What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Neuron
- Statistics
Maurice J. Chacron mainly investigates Neuroscience, Sensory system, Electric fish, Stimulus and Neural coding.
His work in the fields of Neuroscience, such as Biological neural network, overlaps with other areas such as Network architecture.
His study focuses on the intersection of Sensory system and fields such as Pyramidal cell with connections in the field of Information transfer, Sensory input, Bursting and Single spike.
He combines subjects such as Receptive field, Electrophysiology, Neuron and Nervous system with his study of Electric fish.
His Stimulus study also includes fields such as
- Communication which is related to area like Biological system,
- Anatomy which is related to area like Stimulation and Sensory neuron.
His Noise research includes elements of Vestibular system, Audiology and Electroreception.
His most cited work include:
- Neural variability, detection thresholds, and information transmission in the vestibular system. (188 citations)
- Negative Interspike Interval Correlations Increase the Neuronal Capacity for Encoding Time-Dependent Stimuli (187 citations)
- Parallel Processing of Sensory Input by Bursts and Isolated Spikes (168 citations)
What are the main themes of his work throughout his whole career to date?
Maurice J. Chacron mainly focuses on Neuroscience, Electric fish, Sensory system, Stimulus and Neural coding.
His research in Neuroscience focuses on subjects like Coding, which are connected to Otolith.
His study in Electric fish is interdisciplinary in nature, drawing from both Biological system, Receptive field and Midbrain.
In his study, Neuromodulation is strongly linked to Serotonergic, which falls under the umbrella field of Sensory system.
His Stimulus research includes themes of Correlation, Pyramidal cell, Sensory neuron, Information theory and Artificial intelligence.
His Neural coding study combines topics in areas such as Biological neural network and Decorrelation, Statistics.
He most often published in these fields:
- Neuroscience (65.31%)
- Electric fish (45.58%)
- Sensory system (42.18%)
What were the highlights of his more recent work (between 2016-2021)?
- Neuroscience (65.31%)
- Neural coding (33.33%)
- Stimulus (38.10%)
In recent papers he was focusing on the following fields of study:
Maurice J. Chacron spends much of his time researching Neuroscience, Neural coding, Stimulus, Perception and Electric fish.
His work carried out in the field of Neuroscience brings together such families of science as Coding and Serotonin.
His work in the fields of Stimulus, such as Sensory Adaptation, intersects with other areas such as ENCODE.
His biological study spans a wide range of topics, including Electrophysiology and Contrast.
In Electric fish, Maurice J. Chacron works on issues like Sensory input, which are connected to Augmented reality.
His research integrates issues of Serotonergic and Ion channel in his study of Sensory system.
Between 2016 and 2021, his most popular works were:
- The statistics of the vestibular input experienced during natural self‐motion differ between rodents and primates (26 citations)
- Descending pathways generate perception of and neural responses to weak sensory input. (21 citations)
- Feedback optimizes neural coding and perception of natural stimuli. (15 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Neuron
- Statistics
Maurice J. Chacron mostly deals with Neuroscience, Neural coding, Perception, Electric fish and Sensory system.
His work in Stimulus and Vestibular system is related to Neuroscience.
His study looks at the intersection of Neural coding and topics like Coding with Vestibular nuclei, Motor coordination and Motion.
His research investigates the connection between Perception and topics such as Contrast that intersect with issues in Orientation, Head and Otolith.
Maurice J. Chacron has included themes like Electrophysiology and Neuron in his Electric fish study.
His study on Sensory system is mostly dedicated to connecting different topics, such as Biological neural network.
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