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Tim Salomons - https://lepubscientifique.com/le-pub-events/

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How to speak so that people want to listen

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Have you ever felt like you’re talking, but nobody is listening? Here’s Julian Treasure to help. In this useful talk, the sound expert demonstrates the how-to’s of powerful speaking -- from some handy vocal exercises to tips on how to speak with empathy. A talk that might help the world sound more beautiful.

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Filip Maric does some work in this space! See this paper for a start: https://www.tandfonline.com/doi/full/10.1080/0142159X.2020.1798914?casa_token=eJDGRHvn4jYAAAAA%3Auh-nfC4_pX-IQy56jP2lS9bI0H-V7KzKdeAThj-_y1jChaUwG6BMRXtl9EVQMnTbpGmFqWMEHae3

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'action at the level of direct drivers of nature decline, although necessary, is not sufficient ... a sustainable global future' is 'only possible with urgent transformative change that tackles the root causes: the interconnected economic, socio-cultural, demographic, political, institutional, and technological indirect drivers behind the direct drivers' (Diaz et al., 2019)

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An international community of academics, clinicians, practitioners and students interested in exploring and advancing the field of environmental physiotherapy. Follow our latest musings on environmental physiotherapy. Ideas, inspiration, news, publications, events, and more. Become part of the first international community of physiotherapists with an interest in researching, developing, and practising physiotherapy at a planetary scale.

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Patient cues to look out for that demonstrate they're not quite 'sticking' with the content

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Patient cues to look out for that demonstrate they're not quite 'sticking' with the content

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Nodding, folding arms, looking dazed, clinician doing all the talking, no questions and discussion

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Keep in touch with the A team and Body in Mind research group!

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Keep in touch with the A team and Body in Mind research group!

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Anna Vogelzang - @anna_vogelzang

Erica Wilkinson - @wilkerica_

Brendan Mouatt – @BrendanMouatt

Tasha Stanton - @Tash_Stanton

Felicity Braithwaite - @dr_flick_

Erin MacIntyre - @erinmacintyre5

Sarah Wallwork -@SarahBWallwork

Caitlin Howlett - @caitlinahowlett

Brian Pulling - @BrianPulling

Millie Mardon - @Millie_Mardon

Emma Karran - @Emmakarran

Jane Chalmers – @KjaneChalmers

Ash Grant - @ashley_grant5

Calie Altman - @carliealtmann

Hayley Leake - @hayleyleake

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What do YOU hear?

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Grover drops F-Bomb on Sesame Street (Original)

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"Education – the most powerful and renewable energy on earth" - Dave Butler

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"Education – the most powerful and renewable energy on earth" - Dave Butler

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Think of this as homeostatic protection model - lots of problems fit here (e.g., chronic fatigue, chronic concussion, anxiety)

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Most of us are DIM hunters (patients and health care professionals)

Let's flip the script and go SIM hunting!

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A fear avoidance pathway as holistic confrontation 

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A fear avoidance pathway as holistic confrontation 

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Suggestion:  HCP uses pre-existing or drawn images/infographics  and seeks contrast with existing mental model. Ideally at least two images/infographics (two allows contrast)

Give time to reflect and observe possible relationships

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Holistic Confrontation targeting flawed mental models 

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Holistic Confrontation targeting flawed mental models 

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Suggestion: Patient draws model which is compared and contrasted with a more appropriate model

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1. You can be completely wrong and off the planet

2. Or have a flawed mental model

3. Or make a categorisation error (misconstruing emergent phenomena as linear)

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Examples for rejecting conspiracy theory

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Examples for rejecting conspiracy theory

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How do we shift our 'conspiracy theories'

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How do we shift our 'conspiracy theories'

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We often go out and seek information that supports our ideas and biases

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We often go out and seek information that supports our ideas and biases

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Pedagogy - teaching kids
Andragogy - teaching adults; difficult because they come with existing knowledge

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A key part of learning should be helping people to learn before they learn to learn

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and fits perfectly with Explain Pain. A great example being Robin Williams in Dead Poets Society

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References for Day 3 Session 5: Dave Butler

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References for Day 3 Session 5: Dave Butler

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Professional Certificate in Pain Sciences

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Professional Certificate in Pain Sciences

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Why the Professional Certificate in Pain Sciences?
On completion of the course Pain Theory and Science, students should be able to:

Describe the biological and psychosocial factors that contribute to pain.

