Tipu Z Aziz

University Pompeu Fabra, Barcino, Catalonia, Spain

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Publications (290)1140.83 Total impact

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    ABSTRACT: Introduction & objectives: Adaptive deep brain stimulation (aDBS) uses feedback from brain signals to guide stimulation. A recent acute trial of unilateral aDBS showed that aDBS can lead to substantial improvements in contralateral hemibody Unified Parkinson's Disease Rating Scale (UPDRS) motor scores and may be superior to conventional continuous DBS in Parkinson's disease (PD). We test whether potential benefits are retained with bilateral aDBS and in the face of concurrent medication. Methods: We applied bilateral aDBS in 4 patients with PD undergoing DBS of the subthalamic nucleus. aDBS was delivered bilaterally with independent triggering of stimulation according to the amplitude of β activity at the corresponding electrode. Mean stimulation voltage was 3.0±0.1 volts. Motor assessments consisted of double-blinded video-taped motor UPDRS scores that included both limb and axial features. Results: UPDRS scores were 43% (p=0.04; Cohen's d=1.62) better with aDBS than without stimulation. Motor improvement with aDBS occurred despite an average time on stimulation (ToS) of only 45%. Levodopa was well tolerated during aDBS and led to further reductions in ToS. Conclusion: Bilateral aDBS can improve both axial and limb symptoms and can track the need for stimulation across drug states.
    Journal of neurology, neurosurgery, and psychiatry 10/2015; DOI:10.1136/jnnp-2015-310972 · 6.81 Impact Factor
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    ABSTRACT: The frontal cortex and basal ganglia form a set of parallel but mostly segregated circuits called cortico-basal ganglia loops. The oculomotor loop controls eye movements and can direct relatively simple movements, such as reflexive prosaccades, without external help but needs input from “higher” loops for more complex behaviors. The antisaccade task requires the dorsolateral prefrontal cortex, which is part of the prefrontal loop. Information flows from prefrontal to oculomotor circuits in the striatum, and directional errors in this task can be considered a measure of failure of prefrontal control over the oculomotor loop. The antisaccadic error rate (AER) is increased in Parkinson’s disease (PD). Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has no effect on the AER, but a previous case suggested that DBS of the globus pallidus interna (GPi) might. Our aim was to compare the effects of STN DBS and GPi DBS on the AER. We tested eye movements in 14 human DBS atients and 10 controls. GPiDBS substantially reduced the AER, restoring lost higher control over oculomotor function. Interloop information flow involves striatal neurons that receive cortical input and project to pallidum. They are normally silentwhenquiescent, but inPDthey fire randomly, creating noise thatmayaccount for the degradation in interloop control. The reduced AER with GPi DBS could be explained by retrograde stimulation of striatopallidal axons with consequent activation of inhibitory collaterals and reduction in background striatal firing rates. This study may help explain aspects of PD pathophysiology and the mechanism of action of GPi DBS.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 09/2015; DOI:10.1523/JNEUROSCI.2317-15.2015 · 6.34 Impact Factor
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    ABSTRACT: Parkinsons disease is a complex neurodegenerative disorder for which patients present many symptoms, tremor being the main one. In advanced stages of the disease, Deep Brain Stimulation is a generalized therapy which can significantly improve the motor symptoms. However despite its beneficial effects on treating the symptomatology, the technique can be improved. One of its main limitations is that the parameters are fixed, and the stimulation is provided uninterruptedly, not taking into account any fluctuation in the patients state. A closed-loop system which provides stimulation by demand would adjust the stimulation to the variations in the state of the patient, stimulating only when it is necessary. It would not only perform a more intelligent stimulation, capable of adapting to the changes in real time, but also extending the devices battery life, thereby avoiding surgical interventions. In this work we design a tool that learns to recognize the principal symptom of Parkinsons disease and particularly the tremor. The goal of the designed system is to detect the moments the patient is suffering from a tremor episode and consequently to decide whether stimulation is needed or not. For that, local field potentials were recorded in the subthalamic nucleus of ten Parkinsonian patients, who were diagnosed with tremor-dominant Parkinsons disease and who underwent surgery for the implantation of a neurostimulator. Electromyographic activity in the forearm was simultaneously recorded, and the relation between both signals was evaluated using two different synchronization measures. The results of evaluating the synchronization indexes on each moment represent the inputs to the designed system. Finally, a fuzzy inference system was applied with the goal of identifying tremor episodes. Results are favourable, reaching accuracies of higher 98.7 % in 70 % of the patients.
