OSCR

Skin-attached bioadhesive patch enabling ultrasound deep brain stimulation and real-time electrophysiological monitoring for REM sleep enhancement.

Code ↔ Paper

16 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 16 matches · 2 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Results › Design and characterization of CRUTA with adjustable focal depth ↔ NEUSLeeP/Simulations/BeamProfileSkull.m, lines 490–535 · score 0.78 · beam profile, radial FWHM, acoustic field, focal depth, free field, skull
  2. [2] § Methods › Design and characterization of CRUTA › Acoustic field mapping ↔ NEUSLeeP/Simulations/BeamProfileSkullParameters.m, lines 501–586 · score 0.75 · 0–100 mm, acoustic field, radial profiles, thick, skull, axial
  3. [3] § Methods › Stress adaptation and REM enhancement evaluation post-FUS with NEUSLeeP › Heart rate variability (RMSSDHRV) ↔ NEUSLeeP/EEG /SleepAnalysis2.m, lines 310–372 · score 0.74 · 5–15 Hz, RR interval, bandpass filter, root, square, peak
  4. [4] § Methods › Stress adaptation and REM enhancement evaluation post-FUS with NEUSLeeP › Heart rate variability (RMSSDHRV) ↔ NEUSLeeP/EEG /process_HRV.m, lines 39–101 · score 0.74 · 5–15 Hz, RR interval, bandpass filter, root, square, peak
  5. [5] § Results › Design and characterization of CRUTA with adjustable focal depth ↔ NEUSLeeP/Simulations/BeamProfileSkullParameters.m, lines 501–586 · score 0.67 · beam profile, radial FWHM, acoustic field, skull, thickness, depth
  6. [6] § Results › Stress response of NEUSLeeP-enabled STN-FUS ↔ MRI-Study/scripts/batch_extract_images_hariri.sh, lines 1–51 · score 0.65 · amygdala ROI, right amygdala, Left Amygdala, bilaterally, Neutral, Anger
  7. [7] § Results › Stress response of NEUSLeeP-enabled STN-FUS ↔ MRI-Study/scripts/extract_image.sh, lines 1–62 · score 0.65 · amygdala ROI, right amygdala, Left Amygdala, bilaterally, Neutral, Anger
  8. [8] § Methods › Design and characterization of CRUTA › Acoustic field mapping ↔ NEUSLeeP/Verasonics Vantage Script/DARPA_NEUSLEEP_Study.m, lines 16–104 · score 0.62 · HIFU, LEMO, commercially, Verasonics, dimensional, Vantage
  9. [9] § Results › Design and characterization of CRUTA with adjustable focal depth ↔ NEUSLeeP/Simulations/BeamProfileSkull.m, lines 490–535 · score 0.57 · peak pressure, Acoustic field, focal depth, skulls, profiles, radial
  10. [10] § Methods › Material characterization (Eco-PEIE-Gel and ASG) › Stress/strain test ↔ NEUSLeeP/Mechanical Tests/Stress_strainTest_step1.m, lines 55–106 · score 0.55 · stress strain, gauge, Force
  11. [11] § Methods › Stress adaptation and REM enhancement evaluation post-FUS with NEUSLeeP › Sleep study with NEUSLeeP ↔ NEUSLeeP/EEG /SleepAnalysis2.m, lines 50–131 · score 0.52 · heart rate, EEG, ECG, HRV, monitoring, signal
  12. [12] § Methods › Material characterization (Eco-PEIE-Gel and ASG) › Adhesion strength/cycle ↔ NEUSLeeP/Simulations/EnergyReleaseRate.m, the whole file · a weak match · score 0.52 · adhesion strength, angle, peel, width
  13. [13] § Methods › Subthalamic nucleus target engagement using CRUTA › Experimental setup ↔ MRI-Study/scripts/MakeRestingRun1AFNIProcRunScript_Censor0.4.sh, the whole file · a weak match · score 0.52 · pre FUS, post FUS, Fast, EPI, STN, MRI
  14. [14] § Methods › Stress adaptation and REM enhancement evaluation post-FUS with NEUSLeeP › Sleep study with NEUSLeeP ↔ NEUSLeeP/Verasonics Vantage Script/DARPA_NEUSLEEP_Study.m, lines 16–104 · score 0.52 · computer, LEMO, Verasonics, external, Vantage, transducer
  15. [15] § Results › Design and characterization of CRUTA with adjustable focal depth ↔ NEUSLeeP/Simulations/BeamProfileSkull.m, lines 46–106 · score 0.51 · concentric ring, CRUTA, skull, delay, axial, mm
  16. [16] § Results › STN-FUS results in ipsilateral changes of the basal ganglia network ↔ NEUSLeeP/EEG /alpha_band_channels.m, lines 181–231 · score 0.50 · power spectral density, EEG, band, 0.1 Hz

