matlab custom-made functions Search Results


matlab statistics toolbox  (MathWorks Inc)
96
MathWorks Inc matlab statistics toolbox
Matlab Statistics Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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machine learning toolbox  (MathWorks Inc)
96
MathWorks Inc machine learning toolbox
Machine Learning Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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r2020a signal processing toolbox  (MathWorks Inc)
98
MathWorks Inc r2020a signal processing toolbox
R2020a Signal Processing Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 98/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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custom-made, pressure-operated pump  (Sensirion ag)
90
Sensirion ag custom-made, pressure-operated pump
Custom Made, Pressure Operated Pump, supplied by Sensirion ag, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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eeg feature extraction toolbox  (MathWorks Inc)
96
MathWorks Inc eeg feature extraction toolbox
Eeg Feature Extraction Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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hdeeg data processing and analysis functions  (electrical geodesics)
90
electrical geodesics hdeeg data processing and analysis functions
VWM task design and SSVEP frequency tagging technique. (A) An example trial sequence for the full-report paradigm tested. During fixation, four black squares were presented in each quadrant (600 ms) and followed by an encoding period (1000 ms). During encoding, each stimulus flickered at a unique frequency (3 Hz, 5 Hz, 12 Hz, and 20 Hz) placed one per quadrant. Next, a maintenance period (1000 ms) was followed by retrieval. There were two retrieval task types: (i) simultaneous and (ii) sequential. During simultaneous recall, participants were instructed to choose and place the four encoded polygons in the location that they remembered. During sequential recall, participants were randomly designated one location at a time to place each polygon. After the participant placed the shape, the bounding black square turned green to indicate that the choice had been registered and a new black square appeared at another location. In both recall tasks, all the selected shapes remained visible within the bounding box until the conclusion of the trial. Responses were unspeeded. (B) During encoding, <t>hdEEG</t> <t>data</t> was collected (artificial waveform data). (C) Individual trials were sorted by accuracy: the number of correct trials for each frequency was matched with the number of incorrect trials. A fast Fourier transform was applied to the raw electrical signal, averaged across electrodes, and individual component frequency amplitudes were extracted from the FFT data corresponding to the flicker frequency of each stimuli for both correct and incorrect trials. The data presented here are hypothesized and are not actual results.
Hdeeg Data Processing And Analysis Functions, supplied by electrical geodesics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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prism (v.9.4.1  (GraphPad Software Inc)
90
GraphPad Software Inc prism (v.9.4.1
VWM task design and SSVEP frequency tagging technique. (A) An example trial sequence for the full-report paradigm tested. During fixation, four black squares were presented in each quadrant (600 ms) and followed by an encoding period (1000 ms). During encoding, each stimulus flickered at a unique frequency (3 Hz, 5 Hz, 12 Hz, and 20 Hz) placed one per quadrant. Next, a maintenance period (1000 ms) was followed by retrieval. There were two retrieval task types: (i) simultaneous and (ii) sequential. During simultaneous recall, participants were instructed to choose and place the four encoded polygons in the location that they remembered. During sequential recall, participants were randomly designated one location at a time to place each polygon. After the participant placed the shape, the bounding black square turned green to indicate that the choice had been registered and a new black square appeared at another location. In both recall tasks, all the selected shapes remained visible within the bounding box until the conclusion of the trial. Responses were unspeeded. (B) During encoding, <t>hdEEG</t> <t>data</t> was collected (artificial waveform data). (C) Individual trials were sorted by accuracy: the number of correct trials for each frequency was matched with the number of incorrect trials. A fast Fourier transform was applied to the raw electrical signal, averaged across electrodes, and individual component frequency amplitudes were extracted from the FFT data corresponding to the flicker frequency of each stimuli for both correct and incorrect trials. The data presented here are hypothesized and are not actual results.
Prism (V.9.4.1, supplied by GraphPad Software Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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prism (v.9.4.1 - by Bioz Stars, 2026-06
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zen blue 2.5  (Carl Zeiss)
90
Carl Zeiss zen blue 2.5
VWM task design and SSVEP frequency tagging technique. (A) An example trial sequence for the full-report paradigm tested. During fixation, four black squares were presented in each quadrant (600 ms) and followed by an encoding period (1000 ms). During encoding, each stimulus flickered at a unique frequency (3 Hz, 5 Hz, 12 Hz, and 20 Hz) placed one per quadrant. Next, a maintenance period (1000 ms) was followed by retrieval. There were two retrieval task types: (i) simultaneous and (ii) sequential. During simultaneous recall, participants were instructed to choose and place the four encoded polygons in the location that they remembered. During sequential recall, participants were randomly designated one location at a time to place each polygon. After the participant placed the shape, the bounding black square turned green to indicate that the choice had been registered and a new black square appeared at another location. In both recall tasks, all the selected shapes remained visible within the bounding box until the conclusion of the trial. Responses were unspeeded. (B) During encoding, <t>hdEEG</t> <t>data</t> was collected (artificial waveform data). (C) Individual trials were sorted by accuracy: the number of correct trials for each frequency was matched with the number of incorrect trials. A fast Fourier transform was applied to the raw electrical signal, averaged across electrodes, and individual component frequency amplitudes were extracted from the FFT data corresponding to the flicker frequency of each stimuli for both correct and incorrect trials. The data presented here are hypothesized and are not actual results.
Zen Blue 2.5, supplied by Carl Zeiss, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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spike2  (plexon inc)
90
plexon inc spike2
VWM task design and SSVEP frequency tagging technique. (A) An example trial sequence for the full-report paradigm tested. During fixation, four black squares were presented in each quadrant (600 ms) and followed by an encoding period (1000 ms). During encoding, each stimulus flickered at a unique frequency (3 Hz, 5 Hz, 12 Hz, and 20 Hz) placed one per quadrant. Next, a maintenance period (1000 ms) was followed by retrieval. There were two retrieval task types: (i) simultaneous and (ii) sequential. During simultaneous recall, participants were instructed to choose and place the four encoded polygons in the location that they remembered. During sequential recall, participants were randomly designated one location at a time to place each polygon. After the participant placed the shape, the bounding black square turned green to indicate that the choice had been registered and a new black square appeared at another location. In both recall tasks, all the selected shapes remained visible within the bounding box until the conclusion of the trial. Responses were unspeeded. (B) During encoding, <t>hdEEG</t> <t>data</t> was collected (artificial waveform data). (C) Individual trials were sorted by accuracy: the number of correct trials for each frequency was matched with the number of incorrect trials. A fast Fourier transform was applied to the raw electrical signal, averaged across electrodes, and individual component frequency amplitudes were extracted from the FFT data corresponding to the flicker frequency of each stimuli for both correct and incorrect trials. The data presented here are hypothesized and are not actual results.
Spike2, supplied by plexon inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pat neurofeedback device  (NeuroTek Corporation)
90
NeuroTek Corporation pat neurofeedback device
Paired sample t -test of the last vs. first <t> neurofeedback </t> session in 18 subjects .
Pat Neurofeedback Device, supplied by NeuroTek Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pat neurofeedback device - by Bioz Stars, 2026-06
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facsdiva  (Becton Dickinson)
90
Becton Dickinson facsdiva
Paired sample t -test of the last vs. first <t> neurofeedback </t> session in 18 subjects .
Facsdiva, supplied by Becton Dickinson, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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facsdiva - by Bioz Stars, 2026-06
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graphpad prism 7  (GraphPad Software Inc)
90
GraphPad Software Inc graphpad prism 7
Paired sample t -test of the last vs. first <t> neurofeedback </t> session in 18 subjects .
Graphpad Prism 7, supplied by GraphPad Software Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