    Journal of Medical Systems 09/2015; 39(11):155. DOI:10.1007/s10916-015-0328-x · 2.21 Impact Factor
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    K A Mamun · M Mace · M E Lutman · J Stein · X Liu · T Aziz · R Vaidyanathan · S Wang ·
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    ABSTRACT: Correlating electrical activity within the human brain to movement is essential for developing and refining interventions (e.g. deep brain stimulation (DBS)) to treat central nervous system disorders. It also serves as a basis for next generation brain-machine interfaces (BMIs). This study highlights a new decoding strategy for capturing movement and its corresponding laterality from deep brain local field potentials (LFPs). LFPs were recorded with surgically implanted electrodes from the subthalamic nucleus or globus pallidus interna in twelve patients with Parkinson's disease or dystonia during a visually cued finger-clicking task. We introduce a method to extract frequency dependent neural synchronization and inter-hemispheric connectivity features based upon wavelet packet transform (WPT) and Granger causality approaches. A novel weighted sequential feature selection algorithm has been developed to select optimal feature subsets through a feature contribution measure. This is particularly useful when faced with limited trials of high dimensionality data as it enables estimation of feature importance during the decoding process. This novel approach was able to accurately and informatively decode movement related behaviours from the recorded LFP activity. An average accuracy of 99.8% was achieved for movement identification, whilst subsequent laterality classification was 81.5%. Feature contribution analysis highlighted stronger contralateral causal driving between the basal ganglia hemispheres compared to ipsilateral driving, with causality measures considerably improving laterality discrimination. These findings demonstrate optimally selected neural synchronization alongside causality measures related to inter-hemispheric connectivity can provide an effective control signal for augmenting adaptive BMIs. In the case of DBS patients, acquiring such signals requires no additional surgery whilst providing a relatively stable and computationally inexpensive control signal. This has the potential to extend invasive BMI, based on recordings within the motor cortex, by providing additional information from subcortical regions.
    Journal of Neural Engineering 08/2015; 12(5-5):056011. DOI:10.1088/1741-2560/12/5/056011 · 3.30 Impact Factor
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    ABSTRACT: It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.
    Frontiers in Behavioral Neuroscience 06/2015; 9. DOI:10.3389/fnbeh.2015.00167 · 3.27 Impact Factor
  • Arnar Astradsson · Tipu Z Aziz ·
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    ABSTRACT: Introduction: The mean age of onset of Parkinson's disease is about 65 years, with a median time of 9 years between diagnosis and death. Methods and outcomes: We conducted a systematic review and aimed to answer the following clinical question: What are the effects of fetal cell or stem cell-derived therapy in people with Parkinson's disease? We searched: Medline, Embase, The Cochrane Library and other important databases up to September 2014 (Clinical Evidence reviews are updated periodically; please check our website for the most up-to-date version of this review). We included harms alerts from relevant organisations such as the US Food and Drug Administration (FDA) and the UK Medicines and Healthcare products Regulatory Agency (MHRA). Results: We found two studies that met our inclusion criteria. We performed a GRADE evaluation of the quality of evidence for interventions. Conclusions: In this systematic review we present information relating to the effectiveness and safety of the following interventions: fetal cell therapy versus deep brain stimulation; fetal cell therapy versus sham surgery; stem cell-derived therapy versus deep brain stimulation; stem cell-derived therapy versus sham surgery.
    Clinical evidence 04/2015; 2015.
