Research from the University of Jones Hopkins has shed light on how mammals track their position and orientation in space during movement. Scientists have discovered that visual cues of movement allow the brain to adapt and recalibrate its internal map even in the absence of stable visual landmarks.
When moving in space, the brain processes a significant amount of sensory information regarding position and speed, and it must efficiently process and interpret all of this data. Through experiments, researchers found that the brain is capable of continuously readjusting, relying solely on visual cues – patterns of motion perceived while in motion.
The study focused on how the brain of mammals utilizes visual cues for spatial orientation. By modifying the speed and direction of visual cues in virtual reality, researchers were able to manipulate animals’ perception of their location.
During the experiment, rats navigated through a virtual reality environment where luminous stripes were projected onto the walls. These stripes provided a subconscious indication of the rats’ speed and general position in space. When the stripes rotated in the opposite direction with each step the rats took, the rats’ hippocampus responded as if they were moving twice as fast, leading to a distortion in their perception of location.
The laboratory setup consisted of a virtual reality dome and projected stripes onto the walls.
Even after the projection of the stripes was turned off, the rats continued to perceive themselves as moving faster than they actually were. This experiment demonstrated that the mammalian brain can adjust its speed and location without the presence of visual landmarks.
The study also provides insight into the functioning of the hippocampus in mammals – the brain region linked to Alzheimer’s disease and other types of dementia. Understanding how the brain constructs such cognitive maps could offer insights into how memory declines with age and in dementia.
Furthermore, the findings of the study could have implications in robotics. This discovery may contribute to the advancement of artificial intelligence and machine learning algorithms aimed at integrating visual information with spatial perspectives, ultimately laying the groundwork for the development of sophisticated cognitive systems.