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Hire Dr. Peter H.

United Kingdom

USD 100 /hr

Cognitive Neuroscientist with 10+ years experience of computational imaging analysis and behavioural analysis

Profile Summary

Significant experience in computational modelling and both functional and structural imaging analysis

Subject Matter Expertise

• ☆ Neuroscience
• ☆ Behavioral Neuroscience
• ☆ Computational Neuroscience
• ☆ Cognitive Neuroscience
• ☆ Neuroanatomy
• ☆ Neuropsychology
• ☆ Developmental Neuroscience
• ☆ Neurobiology
• ☆ Systems Neuroscience
• ☆ Software Engineering
• ☆ Human Behavior & Psychology
• ☆ Medical Imaging/Radiology
• ☆ Magnetic Resonance Imaging (MRI)

Services

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing Technical Writing, Copywriting, Newswriting

Research Market Research, User Research, Feasibility Study, Fact Checking, Gray Literature Search

Consulting Digital Strategy Consulting, Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-Non ML, Data Visualization, Big Data Analytics, Data Processing, Data Insights

Product Development Product Validation, Prototyping

Work Experience

King's College London

- Present

King's College London

December 2017 - Present

Research Fellow

Imperial College London

October 2015 - Present

Postdoctoral Research Associate

King's College London

November 2014 - October 2015

Education

PhD Experimental Neuroscience (Deparment of Medicine)

Imperial College London

September 2011 - April 2015

MRes Experimental Neuroscience (Department of Medicine)

Imperial College London

October 2010 - October 2011

BSc Neuroscience (Biomedical and Health Sciences)

King's College London

September 2007 - September 2010

Certifications

• Certification details not provided.

Publications

JOURNAL ARTICLE

Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK @article{0adf59b2ed9c4a6b9454c27d4bed676c, title = "Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions", abstract = "Background: There is widespread concern regarding how the COVID-19 pandemic has affected mental health. Emerging meta-analyses suggest that the impact on anxiety/depression may have been transient, but much of the included literature has major methodological limitations. Addressing this topic rigorously requires longitudinal data of sufficient scope and scale, controlling for contextual variables, with baseline data immediately pre-pandemic. Aims: To analyse self-report of symptom frequency from two largely UK-based longitudinal cohorts: Cohort 1 (N = 10,475, two time-points: winter pre-pandemic to UK first winter resurgence), and Cohort 2 (N = 10,391, two time-points, peak first wave to UK first winter resurgence). Method: Multinomial logistic regression applied at the item level identified sub-populations with greater probability of change in mental health symptoms. Permutation analyses characterised changes in symptom frequency distributions. Cross group differences in symptom stability were evaluated via entropy of response transitions. Results: Anxiety was the most affected aspect of mental health. The profiles of change in mood symptoms was less favourable for females and older adults. Those with pre-existing psychiatric diagnoses showed substantially higher probability of very frequent symptoms pre-pandemic and elevated risk of transitioning to the highest levels of symptoms during the pandemic. Elevated mental health symptoms were evident across intra-COVID timepoints in Cohort 2. Conclusions: These findings suggest that mental health has been negatively affected by the pandemic, including in a sustained fashion beyond the first UK lockdown into the first winter resurgence. Women, and older adults, were more affected relative to their own baselines. Those with diagnoses of psychiatric conditions were more likely to experience transition to the highest levels of symptom frequency.", keywords = "Anxiety, COVID, Depression, Fatigue, Insomnia, SARS-CoV-2, Sleep, Well-being", author = "Adam Hampshire and William Trender and Grant, {Jon E.} and Mirza, {M. Berk} and Rosalyn Moran and Hellyer, {Peter J.} and Chamberlain, {Samuel R.}", note = "Funding Information: This work was supported by the Dementia Research Institute, Care Research and Technology Centre . SRC's role in this work was funded by Wellcome ( 110049/Z/15/Z & A ). PJHs role was supported by the NIHR Maudsley BRC . Publisher Copyright: {\textcopyright} 2022", year = "2022", month = apr, doi = "10.1016/j.comppsych.2022.152298", language = "English", volume = "114", journal = "Comprehensive Psychiatry", issn = "0010-440X", publisher = "W.B. Saunders Ltd", } . Comprehensive Psychiatry.

Peter Hellyer, Inga Usher, Keng Siang Lee, Robert Leech, Adam Hampshire, Alexander Alamri, Aswin Chari (2021). “It’s not rocket science” and “It’s not brain surgery”—“It’s a walk in the park”: prospective comparative study . BMJ.

"it's not rocket science" and "it's not brain surgery" - "it's a walk in the park" @article{8c9be9a0fe79451d97dbe07d639c8f8f, title = "{"}it's not rocket science{"} and {"}it's not brain surgery{"} - {"}it's a walk in the park{"}: Prospective comparative study", abstract = "AbstractObjective To compare cognitive testing scores in neurosurgeons and aerospace engineers to help settle the age old argument of which phrase - {"}It's not brain surgery{"}or {"}It's not rocket science{"}- is most deserved. Design International prospective comparative study. Setting United Kingdom, Europe, the United States, and Canada. Participants 748 people (600 aerospace engineers and 148 neurosurgeons). After data cleaning, 401 complete datasets were included in the final analysis (329 aerospace engineers and 72 neurosurgeons). Main outcome measures Validated online test (Cognitron's Great British Intelligence Test) measuring distinct aspects of cognition, spanning planning and reasoning, working memory, attention, and emotion processing abilities. Results The neurosurgeons showed significantly higher scores than the aerospace engineers in semantic problem solving (difference 0.33, 95% confidence interval 0.13 to 0.52). Aerospace engineers showed significantly higher scores in mental manipulation and attention (-0.29, -0.48 to -0.09). No difference was found between groups in domain scores for memory (-0.18, -0.40 to 0.03), spatial problem solving (-0.19, -0.39 to 0.01), problem solving speed (0.03, -0.20 to 0.25), and memory recall speed (0.12, -0.10 to 0.35). When each group's scores for the six domains were compared with those in the general population, only two differences were significant: the neurosurgeons' problem solving speed was quicker (mean z score 0.24, 95% confidence interval 0.07 to 0.41) and their memory recall speed was slower (-0.19, -0.34 to -0.04). Conclusions In situations that do not require rapid problem solving, it might be more correct to use the phrase {"}It's not brain surgery.{"}It is possible that both neurosurgeons and aerospace engineers are unnecessarily placed on a pedestal and that {"}It's a walk in the park{"}or another phrase unrelated to careers might be more appropriate. Other specialties might deserve to be on that pedestal, and future work should aim to determine the most deserving profession.", author = "Inga Usher and Peter Hellyer and Lee, {Keng Siang} and Robert Leech and Adam Hampshire and Alexander Alamri and Aswin Chari", note = "Funding Information: Ethical approval: This study was approved by the University College London research ethics committee (19713/001) and is supported by the Society of British Neurological Surgeons and the United Kingdom Space Agency. Data sharing: Technical appendix, statistical code, and dataset are available from the corresponding author. The general population comparison data from the Great British Intelligence Test are not available as an open dataset. The lead author (AC) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained. Dissemination to participants and related patient and public communities: Results will be disseminated primarily through the Brainbook charity. We will design infographics and a lay summary of the study, which will be disseminated through the charity{\textquoteright}s website and active social media channels. We will provide avenues for the public to ask questions to the authors (via interactive Q&A sessions on Instagram, Twitter, and Facebook). In addition, we aim to disseminate the study findings through press releases. These are with the aims of dispelling myths and increasing access to both specialties and STEM careers in general. Funding Information: This study was commissioned by Brainbook, a United Kingdom charity dedicated to science communication and public engagement in neurosurgery and the neurosciences. We thank the Society of British Neurological Surgeons and the UK Space Agency for support with this study; and the Royal Astronomical Society, European Space Agency, and Canadian Neurological Sciences Federation for publicising the study through various channels. Contributors: IU, KSL, AA, and AC conceived the idea, designed the study, and obtained ethical approval. PH, RL, and AH devised the Cognitron platform and programmed its use for the study. PH and AC analysed the data. IU and AC drafted the manuscript. All authors were involved in the editing of the manuscript and approved the final version before submission. AC is the guarantor. The corresponding author is the guarantor and attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. Funding: IU is funded by a Royal College of Surgeons research fellowship. AC is funded by a Great Ormond Street Hospital Children{\textquoteright}s Charity surgeon-scientist fellowship. The funders had no input into the study conception, design, analysis, or reporting. Competing interests: Three of the authors are neurosurgical trainees or residents; none are aerospace engineers. All authors have completed the ICMJE uniform disclosure form at www.icmje.org/ disclosure-of-interest/ and declare: support from the Royal College of Surgeons and Great Ormond Street Children{\textquoteright}s Charity; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years ; no other relationships or activities that could appear to have influenced the submitted work. Publisher Copyright: {\textcopyright} ", year = "2021", month = dec, day = "1", doi = "10.1136/bmj-2021-067883", language = "English", volume = "375", journal = "BMJ (Online)", issn = "0959-8146", } . The BMJ.

Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom @article{705be5172cd841dbb76320a67a875e15, title = "Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom", abstract = "The COVID-19 pandemic (including lockdown) is likely to have had profound but diverse implications for mental health and well-being, yet little is known about individual experiences of the pandemic (positive and negative) and how this relates to mental health and well-being, as well as other important contextual variables. Here, we analyse data sampled in a large-scale manner from 379,875 people in the United Kingdom (UK) during 2020 to identify population variables associated with mood and mental health during the COVID-19 pandemic, and to investigate self-perceived pandemic impact in relation to those variables. We report that while there are relatively small population-level differences in mood assessment scores pre- to peak-UK lockdown, the size of the differences is larger for people from specific groups, e.g. older adults and people with lower incomes. Multiple dimensions underlie peoples{\textquoteright} perceptions, both positive and negative, of the pandemic{\textquoteright}s impact on daily life. These dimensions explain variance in mental health and can be statistically predicted from age, demographics, home and work circumstances, pre-existing conditions, maladaptive technology use and personality traits (e.g., compulsivity). We conclude that a holistic view, incorporating the broad range of relevant population factors, can better characterise people whose mental health is most at risk during the COVID-19 pandemic.", author = "Adam Hampshire and Hellyer, {Peter J.} and Eyal Soreq and Mehta, {Mitul A.} and Konstantinos Ioannidis and William Trender and Grant, {Jon E.} and Chamberlain, {Samuel R.}", note = "Funding Information: S.R.C. previously consulted for Promentis. He receives honoraria for journal editorial work from Elsevier. J.E.G. has received research grants from the T.L.C. Foundation for Body-Focused Repetitive Behaviors, Biohaven, Promentis and Avanir Pharmaceuticals. M.A.M. has received grant income from Takeda Pharmaceuticals, Johnson & Johnson and Lundbeck. A.H. is owner and founder of Future Cognition Ltd. and H2 Cognitive Designs Ltd., which develop custom cognitive assessment software for other university-based research groups. P.J.H. is the owner and co-founder of H2 Cognitive Designs Ltd. The authors report no other conflicts of interest. Funding Information: This study was conducted in collaboration with BBC2 Horizon. The study was supported by the UK Dementia Research Institute and Biomedical Research Centre at Imperial College London. Technology development was supported by EU-CIG EC Marie‐Curie CIG and NIHR grant II-LB-0715-20006 to A.H. E.S.{\textquoteright}s role was supported by MRC grant MR/R005370/1 to A.H. W.T. is supported by the EPSRC Center for Doctoral Training in Neurotechnology under supervision of A.H. This research was funded in part by Wellcome [110049/Z/15/Z and 110049/Z/15/A] (Grant to S.R.C.). For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. M.A.M. is in part supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King{\textquoteright}s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. We would like to acknowledge COST Action CA16207 {\textquoteleft}European Network for Problematic Usage of the Internet{\textquoteright}, supported by COST (European Cooperation in Science and Technology), and the support of the National UK Research Network for Behavioural Addictions (NUK-BA). Publisher Copyright: {\textcopyright} 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.", year = "2021", month = dec, doi = "10.1038/s41467-021-24365-5", language = "English", volume = "12", journal = "Nature Communications", issn = "2041-1723", publisher = "Nature Publishing Group", number = "1", } . Nature Communications.

Adam Hampshire, Peter J. Hellyer, Eyal Soreq, Mitul A. Mehta, Konstantinos Ioannidis, William Trender, Jon E. Grant, Samuel R. Chamberlain(2021). Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom . Nature Communications. 12. (1). Springer Science and Business Media {LLC}

Adam Hampshire, Peter J. Hellyer, Eyal Soreq, Mitul A. Mehta, Konstantinos Ioannidis, William Trender, Jon E. Grant, Samuel R. Chamberlain (2021). Author Correction: Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom . Nature Communications.

Insights into the impact on daily life of the COVID-19 pandemic and effective coping strategies from free-text analysis of people's collective experiences @article{a81df1d4a29c47fd8930d9bfcd5a4ba2, title = "Insights into the impact on daily life of the COVID-19 pandemic and effective coping strategies from free-text analysis of people's collective experiences", abstract = "There has been considerable speculation regarding how people cope during the COVID-19 pandemic; however, surveys requiring selection from prespecified answers are limited by researcher views and may overlook the most effective measures. Here, we apply an unbiased approach that learns from people's collective lived experiences through the application of natural-language processing of their free-text reports. At the peak of the first lockdown in the United Kingdom, 51 113 individuals provided free-text responses regarding self-perceived positive and negative impact of the pandemic, as well as the practical measures they had found helpful during this period. Latent Dirichlet Allocation identified, in an unconstrained data-driven manner, the most common impact and advice topics. We report that six negative topics and seven positive topics are optimal for capturing the different ways people reported being affected by the pandemic. Forty-five topics were required to optimally summarize the practical coping strategies that they recommended. General linear modelling showed that the prevalence of these topics covaried substantially with age. We propose that a wealth of coping measures may be distilled from the lived experiences of the general population. These may inform feasible individually tailored digital interventions that have relevance during and beyond the pandemic. ", keywords = "COVID-19, free text, mental health, pandemic, pragmatic interventions, topic modelling", author = "Adam Hampshire and Hellyer, {Peter J.} and William Trender and Chamberlain, {Samuel R.}", note = "Funding Information: This work was supported by funding to A.H. from the UK Dementia Research Institute Care Research and Technology Centre at Imperial College London. S.R.C.'s role in this work was funded by Wellcome (grant no. 110049/Z/15/Z & A). P.J.H.'s role was funded by the King's College London SLaM BRC. W.T. contributed to this study as part of an EPSRC Neurotechnology Centre for Doctoral Training studentship. Acknowledgements Publisher Copyright: {\textcopyright} 2021 The Authors.", year = "2021", month = oct, day = "12", doi = "10.1098/rsfs.2021.0051", language = "English", volume = "11", journal = "Interface Focus", issn = "2042-8898", publisher = "Royal Society", number = "6", } . Interface Focus.

Cognitive deficits in people who have recovered from COVID-19 @article{99c1e2ecdaf64ba288a95207e295c7e8, title = "Cognitive deficits in people who have recovered from COVID-19", abstract = "Background: There is growing concern about possible cognitive consequences of COVID-19, with reports of {\textquoteleft}Long COVID{\textquoteright} symptoms persisting into the chronic phase and case studies revealing neurological problems in severely affected patients. However, there is little information regarding the nature and broader prevalence of cognitive problems post-infection or across the full spread of disease severity. Methods: We sought to confirm whether there was an association between cross-sectional cognitive performance data from 81,337 participants who between January and December 2020 undertook a clinically validated web-optimized assessment as part of the Great British Intelligence Test, and questionnaire items capturing self-report of suspected and confirmed COVID-19 infection and respiratory symptoms. Findings: People who had recovered from COVID-19, including those no longer reporting symptoms, exhibited significant cognitive deficits versus controls when controlling for age, gender, education level, income, racial-ethnic group, pre-existing medical disorders, tiredness, depression and anxiety. The deficits were of substantial effect size for people who had been hospitalised (N = 192), but also for non-hospitalised cases who had biological confirmation of COVID-19 infection (N = 326). Analysing markers of premorbid intelligence did not support these differences being present prior to infection. Finer grained analysis of performance across sub-tests supported the hypothesis that COVID-19 has a multi-domain impact on human cognition. Interpretation: Interpretation. These results accord with reports of {\textquoteleft}Long Covid{\textquoteright} cognitive symptoms that persist into the early-chronic phase. They should act as a clarion call for further research with longitudinal and neuroimaging cohorts to plot recovery trajectories and identify the biological basis of cognitive deficits in SARS-COV-2 survivors. Funding: Funding. AH is supported by the UK Dementia Research Institute Care Research and Technology Centre and Biomedical Research Centre at Imperial College London. WT is supported by the EPSRC Centre for Doctoral Training in Neurotechnology. SRC is funded by a Wellcome Trust Clinical Fellowship 110,049/Z/15/Z. JMB is supported by Medical Research Council (MR/N013700/1). MAM, SCRW and PJH are, in part, supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London", keywords = "Attention, Cognition, COVID-19, Deficits, Long covid, Memory, Online assessment, Planning, Reasoning", author = "Adam Hampshire and William Trender and Chamberlain, {Samuel R.} and Jolly, {Amy E.} and Grant, {Jon E.} and Fiona Patrick and Ndaba Mazibuko and Williams, {Steve CR} and Barnby, {Joseph M.} and Peter Hellyer and Mehta, {Mitul A.}", note = "Funding Information: AH is supported by the UK Dementia Research Institute Care Research and Technology Centre and Biomedical Research Centre at Imperial College London. WT is supported by the EPSRC Centre for Doctoral Training in Neurotechnology. SRC is funded by a Wellcome Trust Clinical Fellowship 110,049/Z/15/Z. JMB is supported by Medical Research Council (MR/N013700/1). MAM, SCRW and PJH are, in part, supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London Funding Information: All data are freely available in fully anonymised format for academic researchers on request to the corresponding author. We would like to thank the BBC2 Horizon team for their support in promoting this study. Funding Information: Dr. Hampshire reports grants from UK Dementia Research Institute, outside the submitted work and is Co-director and owner of H2CD Ltd, and owner and director of Future Cognition Ltd, which support online studies and develop custom cognitive assessment software respectively. Dr. Hellyer reports personal fees from H2CD Ltd, outside the submitted work. Dr. Chamberlain reports grants from Wellcome, personal fees from Elsevier, personal fees from Prometis (not current), outside the submitted work. Dr. Grant reports grants from Otsuka, grants from Biohaven, grants from Avanir, outside the submitted work. Dr. Patrick reports grants from H Lundbeck A/S, non-financial support from Astra Zeneca, non-financial support from Janssen, outside the submitted work. Dr. Mehta reports grants from H Lundbeck A/S, non-financial support from Astra Zeneca, non-financial support from Janssen, outside the submitted work. Dr. Williams has nothing to disclose. Dr. Mazibuko has nothing to disclose. Dr. Jolly has nothing to disclose. Mr. Trender has nothing to declare. Dr. Barnby has nothing to disclose. Publisher Copyright: {\textcopyright} 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.", year = "2021", month = jul, day = "22", doi = "10.1016/j.eclinm.2021.101044", language = "English", journal = "EClinicalMedicine", issn = "2589-5370", publisher = "Lancet Publishing Group", } . EClinicalMedicine.

From biomechanics to pathology @article{613dd049926a4167bf4123f63fd9d05b, title = "From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury", abstract = "The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a controlled cortical impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4 T MRI at 2 weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in the corpus callosum, indicating white matter changes in the segments subjected to high strain, as predicted by the model. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of traumatic brain injury. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets.", author = "Donat, {Cornelius K} and {Yanez Lopez}, Maria and Magdalena Sastre and Nicoleta Baxan and Marc Goldfinger and Reneira Seeamber and Franziska M{\"u}ller and Polly Davies and Peter Hellyer and Petros Siegkas and Steve Gentleman and Sharp, {David J} and Mazdak Ghajari", note = "Funding Information: This study was funded through Wellcome Trust Networks of Excellence and the Royal British Legion at the Centre for Blast Injury Studies, Imperial College London. Publisher Copyright: {\textcopyright} 2021 The Author(s) (2021). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.", year = "2021", month = feb, day = "12", doi = "10.1093/brain/awaa336", language = "English", volume = "144", pages = "70--91", journal = "Brain", issn = "0006-8950", publisher = "Oxford University Press", number = "1", } . Brain : a journal of neurology.