VWM task design and SSVEP frequency tagging technique. (A) An example trial sequence for the full-report paradigm tested. During fixation, four black squares were presented in each quadrant (600 ms) and followed by an encoding period (1000 ms). During encoding, each stimulus flickered at a unique frequency (3 Hz, 5 Hz, 12 Hz, and 20 Hz) placed one per quadrant. Next, a maintenance period (1000 ms) was followed by retrieval. There were two retrieval task types: (i) simultaneous and (ii) sequential. During simultaneous recall, participants were instructed to choose and place the four encoded polygons in the location that they remembered. During sequential recall, participants were randomly designated one location at a time to place each polygon. After the participant placed the shape, the bounding black square turned green to indicate that the choice had been registered and a new black square appeared at another location. In both recall tasks, all the selected shapes remained visible within the bounding box until the conclusion of the trial. Responses were unspeeded. (B) During encoding, hdEEG data was collected (artificial waveform data). (C) Individual trials were sorted by accuracy: the number of correct trials for each frequency was matched with the number of incorrect trials. A fast Fourier transform was applied to the raw electrical signal, averaged across electrodes, and individual component frequency amplitudes were extracted from the FFT data corresponding to the flicker frequency of each stimuli for both correct and incorrect trials. The data presented here are hypothesized and are not actual results.

