What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Mathematical analysis
- Neuron
His primary areas of investigation include Neuroscience, Visual cortex, Stimulus, Artificial intelligence and Receptive field.
His work on Neuroscience is being expanded to include thematically relevant topics such as Synaptic plasticity.
In the subject of general Synaptic plasticity, his work in Homosynaptic plasticity, Synaptic scaling, Spike-timing-dependent plasticity and Nonsynaptic plasticity is often linked to Competition, thereby combining diverse domains of study.
His Stimulus study which covers Surround suppression that intersects with Pattern recognition, Neural coding, Biological neural network and Sensory neuroscience.
His work in the fields of Artificial neural network overlaps with other areas such as Simple.
His research investigates the connection with Receptive field and areas like Ocular dominance column which intersect with concerns in Monocular deprivation, Development, Ocular Physiological Phenomena and Optics.
His most cited work include:
- Competitive Hebbian learning through spike-timing-dependent synaptic plasticity (1941 citations)
- Neural Mechanisms of Orientation Selectivity in the Visual Cortex (573 citations)
- Ocular dominance column development: analysis and simulation (568 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Neuroscience, Visual cortex, Stimulus, Artificial intelligence and Receptive field.
Neuroscience is a component of his Excitatory postsynaptic potential, Inhibitory postsynaptic potential, Surround suppression, Simple cell and Sensory system studies.
His Visual cortex study combines topics in areas such as Orientation and Biological system.
The various areas that he examines in his Stimulus study include Feed forward, Neural Inhibition, Electrophysiology and Nonlinear system.
His work in the fields of Artificial intelligence, such as Hebbian theory, overlaps with other areas such as Simple.
In his study, which falls under the umbrella issue of Receptive field, Communication is strongly linked to Lateral geniculate nucleus.
He most often published in these fields:
- Neuroscience (37.58%)
- Visual cortex (27.88%)
- Stimulus (20.00%)
What were the highlights of his more recent work (between 2017-2021)?
- Neuroscience (37.58%)
- Stimulus (20.00%)
- Excitatory postsynaptic potential (12.73%)
In recent papers he was focusing on the following fields of study:
Neuroscience, Stimulus, Excitatory postsynaptic potential, Visual cortex and Inhibitory postsynaptic potential are his primary areas of study.
His Neuroscience study integrates concerns from other disciplines, such as Artificial neural network and Homeostasis.
His Stimulus study incorporates themes from Convolutional neural network, Pattern recognition, System model and Nonlinear system.
Set and Visual perception is closely connected to Sensory system in his research, which is encompassed under the umbrella topic of Excitatory postsynaptic potential.
His Visual cortex research integrates issues from Perception, Surround suppression, Cognitive science, Optogenetics and Neural correlates of consciousness.
His Surround suppression research is multidisciplinary, incorporating elements of Orientation, Feedback loop and Electrophysiology.
Between 2017 and 2021, his most popular works were:
- A deep learning framework for neuroscience (199 citations)
- The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability (63 citations)
- How biological attention mechanisms improve task performance in a large-scale visual system model. (27 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Neuron
- Mathematical analysis
The scientist’s investigation covers issues in Stimulus, Neuroscience, Excitatory postsynaptic potential, Sensory system and Visual cortex.
His research investigates the link between Stimulus and topics such as Nonlinear system that cross with problems in Network dynamics, Cerebral cortex, Neuron, Sensory cortex and Statistical physics.
His work carried out in the field of Neuroscience brings together such families of science as Artificial neural network and Deep learning.
His Sensory system study combines topics in areas such as Visual perception, Convolutional neural network and Set.
In his study, Variety, Cognition and Perspective is strongly linked to Perception, which falls under the umbrella field of Visual cortex.
His Inhibitory postsynaptic potential study integrates concerns from other disciplines, such as Surround suppression, Somatostatin and Disinhibition.
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