Discovery in the brains of army veterans with chronic pain could pave way for personalized treatments

Summer Outdoor Safety for Elderly Nursing Home Residents
Summer Outdoor Safety for Elderly Nursing Home Residents


A new study is the first to investigate brain connectivity patterns at rest in veterans with both chronic pain and trauma, finding three unique brain subtypes potentially indicating high, medium, and low susceptibility to pain and trauma symptoms. The findings provide an objective measurement of pain and trauma susceptibility and could pave the way for personalized treatments and new therapies based on neural connectivity patterns.  

Chronic pain and trauma often co-occur. However, most previous research investigated them in isolation and using subjective measures such as surveys, leading to an incomplete picture. A new study in Frontiers in Pain Research has filled in some of the blanks. It found three unique brain connectivity signatures that appear to indicate veteran susceptibility or resilience to pain and trauma, regardless of their diagnostic or combat history. The study could pave the way for more objective measurements of pain and trauma, leading to targeted and personalized treatments.

Chronic pain and trauma are linked but not studied together

“Chronic pain is a major public health concern, especially among veterans,” said first author Prof Irina Strigo of the San Francisco Veterans Affairs Health Care Center. “Moreover, chronic pain sufferers almost never present with a single disorder but often with multiple co-morbidities, such as trauma, posttraumatic stress, and depression.”

Researchers already understand that both pain and trauma can affect connections in our brains, but no-one had studied this in the context of co-occurring trauma and pain. Much pain and trauma research also relies on subjective measurements, such as questionnaires, rather than objective measurements, such as brain scans.

Identifying brain connectivity signatures of pain and trauma

Taking a different approach, the researchers behind this new research studied a group of 57 veterans with both chronic back pain and trauma. The group had quite varied symptoms in terms of pain and trauma severity. By scanning the veterans’ brains using functional magnetic resonance imaging, the researchers identified the strength of connections between brain regions involved in pain and trauma. They then used a statistical technique to automatically group the veterans based on their brain connection signatures, regardless of their self-reported pain and trauma levels.

Based on the veterans’ brain activity, the computer automatically divided them into three groups. Strikingly, these divisions were comparable to the severity of the veterans’ symptoms, and they fell into a low, medium, or high symptom group.

The researchers hypothesized that the pattern of brain connections found in the low symptom group allowed veterans to avoid some of the emotional fallout from pain and trauma, and also included natural pain reduction capabilities. Conversely, the high symptom group demonstrated brain connection patterns that may have increased their chances of anxiety and catastrophizing when experiencing pain.

Interestingly, based on self-reported pain and trauma symptoms, the medium symptom group was largely similar to the low symptom group. However, the medium symptom group showed differences in their brain connectivity signature, which suggested that they were better at focusing on other things when experiencing pain, reducing its impact.  

Putting the findings into future practice

“Despite the fact that the majority of subjects within each subgroup had a co-morbid diagnosis of pain and trauma, their brain connections differed,” said Strigo.

“In other words, despite demographic and diagnostic similarities, we found neurobiologically distinct groups with different mechanisms for managing pain and trauma. Neurobiological-based subgroups can provide insights into how these individuals will respond to brain stimulation and psychopharmacological treatments.”

So far, the researchers don’t know whether the neural hallmarks they found represent a vulnerability to trauma and pain or a consequence of these conditions. However, the technique is interesting, as it provides an objective and unbiased hallmark of pain and trauma susceptibility or resilience. It does not rely on subjective measures such as the surveys. In fact, subjective measurements of pain in this study would not differentiate between the low and medium groups.

Techniques that use objective measures, such as brain connectivity, appear more sensitive and could provide a clearer overall picture of someone’s resilience or susceptibility to pain and trauma, thereby guiding personalized treatment and paving the way for new treatments.

Early detection of arthritis using artificial intelligence


There are many different types of arthritis, and diagnosing the exact type of inflammatory disease that is affecting a patient’s joints is not always easy. In an interdisciplinary research project conducted at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, computer scientists and physicians have now succeeded in teaching artificial neural networks to differentiate between rheumatoid arthritis, psoriatic arthritis and healthy joints.