Synthesise theoretical models of pain to explain its complexity from a biopsychosocial perspective.

Describe the functions of nociceptive, immune, autonomic, neuroendocrine and motor systems in pain.

Identify clinical signs and symptoms that are associated with pain-related mechanisms.

Apply pain sciences principles to the assessment and management of people with pain.

Recognise and differentiate important clinical pain states.

On completion of the course Pain Education, students should be able to:

Discuss theoretical approaches to adult education and their application to pain education

Apply a range of teaching strategies to maximise learning in clinical and other education settings.

Design and implement learner-centred education programs for clinician, patient and general public contexts

Critically reflect on the design, implementation and evaluation of teaching and learning activities

Explain pain effectively within a biopsychosocial framework

Who can attend?

This certificate is open to health professionals with undergraduate qualifications and is most suited to those who have clinical experience with patients with pain. Previous completion of undergraduate courses in anatomy, physiology and neuroscience is assumed.

The professional certificate is composed of two pain-specific courses, Pain Theory and Science and Pain Education.

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professional certificate in pain sciences

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Professional Certificate in Pain Sciences

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On completion of the course Pain Theory and Science, students should be able to: Describe the biological and psychosocial factors that contribute to pain. Synthesise theoretical models of pain to explain its complexity from a biopsychosocial perspective. Describe the functions of nociceptive, immune, autonomic, neuroendocrine and motor systems in pain.

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Explain Pain poster set Set of four posters based on concepts from the Explain Pain range, each A2 size (42cm x 60cm), plasticoated finish. AUD $40.00

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Persistent pain affects 30-50% of us

Its impact is significant, negatively affecting our physical and mental health, our social and home lives and our ability to stay in work.

There are a lot of misconceptions about persistent pain

Common public understanding is significantly out of step with current scientific thinking.

Understanding pain is important

How you think about your pain can change the way it feels and how you respond to it.

Healthcare design and delivery doesn't always reflect the best scientific understanding

It often fails to fully embrace the complicated biological, psychological and social nature of pain.

Change is needed

Where better place to start than raising awareness, facilitating a better understanding and empowering people to take back control?

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Its impact is significant, negatively affecting our physical and mental health, our social and home lives and our ability to stay in work. Common public understanding is significantly out of step with current scientific thinking. How you think about your pain can change the way it feels and how you respond to it.

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Unfortunately this is more and more relevant for our Canadian friends

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'Don't flare up (but don't freak out if you do)'

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'Don't flare up (but don't freak out if you do)'

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Can we convince him to do the AMP dance?

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Remember Goldilocks - we have to find just the right amount (of activity, learning, or anything else we do!)

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FOR INDIVIDUALS FOR HEALTH PROFESSIONALS FOR INSURERS

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Explain Pain Handbook
Ongoing pain is now the most costly health problem facing the planet. With the combined yearly cost of treatment and loss of productivity measured in the hundreds of billions of dollars and rising, pain is more costly than heart disease, diabetes and cancer. But the personal cost of chronic pain can be even worse because it can be so distressing, so disabling and so persistent that it stops you from doing the things you want to do - the things that give your life meaning. However, over the last 20 years a new, powerful and scientific treatment has emerged that has been nothing less than a revolution. There are no pills, no electronic gadgets, no bad side effects, and most importantly, you can do it yourself. The Explain Pain Revolution is all about understanding pain - understanding that many things, often surprising things can, and do, contribute to pain, and what to do about these. The Explain Pain Handbook: Protectometer is the latest step in the Explain Pain Revolution from the authors who really started the revolution over a decade ago with the original and best selling book Explain Pain.

