Check out some of the papers that were recently published by DMCBH members:

Anthony Phillips, Stan Floresco: Potentiation of prefrontal cortex dopamine function by the novel cognitive enhancer d-govadine  

Journal: Neuropharmacology

This study investigates a new compound called d-Govadine (d-GOV) for its potential to improve cognitive function in psychiatric disorders like schizophrenia and mood disorders. d-GOV specifically targets the prefrontal cortex (PFC), a brain region associated with cognitive functions, by increasing dopamine levels without affecting other brain regions involved in reward processing. The study shows that d-GOV enhances dopamine levels in the PFC when administered directly into the PFC or a brain region called the ventral tegmental area (VTA). Blocking glutamate transmission disrupts d-GOV’s effect on dopamine, suggesting that d-GOV acts by engaging a feedback loop between the PFC and VTA. This novel mechanism of action represents a promising avenue for developing drugs to improve cognitive function in psychiatric disorders. 


Luke Clark: Computational modelling of reinforcement learning and functional neuroimaging of probabilistic reversal for dissociating compulsive behaviours in gambling and cocaine use disorders 

Journal: BJPsych Open

This study investigates cognitive flexibility in individuals with cocaine use disorder and gambling disorder compared to control participants. Using probabilistic reversal learning tasks, researchers analyzed data from both groups, employing computational modeling methods and functional magnetic resonance imaging (fMRI).

Results revealed differences in flexibility between the two disorders: individuals with gambling disorder exhibited lower ‘stimulus stickiness’ and altered neural activity in regions like the cingulate gyrus and amygdala, whereas those with cocaine use disorder showed distinct responses to punishment prediction errors and neural activity differences in the superior frontal gyrus. These findings shed light on the unique cognitive and neural mechanisms underlying flexibility in these disorders, potentially informing psychiatric classification and treatment strategies. 


Ghassan Hamarneh: Evaluating the clinical utility of artificial intelligence assistance and its explanation on the glioma grading task 

Journal: Artificial Intelligence in Medicine

In assessing the safe and effective integration of artificial intelligence (AI) into clinical practice, a user-centered evaluation was conducted involving 35 neurosurgeons to examine the utility of AI assistance and its explainability in glioma grading. Participants reviewed 25 brain MRI scans of glioma patients, providing judgments on grading both with and without AI assistance. The AI model, trained on the BraTS dataset with 88.0% accuracy, was accompanied by explanations generated using the SmoothGrad algorithm, chosen for its fidelity to AI decision processes among 16 algorithms. Results demonstrated a significant improvement in task performance when physicians were assisted by AI prediction, increasing from an average accuracy of 82.5% to 87.7%. However, the addition of AI explanation did not substantially impact performance, maintaining accuracy at 88.5%.

Analysis revealed that while AI assistance aligned physicians’ decision patterns with AI, the lack of explicit reasoning in AI explanations limited their utility in aiding physicians’ discernment of potentially incorrect predictions. This evaluation underscores AI’s clinical utility in glioma grading while highlighting the need for improved explainable AI techniques to address clinical usage gaps and enhance decision-making support in medical settings. 


Teresa Liu-Ambrose: Cross-sectional and longitudinal neural predictors of physical activity and sedentary behaviour from a 6-month randomized controlled trial  

Journal: Scientific Reports

This study explores how our brains assess the benefits of physical activity versus sedentary behavior. Researchers analyzed brain activity in adults participating in a 6-month trial to increase physical activity and reduce sedentary time. They found that brain activity related to decision-making was linked to levels of physical activity, suggesting that engaging in physical activity requires cognitive effort. In contrast, sedentary behavior seemed to lack this cognitive control, implying that it may be our default behavior. This highlights the importance of understanding how our brains weigh immediate rewards against long-term health when making lifestyle choices. 


Sophia Frangou: Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation 

Journal: The Lancet Digital Health

This study aimed to find the best method for creating normative models of brain structure by comparing different algorithms and parameters. Researchers analyzed data from over 37,000 healthy individuals across various age groups and regions. They found that a method called multivariate fractional polynomial regression (MFPR) performed the best, particularly when using non-linear polynomials for age and linear effects of global measures as covariates. These models accurately represented age-related brain changes and remained stable over time. The findings offer valuable insights into normal brain development and can guide future research and clinical practices. The model and scripts used in the study are freely available for further use. 


Tim Murphy: Traumatic brain injury disrupts state-dependent functional cortical connectivity in a mouse model 

Journal: Cerebral Cortex

This study looks at how traumatic brain injury (TBI) affects the connections between different parts of the brain and how these connections relate to brain function. TBI, which is a major cause of death in young people, can lead to problems with thinking and movement. The researchers studied this using mice with brain injuries similar to those seen in humans. They used advanced imaging techniques to see how brain connections change over time after injury. They found that TBI disrupts brain connections right after the injury, but some connections start to recover over a few weeks. Interestingly, they also found that the changes in brain activity were linked to whether the mice were moving or still. Overall, the study shows that TBI has complex effects on brain connections and activity, which can depend on what the person or animal is doing at the time. 


Lauren Emberson: Longitudinal assessments of functional near-infrared spectroscopy background functional connectivity in low- and middle-income infants during a social cognition task 

Journal: Journal of Experimental Psychology: General

In this study, researchers investigated how the brain processes social stimuli in infants during the first two years of life, focusing on understanding the neural basis of behavioral selectivity to social cues shortly after birth. They used a technique called functional near-infrared spectroscopy (fNIRS) to measure brain connectivity patterns at 6 and 24 months of age in infants from Bangladesh, who were exposed to different levels of environmental adversity (low- and middle-income backgrounds). 

They found that at 6 months, both low- and middle-income infants showed similar patterns of brain connectivity, with moderate connections between different brain regions. However, by 24 months, the patterns diverged between the two groups. The low-income group showed increased connectivity across the brain, while the middle-income group showed decreased connectivity, particularly within the right hemisphere. 

These results suggest that early environmental influences, such as socioeconomic status, can impact how the brain develops in response to social stimuli. The study provides insights into how social processing abilities develop in infants and how they may be influenced by their early life experiences.