homemade epidural electroencephalogram (eeg) electrodes  (PlasticsOne inc)

Journal: iScience

Article Title: Optical defocus affects differently ON and OFF visual pathways

doi: 10.1016/j.isci.2025.112500

Figure Lengend Snippet: Human cortical responses show a preference for small dark stimuli and large light surfaces (A) Human cortical responses to the onset of dark (blue) and light (red) checkerboards (0.5 s, midgray background) measured with electroencephalography. Each row illustrates a different observer (LB, MA, RN, EL) and each column a different check size (from 0.14 to 4.48°). (B) Size tuning for dark and light checkerboard stimuli calculated as the maximum minus minimum response between 50 and 200 ms after response onset (25–75 repeats). (C) Average ( n = 18) normalized cortical responses to dark (blue) and light stimuli (red) with different sizes (left). (D) Normalized dark minus light response. Top cartoons: small stimuli drive OFF pathways better (left) because light stimuli are more expanded by neuronal blur within the suppressive receptive field flanks. Large surfaces drive ON pathways better because OFF pathways have strong surround suppression.

Article Snippet: Custom dry electrode wireless electroencephalogram (EEG) system (DSI-7-Flex) , Wearable Sensing , N/A.

Techniques:

Journal: iScience

Article Title: Optical defocus affects differently ON and OFF visual pathways

doi: 10.1016/j.isci.2025.112500

Figure Lengend Snippet: Defocus tuning of ON and OFF pathways in human visual cortex (A) Human cortical responses to the onset of dark (blue) and light (red) checkerboards measured with electroencephalography under different levels of optical defocus induced with contact lenses (0.28° checks, 1.8 cpd). Each row illustrates an observer (LB, RN, EL, MA, AA, SP) and each column a level of optical defocus (from −5 to +5 diopters). We show the 6 out of 10 observers that best represent the spectrum of individual differences. (B) Defocus tuning for dark (blue) and light (red) stimuli calculated as the maximum minus minimum response between 50 and 200 ms after stimulus onset. (C) Average ( n = 10) normalized cortical responses to dark and light stimuli measured with different levels of optical defocus (top) and the normalized OFF minus ON response (magenta, bottom). Response amplitude is calculated as in (B). ∗∗ p < 0.01, ∗∗∗ p < 0.001 (Wilcoxon tests). Error bars indicate ±SEM.

Article Snippet: Custom dry electrode wireless electroencephalogram (EEG) system (DSI-7-Flex) , Wearable Sensing , N/A.

Techniques:

Journal: iScience

Article Title: Optical defocus affects differently ON and OFF visual pathways

doi: 10.1016/j.isci.2025.112500

Figure Lengend Snippet: Human cortical responses show a preference for small dark stimuli and large light surfaces (A) Human cortical responses to the onset of dark (blue) and light (red) checkerboards (0.5 s, midgray background) measured with electroencephalography. Each row illustrates a different observer (LB, MA, RN, EL) and each column a different check size (from 0.14 to 4.48°). (B) Size tuning for dark and light checkerboard stimuli calculated as the maximum minus minimum response between 50 and 200 ms after response onset (25–75 repeats). (C) Average ( n = 18) normalized cortical responses to dark (blue) and light stimuli (red) with different sizes (left). (D) Normalized dark minus light response. Top cartoons: small stimuli drive OFF pathways better (left) because light stimuli are more expanded by neuronal blur within the suppressive receptive field flanks. Large surfaces drive ON pathways better because OFF pathways have strong surround suppression.

Article Snippet: Human cortical responses were measured with a custom dry electrode wireless electroencephalogram (EEG) system (Wearable Sensing DSI-7-Flex, San Diego, CA) that allowed us to sample the human visual cortex with the same density than a 128-channel EEG.

