Neuroimaging as a Tool for Diagnosing and Tracking Multiple Sclerosis

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Post by Anastasia Sares

The takeaway

Neuroimaging is a common and useful tool for diagnosing multiple sclerosis. Over the last 25 years, imaging technologies have improved to give us clearer pictures of the main features of MS at greater resolution. Further, machine learning algorithms are being used to advance our knowledge of MS. 

MRI: a key tool for diagnosis

Multiple Sclerosis (MS) is a chronic and progressive autoimmune disorder that happens when the body’s immune cells invade the central nervous system and begin to attack myelin: a protective fatty tissue wrapped around the axons of neurons. Symptoms of MS can vary wildly, depending on the region under attack. If the optic nerve is attacked, people can experience loss of vision; if the spinal cord is attacked, shooting nerve pain can be the result. 

Because MS symptoms are so variable, MRI is one of the key tools for diagnosis. MRI is non-invasive and allows a clinician to see lesions: areas of the brain that have been attacked by the body’s immune cells, appearing in the brain or spine even when the patient is not currently experiencing any symptoms. However, identifying the lesions in the first place can be difficult to the untrained eye, and being sure they are caused by MS (and not another disease) is also challenging. Therefore, to better diagnose and treat MS, we need to make it as easy as possible for clinicians to find and examine these lesions.

Using MRI to search for lesions

There are many types of MRI sequences, and each of them can highlight different characteristics of human tissue. MRI uses a strong magnetic field to align hydrogen nuclei (protons) so that they are oriented in the same direction. Then, it hits these protons with a radio frequency pulse that sends them all spinning. When the protons relax back into alignment, they emit radio energy that can be detected by the machine. Protons embedded in different types of tissue will have different resonant properties that affect how long they spin before relaxing. So, it is possible to optimize the radio pulse frequency and the time of detection in such a way that MS lesions will be more visible in the final image.

The current recommended MRI sequence for finding MS lesions is called T2 FLAIR. T2-weighted images use a slow radio pulse frequency and a longer wait time after a pulse for detection. These properties make the sequence excellent for picking up tissues with increased water content, whose hydrogen protons have a longer period of resonance. FLAIR stands for “Fluid Attenuated Inversion Recovery,” which uses an extra radio pulse to suppress signals coming from free-flowing fluids (water, cerebrospinal fluid), making those parts of the image less bright. MS lesions still show up brightly on the image.

Adapted from Bakshi et al. 2001

Similar to FLAIR, other “inversion recovery” sequences have been developed (with names like PSIR and STIR), but these have not overtaken the FLAIR sequence for brain MRIs.

Most early imaging research in MS focused on the brain, but it is now recognized that getting a good spinal cord MRI can be important for a diagnosis. There can be lesions here as well, and they may cause more disabling symptoms. Spinal cord lesions can also help confirm a diagnosis of MS, ruling out other diseases known as MS “mimics” that look similar on brain MRIs. Spinal cord imaging is more prone to interference from bodily processes like heartbeat, breathing, and swallowing, so every advance in this field matters. In the spinal cord, the recommended MRI sequences are different, including STIR or PSIR mentioned above.

Another technique for lesion detection is to use a contrast agent called gadolinium, which is injected into the blood right before an MRI. It is called a contrast agent because it helps to enhance the contrast of the MRI signal wherever it goes, causing a bright glow on a scan. Normally, gadolinium cannot get through the blood-brain barrier (the tight network of cells that separates the central nervous system from the rest of the body). However, if a person is currently having an MS attack, the blood-brain barrier becomes leaky at the site of the lesion. So, the location of “active” lesions will glow brightly on the MRI. However, it is not ideal for the health of the patient to use gadolinium repeatedly since it can accumulate in the central nervous system.

How can artificial intelligence help?

MS is a field ripe for machine learning applications. The basic problem is one of image classification, which is a staple in the machine learning world. Some algorithms for lesion detection have recently been proposed, and these can identify lesions, calculate their volume, and measure overall brain size, These measures can also be tracked over time in patients to get a clearer idea of disease progression.

