Gray Matter Atrophy Correlates with Neurotransmitter Dysfunction in Multiple Sclerosis

Post by Lincoln Tracy

The takeaway

Region-specific gray matter atrophy may impact neurotransmitter systems (e.g., dopamine, serotonin), which may contribute to clinical manifestations and symptoms of multiple sclerosis. 

What's the science?

Multiple sclerosis (MS), a chronic neurological disease, displays specific topographic and temporal patterns of gray matter atrophy. The progression of gray matter atrophy corresponds with clinically relevant symptoms of MS, such as locomotor disability, cognitive impairment, fatigue, and depression. Evidence from studies of MS and other neurodegenerative disorders suggests an imbalance of excitatory and inhibitory neurotransmitters as one of the pathological substrates contributing to neuro-axonal loss and progressive gray matter atrophy, underlying the development of specific symptoms. This week in Molecular Psychiatry, Fiore and colleagues sought to determine whether MS severity and common MS symptoms were associated with atrophy of specific brain regions that were spatially correlated with specific neurotransmitters. 

How did they do it?

The authors recruited 286 MS patients (173 women) and 172 neurologically normal individuals (92 women) to act as controls. All MS patients completed a neurological evaluation and a series of tests and questionnaires to measure their cognitive function, fatigue, and depression, before undergoing a magnetic resonance imaging (MRI) scan to quantify gray matter atrophy. The atrophy patterns in the MRI scans were correlated with maps of where different neurotransmitter systems were distributed throughout the brain. The authors compared regional gray matter volumes between MS patients and controls to assess what areas of the brain showed significant gray matter atrophy and whether such a pattern of gray matter atrophy was spatially correlated with specific neurotransmitter systems. The authors also tested whether patients with different clinical MS phenotypes (e.g., relapsing/remitting or progressive) displayed differences in brain atrophy. Finally, they explored whether differences in cognitive impairment, fatigue, and depression were associated with gray matter atrophy and neurotransmitter distribution in patients with MS. 

What did they find?

First, the authors found MS patients had more severe gray matter atrophy compared to the neurologically normal controls, specifically in the fronto-temporo-parieto-occipital regions and the cerebellum. These atrophied areas were associated with a higher distribution of serotonin, dopamine, mu-opioid, noradrenaline, acetylcholine, and glutamate receptors. Second, progressive MS patients had more gray matter atrophy in the cerebellum, hippocampus, left temporal cortex, left putamen, and left insula than patients with relapsing-remitting MS, but this pattern of gray matter atrophy was not associated with any significant neurotransmitter distribution. Finally, cognitively impaired MS patients had more widespread atrophy in the cortex, deep nuclei, and cerebellum compared to cognitively preserved MS patients. The atrophied regions were spatially correlated with a higher distribution of dopamine, noradrenaline, serotonin, acetylcholine, and glutamate receptors. MS patients with fatigue had atrophy in the bilateral precuneus and a suite of other brain regions including the right superior temporal gyrus, but no associations with neurotransmitter distribution were observed. There were no differences in gray matter atrophy between MS patients with and without depression. Overall, these results suggest gray matter atrophy in specific brain regions may negatively affect specific neurotransmitter systems, which in turn may contribute to different presentations and symptoms of MS.   

What's the impact?

The results of this study may improve our understanding of the pathophysiological processes underlying the various clinical manifestations of MS, including common symptoms such as cognitive impairment and fatigue. If future studies confirm these results, the findings could pave the way for the development of new neurotransmitter-modulating therapies for MS, which may result in improved quality of life for patients. 

Neurons Receiving Input From a Computer Chip Demonstrate Learning in a Game of “Pong”

Post by Lani Cupo

The takeaway

The future of artificial intelligence is reimagined with DishBrain, a new technology that combines neurons, grown in a petri dish, with stimuli and feedback from electrical circuits. The authors present a “Pong”-playing system that they claim embodies the foundation of sentience.

What's the science?

Neurons and computer hardware share a common language: electricity. It has been theorized that combining real biological neurons with silicone hardware would allow a synthetic system to represent complexity that modern computers (using binary) alone cannot capture. Previously, however, the advantages of biological neural circuits have not been integrated into digital, silicone systems. Recently in Neuron, Kagan and colleagues present a form of synthetic biological intelligence called DishBrain: a petri dish of neurons embedded with a multi-electrode array that provides electrophysiological stimulation and recording to create a simulated game world that allows the neural circuit to learn the game “Pong” in real-time.

How did they do it?

The authors first generated cortical neurons from two sources: human pluripotent stem cells and mouse embryos. These neurons were then allowed to mature on plates made of multi-electrode arrays, developing into complex, interconnected neural circuits. The authors developed a system that leveraged software to not only record electrical activity from the neurons but also provide noninvasive electrical stimuli that mimic action potentials. In order to demonstrate real-time learning, the authors simulated the game “Pong”. They provided “sensory” information representing a ball moving on a trajectory. Electrophysiological activity in a predefined “motor” cluster of neurons was recorded, representing moving a paddle up or down. If the movement would result in an interruption of the ball’s trajectory, a predictable stimulus was presented to all the neurons at once, serving as positive feedback. If, however, the movement would not interrupt the ball’s path, an unpredictable stimulus was provided. The authors examined the hit-miss ratio, which they defined as the average rally length, as a metric of learning. As experimental controls, they compared the cell cultures to three different conditions: 1) Petri dishes with only cell culture media (no cells), 2) rest sessions, where the cells could control the paddle, but received no "sensory input", and 3) sessions that replicated the experiment, but where the paddle was controlled by random noise. With the recordings of cell firings, the authors examined functional connectivity within the culture and how cell activity related to performance in the task.