Who is this book for?
This book is for anyone experiencing pain, as well as their families, their friends and their health professionals. Whether you are experiencing ongoing back pain, neck pain, shoulder or knee pain, headaches, or have been diagnosed with Fibromyalgia, neuropathic pain, Complex Regional Pain Syndrome or any other chronic pain syndrome, you will find helpful and practical information that will be immediately useful. Many people with chronic pain feel like they have tried everything and run out of options. We know that there are millions of people experiencing chronic pain who have tried therapies of all kinds with no relief and now feel like they are battling on their own. This book is for you! The Explain Pain Handbook: Protectometer has been carefully written and constructed so that you will immediately start to understand your pain better and do things to reduce your pain today. However, if you are currently receiving the assistance of a health professional, The Explain Pain Handbook: Protectometer will help you and your clinician explore new avenues for your recovery and rehabilitation.
What will you learn?
If you stick at it, by the end of this book, you will:

Understand why you are hurting

Know how to 'power up' other therapies, especially movement and exercise

Be well on your way to treating your pain scientifically and safely

Know where you can seek an even deeper understanding of pain

Be ready to help others who are on the same journey

BUY NOW

The centrepiece of this brand new book is 'The Protectometer'. The Protectometer is a device unlike anything else that will help you to develop a deep understanding of YOUR unique and individual experience of pain and create a personalised treatment plan. The Protectometer will help you to understand how many things interact in your life to influence your pain and help you identify ways to change your personal pain formula to reduce pain and get back to living the life you want to.

Find out more...

Every Handbook has a bonus fold-out Sarah-Bella poster that graphically illustrates dozens of pain stories. We invite you to spend some time with Sarah-Bella discovering your personal pain story and ideas for treatment that will give you hope and enable you to reduce your pain and get back to life.

Buy the poster.

A DIM (danger in me ) is anything that is dangerous to your body tissues, life, livelihood, job, happiness and day to day function. A SIM (safety in me) is anything that makes you stronger, healthier, happier and more confident. The most important thing in pain treatment is to identify your DIMs and SIMs, modify and remove DIMs and strengthen and gather SIMS.

Join the community.

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Explain Pain Protectometer Neuro Orthopedic Institute

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Explain Pain HandbookOngoing pain is now the most costly health problem facing the planet. With the combined yearly cost of treatment and loss of productivity measured in the hundreds of billions of dollars and rising, pain is more costly than heart disease, diabetes and cancer.

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A bit of controversy for the right patient!

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Celebrate your comparisons and contradictions!

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Celebrate your comparisons and contradictions!

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And give your patients time to respond (be comfortable in your silence)

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How can you help a learner learn? TIE it up!

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How can you help a learner learn? TIE it up!

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Tactics
Insights
Energy

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Links to key papers in the comments!

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Read the transcript >

Once upon a time, all the lands were fraught with persistent pain. So widespread was this affliction that one in four people experienced it. The pain lasted more than 3 months. It shadowed their daily lives... held them back from everyday activities ... and the interventions they tried proved useless...

Hey, pain! Go away! We've tried it all But still you stay! Moving less, Taking pills, Knives and needles

Hey, pain! Go away! We've tried it all But still you stay!

But the pain remains like a loyal companion.

The peoples' hopes faded and they became resigned to living with the pain - only now, the pain was a beast! Then, along came a group of researchers, of which I am one. "Back off, big fella!" I'm Professor Lorimer Moseley and I'm a pain scientist.

Pain scientists are starting to think differently about pain and its causes. And we're making exciting discoveries...

Like how the way you think about your pain can change the way it feels. Over the next few minutes, I'll help you to understand your pain. Understanding is important because it can change how much things hurt and how much your body can do... And can help you to tame the beast.

First, trust me about this... Pain is not an accurate measure of tissue health. Pain is a protector. By making unpleasant feelings, your brain changes your behaviour - so you can avoid injury or your tissues can heal. Sometimes pain is not helpful - like phantom limb pain. You don't expect a missing limb to ache. But it does and the pain is very real.

So how do we explain this? Pain is a warning signal from your brain that depends on credible evidence to say your body needs protecting. Sometimes it's too protective and you get unnecessary warning signals. Pain scientists now understand that there are many ways our nervous system ends up producing unnecessary warning signals. Take conditioning for example.

