Outcome
Type |
Measure |
Description |
Time frame |
Safety issue |
Primary |
Experiment 1.a. Behavioral accuracy |
Mean percentage of responses that are correct |
3 hours |
|
Primary |
Experiment 1.a. Reaction time |
The time, measured in milliseconds, that it takes a subject to press the "match" or "nonmatch" button after the memory probe appears. |
3 hours |
|
Primary |
Experiment 1.a. Changes in multivariate pattern classification of electroencephalography data in response to prioritization cues and in response to pulses of transcranial magnetic stimulation. |
Multivariate pattern classification is a method from machine learning that can be used to assess the neural representation of stimulus information in electroencephalographic signal (i.e., to "decode" the signal). The outcome measure is how decoder performance will change as a function of a stimulus's priority status, and in response to a pulse of transcranial magnetic stimulation. Note that this method entails analysis of the broadband electroencephalographic signal (bandpass filtered from 1-100Hz) in each of two formats: time domain, and spectrally transformed. The spectrally transformed analysis does not entail the separate analysis of discrete functionally defined frequency bands (e.g., alpha, beta, etc.) Rather, spectral power values at every integer frequency from 2 to 20 Hz and every other integer from 22 to 50 Hz - yielding 34 frequencies per channel - are used as features in the analysis. |
3 hours |
|
Primary |
Experiment 1.a. Spatially distributed phase coupling extraction-identified components of the transcranial magnetic stimulation-evoked electroencephalography signal |
Spatially distributed phase coupling extraction-identified components of the transcranial magnetic stimulation-evoked electroencephalography signal will indicate whether the unattended memory item reactivation effect is carried by a de novo component in the electroencephalography signal or by a change in the power of one or more beta components that were present in the signal prior to the delivery of transcranial magnetic stimulation. Note that this method entails analysis of a spectral transformation of the broadband electroencephalographic signal that does not entail the separate analysis of discrete functionally defined frequency bands (e.g., alpha, beta, etc.) Rather, spectral power values at every integer frequency from 2 to 20 Hz and every other integer from frequency from 22 to 30 Hz - yielding 24 frequencies per channel - are entered into the analysis. No a priori assumptions are made about the frequency composition of components that the method will identify. |
3 hours |
|
Primary |
Experiment 2.a. The amplitude of multivariate inverted encoding model-reconstructions of stimulus location, derived from the transcranial magnetic stimulation-evoked response |
Multivariate inverted encoding modeling will be used to reconstruct the representation of stimulus locations from the electroencephalography data, and the strength of the representation will be compared across three stimulus conditions. Note that this method entails analysis of the broadband electroencephalographic signal (bandpass filtered from 1-100Hz) in each of two formats: time domain, and spectrally transformed. The spectrally transformed analysis does not entail the separate analysis of discrete functionally defined frequency bands (e.g., alpha, beta, etc.). Rather, spectral power values at every integer frequency from 2 to 20 Hz and at every other integer frequency from 22 to 50 Hz - yielding 34 frequencies per channel -- are used as features in the analysis. |
5 hours |
|
Primary |
Experiment 2.a. Spatially distributed phase coupling extraction-identified components of the transcranial magnetic stimulation-evoked electroencephalography signal |
Spatially distributed phase coupling extraction-identified components of the transcranial magnetic stimulation-evoked electroencephalography signal will indicate whether the unattended memory item reactivation effect is carried by a de novo component in the electroencephalographic signal, or by a change in the power of one or more components that were present in the signal prior to the delivery of transcranial magnetic stimulation. Note that this method entails analysis of a spectral transformation of the broadband electroencephalographic signal that does not entail the separate analysis of discrete functionally defined frequency bands (e.g., alpha, beta, etc.) Rather, spectral power values at every integer frequency from 2 to 20 Hz and every other integer from frequency from 22 to 30 Hz - yielding 24 frequencies per channel - are entered into the analysis. No a priori assumptions are made about the frequency composition of components that the method will identify. |
5 hours |
|
Primary |
Experiment 2.a. Correlation of the amplitude of multivariate inverted encoding model-reconstructions of the location of the unattended memory item with alpha band power. |
Correlation of the amplitude of multivariate inverted encoding model-reconstructions of the location of the unattended memory item, derived from the transcranial magnetic stimulation-evoked response, with alpha band power when targeting occipital cortex. |
