4,890 research outputs found

    Increasing striatal dopamine release through repeated bouts of theta burst transcranial magnetic stimulation of the left dorsolateral prefrontal cortex. A 18F-desmethoxyfallypride positron emission tomography study

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    IntroductionTranscranial Magnetic Stimulation (TMS) can modulate fronto-striatal connectivity in the human brain. Here Positron Emission Tomography (PET) and neuro-navigated TMS were combined to investigate the dynamics of the fronto-striatal connectivity in the human brain. Employing 18F-DesmethoxyFallypride (DMFP) – a Dopamine receptor-antagonist – the release of endogenous dopamine in the striatum in response to time-spaced repeated bouts of excitatory, intermittent theta burst stimulation (iTBS) of the Left-Dorsolateral Prefrontal Cortex (L-DLPFC) was measured.Methods23 healthy participants underwent two PET sessions, each one with four blocks of iTBS separated by 30 minutes: sham (control) and verum (90% of individual resting motor threshold). Receptor Binding Ratios were collected for sham and verum sessions across 37 time frames (about 130 minutes) in striatal sub-regions (Caudate nucleus and Putamen).ResultsVerum iTBS increased the dopamine release in striatal sub-regions, relative to sham iTBS. Dopamine levels in the verum session increased progressively across the time frames until frame number 28 (approximately 85 minutes after the start of the session and after three iTBS bouts) and then essentially remained unchanged until the end of the session.ConclusionResults suggest that the short-timed iTBS protocol performed in time-spaced blocks can effectively induce a dynamic dose dependent increase in dopaminergic fronto-striatal connectivity. This scheme could provide an alternative to unpleasant and distressing, long stimulation protocols in experimental and therapeutic settings. Specifically, it was demonstrated that three repeated bouts of iTBS, spaced by short intervals, achieve larger effects than one single stimulation. This finding has implications for the planning of therapeutic interventions, for example, treatment of major depression

    Advancing the Study of Functional Connectome Development

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    A better understanding of functional changes in the brain across childhood offers the potential to better support neurodevelopmental and learning challenges. However, neuroimaging tools such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are vulnerable to head motion and other artifacts, and studies have had limited reproducibility. To accomplish research goals, we need to understand the reliability and validity of data collection, processing, and analysis strategies. Neuroimaging datasets contain individually unique information, but identifiability is reduced by noise or lack of signal, suggesting it can be a measure of validity. The goal of this thesis was to use identifiability to benchmark different methodologies, and describe how identifiability associates with age across early childhood. I first compared several different fMRI preprocessing pipelines for data collected from young children. Preprocessing techniques are often controversial due to specific drawbacks and have typically been assessed with adult datasets, which have much less head motion. I found benefits to the use of global signal regression and temporal censoring, but overly strict censoring can impact identifiability, suggesting noise removed must be balanced against signal retained. I also compared several different EEG measures of functional connectivity (FC). EEG can be vulnerable to volume conduction artifacts that can be mitigated by only considering shared information with a time delay between signals. However, I found that mitigation strategies result in lower identifiability, suggesting that while removing confounding noise they also discard substantial signal of interest. Individual experiences may shape development in an individually unique way, which is supported by evidence that adults have more individually identifiable patterns of FC than children. I found that across 4 to 8 years of age, identifiability increased via increased self-stability, but without changes in similarity-to-others. In the absence of ground truth, it is difficult to argue for or against analysis decisions based solely on a theoretical framework and need to also be validated. My work highlights the importance of not thinking about techniques in a valid-invalid dichotomy; certain methods may be sub-optimal while still being preferable to alternatives if they better manage the trade off between noise removed and signal retained

    Friction of biomechanical interfaces

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    Modular architecture facilitates noise-driven control of synchrony in neuronal networks