Journal: Cognitive, affective & behavioral neuroscience

Article Title: Electrophysiological correlates of encoding processes in a full-report visual working memory paradigm

doi: 10.3758/s13415-018-0574-8

Figure Lengend Snippet: VWM task design and SSVEP frequency tagging technique. (A) An example trial sequence for the full-report paradigm tested. During fixation, four black squares were presented in each quadrant (600 ms) and followed by an encoding period (1000 ms). During encoding, each stimulus flickered at a unique frequency (3 Hz, 5 Hz, 12 Hz, and 20 Hz) placed one per quadrant. Next, a maintenance period (1000 ms) was followed by retrieval. There were two retrieval task types: (i) simultaneous and (ii) sequential. During simultaneous recall, participants were instructed to choose and place the four encoded polygons in the location that they remembered. During sequential recall, participants were randomly designated one location at a time to place each polygon. After the participant placed the shape, the bounding black square turned green to indicate that the choice had been registered and a new black square appeared at another location. In both recall tasks, all the selected shapes remained visible within the bounding box until the conclusion of the trial. Responses were unspeeded. (B) During encoding, hdEEG data was collected (artificial waveform data). (C) Individual trials were sorted by accuracy: the number of correct trials for each frequency was matched with the number of incorrect trials. A fast Fourier transform was applied to the raw electrical signal, averaged across electrodes, and individual component frequency amplitudes were extracted from the FFT data corresponding to the flicker frequency of each stimuli for both correct and incorrect trials. The data presented here are hypothesized and are not actual results.

Article Snippet: 2.6 Electrophysiological data analysis 2.6.1 Preprocessing The hdEEG data were processed and analyzed using a combination of functions from the Net Station 5.0 software package (Electrical Geodesics, Inc., Eugene, OR, USA), Brainstorm software package ( Tadel et al. 2011 : http://neuroimage.usc.edu/brainstorm ), and custom-made Matlab scripts.

Techniques: Sequencing

Paired sample t -test of the last vs. first neurofeedback session in 18 subjects .

Journal: Frontiers in Human Neuroscience

Article Title: Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

doi: 10.3389/fnhum.2015.00723

Figure Lengend Snippet: Paired sample t -test of the last vs. first neurofeedback session in 18 subjects .

Article Snippet: The goal of this study was to conduct neurofeedback in children with ASD using the PAT neurofeedback device with the “Focus/Neureka!” (“ Focused Attention” index and “40 Hz-centered Gamma” index) training protocol of Peak Achievement Trainer (PAT) neurofeedback device (Neurotek, Goshen, KY) to investigate: relative changes in EEG bands (e.g., theta [4–8 Hz]) and sub-bands of interest (e.g., low beta [13–18 Hz], high beta [18–30 Hz]) and their ratios (e.g., theta/low beta, etc.) throughout the entire 18 session long course of neurofeedback training in ASD, and during each individual training session using custom-made Matlab application, how gamma power and EEG bands power ratios are changing during individual sessions and between sessions within the course of neurofeedback training in high functioning individuals with ASD, and whether there are any correlation between EEG measures of interest (i.e., relative gamma power, theta/beta ratio) and neurofeedback training indices such as “Focused Attention” index and “40 Hz-centered Gamma” index (Cowan and Albers, ).