Think of Pavlov's dog... Every time food was offered, Pavlov rang a bell. Of course, the dog would salivate seeing the food. This went on for a while. Eventually the dog was conditioned to salivate for the bell alone. Conditioning is just one of the ways your body learns pain. And the longer your nervous system produces pain, the better it gets at producing it. Your body learns pain

So what feeds this beast? Let's look at how pain works... In your body's tissues, there are specific neurones, which normally only respond to harmful stimuli. - whether mechanical, chemical or thermal. When they are activated, they send a warning signal to your spinal cord, which can in turn send a signal to your brain. This activity in neurones is called 'nociception' and it's happening all the time. But it only sometimes results in pain. Most of the time, the brain protects you with other things like movement. Once the warning signal reaches the brain, the brain makes sense of it based on the information arriving and the vast amount already stored. If there's reason to think protection is required, then your brain makes pain.

One of our amazing discoveries is that you can have pain without any physical stimuli. Thoughts and places might activate the warning signals. And the pain feels exactly the same. But it's not just your brain - your spinal cord also learns how to generate unnecessary warning signals.

So how do you know when your nervous system is learning pain? You may notice your pain spreads or comes on without warning. Your body feels odd and it's hard to move properly. Your pain changes quickly with your mood and small annoyances can set it off. Old injuries start to hurt again. You're more sensitive to stimuli. And the longer the pain goes on, the more all of this occurs.

The old way we understood pain left many sufferers feeling like no one believed it was real. Or that for it to hurt so bad, there must be a tissue problem. But we now know how persistent pain happens.

So how can you tame the beast?

Pain is a very personal thing. There's no one size fits all solution. And while you probably have well thought out coping strategies, it's time to take a new approach to dealing with and reducing your pain - one that focuses on retraining your pain system. This might mean testing yourself physically and moving more than you normally would. Being honest about your current attitudes and beliefs can also help. As can asking your health professional new questions.

How do I know if my pain system is being over protective? How can I retrain my pain system to be less protective? How do I know if I'm safe to move?

So be brave and have hope! Because - it is possible to tame the beast!

Visit our website for more information and questions to ask your health professional. tamethebeast.org

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Once upon a time, all the lands were fraught with persistent pain. So widespread was this affliction that one in four people experienced it. The pain lasted more than 3 months. It shadowed their daily lives... held them back from everyday activities ... and the interventions they tried proved useless...

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Permission to Move is a set of tools to treat chronic pain. It is an online course for patients looking to overcome their chronic pain, and it is a collection of resources for clinicians to use in practice.

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Lorimer and Dave on the couch: "The risk of inactivity is greater than the risk of activity"

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Lorimer and Dave on the couch: "The risk of inactivity is greater than the risk of activity"

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"Rest is a decision"

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Target concepts (on the fantastic Pain Revolution website!)

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Target concepts (on the fantastic Pain Revolution website!)

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What do patients value learning about pain?

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What do patients value learning about pain?

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8. Retrain your pain system

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All Target Concepts are on the Pain Rev website too! Great resource!

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All Target Concepts are on the Pain Rev website too! Great resource!

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What do you think Lorimer's expression will be in 5-10 years time? 

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What do you think Lorimer's expression will be in 5-10 years time? 

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Will the moustache return?

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Yes, pain is complex. But "the more you understand, the more likely you will help a patient you haven't met yet make a transformative shift in their life."

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Yes, pain is complex. But "the more you understand, the more likely you will help a patient you haven't met yet make a transformative shift in their life."

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Some days vs all the time? Nuggets of gold in the clinic!

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From Karl Friston' group

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The Wellcome Trust Centre for Neuroimaging, University College London, London, UK

School of Physics, University of Sydney, NSW, Australia

Center for Integrative Brain Function, University of Sydney, NSW, Australia

Brain Dynamics Centre, Westmead Millennium Institute, Westmead, NSW, Australia

Institut für deutsche Sprache und Linguistik, Humboldt-Universität zu Berlin, Berlin, Germany

Biophysical modeling of brain activity has a long and illustrious history ( Ermentrout, 1998; Deco et al., 2008; Coombes, 2010) and has recently profited from technological advances that furnish neuroimaging data at an unprecedented spatiotemporal resolution ( Guillory and Bujarski, 2014; Sporns, 2014). Neuronal modeling is a very active area of research, with applications ranging from the characterization of neurobiological and cognitive processes, ( Jirsa, 2004b, a; Bojak and Liley, 2005; Phillips and Robinson, 2009; Rolls and Treves, 2011) to constructing artificial brains in silico and building brain-machine interface and neuroprosthetic devices, e.g., Einevoll et al., 2013; Whalen et al., 2013. Biophysical modeling has always benefited from interdisciplinary interactions between different and seemingly distant fields; ranging from mathematics and engineering to linguistics and psychology. This Research Topic aims to promote such interactions by promoting papers that contribute to a deeper understanding of neural activity as measured by fMRI or electrophysiology.

