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< Back Peripheral Psychophysiology Our lab is also equipped with a Physio 16 Package from EGI that integrates with our high-density EEG system from EGI. With this system we can seamlessly collect respiration, ECG, Sp02 and other types of peripheral psychophysiological data. The Life Events Checklist (LEC-5) is a standardized questionnaire that gathers information about traumatic life experiences. The LEC-5 provides an insight into one's life experiences and gives context to HRV and EEG data. LEC-5 The Pittsburgh Sleep Quality Index (PSQI) is used to determine the quality of your sleep in the last month. It is no secret that poor sleep is related to stress. The PSQI provides valuable information to our research team. PSQI The Patient Health Questionnaire-9 (PHQ-9) is used to determine the Major Depression Disorder (MDD) symptoms. Depression symptoms can help explain interoceptive data. PHQ-9 The Profile of Mood States (POMS) questionnaire takes record of the participant's mood over the past 7 days. It looks at mood states like anger, fear, depression, etc. POMS The Mini Screen is a survey that screens for psychiatric disorders. This includes eating disorders, depression, obsessive compulsive disorder, PTSD, and other. Mini Screen The Mini Screen Manual explains the results of the Mini Screen. Mini Screen The Generalized Anxiety Disorder-7 (GAD-7) questionnaire is used to determine the Anxiety symptoms. Anxiety is linked to other psychological disorders like PTSD. Anxiety symptoms can help explain interoceptive data. GAD-7 The Connor-Davidson Resilience Scale (CD-RISC) measures resilience. This short survey attempts to gauge how well one responds to stress and adversity. CD-RISC

< Back Eye Tracking The eyes are the window to the mind. In many circumstances, we utilize our vision to focus our attention on an object; therefore, we can learn a lot about what people attend to by tracking their eyes. The Brain Hygiene Lab is equipped with a Tobii Pro Spectrum 150 Eye-tracking system, with Tobii Pro Lab software and Eprime integration. The Life Events Checklist (LEC-5) is a standardized questionnaire that gathers information about traumatic life experiences. The LEC-5 provides an insight into one's life experiences and gives context to HRV and EEG data. LEC-5 The Pittsburgh Sleep Quality Index (PSQI) is used to determine the quality of your sleep in the last month. It is no secret that poor sleep is related to stress. The PSQI provides valuable information to our research team. PSQI The Patient Health Questionnaire-9 (PHQ-9) is used to determine the Major Depression Disorder (MDD) symptoms. Depression symptoms can help explain interoceptive data. PHQ-9 The Profile of Mood States (POMS) questionnaire takes record of the participant's mood over the past 7 days. It looks at mood states like anger, fear, depression, etc. POMS The Mini Screen is a survey that screens for psychiatric disorders. This includes eating disorders, depression, obsessive compulsive disorder, PTSD, and other. Mini Screen The Mini Screen Manual explains the results of the Mini Screen. Mini Screen The Generalized Anxiety Disorder-7 (GAD-7) questionnaire is used to determine the Anxiety symptoms. Anxiety is linked to other psychological disorders like PTSD. Anxiety symptoms can help explain interoceptive data. GAD-7 The Connor-Davidson Resilience Scale (CD-RISC) measures resilience. This short survey attempts to gauge how well one responds to stress and adversity. CD-RISC

< Back Level 1 The Big-Picture and Information This section contains more information about Heart Rate-Variability (HRV), Resilience, EEG, and neurophysiological measurement. After reading about the following topics, please continue to Level 2 for more detailed information. HRV Mindfulness Resilience A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health HRV Modifying Resilience Mechanisms in At-Risk Individuals: A Controlled Study of Mindfulness Training in Marines Preparing for Deployment Mindfulness A Neuroscience Approach to Optimizing Brain Resources for Human Performance in Extreme Environments Resilience In pursuit of resilience: stress, epigenetics, and brain plasticity Resilience Previous Next

< Back Level 0 Basic Information and Layout These are the main projects, physiological systems, methods, and topics relevent to the Thom Lab's research, as well as the manuscripts currently being worked on. Previous Next