Within the scope of the project funded by the Federal Ministry of Education and Research (BMBF) called “Molecular characterization of arthritis remission (MASCARA)”, a team led by Prof. Andreas Maier and Lukas Folle from the Chair of Computer Science 5 (Pattern Recognition) and PD Dr. Arnd Kleyer and Prof. Dr. Georg Schett from Department of Medicine 3 at Universitätsklinikum Erlangen had the remit to investigate the following questions: Can artificial intelligence (AI) detect various types of arthritis using joint shape patterns? Does this method allow us to make more precise diagnoses in cases of undifferentiated arthritis? Are there certain areas in joints that should be examined in more detail during a diagnosis?




Missing biomarkers currently often make precise classification of the relevant type of arthritis difficult. X-ray images used to aid diagnosis are not completely reliable either, as their two-dimensionality is not precise enough and leaves room for interpretation. This is in addition to the fact that positioning the joint being examined for an X-ray image can be difficult.

Artificial networks learn using finger joints

To find the answers to its questions, the research team focused its investigations on the metacarpophalangeal joints of the fingers – regions in the body that are very often affected early on in patients with autoimmune diseases such as rheumatoid arthritis or psoriatic arthritis. A network of artificial neurons was trained using finger scans from high-resolution peripheral quantitative computer tomography (HR-pQCT) with the aim of differentiating between “healthy” joints and those from patients with rheumatoid or psoriatic arthritis.

HR-pQCT was selected as it is currently the best quantitative method of producing three-dimensional images of human bones in the highest resolution. In the case of arthritis, changes in the structure of bones can be very accurately detected, which makes precise classification possible.

Neural networks could make more targeted treatment possible

A total of 932 new HR-pQCT scans from 611 patients were then used to check if the artificial network can actually implement what it had learned: Can it provide a correct assessment of the previously classified finger joints?

The results showed that AI detected 82% of the healthy joints, 75% of the cases of rheumatoid arthritis and 68% of the cases of psoriatic arthritis, which is a very high hit probability without any further information. When combined with the expertise of a rheumatologist, it could lead to much more accurate diagnoses. In addition, when presented with cases of undifferentiated arthritis, the network was able to classify them correctly.

“We are very satisfied with the results of the study as they show that artificial intelligence can help us to classify arthritis more easily, which could lead to quicker and more targeted treatment for patients. However, we are aware of the fact that there are other categories that need to be fed into the network. We are also planning to transfer the AI method to other imaging methods such as ultrasound or MRI, which are more readily available,” explains Lukas Folle.

Hotspots could lead to faster diagnoses

Whereas the research team was able to use high-resolution computer tomography, this type of imaging is only rarely available to physicians under normal circumstances because of restraints in terms of space and costs. However, these new findings are still useful as the neural network detected certain areas of the joints that provide the most information about a specific type of arthritis that are known as intra-articular hotspots. “In future, this could mean that physicians could use these areas as another piece in the diagnostic puzzle to confirm suspected cases,” explains Dr. Kleyer. This would save time and effort during the diagnosis and is already in fact possible using ultrasound, for example. Kleyer and Maier are planning to investigate this approach further in another project with their research groups.

What is an Autism-friendly community?

What is an Autism-friendly community? | Adam Harris | TEDxBallyroanLibrary  - YouTube


Adam is AsIAm’s Chief Executive Officer, having held the position since he founded the organisation in 2013. Adam set up AsIAm based on his own experiences growing up as a young autistic person in Ireland. Diagnosed with Asperger’s Syndrome from an early age, the condition was far less understood or even known as it is today. Having spent his initial school years within the special education stream, he moved to a mainstream school in Second Class and was supported by an SNA. By secondary school age,

Adam began to socialise independently in his teenage years. He was nonetheless frustrated at the lack of any real understanding of autism and the many examples of social inclusion to which the community are subjected to. This inspired him to establish AsIAm whilst studying for his Leaving Cert – with the aim of giving autistic people a voice and starting a national conversation.

