Trends in Cognitive Science 25周年特辑：Looking Forward

为了庆祝Trends in Cognitive Sciences创刊25周年，本期TiCS安排了一个特辑，由领域大牛们撰写了他们认为在未来25年里比较重要的开放性认知科学问题。这些文章涉及到认知科学的各个主题，也包括了认知科学在现实世界的适用性、认知科学与人工智能的互动等等。这篇推送整理了这个特辑文章的目录和小结，可供参考~

Link：https://www.cell.com/trends/cognitive-sciences/current

Matthew M. Botvinick; Realizing the promise of AI: a new calling for cognitive science.

Rapid progress in artificial intelligence (AI) places a new spotlight on a long-standing question: how can we best develop AI to maximize its benefits to humanity? Answering this question in a satisfying and timely way represents an exciting challenge not only for AI research but also for all member disciplines of cognitive science.

Nick Chater; The computational society. 

How do individual human minds create languages, legal systems, scientific theories, and technologies? From a cognitive science viewpoint, such collective phenomena may be considered a type of distributed computation in which human minds together solve computational problems beyond any individual. This viewpoint may also shift our perspective on individual minds.

Floris P. de Lange,Lea-Maria Schmitt,Micha Heilbron; Reconstructing the predictive architecture of the mind and brain. 

Predictive processing has become an influential framework in cognitive neuroscience. However, it often lacks specificity and direct empirical support. How can we probe the nature and limits of the predictive brain? We highlight the potential of recent advances in artificial intelligence (AI) for providing a richer and more computationally explicit test of this theory of cortical function.

Andreas K. Engel,Christian Gerloff; Dynamic functional connectivity: causative or epiphenomenal?. 

Dynamic coupling of neural signals is a hallmark of brain networks, but its potential relevance is still debated. Does coupling play a causal role for network functions, or is it just a by-product of structural connectivity or other physiological processes? With intervention techniques that have become available, experiments seem within reach that may provide answers to this long-standing question.

Chris D. Frith,Uta Frith; The mystery of the brain–culture interface. 

Nature and culture work together to shape who we are. We are embedded in culture and are profoundly influenced by what those around us say and do. The interface between minds occurs at the level of explicit metacognition, which is at the top of our brain's control hierarchy. But how do our brains do this?

Shihui Han; Default beliefs as a basis of social decision-making. 

Default beliefs are implicit assumptions about the future existence of oneself, others, and the environment. They differ from individual and cultural beliefs in that they are held universally, implicitly, and with high confidence. What is the content of default beliefs? How are they represented in the brain? And what is their role in social decision-making?

Catherine A. Hartley; How do natural environments shape adaptive cognition across the lifespan? 

How does human cognition adapt to idiosyncratic features of our real-world experiences across our lifetimes? The dynamic interaction between individuals and their natural environments is rarely the focus of study within cognitive science, but I argue that a more ecological approach will be critical for advancing developmental science and revealing the adaptive nature of cognition.

Agustin Ibanez; The mind’s golden cage and cognition in the wild. 

The mind has been traditionally conceived as a set of differentiated, compartmentalized cognitive elements. However, understanding everyday, naturalistic cognition across brain health and disease entails major challenges. How can mainstream approaches be extended to cognition in the wild? Pragmatic, methodological, disease-related, and theoretical turns are proposed for future scientific development.

Michael Inzlicht,Aidan V. Campbell; Effort feels meaningful.

People often dislike effort and avoid it when they can, but effort can also imbue tasks with meaning. This is the case for real-life tasks, but also novel tasks devoid of true purpose. Why does effort feel meaningful, under what conditions, and for whom?

Neil A. Lewis Jr; What would make cognitive science more useful?

What would make cognitive science more useful? In this essay, I argue that the cognitive sciences could advance theories and be more useful to society if they devoted more effort to conducting research in ways that include a more diverse set of participants and stakeholders than they have historically.

Ka-Yuet Liu,Hakwan Lau; Subjective experiences as nodes within mental disorder networks。

What are the functional roles of subjective experiences? Answering this question amounts to charting a course for the cognitive science of consciousness, where mental processes can be described in terms of their functions. If we strategically focus on mental disorders, preliminary answers may be in sight within 25 years.

Eleanor A. Maguire; Does memory research have a realistic future?

