1 00:00:08,419 --> 00:00:06,680 great I'm going to be here today and I'm 2 00:00:13,039 --> 00:00:08,429 going to talk about some brain imaging 3 00:00:16,010 --> 00:00:13,049 of the brain signals from subjects that 4 00:00:18,320 --> 00:00:16,020 we've studied with correlated brain 5 00:00:20,359 --> 00:00:18,330 signals now first of all I wanted to 6 00:00:23,480 --> 00:00:20,369 acknowledge all my collaborators and 7 00:00:26,150 --> 00:00:23,490 co-investigators Liana Standish from 8 00:00:29,720 --> 00:00:26,160 bastyr university Laila Kozak Jeanne 9 00:00:31,910 --> 00:00:29,730 actor Berg Karen cook James Lake Clark 10 00:00:34,340 --> 00:00:31,920 Johnson and we wanted to thank Dean 11 00:00:36,799 --> 00:00:34,350 Radin for help with our EEG alpha 12 00:00:42,170 --> 00:00:36,809 analysis to which I'll show a little bit 13 00:00:44,030 --> 00:00:42,180 later on so the question is is there 14 00:00:46,430 --> 00:00:44,040 evidence for correlations between 15 00:00:49,220 --> 00:00:46,440 distance intentionality and brain 16 00:00:52,549 --> 00:00:49,230 function in recipients of distance 17 00:00:59,180 --> 00:00:52,559 intentionality who are tested using fMRI 18 00:01:00,740 --> 00:00:59,190 and EEG now for a background history has 19 00:01:03,860 --> 00:01:00,750 shown evidence for connection between 20 00:01:07,250 --> 00:01:03,870 human beings we all like connections 21 00:01:09,410 --> 00:01:07,260 between those we love and those that we 22 00:01:11,679 --> 00:01:09,420 work with and so how are we connected 23 00:01:15,080 --> 00:01:11,689 there could be spiritual connections 24 00:01:17,749 --> 00:01:15,090 emotional connections sensory 25 00:01:20,719 --> 00:01:17,759 connections now all of you you have a 26 00:01:23,300 --> 00:01:20,729 sensory connection with me right now so 27 00:01:25,760 --> 00:01:23,310 you can you can see me and I can see you 28 00:01:28,700 --> 00:01:25,770 I have a sensory connection and then 29 00:01:32,870 --> 00:01:28,710 there's energy connections so all of 30 00:01:36,920 --> 00:01:32,880 these have influence on how my theory is 31 00:01:40,010 --> 00:01:36,930 on how the brain works okay so a little 32 00:01:43,069 --> 00:01:40,020 bit of background in my regular work I 33 00:01:46,789 --> 00:01:43,079 do brain imaging of different diseases 34 00:01:48,740 --> 00:01:46,799 and and different research projects so 35 00:01:50,810 --> 00:01:48,750 one of my biggest projects is to study 36 00:01:53,120 --> 00:01:50,820 children with learning disabilities and 37 00:01:55,550 --> 00:01:53,130 so I do a lot of brain imaging of 38 00:01:59,090 --> 00:01:55,560 language in children with learning 39 00:02:00,800 --> 00:01:59,100 disabilities but so functional magnetic 40 00:02:03,620 --> 00:02:00,810 resonance imaging is a technique for 41 00:02:06,440 --> 00:02:03,630 measuring brain activation using blood 42 00:02:10,369 --> 00:02:06,450 oxygen level dependence which is called 43 00:02:13,040 --> 00:02:10,379 bold but now fMRI is completely 44 00:02:15,410 --> 00:02:13,050 dependent on the water in the brain 45 00:02:17,870 --> 00:02:15,420 so we've heard some talk before about 46 00:02:20,390 --> 00:02:17,880 the importance of water and that's 47 00:02:23,440 --> 00:02:20,400 exactly what we're measuring in the 48 00:02:27,350 --> 00:02:23,450 brain is the water signal which may be 49 00:02:32,000 --> 00:02:27,360 influenced by the oxygen but the real 50 00:02:34,460 --> 00:02:32,010 signal is coming from the water so how 51 00:02:37,250 --> 00:02:34,470 is it statistically tested is there a 52 00:02:40,280 --> 00:02:37,260 possibility of false positives and I'll 53 00:02:44,780 --> 00:02:40,290 go through some of the statistical tests 54 00:02:49,670 --> 00:02:44,790 that we use to test for the significance 55 00:02:53,090 --> 00:02:49,680 of brain activation that we get so 56 00:02:56,150 --> 00:02:53,100 there's been a blossoming of MRI in the 57 00:02:58,340 --> 00:02:56,160 in its ability to brain scan and I 58 00:03:02,000 --> 00:02:58,350 borrowed some slides from Mark Cohen 59 00:03:03,860 --> 00:03:02,010 from UCLA and so and I'm going to give 60 00:03:07,070 --> 00:03:03,870 you a little background on brain imaging 61 00:03:08,990 --> 00:03:07,080 but there's a blossoming of advances in 62 00:03:11,150 --> 00:03:09,000 brain imaging techniques that's happened 63 00:03:13,610 --> 00:03:11,160 and just like the past five to ten years 64 00:03:15,530 --> 00:03:13,620 that's allowed us to measure new things 65 00:03:22,430 --> 00:03:15,540 in the brain that we haven't been able 66 00:03:26,570 --> 00:03:22,440 to do before okay so brain activation is 67 00:03:28,940 --> 00:03:26,580 what happens when you think so so if all 68 00:03:31,040 --> 00:03:28,950 of you put up your right hand and you if 69 00:03:33,680 --> 00:03:31,050 all of you go like this with your right 70 00:03:37,280 --> 00:03:33,690 hand and as you're doing this you are 71 00:03:40,340 --> 00:03:37,290 activating your motor cortex on your 72 00:03:43,880 --> 00:03:40,350 left side so it crosses over so your 73 00:03:47,180 --> 00:03:43,890 right hand activates part on your left 74 00:03:49,760 --> 00:03:47,190 brain it crosses over and so you're 75 00:03:52,160 --> 00:03:49,770 activating parts of your motor cortex 76 00:03:55,729 --> 00:03:52,170 right up here of your left side of your 77 00:03:58,370 --> 00:03:55,739 brain and this causes a change in CBF 78 00:04:01,729 --> 00:03:58,380 stands for cerebral blood flow it 79 00:04:04,880 --> 00:04:01,739 changes the cerebral blood volume oxygen 80 00:04:08,870 --> 00:04:04,890 and venous oxygen and glucose 81 00:04:10,759 --> 00:04:08,880 utilization so all of these things 82 00:04:15,140 --> 00:04:10,769 happen is your change your brain 83 00:04:18,229 --> 00:04:15,150 activation now it also changes the 84 00:04:19,930 --> 00:04:18,239 electrical activity in your brain which 85 00:04:24,060 --> 00:04:19,940 you can measure with 86 00:04:28,290 --> 00:04:24,070 electroencephalography techniques 87 00:04:31,020 --> 00:04:28,300 and so the the technique with functional 88 00:04:34,130 --> 00:04:31,030 MRI is dependent on the fact that we 89 00:04:37,140 --> 00:04:34,140 have an influence of the blood oxygen on 90 00:04:39,240 --> 00:04:37,150 the tissue a signal that we get even 91 00:04:41,880 --> 00:04:39,250 though it's some distant it could be 92 00:04:44,820 --> 00:04:41,890 some distant from the from the blood 93 00:04:47,520 --> 00:04:44,830 vessel so here's the blood vessel in the 94 00:04:50,400 --> 00:04:47,530 brain and we can pick up signal over 95 00:04:52,530 --> 00:04:50,410 here because of the influence of the 96 00:04:57,650 --> 00:04:52,540 oxygen on the water in the tissue over 