The spine problem: finding a function for dendritic spines

Abstract

Why do neurons have dendritic spines? This question—the heart of what Yuste calls “the spine problem”—presupposes that why-questions of this sort have scientific answers: that empirical findings can favor or count against claims about why neurons have spines. Here we show how such questions can receive empirical answers. We construe such why-questions as questions about how spines make a difference to the behavior of some mechanism that we take to be significant. Why-questions are driven fundamentally by the effort to understand how some item, such as the dendritic spine, is situated in the causal structure of the world (the causal nexus). They ask for a filter on that busy world that allows us to see a part’s individual contribution to a mechanism, independent of everything else going on. So understood, answers to why-questions can be assessed by testing the claims these answers make about the causal structure of a mechanism. We distinguish four ways of making a difference to a mechanism (necessary, modulatory, component, background condition), and we sketch their evidential requirements. One consequence of our analysis is that there are many spine problems and that any given spine problem might have many acceptable answers.

The mysteries of remote memory

“…Dendritic spines represent the postsynaptic component of excitatory synapses and their growth has been postulated as a necessary mechanism of neural circuits to accommodate plastic changes taking place during a learning-engaged signalling cascade. The size and density of spines during this structural remodelling process have been found to change in a number of synaptic and behavioural plasticity paradigms, leading to the suggestion that they may form a structural basis for long-term memory [ 39 , 115 – 119 ]. Dendritic spines show different shapes: mushroom, thin, stubby and branched types, while the types most reported in memory studies are the thin spines with a small head (i.e.…”

“…Zooming into such memory traces, the synaptic storage of mnemonic information is thought to occur in basal and apical dendritic spines in pyramidal neurons: dendritic spines represent a means for structural remodelling in the brain where plastic changes occur during learning and memories get stored [ 39 , 40 ]. Notwithstanding, from engrams to spines surprisingly little evidence exists in the literature on the grounds of remote information processing, maintenance and storage to account for the lifelong and persistent nature of the mnemonic signal.…”

A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior

“…We may wish for such a theory to be biophysical in the sense that it goes beyond descriptions of BOLD magnitudes, explaining also neurophysiological data [127], and to be mechanistic in the sense that we understand how a change in network-level neurophysiological processes will lead to a change in behavior [128,129]. We suggest that a network-based theory of human learning will require models that explicitly bridge network models of brain function with mathematical models of human behavior (Figure 4).…”

Cajal’s Law of Dynamic Polarization: Mechanism and Design

“…1 . Malanowski and Craver [22] review Cajal's [3] pioneering judgment that dendritic spines are real entities and not artifacts of the Golgi's staining technique. According to them, Cajal's result prompted a transparently teleological question: "why do neurons have spines?"…”