30 research outputs found

    Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain

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    Magnetoencephalography (MEG) is a noninvasive technique for investigating neuronal activity in the living human brain. The time resolution of the method is better than 1 ms and the spatial discrimination is, under favorable circumstances, 2-3 mm for sources in the cerebral cortex. In MEG studies, the weak 10 fT-1 pT magnetic fields produced by electric currents flowing in neurons are measured with multichannel SQUID (superconducting quantum interference device) gradiometers. The sites in the cerebral cortex that are activated by a stimulus can be found from the detected magnetic-field distribution, provided that appropriate assumptions about the source render the solution of the inverse problem unique. Many interesting properties of the working human brain can be studied, including spontaneous activity and signal processing following external stimuli. For clinical purposes, determination of the locations of epileptic foci is of interest. The authors begin with a general introduction and a short discussion of the neural basis of MEG. The mathematical theory of the method is then explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices. Finally, several MEG experiments performed in the authors' laboratory are described, covering studies of evoked responses and of spontaneous activity in both healthy and diseased brains. Many MEG studies by other groups are discussed briefly as well.Peer reviewe

    VLSI Circuits for Bidirectional Neural Interfaces

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    Medical devices that deliver electrical stimulation to neural tissue are important clinical tools that can augment or replace pharmacological therapies. The success of such devices has led to an explosion of interest in the field, termed neuromodulation, with a diverse set of disorders being targeted for device-based treatment. Nevertheless, a large degree of uncertainty surrounds how and why these devices are effective. This uncertainty limits the ability to optimize therapy and gives rise to deleterious side effects. An emerging approach to improve neuromodulation efficacy and to better understand its mechanisms is to record bioelectric activity during stimulation. Understanding how stimulation affects electrophysiology can provide insights into disease, and also provides a feedback signal to autonomously tune stimulation parameters to improve efficacy or decrease side-effects. The aims of this work were taken up to advance the state-of-the-art in neuro-interface technology to enable closed-loop neuromodulation therapies. Long term monitoring of neuronal activity in awake and behaving subjects can provide critical insights into brain dynamics that can inform system-level design of closed-loop neuromodulation systems. Thus, first we designed a system that wirelessly telemetered electrocorticography signals from awake-behaving rats. We hypothesized that such a system could be useful for detecting sporadic but clinically relevant electrophysiological events. In an 18-hour, overnight recording, seizure activity was detected in a pre-clinical rodent model of global ischemic brain injury. We subsequently turned to the design of neurostimulation circuits. Three critical features of neurostimulation devices are safety, programmability, and specificity. We conceived and implemented a neurostimulator architecture that utilizes a compact on-chip circuit for charge balancing (safety), digital-to-analog converter calibration (programmability) and current steering (specificity). Charge balancing accuracy was measured at better than 0.3%, the digital-to-analog converters achieved 8-bit resolution, and physiological effects of current steering stimulation were demonstrated in an anesthetized rat. Lastly, to implement a bidirectional neural interface, both the recording and stimulation circuits were fabricated on a single chip. In doing so, we implemented a low noise, ultra-low power recording front end with a high dynamic range. The recording circuits achieved a signal-to-noise ratio of 58 dB and a spurious-free dynamic range of better than 70 dB, while consuming 5.5 μW per channel. We demonstrated bidirectional operation of the chip by recording cardiac modulation induced through vagus nerve stimulation, and demonstrated closed-loop control of cardiac rhythm

    Sensing the world through predictions and errors

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    Efficient Schemes for Adaptive Frequency Tracking and their Relevance for EEG and ECG

