There is now compelling evidence that the allocation of memory to specific neurons (neuronal allocation) and synapses (synaptic allocation) in a neurocircuit is not random and that instead specific mechanisms, such as increases in neuronal excitability and synaptic tagging and capture, determine the exact sites where memories are stored. We propose an integrated view of these processes, such that neuronal allocation, synaptic tagging and capture, spine clustering and metaplasticity reflect related aspects of memory allocation mechanisms. Importantly, the properties of these mechanisms suggest a set of rules that profoundly affect how memories are stored and recalled.

Modeling studies suggest that clustered structural plasticity of dendritic spines is an efficient mechanism of information storage in cortical circuits. However, why new clustered spines occur in specific locations and how their formation relates to learning and memory (L&M) remain unclear. Using in vivo two-photon microscopy, we track spine dynamics in retrosplenial cortex before, during, and after two forms of episodic-like learning and find that spine turnover before learning predicts future L&M performance, as well as the localization and rates of spine clustering. Consistent with the idea that these measures are causally related, a genetic manipulation that enhances spine turnover also enhances both L&M and spine clustering. Biophysically inspired modeling suggests turnover increases clustering, network sparsity, and memory capacity. These results support a hotspot model where spine turnover is the driver for localization of clustered spine formation, which serves to modulate network function, thus influencing storage capacity and L&M.

Heritable mutations, known as inborn errors of metabolism, cause numerous devastating human diseases, typically as a result of a deficiency in essential metabolic products or the accumulation of toxic intermediates. We have isolated a missense mutation in the Drosophila sugarkill (sgk) gene that causes phenotypes analogous to symptoms of triosephosphate isomerase (TPI) deficiency, a human familial disease, characterized by anaerobic metabolic dysfunction resulting from pathological missense mutations affecting the encoded TPI protein. In Drosophila, the sgk gene encodes the glycolytic enzyme TPI. Our analysis of sgk mutants revealed TPI impairment associated with reduced longevity, progressive locomotor deficiency, and neural degeneration. Biochemical studies demonstrate that mutation of this glycolytic enzyme gene does not result in a bioenergetic deficit, suggesting an alternate cause of enzymopathy associated with TPI impairment.