Vestibular agnosia in traumatic brain injury and its link to imbalance @article{0b4c3020cfa247a4b0a70a71d486a64f, title = "Vestibular agnosia in traumatic brain injury and its link to imbalance", abstract = "Vestibular dysfunction, causing dizziness and imbalance, is a common yet poorly understood feature in patients with TBI. Damage to the inner ear, nerve, brainstem, cerebellum and cerebral hemispheres may all affect vestibular functioning, hence, a multi-level assessment-from reflex to perception-is required. In a previous report, postural instability was the commonest neurological feature in ambulating acute patients with TBI. During ward assessment, we also frequently observe a loss of vertigo sensation in patients with acute TBI, common inner ear conditions and a related vigorous vestibular-ocular reflex nystagmus, suggesting a 'vestibular agnosia'. Patients with vestibular agnosia were also more unbalanced; however, the link between vestibular agnosia and imbalance was confounded by the presence of inner ear conditions. We investigated the brain mechanisms of imbalance in acute TBI, its link with vestibular agnosia, and potential clinical impact, by prospective laboratory assessment of vestibular function, from reflex to perception, in patients with preserved peripheral vestibular function. Assessment included: vestibular reflex function, vestibular perception by participants' report of their passive yaw rotations in the dark, objective balance via posturography, subjective symptoms via questionnaires, and structural neuroimaging. We prospectively screened 918 acute admissions, assessed 146 and recruited 37. Compared to 37 matched controls, patients showed elevated vestibular-perceptual thresholds (patients 12.92°/s versus 3.87°/s) but normal vestibular-ocular reflex thresholds (patients 2.52°/s versus 1.78°/s). Patients with elevated vestibular-perceptual thresholds [3 standard deviations (SD) above controls' average], were designated as having vestibular agnosia, and displayed worse posturography than non-vestibular-agnosia patients, despite no difference in vestibular symptom scores. Only in patients with impaired postural control (3 SD above controls' mean), whole brain diffusion tensor voxel-wise analysis showed elevated mean diffusivity (and trend lower fractional anisotropy) in the inferior longitudinal fasciculus in the right temporal lobe that correlated with vestibular agnosia severity. Thus, impaired balance and vestibular agnosia are co-localized to the inferior longitudinal fasciculus in the right temporal lobe. Finally, a clinical audit showed a sevenfold reduction in clinician recognition of a common peripheral vestibular condition (benign paroxysmal positional vertigo) in acute patients with clinically apparent vestibular agnosia. That vestibular agnosia patients show worse balance, but without increased dizziness symptoms, explains why clinicians may miss treatable vestibular diagnoses in these patients. In conclusion, vestibular agnosia mediates imbalance in traumatic brain injury both directly via white matter tract damage in the right temporal lobe, and indirectly via reduced clinical recognition of common, treatable vestibular diagnoses.", keywords = "self-motion perception, traumatic brain injury, vertigo, vestibular agnosia, vestibular cognition", author = "Elena Calzolari and Mariya Chepisheva and Smith, {Rebecca M.} and Mohammad Mahmud and Hellyer, {Peter J.} and Vassilios Tahtis and Qadeer Arshad and Amy Jolly and Mark Wilson and Heiko Rust and Sharp, {David J.} and Seemungal, {Barry M.}", note = "Funding Information: The Medical Research Council (MRC). The Imperial Health Charity, The NIHR Imperial Biomedical Research Centre, NIHR Clinical Doctoral Research Fellowship, The US Department of Defense - Congressionally Directed Medical Research Program (CDMRP). Publisher Copyright: {\textcopyright} 2020 The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.", year = "2021", month = feb, day = "12", doi = "10.1093/brain/awaa386", language = "English", volume = "144", pages = "128--143", journal = "Brain", issn = "0006-8950", publisher = "Oxford University Press (OUP)", number = "1", } . Brain : a journal of neurology.

Jessica Dafflon, Walter H. L. Pinaya, Federico Turkheimer, James H. Cole, Robert Leech, Mathew A. Harris, Simon R. Cox, Heather C. Whalley, Andrew M. McIntosh, Peter J. Hellyer(2020). An automated machine learning approach to predict brain age from cortical anatomical measures . Human Brain Mapping. Wiley

An automated machine learning approach to predict brain age from cortical anatomical measures @article{556c7dd913204a6ca1dfff9b15b8ab41, title = "An automated machine learning approach to predict brain age from cortical anatomical measures", abstract = "The use of machine learning (ML) algorithms has significantly increased in neuroscience. However, from the vast extent of possible ML algorithms, which one is the optimal model to predict the target variable? What are the hyperparameters for such a model? Given the plethora of possible answers to these questions, in the last years, automated ML (autoML) has been gaining attention. Here, we apply an autoML library called Tree‐based Pipeline Optimisation Tool (TPOT) which uses a tree‐based representation of ML pipelines and conducts a genetic programming‐based approach to find the model and its hyperparameters that more closely predicts the subject's true age. To explore autoML and evaluate its efficacy within neuroimaging data sets, we chose a problem that has been the focus of previous extensive study: brain age prediction. Without any prior knowledge, TPOT was able to scan through the model space and create pipelines that outperformed the state‐of‐the‐art accuracy for Freesurfer‐based models using only thickness and volume information for anatomical structure. In particular, we compared the performance of TPOT (mean absolute error [MAE]: 4.612 ± .124 years) and a relevance vector regression (MAE 5.474 ± .140 years). TPOT also suggested interesting combinations of models that do not match the current most used models for brain prediction but generalise well to unseen data. AutoML showed promising results as a data‐driven approach to find optimal models for neuroimaging applications.", keywords = "age prediction, automated machine learning, cortical features, neuroimaging, predictive modelling, structural imaging", author = "{De Faria Dafflon}, Jessica and {Diaz Sanz}, {Walter Hugo} and Turkheimer, {Federico Edoardo} and Cole, {James Howard} and Robert Leech and Harris, {Mathew A.} and Simon Cox and Whalley, {Heather C} and Andrew McIntosh and Hellyer, {Peter John}", note = "{\textcopyright} 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.", year = "2020", month = sep, day = "1", doi = "https://doi.org/10.1002/hbm.25028", language = "English", volume = "41", pages = "3555--3566", journal = "Human Brain Mapping", issn = "1065-9471", publisher = "Wiley-Liss Inc.", number = "13", } . Human Brain Mapping.

Diffusion tensor imaging of lumbar spinal nerves reveals changes in microstructural integrity following decompression surgery associated with improvements in clinical symptoms @article{be18a88724c94820a3725a0ec88b79db, title = "Diffusion tensor imaging of lumbar spinal nerves reveals changes in microstructural integrity following decompression surgery associated with improvements in clinical symptoms: A case report", abstract = "The outcomes from spinal nerve decompression surgery are highly variable with a sizable proportion of elderly foraminal stenosis patients not regaining good pain relief. A better understanding of nerve root compression before and following decompression surgery and whether these changes are mirrored by improvements in symptoms may help to improve clinical decision-making processes. This case study used a combination of diffusion tensor imaging (DTI), clinical questionnaires and motor neurophysiology assessments before and up to 3 months following spinal decompression surgery. In this case report, a 70-year-old women with compression of the left L5 spinal nerve root in the L5-S1 exit foramina was recruited to the study. At 3 months following surgery, DTI revealed marked improvements in left L5 microstructural integrity to a similar level to that seen in the intact right L5 nerve root. This was accompanied by a gradual improvement in pain-related symptoms, mood and disability score by 3 months. Using this novel multimodal approach, it may be possible to track concurrent improvements in pain-related symptoms, function and microstructural integrity of compressed nerves in elderly foraminal stenosis patients undergoing decompression surgery.", keywords = "Diffusion tensor imaging, Motor Function, Pain, Stenosis, Surgery, Symptoms", author = "Hughes, {Sam W.} and P.j. Hellyer and D.j. Sharp and R.d. Newbould and M.c. Patel and P.h. Strutton", year = "2020", month = jun, doi = "10.1016/j.mri.2020.02.007", language = "English", volume = "69", pages = "65--70", journal = "Magnetic Resonance Imaging", issn = "0730-725X", publisher = "Elsevier", } . Magnetic Resonance Imaging.

Analysis of an Automated Machine Learning Approach in Brain Predictive Modelling @article{f260ad9ef98a4e94be2a787835461fcc, title = "Analysis of an Automated Machine Learning Approach in Brain Predictive Modelling: A data-driven approach to Predict Brain Age from Cortical Anatomical Measures", abstract = " The use of machine learning (ML) algorithms has significantly increased in neuroscience. However, from the vast extent of possible ML algorithms, which one is the optimal model to predict the target variable? What are the hyperparameters for such a model? Given the plethora of possible answers to these questions, in the last years, automated machine learning (autoML) has been gaining attention. Here, we apply an autoML library called TPOT which uses a tree-based representation of machine learning pipelines and conducts a genetic-programming based approach to find the model and its hyperparameters that more closely predicts the subject's true age. To explore autoML and evaluate its efficacy within neuroimaging datasets, we chose a problem that has been the focus of previous extensive study: brain age prediction. Without any prior knowledge, TPOT was able to scan through the model space and create pipelines that outperformed the state-of-the-art accuracy for Freesurfer-based models using only thickness and volume information for anatomical structure. In particular, we compared the performance of TPOT (mean accuracy error (MAE): $4.612 \pm .124$ years) and a Relevance Vector Regression (MAE $5.474 \pm .140$ years). TPOT also suggested interesting combinations of models that do not match the current most used models for brain prediction but generalise well to unseen data. AutoML showed promising results as a data-driven approach to find optimal models for neuroimaging applications. ", keywords = "q-bio.NC, stat.ML", author = "Jessica Dafflon and Pinaya, {Walter H. L} and Federico Turkheimer and Cole, {James H.} and Robert Leech and Harris, {Mathew A.} and Cox, {Simon R.} and Whalley, {Heather C.} and McIntosh, {Andrew M.} and Hellyer, {Peter J.}", year = "2019", month = oct, day = "8", language = "English", journal = " arXiv", } . arXiv.