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    Amplitude and frequency are the two primary features of one-dimensional signals, and thus both are widely utilized to analysis data in numerous fields. While amplitude can be examined directly, frequency requires more elaborate approaches, except in the simplest cases. Consequently, a large number of techniques have been proposed over the years to retrieve information about frequency. The most famous method is probably power spectral density estimation. However, this approach is limited to stationary signals since the temporal information is lost. Time-frequency approaches were developed to tackle the problem of frequency estimation in non-stationary data. Although they can estimate the power of a signal in a given time interval and in a given frequency band, these tools have two drawbacks that make them less valuable in certain situations. First, due to their interdependent time and frequency resolutions, improving the accuracy in one domain means decreasing it in the other one. Second, it is difficult to use this kind of approach to estimate the instantaneous frequency of a specific oscillatory component. A solution to these two limitations is provided by adaptive frequency tracking algorithms. Typically, these algorithms use a time-varying filter (a band-pass or notch filter in most cases) to extract an oscillation, and an adaptive mechanism to estimate its instantaneous frequency. The main objective of the first part of the present thesis is to develop such a scheme for adaptive frequency tracking, the single frequency tracker. This algorithm compares favorably with existing methods for frequency tracking in terms of bias, variance and convergence speed. The most distinguishing feature of this adaptive algorithm is that it maximizes the oscillatory behavior at its output. Furthermore, due to its specific time-varying band-pass filter, it does not introduce any distortion in the extracted component. This scheme is also extended to tackle certain situations, namely the presence of several oscillations in a single signal, the related issue of harmonic components, and the availability of more than one signal with the oscillation of interest. The first extension is aimed at tracking several components simultaneously. The basic idea is to use one tracker to estimate the instantaneous frequency of each oscillation. The second extension uses the additional information contained in several signals to achieve better overall performance. Specifically, it computes separately instantaneous frequency estimates for all available signals which are then combined with weights minimizing the estimation variance. The third extension, which is based on an idea similar to the first one and uses the same weighting procedure as the second one, takes into account the harmonic structure of a signal to improve the estimation performance. A non-causal iterative method for offline processing is also developed in order to enhance an initial frequency trajectory by using future information in addition to past information. Like the single frequency tracker, this method aims at maximizing the oscillatory behavior at the output. Any approach can be used to obtain the initial trajectory. In the second part of this dissertation, the schemes for adaptive frequency tracking developed in the first part are applied to electroencephalographic and electrcardiographic data. In a first study, the single frequency tracker is used to analyze interactions between neuronal oscillations in different frequency bands, known as cross-frequency couplings, during a visual evoked potential experiment with illusory contour stimuli. With this adaptive approach ensuring that meaningful phase information is extracted, the differences in coupling strength between stimuli with and without illusory contours are more clearly highlighted than with traditional methods based on predefined filter-banks. In addition, the adaptive scheme leads to the detection of differences in instantaneous frequency. In a second study, two organization measures are derived from the harmonic extension. They are based on the power repartition in the frequency domain for the first one and on the phase relation between harmonic components for the second one. These measures, computed from the surface electrocardiogram, are shown to help predicting the outcome of catheter ablation of persistent atrial fibrillation. The proposed adaptive frequency tracking schemes are also applied to signals recorded in the field of sport sciences in order to illustrate their potential uses. To summarize, the present thesis introduces several algorithms for adaptive frequency tracking. These algorithms are presented in full detail and they are then applied to practical situations. In particular, they are shown to improve the detection of coupling mechanisms in brain activity and to provide relevant organization measures for atrial fibrillation

    Examining targeted brain stimulation to improve vigilant attention in right-hemispheric stroke

