Peyman Golshani

What is he best known for?

The fields of study he is best known for:

• Neuroscience
• Gene
• Neuron

Peyman Golshani spends much of his time researching Neuroscience, Hippocampus, Hippocampal formation, Neural ensemble and Context. His Excitatory postsynaptic potential, Cellular neuroscience, Biological neural network, Neocortex and Visual cortex investigations are all subjects of Neuroscience research. His Excitatory postsynaptic potential research is multidisciplinary, incorporating elements of Visual system, Cholinergic, Depolarization and Membrane potential.

His work carried out in the field of Biological neural network brings together such families of science as CNTNAP2, Astrocyte and Receptor, Molecular neuroscience, Calcium signaling. Peyman Golshani has included themes like Transgene and In vivo in his Hippocampus study. His research integrates issues of Affect, Encoding and Cellular excitability in his study of Hippocampal formation.

His most cited work include:

• Absence of CNTNAP2 Leads to Epilepsy, Neuronal Migration Abnormalities, and Core Autism-Related Deficits (639 citations)
• A shared neural ensemble links distinct contextual memories encoded close in time (420 citations)
• A shared neural ensemble links distinct contextual memories encoded close in time (420 citations)

What are the main themes of his work throughout his whole career to date?

Peyman Golshani spends much of his time researching Neuroscience, Calcium imaging, Inhibitory postsynaptic potential, Hippocampal formation and Visual cortex. He merges Neuroscience with Population in his study. His Calcium imaging research incorporates elements of Neocortex, Microscope, Cerebral cortex and In vivo.

Peyman Golshani has researched Hippocampal formation in several fields, including Interneuron and Epilepsy. His Visual cortex research focuses on Sensory processing and how it connects with Stimulus. He has included themes like Neural ensemble and Encoding in his Hippocampus study.

He most often published in these fields:

• Neuroscience (105.38%)
• Calcium imaging (29.03%)
• Inhibitory postsynaptic potential (20.43%)

What were the highlights of his more recent work (between 2018-2021)?

• Neuroscience (105.38%)
• Visual cortex (25.81%)
• Calcium imaging (29.03%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Neuroscience, Visual cortex, Calcium imaging, Task and Optogenetics. His study on Inhibitory postsynaptic potential and Hippocampal formation is often connected to Population and Huntington's disease as part of broader study in Neuroscience. His work deals with themes such as Object, Perirhinal cortex and Afferent, which intersect with Hippocampal formation.

He interconnects Cerebral cortex, Bursting, Transgene and Mutation in the investigation of issues within Calcium imaging. His research in Optogenetics intersects with topics in Medium spiny neuron, Stimulation, Nucleus and Neuron. His Excitatory postsynaptic potential study also includes fields such as

• Stroke recovery together with Biological neural network,
• CNTNAP2 that connect with fields like Electroencephalography.

Between 2018 and 2021, his most popular works were:

• Correlated Neural Activity and Encoding of Behavior across Brains of Socially Interacting Animals. (68 citations)
• All the light that we can see: a new era in miniaturized microscopy (48 citations)
• Breakdown of spatial coding and interneuron synchronization in epileptic mice. (37 citations)

In his most recent research, the most cited papers focused on:

• Neuroscience
• Gene
• Neuron

Neuroscience, Inhibitory postsynaptic potential, Hippocampal formation, Kinematics and Toolbox are his primary areas of study. Neuroscience and Population are two areas of study in which Peyman Golshani engages in interdisciplinary research. His Inhibitory postsynaptic potential research is multidisciplinary, relying on both Subiculum, Object, Perirhinal cortex, Entorhinal cortex and Afferent.

His Hippocampal formation study integrates concerns from other disciplines, such as Temporal lobe, Epilepsy, Interneuron and Visual cortex. Kinematics is integrated with Task, Deep learning, Artificial intelligence, Transfer of learning and Machine learning in his research. His study in Prefrontal cortex is interdisciplinary in nature, drawing from both Neural activity, Local field potential and Calcium imaging.

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