AIMC Topic: Cognitive Neuroscience

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Employing artificial bee and ant colony optimization in machine learning techniques as a cognitive neuroscience tool.

Scientific reports
Higher education is essential because it exposes students to a variety of areas. The academic performance of IT students is crucial and might fail if it isn't documented to identify the features influencing them, as well as their strengths and shortc...

Studying memory narratives with natural language processing.

Trends in cognitive sciences
Cognitive neuroscience research has begun to use natural language processing (NLP) to examine memory narratives with the hopes of gaining a nuanced understanding of the mechanisms underlying differences in memory recall, both across groups and tasks....

A new era in cognitive neuroscience: the tidal wave of artificial intelligence (AI).

BMC neuroscience
Translating artificial intelligence techniques into the realm of cognitive neuroscience holds promise for significant breakthroughs in our ability to probe the intrinsic mechanisms of the brain. The recent unprecedented development of robust AI model...

The Neuroscience of Human and Artificial Intelligence Presence.

Annual review of psychology
Two decades of social neuroscience and neuroeconomics research illustrate the brain mechanisms that are engaged when people consider human beings, often in comparison to considering artificial intelligence (AI) as a nonhuman control. AI as an experim...

Reconstructing the predictive architecture of the mind and brain.

Trends in cognitive sciences
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 recen...

Explainable artificial intelligence based analysis for interpreting infant fNIRS data in developmental cognitive neuroscience.

Communications biology
In the last decades, non-invasive and portable neuroimaging techniques, such as functional near infrared spectroscopy (fNIRS), have allowed researchers to study the mechanisms underlying the functional cognitive development of the human brain, thus f...

Likelihood approximation networks (LANs) for fast inference of simulation models in cognitive neuroscience.

eLife
In cognitive neuroscience, computational modeling can formally adjudicate between theories and affords quantitative fits to behavioral/brain data. Pragmatically, however, the space of plausible generative models considered is dramatically limited by ...

Mind Meets Machine: Towards a Cognitive Science of Human-Machine Interactions.

Trends in cognitive sciences
As robots advance from the pages and screens of science fiction into our homes, hospitals, and schools, they are poised to take on increasingly social roles. Consequently, the need to understand the mechanisms supporting human-machine interactions is...

Individual differences among deep neural network models.

Nature communications
Deep neural networks (DNNs) excel at visual recognition tasks and are increasingly used as a modeling framework for neural computations in the primate brain. Just like individual brains, each DNN has a unique connectivity and representational profile...

Keep it real: rethinking the primacy of experimental control in cognitive neuroscience.

NeuroImage
Naturalistic experimental paradigms in neuroimaging arose from a pressure to test the validity of models we derive from highly-controlled experiments in real-world contexts. In many cases, however, such efforts led to the realization that models deve...