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    Neglect is a disabling neuropsychological syndrome frequently observed following right-hemispheric stroke. Affected individuals present with attentional deficits, ranging from a difficulty in orienting towards the contralesional space to a generalised difficulty with maintaining attention over time. Neglect may be persistent - particularly its non-lateralised component. This thesis focused on investigating the efficacy of a potential treatment involving non-invasive targeted brain stimulation to improve vigilant attention. In a randomised double-blind sham-controlled crossover study, healthy individuals across the lifespan and stroke patients with attentional impairments received real and sham transcranial direct current stimulation (tDCS) whilst performing a vigilance task. A high-definition montage was used to constrain current delivery over the right dorsolateral prefrontal cortex, a key region of the vigilance network. Results show that, at the group level, targeted tDCS improved target detection across all groups. By examining performance across temporal epochs, it was noted that tDCS did not impede worsening of performance with increasing time-on-task. The superiority of tDCS was however found throughout the task, outlasting stimulation delivery. A lesion anatomy study indicated that task performance was related to lesion location rather than volume. In addition, variability in patients' response to treatment was observed and linked to lesion profile, revealing that damage to specific brain regions caused lack of tDCS response. Finally, a concurrent tDCS-fMRI study was conducted to examine brain network response to tDCS. Brain stimulation did not affect local connectivity, but rather influenced functional connectivity within large-scale networks in the contralateral hemisphere. This finding emerged across groups using different analysis approaches, confirming its robustness. This systematic behavioural and imaging investigation supports a role of tDCS to improve non-lateralised deficits of neglect, which could be harnessed in future clinical trials. Furthermore, it sheds light on network response to precise cortical targeting, revealing its widespread effect.Open Acces

    Can the Voluntary Drive to a Paretic Muscle be Estimated from the Myoelectric Signal during Stimulation?

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    Patients with SCI sometimes recover lost function after using FES. This phenomenon, known as the carry-over effect, is not fully understood. One theory used to explain this mechanism is that electrical stimulation of the peripheral nerve causes antidromic action potentials to reach the anterior horn cells in time with the patient’s voluntary effort. This may reinforce the motor pathways and consequently restore voluntary control. However, the theory has never been properly tested and testing requires a method of measuring the voluntary drive. This project aims to find out whether it is possible to estimate the voluntary drive from measured myoelectric signals. The project is based on an FES cycling system with the ability to adjust the stimulation intensity relating to the corresponding voluntary drive. In paretic muscles, the weak voluntary contraction produces an EMG response. The EMG signal cannot be used directly as an indication of the voluntary drive because of the presence of stimulus artefact and reflexes. Two methods were investigated to estimate the voluntary drive. A time domain method was tested using RMS EMG extracted from a range of time windows following the stimulation pulse. This approach was unsatisfactory because the large variations seen in the RMS EMG amplitudes for the same power output as well as the low sensitivity of it to the change of power output. A frequency domain approach was then tested using coherence between co-contracting muscles. It was encouraging to see that the area under the coherence curve in the β band reflected changes in the power output level. However, further tests showed that this area was also greatly influenced by exercise time, becoming unpredictable after 3 minutes. In conclusion, neither of the two methods of using the myoelectric signal from muscles under stimulation is practical for the estimation of voluntary drive

    Serotonergic modulation of the ventral pallidum by 5HT1A, 5HT5A, 5HT7 AND 5HT2C receptors

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    Introduction: Serotonin's involvement in reward processing is controversial. The large number of serotonin receptor sub-types and their individual and unique contributions have been difficult to dissect out, yet understanding how specific serotonin receptor sub-types contribute to its effects on areas associated with reward processing is an essential step. Methods: The current study used multi-electrode arrays and acute slice preparations to examine the effects of serotonin on ventral pallidum (VP) neurons. Approach for statistical analysis: extracellular recordings were spike sorted using template matching and principal components analysis, Consecutive inter-spike intervals were then compared over periods of 1200 seconds for each treatment condition using a student’s t test. Results and conclusions: Our data suggests that excitatory responses to serotonin application are pre-synaptic in origin as blocking synaptic transmission with low-calcium aCSF abolished these responses. Our data also suggests that 5HT1a, 5HT5a and 5HT7 receptors contribute to this effect, potentially forming an oligomeric complex, as 5HT1a antagonists completely abolished excitatory responses to serotonin application, while 5HT5a and 5HT7 only reduced the magnitude of excitatory responses to serotonin. 5HT2c receptors were the only serotonin receptor sub-type tested that elicited inhibitory responses to serotonin application in the VP. These findings, combined with our previous data outlining the mechanisms underpinning dopamine's effects in the VP, provide key information, which will allow future research to fully examine the interplay between serotonin and dopamine in the VP. Investigation of dopamine and serotonins interaction may provide vital insights into our understanding of the VP's involvement in reward processing. It may also contribute to our understanding of how drugs of abuse, such as cocaine, may hijack these mechanisms in the VP resulting in sensitization to drugs of abuse