Techniques:

Linear regression of the theta/low beta ratio over 18 sessions of neurofeedback training in 18 children with ASD ( R = 0.666, y = −0.079x + 9.49, t = −3.57, p = 0.003) .

Journal: Frontiers in Human Neuroscience

Article Title: Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

doi: 10.3389/fnhum.2015.00723

Figure Lengend Snippet: Linear regression of the theta/low beta ratio over 18 sessions of neurofeedback training in 18 children with ASD ( R = 0.666, y = −0.079x + 9.49, t = −3.57, p = 0.003) .

Article Snippet: The goal of this study was to conduct neurofeedback in children with ASD using the PAT neurofeedback device with the “Focus/Neureka!” (“ Focused Attention” index and “40 Hz-centered Gamma” index) training protocol of Peak Achievement Trainer (PAT) neurofeedback device (Neurotek, Goshen, KY) to investigate: relative changes in EEG bands (e.g., theta [4–8 Hz]) and sub-bands of interest (e.g., low beta [13–18 Hz], high beta [18–30 Hz]) and their ratios (e.g., theta/low beta, etc.) throughout the entire 18 session long course of neurofeedback training in ASD, and during each individual training session using custom-made Matlab application, how gamma power and EEG bands power ratios are changing during individual sessions and between sessions within the course of neurofeedback training in high functioning individuals with ASD, and whether there are any correlation between EEG measures of interest (i.e., relative gamma power, theta/beta ratio) and neurofeedback training indices such as “Focused Attention” index and “40 Hz-centered Gamma” index (Cowan and Albers, ).

Techniques:

Linear regression of the theta/high beta ratio over 18 sessions of neurofeedback training in 18 children with ASD [ R = 0.708, y = −0.088x + 6.24, t (17) = −4.01, p = 0.001] .

Journal: Frontiers in Human Neuroscience

Article Title: Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

doi: 10.3389/fnhum.2015.00723

Figure Lengend Snippet: Linear regression of the theta/high beta ratio over 18 sessions of neurofeedback training in 18 children with ASD [ R = 0.708, y = −0.088x + 6.24, t (17) = −4.01, p = 0.001] .

Article Snippet: The goal of this study was to conduct neurofeedback in children with ASD using the PAT neurofeedback device with the “Focus/Neureka!” (“ Focused Attention” index and “40 Hz-centered Gamma” index) training protocol of Peak Achievement Trainer (PAT) neurofeedback device (Neurotek, Goshen, KY) to investigate: relative changes in EEG bands (e.g., theta [4–8 Hz]) and sub-bands of interest (e.g., low beta [13–18 Hz], high beta [18–30 Hz]) and their ratios (e.g., theta/low beta, etc.) throughout the entire 18 session long course of neurofeedback training in ASD, and during each individual training session using custom-made Matlab application, how gamma power and EEG bands power ratios are changing during individual sessions and between sessions within the course of neurofeedback training in high functioning individuals with ASD, and whether there are any correlation between EEG measures of interest (i.e., relative gamma power, theta/beta ratio) and neurofeedback training indices such as “Focused Attention” index and “40 Hz-centered Gamma” index (Cowan and Albers, ).

Techniques:

Linear regression of the “Focused Attention” index during 20 min long neurofeedback session (mean for all subjects across all sessions [ R = 0.576, y = 0.063x + 70.64 c.u., t (19) = 2.99, p = 0.008] .

Journal: Frontiers in Human Neuroscience

Article Title: Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

doi: 10.3389/fnhum.2015.00723

Figure Lengend Snippet: Linear regression of the “Focused Attention” index during 20 min long neurofeedback session (mean for all subjects across all sessions [ R = 0.576, y = 0.063x + 70.64 c.u., t (19) = 2.99, p = 0.008] .