Paper

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The authors' code

MATLAB · 653 lines · 22 KB · no license · 3 matches

  1. clear; clc; close all;
  3. % =========================================================
  4. % DOMAIN SETUP
  5. % =========================================================
  6. Nx = 320; % axial samples
  7. Ny = 400; % radial samples
  9. Lx = 100e-3; % axial extent = 100 mm
  10. Ly = 60e-3; % radial extent = 60 mm -> display as -30 to 30 mm
  12. dx = Lx / Nx;
  13. dy = Ly / Ny;
  15. % Internal k-Wave coordinates
  16. x = (0:Nx-1) * dx; % m
  17. y = (0:Ny-1) * dy; % m
  19. x_mm = x * 1e3;
  20. y_mm = y * 1e3;
  22. [Xmm, Ymm] = ndgrid(x_mm, y_mm);
  24. kgrid = kWaveGrid(Nx, dx, Ny, dy);
  26. % =========================================================
  27. % DISPLAY COORDINATES
  28. % =========================================================
  29. % Axial display: 0 mm at bottom, 100 mm at top
  30. axial_disp_mm = x_mm(end) - x_mm;
  32. % Radial display: -30 mm to 30 mm
  33. radial_disp_mm = y_mm - mean(y_mm);
  35. % =========================================================
  36. % BASE MEDIUM PROPERTIES
  37. % =========================================================
  38. c_bg = 1500; % m/s
  39. rho_bg = 1000; % kg/m^3
  41. medium_ff.sound_speed = c_bg * ones(Nx, Ny);
  42. medium_ff.density = rho_bg * ones(Nx, Ny);
  43. medium_ff.alpha_coeff = 0.75 * ones(Nx, Ny);
  44. medium_ff.alpha_power = 1.5;
  46. % =========================================================
  47. % SOURCE LOCATION
  48. % =========================================================
  49. src_row = Nx - 3;
  51. src_depth_mm_internal = x_mm(src_row);
  52. src_depth_mm_display = axial_disp_mm(src_row);
  54. % =========================================================
  55. % 8-CHANNEL CONCENTRIC RING ARRAY SPECIFICATION
  56. % =========================================================
  57. ring_ID_mm = [ 5.35, 10.72, 16.07, 21.43, 26.79, 32.15, 37.51, 42.86 ];
  58. ring_OD_mm = [10.07, 15.42, 20.78, 26.14, 31.49, 36.86, 42.21, 47.57 ];
  60. ring_IR_mm = ring_ID_mm / 2;
  61. ring_OR_mm = ring_OD_mm / 2;
  62. ring_mid_mm = (ring_IR_mm + ring_OR_mm) / 2;
  64. nChannels = numel(ring_ID_mm);
  66. % =========================================================
  67. % SOURCE MASK: 2D APPROXIMATION OF 8-CHANNEL CRUTA
  68. % =========================================================
  69. source.p_mask = zeros(Nx, Ny);
  71. array_center_mm = 0;
  72. r_mm = abs(radial_disp_mm - array_center_mm);
  74. channel_map = zeros(1, Ny); % 0 = inactive, 1..8 = channel
  75. for ch = 1:nChannels
  76. idx = (r_mm >= ring_IR_mm(ch)) & (r_mm <= ring_OR_mm(ch));
  77. channel_map(idx) = ch;
  78. end
  80. active_cols = find(channel_map > 0);
  81. source.p_mask(src_row, active_cols) = 1;
  83. % =========================================================
  84. % FOCUSING DELAYS
  85. % =========================================================
  86. f0 = 650e3; % Hz
  87. source_amp = 1e6; % Pa
  89. target_focus_depth_mm = 72.2;
  91. focus_dist_mm = target_focus_depth_mm - src_depth_mm_display;
  92. focus_dist_m = focus_dist_mm * 1e-3;
  94. if focus_dist_mm <= 0
  95. error('Target focal depth must be above the source when measured from bottom to top.');
  96. end
  98. channel_delay_s = zeros(1, nChannels);
  99. for ch = 1:nChannels
  100. r_mid_m = ring_mid_mm(ch) * 1e-3;
  101. path_excess = sqrt(focus_dist_m^2 + r_mid_m^2) - focus_dist_m;
  102. channel_delay_s(ch) = path_excess / c_bg;
  103. end
  105. channel_delay_s = channel_delay_s - max(channel_delay_s);
  106. channel_apod = ones(1, nChannels);
  108. % =========================================================
  109. % TIME ARRAY
  110. % =========================================================
  111. cfl = 0.1;
  112. t_end = 1.3 * (Lx / c_bg);
  113. kgrid.makeTime(c_bg, cfl, t_end);
  115. % =========================================================
  116. % BUILD SOURCE SIGNALS
  117. % =========================================================
  118. active_pts = find(source.p_mask);
  119. nSrc = numel(active_pts);
  121. source.p = zeros(nSrc, numel(kgrid.t_array));
  122. for i = 1:nSrc
  123. [~, col_idx] = ind2sub([Nx, Ny], active_pts(i));
  124. ch = channel_map(col_idx);
  125. if ch > 0
  126. tau = channel_delay_s(ch);
  127. source.p(i, :) = channel_apod(ch) * source_amp * ...
  128. sin(2*pi*f0*(kgrid.t_array + tau));
  129. end
  130. end
  132. % =========================================================
  133. % SENSOR
  134. % =========================================================
  135. sensor.mask = ones(Nx, Ny);
  136. sensor.record = {'p_max', 'p_rms'};
  138. % =========================================================
