CIRB
Neural bases of spatial memory and navigation (UMR7152)
Director: Sidney Wiener
Our research targets the neuronal mechanisms of integration of multisensorial information from the environment with internal signals (such as emotions) for the elaboration, memorization and recall of spatial representations. The goal of our studies is to better understand the neural bases of cognitive processes necessary for an animal to survive in its environment, and their relations to adaptive behaviours and learned and remembered associations. A principal approach is multichannel recordings of ensemble neuronal activity and more global brain activity in the form of local field potential oscillations in the freely moving animal performing orienting, learning and memory tasks. This work focusses on the hippocampal system (affected in Alzheimer's disease) which is distinguished by the presence of neurons responsive to the position and direction of the head in space. These provide tractable experimental models for high-level cognitive representations at the level of single neurons and neural networks. To understand how this activity is implicated in memorization and in informing ongoing behavior, we make simultaneous recordings in downstream structures such as prefrontal cortex (affected in schizophrenia) and ventral striatum (affected in Parkinson's disease). By correlating neurophysioloical activity with behavioral measures we determine the neural bases of cognitive function.
Projects
Multisensory fusion in the elaboration of brain representations of head position and direction.
Research efforts have demonstrated mechanisms of fusion of multi-sensory signals such as visual landmark cues, head acceleration information detected through the vestibular end-organs in the inner ear, optic field flow and locomotion.
Collaborators : Pr. Alain Berthoz, Professor, Collège de France, leader 'Spatial memory and movement control' team LPPA, Dr. A. Arleo, CNRS, UPMC, Paris 6
Neuroengineering analyses of neural ensemble activity.
To understand the nature of coding by simultaneously active neurons and the coordination of activity in conneccted areas of brain networks by synchronization with brain rhythms and other events measured in local field potentials ( LFPs). Recent work has shown how hippocampal signals help form permanent memory traces in the neocortex. Of particular interest is the replay of experience-related neuron activation sequences during 'sharp wave/ripples' during slow wave sleep. The role of neuromodulators such as noradrenaline is investigated.
Collaborators : Y. Gioanni & J.-M. Deniau, INSERM U667 IFR Institut de Biologie, Collège de France ; Pr. G. Buzsáki, Rutgers Univ, New Jersey (USA); Dr. K. Benchenane, UPMC ; Dr. O. Eschenko, Max Planck Inst, Tubingen; Pr. F. Battaglia, SILS Grad Sch Neurosci, Univ Amsterdam; Dr. J-P Tassin, PMNSC, UPMC.
Modelling studies of behavior and neural activity.
Hidden Markov models and Bayesian analyses permit estimation of hidden variables such as the ongoing strategy of a rat performing a maze task. Models permit to determine how well neurophysiological measures correspond to such cognitive parameters.
Collaborators : Dr. Jacques Droulez, DR CNRS, leader ‘Active perception and exploration of objects’ team, LPPA; Dr. M. Humphries, CNT, DEC, ENS.
Neurorobotics.
In order to help desisgn more effective control systems for autonomous mobile robots, we discover brain mechanisms for decision-making and planning and transfer this knowledge to roboticians.
Collaborators: Pr. M. Quoy, & P. Gaussier, ETIS, Univ Cergy; Dr. E. Save, CNRS, Marseille.
Two examples of prefrontal neuron cell assemblies that are synchronously active when hippocampus and prefrontal cortex theta rhythmic oscillations of excitability are coherent. Above) Rasters show timing of discharge of prefrontal neurons. Red stars above and peaks in black traces below indicate synchronous firing. Below) The coherence of theta oscillations in hippocampal and prefrontal LFPs over time is color-coded. Such coherence related cell assemblies appear when the rat learns a new rule in the maze (from Benchenane et al. Neuron 2010).
Simultaneous multichannel recording of local field potentials (LFPs) demonstrating oscillatory activity and action potentials in the hippocampus of an unanesthetized sleeping rat (arrows above and vertical raster bars below (each row corresponds to a single unit isolated from the overlying traces. The black trace is the filtered LFP to reveal 'ripple oscillations' associated with memory replay. Here the ripples were used to trigger local stimulation that briefly suppressed hippocampal cell activity, and impaired learning (not shown; Girardeau et al, 2009, Nature Neuroscience).
Selected Publications 2005-2010
- Benchenane K., Peyrache A., Khamassi M., Tierney P., Gioanni Y., Battaglia F.P. & Wiener S.I. (2010), Coherent theta oscillations and reorganization of spike timing in the hippocampal-prefrontal network upon learning. Neuron, (in press).
- Peyrache A., Khamassi M., Benchenane K., Wiener S.I. & Battaglia F.P. (2009), Replay of rule-learning related neural patterns in the prefrontal cortex during sleep. Nat Neurosci. 12(7):919-26.
- Geisler C., Robbe D., Zugaro M.B., Sirota A. & Buzsaki G. (2007), Hippocampal place cell assemblies are speed-controlled oscillators. Proc Natl Acad Sci, 104(19): 8149-8154.
- Sara S.J. (2009), The locus coeruleus and noradrenergic modulation of cognition. Nat Rev Neurosci, 10(3):211-23.
- Ramadan W., Eschenko O. & Sara S.J. (2009), Hippocampal sharp wave/ripples during sleep for consolidation of associative memory. PLoS One, 4(8):e6697.
- Peyrache A., Benchenane K., Khamassi M., Wiener S.I. & Battaglia F.P. (2010), Sequential reinstatement of neocortical activity during slow oscillations depends on cells' global activity. Front Syst Neurosci, 3:18.
- Girardeau G., Benchenane K., Wiener S.I., Buzsaki G. & Zugaro M.B. (2009), Selective suppression of hippocampal ripples impairs spatial memory. Nat Neurosci, 12:1222-1223.
- Peyrache A., Benchenane K., Khamassi M., Wiener S.I. & Battaglia F.P. (2009), Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution. J Comput Neurosci, Jun 16.
- Peyrache A., Khamassi M., Benchenane K., Wiener S.I. & Battaglia F.P. (2009), Replay of rule-learning related neural patterns in the prefrontal cortex during sleep. Nat Neurosci, 12:919-926.
- Khamassi M., Mulder A.B., Tabuchi E., Douchamps V. & Wiener S.I. (2008), Anticipatory reward signals in ventral striatal neurons of behaving rats. Eur J Neurosci, 28:1849-1866.
- Sara S.J. & Hars B. (2006), In memory of consolidation. Learn Mem, 13(5): 515-21.
- Wiener S.I. & Taube J.S., eds. (2005), Head Direction Cells and Neuronal Mechanisms of Spatial Orientation, MIT Press, Cambridge, 460 pps.
- Zugaro M.B., Monconduit L. & Buzsáki G. (2005), Spike phase precession persists after transient intrahippocampal perturbation. Nat Neurosci. 8(1):67-71.