97 00:05:00,120 --> 00:04:57,660 here okay so one of the first 98 00:05:03,990 --> 00:05:00,130 experiments done with functional MRI was 99 00:05:06,450 --> 00:05:04,000 with photic stimulation and so you can 100 00:05:09,210 --> 00:05:06,460 measure the brain signal say every three 101 00:05:11,700 --> 00:05:09,220 seconds and you keep going beep beep 102 00:05:15,690 --> 00:05:11,710 beep and you go on and then you go off 103 00:05:18,510 --> 00:05:15,700 and you go on I sell off and on and as 104 00:05:21,470 --> 00:05:18,520 you change the stimulus you get a change 105 00:05:25,410 --> 00:05:21,480 in the brain activation as seen by the 106 00:05:27,770 --> 00:05:25,420 mr signal intensity and so we can see 107 00:05:31,110 --> 00:05:27,780 this change and then we can do 108 00:05:33,720 --> 00:05:31,120 statistics to test is this significantly 109 00:05:37,590 --> 00:05:33,730 different than this for all the 110 00:05:41,070 --> 00:05:37,600 different parts of the brain so in 111 00:05:43,440 --> 00:05:41,080 photic stimulation we in this case there 112 00:05:45,990 --> 00:05:43,450 are stimulating for 60 seconds at a time 113 00:05:48,960 --> 00:05:46,000 and then they switch tasks for another 114 00:05:50,940 --> 00:05:48,970 60 seconds and then they switch now 115 00:05:54,180 --> 00:05:50,950 typically we go through about five 116 00:05:56,790 --> 00:05:54,190 cycles of on-off period to get enough 117 00:06:02,370 --> 00:05:56,800 statistics to make a statement about 118 00:06:04,740 --> 00:06:02,380 brain activation so this is an example 119 00:06:08,370 --> 00:06:04,750 of activation with a moving visual 120 00:06:11,400 --> 00:06:08,380 stimulus and so here's here it is in the 121 00:06:14,610 --> 00:06:11,410 back of the brain in the mt region of 122 00:06:20,460 --> 00:06:14,620 the brain v5 these are areas of visual 123 00:06:22,680 --> 00:06:20,470 processing in the brain ok and then to 124 00:06:25,800 --> 00:06:22,690 process the signal we do allow some 125 00:06:28,380 --> 00:06:25,810 problem convolution of the impulse 126 00:06:30,930 --> 00:06:28,390 function in order to process this 127 00:06:33,270 --> 00:06:30,940 because there is a delay so after you 128 00:06:36,510 --> 00:06:33,280 get a stimulus there is a delay of about 129 00:06:37,010 --> 00:06:36,520 five seconds between the onset of the 130 00:06:43,339 --> 00:06:37,020 stimuli 131 00:06:46,279 --> 00:06:43,349 and the change in the bold signal ok so 132 00:06:49,249 --> 00:06:46,289 the temporal resolution is limiting in 133 00:06:52,369 --> 00:06:49,259 fMRI that's one of the limitations and 134 00:06:55,309 --> 00:06:52,379 that's why we like both f MRI and EEG 135 00:06:59,360 --> 00:06:55,319 because the temporal resolution is very 136 00:07:04,309 --> 00:06:59,370 slow in fMRI but the spatial resolution 137 00:07:06,409 --> 00:07:04,319 is very good so we like to do both f MRI 138 00:07:09,439 --> 00:07:06,419 and EEG because we get the best of both 139 00:07:15,740 --> 00:07:09,449 worlds the spatial resolution with fMRI 140 00:07:20,510 --> 00:07:15,750 and the temporal resolution with EEG ok 141 00:07:23,149 --> 00:07:20,520 now we use software developed by a group 142 00:07:27,140 --> 00:07:23,159 and Oxford called FSL so we have 143 00:07:31,240 --> 00:07:27,150 software developed to do the statistics 144 00:07:34,490 --> 00:07:31,250 