  139. % SOURCE DISPLAY MAP
  140. % =========================================================
  141. source_display = zeros(Nx, Ny);
  142. for col = 1:Ny
  143. if channel_map(col) > 0
  144. source_display(src_row, col) = channel_map(col);
  145. end
  146. end
  148. % =========================================================
  149. % RUN FREE-FIELD
  150. % =========================================================
  151. disp('Running free-field simulation...');
  152. input_args = {'PMLInside', false, 'PlotPML', false, 'DisplayMask', 'off'};
  154. sensor_data_ff = kspaceFirstOrder2D(kgrid, medium_ff, source, sensor, input_args{:});
  155. p_max_ff = reshape(sensor_data_ff.p_max, Nx, Ny);
  156. p_rms_ff = reshape(sensor_data_ff.p_rms, Nx, Ny);
  158. % =========================================================
  159. % FIND FREE-FIELD FOCUS LOCATION
  160. % =========================================================
  161. [~, idx_ff] = max(p_max_ff(:));
  162. [focus_row_ff, focus_col_ff] = ind2sub(size(p_max_ff), idx_ff);
  163. focus_axial_ff_mm = axial_disp_mm(focus_row_ff);
  164. focus_radial_ff_mm = radial_disp_mm(focus_col_ff);
  166. % =========================================================
  167. % FREE-FIELD FWHM
  168. % =========================================================
  169. axial_profile_ff_peak = p_max_ff(:, focus_col_ff);
  170. radial_profile_ff_peak = p_max_ff(focus_row_ff, :);
  172. [axial_fwhm_ff_peak_mm, axL_ff_peak, axR_ff_peak] = ...
  173. local_fwhm(axial_disp_mm, axial_profile_ff_peak);
  175. [radial_fwhm_ff_peak_mm, rdL_ff_peak, rdR_ff_peak] = ...
  176. local_fwhm(radial_disp_mm, radial_profile_ff_peak);
  178. % =========================================================
  179. % SWEEP CURVATURES FOR SKULL CASES
  180. % =========================================================
  181. skull_thickness_mm = 6;
  182. skull_center_lat_mm = 0;
  184. % Columns 2-5 in the figure
  185. curvature_list = [0.003, 0.006, 0.009, 0.012];
  186. nCurv = numel(curvature_list);
  188. % Storage
  189. p_max_sk_all = cell(1, nCurv);
  190. skull_mask_all = cell(1, nCurv);
  191. post_skull_mask_all = cell(1, nCurv);
  193. focus_row_sk_all = nan(1, nCurv);
  194. focus_col_sk_all = nan(1, nCurv);
  195. focus_axial_sk_mm_all = nan(1, nCurv);
  196. focus_radial_sk_mm_all = nan(1, nCurv);
  198. axial_profile_sk_all = cell(1, nCurv);
  199. radial_profile_sk_all = cell(1, nCurv);
  201. axial_valid_sk_all = cell(1, nCurv);
  202. radial_valid_sk_all = cell(1, nCurv);
  204. axial_fwhm_sk_mm_all = nan(1, nCurv);
  205. radial_fwhm_sk_mm_all = nan(1, nCurv);
  207. axL_sk_all = nan(1, nCurv);
  208. axR_sk_all = nan(1, nCurv);
  209. rdL_sk_all = nan(1, nCurv);
  210. rdR_sk_all = nan(1, nCurv);
  212. peak_sk_all = nan(1, nCurv);
  214. for k = 1:nCurv
  215. curvature_strength = curvature_list(k);
  217. fprintf('Running skull simulation for curvature = %.4f ...\n', curvature_strength);
  219. % -----------------------------------------------------
  220. % SKULL GEOMETRY
  221. % -----------------------------------------------------
  222. skull_bottom_disp_mm = (src_depth_mm_display + 1.0) + ...
  223. curvature_strength * (radial_disp_mm - skull_center_lat_mm).^2;
  224. skull_top_disp_mm = skull_bottom_disp_mm + skull_thickness_mm;
  226. % Convert skull surfaces to internal x_mm
  227. skull_bottom_internal_mm = x_mm(end) - skull_bottom_disp_mm;
  228. skull_top_internal_mm = x_mm(end) - skull_top_disp_mm;
  230. skull_bottom_2d = repmat(skull_bottom_internal_mm, Nx, 1);
  231. skull_top_2d = repmat(skull_top_internal_mm, Nx, 1);
  233. skull_mask = (Xmm >= skull_top_2d) & (Xmm <= skull_bottom_2d);
  235. medium_skull = medium_ff;
  236. medium_skull.sound_speed(skull_mask) = 2800;
  237. medium_skull.density(skull_mask) = 1900;
  238. medium_skull.alpha_coeff(skull_mask) = 20;
  240. % -----------------------------------------------------
  241. % POST-SKULL VALID FOCUS REGION
  242. % -----------------------------------------------------
  243. post_skull_mask = false(Nx, Ny);
  244. for j = 1:Ny
  245. skull_rows = find(skull_mask(:, j));
  246. if isempty(skull_rows)
  247. post_skull_mask(:, j) = true;
  248. else
  249. skull_axial_vals = axial_disp_mm(skull_rows);
  250. top_of_skull_axial = max(skull_axial_vals);
  251. post_skull_mask(:, j) = axial_disp_mm(:) > top_of_skull_axial;
  252. end
  253. end
  255. % -----------------------------------------------------
  256. % RUN WITH SKULL
  257. % -----------------------------------------------------
  258. sensor_data_sk = kspaceFirstOrder2D(kgrid, medium_skull, source, sensor, input_args{:});
  259. p_max_sk = reshape(sensor_data_sk.p_max, Nx, Ny);
  261. % -----------------------------------------------------
  262. % FIND FOCUS LOCATION (POST-SKULL ONLY)