In general, mean field models of neural activity can be divided into two classes: neural mass and neural field models. The main difference between these classes is that field models prescribe how a quantity characterizing neural activity (such as average depolarization of a neural population) evolves over both space and time as opposed to mass models, which characterize activity over time only; by assuming that all neurons in a population are located at (approximately) the same point. This Research Topic focusses on both classes of models and considers several aspects and their relative merits that: span from synapses to the whole brain; comparisons of their predictions with EEG and MEG spectra of spontaneous brain activity; evoked responses, seizures, and fitting data-to infer brain states and map physiological parameters.

Extensions of Mean Field Models and Modeling of Anaesthetic Action

Some of the contributions consider extensions of neural mass and field models and their relation with other classes of models, with a particular focus on modeling the action of anesthetics:

Liley and Walsh (2013) hypothesize that fast-slow dynamics, as exhibited in individual neuron bursting, dynamically underpins electroencephalographic bursting. They are able to modify a well-known mean field model of the electroencephalogram by adding slow variables. This can be seen as a metaphor for anesthetic action, and allows them to produce a wide variety of burst-like activities. Bojak et al. (2013) look at quantitative modulations of EEG activity resulting from manipulating the anesthetics ketamine and propofol. They are able to determine parameter ranges that produce observed modulations in alpha peak frequency, and predict antagonistic drug interactions. The action of anesthetics, in the context of mean field models, is also discussed by Hutt (2013). The author considers a linear neural population model and presents an analytic derivation of the power spectrum that depends on propofol concentration. He then explains the anesthetic-induced power increase in neural activity as a result of an oscillatory instability and derives conditions under which the power peak shifts to higher frequencies, as observed experimentally in EEG.

The roles of neural mass, conductance based, and neural field models in dynamic causal modeling (DCM) are reviewed and explored by Moran et al. (2013). These authors show that such models can reproduce the characteristics of spectra and evoked responses observed empirically, with conductance based models having a richer repertoire of dynamics than neural mass models. Neural field models are able to capture lateral interactions and allow detailed analysis of structure-function relationships in the cortex.

Modolo et al. (2013) discuss neural masses designed to study the interaction between power-line magnetic fields and brain activity. They demonstrate that EEG alpha power could be modulated by weak membrane depolarization induced by the exposure to power-line magnetic fields and explore the role of input noise on EEG power modulation. A different use of neural fields is presented in Wright and Bourke (2013). These authors propose that both synchronous firing of neurons-and their competition for limited metabolic resources during neural development-lead to ultra-small-world neural networks. These networks then exhibit Möbius strip-like topologies that putatively reflect structure in striatal visual cortex.

The contribution of Pinotsis et al. (2013) introduces a conductance-based neural field model combining biologically realistic synaptic dynamics with neural field equations. These authors demonstrate that both the evoked responses and induced responses show qualitative differences depending on the chosen model, either neural mass or neural field.

Explaining Activity Observed in Neurological Disorders and Cognitive Tasks

Other articles in this Research Topic relate to the use of field models to explain aberrant neural activity and dynamics recorded during cognitive tasks: Kerr et al. (2013) integrate field and network models in a multiscale model. This allows the authors to reveal alterations in cortical information flow between normal subjects and Parkinsonian patients, quantified by a decrease in Spectral Granger Causality between cortical layers in the beta frequency.

Frequency-dependent effects in deep brain stimulation in epileptic patients are studied using computational modeling and intracerebral EEG data in Mina et al. (2013). This paper describes the biophysics of direct stimulation of the thalamic compartment of an established thalamocortical model at the cellular level. It also demonstrates that low-frequency and high-frequency stimulation are beneficial for suppressing epileptic seizures, but that intermediate frequencies favor thalamic oscillations and entrain epileptic dynamics, rather than suppressing them.

