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جلسه چهارم حل تمرین کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Extracting Phase from Hilbert and Morlet Wavelet Transform
* Interpreting Phase Time Series
* Intertrial-phase clustering/Resultant Vector
* Polar plots and Polar Histograms
* Introduction to Rayleigh test for non-uniformity of circular data
#Code #Matlab #Advanced_Neuroscience #BrainDynamicsWorkshop #PracSess4
مباحث جلسه:
* Extracting Phase from Hilbert and Morlet Wavelet Transform
* Interpreting Phase Time Series
* Intertrial-phase clustering/Resultant Vector
* Polar plots and Polar Histograms
* Introduction to Rayleigh test for non-uniformity of circular data
#Code #Matlab #Advanced_Neuroscience #BrainDynamicsWorkshop #PracSess4
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جلسه نهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session9
مباحث جلسه:
* Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session9
Neurosyntax_Workshop_Ephys_Sess9.pdf
3.1 MB
اسلاید های جلسه نهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session9
مباحث جلسه:
* Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session9
Torrence & Compo Wavelet Analysis Software
https://github.com/chris-torrence/wavelets
http://atoc.colorado.edu/research/wavelets/
https://github.com/chris-torrence/wavelets
http://atoc.colorado.edu/research/wavelets/
GitHub
GitHub - ct6502/wavelets: Torrence & Compo Wavelet Analysis Software
Torrence & Compo Wavelet Analysis Software. Contribute to ct6502/wavelets development by creating an account on GitHub.
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جلسه دهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session10
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session10
Neurosyntax_Workshop_Ephys_Sess10.pdf
5.4 MB
اسلاید های جلسه دهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session10
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session10
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جلسه یازدهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session11
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session11
Neurosyntax_Workshop_Ephys_Sess11.pdf
5.3 MB
جلسه یازدهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session11
مباحث جلسه:
* Cross-frequency Coupling - Implementation
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session11
نظرات، انتقادات، و پیشنهادات خودتون رو درباره کارگاه دینامیک مغز میتونید به صورت ناشناس به آیدی زیر ارسال کنید:
https://news.1rj.ru/str/HarfBeManBOT?start=NDUyMzU3NjEz
یا میتونید به صورت شناس به بات کانال ارسال کنید:
@neurosyntax_bot
https://news.1rj.ru/str/HarfBeManBOT?start=NDUyMzU3NjEz
یا میتونید به صورت شناس به بات کانال ارسال کنید:
@neurosyntax_bot
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جلسه پنجم حل تمرین کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
* Cross-frequency amplitude-amplitude comodulation
* Cross-frequency phase-amplitude coupling (Modulation Index)
#Code #Matlab #Advanced_Neuroscience #BrainDynamicsWorkshop #PracSess5
مباحث جلسه:
* Cross-frequency amplitude-amplitude comodulation
* Cross-frequency phase-amplitude coupling (Modulation Index)
#Code #Matlab #Advanced_Neuroscience #BrainDynamicsWorkshop #PracSess5
Neurosyntax_BDTAI_PracSess5.m
5.3 KB
کدهای جلسه پنجم کارگاه دینامیک مغز
تابع و داده MI را میتوانید از لینک زیر دریافت کنید:
https://github.com/tortlab/phase-amplitude-coupling
و Colormap استفاده شده را میتوانید از لینک زیر دریافت کنید:
https://www.mathworks.com/matlabcentral/fileexchange/35730-fire-and-or-custom-colormap-function
#BrainDynamicsWorkshop
#matlab
تابع و داده MI را میتوانید از لینک زیر دریافت کنید:
https://github.com/tortlab/phase-amplitude-coupling
و Colormap استفاده شده را میتوانید از لینک زیر دریافت کنید:
https://www.mathworks.com/matlabcentral/fileexchange/35730-fire-and-or-custom-colormap-function
#BrainDynamicsWorkshop
#matlab
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جلسه دوازدهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session12
مباحث جلسه:
Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
#Video #Advanced_Neuroscience #BrainDynamicsWorkshop #Session12
Neurosyntax_Workshop_Ephys_Sess12.pdf
5.9 MB
اسلایدهای جلسه دوازدهم کارگاه دینامیک مغز: تئوری، آنالیز و تفسیر
مباحث جلسه:
Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session12
مباحث جلسه:
Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
#Slide #Advanced_Neuroscience #BrainDynamicsWorkshop #Session12
🧠 Brain Dynamics Workshop:
Theory, Analysis and Interpretation
@Neuro_Syntax
🖥 Session01
* Introduction to brain signals and their biological substrates
* Signals, Time Series, and intro to Fourier Transform
🖥 Session02
* Discrete Time Fourier Transform
* Welch Power Spectrum
* Sampling Frequency Theorem, Aliasing, Nyquist Frequency
* Spectral Leakage
* Window Functions
+ Matlab Implementations
🖥 Session03
* Accurate scaling of fourier coefficients
* The effect of varying window length and overlap on power spectrum
* What are oscillators?