Many of these algorithms need to be fed a large set of training data—for MS, this means getting a huge number of correctly classified MRIs to learn from. If there are any systematic biases in our diagnosis of MS, these will be replicated by the machine learning program. Finally, someone ultimately must take responsibility for the diagnosis (a doctor, not a machine!), so adding artificial intelligence, while extremely useful, does complicate the accountability landscape.

Moving forward

MS is a disease of the central nervous system, and it has become easier to diagnose as our neuroimaging methods improve in this area of intense research. More advanced MRI sequences are on the horizon, even ones that can detect and quantify the myelin itself (the tissue under attack). Combined with powerful algorithms, these sequences offer clinicians much more information to draw on when making decisions about an MS diagnosis.

References +

Barkhof, F. (1997). Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain, 120(11), 2059–2069.

Tintore, M., Rovira, A., Martınez, M. J., Rio, J., Dıaz-Villoslada, P., Brieva, L., Borras, C., Grive, E., Capellades, J., & Montalban, X. (2000). Isolated Demyelinating Syndromes: Comparison of Different MR Imaging Criteria to Predict Conversion to Clinically Definite Multiple Sclerosis. 5.

Bakshi, R., Ariyaratana, S., Benedict, R. H. B., & Jacobs, L. (2001). Fluid-Attenuated Inversion Recovery Magnetic Resonance Imaging Detects Cortical and Juxtacortical Multiple Sclerosis Lesions. Archives of Neurology, 58(5), 742.

Dolezal, O., Dwyer, M. G., Horakova, D., Havrdova, E., Minagar, A., Balachandran, S., Bergsland, N., Seidl, Z., Vaneckova, M., Fritz, D., Krasensky, J., & Zivadinov, R. (2007). Detection of Cortical Lesions is Dependent on Choice of Slice Thickness in Patients with Multiple Sclerosis. In International Review of Neurobiology (Vol. 79, pp. 475–489). Elsevier.

Thompson, A. J., Banwell, B. L., Barkhof, F., Carroll, W. M., Coetzee, T., Comi, G., Correale, J., Fazekas, F., Filippi, M., Freedman, M. S., Fujihara, K., Galetta, S. L., Hartung, H. P., Kappos, L., Lublin, F. D., Marrie, R. A., Miller, A. E., Miller, D. H., Montalban, X., Mowry, E. M., … Cohen, J. A. (2018). Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. The Lancet. Neurology, 17(2), 162–173.

Chen, Y., Haacke, E. M., & Bernitsas, E. (2020). Imaging of the Spinal Cord in Multiple Sclerosis: Past, Present, Future. Brain Sciences, 10(11), 857.

Wattjes, M. P., Ciccarelli, O., Reich, D. S., Banwell, B., de Stefano, N., Enzinger, C., Fazekas, F., Filippi, M., Frederiksen, J., Gasperini, C., Hacohen, Y., Kappos, L., Li, D., Mankad, K., Montalban, X., Newsome, S. D., Oh, J., Palace, J., Rocca, M. A., Sastre-Garriga, J., … North American Imaging in Multiple Sclerosis Cooperative MRI guidelines working group (2021). 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. The Lancet. Neurology, 20(8), 653–670.

Moazami, F., Lefevre-Utile, A., Papaloukas, C., & Soumelis, V. (2021). Machine Learning Approaches in Study of Multiple Sclerosis Disease Through Magnetic Resonance Images. Frontiers in Immunology, 12, 700582. https://doi.org/10.3389/fimmu.2021.700582

Martí-Juan, G., Frías, M., Garcia-Vidal, A., Vidal-Jordana, A., Alberich, M., Calderon, W., Piella, G., Camara, O., Montalban, X., Sastre-Garriga, J., Rovira, À., & Pareto, D. (2022). Detection of lesions in the optic nerve with magnetic resonance imaging using a 3D convolutional neural network. NeuroImage: Clinical, 36, 103187.

How Our Behavior Influences Productivity

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Post by Leanna Kalinowski and Leigh Christopher

What blocks your productivity?

