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Blanco-Mora, D. A.

Publications and source records attributed to Blanco-Mora, D. A..

2 recordsLinked to original sources

Functional brain imaging predicts population-level visits to urban spaces

Urbanization is increasing around the world, and urban development strategies focusing on sustainability and the welfare of urban residents are needed. In response to this need, the field of neurourbanism has emerged, which leverages research on the human brain to understand and predict the influence of urban environments. For example, studying brain regions involved in reward processing and value-based decision making, such as the ventromedial prefrontal cortex (vmPFC), may help us understand how people interact with and navigate through urban environments. In this study, we aimed to ascertain whether neural activity within the vmPFC can predict population-level visits around the urban spaces of a city - in our case, Lisbon, Portugal. We used the density of photographs taken around Lisbon as a proxy measure of these visits. To do this, we created a stimulus set featuring 160 images of Lisbon sourced from the social media platform, Flickr. Then, study participants in the U.S. who had never visited Lisbon, viewed these images while we recorded their brain activity. We found that in our sample, activity in the vmPFC predicted the density of photographs taken around Lisbon, and hence, the population-level visits. Our research highlights the crucial role of the brain, especially reward-related brain regions, in shaping human behavior within urban environments. By shedding light on the neural mechanisms underlying urban behavior in humans, our research opens exciting possibilities for the future of urban planning. With this knowledge, policymakers and urban planners can potentially design cities that can promote well-being, social interaction, and sustainable living.

neuroscience↗

Brain activation by a VR-based motor imagery andobservation task: An fMRI study

Training motor imagery (MI) and motor observation (MO) tasks is being intensively exploited to promote brain plasticity in the context of post-stroke rehabilitation strategies. The desired brain plasticity mechanisms may benefit from the use of closed-loop neurofeedback, embedded in brain-computer interfaces (BCIs) to provide an alternative non-muscular channel. These can be further augmented through embodied feedback delivered through virtual reality (VR). Here, we used functional magnetic resonance imaging (fMRI) to map brain activation elicited by a VR-based MI-MO BCI task called NeuRow and compared with a conventional non-VR, and MI-only, task based on the Graz BCI paradigm. We found that, in healthy adults, NeuRow elicits stronger brain activation when compared to the Graz task, as well as to an overt motor execution task, recruiting large portions of the parietal and occipital cortices in addition to the motor and premotor cortices. In particular, NeuRow activates the mirror neuron system (MNS), associated with action observation, as well as visual areas related with visual attention and motion processing. We studied a cohort of healthy adults including younger and older subgroups, and found no significant age-related effects in the measured brain activity. Overall, our findings suggest that the virtual representation of the arms in a bimanual MI-MO task engage the brain beyond conventional MI tasks, even in older adults, which we propose could be explored for effective neurorehabilitation protocols.

neuroscience↗