* How can oscillations be generated in the brain? Mechanisms of oscillations in the brain
* Neural oscillations: sustained activity or transient bursts?
* Stationarity and Non-stationarity
* Short-time fourier transform
* Morlet Wavelet representation
+ Matlab Implementations
🖥 Session04
* What are timestamps and what are they used for?
* Multitaper Method for Spectral Estimation: Variability and the problem with averages, Time-locked and Non-time locked, Phase locked and non-phase locked, Slepian Tapers
* Digital Filters - Design and Implementation: What are filters? What are different types of filteres? What are they used for? How do they affect the signal?
+ Matlab Implementations
🖥 Session05
* Hilbert Transform
* Envelope magnitude estimation
* Oscillatory Bout Detection using filter-Hilbert Method
* Oscillatory Bout Detection using BOSC
+ Matlab Implementations
🖥 Session06
* Periodic and aperiodic components in brain signal
* How aperiodic component can affect power analysis
* Parameterizing neural power spectra into periodic and aperiodic components
* Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations
🖥 Session07
* Methodological considerations for studying neural oscillations
🖥 Session08
* Introducing Phase Time Series
* The conditions for a meaningful Phase (Bedrosian Theorem)
* Uses of Phase Time Series
- Inter-trial Phase Clustering
- Cross-frequency phase-amplitude coupling
- Spik-field coherence
- Travelling Waves
🖥 Session09
* Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
🖥 Session10
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
🖥 Session11
* Cross-frequency Coupling - Implementation
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
🖥 Session12
Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
#BrainDynamicsWorkshop #neurosyntax
Theory, Analysis and Interpretation
@Neuro_Syntax
🖥 Session01
* Introduction to brain signals and their biological substrates
* Signals, Time Series, and intro to Fourier Transform
🖥 Session02
* Discrete Time Fourier Transform
* Welch Power Spectrum
* Sampling Frequency Theorem, Aliasing, Nyquist Frequency
* Spectral Leakage
* Window Functions
+ Matlab Implementations
🖥 Session03
* Accurate scaling of fourier coefficients
* The effect of varying window length and overlap on power spectrum
* What are oscillators?
* How can oscillations be generated in the brain? Mechanisms of oscillations in the brain
* Neural oscillations: sustained activity or transient bursts?
* Stationarity and Non-stationarity
* Short-time fourier transform
* Morlet Wavelet representation
+ Matlab Implementations
🖥 Session04
* What are timestamps and what are they used for?
* Multitaper Method for Spectral Estimation: Variability and the problem with averages, Time-locked and Non-time locked, Phase locked and non-phase locked, Slepian Tapers
* Digital Filters - Design and Implementation: What are filters? What are different types of filteres? What are they used for? How do they affect the signal?
