JNeurosci: Highlights From the April 19 Issue
Check out these newsworthy studies from the April 19, 2017, issue of JNeurosci. Media interested in obtaining the full text of the studies should contact media@sfn.org.
An organism's daily behaviors and bodily activities are timed in a roughly 24-hour cycle called a circadian rhythm, which in mammals is regulated by a master clock in the brain's hypothalamus. Although the circadian rhythm is primarily reset by light — synchronizing the organism to the time of day in its environment — studies in nocturnal animals have shown that these rhythms can also be reset when animals are active during a time they are usually sleeping. However, it is unknown whether this applies to animals that are active during the day (diurnal). In this study, researchers show that depriving diurnal rats of sleep or treating them with caffeine enhanced the effect of light in shifting the timing of their wheel running, a daily activity the scientists used to determine shifts in circadian rhythm. In addition, sleep deprivation alone in the early part of the period when they would typically be sleeping also shifted the timing of this activity. Understanding how the timing and quality of sleep as well as how stimulants like caffeine affect circadian rhythms could help to inform therapies designed to deliver treatments at optimal times of day to improve efficacy and reduce side effects.
Corresponding author: Pawan Kumar Jha, kj.pawan@gmail.com
Brain-computer interfaces (BCI) can decode information from regions of the brain that plan and execute movement, and this information can then be used to operate prosthetic devices. These artificial systems are not yet able to emulate fine control of arm and hand actions, such as the ability to grasp objects of different sizes and shapes. In a new study, researchers recorded the activity of 79 neurons in the dorsomedial visual stream (a part of the visual cortex involved in both vision and movement) of two macaques as they viewed, reached for, and grasped five objects requiring different grips. The researchers found that their decoding algorithm was able to predict different types of grasps from the recorded activity with good accuracy, suggesting that this brain region may be an important new source of grasping signals for BCI applications in human patients.
Corresponding author: Patrizia Fattori, patrizia.fattori@unibo.it
is published by the 黑料社, an organization of nearly 37,000 basic scientists and clinicians who study the brain and nervous system.
