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Using perceptual learning to understand and influence face recognition

使用感知学习来理解和影响人脸识别

基本信息

批准号：
ES/R005532/1
负责人：
Ciro Civile
金额：
$ 24.13万
依托单位：
UNIVERSITY OF EXETER
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FR005532%2F1
关键词：
Using perceptual learning understand influence

项目摘要

Perceptual learning is a fundamental cognitive skill. It can be defined as an enhancement in the ability to distinguish between similar stimuli (that otherwise would be very hard to tell apart) as a consequence of experience with them, or with stimuli similar to the target stimuli. The proposed project focuses on the development of this phenomenon as a key factor to our ability to recognise faces. Further, by using a range of neuroscience techniques (EEG/ERP, tDCS, fMRI, TMS) in conjunction with the behavioural designs I have developed, I will investigate methods to improve this perceptual skill and define specific brain structures responsible for the control and development of this phenomenon. So, basically, I aim to find out how we improve at telling things apart (discrimination) and to discover ways of enhancing this ability.I will start by developing the case for perceptual learning as a key contributor to one of the most robust cognitive phenomenon in face recognition i.e. the composite face effect. This refers to individuals' decreased ability to recognise the top half of one face presented in composite with the bottom half of another face when the composite is upright and aligned than when the two halves are offset laterally (misalignment). By using novel categories of prototype-defined chequerboards which participants will be pre-exposed to during the study procedure, I would expect to show a similar composite effect for familiar chequerboards to that usually found with faces. This will be our index of perceptual learning.The project will then continue by using different neurostimulation techniques (tDCS and TMS) to selectively increase and decrease the composite effect for chequerboards and that for faces. Through a combination of tDCS and EEG techniques, this project will also reveal how specific brain responses usually found for faces, can also be found for familiar chequerboards and be altered by neurostimulation. Finally, a combination of tDCS and fMRI will help to localise more precisely the brain structures involved in perceptual learning.This project will provide us with insights into the mechanisms that characterise the development and control of perceptual learning and will extend perceptual learning to face recognition by showing how similar effects to those usually found for faces can be found for categories of stimuli that participants had never seen before entering the lab. It will also provide evidence for the neurocognitive basis of perceptual learning. We will use these results to devise methods of training that can enhance our discrimination abilities in various domains. It would allow us to tailor training programmes (e.g. involving stimuli such as faces, fingerprints, cervical smears, mammograms) to provide maximum benefit in terms of performance by the trainee. As an example, this research would be suitable for enhancing the face recognition skills of frontline and intelligence staff, and one might be able to selectively increase the effectiveness of this training through the use of mobile neuroscience techniques based on the Starstim EEG/tDCS system. It would also give us insights into how to design artificial systems for the detection and recognition of such stimuli, which would be of interest to companies specialised in computer software or apps for face recognition.

知觉学习是一种基本的认知技能。它可以被定义为由于经验的结果而提高了区分相似刺激(否则很难区分)或与目标刺激相似的刺激的能力。拟议的项目侧重于这种现象的发展，将其作为我们识别面孔能力的关键因素。此外，通过使用一系列神经科学技术(EEG/ERP、tdcs、fMRI、TMS)，结合我开发的行为设计，我将研究提高这种感知技能的方法，并确定负责控制和发展这种现象的特定大脑结构。因此，基本上，我的目标是找出我们在区分事物(区分)方面的改进，并找到增强这种能力的方法。我将首先阐述知觉学习作为人脸识别中最强大的认知现象之一--合成面孔效应--的关键贡献因素。这指的是，当合成的脸是竖直的并对齐时，个体识别合成的一张脸的上半部分和另一张脸的下半部分的能力比当两个半部分横向偏移时的能力降低(错位)。通过使用新类别的原型定义的棋盘，参与者将在研究过程中预先接触到这些棋盘，我希望对熟悉的棋盘显示出类似于通常发现的面孔的合成效果。这将是我们感知学习的指标。然后，该项目将继续使用不同的神经刺激技术(tdcs和tms)，选择性地增加和减少棋盘和人脸的综合效果。通过tdcs和EEG技术的结合，这个项目还将揭示如何在面孔上找到特定的大脑反应，在熟悉的棋盘上也能找到，并通过神经刺激改变。最后，tdcs和fMRI的结合将有助于更精确地定位参与知觉学习的大脑结构。这个项目将为我们提供对知觉学习发展和控制的机制的见解，并将通过展示如何在参与者进入实验室之前从未见过的刺激类别中找到与通常对面部发现的效果相似的效果，将知觉学习扩展到人脸识别。这也将为知觉学习的神经认知基础提供证据。我们将利用这些结果来设计培训方法，以提高我们在各个领域的辨别能力。这将使我们能够定制培训方案(例如，涉及面部、指纹、宫颈涂片、乳房X光等刺激物)，以最大限度地提高受训者的表现。例如，这项研究将适合于提高一线和情报人员的人脸识别技能，并且人们可能能够通过使用基于StarSTim EEG/tDCS系统的移动神经科学技术来选择性地提高这种培训的有效性。它还将让我们深入了解如何设计人工系统来检测和识别此类刺激，这将引起专门从事人脸识别计算机软件或应用程序的公司的兴趣。