+ Matlab Implementations
🖥 Session05
* Hilbert Transform
* Envelope magnitude estimation
* Oscillatory Bout Detection using filter-Hilbert Method
* Oscillatory Bout Detection using BOSC
+ Matlab Implementations
🖥 Session06
* Periodic and aperiodic components in brain signal
* How aperiodic component can affect power analysis
* Parameterizing neural power spectra into periodic and aperiodic components
* Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations
🖥 Session07
* Methodological considerations for studying neural oscillations
🖥 Session08
* Introducing Phase Time Series
* The conditions for a meaningful Phase (Bedrosian Theorem)
* Uses of Phase Time Series
- Inter-trial Phase Clustering
- Cross-frequency phase-amplitude coupling
- Spik-field coherence
- Travelling Waves
🖥 Session09
* Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
🖥 Session10
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
🖥 Session11
* Cross-frequency Coupling - Implementation
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
🖥 Session12
Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
#BrainDynamicsWorkshop #neurosyntax
🧠 Brain Dynamics Workshop:
Theory, Analysis and Interpretation
Programming and Practical Training Sessions
@Neuro_Syntax
🟡 Session01
FFT, Welch, STFT, Morlet Wavelet,
Unit Conversion,
Plotting
🟡 Session02
Morlet Wavelet Transform,
Multitaper Power Estimation,
Kernels and Convolution,
Digital Filters,
Hilbert Transform,
BOSC, Flattening Power Spectrum, Oscillation Detection
🟡 Session03
* Oscillation Detection using Envelope Thresholdon Method
* FOOOF - fitting oscillations & one over f (Matlab Implementation)
* fBOSC
🟡 Session04
* Extracting Phase from Hilbert and Morlet Wavelet Transform
* Interpreting Phase Time Series
* Intertrial-phase clustering/Resultant Vector
* Polar plots and Polar Histograms
* Introduction to Rayleigh test for non-uniformity of circular data
🟡 Session05
* Cross-frequency amplitude-amplitude comodulation
* Cross-frequency phase-amplitude coupling (Modulation Index)
#BrainDynamicsWorkshop #neurosyntax
Theory, Analysis and Interpretation
Programming and Practical Training Sessions
@Neuro_Syntax
🟡 Session01
FFT, Welch, STFT, Morlet Wavelet,
Unit Conversion,
Plotting
🟡 Session02
Morlet Wavelet Transform,
Multitaper Power Estimation,
Kernels and Convolution,
Digital Filters,
Hilbert Transform,
BOSC, Flattening Power Spectrum, Oscillation Detection
🟡 Session03
* Oscillation Detection using Envelope Thresholdon Method
* FOOOF - fitting oscillations & one over f (Matlab Implementation)
* fBOSC
🟡 Session04
* Extracting Phase from Hilbert and Morlet Wavelet Transform
* Interpreting Phase Time Series
* Intertrial-phase clustering/Resultant Vector
* Polar plots and Polar Histograms
* Introduction to Rayleigh test for non-uniformity of circular data
🟡 Session05
* Cross-frequency amplitude-amplitude comodulation
* Cross-frequency phase-amplitude coupling (Modulation Index)
#BrainDynamicsWorkshop #neurosyntax
🧠 Brain Dynamics Workshop: Theory, Analysis and Interpretation
Check our Channel: NeuroSyntax
🔲Syllabus:
◻️Introduction to brain signals and their biological substrates
* What are oscillators?
* How can oscillations be generated in the brain? Mechanisms of oscillations in the brain
◻️Signals, Time Series, and Fourier Transform
* Discrete Time Fourier Transform
* Welch Power Spectrum
* Sampling Frequency Theorem, Aliasing, Nyquist Frequency
* Spectral Leakage
* Window Functions
* Accurate scaling of fourier coefficients
* The effect of varying window length and overlap on power spectrum
* Neural oscillations: sustained activity or transient bursts?
* Stationarity and Non-stationarity
* Short-time fourier transform
* Morlet Wavelet representation
* What are timestamps and what are they used for?
* Multitaper Method for Spectral Estimation: Variability and the problem with averages, Time-locked and Non-time locked, Phase locked and non-phase locked, Slepian Tapers
◻️ Digital Filters - Design and Implementation: What are filters? What are different types of filteres? What are they used for? How do they affect the signal?