EEG Pipeline BESA - Updated 2023 1 Collect Data There are hundreds of sites with free, downloadable EEG data that can be imported into BESA. Next 2 Import Data After choosing a dataset, isolate the raw EEG data from the metadata and other contextual information about the experiment. Next 3 Re-reference Data You need to convert the data to an average reference. Next 4 Set Channel Locations Select the files that specifies the channel locations. Next 5 Delete or Interpolate Bad Channels You may want to delete channels that are too noisy, such as the ones around the face. Next 6 Filtering We use filters to take out signals that are definitley not brain data. You need to filter out the very low (<0.01-0.1 Hz) and very high frequencies (>50-100 Hz), as well as the 60 Hz line noise from the ambient electrical wires. Next 7 Run ICA ICA is used to separate out the data into its various signal sources, which are both neural and non-neural. Next 8 Epoching For each stimulus, we want to extract a segment of data just before and just after the stimulus. Next 9 Baseline Removal The signal recorded just before the stimulus is considered the baseline. This is comprised of neural activity that is not in response to the stimulus as well as noise. This baseline is subtracted from the entire epoch, leaving the neural activity that occured in response to the stimulus. Next 10 Component Rejection Once you've run ICA on a dataset, it is possible to reject non-neural signal sources. This section explains how to do that and explains the Sasica plug in. Next 11 Sorting by Stimulus Type Separating the data for each stimulus type into its own file. Next 12 Averaging Trials Separating the data for each stimulus type into its own file. Next 13 Check the Data Head Plots Plot the head maps for the time ranges of interest ​ Download Waveforms Plot the waveforms of the averaged data ​ Download Grand Averaging Averaging all of the data of one type together (such as all face data / scene data) Download 14 Analyze the Data Average Amplitudes Wavelet Analysis Fourier Transforms Phase Coherence Download Resources Filename Key Download Automation Scripts Download EEGLAB Scripts Download Other Download

EEG Pipeline BESA - Updated 2023 1 Collect Data There are hundreds of sites with free, downloadable EEG data that can be imported into BESA. Next 2 Import Data After choosing a dataset, isolate the raw EEG data from the metadata and other contextual information about the experiment. Next 3 Re-reference Data You need to convert the data to an average reference. Next 4 Set Channel Locations Select the files that specifies the channel locations. Next 5 Delete or Interpolate Bad Channels You may want to delete channels that are too noisy, such as the ones around the face. Next 6 Filtering We use filters to take out signals that are definitley not brain data. You need to filter out the very low (<0.01-0.1 Hz) and very high frequencies (>50-100 Hz), as well as the 60 Hz line noise from the ambient electrical wires. Next 7 Run ICA ICA is used to separate out the data into its various signal sources, which are both neural and non-neural. Next 8 Epoching For each stimulus, we want to extract a segment of data just before and just after the stimulus. Next 9 Baseline Removal The signal recorded just before the stimulus is considered the baseline. This is comprised of neural activity that is not in response to the stimulus as well as noise. This baseline is subtracted from the entire epoch, leaving the neural activity that occured in response to the stimulus. Next 10 Component Rejection Once you've run ICA on a dataset, it is possible to reject non-neural signal sources. This section explains how to do that and explains the Sasica plug in. Next 11 Sorting by Stimulus Type Separating the data for each stimulus type into its own file. Next 12 Averaging Trials Separating the data for each stimulus type into its own file. Next 13 Check the Data Head Plots Plot the head maps for the time ranges of interest ​ Download Waveforms Plot the waveforms of the averaged data ​ Download Grand Averaging Averaging all of the data of one type together (such as all face data / scene data) Download 14 Analyze the Data Average Amplitudes Wavelet Analysis Fourier Transforms Phase Coherence Download Resources Filename Key Download Automation Scripts Download EEGLAB Scripts Download Other Download