Have you ever wanted to get something done, but found yourself endlessly putting it off? Or, in an attempt to start the day off on a productive note, been paralyzed by your long list of tasks to do? These experiences have one thing in common: they involve shifts in your attention or motivation. 

Feeling motivated can help us to stay productive, however, our motivation can wax and wane over time. And, sometimes, we simply don’t have the motivation needed to work at our best. We can also become easily distracted throughout the day, or develop bad habits that prevent us from achieving our goals. This is known as the intention-action gap - the concept that our intentions do not always translate into action. 

In an ideal world, we would avoid distractions, work efficiently and accomplish everything we planned. However, as human beings, we’re susceptible to distractions and we have limited willpower. Fortunately, there are helpful strategies that we can use to aid in the development of better productivity habits. BrainPost partnered with Intelligent Change (creators of The Five Minute Journal) to highlight some of the top, scientifically-backed strategies that you can implement to stay on track.

Creating a simple plan to reduce the noise

Why is it so hard to accomplish what we want? Although it may seem like we know exactly what needs to be done, this can often be the first barrier to productivity - noise. There is so much going on in our day-to-day lives that our goals can seem overwhelming. This is why implementation intentions - a simple plan that states where, when, or what we will do- can be immensely helpful. One research study found that those who wrote down where and when they were going to exercise were more than twice as likely to follow through on their exercise plan. This research highlights that it’s not always about boosting inherent motivation. A simple cue in our environment, in this case, like the indication of where or when the action will take place, helps lead to the desired behavior, which then, in turn, encourages even greater motivation later on. 

What else can help us filter through the noise? Another important, but often overlooked concept in productivity, is prioritization. By whittling down our to-do list to just a few or even one very important task, we simplify our lives and lighten our cognitive load. Choosing one task to focus on at a time can also reduce choice overload - when too many choices make it difficult to decide what to do, hindering action. Sometimes, one of the biggest challenges is identifying what is actually most important - and this can be especially uncomfortable when the most important thing is something we’ve been avoiding. This is why prioritizing the most important task to focus on for the day can be a powerful way to follow through on our goals. 

Using sub-goals and progress monitoring to boost motivation

There are pros and cons to setting a significant goal, such as writing a graduate school thesis or training for a marathon. On one hand, difficult goals that require considerable effort lead to higher performance and motivation, because people feel a greater sense of accomplishment after completing something challenging. On the other hand, goals that are too challenging or that exceed the limits of one’s capabilities are more likely to be abandoned midway through. Chunking goals into smaller steps (i.e., setting “sub-goals”) can help make those larger goals more attainable while still retaining the overarching challenge and reward. For example, setting a goal to spend an hour a day working on your thesis can help to provide daily bursts of reward, keeping the sense of accomplishment and motivation going while working towards the larger goal of completion. 

Whether you are setting sub-goals or powering through your larger goal, research shows that monitoring your progress can help improve your likelihood of success. There are several ways to ensure that progress monitoring is most effective. First, be sure to monitor the progress that is specific to the goal that you are trying to achieve: for example, if your goal is to finish a writing piece, focus your goal on metrics directly related to this (e.g., minutes spent writing) rather than metrics that are indirectly related or vague. Second, monitor your progress in a quantifiable way. While simply checking a box saying “I wrote today” can be motivating for some, it can be more helpful for others to assign numerical values to their progress, like the number of paragraphs written for example. Finally, be sure to physically record your progress, as this also helps to increase your chances of following through on your goal. Tracking your progress in a planner or journal, for example, is one great way to visualize how you’re moving forward.

The Productivity Planner, by Intelligent Change, leverages implementation intentions, prioritization, and time tracking.

Turning a behavior into a habit

Ultimately, productivity strategies can vary from person to person. The strategies offered here can be thought of as tools to help you stay on track when pursuing your goals, and some may stick better than others. Having a system in place to help with productivity can be powerful in developing good habits. This is because repeating certain behaviors can help to reinforce a habit by increasing motivation to perform the same action again, eventually leading to a more automatic (i.e. easier) experience. This process is known as a habit formation loop - a cycle whereby repeated behaviors become more naturally rewarding and easier to perform. Although staying productive is important in the accomplishment of our goals, we are only human, and not every day will be productive. This is why introducing some flexibility into goal-setting, and practicing acceptance when things don’t go as planned, can be just as important.