How do we remember our past experiences? This question remains stubbornly resistant to resolution. The next 25 years may see significant traction on this and other outstanding issues if memory researchers capitalise on exciting technological developments that allow embodied cognition to be studied in ways that closely approximate real life.

James L. McClelland; Capturing advanced human cognitive abilities with deep neural networks.

How can artificial neural networks capture the advanced cognitive abilities of pioneering scientists? I suggest they must learn to exploit human-invented tools of thought and human-like ways of using them, and must engage in explicit goal-directed problem solving as exemplified in the activities of scientists and mathematicians and taught in advanced educational settings.

Sashank Pisupati,Yael Niv; The challenges of lifelong learning in biological and artificial systems.

How do biological systems learn continuously throughout their lifespans, adapting to change while retaining old knowledge, and how can these principles be applied to artificial learning systems? In this Forum article we outline challenges and strategies of ‘lifelong learning’ in biological and artificial systems, and argue that a collaborative study of each system’s failure modes can benefit both.

David Poeppel,William Idsardi; We don’t know how the brain stores anything, let alone words.

Cognitive, computational, and neurobiological approaches have made impressive advances in characterizing the operations that transform linguistic signals into meanings. But our understanding of how words and concepts are retained in the brain remains inadequate. How is the long-term storage of words, or in fact any representations, achieved? This puzzle requires new thinking to stimulate reinvestigation of the storage problem.

Suparna Rajaram; Collective memory and the individual mind.

How does social transmission of information shape individual and collective memory? Taking a cognitive-experimental perspective, I propose three critical research themes to tackle in the next 25 years: the dynamic reciprocity of influence between the individual and the collective; changes in the individual and collective memory structures; and the impact of culture.

Charan Ranganath; What is episodic memory and how do we use it?

What are the neural and computational principles that give rise to episodic memory? Although memory is probably the most studied topic in psychology and cognitive neuroscience, most research has focused on learning at the micro-level. I outline the limitations of this approach and propose a ‘molar’ approach to tackle episodic memory at the scale of life.

Rebecca Saxe; Perceiving and pursuing legitimate power.

How do people perceive and pursue legitimate power? For the social sciences, this question is venerable. Yet, for cognitive science, it offers fresh and generative opportunities to explore how adults evaluate legitimacy, how children learn to do so, and what difference legitimate power makes for people’s thoughts, feelings, and actions.

Linda B. Smith,Hadar Karmazyn-Raz; Episodes of experience and generative intelligence 

How do humans, including toddlers, take knowledge from past experiences and apply this knowledge in new ways? Current approaches to human and artificial intelligence (AI) fail to offer satisfactory explanations. We suggest the explanation will be found in the coherence statistics of the individual time-extended episodes of human experience and the cognitive processes those statistics engage.

Olaf Sporns; The complex brain: connectivity, dynamics, information.

Most would agree, the brain is complex. But, beyond metaphor, does the brain’s complexity demand a paradigm shift in how we study its structure and function? I argue that complexity manifests in three domains – connectivity, dynamics, and information – and that unlocking their interactions will greatly advance our understanding of brain and cognition.

Catherine Tallon-Baudry; The topological space of subjective experience

Subjective experiences often feel rich, yet are most often quantified with simple metrics, such as a few levels on a predefined scale. What are the dimensions and topological organization of subjective experience? How do they relate to behavioral output? And how do they map onto the classical cognitive domains?

Irene Tracey; Why pain hurts.

We have made great strides in understanding how the human brain constructs the multidimensional experience of pain – both acute and chronic – over the past few decades. Pain wears many guises, but at its core, it hurts. How is this core component of pain represented in the brain, and how can we target it for relief?

Thomas W. Elston, Joni D. Wallis; Decoding cognition in real-time

How can we study unobservable cognitive processes that cannot be measured directly? This has been an enduring challenge for cognitive scientists. In this essay we discuss advances in neurotechnology that could allow cognitive processes to be decoded in real-time and the implications that this may have for cognitive science and the treatment of neuropsychiatric disease.

Robert J. Zatorre; Going down to go up: understanding human auditory cognition by investigating cortical–subcortical interactions

Human auditory cognition spans everything from detecting a creaking door in the night to enjoying beautiful music. Neurofunctional models of these processes tend to focus on cortical networks, but how do subcortical circuits contribute to auditory cognition? Answering this question will lead to a richer understanding of how we process the complex auditory world.

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