Fast Visual Recognition Research Articles

Large-scale network dynamics underlying the first few hundred milliseconds after stimulus presentation: An investigation of visual recognition memory using iEEG.

Recognition memory is the ability to recognize previously encountered objects. Even this relatively simple, yet extremely fast, ability requires the coordinated activity of large-scale brain networks. However, little is known about the sub-second dynamics of these networks. The majority of current studies into large-scale network dynamics is primarily based on imaging techniques suffering from either poor temporal or spatial resolution. We investigated the dynamics of large-scale functional brain networks underlying recognition memory at the millisecond scale. Specifically, we analyzed dynamic effective connectivity from intracranial electroencephalography while epileptic subjects (n = 18) performed a fast visual recognition memory task. Our data-driven investigation using Granger causality and the analysis of communities with the Louvain algorithm spotlighted a dynamic interplay of two large-scale networks associated with successful recognition. The first network involved the right visual ventral stream and bilateral frontal regions. It was characterized by early, predominantly bottom-up information flow peaking at 115 ms. It was followed by the involvement of another network with predominantly top-down connectivity peaking at 220 ms, mainly in the left anterior hemisphere. The transition between these two networks was associated with changes in network topology, evolving from a more segregated to a more integrated state. These results highlight that distinct large-scale brain networks involved in visual recognition memory unfold early and quickly, within the first 300 ms after stimulus onset. Our study extends the current understanding of the rapid network changes during rapid cognitive processes.

A Fast Visual Recognition Memory System in Humans Identified Using Intracerebral ERP.

One key item of information retrieved when surveying our visual world is whether or not objects are familiar. However, there is no consensus on the respective roles of medial temporal lobe structures, particularly the perirhinal cortex (PRC) and hippocampus. We considered whether the PRC could support a fast recognition memory system independently from the hippocampus. We recorded the intracerebral electroencephalograph activity of epileptic patients while they were performing a fast visual recognition memory task, constraining them to use their quickest strategy. We performed event-related potential (ERP) and classification analyses. The PRC was, by far, the earliest region involved in recognition memory. This activity occurred before the first behavioral responses and was found to be related to reaction times, unlike the hippocampus. Single-trial analyses showed that decoding power was equivalent in the PRC and hippocampus but occurred much earlier in the PRC. A critical finding was that recognition memory-related activity occurred in different frontal and parietal regions, including the supplementary motor area, before the hippocampus. These results, based on ERP analyses, suggest that the human brain is equipped with a fast recognition memory system, which may bypass the hippocampus and in which the PRC plays a critical role.

Age effects on the neural processing of object-context associations in briefly flashed natural scenes

In daily life, fast visual recognition of surrounding objects is facilitated through context-based expectations. However the ability to rapidly and accurately recognize unexpected stimuli in a given environment is also crucial and this ability is impaired with age. The present fMRI study aimed at comparing in young and older adults the neural correlates of fast object processing. Patterns of cerebral activity were investigated in response to briefly-presented (100 ms) congruent and incongruent natural scenes. Participants were slower and less accurate when categorizing objects in incongruent relative to congruent contexts. This behavioral cost was notably more pronounced in the older group. Height and multivariate patterns of fMRI activity in context-selective regions were equivalent in both age groups, suggesting preserved processing of coarse scene features in older participants. Incongruent scenes elicited additional activity in the parahippocampal gyrus that possibly reflected simultaneous activation of rarely co-occurring neural representations. Contextual effects were observed in object-selective cortex for the young group only, and may be driven by detection of mismatch between actually perceived and previously-experienced associations. In the older group exclusively, increased bilateral prefrontal and left fusiform activity in response to incongruent scenes was observed. However this supplemental activity was not found to efficiently contribute to improve task performance in difficult visual conditions. Altogether these results suggest age-related changes in the interaction between object- and context-processing pathways, that may subserve impairment in fast identification of unexpected objects in natural scenes.

Pick-and-Place Task Implementation Using Visual Open-Loop Control

Abstract In the ever increasing number of robotic system applications in the industry, the robust and fast visual recognition and pose estimation of workpieces are of utmost importance. One of the ubiquitous tasks in industrial settings is the pick-and-place task where the object recognition is often important. In this paper, we present a new implementation of a work-piece sorting system using a template matching method for recognizing and estimating the position of planar workpieces with sparse visual features. The proposed framework is able to distinguish between the types of objects presented by the user and control a serial manipulator equipped with parallel finger gripper to grasp and sort them automatically. The system is furthermore enhanced with a feature that optimizes the visual processing time by automatically adjusting the template scales. We test the proposed system in a real-world setup equipped with a UR5 manipulator and provide experimental results documenting the performance of our approach.