of the brain signal and we can measure 145 00:07:38,629 --> 00:07:34,500 single-subject statistics and we can do 146 00:07:41,749 --> 00:07:38,639 group statistics let me go ok and it's 147 00:07:44,330 --> 00:07:41,759 called the GLM estimation so we have 148 00:07:47,420 --> 00:07:44,340 this model that we apply to the brain 149 00:07:50,089 --> 00:07:47,430 signal which we use to figure out how 150 00:07:52,760 --> 00:07:50,099 close the model fits with the actual 151 00:07:55,100 --> 00:07:52,770 signal we get from the brain and we use 152 00:07:57,260 --> 00:07:55,110 that model to test every voxel in the 153 00:08:03,140 --> 00:07:57,270 brain to see if there's a significant 154 00:08:07,850 --> 00:08:03,150 activation and we do some 155 00:08:10,909 --> 00:08:07,860 autocorrelation and we and we're able to 156 00:08:13,700 --> 00:08:10,919 get brain activation map in the brain 157 00:08:15,260 --> 00:08:13,710 I'll show you some in a minute but now 158 00:08:16,760 --> 00:08:15,270 we've published a paper in the journal 159 00:08:20,659 --> 00:08:16,770 of alternative and complementary 160 00:08:23,260 --> 00:08:20,669 medicine Genie actor Berg is the first 161 00:08:25,999 --> 00:08:23,270 author on this paper she's from Hawaii 162 00:08:28,969 --> 00:08:26,009 and so is Karen they're both from a why 163 00:08:33,769 --> 00:08:28,979 I'm from Seattle and my job was to 164 00:08:36,800 --> 00:08:33,779 analyze the signal so they sent me the 165 00:08:42,380 --> 00:08:36,810 images that came from the scanner and my 166 00:08:44,860 --> 00:08:42,390 job was to analyze the brain images so 167 00:08:47,840 --> 00:08:44,870 the subjects consisted of 22 168 00:08:48,960 --> 00:08:47,850 participants 11 pairs of healer and 169 00:08:52,949 --> 00:08:48,970 recipients 170 00:08:54,929 --> 00:08:52,959 now in the Big Island of Hawaii they 171 00:08:57,540 --> 00:08:54,939 have these Hawaiian healers that are 172 00:09:00,119 --> 00:08:57,550 gifted these are the gifted Hawaiian 173 00:09:02,040 --> 00:09:00,129 healers and they know how to send their 174 00:09:06,119 --> 00:09:02,050 energy and they know how to influence 175 00:09:09,990 --> 00:09:06,129 their energy for good to heal so Jeannie 176 00:09:13,710 --> 00:09:10,000 is the one who selected these healers to 177 00:09:19,439 --> 00:09:13,720 do this commute this experiment with the 178 00:09:21,290 --> 00:09:19,449 fMRI so in the experimental conditions 179 00:09:24,509 --> 00:09:21,300 the healer was in a control room 180 00:09:27,720 --> 00:09:24,519 physically an optically isolated from 181 00:09:29,699 --> 00:09:27,730 the receiver in the scanner so the 182 00:09:31,769 --> 00:09:29,709 scanner is deep in this tunnel if you 183 00:09:34,650 --> 00:09:31,779 have ever how many of you had an MRI if 184 00:09:36,389 --> 00:09:34,660 you had an MRI it's kind of daunting 185 00:09:40,290 --> 00:09:36,399 because you have to go in this deep 186 00:09:42,660 --> 00:09:40,300 tunnel it's really noisy and you say how 187 00:09:45,269 --> 00:09:42,670 how could you do a brain activation like 188 00:09:49,170 --> 00:09:45,279 this with all this noise how could this 189 00:09:52,400 --> 00:09:49,180 ever work well it does work because you 190 00:09:55,199 --> 00:09:52,410 can you have the on and off stimulus 191 00:09:57,960 --> 00:09:55,209 while the noise is going on so the noise