A large-scale, cross-sectional investigation into the efficacy of brain training @article{b19bf799ab644aefa3baccc1738272b7, title = "A large-scale, cross-sectional investigation into the efficacy of brain training", abstract = "Brain training is a large and expanding industry, and yet there is a recurrent and ongoing debate concerning its scientific basis or evidence for efficacy. Much of evidence for the efficacy of brain training within this debate is from small-scale studies that do not assess the type of “brain training,” the specificity of transfer effects, or the length of training required to achieve a generalized effect. To explore these factors, we analyze cross-sectional data from two large Internet-cohort studies (total N = 60,222) to determine whether cognition differs at the population level for individuals who report that they brain train on different devices, and across different timeframes, with programs in common use circa 2010–2013. Examining scores for an assessment of working-memory, reasoning and verbal abilities shows no cognitive advantages for individuals who brain train. This contrasts unfavorably with significant advantages for individuals who regularly undertake other cognitive pursuits such as computer, board and card games. However, finer grained analyses reveal a more complex relationship between brain training and cognitive performance. Specifically, individuals who have just begun to brain train start from a low cognitive baseline compared to individuals who have never engaged in brain training, whereas those who have trained for a year or more have higher working-memory and verbal scores compared to those who have just started, thus suggesting an efficacy for brain training over an extended period of time. The advantages in global function, working memory, and verbal memory after several months of training are plausible and of clinically relevant scale. However, this relationship is not evident for reasoning performance or self-report measures of everyday function (e.g., employment status and problems with attention). These results accord with the view that although brain training programs can produce benefits, these might extend to tasks that are operationally similar to the training regime. Furthermore, the duration of training regime required for effective enhancement of cognitive performance is longer than that applied in most previous studies.", keywords = "Brain training, Commercial brain training, Cross sectional study, Efficacy of brain training, Memory", author = "Adam Hampshire and Stefano Sandrone and Hellyer, {Peter John}", year = "2019", month = jul, day = "3", doi = "10.3389/fnhum.2019.00221", language = "English", volume = "13", journal = "Frontiers In Human Neuroscience", issn = "1662-5161", publisher = "Frontiers Media S.A.", } . Frontiers In Human Neuroscience.

Mapping cortical surface features in treatment resistant schizophrenia with in vivo structural MRI @article{be98d474568b40a1a2b58223fbe8a75f, title = "Mapping cortical surface features in treatment resistant schizophrenia with in vivo structural MRI", abstract = "Decreases in cortical volume (CV), thickness (CT) and surface area (SA) have been reported in individuals with schizophrenia by in vivo MRI studies. However, there are few studies that examine these cortical measures as potential biomarkers of treatment resistance (TR) and treatment response (NTR) in schizophrenia. This study used structural MRI to examine differences in CV, CT, and SA in 42 adults with schizophrenia (TR = 21, NTR = 21) and 23 healthy controls (HC) to test the hypothesis that individuals with TR schizophrenia have significantly greater reductions in these cortical measures compared to individuals with NTR schizophrenia. We found that individuals with TR schizophrenia showed significant reductions in CV and CT compared to individuals with NTR schizophrenia in right frontal and precentral regions, right parietal and occipital cortex, left temporal cortex and bilateral cingulate cortex. In line with previous literature, the temporal lobe and cingulate gyrus in both patient groups showed significant reductions of all three measures when compared to healthy controls. Taken together these results suggest that regional changes in CV and CT may index mechanisms specific to TR schizophrenia and potentially identify patients with TR schizophrenia for earlier treatment.", keywords = "Cortical thickness, Cortical volume, MRI, Schizophrenia, Treatment resistant", author = "Barry, {Erica F.} and Vanes, {Lucy D.} and Andrews, {Derek S.} and Krisna Patel and Horne, {Charlotte M.} and Elias Mouchlianitis and Hellyer, {Peter J.} and Shergill, {Sukhi S.}", year = "2019", month = apr, day = "1", doi = "10.1016/j.psychres.2019.02.028", language = "English", volume = "274", pages = "335--344", journal = "Psychiatry Research", issn = "0165-1781", } . Psychiatry Research.

Peter Hellyer, Federico E. Turkheimer, Angie A. Kehagia, Paul Expert, Louis-David Lord, Jakub Vohryzek, Jessica De Faria Dafflon, Mick Brammer, Robert Leech(2019). Conflicting emergences. Weak vs. strong emergence for the modelling of brain function . Neuroscience & Biobehavioral Reviews. 99. p. 3--10. Elsevier {BV}

Erica F. Barry, Lucy D. Vanes, Derek S. Andrews, Krisna Patel, Charlotte M. Horne, Elias Mouchlianitis, Peter J. Hellyer, Sukhi S. Shergill(2019). Mapping cortical surface features in treatment resistant schizophrenia with in vivo structural MRI . Psychiatry Research. 274. p. 335--344. Elsevier {BV}

Active acquisition for multimodal neuroimaging [version 2; peer review @article{f6d3093d95554397ae068282ae4f08d0, title = "Active acquisition for multimodal neuroimaging [version 2; peer review: 2 approved, 1 approved with reservations]", abstract = "In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field-of-view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.", keywords = "Active acquisition, Brain, MRI, Neuroimaging", author = "Cole, {James H.} and Romy Lorenz and Fatemeh Geranmayeh and Tobias Wood and Peter Hellyer and Steven Williams and Federico Turkheimer and Robert Leech", year = "2018", month = nov, day = "14", doi = "10.12688/wellcomeopenres.14918.2", language = "English", volume = "3", journal = "Wellcome Open Research", issn = "2398-502X", publisher = "F1000 Research Ltd.", } . Wellcome Open Research.

Chaos in Homeostatically Regulated Neural Systems @article{c937c2fa392a4d26b0c540bd90271d67, title = "Chaos in Homeostatically Regulated Neural Systems", abstract = "Low-dimensional yet rich dynamics often emerge in the brain. Examples include oscillations and chaotic dynamics during sleep, epilepsy, and voluntary movement. However, a general mechanism for the emergence of low dimensional dynamics remains elusive. Here, we consider Wilson-Cowan networks and demonstrate through numerical and analytical work that a type of homeostatic regulation of the network firing rates can paradoxically lead to a rich dynamical repertoire. The dynamics include mixed-mode oscillations, mixed-mode chaos, and chaotic synchronization. This is true for single recurrently coupled node, pairs of reciprocally coupled nodes without self-coupling, and networks coupled through experimentally determined weights derived from functional magnetic resonance imaging data. In all cases, the stability of the homeostatic set point is analytically determined or approximated. The dynamics at the network level are directly determined by the behavior of a single node system through synchronization in both oscillatory and non-oscillatory states. Our results demonstrate that rich dynamics can be preserved under homeostatic regulation or even be caused by homeostatic regulation.", keywords = "q-bio.NC", author = "Wilten Nicola and Peter Hellyer and Campbell, {Sue Ann} and Claudia Clopath", note = "25 pages, 5 figures", year = "2018", month = jan, day = "30", language = "Undefined/Unknown", journal = " arXiv", } . arXiv.

Sara De Simoni, Peter O Jenkins, Niall J Bourke, Jessica J Fleminger, Peter J Hellyer, Amy E Jolly, Maneesh C Patel, James H Cole, Robert Leech, David J Sharp(2018). Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury . Brain. 141. (1). p. 148--164. Oxford University Press ({OUP})

Peter John Hellyer, Daniele Marinazzo, Claudia Clopath, Angie A. Kehagia, Federico E. Turkheimer, Robert Leech(2017). From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction . PLOS Computational Biology. 13. (8). p. e1005721. Public Library of Science ({PLoS})

Protein synthesis is associated with high-speed dynamics and broad-band stability of functional hubs in the brain @article{85b8de5482814e74a3bd9b04dc558564, title = "Protein synthesis is associated with high-speed dynamics and broad-band stability of functional hubs in the brain", abstract = "L-[1-11C]leucine PET can be used to measure in vivo protein synthesis in the brain. However, the relationship between regional protein synthesis and on-going neural dynamics is unclear. We use a graph theoretical approach to examine the relationship between cerebral protein synthesis (rCPS) and both static and dynamical measures of functional connectivity (measured using resting state functional MRI, R-fMRI). Our graph theoretical analysis demonstrates a significant positive relationship between protein turnover and static measures of functional connectivity. We compared these results to simple measures of metabolism in the cortex using [18F]FDG PET). Whilst some relationship between [18F]FDG binding and graph theoretical measures was present, there remained a significant relationship between protein turnover and graph theoretical measures, which were more robustly explained by L-[1-11C]Leucine than [18F]FDG PET. This relationship was stronger in dynamics at a faster temporal resolution relative to dynamics measured over a longer epoch. Using a Dynamic connectivity approach, we also demonstrate that broad-band dynamic measures of Functional Connectivity (FC), are inversely correlated with protein turnover, suggesting greater stability of FC in highly interconnected hub regions is supported by protein synthesis. Overall, we demonstrate that cerebral protein synthesis has a strong relationship independent of tissue metabolism to neural dynamics at the macroscopic scale.", keywords = "Resting State, Protein Synthesis, Functional Connectivity, Graph Theory, Dynamics", author = "Hellyer, {Peter J.} and Alberto Pellizzon and Erica Barry and Mattia Veronese and Gaia Rizzo and Matteo Tonietto and Manuel Sch{\"u}tze and Michael Brammer and {Aur{\'e}lio Romano-Silva}, Marco and Alessandra Bertoldo and Turkheimer, {Federico E.}", year = "2017", month = jul, day = "15", doi = "10.1016/j.neuroimage.2017.04.062", language = "English", volume = "155", pages = "209–216", journal = "NeuroImage", issn = "1053-8119", publisher = "ACADEMIC PRESS INC ELSEVIER SCIENCE", } . NeuroImage.