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    ABSTRACT: Rest tremor is a cardinal symptom of Parkinson's disease (PD), and is readily suppressed by deep brain stimulation (DBS) of the subthalamic nucleus (STN). The therapeutic effect of the latter on bradykinesia and rigidity has been associated with the suppression of exaggerated beta (13-30 Hz) band synchronization in the vicinity of the stimulating electrode, but there is no correlation between beta suppression and tremor amplitude. In the present study, we investigate whether tremor suppression is related to suppression of activities at other frequencies. We recorded hand tremor and contralateral local field potential (LFP) activity from DBS electrodes during stimulation of the STN in 15 hemispheres in 11 patients with PD. DBS was applied with increasing voltages starting at 0.5 V until tremor suppression was achieved or until 4.5 V was reached. Tremor was reduced to 48.9% ± 10.9% of that without DBS once stimulation reached 2.5-3 V (t14 = -4.667, p < 0.001). There was a parallel suppression of low gamma (31-45 Hz) power to 92.5% ± 3% (t14 = -2.348, p = 0.034). This was not seen over a band containing tremor frequencies and their harmonic (4-12 Hz), or over the beta band. Moreover, low gamma power correlated with tremor severity (mean r = 0.43 ± 0.14, p = 0.008) within subjects. This was not the case for LFP power in the other two bands. Our findings support a relationship between low gamma oscillations and PD tremor, and reinforce the principle that the subthalamic LFP is a rich signal that may contain information about the severity of multiple different Parkinsonian features. © 2015 The Authors. Neuromodulation: Technology at the Neural Interface published by Wiley Periodicals, Inc. on behalf of International Neuromodulation Society.
    Neuromodulation 04/2015; 18(5). DOI:10.1111/ner.12297 · 2.70 Impact Factor
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    ABSTRACT: Local field potential (LFP) recordings from patients with deep brain stimulation electrodes in the basal ganglia have suggested that frequency-specific activities correlate with force or effort, but previous studies have not been able to disambiguate the two. Here, we dissociated effort from actual force generated by contrasting the force generation of different fingers while recording LFP activity from the subthalamic nucleus (STN) in patients with Parkinson's disease who had undergone functional surgery. Patients were studied while on their normal dopaminergic medication. We investigated the relationship between frequency-specific oscillatory activity in the STN and voluntary flexion of either the index or little finger at different effort levels. At each tested effort level (10%, 25%, and 40% of the maximal voluntary contraction force of each individual finger), the index finger generated larger force than the little finger. Movement-related suppression of beta-band power in the STN LFP was significantly modulated by effort, but not by which finger was used, suggesting that the beta suppression in the STN LFP during sustained contraction serves as a proxy for effort. The absolute force scaled with beta power suppression, but with the scaling determined by the maximal voluntary contraction force of the motor effector. Our results argue against the hypothesis that the basal ganglia are directly involved in the parameterization of force during movement and support a role of the STN in the control of motor effort to be attributed to a response. Copyright © 2015 the authors 0270-6474/15/355941-09$15.00/0.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 04/2015; 35(15):5941-9. DOI:10.1523/JNEUROSCI.4609-14.2015 · 6.34 Impact Factor
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    ABSTRACT: Parkinson is a neurodegenerative disease, in which tremor is the main symptom. This paper investigates the use of different classification methods to identify tremors experienced by Parkinsonian patients. Some previous research has focussed tremor analysis on external body signals (e.g., electromyography, accelerometer signals, etc.). Our advantage is that we have access to sub-cortical data, which facilitates the applicability of the obtained results into real medical devices since we are dealing with brain signals directly.
