To orient ourselves in space, our brain generates an internal coordinate system. Heidelberg researchers now refute the current model on how nerve cells generate this mental map.
The food pellet must be further away—a mouse is foraging for food. To estimate distances and to orient itself in space, the brain forms an internal spatial map. So-called grid neurons take on an important role in this process. They fire when the mouse happens to be at decisive positions.
From a bird's perspective, the activity pattern of a grid cell forms a hexagonal pattern in space—very reminiscent of a coordinate system on a map (see figure). But how is this abstract activity pattern generated that is not based on sensory input from the environment?
To find answers, researchers investigated neuronal connections by means of theoretical models. The currently most promising model is now refuted by scientists from the Bernstein Center Heidelberg/Mannheim and the Department of Clinical Neurobiology at the Medical Faculty of Heidelberg University and The German Cancer Research Center (DKFZ), who put the model to test in animal experiments.
"In our study, we measured the nerve cell activity in freely moving mice," explains Christina Buetfering, first author of the study. "We were interested in grid cells as well as nerve cells that interconnect the grid cells: so-called interneurons".
The crucial trick: the activity of interneurons could be selectively switched on and off by light signals in genetically modified mice. While the mice moved around during foraging, the researchers activated the cells now and then. This helped them to identify and closely observe the interneurons in the measured data stream. Also, they were able to analyze how grid cells responded to the activity of interneurons—giving a hint on how the neurons must be connected.
The scientists discovered that interneurons show no spatial activity patterns like grid cells do. In addition, individual interneurons are not exclusively connected to grid cells with similar activity patterns. Instead, they get their input signals from very different grid cells and send their output information to diverse nerve cells.
"With these results we were able to refute two basic predictions of the current theoretical network model," Buetfering discusses. "The model assumes that for generating the inner mental map, grid cells of the same spatial orientation must be very closely connected—which was thought to be realized via spatially active interneurons."
However, interneurons seem to have a different main task. The cells send inhibitory signals to quite different neurons in their environment. Therefore, they possibly rather take over a modulating function by ensuring a balance between excitation and inhibition in the brain area during excessive nerve cell activity.
In this way they could prevent epileptic seizures. How grid cells manage to fire at the right time at the right place—thereby generating the abstract mental coordinate system—has, once again, become more mysterious.
The Bernstein Center Heidelberg/Mannheim is part of the National Bernstein Network Computational Neuroscience in Germany. With this funding initiative, the German Federal Ministry of Education and Research (BMBF) has supported the new discipline of Computational Neuroscience since 2004 with over 180 million Euros. The network is named after the German physiologist Julius Bernstein (1835-1917).
Prof. Dr. Hannah Monyer
Clinical Neurobiology (A230)
German Cancer Research Center
Im Neuenheimer Feld 280
Tel: +49 (0)6221 42 3100
C. Buetfering, K. Allen & H. Monyer (2014): Parvalbumin interneurons provide grid cell-driven recurrent inhibition in the medial entorhinal cortex. Nature Neuroscience, advanced online publication
http://www.dkfz.de/de/klinische-neurobiologie Lab Hannah Monyer
http://www.uni-heidelberg.de Heidelberg University
http://www.klinikum.uni-heidelberg.de Heidelberg University Hospital
http://www.dkfz.de German Cancer Research Center
http://www.bccn-heidelberg-mannheim.de Bernstein Center Heidelberg/Mannheim
http://www.nncn.de National Bernstein Network Computational Neuroscience
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