  263. % -----------------------------------------------------
  264. p_max_sk_post = p_max_sk;
  265. p_max_sk_post(~post_skull_mask) = -Inf;
  267. [~, idx_sk] = max(p_max_sk_post(:));
  268. [focus_row_sk, focus_col_sk] = ind2sub(size(p_max_sk_post), idx_sk);
  270. focus_axial_sk_mm = axial_disp_mm(focus_row_sk);
  271. focus_radial_sk_mm = radial_disp_mm(focus_col_sk);
  273. % -----------------------------------------------------
  274. % FWHM PROFILES
  275. % -----------------------------------------------------
  276. axial_profile_sk_peak = p_max_sk(:, focus_col_sk);
  277. radial_profile_sk_peak = p_max_sk(focus_row_sk, :);
  279. axial_valid_sk_peak = (~skull_mask(:, focus_col_sk)) & post_skull_mask(:, focus_col_sk);
  280. radial_valid_sk_peak = (~skull_mask(focus_row_sk, :).') & post_skull_mask(focus_row_sk, :).';
  282. [axial_fwhm_sk_peak_mm, axL_sk_peak, axR_sk_peak] = ...
  283. local_fwhm_masked(axial_disp_mm, axial_profile_sk_peak, axial_valid_sk_peak);
  285. [radial_fwhm_sk_peak_mm, rdL_sk_peak, rdR_sk_peak] = ...
  286. local_fwhm_masked(radial_disp_mm, radial_profile_sk_peak, radial_valid_sk_peak);
  288. % -----------------------------------------------------
  289. % STORE
  290. % -----------------------------------------------------
  291. p_max_sk_all{k} = p_max_sk;
  292. skull_mask_all{k} = skull_mask;
  293. post_skull_mask_all{k} = post_skull_mask;
  295. focus_row_sk_all(k) = focus_row_sk;
  296. focus_col_sk_all(k) = focus_col_sk;
  297. focus_axial_sk_mm_all(k) = focus_axial_sk_mm;
  298. focus_radial_sk_mm_all(k) = focus_radial_sk_mm;
  300. axial_profile_sk_all{k} = axial_profile_sk_peak;
  301. radial_profile_sk_all{k} = radial_profile_sk_peak;
  303. axial_valid_sk_all{k} = axial_valid_sk_peak;
  304. radial_valid_sk_all{k} = radial_valid_sk_peak;
  306. axial_fwhm_sk_mm_all(k) = axial_fwhm_sk_peak_mm;
  307. radial_fwhm_sk_mm_all(k) = radial_fwhm_sk_peak_mm;
  309. axL_sk_all(k) = axL_sk_peak;
  310. axR_sk_all(k) = axR_sk_peak;
  311. rdL_sk_all(k) = rdL_sk_peak;
  312. rdR_sk_all(k) = rdR_sk_peak;
  314. peak_sk_all(k) = max(p_max_sk_post(:));
  315. end
  317. % =========================================================
  318. % COMMON COLOR LIMITS
  319. % =========================================================
  320. clim_pmax = [0 1.5e6]; % Pa
  321. clim_prof = [0 2.5]; % MPa
  323. % =========================================================
  324. % PLOT 3x5 FIGURE
  325. % Row 1 = Acoustic field
  326. % Row 2 = Axial FWHM
  327. % Row 3 = Radial FWHM
  328. % Col 1 = Free-field
  329. % Col 2-5 = Skull with curvature sweep
  330. % =========================================================
  331. figure('Color', 'w', 'Name', 'Curvature Sweep: Free-field and Skull Cases', ...
  332. 'Position', [50 40 1800 950]);
  334. ax_field = gobjects(1, 5);
  336. % =========================================================
  337. % COLUMN 1: FREE-FIELD
  338. % =========================================================
  339. ax_field(1) = subplot(3,5,1);
  340. imagesc(radial_disp_mm, axial_disp_mm, p_max_ff);
  341. axis image;
  342. set(gca, 'YDir', 'normal');
  343. colormap(gca, turbo);
  344. caxis(clim_pmax);
  345. hold on;
  346. plot(focus_radial_ff_mm, focus_axial_ff_mm, 'wo', 'MarkerSize', 8, 'LineWidth', 1.8);
  347. yline(target_focus_depth_mm, 'w--', '72.2 mm target', 'LineWidth', 1.0);
  348. title('No Skull');
  349. xlabel('Radial position (mm)');
  350. ylabel('Axial depth (mm)');
  351. xlim([-30 30]);
  352. ylim([0 100]);
  353. hold off;
  355. subplot(3,5,6);
  356. axial_profile_ff_peak_mpa = axial_profile_ff_peak / 1e6;
  357. plot(axial_disp_mm, axial_profile_ff_peak_mpa, 'b-', 'LineWidth', 1.5); hold on;
  358. halfmax_ff_ax = max(axial_profile_ff_peak_mpa) / 2;
  359. yline(halfmax_ff_ax, 'k--', 'LineWidth', 1);
  360. if ~isnan(axL_ff_peak), xline(axL_ff_peak, 'r--', 'LineWidth', 1); end
  361. if ~isnan(axR_ff_peak), xline(axR_ff_peak, 'r--', 'LineWidth', 1); end
  362. plot([axL_ff_peak axR_ff_peak], [halfmax_ff_ax halfmax_ff_ax], ...
  363. 'ro', 'MarkerFaceColor', 'r');
  364. title(sprintf('Axial FWHM = %.2f mm', axial_fwhm_ff_peak_mm));
  365. xlabel('Axial depth (mm)');
  366. ylabel('Pressure (MPa)');
  367. xlim([0 100]);
  368. ylim(clim_prof);
  369. grid on;
  370. hold off;
  372. subplot(3,5,11);
  373. radial_profile_ff_peak_mpa = radial_profile_ff_peak / 1e6;
  374. plot(radial_disp_mm, radial_profile_ff_peak_mpa, 'b-', 'LineWidth', 1.5); hold on;
  375. halfmax_ff_rd = max(radial_profile_ff_peak_mpa) / 2;
  376. yline(halfmax_ff_rd, 'k--', 'LineWidth', 1);
  377. if ~isnan(rdL_ff_peak), xline(rdL_ff_peak, 'r--', 'LineWidth', 1); end
  378. if ~isnan(rdR_ff_peak), xline(rdR_ff_peak, 'r--', 'LineWidth', 1); end