EMDR Therapy: What’s Happening in the Brain?

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Post by Anastasia Sares

Eye movements to treat traumatic disorders

In 1989, Francine Shapiro published a technique for treating trauma using eye movements. In the technique, a client will bring a traumatic incident to mind, and recall it while simultaneously following the therapist’s finger as it moves back and forth across their field of vision. A session also includes repeated evaluations of thoughts, emotions, and body sensations surrounding the event. This therapeutic approach came to be known as Eye Movement Desensitization and Reprocessing, or EMDR. Shapiro observed its effectiveness in treating severe post-traumatic stress disorder (PTSD). However, both scientists and the public viewed the technique with skepticism. For starters, it seemed “too easy,” (the words of one patient in Shapiro’s 1989 paper). It didn’t help that it was unclear how the technique worked and that it seemed similar to less scientifically reputable techniques such as hypnosis.

Despite its detractors, EMDR has slowly grown to become one of the preferred treatments for PTSD. Scientists and clinicians have teamed up to run randomized controlled trials, where people are assigned randomly to either EMDR or another treatment condition. These experiments are considered the gold standard for determining a treatment’s efficacy in the medical field, and enough of them have been done that we can now perform meta-analyses, which synthesize all the results from different experiments into one big analysis. The results? EMDR is at least as effective as other well-established treatments like cognitive-behavioral therapy or exposure therapy.

What does EMDR do in the brain?

The main hypothesis developed by Shapiro and colleagues to explain EMDR is called the Adaptive Information Processing model. According to this model, traumatic memories are not fully processed in the brain and create their own maladaptive networks that can be triggered, leading to flashbacks and other unwanted phenomena. EMDR encourages the traumatic memory to be brought up, fully processed, and reconsolidated in a more adaptive manner, integrating it with the rest of an individual’s life experience and diminishing its power to cause fear. Shapiro emphasizes the difference between memory reconsolidation (the hypothesized mechanism for EMDR), and memory extinction (the basis for exposure therapy).

EMDR responsiveness has indeed been linked with memory structures, such as the parahippocampal gyrus, deep in the brain. One study showed that at the start of EMDR therapy, there was greater activation in the frontal cortex (responsible for executive control) and the occipital cortex (responsible for visual stimuli). By the end of therapy, activity had shifted towards the parahippocampal gyrus and parietal lobe. Thus, the idea that eye movements promote memory reprocessing does not seem too far-fetched, but the exact mechanisms of EMDR are still being worked out.

One idea is that eye movements may take space in working memory, giving less “bandwidth” to the traumatic memory and therefore making it less vivid. Another is that they mimic the eye movements of REM sleep (the period of the sleep cycle where memories are consolidated) and thus promote reconsolidation of the traumatic memory. It's important to note here that EMDR can be done with methods other than eye movement, including tapping one’s shoulders on the right and left side or holding buzzers in the hands that vibrate in a right/left pattern. These methods are collectively called bilateral stimulation.

Some research shows that the bilateral stimulation used in EMDR can be effective even in animals who cannot be told the goal of the “therapy.” A recent study showed that when rodents were exposed to lights moving back and forth, their response to a previously fearful stimulus decreased (See a previous BrainPost).

What’s new?

Shapiro never intended EMDR to be applied solely to PTSD, and lately, there have been studies looking at its efficacy for other conditions, such as obsessive-compulsive disorder, psychosis, substance use disorders, and depression. While some results may look promising, there is not yet enough information to run the kind of meta-analyses that have established EMDR’s efficacy for PTSD.

Finally, Otgaar and colleagues have cautioned that undergoing EMDR therapy may change the validity of witness testimony in court, since it is, after all, a form of memory reprocessing, and could affect details of an event as the victim remembers it.

What's the bottom line?

