MICA: The Translational, Computational and Neurocognitive Basis of Anxiety

MICA：焦虑的转化、计算和神经认知基础

• 批准号: MR/R020817/1
• 负责人: Oliver Robinson
• 金额: $ 220.89万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FR020817%2F1
• 关键词: MICA; Translational; Computational; Neurocognitive; Basis

One in four of us will suffer from some form of mental health problem in a given year. For the majority of us, this will be some form of anxiety or stress related problem. Some people's anxiety is so crippling that they end up housebound. Anxiety costs the UK economy over £14 billion a year.We currently have effective clinical treatments, both psychological (i.e. therapy) and pharmacological (i.e. medication), that can treat anxiety. However, we are not currently able to effectively target these treatments to people who will respond. In fact, for most people, the first treatment that they try will not work. Even more worrying is that for up to 25% of sufferers; none of our current treatments will work.There are at least two reasons that we have these problems targeting treatments:I) We do not know how our current treatments work at a biological levelII) We do not know how debilitating feelings of anxiety emerge from the underlying biology.Without a better understanding of both of these issues we will not improve our ability to target treatments. This fellowship therefore seeks to improve our understanding of the biological basis of anxiety symptoms and treatments. It focuses on psychological treatments and aims to better understand 1) the neural circuitry by which psychological treatment works; 2) develop new psychological treatments; and 3) better refine our understanding of the biological bases of anxiety diagnosis. Specifically:1) Neural Circuitry:Over the last decade, I have identified a brain circuit which drives feelings of anxiety but we do not know if it changes following treatment. In this project I will scan the brains of anxious people undergoing psychological treatment for anxiety and compare them to anxious people who are not. If we show that this same circuit is important for treatment response, it will enable us to better target treatments to individuals, and reduce the number of people who try treatments that do not work for them.2) Treatments:In parallel with this I will attempt to develop a new computerised treatment for anxiety. This is possible because my advances in a new field known as computational psychiatry have given us tools that provide better insight into the computational process of the brain, and how they change in anxiety disorders. I will therefore develop a computerised training procedure that targets these computational processes and test it in a treatment study. If this works, it will provide a quick and cost effective treatment that could be delivered by smartphones and ultimately reduce the number of individuals suffering from anxiety.3) Diagnosis:Finally, I will try to improve our understanding of how debilitating feelings of anxiety emerge in the first place. It is increasingly clear that our current diagnoses, which are based on symptom checklists, do not reflect truly separate biological categories. I will therefore search for 'trans-diagnostic' dimensions that drive anxiety but which cut across our current categories. I shall do this by getting thousands of people to complete a simple psychological task online that I have previously linked to debilitating anxiety. In addition, we will collect a wide range of other psychological tasks and questionnaires from these people. Applying state-of-the-art statistical methods to this 'big data' will enable us to identify trans-diagnostic dimensions that drive anxiety symptoms. In the long term these new trans-diagnostic dimensions will improve our ability to determine the biological factors driving symptoms and hence help us predict treatment response and develop new treatments.In sum, I will combine my unique inter-disciplinary skill-set, with my breakthroughs in delineating the neural and computational basis of anxiety, to develop new and more effective clinical tools for anxiety diagnosis and treatment, with the ultimate goal of improving the quality of life for millions of sufferers.