  379. plot([rdL_ff_peak rdR_ff_peak], [halfmax_ff_rd halfmax_ff_rd], ...
  380. 'ro', 'MarkerFaceColor', 'r');
  381. title(sprintf('Radial FWHM = %.2f mm', radial_fwhm_ff_peak_mm));
  382. xlabel('Radial position (mm)');
  383. ylabel('Pressure (MPa)');
  384. xlim([-30 30]);
  385. ylim(clim_prof);
  386. grid on;
  387. hold off;
  389. % =========================================================
  390. % COLUMNS 2-5: SKULL CURVATURE SWEEP
  391. % =========================================================
  392. for k = 1:nCurv
  393. col_idx = k + 1;
  395. p_max_sk = p_max_sk_all{k};
  396. skull_mask = skull_mask_all{k};
  398. focus_axial_sk_mm = focus_axial_sk_mm_all(k);
  399. focus_radial_sk_mm = focus_radial_sk_mm_all(k);
  401. axial_profile_sk_peak = axial_profile_sk_all{k};
  402. radial_profile_sk_peak = radial_profile_sk_all{k};
  404. axial_valid_sk_peak = axial_valid_sk_all{k};
  405. radial_valid_sk_peak = radial_valid_sk_all{k};
  407. axial_fwhm_sk_peak_mm = axial_fwhm_sk_mm_all(k);
  408. radial_fwhm_sk_peak_mm = radial_fwhm_sk_mm_all(k);
  410. axL_sk_peak = axL_sk_all(k);
  411. axR_sk_peak = axR_sk_all(k);
  412. rdL_sk_peak = rdL_sk_all(k);
  413. rdR_sk_peak = rdR_sk_all(k);
  415. curvature_strength = curvature_list(k);
  417. % ---------------- Row 1: Acoustic field ----------------
  418. ax_field(col_idx) = subplot(3,5,col_idx);
  419. imagesc(radial_disp_mm, axial_disp_mm, p_max_sk);
  420. axis image;
  421. set(gca, 'YDir', 'normal');
  422. colormap(gca, turbo);
  423. caxis(clim_pmax);
  424. hold on;
  426. h1 = imagesc(radial_disp_mm, axial_disp_mm, double(skull_mask));
  427. set(h1, 'AlphaData', 0.16 * double(skull_mask));
  428. contour(radial_disp_mm, axial_disp_mm, skull_mask, [1 1], 'w', 'LineWidth', 1.5);
  430. plot(focus_radial_sk_mm, focus_axial_sk_mm, 'wo', 'MarkerSize', 8, 'LineWidth', 1.8);
  431. yline(target_focus_depth_mm, 'w--', '72.2 mm target', 'LineWidth', 1.0);
  433. caxis(clim_pmax);
  434. title(sprintf('Skull, curv = %.4f', curvature_strength));
  435. xlabel('Radial position (mm)');
  436. if col_idx == 2
  437. ylabel('Axial depth (mm)');
  438. end
  439. xlim([-30 30]);
  440. ylim([0 100]);
  441. hold off;
  443. % ---------------- Row 2: Axial FWHM ----------------
  444. subplot(3,5,5 + col_idx);
  445. axial_profile_sk_peak_mpa = axial_profile_sk_peak / 1e6;
  446. axial_profile_sk_plot = axial_profile_sk_peak_mpa;
  447. axial_profile_sk_plot(~axial_valid_sk_peak) = NaN;
  449. plot(axial_disp_mm, axial_profile_sk_plot, 'b-', 'LineWidth', 1.5); hold on;
  450. halfmax_sk_ax = max(axial_profile_sk_plot, [], 'omitnan') / 2;
  451. yline(halfmax_sk_ax, 'k--', 'LineWidth', 1);
  452. if ~isnan(axL_sk_peak), xline(axL_sk_peak, 'r--', 'LineWidth', 1); end
  453. if ~isnan(axR_sk_peak), xline(axR_sk_peak, 'r--', 'LineWidth', 1); end
  454. plot([axL_sk_peak axR_sk_peak], [halfmax_sk_ax halfmax_sk_ax], ...
  455. 'ro', 'MarkerFaceColor', 'r');
  456. title(sprintf('Axial FWHM = %.2f mm', -axial_fwhm_sk_peak_mm));
  457. xlabel('Axial depth (mm)');
  458. if col_idx == 2
  459. ylabel('Pressure (MPa)');
  460. end
  461. xlim([0 100]);
  462. ylim(clim_prof);
  463. grid on;
  464. hold off;
  466. % ---------------- Row 3: Radial FWHM ----------------
  467. subplot(3,5,10 + col_idx);
  468. radial_profile_sk_peak_mpa = radial_profile_sk_peak / 1e6;
  469. radial_profile_sk_plot = radial_profile_sk_peak_mpa;
  470. radial_profile_sk_plot(~radial_valid_sk_peak) = NaN;
  472. plot(radial_disp_mm, radial_profile_sk_plot, 'b-', 'LineWidth', 1.5); hold on;
  473. halfmax_sk_rd = max(radial_profile_sk_plot, [], 'omitnan') / 2;
  474. yline(halfmax_sk_rd, 'k--', 'LineWidth', 1);
  475. if ~isnan(rdL_sk_peak), xline(rdL_sk_peak, 'r--', 'LineWidth', 1); end
  476. if ~isnan(rdR_sk_peak), xline(rdR_sk_peak, 'r--', 'LineWidth', 1); end
  477. plot([rdL_sk_peak rdR_sk_peak], [halfmax_sk_rd halfmax_sk_rd], ...
  478. 'ro', 'MarkerFaceColor', 'r');
  479. title(sprintf('Radial FWHM = %.2f mm', radial_fwhm_sk_peak_mm));
  480. xlabel('Radial position (mm)');
  481. if col_idx == 2
  482. ylabel('Pressure (MPa)');
  483. end
  484. xlim([-30 30]);
  485. ylim(clim_prof);
  486. grid on;
  487. hold off;
  488. end
  490. % =========================================================
  491. % SINGLE COLORBAR FOR ACOUSTIC FIELD ROW
  492. % =========================================================
  493. cb = colorbar(ax_field(end), 'Position', [0.92 0.71 0.012 0.20]);
  494. ylabel(cb, 'Peak pressure (Pa)');
  496. % =========================================================
  497. % SUMMARY METRICS
  498. % =========================================================
  499. output_peak_ff = max(p_max_ff(:));
  501. fprintf('\n===== CURVATURE SWEEP SUMMARY =====\n');