Article Snippet: The goal of this study was to conduct neurofeedback in children with ASD using the PAT neurofeedback device with the “Focus/Neureka!” (“ Focused Attention” index and “40 Hz-centered Gamma” index) training protocol of Peak Achievement Trainer (PAT) neurofeedback device (Neurotek, Goshen, KY) to investigate: relative changes in EEG bands (e.g., theta [4–8 Hz]) and sub-bands of interest (e.g., low beta [13–18 Hz], high beta [18–30 Hz]) and their ratios (e.g., theta/low beta, etc.) throughout the entire 18 session long course of neurofeedback training in ASD, and during each individual training session using custom-made Matlab application, how gamma power and EEG bands power ratios are changing during individual sessions and between sessions within the course of neurofeedback training in high functioning individuals with ASD, and whether there are any correlation between EEG measures of interest (i.e., relative gamma power, theta/beta ratio) and neurofeedback training indices such as “Focused Attention” index and “40 Hz-centered Gamma” index (Cowan and Albers, ).

Techniques:

Correlation of the theta/beta with the “Focused Attention” index during 20 min of neurofeedback training (across all sessions, r = −0.70, p = 0.001) .

Journal: Frontiers in Human Neuroscience

Article Title: Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

doi: 10.3389/fnhum.2015.00723

Figure Lengend Snippet: Correlation of the theta/beta with the “Focused Attention” index during 20 min of neurofeedback training (across all sessions, r = −0.70, p = 0.001) .

Article Snippet: The goal of this study was to conduct neurofeedback in children with ASD using the PAT neurofeedback device with the “Focus/Neureka!” (“ Focused Attention” index and “40 Hz-centered Gamma” index) training protocol of Peak Achievement Trainer (PAT) neurofeedback device (Neurotek, Goshen, KY) to investigate: relative changes in EEG bands (e.g., theta [4–8 Hz]) and sub-bands of interest (e.g., low beta [13–18 Hz], high beta [18–30 Hz]) and their ratios (e.g., theta/low beta, etc.) throughout the entire 18 session long course of neurofeedback training in ASD, and during each individual training session using custom-made Matlab application, how gamma power and EEG bands power ratios are changing during individual sessions and between sessions within the course of neurofeedback training in high functioning individuals with ASD, and whether there are any correlation between EEG measures of interest (i.e., relative gamma power, theta/beta ratio) and neurofeedback training indices such as “Focused Attention” index and “40 Hz-centered Gamma” index (Cowan and Albers, ).

Techniques:

Linear regression of the relative power of Gamma band over 18 sessions of neurofeedback training in 18 children with ASD ( R = 0.491, y = 0.022x + 1.45%, t = 2.25, p = 0.039) .

Journal: Frontiers in Human Neuroscience

Article Title: Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder

doi: 10.3389/fnhum.2015.00723

Figure Lengend Snippet: Linear regression of the relative power of Gamma band over 18 sessions of neurofeedback training in 18 children with ASD ( R = 0.491, y = 0.022x + 1.45%, t = 2.25, p = 0.039) .

Article Snippet: The goal of this study was to conduct neurofeedback in children with ASD using the PAT neurofeedback device with the “Focus/Neureka!” (“ Focused Attention” index and “40 Hz-centered Gamma” index) training protocol of Peak Achievement Trainer (PAT) neurofeedback device (Neurotek, Goshen, KY) to investigate: relative changes in EEG bands (e.g., theta [4–8 Hz]) and sub-bands of interest (e.g., low beta [13–18 Hz], high beta [18–30 Hz]) and their ratios (e.g., theta/low beta, etc.) throughout the entire 18 session long course of neurofeedback training in ASD, and during each individual training session using custom-made Matlab application, how gamma power and EEG bands power ratios are changing during individual sessions and between sessions within the course of neurofeedback training in high functioning individuals with ASD, and whether there are any correlation between EEG measures of interest (i.e., relative gamma power, theta/beta ratio) and neurofeedback training indices such as “Focused Attention” index and “40 Hz-centered Gamma” index (Cowan and Albers, ).

Techniques: