Scene complexity modulates degree of feedback activity during object detection in natural scenes.

Iris I. A. Groen,Sennay Ghebreab,Sara Jahfari,Victor A. F. Lamme,Noor Seijdel,H. Steven Scholte,Samuel J. Gershman

doi:10.1371/journal.pcbi.1006690

Abstract

Selective brain responses to objects arise within a few hundreds of milliseconds of neural processing, suggesting that visual object recognition is mediated by rapid feed-forward activations. Yet disruption of neural responses in early visual cortex beyond feed-forward processing stages affects object recognition performance. Here, we unite these discrepant findings by reporting that object recognition involves enhanced feedback activity (recurrent processing within early visual cortex) when target objects are embedded in natural scenes that are characterized by high complexity. Human participants performed an animal target detection task on natural scenes with low, medium or high complexity as determined by a computational model of low-level contrast statistics. Three converging lines of evidence indicate that feedback was selectively enhanced for high complexity scenes. First, functional magnetic resonance imaging (fMRI) activity in early visual cortex (V1) was enhanced for target objects in scenes with high, but not low or medium complexity. Second, event-related potentials (ERPs) evoked by target objects were selectively enhanced at feedback stages of visual processing (from ~220 ms onwards) for high complexity scenes only. Third, behavioral performance for high complexity scenes deteriorated when participants were pressed for time and thus less able to incorporate the feedback activity. Modeling of the reaction time distributions using drift diffusion revealed that object information accumulated more slowly for high complexity scenes, with evidence accumulation being coupled to trial-to-trial variation in the EEG feedback response. Together, these results suggest that while feed-forward activity may suffice to recognize isolated objects, the brain employs recurrent processing more adaptively in naturalistic settings, using minimal feedback for simple scenes and increasing feedback for complex scenes.

Highlights

Object recognition is often regarded as a task that is solved in the first wave of visual processing [1]
There is evidence that disruption of visual processing beyond feed-forward stages leads to decreased object detection performance
In parahippocampal place area (PPA), differential activity related to target-presence was least pronounced for the high complexity scenes compared to the medium complexity scenes, while V1 activity was only modulated by target presence for high complexity scenes

Summary

Introduction

Object recognition is often regarded as a task that is solved in the first wave of visual processing [1]. One way in which feedback is thought to facilitate object recognition is through visual routines such as curve tracing and texture segmentation, to integrate line segments and other low-level features encoded in early visual areas [21,22,23]. Supporting this model of visual processing, transcranial stimulation evidence shows that detection of target objects in natural scenes deteriorates when neural activity in early visual cortex is disrupted not just at feed-forward processing stages (e.g., 100 ms after stimulus onset), and at feedback stages (e.g., 220 ms after stimulus onset [24,25])

Methods

Results

Discussion

Conclusion