  502. fprintf('Axial axis : 0 mm bottom -> 100 mm top\n');
  503. fprintf('Radial axis : -30 mm -> 30 mm\n');
  504. fprintf('Source axial position : %.2f mm\n', src_depth_mm_display);
  505. fprintf('Target focal depth : %.2f mm\n', target_focus_depth_mm);
  506. fprintf('Focus distance from source : %.2f mm\n', focus_dist_mm);
  507. fprintf('Skull thickness : %.2f mm\n', skull_thickness_mm);
  508. fprintf('Free-field peak : %.4g Pa\n', output_peak_ff);
  509. fprintf('Free-field focus : axial = %.2f mm, radial = %.2f mm\n', ...
  510. focus_axial_ff_mm, focus_radial_ff_mm);
  511. fprintf('Free-field axial FWHM : %.2f mm\n', axial_fwhm_ff_peak_mm);
  512. fprintf('Free-field radial FWHM : %.2f mm\n', radial_fwhm_ff_peak_mm);
  513. fprintf('\n');
  515. for k = 1:nCurv
  516. peak_loss_pct = 100 * (1 - peak_sk_all(k) / output_peak_ff);
  517. focus_shift_axial_mm = focus_axial_sk_mm_all(k) - focus_axial_ff_mm;
  518. focus_shift_radial_mm = focus_radial_sk_mm_all(k) - focus_radial_ff_mm;
  520. fprintf('Curvature = %.4f\n', curvature_list(k));
  521. fprintf(' Skull peak (post-skull) : %.4g Pa\n', peak_sk_all(k));
  522. fprintf(' Peak loss : %.2f %%\n', peak_loss_pct);
  523. fprintf(' Focus : axial = %.2f mm, radial = %.2f mm\n', ...
  524. focus_axial_sk_mm_all(k), focus_radial_sk_mm_all(k));
  525. fprintf(' Focus shift : axial = %.2f mm, radial = %.2f mm\n', ...
  526. focus_shift_axial_mm, focus_shift_radial_mm);
  527. fprintf(' Axial FWHM : %.2f mm\n', axial_fwhm_sk_mm_all(k));
  528. fprintf(' Radial FWHM : %.2f mm\n', radial_fwhm_sk_mm_all(k));
  529. fprintf('\n');
  530. end
  531. fprintf('===================================\n\n');
  533. % =========================================================
  534. % LOCAL FUNCTIONS
  535. % =========================================================
  536. function [fwhm, x_left, x_right] = local_fwhm(coord, profile)
  537. profile = double(profile(:));
  538. coord = double(coord(:));
  540. x_left = NaN;
  541. x_right = NaN;
  542. fwhm = NaN;
  544. if all(profile == 0) || max(profile) <= 0
  545. return;
  546. end
  548. [~, imax] = max(profile);
  549. halfmax = max(profile) / 2;
  550. above = profile >= halfmax;
  552. left_idx = find(above(1:imax), 1, 'first');
  553. right_idx = imax - 1 + find(above(imax:end), 1, 'last');
  555. if isempty(left_idx) || isempty(right_idx)
  556. return;
  557. end
  559. if left_idx == 1
  560. x_left = coord(left_idx);
  561. else
  562. x1 = coord(left_idx - 1);
  563. x2 = coord(left_idx);
  564. y1 = profile(left_idx - 1);
  565. y2 = profile(left_idx);
  566. x_left = x1 + (halfmax - y1) * (x2 - x1) / (y2 - y1);
  567. end
  569. if right_idx == numel(profile)
  570. x_right = coord(right_idx);
  571. else
  572. x1 = coord(right_idx);
  573. x2 = coord(right_idx + 1);
  574. y1 = profile(right_idx);
  575. y2 = profile(right_idx + 1);
  576. x_right = x1 + (halfmax - y1) * (x2 - x1) / (y2 - y1);
  577. end
  579. fwhm = x_right - x_left;
  580. end
  582. function [fwhm, x_left, x_right] = local_fwhm_masked(coord, profile, valid_mask)
  583. profile = double(profile(:));
  584. coord = double(coord(:));
  585. valid_mask = logical(valid_mask(:));
  587. x_left = NaN;
  588. x_right = NaN;
  589. fwhm = NaN;
  591. if numel(coord) ~= numel(profile) || numel(profile) ~= numel(valid_mask)
  592. error('coord, profile, and valid_mask must have the same length.');
  593. end
  595. profile(~valid_mask) = NaN;
  597. if all(isnan(profile))
  598. return;
  599. end
  601. peak_val = max(profile, [], 'omitnan');
  602. if isempty(peak_val) || isnan(peak_val) || peak_val <= 0
  603. return;
  604. end
  606. halfmax = peak_val / 2;
  608. tmp = profile;
  609. tmp(isnan(tmp)) = -Inf;
  610. [~, imax] = max(tmp);
  612. if ~isfinite(tmp(imax))
  613. return;
  614. end
  616. above = (profile >= halfmax);
  618. if ~above(imax)
  619. return;
  620. end
  622. left_idx = imax;
  623. while left_idx > 1 && above(left_idx - 1)
  624. left_idx = left_idx - 1;
  625. end
  627. right_idx = imax;
  628. while right_idx < numel(profile) && above(right_idx + 1)
  629. right_idx = right_idx + 1;
  630. end
  632. if left_idx == 1 || isnan(profile(left_idx - 1))
  633. x_left = coord(left_idx);
  634. else
  635. x1 = coord(left_idx - 1);
  636. x2 = coord(left_idx);
  637. y1 = profile(left_idx - 1);
  638. y2 = profile(left_idx);
  639. x_left = x1 + (halfmax - y1) * (x2 - x1) / (y2 - y1);
  640. end
  642. if right_idx == numel(profile) || isnan(profile(right_idx + 1))
  643. x_right = coord(right_idx);
  644. else
  645. x1 = coord(right_idx);
  646. x2 = coord(right_idx + 1);
  647. y1 = profile(right_idx);
  648. y2 = profile(right_idx + 1);
  649. x_right = x1 + (halfmax - y1) * (x2 - x1) / (y2 - y1);
  650. end
  652. fwhm = x_right - x_left;
  653. end