< Back Level 2 Textbook Chapters, Review Articles, and Specific Information This section contains detailed information about neurophysiology, resilience, and various topics and physiological systems that our research focuses on. Methods Physiology Topics An Introduction To The Event-Related Potential Technique EEG Heart rate variability Standards of measurement, physiological interpretation, and clinical use HRV Effects of Chronic Exercise on Feelings of Energy and Fatigue: A Quantitative Synthesis Meta Effects of incremental exercise on cerebral oxygenation measured by near-infrared spectroscopy: A systematic review Meta The Effect of Exercise Training on Anxiety Symptoms Among Patients Meta A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology NIRS A wearable multi-channel fNIRS system for brain imaging in freely moving subjects NIRS Implicit emotion regulation in the presence of threat: Neural and autonomic correlates NIRS Time domain functional NIRS imaging for human brain mapping NIRS Autonomic Nervous System Diagram ANS Ch 1: Getting Inside and Getting Around Circuits Ch 4: Disorder of the corticolimbic circuit Circuits Previous Next

EEG Pipeline BESA - Updated 2023 1 Collect Data There are hundreds of sites with free, downloadable EEG data that can be imported into BESA. Next 2 Import Data After choosing a dataset, isolate the raw EEG data from the metadata and other contextual information about the experiment. Next 3 Re-reference Data You need to convert the data to an average reference. Next 4 Set Channel Locations Select the files that specifies the channel locations. Next 5 Delete or Interpolate Bad Channels You may want to delete channels that are too noisy, such as the ones around the face. Next 6 Filtering We use filters to take out signals that are definitley not brain data. You need to filter out the very low (<0.01-0.1 Hz) and very high frequencies (>50-100 Hz), as well as the 60 Hz line noise from the ambient electrical wires. Next 7 Run ICA ICA is used to separate out the data into its various signal sources, which are both neural and non-neural. Next 8 Epoching For each stimulus, we want to extract a segment of data just before and just after the stimulus. Next 9 Baseline Removal The signal recorded just before the stimulus is considered the baseline. This is comprised of neural activity that is not in response to the stimulus as well as noise. This baseline is subtracted from the entire epoch, leaving the neural activity that occured in response to the stimulus. Next 10 Component Rejection Once you've run ICA on a dataset, it is possible to reject non-neural signal sources. This section explains how to do that and explains the Sasica plug in. Next 11 Sorting by Stimulus Type Separating the data for each stimulus type into its own file. Next 12 Averaging Trials Separating the data for each stimulus type into its own file. Next 13 Check the Data Head Plots Plot the head maps for the time ranges of interest ​ Download Waveforms Plot the waveforms of the averaged data ​ Download Grand Averaging Averaging all of the data of one type together (such as all face data / scene data) Download 14 Analyze the Data Average Amplitudes Wavelet Analysis Fourier Transforms Phase Coherence Download Resources Filename Key Download Automation Scripts Download EEGLAB Scripts Download Other Download

EEG Pipeline BESA - Updated 2023 1 Collect Data There are hundreds of sites with free, downloadable EEG data that can be imported into BESA. Next 2 Import Data After choosing a dataset, isolate the raw EEG data from the metadata and other contextual information about the experiment. Next 3 Re-reference Data You need to convert the data to an average reference. Next 4 Set Channel Locations Select the files that specifies the channel locations. Next 5 Delete or Interpolate Bad Channels You may want to delete channels that are too noisy, such as the ones around the face. Next 6 Filtering We use filters to take out signals that are definitley not brain data. You need to filter out the very low (<0.01-0.1 Hz) and very high frequencies (>50-100 Hz), as well as the 60 Hz line noise from the ambient electrical wires. Next 7 Run ICA ICA is used to separate out the data into its various signal sources, which are both neural and non-neural. Next 8 Epoching For each stimulus, we want to extract a segment of data just before and just after the stimulus. Next 9 Baseline Removal The signal recorded just before the stimulus is considered the baseline. This is comprised of neural activity that is not in response to the stimulus as well as noise. This baseline is subtracted from the entire epoch, leaving the neural activity that occured in response to the stimulus. Next 10 Component Rejection Once you've run ICA on a dataset, it is possible to reject non-neural signal sources. This section explains how to do that and explains the Sasica plug in. Next 11 Sorting by Stimulus Type Separating the data for each stimulus type into its own file. Next 12 Averaging Trials Separating the data for each stimulus type into its own file. Next 13 Check the Data Head Plots Plot the head maps for the time ranges of interest ​ Download Waveforms Plot the waveforms of the averaged data ​ Download Grand Averaging Averaging all of the data of one type together (such as all face data / scene data) Download 14 Analyze the Data Average Amplitudes Wavelet Analysis Fourier Transforms Phase Coherence Download Resources Filename Key Download Automation Scripts Download EEGLAB Scripts Download Other Download