EMDR therapy is a validated, non-pharmaceutical technique for the treatment of PTSD, and perhaps other mental health issues. While we don’t fully understand how it works, it involves memory processing and reconsolidation of previously acquired memories. As with any mental health treatment, make sure you ask a licensed therapist about this technique regarding your own situation.

References +

Jeffries, F. W., & Davis, P. (2013). What is the Role of Eye Movements in Eye Movement Desensitization and Reprocessing (EMDR) for Post-Traumatic Stress Disorder (PTSD)? A Review. Behavioural and Cognitive Psychotherapy, 41(3), 290–300. https://doi.org/10.1017/S1352465812000793

Marsden, Z., Lovell, K., Blore, D., Ali, S., & Delgadillo, J. (2018a). A randomized controlled trial comparing EMDR and CBT for obsessive-compulsive disorder. Clinical Psychology & Psychotherapy, 25(1), e10–e18. https://doi.org/10.1002/cpp.2120

Nardo, D., Högberg, G., Looi, J. C. L., Larsson, S., Hällström, T., & Pagani, M. (2010). Gray matter density in limbic and paralimbic cortices is associated with trauma load and EMDR outcome in PTSD patients. Journal of Psychiatric Research, 44(7), 477–485. https://doi.org/10.1016/j.jpsychires.2009.10.014

Novo Navarro, P., Landin-Romero, R., Guardiola-Wanden-Berghe, R., Moreno-Alcázar, A., Valiente-Gómez, A., Lupo, W., García, F., Fernández, I., Pérez, V., & Amann, B. L. (2018). 25 years of Eye Movement Desensitization and Reprocessing (EMDR): The EMDR therapy protocol, hypotheses of its mechanism of action and a systematic review of its efficacy in the treatment of post-traumatic stress disorder. Revista de Psiquiatría y Salud Mental (English Edition), 11(2), 101–114. https://doi.org/10.1016/j.rpsmen.2015.12.002

Otgaar, H., Houben, S. T. L., Rassin, E., & Merckelbach, H. (2021). Memory and eye movement desensitization and reprocessing therapy: A potentially risky combination in the courtroom. Memory, 29(9), 1254–1262. https://doi.org/10.1080/09658211.2021.1966043

Pagani, M., Di Lorenzo, G., Monaco, L., Daverio, A., Giannoudas, I., La Porta, P., Verardo, A. R., Niolu, C., Fernandez, I., & Siracusano, A. (2015). Neurobiological response to EMDR therapy in clients with different psychological traumas. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.01614

Roberts, B. R. T., Fernandes, M. A., & MacLeod, C. M. (2020). Re-evaluating whether bilateral eye movements influence memory retrieval. PLOS ONE, 15(1), e0227790. https://doi.org/10.1371/journal.pone.0227790

Santarnecchi, E., Bossini, L., Vatti, G., Fagiolini, A., La Porta, P., Di Lorenzo, G., Siracusano, A., Rossi, S., & Rossi, A. (2019). Psychological and Brain Connectivity Changes Following Trauma-Focused CBT and EMDR Treatment in Single-Episode PTSD Patients. Frontiers in Psychology, 10, 129. https://doi.org/10.3389/fpsyg.2019.00129

Shapiro, F. (1989). Efficacy of the eye movement desensitization procedure in the treatment of traumatic memories. Journal of Traumatic Stress, 2(2), 25.

Solomon, R. M., & Shapiro, F. (2008). EMDR and the Adaptive Information Processing Model: Potential Mechanisms of Change. Journal of EMDR Practice and Research, 2(4), 315–325. https://doi.org/10.1891/1933-3196.2.4.315

Talbot, D. (2021). Examination of Initial Evidence for EMDR as a Treatment for Obsessive-Compulsive Disorder. Journal of EMDR Practice and Research, 15(3), 167–173. https://doi.org/10.1891/EMDR-D-21-00004

Valiente-Gómez, A., Moreno-Alcázar, A., Treen, D., Cedrón, C., Colom, F., Pérez, V., & Amann, B. L. (2017). EMDR beyond PTSD: A Systematic Literature Review. Frontiers in Psychology, 8, 1668. https://doi.org/10.3389/fpsyg.2017.01668