BeamProfileSkull.m at commit baa5d8b, no license · at the source

Overview

Authors: Kai Wing Kevin Tang1, Benjamin Baird2, William D Moscoso-Barrera1, Mengxia Yu1, Mengmeng Yao1, Jinmo Jeong1, Ilya Pyatnitskiy1, Anakaren Romero Lozano1, Jiachen Wang1, Ju-Chun Hsieh1, Tony Sungjin Chae1, Daniel Song1, Julieta Garcia1, Rithvik Mittapalli1, Adam Bush1, Wynn Legon3, Vincent Mysliwiec4, Gregory A Fonzo5, Huiliang Wang1
ORCID iDs: Kai Wing Kevin Tang, Benjamin Baird, Mengmeng Yao, Jinmo Jeong, Anakaren Romero Lozano, Ju-Chun Hsieh, Gregory A Fonzo, Huiliang Wang
  1. Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX USA
  2. Department of Psychology, The University of Texas at Austin, Austin, TX USA
  3. Fralin Biomedical Research Institute, Virginia Polytechnic Institute, Blacksburg, VA USA
  4. Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science at San Antonio, San Antonio, TX USA
  5. Department of Psychiatry and Behavioral Sciences, Dell Medical School, The University of Texas at Austin, Austin, TX USA
Institutions: The University of Texas at Austin (United States); Virginia Tech (United States); The University of Texas at San Antonio Health Science Center (United States)
Journal: Nature communications, volume 17, issue 1, article 5570
Dates: received 5 March 2026; accepted 18 May 2026; published online 4 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41467-026-73787-6 · PMID 42243115 · PMCID PMC13294382 · OpenAlex W7163528177
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: other (modality), human (organism), clinical / translational (subfield)
Methods: Spectral & time-frequency, Statistics, Preprocessing, Physiology & signal measures
Keywords: Biomedical engineering, Electrical and electronic engineering, Translational research
MeSH: Deep Brain Stimulation*, Sleep, REM*, Electrophysiological Phenomena, Humans, Skin, Wearable Electronic Devices (* major topic)
Topic: Advanced Sensor and Energy Harvesting Materials (Biomedical Engineering, Engineering), according to OpenAlex
Funding: United States Department of Defense | Defense Advanced Research Projects Agency
Citations: not cited yet (Europe PMC); 130 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repositories

Its files are read in the Code ↔ Paper reader above, with 16 matches between paragraphs and lines of code.

kevintang725/DARPA-NEUSLEEP

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: baa5d8bbfba157ea4996a239b4ee2b66294bfc0e, 2 April 2026
Languages: Python (133), Shell (129), MATLAB (45)
Size: 4,604 files, 307 scripts
Software Heritage: not archived
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: NumPy (66 files), Matplotlib (55 files), AFNI (40 files), Signal Processing Toolbox (11 files), FSL (10 files), EEGLAB (5 files), Image Processing Toolbox (2 files), Statistics and Machine Learning Toolbox (2 files), PsychoPy (2 files), dcm2niix (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
308 files
At the source: github.com/kevintang725/DARPA-NEUSLEEP

Zenodo 19391527

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
At the source:

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Read it in the paper: doi.org/10.1038/s41467-026-73787-6.

