What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Artificial intelligence
- Cognition
His primary scientific interests are in Neuroscience, Cognitive psychology, Reinforcement learning, Prefrontal cortex and Brain mapping.
Neuroscience and Reinforcement are commonly linked in his work.
The concepts of his Cognitive psychology study are interwoven with issues in Dissociation and Social psychology.
The study incorporates disciplines such as Strategy, Neuroeconomics, Evidential decision theory and Decision analysis in addition to Reinforcement learning.
The Dorsolateral prefrontal cortex research he does as part of his general Prefrontal cortex study is frequently linked to other disciplines of science, such as Ageing, therefore creating a link between diverse domains of science.
His research investigates the connection between Brain mapping and topics such as Intertemporal choice that intersect with problems in Caudate nucleus, Visual perception and Dorsum.
His most cited work include:
- Prefrontal cortex and decision making in a mixed-strategy game. (550 citations)
- A hierarchy of intrinsic timescales across primate cortex (458 citations)
- Neuronal basis of age-related working memory decline (301 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Neuroscience, Cognitive psychology, Reinforcement learning, Prefrontal cortex and Artificial intelligence.
His study in Orbitofrontal cortex, Cortex, Primate, Premovement neuronal activity and Posterior parietal cortex is done as part of Neuroscience.
His study looks at the intersection of Cognitive psychology and topics like Cognition with Perception and Sensory system.
His work deals with themes such as Strategy, Game theory and Social decision making, which intersect with Reinforcement learning.
His Prefrontal cortex research is multidisciplinary, relying on both Working memory, Intertemporal choice and Temporal discounting.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Pattern recognition.
He most often published in these fields:
- Neuroscience (52.90%)
- Cognitive psychology (26.45%)
- Reinforcement learning (22.58%)
What were the highlights of his more recent work (between 2017-2021)?
- Neuroscience (52.90%)
- Developmental psychology (7.10%)
- Sensory system (7.74%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Neuroscience, Developmental psychology, Sensory system, Reinforcement learning and Cognitive psychology.
His Neuroscience study focuses mostly on Cortex, Prefrontal cortex, Orbitofrontal cortex, Dopamine receptor D2 and Addiction.
His Prefrontal cortex research is multidisciplinary, incorporating elements of Synaptic plasticity, Working memory, Neurophysiology and Anterior cingulate cortex.
In the field of Developmental psychology, his study on Autism overlaps with subjects such as Preference.
He combines subjects such as Stimulus, Cognition, Superior colliculus and Thalamus with his study of Sensory system.
His studies deal with areas such as Saccadic masking and Perception as well as Cognitive psychology.
Between 2017 and 2021, his most popular works were:
- Persistent Spiking Activity Underlies Working Memory. (102 citations)
- Orbitofrontal Circuits Control Multiple Reinforcement-Learning Processes (42 citations)
- Flexible combination of reward information across primates. (28 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Artificial intelligence
- Cognition
His main research concerns Neuroscience, Orbitofrontal cortex, Prefrontal cortex, Reinforcement learning and Volatility.
He merges Neuroscience with Retinal waves in his study.
His Orbitofrontal cortex research includes elements of Ventral striatum, Neurochemical and Dopamine.
Daeyeol Lee interconnects Synaptic plasticity, Working memory and Neurophysiology in the investigation of issues within Prefrontal cortex.
The various areas that Daeyeol Lee examines in his Reinforcement learning study include Nucleus accumbens, Amygdala and Biological neural network.
His research investigates the link between Volatility and topics such as Dorsolateral prefrontal cortex that cross with problems in Anterior cingulate cortex.
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