5 hours |
|
Primary |
Experiment 2.a. Correlation of the amplitude of multivariate inverted encoding model-reconstructions of the location of the unattended memory item with beta-band power |
Correlation of the amplitude of multivariate inverted encoding model-reconstructions of the location of the unattended memory item, derived from the transcranial magnetic stimulation-evoked response, with beta-band power when targeting the intraparietal sulcus. |
5 hours |
|
Primary |
Experiment 3.a. Power in the alpha band of the EEG as a function of retinotopic location |
Power in the alpha band of the EEG as a function of retinotopic location |
4 hours |
|
Primary |
Experiment 3.a. Frequency in the alpha band of the EEG as a function of retinotopic location |
Frequency in the alpha band of the EEG as a function of retinotopic location |
4 hours |
|
Primary |
Experiment 3.a. Spatially distributed phase coupling extraction-identified components of the electroencephalography signal from signals corresponding to the attended location |
Spatially distributed phase coupling extraction-identified components of the electroencephalography signal from signals corresponding to the attended location to assess whether expectation-related shifts in alpha-band frequency are produced by a change in the frequency of one oscillator or by a change in the relative power of multiple oscillators. |
4 hours |
|
Primary |
Experiment 4.a. Behavioral accuracy assessed as mean percentage correct responses. |
Behavioral accuracy assessed as mean percentage correct responses. |
4 hours |
|
Primary |
Experiment 4.a. Reaction time assess as latency to press response button after onset of critical stimulus. |
Reaction time assess as latency to press response button after onset of critical stimulus. |
4 hours |
|
Primary |
Experiment 4.a. Power in the alpha band of the EEG as a function of retinotopic location |
Power in the alpha band of the EEG as a function of retinotopic location |
4 hours |
|
Primary |
Experiment 4.a. Frequency in the alpha band of the EEG as a function of retinotopic location |
Frequency in the alpha band of the EEG as a function of retinotopic location |
4 hours |
|
Primary |
Experiment 4.a. Spatially distributed phase coupling extraction-identified alpha-band components of the electroencephalography signal from signals corresponding to the attended location |
Spatially distributed phase coupling extraction-identified components of the electroencephalography signal from signals corresponding to the attended location to assess whether expectation-related shifts in alpha-band frequency are produced by a change in the frequency of one oscillator or by a change in the relative power of multiple oscillators. |
4 hours |
|
Primary |
Experiment 5. The amplitude of the "contralateral delay activity" (CDA) slow component of the EEG during the time period from 1000-1600 milliseconds after stimulus array onset. |
The amplitude of the CDA slow component of the EEG during the time period from 1000-1600 milliseconds after stimulus array onset. Note that this is an event-related potential analysis in which time-domain datas are trial averaged. The data are not spectrally transformed, so functionally defined frequency bands in the EEG (e.g., alpha, beta, etc.) are not relevant for this outcome. |
4 hours |
|
Primary |
Experiment 5. Multivariate inverted encoding modeling of the EEG signal to determine whether or not stimulus information is carried in this signal. |
Multivariate inverted encoding modeling of the EEG signal to determine whether or not stimulus information is carried in this signal. Note that this method entails analysis of the broadband electroencephalographic signal (bandpass filtered from 1-100Hz) in each of two formats: time domain, and spectrally transformed. The spectrally transformed analysis does not entail the separate analysis of discrete functionally defined frequency bands (e.g., alpha, beta, etc.). Rather, spectral power values at every integer frequency from 2 to 20 Hz and at every other integer frequency from 22 to 50 Hz - yielding 34 frequencies per channel -- are used as features in the analysis. |
4 hours |
|
Primary |
Experiment 6. Multivariate inverted encoding modeling of the EEG signal to determine whether or not contextual information is carried in this signal |
Multivariate inverted encoding modeling of the EEG signal to determine whether or not contextual information is carried in this signal. Note that this method entails analysis of the broadband electroencephalographic signal (bandpass filtered from 1-100Hz) in each of two formats: time domain, and spectrally transformed. The spectrally transformed analysis does not entail the separate analysis of discrete functionally defined frequency bands (e.g., alpha, beta, etc.). Rather, spectral power values at every integer frequency from 2 to 20 Hz and at every other integer frequency from 22 to 50 Hz - yielding 34 frequencies per channel -- are used as features in the analysis. |
4 hours |
|