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    H.Y., A.H.-I., and S.S. acknowledge MEXT Grant-in-Aid for Transformative Research Areas (B) “Multicellular Neurobiocomputing” (21H05164), JSPS KAKENHI (18H03325, 19H00846, 20H02194, 20K20550, 22H03657, 22K19821, 22KK0177, and 23H03489), JST-PRESTO (JMPJPR18MB), JST-CREST (JPMJCR19K3), and Tohoku University RIEC Cooperative Research Project Program for financial support. F.P.S., V.P., and J.Z. received support from the Max-Planck-Society. F.P.S. acknowledges funding by SMARTSTART, the joint training program in computational neuroscience by the VolkswagenStiftung and the Bernstein Network. F.P.S. and V.P. were funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), SFB-1528–Cognition of Interaction. V.P. was supported by the DFG under Germany’s Excellence Strategy EXC 2067/1- 390729940. V.B. and A.L. were supported by a Sofja Kovalevskaja Award from the Alexander von Humboldt Foundation, endowed by the Federal Ministry of Education and Research. A.L. is a member of the Machine Learning Cluster of Excellence EXC 2064/1- 39072764. M.A.M. acknowledges the Spanish Ministry and Agencia Estatal de investigación (AEI) through Project of I + D + i (PID2020-113681GB-I00), financed by MICIN/AEI/10.13039/501100011033 and FEDER “A way to make Europe”, and the Consejería de Conocimiento, Investigación Universidad, Junta de Andalucía and European Regional Development Fund (P20-00173) for financial support. J.Z. received financial support from the Joachim Herz Stiftung. J.S. acknowledges Horizon 2020 Future and Emerging Technologies (grant agreement 964877-NEUChiP), Ministerio de Ciencia, Innovación y Universidades (PID2019-108842GB-C21), and Departament de Recerca i Universitats, Generalitat de Catalunya (2017-SGR-1061 and 2021-SGR-00450) for financial support.Supplementary Materials This PDF file includes: Supplementary Text, file:///D:/Modular-architecture-facilitates-.pdfHigh-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.D+i: P20-00173, PID2020-113681GB-I00Innovación y Universidades PID2019-108842GB-C21Horizon2020 Future and Emerging Technologies 964877-NEUChiPMinisterio de Ciencia, Innovación y Universidades (PID2019-108842GB-C21)Departament de Recerca i Universitats, Generalitat de Catalunya (2017-SGR-1061, 2021-SGR-00450)MICIN/AEI/10.13039/501100011033FEDER “A way to make Europe”Junta de AndalucíaEuropean Regional Development Fun

    The 2023 wearable photoplethysmography roadmap

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    Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology

    A novel behavioural paradigm for characterising anticipatory postural adjustments in mice

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    Daily we use purposeful, voluntary movements to interact with our environment. These movements demand and cause our body to experience a weight redistribution, i.e., anticipatory postural adjustments (APAs), and it’s the appropriate employment of these APAs that allows us to complete said voluntary movements without falling over or losing our equilibrium. The literature suggests that for humans, monkeys, and several quadrupeds, APAs are crucial at initiation and during movement. However, research has been somewhat limited due to the lack of behavioural paradigms that would allow for a better understanding into the neural circuitry involved with APAs. Given the widespread availability of genetic tools and advanced viral techniques in mice I focused my efforts in developing a novel behavioral paradigm for this species. The first chapters detail the reasoning behind the development of this novel behavioural paradigm while also providing a complete description of the different components and their functions. Later chapters use the custom-designed setup to characterise mouse APAs, incorporating various recording approaches designed to quantify APAs and compare them to those described in prior work, highlighting possible interspecifies similarities and differences. Additionally, I briefly discuss the potential neural circuitry of APAs informed by my own data and research that has been done in different animals, providing a comprehensive overview of APAs in mice

    Mathematical modelling and analysis of soil and plant root interactions

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    The influence of plants on soil water transport is a relevant factor in a number of ecological contexts. Examples include: the resistance of crops to drought, the prevention of floods and the protection of soils from erosion. There exists strong experimental evidence that interactions between soil and plant roots change a soil’s hydraulic properties. Nevertheless, it remains a challenge to anticipate the impact of specific root traits on the infiltration of water through soil. In an attempt to address the issue above, this thesis presents modifications of Richards’ equation—the classic model for water transport through soil—to incorporate some effects that root systems are known to have on soil hydraulic properties. First, a model is developed that incorporates the phenomenon of root-oriented preferential flow. Using the finite element method and Bayesian optimisation, a pipeline is developed to calibrate the model against experimental data. Moreover, it is shown how existing root architectural models can be used in conjunction with our model to investigate the influence that root system traits have on infiltration and water uptake. Results suggest that this modification of Richards’ equation leads to improved agreement of simulations with reference pore water pressure profiles, which are derived from experimental data regarding the hydraulic conductivity of vegetated soils. Following this, the developed model is used to obtain simulations of various infiltration scenarios. These reveal that, up to a critical point, increasing preferential flow strength reduces water loss from the rooted zone. Furthermore, evidence is provided to suggest that root systems with a reduced gravitropic response allow a greater retention of water in the rooted zone following precipitation and, hence, are among the most effective at delaying the onset of water deficits. In another case, an alternative modification is proposed whereby Richards’ equation is coupled with an equation for water transport through roots. This model accounts for root water uptake and hydraulic lift through a Neumann boundary condition at the root-soil interface. By using the methods of Rothe and Galerkin, existence of a solution to this coupled model is then established. Uniqueness is shown by Kruzkov’s variable doubling method, but applied only in time.UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/L016508/01Scottish Funding Counci
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