Over the past five years, he has had the huge honour of meeting so many members of the community around the county who want to help build a more autism-aware and understanding Ireland. A self-confessed workaholic, Adam enjoys public speaking, blogging about all things autistic and helping the many organisations and committees he’s a member of working for autism and inclusion.

When he’s off, he enjoys spending time with his family and friends, not to mention Harry and Bobby (his dogs!). Adam is AsIAm’s Chief Executive Officer, having held the position since he founded the organisation in 2013. Adam set up AsIAm based on his own experiences growing up as a young autistic person in Ireland.

Diagnosed with Asperger’s Syndrome from an early age, the condition was far less understood or even known as it is today. Having spent his initial school years within the special education stream, he moved to a mainstream school in Second Class and was supported by an SNA. By secondary school age, Adam began to socialise independently in his teenage years. He was nonetheless frustrated at the lack of any real understanding of autism and the many examples of social inclusion to which the community are subjected. This inspired him to establish AsIAm whilst studying for his Leaving Cert – with the aim of giving autistic people a voice and starting a national conversation.


Creating Meaningful Careers for Autistic Adults

Creating Meaningful Careers for Adults with Autism | Bradley McGarry |  TEDxErie - YouTube

Bradley McGarry talks about careers for adults with Autism at a 2015 TEDx event in Erie, Pennsylvania.

Brad McGarry is a native of Erie, PA & the Director of The Autism Initiative at Mercyhurst University, the 3rd highest ranked program in the U.S. for Impressive Special College Programs for Students with Autism. In 1999, he received his Master’s in Community Counseling and then completed a Masters Certificate in Special Education with a concentration in Applied Behavioral Analysis. Brad has passionately worked to raise awareness and support for Autism not only in the Erie community but also across the nation.
Over the past three years he has testified before the 112th United States Congress, was nominated for the Temple Grandin Award through the Autism Connection of Pennsylvania and was a contributing author to the published guide, “Emerging Practices for Supporting Students on the Autism Spectrum in Higher Education”. Brad & the AIM Program have been featured in The Chronicle of Higher Education, Forbes Magazine, NBC’s TODAY.com, C-SPAN and Autism/Asperger Digest.

A sustainable living community for adults on the autism spectrum

A sustainable living community for adults on the autism spectrum | Heidi  Stieglitz Ham | TEDxPerth - YouTube


Heidi Stieglitz Ham brought together a team of architects, psychologists, occupational therapists, speech pathologists and researchers to design a sustainable living community for people with High-Functioning Autism (HFA) and Asperger Syndrome (AS). This innovative community is the first of its kind in the world.

Different to a group home or institution, the individuals will have their own independent living units made of sustainable materials and community areas would be designed for shared spaces. The vision is for the community to “live off the grid” and be sustainable using solar and wind power.

Green spaces for organic gardening and therapy will be included. Ham’s training centres will provide job coaching, and various forms of therapy services and provide a safe place to learn about becoming independent in a chaotic world. The community will also encourage other neurotypical adults to live there as well to provide role models and offer a safety net for the adults with autism.

Heidi Stieglitz Ham is a cognitive psychologist and a speech-language pathologist. After spending 11 years in clinical settings, she undertook a major career change and moved into academia, earning her PhD from the University of Edinburgh in 2010 investigating developmental dyspraxia and cognitive processing in individuals with autism. Heidi has worked with individuals with autism and their families in the United States, United Kingdom, Nigeria and Australia.

She is passionate about helping individuals to transition from adolescence to adulthood and helping them succeed in life, especially post secondary school when support services are often limited. Motivated to see positive change in this area, she is pioneering an innovative approach to improving functional outcomes of adults on the autism spectrum. She is the owner of Autism and Language Intervention – WA, in Perth, a university associate at Curtin University, a member of the Curtin Autism Research Group (CARG) and conducts research within the Autism Cooperative Research Centre. She holds an academic title of Lecturer at University of Queensland.