Tuning curve shift by attention modulation in cortical neurons: a computational study of its mechanisms.
Physiological studies of visual attention have demonstrated that focusing attention near a visual cortical neuron's receptive field (RF) results in enhanced evoked activity and RF shift. In this work, we explored the mechanisms of attention induced RF shifts in cortical network models that receive an attentional 'spotlight'. Our main results are threefold. First, whereas a 'spotlight' input always produces toward-attention shift of the population activity profile, we found that toward-attention shifts in RFs of single cells requires multiplicative gain modulation. Secondly, in a feedforward two-layer model, focal attentional gain modulation in first-layer neurons induces RF shift in second-layer neurons downstream. In contrast to experimental observations, the feedforward model typically fails to produce RF shifts in second-layer neurons when attention is directed beyond RF boundaries. We then show that an additive spotlight input combined with a recurrent network mechanism can produce the observed RF shift. Inhibitory effects in a surround of the attentional focus accentuate this RF shift and induce RF shrinking. Thirdly, we considered interrelationship between visual selective attention and adaptation. Our analysis predicts that the RF size is enlarged (respectively reduced) by attentional signal directed near a cell's RF center in a recurrent network (resp. in a feedforward network); the opposite is true for visual adaptation. Therefore, a refined estimation of the RF size during attention and after adaptation would provide a probe to differentiate recurrent versus feedforward mechanisms for RF shifts.
Compte
Albert
A
Instituto de Neurociencias de Alicante, Universidad Miguel Hernández - Consejo Superior de Investigaciones Científicas, 03550 Sant Joan d'Alacant, Spain. acompte@umh.es
Wang
Xiao-Jing
XJ
D000222:Adaptation, Physiological / Q000502:physiology; D000818:Animals; D001288:Attention / Q000502:physiology*; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology; D005403:Fixation, Ocular / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009473:Neuronal Plasticity / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*; D014794:Visual Fields / Q000502:physiology*