Decoding time-varying functional connectivity networks via linear graph embedding methods @article{760b8cd12b8547a48333c7277bdea4fc, title = "Decoding time-varying functional connectivity networks via linear graph embedding methods", abstract = "An exciting avenue of neuroscientific research involves quantifying the time-varying properties of functional connectivity networks. As a result, many methods have been proposed to estimate the dynamic properties of such networks. However, one of the challenges associated with such methods involves the interpretation and visualization of high-dimensional, dynamic networks. In this work, we employ graph embedding algorithms to provide low-dimensional vector representations of networks, thus facilitating traditional objectives such as visualization, interpretation and classification. We focus on linear graph embedding methods based on principal component analysis and regularized linear discriminant analysis. The proposed graph embedding methods are validated through a series of simulations and applied to fMRI data from the Human Connectome Project.", keywords = "Brain decoding, Dynamic networks, Functional connectivity, Graph embedding, Visualization", author = "Monti, {Ricardo P.} and Romy Lorenz and Peter Hellyer and Robert Leech and Christoforos Anagnostopoulos and Giovanni Montana", year = "2017", month = mar, day = "20", doi = "10.3389/fncom.2017.00014", language = "English", volume = "11", journal = "Frontiers in Computational Neuroscience", issn = "1662-5188", publisher = "Frontiers Media S.A.", } . Frontiers in Computational Neuroscience.

Auditory and visual connectivity gradients in frontoparietal cortex @article{adcea63f56ab4b239618381ef672d537, title = "Auditory and visual connectivity gradients in frontoparietal cortex: Frontoparietal Audiovisual Gradients", abstract = "A frontoparietal network of brain regions is often implicated in both auditory and visual information processing. Although it is possible that the same set of multimodal regions subserves both modalities, there is increasing evidence that there is a differentiation of sensory function within frontoparietal cortex. Magnetic resonance imaging (MRI) in humans was used to investigate whether different frontoparietal regions showed intrinsic biases in connectivity with visual or auditory modalities. Structural connectivity was assessed with diffusion tractography and functional connectivity was tested using functional MRI. A dorsal–ventral gradient of function was observed, where connectivity with visual cortex dominates dorsal frontal and parietal connections, while connectivity with auditory cortex dominates ventral frontal and parietal regions. A gradient was also observed along the posterior–anterior axis, although in opposite directions in prefrontal and parietal cortices. The results suggest that the location of neural activity within frontoparietal cortex may be influenced by these intrinsic biases toward visual and auditory processing. Thus, the location of activity in frontoparietal cortex may be influenced as much by stimulus modality as the cognitive demands of a task. It was concluded that stimulus modality was spatially encoded throughout frontal and parietal cortices, and was speculated that such an arrangement allows for top–down modulation of modality-specific information to occur within higher-order cortex. This could provide a potentially faster and more efficient pathway by which top–down selection between sensory modalities could occur, by constraining modulations to within frontal and parietal regions, rather than long-range connections to sensory cortices. Hum Brain Mapp, 2016. {\textcopyright} 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.", author = "Braga, {Rodrigo M.} and Hellyer, {Peter J.} and Wise, {Richard J. S.} and Robert Leech", year = "2016", month = aug, day = "29", doi = "10.1002/hbm.23358", language = "English", journal = "Human Brain Mapping", issn = "1065-9471", publisher = "Wiley-Liss Inc.", } . Human Brain Mapping.

Braga RM, Hellyer PJ, Wise RJ, Leech R, Human brain mapping, 2016, 2016 .

Carhart-Harris RL, Muthukumaraswamy S, Roseman L, Kaelen M, Droog W, Murphy K, Tagliazucchi E, Schenberg EE, Nest T, Orban C, Leech R, Williams LT, Williams TM, Bolstridge M, Sessa B, McGonigle J, Sereno MI, Nichols D, Hellyer PJ, Hobden P, Proceedings of the National Academy of Sciences of the United States of America, 2016, vol. 113, no. 17, pp. 4853-4858, 2016 .

Scott G, Ramlackhansingh AF, Edison P, Hellyer P, Cole J, Veronese M, Leech R, Greenwood RJ, Turkheimer FE, Gentleman SM, Heckemann RA, Matthews PM, Brooks DJ, Sharp DJ, Neurology, 2016, vol. 86, no. 9, pp. 821-828, 2016 .

Network mechanisms of intentional learning @article{fb80c447e4394738a4c7de38ba45274f, title = "Network mechanisms of intentional learning", abstract = "The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flexible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ventral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple distinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus-response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated.", keywords = "Caudate, Dynamic causal modelling, Frontal cortex, Functional connectivity, Learning", author = "Adam Hampshire and Hellyer, {Peter J.} and Beth Parkin and Nole Hiebert and Penny MacDonald and Owen, {Adrian M.} and Robert Leech and James Rowe", year = "2016", month = feb, day = "15", doi = "10.1016/j.neuroimage.2015.11.060", language = "English", volume = "127", pages = "123--134", journal = "NeuroImage", issn = "1053-8119", publisher = "ACADEMIC PRESS INC ELSEVIER SCIENCE", } . NeuroImage.

Amyloid pathology and axonal injury after brain trauma @article{9d04bf10d5e9400097478733ae3a72f0, title = "Amyloid pathology and axonal injury after brain trauma", abstract = "OBJECTIVE: To image β-amyloid (Aβ) plaque burden in long-term survivors of traumatic brain injury (TBI), test whether traumatic axonal injury and Aβ are correlated, and compare the spatial distribution of Aβ to Alzheimer disease (AD).METHODS: Patients 11 months to 17 years after moderate-severe TBI underwent (11)C-Pittsburgh compound B ((11)C-PiB)-PET, structural and diffusion MRI, and neuropsychological examination. Healthy aged controls and patients with AD underwent PET and structural MRI. Binding potential (BPND) images of (11)C-PiB, which index Aβ plaque density, were computed using an automatic reference region extraction procedure. Voxelwise and regional differences in BPND were assessed. In TBI, a measure of white matter integrity, fractional anisotropy, was estimated and correlated with (11)C-PiB BPND. RESULTS: Twenty-eight participants (9 with TBI, 9 controls, 10 with AD) were assessed. Increased (11)C-PiB BPND was found in TBI vs controls in the posterior cingulate cortex and cerebellum. Binding in the posterior cingulate cortex increased with decreasing fractional anisotropy of associated white matter tracts and increased with time since injury. Compared to AD, binding after TBI was lower in neocortical regions but increased in the cerebellum.CONCLUSIONS: Increased Aβ burden was observed in TBI. The distribution overlaps with, but is distinct from, that of AD. This suggests a mechanistic link between TBI and the development of neuropathologic features of dementia, which may relate to axonal damage produced by the injury.", author = "Gregory Scott and Ramlackhansingh, {Anil F} and Paul Edison and Peter Hellyer and James Cole and Mattia Veronese and Rob Leech and Greenwood, {Richard J} and Turkheimer, {Federico E} and Gentleman, {Steve M} and Heckemann, {Rolf A} and Matthews, {Paul M} and Brooks, {David J} and Sharp, {David J}", note = "{\textcopyright} 2016 American Academy of Neurology.", year = "2016", month = feb, day = "3", doi = "10.1212/WNL.0000000000002413", language = "English", journal = "Neurology", issn = "0028-3878", publisher = "LIPPINCOTT WILLIAMS & WILKINS", } . Neurology.

Hampshire A, Hellyer PJ, Parkin B, Hiebert N, MacDonald P, Owen AM, Leech R, Rowe J, NeuroImage, 2016, vol. 127, pp. 123-134, 2016 .

Local inhibitory plasticity tunes macroscopic brain dynamics and allows the emergence of functional brain networks @article{c4f72a91aed04e579b2be97b8b6b4d36, title = "Local inhibitory plasticity tunes macroscopic brain dynamics and allows the emergence of functional brain networks", abstract = "Rich, spontaneous brain activity has been observed across a range of different temporal and spatial scales. These dynamics are thought to be important for efficient neural functioning. A range of experimental evidence suggests that these neural dynamics are maintained across a variety of different cognitive states, in response to alterations of the environment and to changes in brain configuration (e.g., across individuals, development and in many neurological disorders). This suggests that the brain has evolved mechanisms to maintain rich dynamics across a broad range of situations. Several mechanisms based around homeostatic plasticity have been proposed to explain how these dynamics emerge from networks of neurons at the microscopic scale. Here we explore how a homeostatic mechanism may operate at the macroscopic scale: in particular, focusing on how it interacts with the underlying structural network topology and how it gives rise to well-described functional connectivity networks. We use a simple mean-field model of the brain, constrained by empirical white matter structural connectivity where each region of the brain is simulated using a pool of excitatory and inhibitory neurons. We show, as with the microscopic work, that homeostatic plasticity regulates network activity and allows for the emergence of rich, spontaneous dynamics across a range of brain configurations, which otherwise show a very limited range of dynamic regimes. In addition, the simulated functional connectivity of the homeostatic model better resembles empirical functional connectivity network. To accomplish this, we show how the inhibitory weights adapt over time to capture important graph theoretic properties of the underlying structural network. Therefore, this work presents suggests how inhibitory homeostatic mechanisms facilitate stable macroscopic dynamics to emerge in the brain, aiding the formation of functional connectivity networks.", keywords = "Homeostasis, Intrinsic connectivity networks, Neural dynamics, Plasticity", author = "Hellyer, {Peter J.} and Barbara Jachs and Claudia Clopath and Robert Leech", year = "2016", month = jan, day = "1", doi = "10.1016/j.neuroimage.2015.08.069", language = "English", volume = "124", pages = "85--95", journal = "NeuroImage", issn = "1053-8119", publisher = "ACADEMIC PRESS INC ELSEVIER SCIENCE", } . NeuroImage.

Hellyer PJ, Jachs B, Clopath C, Leech R, NeuroImage, 2016, vol. 124, no. Pt A, pp. 85-95, 2016 .

