Try this, but note that your variables are highly skewed, so you should try boxplot or boxchart (median and IQR instead of mean and SD).
tab = load('example.mat').Local_Mat_Data;
t = groupsummary(tab, 'Region', {'mean', 'min', 'max', 'std'});
capsz = 20;
linew = 1.5;
hold on
plot(t.Region, t.mean_LocCycLim_MIN, 'Marker', '_', 'LineStyle', 'none', 'LineWidth', linew, 'Color', 'k', 'MarkerSize', capsz)
plot(t.Region, t.min_LocCycLim_MIN, 'Marker', '_', 'LineStyle', 'none', 'LineWidth', linew, 'Color', 'g', 'MarkerSize', capsz)
plot(t.Region, t.max_LocCycLim_MIN, 'Marker', '_', 'LineStyle', 'none', 'LineWidth', linew, 'Color', 'b', 'MarkerSize', capsz)
errorbar(t.Region, t.mean_LocCycLim_MIN, t.std_LocCycLim_MIN,'.','Color', 'k', 'LineWidth', linew, 'CapSize', capsz)
h = gca;
h.YGrid = 'on';
h.GridAlpha = 0.5;
h.XLim = [min(tab.Region) - 1, max(tab.Region) + 1];
h.XTick = t.Region;
h.XTickLabel = "Region " + h.XTick;
title('LocCycLim_MIN', 'Interpreter', 'none')
h.Box = 'on';
