Topic: metabolic cost

Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing

Hippocampal place cell populations putatively encode allocentric spatial position [1-4]. In bats and rodents, place cells exhibit heterogeneously sized and overlapping receptive (or place) fields [5-9]. These heterogeneous place fields instantiate a multiscale spatial tuning landscape in which the larger place fields of some place cells encompass the relatively more numerous narrowly tuned place fields of other cells (Fig 1a). In this work, we investigate the effectiveness of such multiscale codes for encoding allocentric spatial position. We do so by deriving closed-form expressions for how w

A large part of mammalian brains is dedicated to sensory processing. Sensory receptors extract distinct but partly correlated features of the environment that vary at different timescales, and then transmit them through subcortical structures and a succession of recurrently connected cortical areas. A general theory on how sensory pathways encode, propagate, and transform sensory features is still missing. To understand how biophysically realistic neural networks support these fundamental brain functions, we developed an analytical framework based on the principle of efficient coding (Barlow,