Bhattacharya's paper ( Bhattacharya, 2013) also focuses on explaining brain oscillations in sickness and health. The author replaces the "alpha function" approximation for synaptic transmission by a kinetic framework of neurotransmitter and receptor dynamics. The results are compared with experimental studies and shown to be consistent; they also lead to an order of magnitude improvement in simulation times compared to the alpha function approach commonly adopted in neural mass models.

In Srinivasan et al. (2013) the authors study an important phenomenon observed in EEG data, called phase-amplitude coupling, and show how it can be modeled using classical Wilson and Cowan equations. This is not only a mathematical exercise; it allows for a description of important top-down influences on local networks as a result of behavioral (e.g., attentional) or pharmacological manipulations-and fits well with results from the animal and human literature.

In another paper, Robinson et al. (2012) explore the functional neuroimaging measurements required to characterize neocortical activity. In particular, they show that some state changes can occur independently of changes in average amplitude, power, or metabolic indexes. They then introduce a new measure of complexity that can uncover the corresponding dynamical structure inherent in cortical activity, which would otherwise be difficult or impossible to detect.

Finally, beim Graben and Rodrigues (2012) reduce a simplified 3-compartment neuron model into a leaky integrate-and-fire (LIF) model describing spiking dynamics and derive an observation model for dendritic dipole currents in extracellular space that contributes to the local field potential (LFP) of a neural population. They introduce a new way to predict LFPs in network simulations involving only single-compartment neurons and compare their method with the results of an earlier approach ( Mazzoni et al., 2008).

Theory of Mean Field Models

In addition to papers focussing on applications, this Research Topic includes theoretical papers studying the mathematical aspects of mean field theory: Bressloff and Wilkerson (2012) study rigorous aspects of field models using an off-centered connectivity kernel that can serve as a model for direction selectivity. They prove the existence and stability of stimulus-induced activity pulses assuming a Heaviside firing rate function and including spatiotemporal noise. These authors conclude that freely moving pulses are more sensitive to multiplicative noise than stimulus-locked pulses.

In Gray and Robinson (2013), the authors address an important issue in the literature on neural networks; that is, what are the effects of time delays and dendritic time constants on the stability constraints of the network dynamics. They approach this question from the perspective of their prior work, in particular the Robinson, Rennie Wright model (RRW). Within this framework, they introduce a constant time delay and then systematically analyze the stability of a network state as a function of time delays and other parameters.

Roy and Jirsa (2013) show how a novel neurocomputational unit model qualitatively captures the complex dynamics exhibited by a full network of parabolic bursting neurons. The reduced representation is mathematically tractable and allows the authors to derive appropriate boundary conditions for various dynamical regimes. This approach sheds light on the role of slow oscillations for determining the global behavior of brain networks. Finally, Augustin et al. (2013) examine how the dynamics of adaptation currents contribute to spike rate oscillations in recurrent neural networks. They find frequency-dependent effects that can have roles in generation of specific frequencies and selective signal propagation.

The above anthology of papers provides illustrative examples of recent advances in biophysical modeling. This line of work speaks to the hope that such models may help explain neural dynamics that underpin disorders like epilepsy or Parkinson's disease as well as normal functions like attention or working memory; an endeavor we hope the articles in this volume will progress.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Ermentrout, B. (1998). Neural networks as spatio-temporal pattern-forming systems. Rep. Prog. Phys. 61, 353. doi: 10.1088/0034-4885/61/4/002

CrossRef Full Text | Google Scholar

Whalen, A. J., Brennan, S. N., Sauer, T. D., and Schiff, S. J. (2013). Observability and controllability of neuronal network motifs. arXiv preprint arXiv. 1307, 5478.
Google Scholar
Keywords: integro-differential equations, neural field theory, neural masses, anaesthesia, electrophysiology, electroencephalogram, oscillations, neural disorders

Citation: Pinotsis D, Robinson P, beim Graben P and Friston K (2014) Neural masses and fields: modeling the dynamics of brain activity. Front. Comput. Neurosci. 8:149. doi: 10.3389/fncom.2014.00149

Received: 22 October 2014; Accepted: 30 October 2014;
Published online: 17 November 2014.

