Precise functional connections between the dorsal anterior cingulate cortex and areas recruited for physical inference.
Ana Navarro-CebriánJason FischerPublished in: The European journal of neuroscience (2022)
Recent work has identified brain areas that are engaged when people predict how the physical behaviour of the world will unfold-an ability termed intuitive physics. Among the many unanswered questions about the neural mechanisms of intuitive physics is where the key inputs come from: Which brain regions connect up with intuitive physics processes to regulate when and how they are engaged in service of our goals? In the present work, we targeted the dorsal anterior cingulate cortex (dACC) for study based on characteristics that make it well-positioned to regulate intuitive physics processes. The dACC is richly interconnected with frontoparietal regions and is implicated in mapping contexts to actions, a process that would benefit from physical predictions to indicate which action(s) would produce the desired physical outcomes. We collected resting state functional magnetic resonance imaging (MRI) data in 17 participants and used independent task-related runs to find the pattern of activity during a physical inference task in each individual participant. We found that the strongest resting state functional connections of the dACC not only aligned well with physical inference-related activity at the group level, it also mirrored individual differences in the positioning of physics-related activity across participants. Our results suggest that the dACC might be a key structure for regulating the engagement of intuitive physics processes in the brain.
Keyphrases
- resting state
- functional connectivity
- mental health
- physical activity
- magnetic resonance imaging
- spinal cord
- single cell
- healthcare
- neuropathic pain
- machine learning
- computed tomography
- adipose tissue
- white matter
- type diabetes
- electronic health record
- spinal cord injury
- skeletal muscle
- multiple sclerosis
- insulin resistance
- big data
- cancer therapy
- data analysis