Tracing map

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  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 307 scripts, each with its path and the digest of its content;
  • 16 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

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Data availability statement

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Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 19 authors, 3 keywords, 6 MeSH terms, 1 funder, 125 references.

Cite

This paper

Tang, K. W. K., Baird, B., Moscoso-Barrera, W. D., Yu, M., Yao, M., Jeong, J., Pyatnitskiy, I., Romero Lozano, A., Wang, J., Hsieh, J.-C., Chae, T. S., Song, D., Garcia, J., Mittapalli, R., Bush, A., Legon, W., Mysliwiec, V., Fonzo, G. A., & Wang, H. (2026). Skin-attached bioadhesive patch enabling ultrasound deep brain stimulation and real-time electrophysiological monitoring for REM sleep enhancement. Nature communications, 17(1), 5570. https://doi.org/10.1038/s41467-026-73787-6

BibTeX

@article{tang2026skin,
author = {Tang, Kai Wing Kevin and Baird, Benjamin and Moscoso-Barrera, William D and Yu, Mengxia and Yao, Mengmeng and Jeong, Jinmo and Pyatnitskiy, Ilya and Romero Lozano, Anakaren and Wang, Jiachen and Hsieh, Ju-Chun and Chae, Tony Sungjin and Song, Daniel and Garcia, Julieta and Mittapalli, Rithvik and Bush, Adam and Legon, Wynn and Mysliwiec, Vincent and Fonzo, Gregory A and Wang, Huiliang},
title = {{Skin-attached bioadhesive patch enabling ultrasound deep brain stimulation and real-time electrophysiological monitoring for REM sleep enhancement}},
journal = {Nature communications},
year = {2026},
month = jun,
volume = {17},
number = {1},
pages = {5570},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-73787-6},
url = {https://doi.org/10.1038/s41467-026-73787-6},
pmid = {42243115},
pmcid = {PMC13294382}
}

RIS

TY - JOUR
AU - Tang, Kai Wing Kevin
AU - Baird, Benjamin
AU - Moscoso-Barrera, William D
AU - Yu, Mengxia
AU - Yao, Mengmeng
AU - Jeong, Jinmo
AU - Pyatnitskiy, Ilya
AU - Romero Lozano, Anakaren
AU - Wang, Jiachen
AU - Hsieh, Ju-Chun
AU - Chae, Tony Sungjin
AU - Song, Daniel
AU - Garcia, Julieta
AU - Mittapalli, Rithvik
AU - Bush, Adam
AU - Legon, Wynn
AU - Mysliwiec, Vincent
AU - Fonzo, Gregory A
AU - Wang, Huiliang
TI - Skin-attached bioadhesive patch enabling ultrasound deep brain stimulation and real-time electrophysiological monitoring for REM sleep enhancement
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/06/04
VL - 17
IS - 1
SP - 5570
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-73787-6
UR - https://doi.org/10.1038/s41467-026-73787-6
LA - en
ER -

CSL-JSON

{
"id": "10.1038/s41467-026-73787-6",
"type": "article-journal",
"title": "Skin-attached bioadhesive patch enabling ultrasound deep brain stimulation and real-time electrophysiological monitoring for REM sleep enhancement",
"container-title": "Nature communications",
"author": [
{
"family": "Tang",
"given": "Kai Wing Kevin"
},
{
"family": "Baird",
"given": "Benjamin"
},
{
"family": "Moscoso-Barrera",
"given": "William D"
},
{
"family": "Yu",
"given": "Mengxia"
},
{
"family": "Yao",
"given": "Mengmeng"
},
{
"family": "Jeong",
"given": "Jinmo"
},
{
"family": "Pyatnitskiy",
"given": "Ilya"
},
{
"family": "Romero Lozano",
"given": "Anakaren"
},
{
"family": "Wang",
"given": "Jiachen"
},
{
"family": "Hsieh",
"given": "Ju-Chun"
},
{
"family": "Chae",
"given": "Tony Sungjin"
},
{
"family": "Song",
"given": "Daniel"
},
{
"family": "Garcia",
"given": "Julieta"
},
{
"family": "Mittapalli",
"given": "Rithvik"
},
{
"family": "Bush",
"given": "Adam"
},
{
"family": "Legon",
"given": "Wynn"
},
{
"family": "Mysliwiec",
"given": "Vincent"
},
{
"family": "Fonzo",
"given": "Gregory A"
},
{
"family": "Wang",
"given": "Huiliang"
}
],
"container-title-short": "Nat Commun",
"volume": "17",
"issue": "1",
"page": "5570",
"DOI": "10.1038/s41467-026-73787-6",
"PMID": "42243115",
"PMCID": "PMC13294382",
"ISSN": "2041-1723",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s41467-026-73787-6",
"language": "en",
"issued": {
"date-parts": [
[
2026,
6,
4
]
]
}
}

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