Neurogenesis in the dentate gyrus: carrying the message or dictating the tone

Abstract

The dentate gyrus (DG) is a region in the mammalian brain critical for memory encoding with a neuronal architecture and function that deviates considerably from other cortical areas. One of the major differences of the DG compared to other brain regions is the finding that the dentate gyrus generates new principal neurons that are continuously integrated into a fully functional neural circuit throughout life. Another distinguishing characteristic of the dentate network is that the majority of principal neurons are held under strong inhibition and rarely fire action potentials. These two findings raise the question why a predominantly silent network would need to continually incorporate more functional units. The sparse nature of the neural code in the DG is thought to be fundamental to dentate network function, yet the relationship between neurogenesis and low activity levels in the network remains largely unknown. Clues to the functional role of new neurons come from inquiries at the cellular as well as the behavioral level. Few studies have bridged the gap between these levels of inquiry by considering the role of young neurons within the complex dentate network during distinct stages of memory processing. We will review and discuss from a network perspective, the functional role of immature neurons and how their unique cellular properties can modulate the dentate network in memory guided behaviors.

Adult neurogenesis in the mammalian hippocampus: Why the dentate gyrus?

“…Hence, these findings strongly implicate abGCs in the local control of IN activity that feeds back onto the entire GC population to control firing (Lacefield et al 2012). Such observations are consistent with the morphology of DG PV basket cells that receive input from GCs and extend axonal arborizations across large swathes of the GCL (Lübke et al 1998) and support the hypothesis that abGCs impact activity across the entire DG network (see also Piatti et al 2013).…”

How Does the Brain Solve the Computational Problems of Spatial Navigation?

“…This hypothesis is supported by electrophysiological work Marrone et al 2011;Satvat et al 2011) and behavioral studies (McHugh et al 2007;Tronel et al 2012;Kheirbek et al 2012;Nakashiba et al 2012;Gilbert et al 2001;Creer et al 2010;Clelland et al 2009;Sahay et al 2011;Goodrich-Hunsaker et al 2008;Morris et al 2012;Kesner 2013;Tronel et al 2012;Lee et al 2004b). A number of developmental, physiological, and anatomical factors, including neurogenesis (Nakashiba et al 2012;Piatti et al 2013), sparse firing (Barnes et al 1990;Jung and McNaughton 1993;Chawla et al 2005;Neunuebel and Knierim 2012), large efficacious mossy terminals (McNaughton and Morris 1987;Henze et al 2002), and the anatomical divergence of inputs from EC onto DG , are likely to play a mechanistic role in the pattern separation functionality of this layer, possibly for the formation of independent (if not completely separated) representations of relatively similar places and environments [see recent review articles Aimone et al (2011), Yassa and Stark (2011), Schmidt et al (2012, Piatti et al (2013), Kesner (2013)]. …”

Adult Hippocampal Neurogenesis, Fear Generalization, and Stress

“…The MFB contacts with thorny excrescence-like spines of CA3 pyramidal cells mediate feed-forward excitation (FFE), whereas the disproportionately more numerous filopodial contacts with inhibitory interneurons mediate feedforward inhibition (FFI) onto CA3 pyramidal neurons (Nicoll and Schmitz, 2005). It is thought that a balance between FFE and FFI onto CA3 neurons is required for dictating the temporal window of activation of CA3 neurons, facilitate sparse coding and modulate excitation of the recurrent collateral circuitry of CA3; features long recognized as conducive to pattern separation-completion balance (Treves and Rolls, 1992;O'Reilly and McClelland, 1994;Bragin et al, 1995;McClelland and Goddard, 1996;Acsady and Kali, 2007;McBain, 2008;Cerasti and Treves, 2010;Torborg et al, 2010;Ikrar et al, 2013;Piatti et al, 2013). Furthermore and importantly, decreased FFI connectivity has been associated with increased time dependent loss of memory precision and generalization of fear (Ruediger et al, 2012).…”