EEG Pipeline BESA - Updated 2023 1 Collect Data There are hundreds of sites with free, downloadable EEG data that can be imported into BESA. Next 2 Import Data After choosing a dataset, isolate the raw EEG data from the metadata and other contextual information about the experiment. Next 3 Re-reference Data You need to convert the data to an average reference. Next 4 Set Channel Locations Select the files that specifies the channel locations. Next 5 Delete or Interpolate Bad Channels You may want to delete channels that are too noisy, such as the ones around the face. Next 6 Filtering We use filters to take out signals that are definitley not brain data. You need to filter out the very low (<0.01-0.1 Hz) and very high frequencies (>50-100 Hz), as well as the 60 Hz line noise from the ambient electrical wires. Next 7 Run ICA ICA is used to separate out the data into its various signal sources, which are both neural and non-neural. Next 8 Epoching For each stimulus, we want to extract a segment of data just before and just after the stimulus. Next 9 Baseline Removal The signal recorded just before the stimulus is considered the baseline. This is comprised of neural activity that is not in response to the stimulus as well as noise. This baseline is subtracted from the entire epoch, leaving the neural activity that occured in response to the stimulus. Next 10 Component Rejection Once you've run ICA on a dataset, it is possible to reject non-neural signal sources. This section explains how to do that and explains the Sasica plug in. Next 11 Sorting by Stimulus Type Separating the data for each stimulus type into its own file. Next 12 Averaging Trials Separating the data for each stimulus type into its own file. Next 13 Check the Data Head Plots Plot the head maps for the time ranges of interest ​ Download Waveforms Plot the waveforms of the averaged data ​ Download Grand Averaging Averaging all of the data of one type together (such as all face data / scene data) Download 14 Analyze the Data Average Amplitudes Wavelet Analysis Fourier Transforms Phase Coherence Download Resources Filename Key Download Automation Scripts Download EEGLAB Scripts Download Other Download

< Back EEG The brain is made up of a vast array of neural networks that can be measured with electroencephalography (EEG). From resting-state activity, to the detection of emotional processing and cognitive function, EEG literally provides a window into the brain. The Brain Hygiene Lab uses a high-density EEG system designed and manufactured by Electrical Geodesic, Inc. The Life Events Checklist (LEC-5) is a standardized questionnaire that gathers information about traumatic life experiences. The LEC-5 provides an insight into one's life experiences and gives context to HRV and EEG data. LEC-5 The Pittsburgh Sleep Quality Index (PSQI) is used to determine the quality of your sleep in the last month. It is no secret that poor sleep is related to stress. The PSQI provides valuable information to our research team. PSQI The Patient Health Questionnaire-9 (PHQ-9) is used to determine the Major Depression Disorder (MDD) symptoms. Depression symptoms can help explain interoceptive data. PHQ-9 The Profile of Mood States (POMS) questionnaire takes record of the participant's mood over the past 7 days. It looks at mood states like anger, fear, depression, etc. POMS The Mini Screen is a survey that screens for psychiatric disorders. This includes eating disorders, depression, obsessive compulsive disorder, PTSD, and other. Mini Screen The Mini Screen Manual explains the results of the Mini Screen. Mini Screen The Generalized Anxiety Disorder-7 (GAD-7) questionnaire is used to determine the Anxiety symptoms. Anxiety is linked to other psychological disorders like PTSD. Anxiety symptoms can help explain interoceptive data. GAD-7 The Connor-Davidson Resilience Scale (CD-RISC) measures resilience. This short survey attempts to gauge how well one responds to stress and adversity. CD-RISC

Introduction Level 0 is the basic layout of the Brain Hygiene Lab. Level 1 contains broad information about our focuses. Level 2 contains pertinent review articles, textbook chapters, and information about the methods used to gather data, as well as other important information. Please review these pages to gain a greater understanding of the research being conducted by the Brain Hygiene Lab. Level 0 Level 1 Level 2