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Structural dynamics of dendritic spines in memory and cognition

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Recent studies show that dendritic spines are dynamic structures. Their rapid creation, destruction and shape-changing are essential for short- and long-term plasticity at excitatory synapses on pyramidal neurons in the cerebral cortex. The onset of long-term potentiation, spine-volume growth and an increase in receptor trafficking are coincident, enabling a ‘functional readout’ of spine structure that links the age, size, strength and lifetime of a synapse. Spine dynamics are also implicated in long-term memory and cognition: intrinsic fluctuations in volume can explain synapse maintenance over long periods, and rapid, activity-triggered plasticity can relate directly to cognitive processes. Thus, spine dynamics are cellular phenomena with important implications for cognition and memory. Furthermore, impaired spine dynamics can cause psychiatric and neurodevelopmental disorders.

Section snippets

Dendritic spines

On pyramidal neurons in the cerebral cortex, excitatory synapses terminate at spines, which are short protrusions joined to the main dendrite by a thin neck. Discovered in the 19th century and intensely scrutinized in the 20th century, dendritic spines are found in higher animals 1, 2 and some insects 3, 4. Spines exist only on certain types of neurons, including pyramidal neurons in the cortex, medium spiny neurons in the basal ganglia and Purkinje cells in the cerebellum. Spines are more

Activity-dependent structural plasticity of dendritic spines and receptor trafficking

At the level of the dendritic spine, structural dynamics and receptor trafficking both contribute to functional plasticity. For example, spine enlargement occurs within a minute (Figure 1a) [21], a time course that matches the rapid induction of LTP. Enlarged spines also explain the long-term maintenance of LTP, given that the number of functional AMPA receptors correlates with spine volume 14, 15, 16, 17, 18, 19, 20 (Figure 1c). And spine enlargement 45, 46, like the late phase of LTP and

Long-term intrinsic fluctuations and maintenance of spines

Neuronal networks reflect the properties of spine populations, rather than those of a single spine, because the generation of action potentials in a neuron requires the activation of many synapses. We recently identified a key phenomenon that affects the long-term behaviors of spine populations. Through the observation and systematic quantification of spine dynamics over periods of days (Figure 1b) [42], it became apparent that spine volumes grew and shrank spontaneously. These volumetric

Abnormalities in spine dynamics and mental disorders: a working model

Many clinical investigators have proposed that synapses are major sites of pathogenesis for mental disorders such as schizophrenia, autism and other conditions that show normal gross anatomy 7, 71, 72, 73. Here, we summarize the reports of dendritic spine abnormalities in these disorders and present a hypothesis for how these changes might yield such diverse symptoms.

Rapid structural dynamics of spines in cognition: a new hypothesis

Within the brain, the coordinated firing of neurons in space and time underlies myriad functions, including the cognitive processes of perception, emotion and volition 8, 96, 97. A major challenge in neuroscience is to delineate the physical conditions of the conscious brain 96, 98, sometimes referred to as the neuronal correlates of consciousness [99].

Unfortunately, many studies of these correlates reduce every neuron to its action potential. This presents an incomplete picture of cognitive

Concluding remarks

We have described the close relationship between spine structure and function, and introduced the hypothesis that intrinsic fluctuations in spine volumes account for the long-term maintenance of spines. The biophysical properties of these fluctuations could mirror the psychological properties of complex behaviors such as forgetting. Intrinsic fluctuations also predict the spontaneous generation of abundant new spines, leading to the random-generation-and-test model of new-memory acquisition.

We

Acknowledgements

We thank M. Fukuda, K. Kasai, A. Sawa and K. Toyama for helpful discussions. This work was supported by Grants-in-Aids from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan (H.K., J.N.).

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