RT Journal Article
SR Electronic
T1 Experience drives the development of novel, reliable cortical sensory representations from endogenously structured networks
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.11.14.516507
DO 10.1101/2022.11.14.516507
A1 Sigrid Trägenap
A1 David E. Whitney
A1 David Fitzpatrick
A1 Matthias Kaschube
YR 2022
UL http://biorxiv.org/content/early/2022/11/14/2022.11.14.516507.abstract
AB Cortical circuits embody remarkably reliable neural representations of sensory stimuli that are critical for perception and action. The fundamental structure of these network representations is thought to arise early in development prior to the onset of sensory experience. However, how these endogenously generated networks respond to the onset of sensory experience, and the extent to which they reorganize with experience remains unclear. Here we examine this ‘nature-nurture transform’ using chronic in vivo calcium imaging to probe the developmental emergence of the representation of orientation in visual cortex of the ferret, a species with a well-defined modular network of orientation-selective responses. At eye opening, visual stimulation of endogenous networks evokes robust modular patterns of cortical activity. However, these initial evoked activity patterns are strikingly different from those in experienced animals, exhibiting a high degree of variability both within and across trials that severely limits stimulus discriminability. In addition, visual experience is accompanied by a number of changes in the structure of the early evoked modular patterns including a reduction in dimensionality and a shift in the leading pattern dimensions indicating significant network reorganization. Moreover, these early evoked patterns and their changes are only loosely constrained by the endogenous network structure of spontaneous activity, and spontaneous activity itself reorganizes considerably to align with the novel evoked patterns. Based on a computational network model, we propose that the initial evoked activity patterns reflect novel visual input that is only poorly aligned with the endogenous networks and that highly reliable visual representations emerge from a realignment of feedforward and recurrent networks that is optimal for these novel patterns of visually driven activity.Competing Interest StatementThe authors have declared no competing interest.