在给定的一年中，我们四分之一将遭受某种形式的心理健康问题。对于我们大多数人而言，这将是某种形式的焦虑或压力有关的问题。有些人的焦虑是如此削弱，以至于他们最终被房屋驱逐出境。焦虑使英国经济每年超过140亿英镑。我们目前进行了有效的临床治疗，无论是心理学（即治疗）和药物（即药物），可以治疗焦虑。但是，我们目前无法有效地将这些治疗定位于会有回应的人。实际上，对于大多数人来说，他们尝试的第一种治疗方法将无法使用。更令人担忧的是，多达25％的患者；我们目前的治疗均无法正常工作。至少有两个原因是我们在生物学水平上遇到这些问题的问题：i）我们不知道我们当前的治疗方法在生物学水平上如何起作用）我们不知道如何从潜在的生物学中浮现出使人衰弱的焦虑感。如果没有更好地了解这两个问题，我们将无法提高我们的靶向治疗能力。因此，该团契旨在提高我们对动画症状和治疗的生物学基础的理解。它的重点是心理治疗，旨在更好地理解心理治疗的神经回路； 2）发展新的心理疗法； 3）更好地完善我们的理解：1）神经回路：在过去的十年中，我确定了一种脑电路，它使人有焦虑的感觉，但我们不知道它是否在治疗后会发生变化。在这个项目中，我将扫描受到焦虑心理治疗的焦虑症患者的大脑，并将他们与焦虑的人进行比较。如果我们证明同一电路对于治疗反应很重要，它将使我们能够更好地针对个人的治疗，并减少尝试对他们不起作用的治疗方法的人数。2）治疗：与此相关，我将尝试开发一种新的计算机治疗焦虑。这是可能的，因为我在一个被称为计算精神病学的新领域的进步为我们提供了对大脑计算过程以及它们如何改变焦虑症的工具。因此，我将制定针对这些计算过程的计算机化培训程序，并在治疗研究中对其进行测试。如果有效，它将提供一种快速且具有成本效益的治疗方法，可以通过智能手机提供，并最终减少患有焦虑症的人的数量。3）诊断：最后，我将尝试提高我们对首先降低焦虑感的理解。越来越明显的是，我们当前基于症状清单的诊断并不能反映出真正单独的生物学类别。因此，我将搜索“跨诊断”维度，这些维度会引起焦虑，但逐渐跨越了我们当前的类别。我将通过让成千上万的人在网上完成一项简单的心理任务来做到这一点，我以前曾与使人虚弱的动画联系在一起。此外，我们将从这些人那里收集广泛的其他心理任务和问卷。将最新的统计方法应用于此“大数据”将使我们能够识别出驱动焦虑症状的反诊断维度。从长远来看，这些新的跨诊断维度将提高我们确定驱动症状的生物学因素的能力，从而帮助我们预测治疗的反应并发展新的治疗方法。总而言之，我将结合我独特的跨学科跨学科技能，以及我的突破性，以及确定焦虑的神经和计算基础的最终质量，以开发新的和更有效的工具，以促进新的和更有效的工具，并具有生动诊断，并具有生命性的工具，并具有生命性的工具，并具有生命的临床工具，并具有生命性的效果，并具有生命性的范围，并具有生动的临床工具，并具有良好的临床性能，并具有生动的诊断，并具有较大的良好性，并具有生动的诊断，并具有良好的质量。患者。

项目成果

Measuring cognitive effort without difficulty.

• DOI: 10.3758/s13415-023-01065-9
• 发表时间: 2023-04
• 期刊: Cognitive, affective & behavioral neuroscience
• 作者: Fleming H;Robinson OJ;Roiser JP
• 通讯作者: Roiser JP

Efficacy of attention bias modification via smartphones in a large population sample.

• DOI: 10.1098/rsos.211629
• 发表时间: 2022-08
• 期刊: ROYAL SOCIETY OPEN SCIENCE
• 影响因子: 3.5
• 作者: Chelliah, Alysha;Robinson, Oliver
• 通讯作者: Robinson, Oliver

The role of prefrontal-subcortical circuitry in negative bias in anxiety: Translational, developmental and treatment perspectives.

• DOI: 10.1177/2398212818774223
• 发表时间: 2018-01
• 期刊: Brain and neuroscience advances
• 作者: Carlisi CO;Robinson OJ
• 通讯作者: Robinson OJ

How representative are neuroimaging samples? Large-scale evidence for trait anxiety differences between fMRI and behaviour-only research participants.

• DOI: 10.1093/scan/nsab057
• 发表时间: 2021-09-30
• 期刊: Social cognitive and affective neuroscience
• 影响因子: 4.2
• 作者: Charpentier CJ;Faulkner P;Pool ER;Ly V;Tollenaar MS;Kluen LM;Fransen A;Yamamori Y;Lally N;Mkrtchian A;Valton V;Huys QJM;Sarigiannidis I;Morrow KA;Krenz V;Kalbe F;Cremer A;Zerbes G;Kausche FM;Wanke N;Giarrizzo A;Pulcu E;Murphy S;Kaltenboeck A;Browning M;Paul LK;Cools R;Roelofs K;Pessoa L;Harmer CJ;Chase HW;Grillon C;Schwabe L;Roiser JP;Robinson OJ;O'Doherty JP
• 通讯作者: O'Doherty JP

Association Between a Directly Translated Cognitive Measure of Negative Bias and Self-reported Psychiatric Symptoms.

• DOI: 10.1016/j.bpsc.2020.02.010
• 发表时间: 2022-03
• 期刊: Biological psychiatry. Cognitive neuroscience and neuroimaging
• 作者: Daniel-Watanabe L;McLaughlin M;Gormley S;Robinson OJ
• 通讯作者: Robinson OJ