Delayed formation of neural representations of space in aged mice.

Aging is associated with cognitive deficits, with spatial memory being very susceptible to decline. The hippocampal dentate gyrus (DG) is important for processing spatial information in the brain and is particularly vulnerable to aging, yet its sparse activity has led to difficulties in assessing changes in this area. Using in vivo two-photon calcium imaging, we compared DG neuronal activity and representations of space in young and aged mice walking on an unfamiliar treadmill. We found that calcium activity was significantly higher and less tuned to location in aged mice, resulting in decreased spatial information encoded in the DG. However, with repeated exposure to the same treadmill, both spatial tuning and information levels in aged mice became similar to young mice, while activity remained elevated. Our results show that spatial representations of novel environments are impaired in the aged hippocampus and gradually improve with increased familiarity. Moreover, while the aged DG is hyperexcitable, this does not disrupt neural representations of familiar environments.

Delayed formation of neural representations of space in aged mice.

Aging is associated with cognitive deficits, with spatial memory being very susceptible to decline. The hippocampal dentate gyrus (DG) is important for processing spatial information in the brain and is particularly vulnerable to aging, yet its sparse activity has led to difficulties in assessing changes in this area. Using in vivo two-photon calcium imaging, we compared DG neuronal activity and representations of space in young and aged mice walking on an unfamiliar treadmill. We found that calcium activity was significantly higher and less tuned to location in aged mice, resulting in decreased spatial information encoded in the DG. However, with repeated exposure to the same treadmill, both spatial tuning and information levels in aged mice became similar to young mice, while activity remained elevated. Our results show that spatial representations of novel environments are impaired in the aged hippocampus and gradually improve with increased familiarity. Moreover, while the aged DG is hyperexcitable, this does not disrupt neural representations of familiar environments.

Transcriptional regulation of neural stem cell expansion in the adult hippocampus.

Experience governs neurogenesis from radial-glial neural stem cells (RGLs) in the adult hippocampus to support memory. Transcription factors (TFs) in RGLs integrate physiological signals to dictate self-renewal division mode. Whereas asymmetric RGL divisions drive neurogenesis during favorable conditions, symmetric divisions prevent premature neurogenesis while amplifying RGLs to anticipate future neurogenic demands. The identities of TFs regulating RGL symmetric self-renewal, unlike those that regulate RGL asymmetric self-renewal, are not known. Here, we show in mice that the TF Kruppel-like factor 9 (Klf9) is elevated in quiescent RGLs and inducible, deletion of Klf9 promotes RGL activation state. Clonal analysis and longitudinal intravital two-photon imaging directly demonstrate that Klf9 functions as a brake on RGL symmetric self-renewal. In vivo translational profiling of RGLs lacking Klf9 generated a molecular blueprint for RGL symmetric self-renewal that was characterized by upregulation of genetic programs underlying Notch and mitogen signaling, cell cycle, fatty acid oxidation, and lipogenesis. Together, these observations identify Klf9 as a transcriptional regulator of neural stem cell expansion in the adult hippocampus.

In humans and other mammals, a region of the brain known as the hippocampus plays important roles in memory. New experiences guide cells in the hippocampus known as radial-glial neural stem cells (RGLs) to divide to make new neurons and other types of cells involved in forming memories. Each time an RGL divides, it can choose to divide asymmetrically to maintain a copy of itself and make a new cell of another type, or divide symmetrically (a process known as symmetric self-renewal) to produce two RGLs. Symmetric self-renewal helps to restore and replenish the pool of stem cells in the hippocampus that are lost due to injury or age, allowing us to continue making new neurons. Proteins known as transcription factors are believed to control how RGLs divide. Previous studies have identified several transcription factors that regulate the RGLs splitting asymmetrically to make neurons and other cells. But the identities of the transcription factors that regulate symmetric self-renewal in the adult hippocampus have remained elusive. Here, Guo et al. searched for transcription factors that regulate symmetric self-renewal of RGLs in mice. The experiments found that RGLs that are resting and not dividing (referred to as 'quiescent') have higher levels of a transcription factor called Klf9 than RGLs that are actively dividing. Loss of the gene encoding Klf9 triggered quiescent RGLs to start dividing, and further experiments showed that Klf9 directly inhibited symmetric self-renewal. Guo et al. then used an approach called in vivo translational profiling to generate a blueprint that revealed new insights into the molecular processes involved in this symmetric division. These findings pave the way for researchers to develop strategies that may expand the numbers of stem cells in the hippocampus. This could eventually be used to help replenish brain circuits with neurons and improve the memory of individuals with Alzheimer's disease or other conditions that cause memory loss.

Treadmill-based task for assessing spatial memory in head-fixed mice.

Several mouse in vivo neuronal recording techniques require head fixation. Head-fixed treadmill walking can be used to design tasks that enable the study of neural activity in the context of behavior. Here, we provide a detailed protocol for constructing a treadmill with tactile spatial cues, training mice on a rewarded behavioral task, and analyzing behavioral data. We discuss common problems and solutions we have developed to optimize training. Finally, we demonstrate how to test spatial memory performance using this task.