Techniques:

Journal: iScience

Article Title: Optical defocus affects differently ON and OFF visual pathways

doi: 10.1016/j.isci.2025.112500

Figure Lengend Snippet: Defocus tuning of ON and OFF pathways in human visual cortex (A) Human cortical responses to the onset of dark (blue) and light (red) checkerboards measured with electroencephalography under different levels of optical defocus induced with contact lenses (0.28° checks, 1.8 cpd). Each row illustrates an observer (LB, RN, EL, MA, AA, SP) and each column a level of optical defocus (from −5 to +5 diopters). We show the 6 out of 10 observers that best represent the spectrum of individual differences. (B) Defocus tuning for dark (blue) and light (red) stimuli calculated as the maximum minus minimum response between 50 and 200 ms after stimulus onset. (C) Average ( n = 10) normalized cortical responses to dark and light stimuli measured with different levels of optical defocus (top) and the normalized OFF minus ON response (magenta, bottom). Response amplitude is calculated as in (B). ∗∗ p < 0.01, ∗∗∗ p < 0.001 (Wilcoxon tests). Error bars indicate ±SEM.

Article Snippet: Human cortical responses were measured with a custom dry electrode wireless electroencephalogram (EEG) system (Wearable Sensing DSI-7-Flex, San Diego, CA) that allowed us to sample the human visual cortex with the same density than a 128-channel EEG.

Techniques:

Journal: Brain and behavior

Article Title: The Feasibility and Test-Retest Reliability of Wireless Dry-Electrode EEG During a Dynamic Psychomotor Virtual Reality Task.

doi: 10.1002/brb3.70448

Figure Lengend Snippet: FIGURE 1 A schematic timeline of the experimental design (read from left, follow the arrows). The virtual reality headset and the EEG systems shown are the Meta Quest 3 (Meta Quest 3, Menlo Park, USA) and the wireless DSI-7 system (Wearable Sensing, LLC, USA), respectively. EEG was recorded for 1 min before and after VRex exposure, and continuously recorded during the 11-min VRex protocol. VRex = virtual reality exergame; EEG = electroencephalogram.

Article Snippet: See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense FIGURE 2 (a) Virtual reality (VR) headset (Meta Quest 3, Meta, USA), the dry-electrode electroencephalogram (EEG) system (DSI-7, Wearable Sensing, LLC, USA) with electrodes (F3, F4, C3, C4, Pz, P3, and P4) based upon the international 10–20 system, and view of the combined participant setup (front, back, side views) next to the casted VR boxing exergame. (b) From left: the heart rate hardware, the punch tracking device, the VR game, the VR task, example of participants during testing.

Techniques:

Journal: Brain and behavior

Article Title: The Feasibility and Test-Retest Reliability of Wireless Dry-Electrode EEG During a Dynamic Psychomotor Virtual Reality Task.

doi: 10.1002/brb3.70448

Figure Lengend Snippet: FIGURE 2 (a) Virtual reality (VR) headset (Meta Quest 3, Meta, USA), the dry-electrode electroencephalogram (EEG) system (DSI-7, Wearable Sensing, LLC, USA) with electrodes (F3, F4, C3, C4, Pz, P3, and P4) based upon the international 10–20 system, and view of the combined participant setup (front, back, side views) next to the casted VR boxing exergame. (b) From left: the heart rate hardware, the punch tracking device, the VR game, the VR task, example of participants during testing.

Article Snippet: See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense FIGURE 2 (a) Virtual reality (VR) headset (Meta Quest 3, Meta, USA), the dry-electrode electroencephalogram (EEG) system (DSI-7, Wearable Sensing, LLC, USA) with electrodes (F3, F4, C3, C4, Pz, P3, and P4) based upon the international 10–20 system, and view of the combined participant setup (front, back, side views) next to the casted VR boxing exergame. (b) From left: the heart rate hardware, the punch tracking device, the VR game, the VR task, example of participants during testing.

Techniques:

Journal: Brain and behavior

Article Title: The Feasibility and Test-Retest Reliability of Wireless Dry-Electrode EEG During a Dynamic Psychomotor Virtual Reality Task.

doi: 10.1002/brb3.70448

Figure Lengend Snippet: FIGURE 3 The statistical topographical plots display the normalized interindividual power spectrum densities (µV2/Hz) differences between the test and the retest sessions, with the local p-value parameters represented. These topographical plots were computed for frequency range of 4–30 Hz (panel a; frequencies ranging from the theta to the beta band) and the alpha band (8–12 Hz; panel b) across all electrode sites. Plots were presented for the (i) pre-virtual reality (VR) exposure, (ii) VR Round-1, (iii) the first rest interval (Rest-1), (iv) VR Round-2, (v) the second rest interval (Rest-2), (vi) VR Round-3, and (vii) post-VR exposure. Such topographical maps demonstrate that across electrode sites, no significant differences were found when comparing test and retest sessions, for neither the pre-, during, nor the post-VR EEG collections. This was displayed both within the alpha band, as well as across the theta–beta band frequency range.