◻️ Hilbert Transform
* Envelope magnitude estimation
* Phase Estimation
◻️Oscillatory Bout Detection
* Oscillatory Bout Detection using filter-Hilbert Method, BOSC, eBOSC, and fBOSC
◻️Parameterizing neural power spectra into periodic and aperiodic components
* Periodic and aperiodic components in brain signal
* How aperiodic component can affect power analysis
* Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations
◻️ Methodological considerations for studying neural oscillations
◻️ Introducing Phase Time Series
* The conditions for a meaningful Phase (Bedrosian Theorem)
* Uses of Phase Time Series
* Inter-trial Phase Clustering/Phase Coherence/Resultant Vector
◻️ Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
◻️Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
🟨 + Matlab implementation of the analyses and Codes
Check our Channel: NeuroSyntax
🔲Syllabus:
◻️Introduction to brain signals and their biological substrates
* What are oscillators?
* How can oscillations be generated in the brain? Mechanisms of oscillations in the brain
◻️Signals, Time Series, and Fourier Transform
* Discrete Time Fourier Transform
* Welch Power Spectrum
* Sampling Frequency Theorem, Aliasing, Nyquist Frequency
* Spectral Leakage
* Window Functions
* Accurate scaling of fourier coefficients
* The effect of varying window length and overlap on power spectrum
* Neural oscillations: sustained activity or transient bursts?
* Stationarity and Non-stationarity
* Short-time fourier transform
* Morlet Wavelet representation
* What are timestamps and what are they used for?
* Multitaper Method for Spectral Estimation: Variability and the problem with averages, Time-locked and Non-time locked, Phase locked and non-phase locked, Slepian Tapers
◻️ Digital Filters - Design and Implementation: What are filters? What are different types of filteres? What are they used for? How do they affect the signal?
◻️ Hilbert Transform
* Envelope magnitude estimation
* Phase Estimation
◻️Oscillatory Bout Detection
* Oscillatory Bout Detection using filter-Hilbert Method, BOSC, eBOSC, and fBOSC
◻️Parameterizing neural power spectra into periodic and aperiodic components
* Periodic and aperiodic components in brain signal
* How aperiodic component can affect power analysis
* Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations
◻️ Methodological considerations for studying neural oscillations
◻️ Introducing Phase Time Series
* The conditions for a meaningful Phase (Bedrosian Theorem)
* Uses of Phase Time Series
* Inter-trial Phase Clustering/Phase Coherence/Resultant Vector
◻️ Cross-frequency Coupling
————Introduction
————Network Architecture and Mechanisms
+ Phase-phase coupling
+ Phase-frequency coupling
+ Phase-amplitude coupling
+ Amlitude-amplitude coupling
* Cross-frequency Coupling - Implementation
— Cross-frequency amplitude amplitude coupling
— Cross-frequency phase-amplitude coupling (PAC)
— Modualtion Index
— Dissociating spurious from valid PACs
— Harmonics
— Harmonic vs Non-Harmonic PAC
— Filter Settings for Phase and Amplitude Estimation in phase-amplitude coupling measures
— Detecting n:m phase-phase coupling
— Surrogate statistical tests for cross-freq coupling and cautions
* Cross-frequency Coupling - Function
— Integration Problem
— CFC for long-distance communication
— Multi-item/sequence representation
— Sensory Parsing
◻️Brain Oscillations and the Importance of Waveform Shape
* Introduction and Examples of Nonsinusoidal signals in the neural recordings
* Physiological Relevance of Oscillation Waveform
— Features of Nonsinusoidal Waveforms Relate to Physiology
— Features of Oscillatory Waveforms Relate to Behavior and Disease
* Methods
— Zero-crossing/Quadrant Point Method of Phase Estimation
— Empirical mode decompositions
——— Computations
——— Drawbacks
——— Ensemble Empirical Mode Decomposition
——— Noise-aided Multivariate Empirical Mode Decomposition
— Cycle-by-cycle analysis of Neural Oscillations
— Instantaneous Frequency
🟨 + Matlab implementation of the analyses and Codes
‼️تمام محتوای این دوره کاملا رایگان می باشد.
به کانال ما مراجعه کنید: نوروسینتکس
ارتباط با ما: @neurosyntax_bot
به کانال ما مراجعه کنید: نوروسینتکس
ارتباط با ما: @neurosyntax_bot
کارگاه دینامیک مغز: نظریه، تحلیل و تفسیر سیگنال های مغزی
در طی این دوره با سیگنال های الکتریکی مغز آشنا خواهید شد و روش های تحلیل و تفسیر سیگنال را "از پایه" خواهید آموخت. کارگاه شامل دو نوع جلسات نظریه و حل تمرین است. در نظریه، شما با مبانی فیزیولوژیک سیگنال های مغزی آشنا خواهید شد، نوروبیولوژی چگونگی تشکیل نوسانات را خواهید آموخت و با مبانی روش های تحلیل سیگنال آشنا خواهید شد. در جلسات حل تمرین، در متلب، کدهای تحلیل سیگنال را مینویسیم. در این جلسات بدنه اصلی کدها به صورت خط به خط بررسی میشود تا درک مناسبی از کدنویسی تحلیل سیگنال های مغزی ایجاد شود.
◻️سر فصل کامل این دوره را میتوانید از این لینک دریافت کنید: سیلابس دوره
◻️پیش نیاز این دوره آشنایی با مقدمات برنامه نویسی متلب است که میتوانید آن را به صورت رایگان از کانال ما دریافت کنید: کانال سوفی فیلیا - کافیست هشتگ #matlab و #saman را در این کانال جستجو کنید. (مقدمات برنامه نویسی پایتون را نیز میتوانید به صورت رایگان از همین کانال با هشتگ #python و #saman دریافت کنید.)
◻️تمامی ویدیو ها، اسلاید ها و کدهای متلب مربوط به جلسات 1 تا 12 دوره دینامیک مغز را میتوانید به صورت رایگان از کانال نوروسینتکس دریافت کنید:
دریافت محتوا جلسات نظری،
دریافت جلسات حل تمرین
‼️تمام محتوای این دوره کاملا رایگان می باشد.
به کانال ما مراجعه کنید: نوروسینتکس
ارتباط با ما: @neurosyntax_bot
در طی این دوره با سیگنال های الکتریکی مغز آشنا خواهید شد و روش های تحلیل و تفسیر سیگنال را "از پایه" خواهید آموخت. کارگاه شامل دو نوع جلسات نظریه و حل تمرین است. در نظریه، شما با مبانی فیزیولوژیک سیگنال های مغزی آشنا خواهید شد، نوروبیولوژی چگونگی تشکیل نوسانات را خواهید آموخت و با مبانی روش های تحلیل سیگنال آشنا خواهید شد. در جلسات حل تمرین، در متلب، کدهای تحلیل سیگنال را مینویسیم. در این جلسات بدنه اصلی کدها به صورت خط به خط بررسی میشود تا درک مناسبی از کدنویسی تحلیل سیگنال های مغزی ایجاد شود.
◻️سر فصل کامل این دوره را میتوانید از این لینک دریافت کنید: سیلابس دوره
◻️پیش نیاز این دوره آشنایی با مقدمات برنامه نویسی متلب است که میتوانید آن را به صورت رایگان از کانال ما دریافت کنید: کانال سوفی فیلیا - کافیست هشتگ #matlab و #saman را در این کانال جستجو کنید. (مقدمات برنامه نویسی پایتون را نیز میتوانید به صورت رایگان از همین کانال با هشتگ #python و #saman دریافت کنید.)
◻️تمامی ویدیو ها، اسلاید ها و کدهای متلب مربوط به جلسات 1 تا 12 دوره دینامیک مغز را میتوانید به صورت رایگان از کانال نوروسینتکس دریافت کنید:
دریافت محتوا جلسات نظری،
دریافت جلسات حل تمرین
‼️تمام محتوای این دوره کاملا رایگان می باشد.
به کانال ما مراجعه کنید: نوروسینتکس
ارتباط با ما: @neurosyntax_bot
اگر در گروه هایی هستید که فکر میکنید به محتوای کارگاه دینامیک مغز علاقه مند خواهند بود میتونید دو پیام بالا رو در گروه ها فوروارد کنید و با این کار در گسترش محتوای این کانال به ما کمک کنید.