Complexities and uncertainties of neuronal network function

Abstract

The nervous system generates behaviours through the activity in groups of neurons assembled into networks. Understanding these networks is thus essential to our understanding of nervous system function.Understanding a network requires information on its component cells, their interactions and their functional properties. Few networks come close to providing complete information on these aspects. However, even if complete information were available it would still only provide limited insight into network function. This is because the functional and structural properties of a network are not fixed but are plastic and can change over time. The number of interacting network components, their (variable) functional properties, and various plasticity mechanisms endows networks with considerable flexibility, but these features inevitably complicate network analyses.This review will initially discuss the general approaches and problems of network analyses. It will then examine the success of these analyses in a model spinal cord locomotor network in the lamprey, to determine to what extent in this relatively simple vertebrate system it is possible to claim detailed understanding of network function and plasticity.

Neuronal network analyses: premises, promises and uncertainties

“…I have outlined this for the model network that I work on, the lamprey spinal cord locomotor network (see Parker 2006a). Repeated claims that this network has been experimentally characterized (e.g.…”

“…Grillner et al 2005) to the extent that behaviour can be explained in terms of specific functional interactions between identified neurons ('we can actually make the bridge from the molecular to the behavioural level'; Grillner 1999) are very widely accepted within and outside the field. However, these claims and their acceptance ignore the uncertainties over the characterization of network components (see Rovainen 1983;Buchanan 1999;Parker 2006a) and hide very significant gaps in our understanding of the basic network connectivity (figure 1; see Parker 2006a). These uncertainties alone (there are more) logically preclude any claims of direct deterministic links between cellular properties and network function and behaviour (see Parker 2006a; figure 1).…”

“…At the opposite end of the scale, we can characterize and quantify behaviours and correlate them with activity imaged with increasing sophistication in different regions of the brain. However, between these two levels there is an 'explanatory gap' that has prevented us from explaining behaviours directly in terms of their underlying cellular and synaptic mechanisms (Dudai 2004;Parker 2006a). We are thus data-rich but lack knowledge of how to integrate these data into a coherent picture of brain function.…”

“…The diagram also omits ipsilateral inhibitory inputs and crossing excitatory inputs (see Parker 2006a for a more detailed discussion). The apparent characterization here is achieved by assumption and extrapolation and by omitting reference to highlighted gaps in our knowledge (Rovainen 1983;Buchanan 1999;Parker 2006a). …”

“…These claims are difficult to evaluate without detailed knowledge of the specific systems studied. However, they often lack direct causal links and instead rely on assumptions and extrapolations between the molecular, cellular, network and behavioural levels (see Dudai 2004;Parker 2006a).…”