Article Snippet: See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense FIGURE 2 (a) Virtual reality (VR) headset (Meta Quest 3, Meta, USA), the dry-electrode electroencephalogram (EEG) system (DSI-7, Wearable Sensing, LLC, USA) with electrodes (F3, F4, C3, C4, Pz, P3, and P4) based upon the international 10–20 system, and view of the combined participant setup (front, back, side views) next to the casted VR boxing exergame. (b) From left: the heart rate hardware, the punch tracking device, the VR game, the VR task, example of participants during testing.

Techniques:

Journal: Brain and behavior

Article Title: The Feasibility and Test-Retest Reliability of Wireless Dry-Electrode EEG During a Dynamic Psychomotor Virtual Reality Task.

doi: 10.1002/brb3.70448

Figure Lengend Snippet: FIGURE 4 Mean EEG spectral power estimate comparisons between conditions for all electrode placements for all participants for the average (4–30 Hz) frequency range. These are presented for the (a) pre-virtual reality (VR) exposure, (b) VR Round-1, (c) the first rest interval (Rest-1), (d) VR Round-2, (e) the second rest interval (Rest-2), (f) VR Round-3, and (g) post-VR exposure.

Article Snippet: See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense FIGURE 2 (a) Virtual reality (VR) headset (Meta Quest 3, Meta, USA), the dry-electrode electroencephalogram (EEG) system (DSI-7, Wearable Sensing, LLC, USA) with electrodes (F3, F4, C3, C4, Pz, P3, and P4) based upon the international 10–20 system, and view of the combined participant setup (front, back, side views) next to the casted VR boxing exergame. (b) From left: the heart rate hardware, the punch tracking device, the VR game, the VR task, example of participants during testing.

Techniques:

Journal: Brain and behavior

Article Title: The Feasibility and Test-Retest Reliability of Wireless Dry-Electrode EEG During a Dynamic Psychomotor Virtual Reality Task.

doi: 10.1002/brb3.70448

Figure Lengend Snippet: FIGURE 5 Bland–Altman plots for the continuous EEG data, comparing the test and retest sessions. The plots display the global 10log10 transformed power spectrum density (PSD) differences between the sessions, against each participant’s mean. These are presented for the (a) pre-virtual reality (VR) exposure, (b) VR Round-1, (c) the first rest interval (Rest-1), (d) VR Round-2, (e) the second rest interval (Rest-2), (f) VR Round-3, and (g) post-VR exposure.

Article Snippet: See the T erm s and C onditions (https://onlinelibrary.w iley.com /term s-and-conditions) on W iley O nline L ibrary for rules of use; O A articles are governed by the applicable C reative C om m ons L icense FIGURE 2 (a) Virtual reality (VR) headset (Meta Quest 3, Meta, USA), the dry-electrode electroencephalogram (EEG) system (DSI-7, Wearable Sensing, LLC, USA) with electrodes (F3, F4, C3, C4, Pz, P3, and P4) based upon the international 10–20 system, and view of the combined participant setup (front, back, side views) next to the casted VR boxing exergame. (b) From left: the heart rate hardware, the punch tracking device, the VR game, the VR task, example of participants during testing.

Techniques: Transformation Assay

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Transcriptional readout of neuronal activity via an engineered Ca 2+ -activated protease