Effects of lesions on synchrony and metastability in cortical networks @article{5529692e027b4fd3b0853a39a0e925c5, title = "Effects of lesions on synchrony and metastability in cortical networks", abstract = "At the macroscopic scale, the human brain can be described as a complex network of white matter tracts integrating grey matter assemblies - the human connectome. The structure of the connectome, which is often described using graph theoretic approaches, can be used to model macroscopic brain function at low computational cost. Here, we use the Kuramoto model of coupled oscillators with time-delays, calibrated with respect to empirical functional MRI data, to study the relation between the structure of the connectome and two aspects of functional brain dynamics - synchrony, a measure of general coherence, and metastability, a measure of dynamical flexibility. Specifically, we investigate the relationship between the local structure of the connectome, quantified using graph theory, and the synchrony and metastability of the model's dynamics. By removing individual nodes and all of their connections from the model, we study the effect of lesions on both global and local dynamics. Of the nine nodal graph-theoretical properties tested, two were able to predict effects of node lesion on the global dynamics. The removal of nodes with high eigenvector centrality leads to decreases in global synchrony and increases in global metastability, as does the removal of hub nodes joining topologically segregated network modules. At the level of local dynamics in the neighbourhood of the lesioned node, structural properties of the lesioned nodes hold more predictive power, as five nodal graph theoretical measures are related to changes in local dynamics following node lesions. We discuss these results in the context of empirical studies of stroke and functional brain dynamics.", keywords = "Connectome, Graph theory, Kuramoto model, Metastability, Neural dynamics, Stroke", author = "Franti{\v s}ek V{\'a}{\v s}a and Murray Shanahan and Hellyer, {Peter J.} and Gregory Scott and Joana Cabral and Robert Leech", year = "2015", month = sep, day = "1", doi = "10.1016/j.neuroimage.2015.05.042", language = "English", volume = "118", pages = "456--467", journal = "NeuroImage", issn = "1053-8119", publisher = "ACADEMIC PRESS INC ELSEVIER SCIENCE", } . NeuroImage.

František Váša, Murray Shanahan, Peter J. Hellyer, Gregory Scott, Joana Cabral, Robert Leech(2015). Effects of lesions on synchrony and metastability in cortical networks . NeuroImage. 118. p. 456--467. Elsevier {BV}

Dental students' perceptions of their experience at a residential outreach centre @article{76ff5a5b3e1342d9ab6d5dcbe7394293, title = "Dental students' perceptions of their experience at a residential outreach centre", abstract = "Introduction The Portsmouth Dental Academy delivers an interprofessional education to dental students on outreach placement from King's College London Dental Institute.Aim To establish what the dental students' attitudes to the placement are and how these correlate to the perceptions of the staff who work with them.Method Using Delphi consensus procedures, a simple, closed, two-question questionnaire was developed. The questionnaire was completed by the students and then, to triangulate the results, was subsequently applied to staff who teach and assist them on clinic.Results To the question: Why do you think the experience that is commonly termed the 'Portsmouth experience' is so successful 'in the eyes of the students'?, the students ranked first the response: 'Students gain experience in primary dental care clinical practice under the current NHS contract - UDAs and KPIs'. To the second question: What do you think the students most enjoyed about working in Portsmouth?, the students ranked first: 'A sense of independence - being made to make their own decisions'.Conclusion The students' major perception of the 'Portsmouth experience' centres around the placement being a realistic preparation for their future practising career. This is combined with a strong sense of belonging when studying and working at the Academy.", author = "Radford, {D. R.} and P. Hellyer", year = "2015", month = aug, day = "28", doi = "10.1038/sj.bdj.2015.646", language = "English", volume = "219", pages = "171--174", journal = "British Dental Journal", issn = "0007-0610", publisher = "Nature Publishing Group", number = "4", } . British Dental Journal.

Cognitive flexibility through metastable neural dynamics is disrupted by damage to the structural connectome @article{03a21d0962a741c689e65c844328da53, title = "Cognitive flexibility through metastable neural dynamics is disrupted by damage to the structural connectome", abstract = "Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome.", keywords = "Cognitive flexibility, Computational modeling, Connectome, Metastability, Traumatic brain injury", author = "Hellyer, {Peter J.} and Gregory Scott and Murray Shanahan and Sharp, {David J.} and Robert Leech", year = "2015", month = jun, day = "17", doi = "10.1523/JNEUROSCI.4648-14.2015", language = "English", volume = "35", pages = "9050--9063", journal = "Journal of Neuroscience", issn = "0270-6474", publisher = "Society for Neuroscience", number = "24", } . Journal of Neuroscience.

Graph embeddings of dynamic functional connectivity reveal discriminative patterns of task engagement in HCP data @article{6d342b22e5ff4d6c9c604d3b2d534d38, title = "Graph embeddings of dynamic functional connectivity reveal discriminative patterns of task engagement in HCP data", abstract = "There is increasing evidence to suggest functional connectivity networks are non-stationary. This has lead to the development of novel methodologies with which to accurately estimate time-varying functional connectivity networks. Many of these methods provide unprecedented temporal granularity by estimating a functional connectivity network at each point in time; resulting in high-dimensional output which can be studied in a variety of ways. One possible method is to employ graph embedding algorithms. Such algorithms effectively map estimated networks from high-dimensional spaces down to a low dimensional vector space; thus facilitating visualization, interpretation and classification. In this work, the dynamic properties of functional connectivity are studied using working memory task data from the Human Connectome Project. A recently proposed method is employed to estimate dynamic functional connectivity networks. The results are subsequently analyzed using two graph embedding methods based on linear projections. These methods are shown to provide informative embeddings that can be directly interpreted as functional connectivity networks.", keywords = "stat.AP, q-bio.NC", author = "Monti, {Ricardo Pio} and Romy Lorenz and Peter Hellyer and Robert Leech and Christoforos Anagnostopoulos and Giovanni Montana", note = "4 pages, 1 figure, 5th International Workshop on Pattern Recognition in Neuroimaging, Stanford University, 2015", year = "2015", month = jun, day = "17", language = "Undefined/Unknown", journal = " arXiv", } . arXiv.

Váša F, Shanahan M, Hellyer PJ, Scott G, Cabral J, Leech R, NeuroImage, 2015 .

Fagerholm ED, Hellyer PJ, Scott G, Leech R, Sharp DJ, Brain : a journal of neurology, 2015, vol. 138, no. Pt 6, pp. 1696-1709 .

Hellyer PJ, Scott G, Shanahan M, Sharp DJ, Leech R, The Journal of neuroscience : the official journal of the Society for Neuroscience, 2015, vol. 35, no. 24, pp. 9050-9063 .

Parkin BL, Hellyer PJ, Leech R, Hampshire A, The Journal of neuroscience : the official journal of the Society for Neuroscience, 2015, vol. 35, no. 20, pp. 7660-7673 .

Scott G, Hellyer PJ, Hampshire A, Leech R, Human brain mapping, 2015, vol. 36, no. 4, pp. 1348-1364 .

Fagerholm ED, Lorenz R, Scott G, Dinov M, Hellyer PJ, Mirzaei N, Leeson C, Carmichael DW, Sharp DJ, Shew WL, Leech R, The Journal of neuroscience : the official journal of the Society for Neuroscience, 2015, vol. 35, no. 11, pp. 4626-4634 .

The Neuroanatomical Correlates of Training-Related Perceptuo-Reflex Uncoupling in Dancers @article{4ff67d96e1ee447db72e092171d8dcfb, title = "The Neuroanatomical Correlates of Training-Related Perceptuo-Reflex Uncoupling in Dancers", abstract = "Sensory input evokes low-order reflexes and higher-order perceptual responses. Vestibular stimulation elicits vestibular-ocular reflex (VOR) and self-motion perception (e.g., vertigo) whose response durations are normally equal. Adaptation to repeated whole-body rotations, for example, ballet training, is known to reduce vestibular responses. We investigated the neuroanatomical correlates of vestibular perceptuo-reflex adaptation in ballet dancers and controls. Dancers' vestibular-reflex and perceptual responses to whole-body yaw-plane step rotations were: (1) Briefer and (2) uncorrelated (controls' reflex and perception were correlated). Voxel-based morphometry showed a selective gray matter (GM) reduction in dancers' vestibular cerebellum correlating with ballet experience. Dancers' vestibular cerebellar GM density reduction was related to shorter perceptual responses (i.e. positively correlated) but longer VOR duration (negatively correlated). Contrastingly, controls' vestibular cerebellar GM density negatively correlated with perception and VOR. Diffusion-tensor imaging showed that cerebral cortex white matter (WM) microstructure correlated with vestibular perception but only in controls. In summary, dancers display vestibular perceptuo-reflex dissociation with the neuronatomical correlate localized to the vestibular cerebellum. Controls' robust vestibular perception correlated with a cortical WM network conspicuously absent in dancers. Since primary vestibular afferents synapse in the vestibular cerebellum, we speculate that a cerebellar gating of perceptual signals to cortical regions mediates the training-related attenuation of vestibular perception and perceptuo-reflex uncoupling.", author = "Y. Nigmatullina and P.J. Hellyer and P. Nachev and D.J. Sharp and BM. Seemungal", year = "2015", month = feb, doi = "10.1093/cercor/bht266", language = "English", volume = "25", pages = "554--562", journal = "Cerebral Cortex", issn = "1047-3211", publisher = "Oxford University Press", number = "2", } . Cerebral Cortex.

Scott G, Hellyer PJ, Ramlackhansingh AF, Brooks DJ, Matthews PM, Sharp DJ, Journal of neuroinflammation, 2015, vol. 12, pp. 224, 2015 .

