Real-time Control of Decoded Brain Activity Using Artificial Neural Networks

使用人工神经网络实时控制解码的大脑活动

• 批准号: RGPIN-2022-04267
• 负责人: TaschereauDumouchel, Vincent
• 金额: $ 1.89万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=763629
• 关键词: Real; time; Control; Decoded; Brain

Our psychological well-being is greatly affected by our subjective emotional experiences. Yet we know surprisingly little about the brain mechanisms that generate such subjective states. Scientific progress in the field has been limited in part because we possess few methods capable of controlling fine-grained brain activity at will. Here we propose to address this issue with a new method combining artificial intelligence and brain imaging. More precisely, we propose to leverage modern artificial neural networks to generate "synthetic" visual stimuli capable of triggering specific patterns of brain activity. Previous experiments conducted in macaque monkeys showed that such synthetic stimuli were far more effective than the best natural stimuli at increasing the firing rate of specific neurons in the visual system. Importantly, such synthetic stimuli were also not recognized as instances of any particular object category which means that they could potentially be used without participants' awareness of the purpose or content of the manipulated brain activity. This NSERC Discovery grant will investigate if synthetic visual stimuli can be used to robustly and unconsciously generate subjective affective experiences. More precisely, we will determine if subjective experiences of fear can be generated by unconsciously activating the brain representation of feared animals in the ventral visual system. This proposal has two main objectives: First, we will adapt and validate an approach to generate synthetic images from functional magnetic resonance imaging (fMRI) activity. We will use two existing datasets to generate synthetic images associated with the visual presentation of animals from 30 different categories. Second, we will recruit participants reporting fear of some of the animals in our dataset. In a series of pre-registered double-blind placebo controlled fMRI experiments, we will determine if synthetic images generated from feared animal categories can modulate the targeted brain activity, subjective fear and physiological defensive responses. We hypothesize that synthetic stimuli will increase the activation of the brain representation of the feared animal and generate subjective experiences of fear and physiological defensive responses. This research project represents one of the first attempts to use artificial neural networks to control brain activity in humans. The synthetic stimuli created using this approach could present a unique opportunity to control specific brain representations in isolation, a feat that is usually impossible to achieve using natural stimuli. Such an intervention method could allow us to develop a direct means to interrogate how the brain generates subjective emotional experiences, representing a very valuable asset for the study of affective neurosciences and human consciousness.

我们的心理健康很大程度上受到主观情绪体验的影响。然而，我们对产生这种主观状态的大脑机制知之甚少。该领域的科学进步受到限制，部分原因是我们几乎没有能够随意控制细粒度大脑活动的方法。在这里，我们提出了一种结合人工智能和脑成像的新方法来解决这个问题。更准确地说，我们建议利用现代人工神经网络来产生能够触发特定大脑活动模式的“合成”视觉刺激。先前在猕猴身上进行的实验表明，在增加视觉系统中特定神经元的放电率方面，这种合成刺激比最好的自然刺激要有效得多。重要的是，这种合成刺激也不被认为是任何特定对象类别的实例，这意味着它们可能在没有参与者意识到操纵大脑活动的目的或内容的情况下被使用。这项NSERC发现基金将研究合成视觉刺激是否可以被用来产生强烈的、无意识的主观情感体验。更准确地说，我们将确定是否可以通过无意识地激活腹侧视觉系统中恐惧动物的大脑表征来产生主观的恐惧体验。本提案有两个主要目标：首先，我们将适应并验证一种从功能磁共振成像（fMRI）活动生成合成图像的方法。我们将使用两个现有的数据集来生成与30个不同类别动物的视觉表现相关的合成图像。其次，我们将招募对我们数据集中的一些动物感到恐惧的参与者。在一系列预先注册的双盲安慰剂对照fMRI实验中，我们将确定由恐惧动物类别生成的合成图像是否可以调节目标大脑活动、主观恐惧和生理防御反应。我们假设，合成刺激将增加大脑对恐惧动物表征的激活，并产生主观的恐惧体验和生理防御反应。这个研究项目代表了使用人工神经网络控制人类大脑活动的首次尝试之一。使用这种方法产生的合成刺激可以提供一个独特的机会来单独控制特定的大脑表征，这是使用自然刺激通常不可能实现的壮举。这种干预方法可以让我们发展一种直接的手段来询问大脑是如何产生主观情绪体验的，这对于情感神经科学和人类意识的研究来说是非常宝贵的资产。