View Mayank Mehta's TEDx talk: It turns out we can shut off the parts of our brain that maps our world -- using technologies including Virtual Reality. What might we learn about how we perceive space and time, and brain health along the way?
Neurons are made of a small body or soma, but extensive, tree like structures called dendrites. We measured the electrical activity of dendrites in freely behaving subjects for the first time and found that dendrites generate nearly ten times as many spikes as the cell body.
Neurons in a part of the brain called the hippocampus are crucial for learning and memory but the underlying mechanisms are not fully understood. Our study addressed this by demonstrating a causal and surprisingly direct influence of visual cues on these neurons' activity.
Virtual reality is becoming an increasingly popular technique for many purposes, but how individual neurons react when the subjects explore virtual reality is unknown. We made these measurements and found surprising results
A wide range of environmental stimuli and brain rhythms, generate precise mental maps of space. The mechanism by which this happens remain to be understood. A noninvasive virtual reality system reveals that there are multiple neural maps of space that compete with each other.
Our research has focused on computational and experimental investigations of learning and memory, seeking to understand how the brain learns and remembers how to navigate unfamiliar environments, research aimed at paving the way to better understanding mechanisms of learning and memory in neural networks.
UCLA researchers have for the first time measured the activity of a brain region known to be involved in learning, memory and Alzheimer's disease during sleep. They discovered that this region, called the entorhinal cortex, behaves as if it is remembering something, even during anesthesia-induced sleep.
In a discovery that challenges conventional wisdom on the brain mechanisms of learning, UCLA neuro-physicists have found there is an optimal brain "rhythm," or frequency, for changing synaptic strength. And further, like stations on a radio dial, each synapse is tuned to a different optimal frequency for learning.
Rhythms in the brain that are associated with learning become stronger as the body moves faster. Our research team found that the strength of the gamma rhythm grew substantially as running speed increased, bringing scientists a step closer to understanding the brain functions essential for learning and navigation.
Memories are stored in both the neocortex and the hippocampus. Then, during sleep, the hippocampus, acting as a temporary storage system, is cleared for another day of learning, while the memories are retained in the neocortex, which provides permanent storage much like a computer hard disk.
Neurons are tree-like cells with connections between neurons made on branch-like processes called dendrites. A novel, biophysical 'Hebbian' learning rule is proposed that explains the dendritic contribution to learning.
Neuronal communication is crucial for learning and this requires high temporal precision. A mechanism is proposed where brain rhythms make neuronal communication more precise and facilitate learning.
The mind is thought to be the emergent property of the activities of ensembles of neurons. The nature of these emergent properties and how they arise are unknown. This is the focus of our research. In particular, our current research addresses the following fundamental questions in Neurophysics:
How is information about the physical world represented by ensembles of neurons? In particular, what are the neural mechanisms of perceiving space-time?
How do these neural representations evolve with learning?
What is the role of brain rhythms in learning and memory?
How does sleep influence learning?
To address these questions we use both experimental and theoretical approaches as follows:
- Develop hardware to measure and manipulate neural activity and behavior.
- Measure the activity of ensembles of well isolated neurons from many hippocampal and neocortical areas simultaneously during learning and during sleep.
- Develop data analysis tools to decipher the patterns of neural activity and field potentials, and their relationship to behavior.
- Develop biophysical theories of synapses, neurons and neuronal networks that can explain these experimental findings, relate them to the underlying cellular mechanisms, and make experimentally testable predictions.
The results would not only provide fundamental understanding of neural ensemble dynamics but also point to novel ways of treating learning and memory disorders.
Linking hippocampal multiplexed tuning, Hebbian plasticity and navigation. Jason Moore, Jesse Cushman, Lavanya Acharya, Brianna Popeney, Mayank Mehta (2021). PDF.
Virtual reality can be used to boost or control
brain rhythms and to alter neural dynamics, wiring and plasticity
Enhanced hippocampal theta
rhythmicity and emergence of eta oscillation in virtual reality. Karen Safaryan
& Mayank R. Mehta. Nature Neuroscience Volume 24, pages 1065-1070 (2021).
Follow this link to watch Mayak Mehta's KITP Blackboard Lunch talk on the neurophysics of Space, Time and Learning. Watch the video.
Luke Kemp explores why researchers such as Mayank Mehta are using rats to work out whether there's a link between VR and dementia. Read news coverage here.
Neurons are ten times more active than previously measured. Dendrites occupy more than 90% of neuronal tissue but are difficult to measure. Moore et al developed a technique to record the subthreshold membrane potential and spikes from neocortical distal dendrites. Read news coverage here.
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