Homological scaffolds of brain functional networks @article{bdd6fd040a7b4f3490d089593f983238, title = "Homological scaffolds of brain functional networks", abstract = "Networks, as efficient representations of complex systems, have appealed to scientists for a long time and now permeate many areas of science, including neuroimaging (Bullmore and Sporns 2009 Nat. Rev. Neurosci. 10, 186–198. (doi:10.1038/nrn2618)). Traditionally, the structure of complex networks has been studied through their statistical properties and metrics concerned with node and link properties, e.g. degree-distribution, node centrality and modularity. Here, we study the characteristics of functional brain networks at the mesoscopic level from a novel perspective that highlights the role of inhomogeneities in the fabric of functional connections. This can be done by focusing on the features of a set of topological objects—homological cycles—associated with the weighted functional network. We leverage the detected topological information to define the homological scaffolds, a new set of objects designed to represent compactly the homological features of the correlation network and simultaneously make their homological properties amenable to networks theoretical methods. As a proof of principle, we apply these tools to compare resting-state functional brain activity in 15 healthy volunteers after intravenous infusion of placebo and psilocybin—the main psychoactive component of magic mushrooms. The results show that the homological structure of the brain's functional patterns undergoes a dramatic change post-psilocybin, characterized by the appearance of many transient structures of low stability and of a small number of persistent ones that are not observed in the case of placebo.", author = "Giovanni Petri and Paul Expert and Federico Turkheimer and Carhart-Harris, {Robin L} and Nutt, {David J.} and Pete Hellyer and Francesco Vaccarino", year = "2014", month = dec, day = "6", doi = "10.1098/rsif.2014.0873", language = "English", volume = "11", pages = "1--10", journal = "Journal of the Royal Society, Interface / the Royal Society", issn = "1742-5689", publisher = "The Royal Society", number = "101", } . Journal of the Royal Society, Interface / the Royal Society.

Petri G, Expert P, Turkheimer F, Carhart-Harris R, Nutt D, Hellyer PJ, Vaccarino F, Journal of the Royal Society, Interface / the Royal Society, 2014, vol. 11, no. 101, pp. 20140873 .

Monti RP, Hellyer P, Sharp D, Leech R, Anagnostopoulos C, Montana G, NeuroImage, 2014, vol. 103, pp. 427-443 .

Estimating time-varying brain connectivity networks from functional MRI time series @article{55f2bc06f9da4187bac315f4440969ad, title = "Estimating time-varying brain connectivity networks from functional MRI time series", abstract = "At the forefront of neuroimaging is the understanding of the functional architecture of the human brain. In most applications functional networks are assumed to be stationary, resulting in a single network estimated for the entire time course. However recent results suggest that the connectivity between brain regions is highly non-stationary even at rest. As a result, there is a need for new brain imaging methodologies that comprehensively account for the dynamic nature of functional networks. In this work we propose the Smooth Incremental Graphical Lasso Estimation (SINGLE) algorithm which estimates dynamic brain networks from fMRI data. We apply the proposed algorithm to functional MRI data from 24 healthy patients performing a Choice Reaction Task to demonstrate the dynamic changes in network structure that accompany a simple but attentionally demanding cognitive task. Using graph theoretic measures we show that the properties of the Right Inferior Frontal Gyrus and the Right Inferior Parietal lobe dynamically change with the task. These regions are frequently reported as playing an important role in cognitive control. Our results suggest that both these regions play a key role in the attention and executive function during cognitively demanding tasks and may be fundamental in regulating the balance between other brain regions.", author = "Monti, {Ricardo Pio} and Peter Hellyer and David Sharp and Robert Leech and Christoforos Anagnostopoulos and Giovanni Montana", year = "2014", month = dec, doi = "10.1016/j.neuroimage.2014.07.033", language = "English", volume = "103", pages = "427--443", journal = "NeuroImage. Clinical", issn = "1053-8119", publisher = "Elsevier", } . NeuroImage. Clinical.

Ham TE, Bonnelle V, Hellyer P, Jilka S, Robertson IH, Leech R, Sharp DJ, Brain : a journal of neurology, 2014, vol. 137, no. Pt 2, pp. 586-597 .

The entropic brain @article{fee3c747c0b14c51af56509fabc1f9d4, title = "The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs", abstract = "Entropy is a dimensionless quantity that is used for measuring uncertainty about the state of a system but it can also imply physical qualities, where high entropy is synonymous with high disorder. Entropy is applied here in the context of states of consciousness and their associated neurodynamics, with a particular focus on the psychedelic state. The psychedelic state is considered an exemplar of a primitive or primary state of consciousness that preceded the development of modern, adult, human, normal waking consciousness. Based on neuroimaging data with psilocybin, a classic psychedelic drug, it is argued that the defining feature of “primary states” is elevated entropy in certain aspects of brain function, such as the repertoire of functional connectivity motifs that form and fragment across time. Indeed, since there is a greater repertoire of connectivity motifs in the psychedelic state than in normal waking consciousness, this implies that primary states may exhibit “criticality,” i.e., the property of being poised at a “critical” point in a transition zone between order and disorder where certain phenomena such as power-law scaling appear. Moreover, if primary states are critical, then this suggests that entropy is suppressed in normal waking consciousness, meaning that the brain operates just below criticality. It is argued that this entropy suppression furnishes normal waking consciousness with a constrained quality and associated metacognitive functions, including reality-testing and self-awareness. It is also proposed that entry into primary states depends on a collapse of the normally highly organized activity within the default-mode network (DMN) and a decoupling between the DMN and the medial temporal lobes (which are normally significantly coupled). These hypotheses can be tested by examining brain activity and associated cognition in other candidate primary states such as rapid eye movement (REM) sleep and early psychosis and comparing these with non-primary states such as normal waking consciousness and the anaesthetized state.", author = "Carhart-Harris, {Robin L} and Robert Leech and Hellyer, {Peter J} and Murray Shanahan and Amanda Feilding and Enzo Tagliazucchi and Chialvo, {Dante R} and David Nutt", year = "2014", month = feb, doi = "10.3389/fnhum.2014.00020", language = "Undefined/Unknown", volume = "8", journal = "Frontiers in human neuroscience", number = "20", } . Frontiers in human neuroscience.

The control of global brain dynamics @article{125ab0288bee4edda22d19959ec61e67, title = "The control of global brain dynamics: opposing actions of frontoparietal control and default mode networks on attention", abstract = "Understanding how dynamic changes in brain activity control behavior is a major challenge of cognitive neuroscience. Here, we consider the brain as a complex dynamic system and define two measures of brain dynamics: the synchrony of brain activity, measured by the spatial coherence of the BOLD signal across regions of the brain; and metastability, which we define as the extent to which synchrony varies over time. We investigate the relationship among brain network activity, metastability, and cognitive state in humans, testing the hypothesis that global metastability is “tuned” by network interactions. We study the following two conditions: (1) an attentionally demanding choice reaction time task (CRT); and (2) an unconstrained “rest” state. Functional MRI demonstrated increased synchrony, and decreased metastability was associated with increased activity within the frontoparietal control/dorsal attention network (FPCN/DAN) activity and decreased default mode network (DMN) activity during the CRT compared with rest. Using a computational model of neural dynamics that is constrained by white matter structure to test whether simulated changes in FPCN/DAN and DMN activity produce similar effects, we demonstate that activation of the FPCN/DAN increases global synchrony and decreases metastability. DMN activation had the opposite effects. These results suggest that the balance of activity in the FPCN/DAN and DMN might control global metastability, providing a mechanistic explanation of how attentional state is shifted between an unfocused/exploratory mode characterized by high metastability, and a focused/constrained mode characterized by low metastability.", author = "Hellyer, {Peter J} and Murray Shanahan and Gregory Scott and Wise, {Richard JS} and Sharp, {David J} and Robert Leech", year = "2014", month = jan, doi = "10.1523/JNEUROSCI.1853-13.2014", language = "Undefined/Unknown", volume = "34", pages = "451--461", journal = "Journal of neuroscience", issn = "0270-6474", publisher = "Society for Neuroscience", number = "2", } . Journal of neuroscience.

Hellyer PJ, Shanahan M, Scott G, Wise RJ, Sharp DJ, Leech R, The Journal of neuroscience : the official journal of the Society for Neuroscience, 2014, vol. 34, no. 2, pp. 451-461 .

Carhart-Harris RL, Leech R, Hellyer PJ, Shanahan M, Feilding A, Tagliazucchi E, Chialvo DR, Nutt D, Frontiers in human neuroscience, 2014, vol. 8, pp. 20 .

Pituitary dysfunction after blast traumatic brain injury @article{2251f4d0829348c5ae1f76e5aba8e6c3, title = "Pituitary dysfunction after blast traumatic brain injury", abstract = "ObjectivePituitary dysfunction is a recognized consequence of traumatic brain injury (TBI) that causes cognitive, psychological, and metabolic impairment. Hormone replacement offers a therapeutic opportunity. Blast TBI (bTBI) from improvised explosive devices is commonly seen in soldiers returning from recent conflicts. We investigated: (1) the prevalence and consequences of pituitary dysfunction following moderate to severe bTBI and (2) whether it is associated with particular patterns of brain injury.MethodsNineteen male soldiers with moderate to severe bTBI (median age = 28.3 years) and 39 male controls with moderate to severe nonblast TBI (nbTBI; median age = 32.3 years) underwent full dynamic endocrine assessment between 2 and 48 months after injury. In addition, soldiers had structural brain magnetic resonance imaging, including diffusion tensor imaging (DTI), and cognitive assessment.ResultsSix of 19 (32.0%) soldiers with bTBI, but only 1 of 39 (2.6%) nbTBI controls, had anterior pituitary dysfunction (p = 0.004). Two soldiers had hyperprolactinemia, 2 had growth hormone (GH) deficiency, 1 had adrenocorticotropic hormone (ACTH) deficiency, and 1 had combined GH/ACTH/gonadotrophin deficiency. DTI measures of white matter structure showed greater traumatic axonal injury in the cerebellum and corpus callosum in those soldiers with pituitary dysfunction than in those without. Soldiers with pituitary dysfunction after bTBI also had a higher prevalence of skull/facial fractures and worse cognitive function. Four soldiers (21.1%) commenced hormone replacement(s) for hypopituitarism.InterpretationWe reveal a high prevalence of anterior pituitary dysfunction in soldiers suffering moderate to severe bTBI, which was more frequent than in a matched group of civilian moderate to severe nbTBI subjects. We recommend that all patients with moderate to severe bTBI should routinely have comprehensive assessment of endocrine function.", author = "David Baxter and Sharp, {David J} and Claire Feeney and Debbie Papadopoulou and Ham, {Timothy E} and Sagar Jilka and Hellyer, {Peter J} and Patel, {Maneesh C} and Bennett, {Alexander N} and Alan Mistlin", year = "2013", month = oct, doi = "10.1002/ana.23958", language = "English", volume = "74", pages = "527--536", journal = "Annals of Neurology", issn = "0364-5134", publisher = "John Wiley and Sons Inc.", number = "4", } . Annals of Neurology.