    Multifunctional photoacoustic materials for neural engineering

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    Understanding the complex information transfer process of our nervous system is one of the most urgent needs in the biomedical community. Neuromodulation is a technique that can artificially influence or modulate the activity of the target neurons. It's an inevitable tool in both the neuroscience study but also the clinical treatment of neurological diseases. The conventional method for neural modulation is the electrical stimulation using implantable electrodes. However, its intrinsic current leakage problem is an obstacle for further improving its performance in clinical scenarios because of the finite spatial resolution and recording artifacts. In general, an ideal method should be able to modulate neural activities with a high spatial, temporal and functionality specificity but without biocompatibility and reliability issues even in long term. Photoacoustic stimulation is an emerging light-mediated, non-genetic neural modulation method with high spatiotemporal resolution. Multiple devices have been designed in the past few years. But there are still several gaps to be filled to further expand its applications. One is the material mismatch, and another is that more function is needed, for example the capability of simultaneous recording. My research focused on the design and development of two new types of photoacoustic materials to expand the use of photoacoustic stimulation. A soft hydrogel film and a multifunctional fiber-based emitter for photoacoustic neuromodulation have been developed in my Ph.D. research. The study on these materials increased our knowledge to photoacoustic neurostimulation, also help us to investigate the effect of photoacoustic neuromodulation in the treatment of neurological and neurodegenerative diseases

    Immunohistochemical and electrophysiological investigation of E/I balance alterations in animal models of frontotemporal dementia

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    Behavioural variant frontotemporal dementia (bvFTD) is a neurodegenerative disease characterised by changes in behaviour. Apathy, behavioural disinhibition and stereotyped behaviours are the first symptoms to appear and all have a basis in reward and pleasure deficits. The ventral striatum and ventral regions of the globus pallidus are involved in reward and pleasure. It is therefore reasonable to suggest alterations in these regions may underpin bvFTD. One postulated contributory factor is alteration in E/I balance in striatal regions. GABAergic interneurons play a role in E/I balance, acting as local inhibitory brakes, they are therefore a rational target for research investigating early biological predictors of bvFTD. To investigate this, we will carry out immunohistochemical staining for GABAergic interneurons (parvalbumin and neuronal nitric oxide synthase) in striatal regions of brains taken from CHMP2B mice, a validated animal model of bvFTD. We hypothesise that there will be fewer GABAergic interneurons in the striatum which may lead to ‘reward-seeking’ behaviour in bvFTD. This will also enable us to investigate any preclinical alterations in interneuron expression within this region. Results will be analysed using a mixed ANOVA and if significant, post hoc t-tests will be used. The second part of our study will involve extracellular recordings from CHMP2B mouse brains using a multi-electrode array (MEA). This will enable us to determine if there are alterations in local field potentials (LFP) in preclinical and symptomatic animals. We will also be able to see if neuromodulators such as serotonin and dopamine effect LFPs after bath application. We will develop slice preparations to preserve pathways between the ventral tegmental area and the ventral pallidum, an output structure of the striatum, and the dorsal raphe nucleus and the VP. Using the MEA we will stimulate an endogenous release of dopamine and serotonin using the slice preparations as described above. This will enable us to see if there are any changes in LFPs after endogenous release of neuromodulators. We hypothesise there will be an increase in LFPs due to loss of GABAergic interneurons
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