    Biomedical Signal Processing and Control 02/2015; 16. DOI:10.1016/j.bspc.2014.09.006 · 1.42 Impact Factor
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    ABSTRACT: Deep brain stimulation (DBS) is a remarkably effective clinical tool, used primarily for movement disorders. DBS relies on precise targeting of specific brain regions to rebalance the oscillatory behaviour of whole-brain neural networks. Traditionally, DBS targeting has been based upon animal models (such as MPTP for Parkinson’s disease) but has also been the result of serendipity during human lesional neurosurgery. There are, however, no good animal models of psychiatric disorders such as depression and schizophrenia, and progress in this area has been slow. In this paper, we use advanced tractography combined with whole-brain anatomical parcellation to provide a rational foundation for identifying the connectivity ‘fingerprint’ of existing, successful DBS targets. This knowledge can then be used pre-surgically and even potentially for the discovery of novel targets. First, using data from our recent case series of cingulate DBS for patients with treatment-resistant chronic pain, we demonstrate how to identify the structural ‘fingerprints’ of existing successful and unsuccessful DBS targets in terms of their connectivity to other brain regions, as defined by the whole-brain anatomical parcellation. Second, we use a number of different strategies to identify the successful fingerprints of structural connectivity across four patients with successful outcomes compared with two patients with unsuccessful outcomes. This fingerprinting method can potentially be used pre-surgically to account for a patient’s individual connectivity and identify the best DBS target. Ultimately, our novel fingerprinting method could be combined with advanced whole-brain computational modelling of the spontaneous dynamics arising from the structural changes in disease, to provide new insights and potentially new targets for hitherto impenetrable neuropsychiatric disorders.
    New Journal of Physics 01/2015; 17(1-1):015001. DOI:10.1088/1367-2630/17/1/015001 · 3.56 Impact Factor
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    ABSTRACT: Deep brain stimulation (DBS) is approved for idiopathic Parkinson's disease (IPD) but has a poor evidence base in Parkinson-plus syndromes such as multiple system atrophy (MSA). We describe the clinical and neuropathological findings in a man who was initially diagnosed with IPD, in whom DBS was unsuccessful, and in whom MSA was unexpectedly diagnosed at a subsequent autopsy. This case report highlights that DBS is often unsuccessful in MSA and also demonstrates that MSA can masquerade as IPD, which may explain treatment failure in a small group of patients apparently suffering from Parkinson's disease. Additionally, it also presents a case with an unusually long duration of disease prior to death, comparable only to a handful of other cases in the literature.
    Case Reports in Neurology 10/2014; 6(3):232-237. DOI:10.1159/000368571
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    ABSTRACT: Tremor is a cardinal feature of Parkinson's disease and essential tremor, the two most common movement disorders. Yet, the mechanisms underlying tremor generation remain largely unknown. We hypothesized that driving deep brain stimulation electrodes at a frequency closely matching the patient's own tremor frequency should interact with neural activity responsible for tremor, and that the effect of stimulation on tremor should reveal the role of different deep brain stimulation targets in tremor generation. Moreover, tremor responses to stimulation might reveal pathophysiological differences between parkinsonian and essential tremor circuits. Accordingly, we stimulated 15 patients with Parkinson's disease with either thalamic or subthalamic electrodes (13 male and two female patients, age: 50-77 years) and 10 patients with essential tremor with thalamic electrodes (nine male and one female patients, age: 34-74 years). Stimulation at near-to tremor frequency entrained tremor in all three patient groups (ventrolateral thalamic stimulation in Parkinson's disease, P = 0.0078, subthalamic stimulation in Parkinson's disease, P = 0.0312; ventrolateral thalamic stimulation in essential tremor, P = 0.0137; two-tailed paired Wilcoxon signed-rank tests). However, only ventrolateral thalamic stimulation in essential tremor modulated postural tremor amplitude according to the timing of stimulation pulses with respect to the tremor cycle (e.g. P = 0.0002 for tremor amplification, two-tailed Wilcoxon rank sum test). Parkinsonian rest and essential postural tremor severity (i.e. tremor amplitude) differed in their relative tolerance to spontaneous changes in tremor frequency when stimulation was not applied. Specifically, the amplitude of parkinsonian rest tremor remained unchanged despite spontaneous changes in tremor frequency, whereas that of essential postural tremor reduced when tremor frequency departed from median values. Based on these results we conclude that parkinsonian rest tremor is driven by a neural network, which includes the subthalamic nucleus and ventrolateral thalamus and has broad frequency-amplitude tolerance. We propose that it is this tolerance to changes in tremor frequency that dictates that parkinsonian rest tremor may be significantly entrained by low frequency stimulation without stimulation timing-dependent amplitude modulation. In contrast, the circuit influenced by low frequency thalamic stimulation in essential tremor has a narrower frequency-amplitude tolerance so that tremor entrainment through extrinsic driving is necessarily accompanied by amplitude modulation. Such differences in parkinsonian rest and essential tremor will be important in selecting future strategies for closed loop deep brain stimulation for tremor control.