Baxter D, Sharp DJ, Feeney C, Papadopoulou D, Ham TE, Jilka S, Hellyer PJ, Patel MC, Bennett AN, Mistlin A, McGilloway E, Midwinter M, Goldstone AP, Annals of neurology, 2013, vol. 74, no. 4, pp. 527-536 .

Nigmatullina Y, Hellyer PJ, Nachev P, Sharp DJ, Seemungal BM, Cerebral cortex (New York, N.Y. : 1991), 2013 .

Individual prediction of white matter injury following traumatic brain injury @article{6299b5db8f8746feb8cffcd31830ff0a, title = "Individual prediction of white matter injury following traumatic brain injury", abstract = "OBJECTIVE:Traumatic brain injury (TBI) often results in traumatic axonal injury (TAI). This can be difficult to identify using conventional imaging. Diffusion tensor imaging (DTI) offers a method of assessing axonal damage in vivo, but has previously mainly been used to investigate groups of patients. Machine learning techniques are increasingly used to improve diagnosis based on complex imaging measures. We investigated whether machine learning applied to DTI data can be used to diagnose white matter damage after TBI and to predict neuropsychological outcome in individual patients.METHODS:We trained pattern classifiers to predict the presence of white matter damage in 25 TBI patients with microbleed evidence of TAI compared to neurologically healthy age-matched controls. We then applied these classifiers to 35 additional patients with no conventional imaging evidence of TAI. Finally, we used regression analyses to predict indices of neuropsychological outcome for information processing speed, executive function, and associative memory in a group of 70 heterogeneous patients.RESULTS:The classifiers discriminated between patients with microbleeds and age-matched controls with a high degree of accuracy, and outperformed other methods. When the trained classifiers were applied to patients without microbleeds, patients having likely TAI showed evidence of greater cognitive impairment in information processing speed and executive function. The classifiers were also able to predict the extent of impairments in information processing speed and executive function.INTERPRETATION:The work provides a proof of principle that multivariate techniques can be used with DTI to provide diagnostic information about clinically significant TAI.", author = "Hellyer, {Peter J} and Robert Leech and Ham, {Timothy E} and Valerie Bonnelle and Sharp, {David J}", year = "2013", month = apr, doi = "10.1002/ana.23824", language = "Undefined/Unknown", volume = "73", pages = "489--499", journal = "Annals of Neurology", issn = "0364-5134", publisher = "John Wiley and Sons Inc.", number = "4", } . Annals of Neurology.

Timothy Ham, Valerie Bonnelle, Peter J Hellyer, Sagar Jilka, Ian Robertson, Robert Leech, David Sharp(2013). The neural basis of impaired self-awareness after traumatic brain injury . Brain research. p. 586--597. Elsevier

Hellyer, P.J.(2013). Individual prediction of white matter injury following traumatic brain injury . Annals of Neurology.

An investigation of twenty/20 vision in reading @article{e8d5806937314b7898e5de9e71ef66f4, title = "An investigation of twenty/20 vision in reading", abstract = "One functional anatomical model of reading, drawing on human neuropsychological and neuroimaging data, proposes that a region in left ventral occipitotemporal cortex (vOT) becomes, through experience, specialized for written word perception. We tested this hypothesis by presenting numbers in orthographical and digital form with two task demands, phonological and numerical. We observed a main effect of task on left vOT activity but not stimulus type, with increased activity during the phonological task that was also associated with increased activity in the left inferior frontal gyrus, a region implicated in speech production. Region-of-interest analysis confirmed that there was equal activity for orthographical and digital written forms in the left vOT during the phonological task, despite greater visual complexity of the orthographical forms. This evidence is incompatible with a predominantly feedforward model of written word recognition that proposes that the left vOT is a specialized cortical module for word recognition in literate subjects. Rather, the physiological data presented here fits better with interactive computational models of reading that propose that written word recognition emerges from bidirectional interactions between three processes: visual, phonological, and semantic. Further, the present study is in accord with others that indicate that the left vOT is a route through which nonlinguistic stimuli, perhaps high contrast two-dimensional objects in particular, gain access to a predominantly left-lateralized language and semantic system.", author = "Hellyer, {Peter J} and Woodhead, {Zo{\'e} VJ} and Robert Leech and Wise, {Richard JS}", year = "2011", month = oct, day = "12", doi = "10.1523/JNEUROSCI.2740-11.2011", language = "English", volume = "31", pages = "14631--14638", journal = "Journal of neuroscience", issn = "0270-6474", publisher = "Society for Neuroscience", number = "41", } . Journal of neuroscience.

Hellyer, P.J.(2011). An investigation of Twenty/20 vision in reading . Journal of Neuroscience. 31. (41). p. 14631-14638.

PREPRINT

Sijia Zhao, Kengo Shibata, Peter J. Hellyer, William Trender, Sanjay Manohar, Adam Hampshire, Masud Husain(2021). Rapid vigilance and episodic memory decrements in COVID-19 survivors . Cold Spring Harbor Laboratory

OTHER

Jessica Dafflon, Pedro F. Da Costa, František Váša, Ricardo Pio Monti, Danilo Bzdok, Peter J. Hellyer, Federico Turkheimer, Jonathan Smallwood, Emily Jones, Robert Leech(2020). Neuroimaging: into the Multiverse . Cold Spring Harbor Laboratory

Peter Hellyer, Adam Hampshire, William Trender, Samuel R Chamberlain, Amy Jolly, Jon E. Grant, Fiona Patrick, Ndaba Mazibuko, Steve Williams, Joseph M Barnby, et al.(2020). Cognitive deficits in people who have recovered from COVID-19 relative to controls: An N=84,285 online study . Cold Spring Harbor Laboratory

Richard E. Daws, Gregory Scott, Eyal Soreq, Robert Leech, Peter J. Hellyer, Adam Hampshire(2020). Optimisation of functional network resources when learning behavioural strategies for performing complex tasks . Cold Spring Harbor Laboratory

Conflicting Emergences. Weak vs. strong emergence for the modelling of brain function @article{8dd251aaf7d94c8ba4f8b9c310039ea9, title = "Conflicting Emergences. Weak vs. strong emergence for the modelling of brain function", abstract = "The concept of {"}emergence{"} has become commonplace in the modelling of complex systems, both natural and man-made; a functional property{"} emerges{"} from a system when it cannot be readily explained by the properties of the system's sub-units. A bewildering array of adaptive and sophisticated behaviours can be observed from large ensembles of elementary agents such as ant colonies, bird flocks or by the interactions of elementary material units such as molecules or weather elements. Ultimately, emergence has been adopted as the ontological support of a number of attempts to model brain function. This manuscript aims to clarify the ontology of emergence and delve into its many facets, particularly into its {"}strong{"} and {"}weak{"} versions that underpin two different approaches to the modelling of behaviour. The first group of models is here represented by the {"}free energy{"} principle of brain function and the {"}integrated information theory{"} of consciousness. The second group is instead represented by computational models such as oscillatory networks that use mathematical scalable representations to generate emergent behaviours and are then able to bridge neurobiology with higher mental functions. Drawing on the epistemological literature, we observe that due to their loose mechanistic links with the underlying biology, models based on strong forms of emergence are at risk of metaphysical implausibility. This, in practical terms, translates into the overdetermination that occurs when the proposed model becomes only one of a large set of possible explanations for the observable phenomena. On the other hand, computational models that start from biologically plausible elementary units, hence are weakly emergent, are not limited by ontological faults and, if scalable and able to realistically simulate the hierarchies of brain output, represent a powerful vehicle for future neuroscientific research programmes.", keywords = "Bayesian inference, Brain, Computational models, Emergence, Free energy principle, Integrated information theory, Multi-scale, Oscillators, Strong emergence, Weak emergence", author = "Turkheimer, {Federico E} and Peter Hellyer and Kehagia, {Angie A} and Paul Expert and Louis-David Lord and Jakub Vohryzek and {De Faria Dafflon}, Jessica and Mick Brammer and Robert Leech", note = "Copyright {\textcopyright} 2019. Published by Elsevier Ltd.", year = "2019", month = apr, doi = "10.1016/j.neubiorev.2019.01.023", language = "English", volume = "99", pages = "3--10", journal = "Neuroscience and Biobehavioral Reviews", issn = "0149-7634", } . Neuroscience and Biobehavioral Reviews.

WORKING PAPER

Balanced activation in a simple embodied neural simulation @techreport{4a529523bec64daa949b2aba68c2da57, title = "Balanced activation in a simple embodied neural simulation", abstract = "In recent years, there have been many computational models exploring how spontaneous neural dynamics arise out of the brain's structural connectome. Most of these models have focused on the resting state (with no external input) or investigate the effects of simple sensory inputs. However, neural systems exist to process incoming information from the environment and to guide motor output. Here, we explore a very simple neural network model (similar to that used previously to model dynamics at rest) and allow it to control a virtual agent in a very simple environment. This setup generates interesting brain-environment interactions that suggest the need for homeostatic mechanisms to maintain rich spontaneous dynamics. We investigate roles for both local homeostatic plasticity as well as macroscopic task negative activity (that compensates for task positive, sensory input) in regulating activity in response to changing environment. Our results suggest complementary functional roles for both balanced local homeostatic plasticity and balanced task-positive task negative activity in maintaining simulated neural dynamics in the face of interactions with the environment. This work highlights the challenges that feedback between environment and brain presents to neural models as well as the different roles that balancing mechanisms may play; it also suggests a functional role for macroscopic task negative systems in the brain that may be of relevance to understanding large-scale brain systems such as the default mode network.", keywords = "q-bio.NC", author = "Hellyer, {Peter J.} and Claudia Clopath and Kehagia, {Angie A.} and Turkheimer, {Federico E.} and Robert Leech", note = "26 pages, 7 figures, associated github repository: https://github.com/c3nl-neuraldynamics/Avatar", year = "2016", month = jun, day = "11", language = "English", type = "WorkingPaper", } .