Septal projections to the nucleus incertus in the rat: Bidirectional pathways for modulation of hippocampal function

Projections from the nucleus incertus (NI) to the septum have been implicated in the modulation of hippocampal theta rhythm. In this study we describe a previously uncharacterized projection from the septum to the NI, which may provide feedback modulation of the ascending circuitry. Fluorogold injections into the NI resulted in retrograde labeling in the septum that was concentrated in the horizontal diagonal band and areas of the posterior septum including the septofimbrial and triangular septal nuclei. Double-immunofluorescent staining indicated that the majority of NI-projecting septal neurons were calretinin-positive and some were parvalbumin-, calbindin-, or glutamic acid decarboxylase (GAD)−67-positive. Choline acetyltransferase-positive neurons were Fluorogold-negative. Injection of anterograde tracers into medial septum, or triangular septal and septofimbrial nuclei, revealed fibers descending to the supramammillary nucleus, median raphe, and the NI. These anterogradely labeled varicosities displayed synaptophysin immunoreactivity, indicating septal inputs form synapses on NI neurons. Anterograde tracer also colocalized with GAD-67-positive puncta in labeled fibers, which in some cases made close synaptic contact with GAD-67-labeled NI neurons. These data provide evidence for the existence of an inhibitory descending projection from medial and posterior septum to the NI that provides a "feedback loop" to modulate the comparatively more dense ascending NI projections to medial septum and hippocampus. Neural processes and associated behaviors activated or modulated by changes in hippocampal theta rhythm may depend on reciprocal connections between ascending and descending pathways rather than on unidirectional regulation via the medial septum.Grant sponsors: Fundación Alicia Koplowitz Fellowship (to A.M.S.P.), CAPES-Brasil Bex - 4494/09-1 (to F.N.S.) and 4496/09-4 (to C.W.P.) and Fapitec edital #01/08 (to F.N.S.), FIS-isciiiPI10/01399 (to J.S.), National Health and Medical Research Council of Australia - 520299 (to S.M.), 509246, 1005985, and 1005988 (to A.L.G.), the Florey Foundation (to S.M., A.L.G.), Besen Family Foundation (to A.L.G.) and a NEUREN project, FP7-PEOPLE-IRSES PIRSES-GA-2012-318997 (to A.L.G., F.E.O.-B.)

Grid Cells, Place Cells, and Geodesic Generalization for Spatial Reinforcement Learning

Reinforcement learning (RL) provides an influential characterization of the brain's mechanisms for learning to make advantageous choices. An important problem, though, is how complex tasks can be represented in a way that enables efficient learning. We consider this problem through the lens of spatial navigation, examining how two of the brain's location representations—hippocampal place cells and entorhinal grid cells—are adapted to serve as basis functions for approximating value over space for RL. Although much previous work has focused on these systems' roles in combining upstream sensory cues to track location, revisiting these representations with a focus on how they support this downstream decision function offers complementary insights into their characteristics. Rather than localization, the key problem in learning is generalization between past and present situations, which may not match perfectly. Accordingly, although neural populations collectively offer a precise representation of position, our simulations of navigational tasks verify the suggestion that RL gains efficiency from the more diffuse tuning of individual neurons, which allows learning about rewards to generalize over longer distances given fewer training experiences. However, work on generalization in RL suggests the underlying representation should respect the environment's layout. In particular, although it is often assumed that neurons track location in Euclidean coordinates (that a place cell's activity declines “as the crow flies” away from its peak), the relevant metric for value is geodesic: the distance along a path, around any obstacles. We formalize this intuition and present simulations showing how Euclidean, but not geodesic, representations can interfere with RL by generalizing inappropriately across barriers. Our proposal that place and grid responses should be modulated by geodesic distances suggests novel predictions about how obstacles should affect spatial firing fields, which provides a new viewpoint on data concerning both spatial codes