuroprotection. Qualified biomarkers are required to test these promising therapies efficiently. This thesis aims to assess advanced magnetic resonance imaging (MRI) techniques, including diffusion tensor imaging (DTI) and resting state functional MRI (fMRI) as imaging biomarkers of outcome in infants with HIE who underwent hypothermic neuroprotection. FA values in the white matter (WM), obtained in the neonatal period and assessed by tract-based spatial statistics (TBSS), correlated with subsequent developmental quotient (DQ). However, TBSS is not suitable to study grey matter (GM), which is the primary site of injury following an acute hypoxic-ischaemic event. Therefore, a neonatal atlas-based automated tissue labelling approach was applied to segment central and cortical grey and whole brain WM. Mean diffusivity (MD) in GM structures, obtained in the neonatal period correlated with subsequent DQ. Although the central GM is the primary site of injury on conventional MRI following HIE; FA within WM tissue labels also correlated to neurodevelopmental performance scores. As DTI does not provide information on functional consequences of brain injury functional sequel of HIE was studied with resting state fMRI. Diminished functional connectivity was demonstrated in infants who suffered HIE, which associated with an unfavourable outcome. The results of this thesis suggest that MD in GM tissue labels and FA either determined within WM tissue labels or analysed with TBSS correlate to subsequent neurodevelopmental performance scores in infants who suffered HIE treated with hypothermia and may be applied as imaging biomarkers of outcome in this population. Although functional connectivity was diminished in infants with HIE, resting state fMRI needs further study to assess its utility as an imaging biomarker following a hypoxic-ischaemic brain injury.Open Acces

Error minimising gradients for improving cerebellar model articulation controller performance

In motion control applications where the desired trajectory velocity exceeds an actuator’s maximum velocity limitations, large position errors will occur between the desired and actual trajectory responses. In these situations standard control approaches cannot predict the output saturation of the actuator and thus the associated error summation cannot be minimised.An adaptive feedforward control solution such as the Cerebellar Model Articulation Controller (CMAC) is able to provide an inherent level of prediction for these situations, moving the system output in the direction of the excessive desired velocity before actuator saturation occurs. However the pre-empting level of a CMAC is not adaptive, and thus the optimal point in time to start moving the system output in the direction of the excessive desired velocity remains unsolved. While the CMAC can adaptively minimise an actuator’s position error, the minimisation of the summation of error over time created by the divergence of the desired and actual trajectory responses requires an additional adaptive level of control.This thesis presents an improved method of training CMACs to minimise the summation of error over time created when the desired trajectory velocity exceeds the actuator’s maximum velocity limitations. This improved method called the Error Minimising Gradient Controller (EMGC) is able to adaptively modify a CMAC’s training signal so that the CMAC will start to move the output of the system in the direction of the excessive desired velocity with an optimised pre-empting level.The EMGC was originally created to minimise the loss of linguistic information conveyed through an actuated series of concatenated hand sign gestures reproducing deafblind sign language. The EMGC concept however is able to be implemented on any system where the error summation associated with excessive desired velocities needs to be minimised, with the EMGC producing an improved output approximation over using a CMAC alone.In this thesis, the EMGC was tested and benchmarked against a feedforward / feedback combined controller using a CMAC and PID controller. The EMGC was tested on an air-muscle actuator for a variety of situations comprising of a position discontinuity in a continuous desired trajectory. Tested situations included various discontinuity magnitudes together with varying approach and departure gradient profiles.Testing demonstrated that the addition of an EMGC can reduce a situation’s error summation magnitude if the base CMAC controller has not already provided a prior enough pre-empting output in the direction of the situation. The addition of an EMGC to a CMAC produces an improved approximation of reproduced motion trajectories, not only minimising position error for a single sampling instance, but also over time for periodic signals

TMS application in both health and disease

Transcranial magnetic stimulation (TMS) can be useful for therapeutic purposes for a variety of clinical conditions. Numerous studies have indicated the potential of this noninvasive brain stimulation technique to recover brain function and to study physiological mechanisms. Following this line, the articles contemplated in this Research Topic show that this field of knowledge is rapidly expanding and considerable advances have been made in the last few years. There are clinical protocols already approved for Depression (and anxiety comorbid with major depressive disorder), Obsessive compulsive Disorder (OCD), migraine headache with aura, and smoking cessation treatment but many studies are concentrating their efforts on extending its application to other diseases, e.g., as a treatment adjuvant. In this Research Topic we have the example of using TMS for pain, post-stroke depression, or smoking cessation, but other diseases/injuries of the central nervous system need attention (e.g., tinnitus or the surprising epilepsy). Further, the potential of TMS in health is being explored, in particular regarding memory enhancement or the mapping of motor control regions, which might also have implications for several diseases. TMS is a non-invasive brain stimulation technique that can be used for modulating brain activation or to study connectivity between brain regions. It has proven efficacy against neurological and neuropsychiatric illnesses but the response to this stimulation is still highly variable. Research works devoted to studying the response variability to TMS, as well as large-scale studies demonstrating its efficacy in different sub-populations, are therefore of utmost importance. In this editorial, we summarize the main findings and viewpoints detailed within each of the 12 contributing articles using TMS for health and/or disease applications.publishe