doi: 10.1073/pnas.2006521117

Figure Lengend Snippet: scFLARE2 labeling in vivo. (A) Concentrated AAV viruses encoding scFLARE2 and TRE:mCherry were injected bilaterally into the hippocampus and cortex of adult mice. After 6 to 7 d of expression, an optical fiber was implanted in both left and right hemispheres, and blue light was delivered to the right hemisphere via the optical fiber (single 10-min session of 473-nm light at 10 mW, 50% duty cycle [2 s light every 4 s]), while mice were subject to either kainate treatment (right hemisphere, dispensed 2 h before light treatment), regular awake conditions (no treatment), or anesthesia. Mice were perfused and immunostained for imaging analysis 18 to 24 h later. (B) An example EEG trace recorded around the time of light stimulation (blue bar). The pink line indicates when the seizure detection system detected a seizure and light delivery was started. The green boxed region shows the EEG signal leading up to the light trigger. The yellow boxed region is an EEG signal showing an example behavioral seizure occurring during the light stimulation. (C) Representative confocal fluorescence images of both hemispheres, following the experiment in A. Activated scFLARE2 drives expression of mCherry (in red), while immunostaining for VP16 (in cyan) shows expression of the tool (scale bars, 10 μm). (D) Quantification of scFLARE2 activation. For each brain hemisphere, we quantified the total mCherry fluorescence intensity divided by scFLARE expression across seven consecutive brain sections around the virus injection site (three to five fields of view for each section). A total of four to six mice per condition were analyzed. See SI Appendix, Fig. S13 for additional fields of view from several animals. The errors bars reflect the SEM; ****P < 0.0001; one-way ANOVA with Tukey post hoc test. (E) To label downstream neurons indirectly activated during seizure, concentrated AAV viruses encoding scFLARE2 and TRE:mCherry were injected into the hippocampus and cortex of adult mice in the left hemisphere contralateral to kainate injection (right hemisphere). After 6 to 7 d of expression, an optical fiber was implanted and blue light was delivered to the left hemisphere (same parameters as in A), while mice were subject to either kainate treatment (dispensed 2 h before light treatment) or regular awake conditions (no treatment). Mice were perfused and immunostained for imaging analysis 18 to 24 h later. (F) Representative confocal fluorescence images of the left hemisphere. Activated scFLARE2 drives expression of mCherry (in red), while immunostaining for VP16 (in cyan) shows expression of the tool (scale bars, 10 μm). See SI Appendix, Fig. S14 for additional fields of view from several animals. Negative controls are from animals not receiving any light. (G) Quantification of scFLARE2 activation. For each animal (2 mice per condition), we quantified the total mCherry fluorescence intensity divided by scFLARE expression across seven consecutive brain sections around the virus injection site (three to five fields of view for each section). Errors bars reflect the SEM; ****P < 0.0001; one-way ANOVA with Tukey post hoc test.

Article Snippet: Mice were stereotaxically injected with kainate (40 nL, 20 mM in saline; Sigma-Aldrich) in the right dorsal hippocampus (−2 mm AP, −1.25 mm ML, and −1.6 mm DV) and implanted with bipolar electroencephalogram (EEG) depth electrodes (PlasticsOne; Roanoke, VA) within the same hemisphere.

Techniques: Labeling, In Vivo, Injection, Expressing, Imaging, Fluorescence, Immunostaining, Activation Assay, Virus

Journal: Cognitive, affective & behavioral neuroscience

Article Title: Neural and Behavioral Effects of Regulating Emotional Responses to Errors during an Implicit Racial Bias Task

doi: 10.3758/s13415-018-0639-8

Figure Lengend Snippet: Panel A: Electrode montage used for EEG recording, highlighting electrodes (grey) included in the ERN analyses (F3, Fz, F4, FC3, FCz, FC4, C3, Cz, and C4). Panel B: Grand average, response-locked ERP waveforms elicited during errors as a function of prime race, target type, and emotion-regulation instructions. Groups of waveforms enclosed in the box are those used in between-subjects comparisons of first-block performance. “Attend (Group R)” and “Attend (Group S)” indicate the Attend blocks for participants who first completed a Reappraisal block and a Suppression block, respectively, in Experiment 2. Grand averages were weighted by the number of trials and subjects per condition. Shading indicates the time interval during which ERN amplitudes were quantified (30 – 110 ms post-response).

Article Snippet: You can also view each error as an opportunity to learn and do better, knowing there are many, many trials and plenty of opportunities to keep trying.” Electrophysiological Recording The electroencephalogram (EEG) was recorded using 24 Ag/AgCl electrodes fixed in a stretch-lycra cap (ElectroCap, Eaton, OH) placed on the scalp in standard locations (American Encephalographic Society, 1994).

Techniques: Blocking Assay