Edited and reviewed by: Misha Tsodyks, Weizmann Institute of Science, Israel

Copyright © 2014 Pinotsis, Robinson, beim Graben and Friston. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: d.pinotsis@ucl.ac.uk

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Neural masses and fields: modeling the dynamics of brain activity

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Biophysical modelling of brain activity has a long and illustrious history (Coombes, 2010; Deco et al., 2008; Ermentrout, 1998) and has recently profited from technological advances that furnish neuroimaging data at an unprecedented spatiotemporal resolution (Sporns, 2014; Guillory and Bujarski, 2014).

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Nociplastic pain: towards an understanding of prevalent pain conditions

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Nociplastic pain: towards an understanding of prevalent pain conditions

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Nociplastic pain: towards an understanding of prevalent pain conditions

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Nociplastic pain is the semantic term suggested by the international community of pain researchers to describe a third category of pain that is mechanistically distinct from nociceptive pain, which is caused by ongoing inflammation and damage of tissues, and neuropathic pain, which is caused by nerve damage.

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Mechanism approach diagnosing pain

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Abstract

As a mechanisms-based classification of pain 'peripheral neuropathic pain' (PNP) refers to pain arising from a primary lesion or dysfunction in the peripheral nervous system. Symptoms and signs associated with an assumed dominance of PNP in patients attending for physiotherapy have not been extensively studied. The purpose of this study was to identify symptoms and signs associated with a clinical classification of PNP in patients with low back (± leg) pain. Using a cross-sectional, between-subjects design; four hundred and sixty-four patients with low back (± leg) pain were assessed using a standardised assessment protocol. Patients' pain was assigned a mechanisms-based classification based on experienced clinical judgement. Clinicians then completed a clinical criteria checklist specifying the presence or absence of various clinical criteria. A binary logistic regression analysis with Bayesian model averaging identified a cluster of two symptoms and one sign predictive of PNP, including: 'Pain referred in a dermatomal or cutaneous distribution', 'History of nerve injury, pathology or mechanical compromise' and 'Pain/symptom provocation with mechanical/movement tests (e.g. Active/Passive, Neurodynamic) that move/load/compress neural tissue'. This cluster was found to have high levels of classification accuracy (sensitivity 86.3%, 95% CI: 78.0-92.3; specificity 96.0%, 95% CI: 93.4-97.8; diagnostic odds ratio 150.9, 95% CI: 69.4-328.1). Pattern recognition of this empirically-derived cluster of symptoms and signs may help clinicians identify an assumed dominance of PNP mechanisms in patients with low back pain disorders in a way that might usefully inform subsequent patient management.

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peripheral nervous system diseases / classification*

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peripheral nervous system diseases / physiopathology

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national center for biotechnology information

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Mechanisms-based classifications of musculoskeletal pain: part 2 of 3: symptoms and signs of peripheral neuropathic pain in patients with low back (± leg) pain - PubMed

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As a mechanisms-based classification of pain 'peripheral neuropathic pain' (PNP) refers to pain arising from a primary lesion or dysfunction in the peripheral nervous system. Symptoms and signs associated with an assumed dominance of PNP in patients attending for physiotherapy have not been extensiv ...

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What pieces of the puzzle connect nicely? What pieces don't seem to fit?

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What pieces of the puzzle connect nicely? What pieces don't seem to fit?

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Humans are complex after all!

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Central Sensitization in Musculoskeletal Pain- Lost in Translation-

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Links to key references in the comments!

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Putting into practice another learning technique

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Putting into practice another learning technique

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When the interlude music is THAT GOOD... 

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When the interlude music is THAT GOOD... 

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and then you realise it was part of the activity

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The possibility of detecting molecular patterns, wow!

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The possibility of detecting molecular patterns, wow!

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Opioid-induced hyperalgesia (OIH) is defined as a state of nociceptive sensitization caused by exposure to opioids. The condition is characterized by a paradoxical response whereby a patient receiving opioids for the treatment of pain could actually become more sensitive to certain painful stimuli.