Promoting and measuring remyelination and neuroprotection in clinical trials of people with multiple sclerosis

The most tractable strategy to delay or prevent the progressive phase of MS is to promote endogenous remyelination; doing so restores nerve conduction and prevents demyelinated axons from degenerating. The rate-limiting stage in this process is differentiation of oligodendrocyte progenitor cells (OPCs) into mature, myelinating, oligodendrocytes. In animals, agonism of the retinoid X receptor (RXR)-γ enhances remyelination in this way. Metformin also promotes remyelination, this time by overcoming an age-associated block to the responsiveness of OPCs to pro-differentiation factors. In this PhD I show that bexarotene, a non-selective agonist of the RXR receptor, promotes remyelination in people with relapsing remitting multiple sclerosis. Converging evidence from electrophysiology and neuroimaging in a phase II clinical trial (CCMR One) demonstrate that this occurs in demyelinated lesions and is greatest in lesions located in grey matter regions of the brain. I additionally conducted analyses which suggest an age-dependency of bexarotene’s remyelinating effect and led a follow-up sub study of the trial participants which showed the treatment effect afforded by bexarotene is sustained, years after treatment. Unfortunately, bexarotene was poorly tolerated, and so the legacy of this trial will likely be one of shaping the framework for future assessments of remyelinating therapies. As such, I designed, obtained funding and secured approvals for a clinical trial to test the remyelinating effect of the combination of metformin with clemastine (CCMR Two), implementing lessons from CCMR One in the trial design; this is due to commence participant recruitment in 2021. In exploring treatments for progressive forms of MS, not limited to the process of remyelination, I worked with the MS Society to develop and implement a rigorous, expert-led, evidence-based approach to the selection of licensed drugs for repurposing and testing in clinical trials of people with progressive MS. I reviewed the preclinical and clinical literature for a list of compounds and condensed these into a database of summary documents. These were presented to a panel of experts and people affected by MS, ultimately leading to four treatments being recommended for immediate testing in progressive MS trials: R-α-lipoic acid, metformin, the combination treatment of R-α-lipoic acid and metformin, and niacin. Regrettably, much of my research has been halted by the COVID-19 pandemic. In this PhD I had additionally sought to evaluate electrophysiological techniques for quantifying remyelination and neuroprotection – multifocal VEP and saccadometry – in cohorts of people with MS and in the setting of the CCMR Two trial. Instead, when these studies were delayed, I embraced an opportunity to help the Cambridge COVID-19 research effort, working on the RECOVERY trial in the first wave, and leading my own project to analyse enrolment to treatment trials, ultimately describing the barriers to, and implications of, low recruitment rates in advance of the subsequent waves. Consequently, further exploratory research with electrophysiology and the CCMR Two trial will be the subject of post-doctoral research.Multiple Sclerosis Society of the United Kingdo

Brain-muscle axis during treatment of minimal hepatic encephalopathy with L-ornithine L-aspartate

Abstract Background: Minimal Hepatic Encephalopathy (MHE) is a fluctuant cognitive deficit, and a common complication of cirrhosis, with significant health and socioeconomic consequences. Oral L-Ornithine L-Aspartate (LOLA) has been proposed to treat MHE but mechanism and efficacy are unknown. This study hypothesises LOLA treatment will correlate with improvements in: 1) Cognitive function (primary endpoints) 2) Relation to Brain-muscle axis (secondary endpoints) Design and methods: This double-blinded placebo-controlled trial included 34 patients (LOLA n=14, placebo n=20) over 12 weeks. All underwent psychometric testing (PHES, CogstateTM, Stroop, Short Form-36). Secondary endpoints included brain volume, white matter microstructure, brain function (proton MR spectroscopy/ functional MRI); muscle power (handgrip strength, 6-minute-walk-test); anthropometry (upper limb skinfold); muscle metabolome (lateral vastus muscle biopsy LC-MS analysis). Results: Significantly more patients receiving LOLA reported improved energy levels, specifically in Vitality (SF36 subdomain). No differences in PHES, Cogstate and Stroop test performance occured. Change-in-biceps skinfold thickness demonstrated significant gain with LOLA compared to placebo, without differences in power. LC-MS experiments were not discriminatory. Whole Brain differences in FA and RD suggested reduced brain oedema (subcortical volume reduction and global white matter changes). No significant group differences in fMRI task/ resting activation were seen. Spectroscopy of ACC showed significantly higher unresolved glutamine-glutamate (Glx) complex levels with LOLA, also correlating with increased PPI use, and may represent LOLA-driven increased Krebs-cycling or a function of altered gut microbiome. Conclusion: No cognitive benefits were demonstrated. Improved quality of life measures maybe a nutritional consequence also relating to increased biceps skinfold thickness with LOLA. Effects on brain oedema are postulated. Future studies need higher powering to allow subanalysis by aetiology, and smaller voxels at basal ganglia are recommended. Attempts to replicate rising ACC Glx with LOLA and regions of interest identified on fMRI subanalysis may be fruitful.Open Acces