Nature CommunicationsNeurosciencePeer-reviewed journal article
Feedforward attentional selection in sensory cortex
Jacob Alan WesterbergiD, Jeffrey D. SchalliD, Geoffrey Forrest WoodmaniD, Alexander MaieriD
Abstract
Salient objects stand out (pop-out) from their surroundings, grabbing our attention. Whether this phenomenon is a consequence of bottom-up sensory processing or predicated on top-down influence is debated. We show that the neural computation of attentional pop-out is embedded in the earliest cortical sensory response, seemingly void of feedback from higher-level areas. We measured synaptic and spiking activity across cortical columns in mid-level area V4 of monkeys searching for an attention-grabbing stimulus. Indexed by reaction times and behavioral accuracy, attention was captured at variable times. This moment of attentional capture occurred within the earliest feedforward response, both in terms of timing and spatial location. Moreover, the magnitude of the earliest sensory response predicted reaction times. Crucially, errant attentional selection and consequent behavior was associated with errant selection in sensory cortex. Together, these findings demonstrate a dominant role for feedforward activation of sensory cortex for dictating attentional priority and subsequent behavior. In briefWhy do certain objects stand out from their surroundings and seemingly grab our attention? In this study, Westerberg et al. determine that attentional selection for salient objects in our environment is computed in sensory cortex as soon as sensory information arrives. HighlightsO_LIEarly sensory responses in V4 predict attentional selection and behavioral responses C_LIO_LIErrant attentional selection in sensory cortex precedes errant behavior C_LIO_LITonic modulation of sensory cortex can regulate attentional selection C_LI
- organism: non-human primate
- assay: electronic health records
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 12
- FWCI
- 1.79
- Field percentile
- top 16%
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