Bickle foundation. high risk high reward.
NSERC grant. Cross-modal measurement of in-vivo spiking activities from the known cell-types (Neural recoding + analysis)
Aim1. Develop cross-modal electrophysiology recording and stimulation capability combined with optical recording and stimulation at the brain-wide, cellular resolution.
polymer microelectrodes, microLED, transparent glass electrodes, multifunctional probes
Aim2. Generate electro-optical groundtruth recordings by tracking the spiking activities of known cell types over multiple days, and use them to validate existing spike sorting and Ca image analysis algorithms.
Aim3. Develop online analysis software to analyze the electrical and optical recordings in real-time.
Implement algorithms using real-time OS, FPGA, and
NSERC grant. Develop AI-based predicitve neuroinformatics platform for distributed computing environment
Aim 1. Develop web-based platform to benchmark existing neural decoding algorithms using publicly available neural recordings paired with behavioral or sensory recordings.
Based on SpikeForest pipeline in collaboration with Flatiron Institute. Combines calcium imaging analysis, spike sorting analysis, behavioral analysis. Uses IBL and Allen brainobservatory dataset
Aim 2. Develop algorithms to predict voluntary decisions animals make during spatial navigations using existing datasets.
T-maze. W-maze. accuracy and predictive time window evaluation. LFP and spiking information. phase
CIHR grant. Neurodynamics during social functions in normal and autistic brains
I am interested in studying synchronized neurodynamics in a pair of socially interacting animals under naturalistic conditions.
In particular, I want to understand how social behaviours are perceived and generated in distributed brain areas including the auditory and motor cortex, amygdala, and hippocampus.
Mice vocalize at ultrasonic frequencies and I want to investigate how various communication signals play a role in synchronizing neural states in healthy individuals as well as a mouse autism model .
The understanding gained from this research may reveal novel biological markers for autism spectrum disorder (ASD) based on key factors distinguishing autistic and healthy brains in perceiving and expressing vocal communication.
In addition, long-term neural recordings in multiple brain regions could reveal a circuit-level action of pharmacological agents such as R-Baclofen, which has been recently developed and clinically evaluated to treat the symptoms of ASD.
One of the hallmarks of ASD is an enhanced ability to recognize fine perceptual details while missing out on a larger context.
By using ultrasonic vocalization as a behavioural assay, I want to measure how various stages of sensory (auditory) information processing are affected by ASD and understand the action of R-Baclofen in inducing neuroplasticity over an extended period.
Recently, functional brain stimulation is beginning to replace pharmacological treatments for various neurological conditions including Parkinson’s disease, epilepsy, and depression to overcome drug resistance and unintended side effects.
Based on understanding the circuit-level mechanism of R-Baclofen, I want to explore targeted neurostimulation to achieve similar effects in the animal models of ASD.
My initial approach would be to apply a machine-learning driven bidirectional neural interface to detect and interfere with pathological neurodynamics as well as to induce neuroplasticity that affects the resting brain state.