Click on any of the titles to read the full piece!
A recent Berkeley study looked at how human experimenters affect brain activity in bats during spatial tasks. They found that many neurons in the bats' hippocampus responded differently based on which experimenter was present, both when bats were flying and resting. This suggests that animal brains are sensitive to human presence and identity, even when not directly interacting. The findings highlight the need to consider experimenter effects in future research.
A recent Hopkins study shows how memories can be used to trigger goal-directed behavior in mice. Researchers found that specific brain cells in the hippocampus remember shelter locations, and that when threatened, these cells guide mice to safety. Activating these cells artificially made mice go to the shelter, while blocking them disrupted escape. This reveals how the brain uses spatial memories to guide behavior in threatening situations.
A recent study has revealed that non-cognitive skills can be as crucial as cognitive ones for academic success. Researchers found that genetic predispositions for non-cognitive skills became increasingly predictive of academic achievement as children grew older. Environmental factors are also important in this discussion, as well as a feedback loop where children’s personalities and abilities shape their learning experiences.
A recent McGill study used fMRI to examine how the brainstem, often described as the lizard brain, connects with the cortex. Researchers found that certain brainstem regions act as hubs, strongly linking to many cortical regions, influencing brain rhythms, thinking processes, and overall brain organization. The study revealed that brainstem connections reflect patterns of brain activity and cognitive functions. The findings highlight the brainstem's important role in shaping how our brain functions as a whole.
Professor Schweighofer leads the Computational Neuro-Rehabilitation Laboratory. The lab's research focuses on understanding neural mechanisms of motor learning through computational models, examining areas like cerebellar plasticity, sensorimotor cortex reorganization, and adaptive decision-making by conducting behavioral and brain imaging experiments to test their predictions. They also work on optimizing motor skill learning for stroke patients, developing adaptive practice schedules using neural models and AI.
Dr. Schweighofer places great importance on having an interdisciplinary approach, with his students coming from a diverse array of fields such as Biokinesiology, Physical Therapy, Neuroscience, Computer Science, and Biomedical Engineering. He is currently looking for students, with multiple projects being available on all levels for those interested in Computational Neuroscience.
Want to submit a piece? Or trying to write a piece and struggling? Check out the guides here!
Thank you for reading. Reminder: Byte Sized is open to everyone! Feel free to submit your piece. Please read the guides first though.
All submissions to berkan@usc.edu with the header “Byte Sized Submission” in Word Doc format please. Thank you!