What did they find?

At the start of the sessions, they found that human stem cells performed worse than the mouse neurons and controls at the task, possibly due to increased exploratory behavior. However, by the end of the session, both mouse and human-derived cultures performed better than controls, and the human cultures performed slightly better than the mouse, indicative that learning occurred over the session. Importantly, the authors found that feedback was necessary for learning - the cultures only improved in average rally length when feedback was provided to the system. Overall, connectivity within the culture was stronger during gameplay than during rest, which could suggest a direct relationship between activity in “sensory” regions receiving input and “motor” regions supplying output. Increased neuron firing was also related to better performance in the game, although most important was that neuron activity was fairly symmetrical across the surface of the actual physical chip, suggesting a balanced culture.

What's the impact?

Because of the learning in response to environmental stimuli, the authors present DishBrain as a sentient form of synthetic biological intelligence, as the system was “responsive to sensory impressions through adaptive internal processes.” While advances would still be required in terms of hardware and “wetware” of the biological interface, the authors suggest a new direction for artificial intelligence. Their findings not only manifest what was previously confined to the realm of science fiction in terms of inventions but also some of the moral and ethical quandaries as well.

Controlled Breathwork Improves Mood and Reduces Anxiety

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Post by Leanna Kalinowski

The takeaway

Engaging in daily 5-minute breathwork exercises and mindfulness meditation improves mood and reduces anxiety. Cyclic sighing – a voluntary breathwork exercise that primarily focuses on exhales –  showed the greatest benefits compared to other voluntary breathwork techniques.

What's the science?

Controlled breathwork techniques have emerged as a promising avenue for improving mood and reducing stress. Methods that involve passive observation of the breath, such as meditation and yoga, are common practices that have well-demonstrated mental health benefits. These practices have different physiological effects from voluntary breathing techniques, where inhaling and exhaling patterns are directly controlled. However, little is known about how passive and voluntary breathing techniques uniquely affect mental health. This week in Cell Reports Medicine, Yilmaz Balban and colleagues evaluated the difference between passive and voluntary breathing exercises and their effectiveness in improving mood, anxiety, and physiological measures.

How did they do it?

108 participants were divided into four groups – a mindful meditation (control) group and three voluntary breathwork (treatment) groups – and instructed to complete their assigned daily breathing exercise at home for 28 days:

1)    Mindful Meditation (control group): Participants were instructed, for 5 minutes, to close their eyes and observe their breathing while focusing their mental attention on their forehead region. If their focus drifted from that region, they were told to first focus back on their breath, and then refocus back on their forehead.

2)    Cyclic Sighing (breathwork group 1): Participants were instructed to, repeatedly for 5 minutes, inhale slowly until their lungs are expanded, inhale once more to maximally fill their lungs, and then slowly and fully exhale their breath.

3)    Box Breathing (breathwork group 2): Participants were first instructed to take the “CO2 tolerance test”, which includes taking a full deep breath, exhaling as slowly as possible, and then timing how long it takes to empty their lungs. Then, repeatedly for 5 minutes, they inhaled for the same duration it took to empty their lungs in the CO2 tolerance test, held their breath for that same duration, then exhaled for that same duration, then held their breath again for the same duration.

4)    Cyclic Hyperventilation with Retention (breathwork group 3): Participants were instructed to inhale deeply and then exhale by passively “letting their air fall out from the mouth”. They repeated this pattern for 30 breaths, after which they exhaled via the mouth and calmly waited with empty lungs for 15 seconds.

Participants completed two surveys that measured affect and anxiety at baseline and again after the experiment. They also wore a wrist strap during their breathing exercises that collected several physiological measures, including their daily resting heart rate, respiratory rate, and hours of sleep. These measures were collected remotely via a smartphone app.

What did they find?

The researchers found that, following 28 days of breathing exercises, all four groups experienced an increase in daily positive affect, a decrease in negative affect, and a reduction in anxiety. While there were no differences between the meditation (control) and breathwork groups in anxiety and negative affect changes, the three breathwork groups had a higher increase in daily positive affect compared to the meditation group. Upon evaluating the physiological measurements, researchers found a similar pattern: the three breathwork groups had a higher reduction in baseline respiratory rate than the meditation group. For both the positive affect and respiratory rate results, group differences were largely influenced by the cyclic sighing group, suggesting particularly beneficial effects for breathing techniques that emphasize exhaling. No other physiological changes were observed in any of the groups.

What's the impact?

Results from this study suggest that engaging in intentional breath control exercises (e.g., the cyclic sighing technique) provides more benefits to mood than passive breath observation exercises (i.e., mindfulness meditation). While all four breathing techniques were effective in improving mood and decreasing anxiety, daily 5-minute cyclic sighing shows the most promise in being a low-commitment approach to managing stress. Future studies should evaluate whether the consistent practice of these techniques, beyond one month, remains effective in improving psychological outcomes.