Expert-level neural engineering covering neural interfaces, brain-computer interfaces, neural signal processing, deep brain stimulation, and neuroprosthetics.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Utah array: 100 electrode silicon array, acute and chronic recording in cortex. Michigan probe: silicon shank with multiple recording sites along length. EEG: scalp electrodes, non-invasive, low spatial resolution, clinical standard. ECoG: electrocorticography, subdural electrodes, better resolution than EEG. Flexible electronics: conformal arrays reduce mechanical mismatch with brain tissue.
Spike sorting: classify action potentials by waveform shape to identify neurons. LFP: local field potential, population activity, lower frequency than spikes. Common average reference: subtract mean across channels to reduce common noise. Coherence: measure of synchrony between two neural signals in frequency domain. Decoding: machine learning to predict movement or intent from neural signals.
Motor BCI: decode motor cortex signals to control prosthetic or cursor. P300 speller: EEG-based communication for locked-in patients. SSVEP: steady-state visual evoked potential, gaze-based BCI. Closed-loop: detect neural state and deliver feedback or stimulation in real time. Decoder stability: neural tuning drifts over days, adaptive decoders required.
DBS: deep brain stimulation for Parkinson, depression, OCD, high frequency pulses. Charge balance: biphasic pulses prevent electrode and tissue damage. Charge density limit: below 30 microcoulombs per cm squared to avoid damage. TMS: transcranial magnetic stimulation, non-invasive cortical stimulation.
| Pitfall | Fix |
|---|---|
| Single session decoder assuming stability | Neural tuning drifts, use adaptive or recalibrate regularly |
| Charge imbalance causing tissue damage | Always use charge-balanced stimulation waveforms |
| Ignoring electrode impedance changes | High impedance indicates poor contact or tissue reaction |
| Overinterpreting EEG spatial resolution | EEG integrates over large cortical areas |
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Expert-level abstract algebra knowledge. Use when working with groups, rings, fields, modules, Galois theory, representation theory, or algebraic structures. Also use when the user mentions 'group', 'ring', 'field', 'homomorphism', 'isomorphism', 'normal subgroup', 'quotient group', 'Sylow theorem', 'Galois theory', 'polynomial ring', 'ideal', 'module', 'vector space', or 'representation theory'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert-level acoustics knowledge. Use when working with sound waves, acoustic propagation, resonance, standing waves, Doppler effect, room acoustics, ultrasound, noise control, musical acoustics, or architectural acoustics. Also use when the user mentions 'sound wave', 'decibel', 'frequency', 'resonance', 'standing wave', 'Doppler effect', 'acoustic impedance', 'reverberation', 'ultrasound', 'noise control', 'harmonics', or 'sound intensity'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert-level aerodynamics covering subsonic and supersonic flow, lift and drag, airfoil theory, boundary layers, compressible flow, and CFD methods.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert-level air quality engineering covering pollutant sources, atmospheric dispersion, air quality standards, emission controls, and air quality modeling.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert-level aircraft structures covering structural design philosophy, wing and fuselage analysis, fatigue and damage tolerance, composite structures, and certification.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert-level algorithms and complexity theory covering sorting, searching, graph algorithms, dynamic programming, greedy algorithms, NP-completeness, and algorithm design paradigms.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.