Romain Bourboulou, a former student of the PhD Program at NeuroSchool, is the winner of the “Young Researchers” prize of the Bettencourt Schueller Foundation. Created in 1990, this prize has so far distinguished 321 young researchers: this will enable them to carry out their post-doctoral training in the best foreign laboratories of their choice. Romain Bourboulou chose to carry out his post-doctoral internship at the University College London (UCL) to be in the department at the very origin of the first recording of “place cells” (the legend even says that it was in “his” office that the discovery took place!). Romain is now working alongside with John O’Keefe, winner of the 2014 Nobel Prize for the discovery of the said cells! But then, who is Romain? What exactly is he working on? And, what are “place cells”?
Romain Bourboulou is a Doctor in Science, specialising in neuroscience. He completed his thesis at the Institut de Neurobiologie de la Méditerranée in Marseille on the "resolution of spatial coding in the hippocampus". During this thesis, he focused on a better understanding of how information from the outside world influences our cognitive map. To do this, he used an innovative combination of electrophysiological recordings and a behavioural task in virtual reality. His research results showed for the first time that this mental map is dynamic and that it locally adapts according to the availability of sensory information in an environment. He is now carrying out a post-doctoral internship in Prof Caswell Barry's team.
Romain Bourboulou did his thesis in Jérôme Epsztein’s team, co-supervised by Julie Koenig-Gambini: “Neural coding of space and memory“, at the Institut de Neurobiologie de la Méditérannée (INMED). Jérôme Epsztein’s team is interested in understanding spatial navigation and its link with the formation of episodic memory, i.e. the memory of events experienced with their context (date, place, emotional state). The team is composed of multidisciplinary talents, which allows it to carry out studies at the behavioural, intracellular and extracellular levels.
The team’s behavioural approach is quite innovative since they immerse mice in totally virtual environments thanks to virtual reality! Yes, VR mice do exist! This totally controlled environment allows you to have your hand on the external sensory clues available to the animal to locate itself in the environment.
At the extracellular level, electrophysiology electrodes are used to record the activity of hundreds of cells while the animals explore the virtual environment. Intracellular recordings are made by patch-clamp on the neurons of interest.
First, he explains what “place cells” are.
The place cells of the hippocampus
Romain Bourboulou wrote his thesis mainly on extracellular recordings of place cells. These are the cells discovered by John O’Keefe, winner of the 2014 Nobel Prize, to code our environment. Meaning that our brain has cells that code our position in our environment, a bit like a GPS tracking our position at all times. Our brain, and more precisely our hippocampus, has neurons that activate and transmit information about our environment. These neurons must be seen as a whole allowing us to form an external representation of the world around us.
By conducting virtual reality studies, Romain was able to control the environment of mice while recording the activity of hundreds of “place cells” in the hippocampus. What will these cells, and more generally the hippocampus, do when the environment is very visually-poor or very visually-rich? Does it “globally” adapt? Or does it adpat in a selective way according to the need?
How do place cells code our environment?
Romain discovered that the hippocampus adapts in a global way! To see this, he studied the response fields of the place cells, called “place fields”. This place field is defined by a given spatial area on a cognitive map, which is a kind of mental map of the environment. Each place cell is therefore activated when the animal is in the associated receptor field.
Poor and enriched environments
Several kinds of environment were used by Romain Bourboulou during his thesis. On the left, a photo of the environment in virtual reality and three schematic representations of poor (first line) or enriched (2nd and 3rd lines) environments. In the schematic representation, you can notice the more or less precise place fields illustrated by more or less large coloured circles.
How do place cells code in a poor environment?
In a poor environment, it has been observed that fewer place cells are activated, potentially because there are fewer “things” to be seen in this environment. What is interesting is that the place fields are less accurately coded in this condition. These place fields were fewer and wider.
But what happens when there are a lot of stimuli in the environment?
The location cells are more numerous, more stable and more “precise” especially near the objects. This suggests that the hippocampus can adapt globally and locally, potentially for energy-saving reasons, while maximizing information capture. The representation is not complete in our hippocampus, but the cells have much more precise location fields.
Example of extracellular signal
Here is an example of an extracellular signal recorded by Romain Bourboulou. We can see several tens of channels (electrodes) out of the 64 used. The small downward deviations are spikes (action potentials) of cells close to the electrode.
The "fast wave" in the middle represents a "sharp-wave ripple" which is a rapid event during which reactivations linked to the consolidation of information in memory take place in a preferential way.
The research results demonstrate for the first time that the cognitive map, a mental representation of our environment, is dynamic and that it adapts locally and globally according to the availability of sensory information in an environment.
At the end of his PhD in October 2019, Romain Bourboulou has not finished to explore place cells! This is why he decided to do a post-doctorate at University College London in Prof Caswell Barry’s team, thanks to a grant from the Betancourt Foundation. This laboratory is a mythical place regarding the discovery of place cells, since it was in this “Biosciences” department that the first “place cells” were recorded. If you want to study spatial cognition, this is the place to be! Romain was definitely not mistaken in choosing his post-doctorate! Here, he learn a new technique: bi-photonic imaging. This technique makes it possible to plunge into the heart of the brain in full operation, since it allows to “see” and record a film of the “in vivo” activity of neurons. For these two years of post-doctoral studies, Romain will speicialized in the reactivation (replays) of place cells.
How do we remember our environment?
The reactivation of place cells could be essential in learning phenomena and takes place during sleep! This is why it is essential to have a good sleep during a revision period 😉
Overall, in the mouse, reactivation of the place cells, that had been activated when exploring an environment a little earlier, was recorded. This would be a neuronal rereading, these animals replaying sequences from their environment during their sleep. How could they have known this? Thanks to extracellular recordings! Indeed, it was observed that neurons, activated a little earlier during the exploration of an environment, were reactivated during a moment of inactivity i.e. when the stimulus was no longer present!
Here is an example of the very first data obtained by Romain Bourboulou during his post-doctorate.
And now ?
What interests Romain now is how this phenomenon of reactivation is involved in the consolidation of memory. To make the link, he is trying to couple bi-photonic imaging and electrophysiology techniques. In this way he hopes to learn more about the formation of memory within the hippocampus.
He also would like to better understand the mechanisms allowing a “transfer” of memory from the hippocampus to the cortex, once the information is known. He is counting on Prof Caswell Barry’s team, which mixes computational and experimental neuroscience, to be able to advance also with computational models. For example, he has learned to create his own algorithms to be able to verify connectivity hypotheses, which, he believes, open up more research prospects. He now wishes to extend his skills towards theoretical and computational neurosciences in order to complete his experiments and have results from studies mixing theory and experimentation.