    Brain 09/2014; 137:3223-3234. DOI:10.1093/brain/awu250 · 9.20 Impact Factor
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    ABSTRACT: The cortico-basal-ganglia circuit plays a critical role in decision making on the basis of probabilistic information. Computational models have suggested how this circuit could compute the probabilities of actions being appropriate according to Bayes' theorem. These models predict that the subthalamic nucleus (STN) provides feedback that normalizes the neural representation of probabilities, such that if the probability of one action increases, the probabilities of all other available actions decrease. Here we report the results of an experiment testing a prediction of this theory that disrupting information processing in the STN with deep brain stimulation should abolish the normalization of the neural representation of probabilities. In our experiment, we asked patients with Parkinson's disease to saccade to a target that could appear in one of two locations, and the probability of the target appearing in each location was periodically changed. When the stimulator was switched off, the target probability affected the reaction times (RT) of patients in a similar way to healthy participants. Specifically, the RTs were shorter for more probable targets and, importantly, they were longer for the unlikely targets. When the stimulator was switched on, the patients were still faster for more probable targets, but critically they did not increase RTs as the target was becoming less likely. This pattern of results is consistent with the prediction of the model that the patients on DBS no longer normalized their neural representation of prior probabilities. We discuss alternative explanations for the data in the context of other published results.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 08/2014; 34(33):10844-10852. DOI:10.1523/JNEUROSCI.1065-14.2014 · 6.34 Impact Factor
  • Holly A. Roy · Tipu Z. Aziz ·
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    ABSTRACT: Deep brain stimulation is a neurosurgical technique that can be used to alleviate symptoms in a growing number of neurological conditions through modulating activity within brain networks. Certain applications of deep brain stimulation are relevant for the management of symptoms in multiple sclerosis. In this paper we discuss existing treatment options for tremor, facial pain and urinary dysfunction in multiple sclerosis and discuss evidence to support the potential use of deep brain stimulation for these symptoms. Copyright © 2014 Elsevier B.V. All rights reserved.
    Multiple Sclerosis and Related Disorders 07/2014; 3(4). DOI:10.1016/j.msard.2014.02.003 · 0.88 Impact Factor
  • Sandra G J Boccard · James J Fitzgerald · Tipu Z Aziz ·

    Neurosurgery 06/2014; 75(4). DOI:10.1227/NEU.0000000000000476 · 3.62 Impact Factor
  • Alexander L Green · Tipu Z Aziz ·

    Brain 05/2014; 137(7). DOI:10.1093/brain/awu126 · 9.20 Impact Factor
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    ABSTRACT: There is solid evidence of the long term efficacy of deep brain stimulation of the globus pallidus pars interna in the treatment of generalised dystonia. However there are conflicting reports concerning whether certain subgroups gain more benefit from treatment than others. We analysed the results of a series of 60 cases to evaluate the effects of previously proposed prognostic factors including dystonia aetiology, dystonia phenotype, age at onset of dystonia, and duration of dystonia prior to treatment. 60 patients with medically intractable primary or secondary generalised dystonia were treated with deep brain stimulation of the globus pallidus pars interna during the period 1999-2010 at the Department of Neurosurgery in Oxford, UK. Patients were assessed using the Burke-Fahn-Marsden (BFM) Dystonia Rating Scale prior to surgery, 6 months after implantation and thereafter at 1 year, 2 years and 5 years follow-up. The group showed mean improvements in the BFM severity and disability scores of 43% and 27%, respectively, by 6 months, and this was sustained. The results in 11 patients with DYT gene mutations were significantly better than in non-genetic primary cases. The results in 12 patients with secondary dystonia were not as good as those seen in non-genetic primary cases but there remained a significant beneficial effect. Age of onset of dystonia, duration of disease prior to surgery, and myoclonic versus torsional disease phenotype had no significant effect on outcome. The aetiology of dystonia was the sole factor predicting a better or poorer outcome from globus pallidus pars interna stimulation in this series of patients with generalised dystonia. However even the secondary cases that responded the least well had a substantial reduction in BFM scores compared with preoperative clinical assessments, and these patients should still be considered for deep brain stimulation.