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Toll-like receptors in chronic pain_ Nicotra et al

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"However, the biggest problem in neuroscience is not the limits of technology, but the way inferences are being drawn from that technology"

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The recent unveiling of the BRAIN Initiative promised a greater understanding of cognition through improved imaging techniques. However, the biggest problem in neuroscience is not the limits of technology, but the way inferences are being drawn from that technology.

The usual inference drawn from functional neuroimaging Techniques for viewing the brain and its activity, especiall... studies is that when a certain cognitive process occurs, a particular brain area is active. However, on closer inspection, Poldrack noted an 'epidemic of reasoning' occurring, with researchers falling foul of the fallacy of reverse inference (2006). This is a process of induction entailing reasoning backwards from the observed brain activity to a particular cognitive process not directly tested, but perhaps linked to the task used, drawing on other research implicating that brain area with that cognitive process.

Such inferences are thus weaker than ones drawn from a direct engagement of a cognitive process, and are not deductively valid, because the brain area in question will almost certainly have more than one function. They are often used to interpret unexpected results, but Poldrack states that despite their low predictive power making them relatively uncertain, it has become common for a study's conclusions to rest entirely on a reverse inference. Aside from leading to unsteady conclusions, it may also influence the research that others conduct, wasting large amounts of time and funding while researchers test the wrong questions.

A spectacular recent example of the misuse of reverse inference is that of James Fallon, who used a brain scan to diagnose himself as a psychopath. Fallon noticed that a scan of his own brain, taken during a study on dementia, had abnormally low activity in some frontal lobe areas. Other research has implicated these areas in empathy and moral reasoning, which are allegedly abnormal in psychopathic individuals, leading Fallon to conclude that he too was a psychopath. Nonetheless, research on dementia does not typically use empathy tasks, so it is unlikely that the reduced activity in Fallon's frontal lobes reflected pathological empathic ability. Fallon made a reverse inference - and a silly one at that.

However, despite this grim picture, Poldrack argues that reverse inferences can be used to generate hypotheses for future research, and there are ways to improve the confidence researchers can have in them. Firstly, increasing the specificity of the brain region of interest will narrow down possible cognitive processes, because complex processes (such as empathy) may have been associated with niche areas within a larger structure (such as the frontal lobe) and not with others. A further tactic discussed by Hutzler is to consider the nature of the task used, and only suggest cognitive process which are likely to be involved in that task (an approach Fallon certainly didn't take) (2013). This tactic technically reduces the risk of false alarms, because it reduces the number of alternative explanations, although there still may be several options.

So perhaps reverse inferences can be acceptable, but their blatant misuse is certainly something to watch out for if neuroscience is to truly advance further.

~

Written by Lexie Thorpe.

~

References:

Hutzler F. (2013). Reverse inference is not a fallacy per se: Cognitive processes can be inferred from functional imaging data, NeuroImage, 84 1061-1069. DOI: 10.1016/j.neuroimage.2012.12.075

Poldrack R. (2006). Can cognitive processes be inferred from neuroimaging data?, Trends in Cognitive Sciences, 10 (2) 59-63. DOI: 10.1016/j.tics.2005.12.004

Stromberg, Joseph. "The Neuroscientist Who Discovered He Was A Psychopath." SmithsonianMag. Smithsonian, 22 November 2013. Web. 10 January 2014. < http://www.smithsonianmag.com/science-nature/the-neuroscientist-who-discovered-he-was-a-psychopath-180947814/>.

Image made by Kate Jones and adapted from Hutzler F. (2013).

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Reverse Inference: Neuroscience's Greatest Fallacy? - Knowing Neurons

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The recent unveiling of the BRAIN Initiative promised a greater understanding of cognition through improved imaging techniques. However, the biggest problem in neuroscience is not the limits of technology, but the way inferences are being drawn from that technology. The usual inference drawn from functional neur ...

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The -Amps that increase synaptic efficacy of nociceptive neurotags

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The -Amps that increase synaptic efficacy of nociceptive neurotags

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Damps (damage-Associated Molecular Patterns),

Pamps (Pathogen-Associated Molecular Patterns)

Xamps (Xenobiotic-Associated Molecular Patterns)

Camps (Cognition-Associated Molecular Patterns)

Bamps (Behaviour-Associated Molecular Patterns)