    Journal of neurology, neurosurgery, and psychiatry 04/2014; 85(12). DOI:10.1136/jnnp-2013-306833 · 6.81 Impact Factor
  • Carole Joint · Tipu Z. Aziz ·

    World Neurosurgery 03/2014; 82(6). DOI:10.1016/j.wneu.2014.03.027 · 2.88 Impact Factor
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    ABSTRACT: Targeted electric deep brain stimulation in midbrain nuclei in humans alters cardiovascular parameters, presumably by modulating autonomic and baroreflex function. Baroreflex modulation of sympathetic outflow is crucial for cardiovascular regulation and is hypothesized to occur at 2 distinct brain locations. The aim of this study was to evaluate sympathetic outflow in humans with deep brain stimulating electrodes during ON and OFF stimulation of specific midbrain nuclei known to regulate cardiovascular function. Multiunit muscle sympathetic nerve activity was recorded in 17 patients undergoing deep brain stimulation for treatment of chronic neuropathic pain (n=7) and Parkinson disease (n=10). Sympathetic outflow was recorded during ON and OFF stimulation. Arterial blood pressure, heart rate, and respiratory frequency were monitored during the recording session, and spontaneous vasomotor and cardiac baroreflex sensitivity were assessed. Head-up tilt testing was performed separately in the patients with Parkinson disease postoperatively. Stimulation of the dorsal most part of the subthalamic nucleus and ventrolateral periaqueductal gray resulted in improved vasomotor baroreflex sensitivity, decreased burst frequency and blood pressure, unchanged burst amplitude distribution, and a reduced fall in blood pressure after tilt. Stimulation of the dorsolateral periaqueductal gray resulted in a shift in burst amplitude distribution toward larger amplitudes, decreased spontaneous beat-to-beat blood pressure variability, and unchanged burst frequency, baroreflex sensitivity, and blood pressure. Our results indicate that a differentiated regulation of sympathetic outflow occurs in the subthalamic nucleus and periaqueductal gray. These results may have implications in our understanding of abnormal sympathetic discharge in cardiovascular disease and provide an opportunity for therapeutic targeting.
    Hypertension 02/2014; 63(5). DOI:10.1161/HYPERTENSIONAHA.113.02970 · 6.48 Impact Factor

Publication Stats

8k Citations
1,140.83 Total Impact Points


  • 2015
    • University Pompeu Fabra
      • Center of Brain and Cognition (CBC)
      Barcino, Catalonia, Spain
  • 2007-2015
    • Oxford University Hospitals NHS Trust
      • • Department of Surgery
      • • Department of Clinical Neurology
      • • Department of Neurosurgery
      • • Nuffield Department of Surgery
      Oxford, England, United Kingdom
  • 1998-2015
    • University of Oxford
      • Department of Physiology, Anatomy and Genetics
      Oxford, England, United Kingdom
  • 2011-2014
    • Aarhus University
      • Centre of Functionally Integrative Neuroscience CFIN
      Aarhus, Central Jutland, Denmark
  • 2013
    • University of Jyväskylä
      Jyväskylä, Central Finland, Finland
  • 2007-2010
    • University of Reading
      • • School of Systems Engineering
      • • Department of Cybernetics
      Reading, England, United Kingdom
  • 2004-2008
    • Imperial College London
      • Faculty of Medicine
      Londinium, England, United Kingdom
    • Universität Heidelberg
      Heidelburg, Baden-Württemberg, Germany