1 00:00:05,360 --> 00:00:07,360 WELCOME TO THE WEDNESDAY 2 00:00:07,360 --> 00:00:09,520 AFTERNOON LECTURE SERIES. 3 00:00:09,520 --> 00:00:14,200 I'M CHRISTINE HUNTER, THE ACTING 4 00:00:14,200 --> 00:00:15,960 DIRECTOR OF SOCIAL SCIENCE AT 5 00:00:15,960 --> 00:00:16,960 NIH. 6 00:00:16,960 --> 00:00:17,920 I'M THRILLED TO BE INTRODUCED 7 00:00:17,920 --> 00:00:21,400 THE WALS SPEAKER, DAMIEN FAIR, 8 00:00:21,400 --> 00:00:23,480 USING NEUROIMAGING TO 9 00:00:23,480 --> 00:00:24,200 INVESTIGATE A HOST OF CONCERNS 10 00:00:24,200 --> 00:00:26,720 IN COGNITIVE DEVELOPMENT IN 11 00:00:26,720 --> 00:00:27,480 CHILDREN 12 00:00:27,480 --> 00:00:29,640 TODAY'S SEMINAR IS SPECIAL. 13 00:00:29,640 --> 00:00:32,280 THE NIH DIRECTOR'S LECTURES ARE 14 00:00:32,280 --> 00:00:35,400 HAND PICKED BY THE NIH DIRECTOR 15 00:00:35,400 --> 00:00:40,280 MONGS ALL WALS SPEAKERS. 16 00:00:40,280 --> 00:00:41,720 BELIEVING TO BE THE MOST 17 00:00:41,720 --> 00:00:43,120 EXCITING IN THE NATION. 18 00:00:43,120 --> 00:00:45,480 OUR SPEAKER TODAY FITS THAT 19 00:00:45,480 --> 00:00:51,000 DESCRIPTION. 20 00:00:51,000 --> 00:00:52,600 AT THE UNIVERSITY OF MINNESOTA 21 00:00:52,600 --> 00:00:55,640 DR. DAMIEN FAIR IS THE REDLEAF 22 00:00:55,640 --> 00:00:57,800 ENDOWED DIRECTOR AT THE MASONIC 23 00:00:57,800 --> 00:00:58,400 INSTITUTE FOR THE DEVELOPING 24 00:00:58,400 --> 00:01:01,160 BRAIN AND HE IS PROFESSOR AT THE 25 00:01:01,160 --> 00:01:01,800 INSTITUTE OF CHILD DEVELOPMENT 26 00:01:01,800 --> 00:01:04,000 AND THE DEPARTMENT OF 27 00:01:04,000 --> 00:01:04,480 PEDIATRICS. 28 00:01:04,480 --> 00:01:09,800 HIS INTERESTS ARE AUTISM 29 00:01:09,800 --> 00:01:11,040 SPECTRUM, ACHIEVEMENT GAP, CHILD 30 00:01:11,040 --> 00:01:13,920 MENTAL HEALTH TO MENTION A FEW 31 00:01:13,920 --> 00:01:14,120 TALKS. 32 00:01:14,120 --> 00:01:17,880 HIS RESEARCH USING NEUROIMAGING 33 00:01:17,880 --> 00:01:20,600 TO PROBE UNDERLYING BRAIN. 34 00:01:20,600 --> 00:01:26,080 HE USES MRI AND RESTING STATE 35 00:01:26,080 --> 00:01:30,560 MRI TO TEST TYPICAL AND ATYPICAL 36 00:01:30,560 --> 00:01:30,880 POPULATIONS. 37 00:01:30,880 --> 00:01:34,240 THERE ARE VARIOUS MRI TECHNIQUES 38 00:01:34,240 --> 00:01:37,400 IN NEUROPSYCHIATRIC DISORDERS 39 00:01:37,400 --> 00:01:41,920 SUCH AS ATTENTION DEFICIT 40 00:01:41,920 --> 00:01:43,240 HYPERACTIVITY DISORDER. 41 00:01:43,240 --> 00:01:48,080 THE GOAL OF THIS RESEARCH IS 42 00:01:48,080 --> 00:01:49,840 INDIVIDUALIZE PATIENTS TO 43 00:01:49,840 --> 00:01:52,080 DEVELOP DIAGNOSTIC, THERAPEUTIC 44 00:01:52,080 --> 00:01:55,080 STUDIES. 45 00:01:55,080 --> 00:01:58,120 HE RECEIVED HIS DEGREE IN 46 00:01:58,120 --> 00:02:00,720 AUGUSTANA COLLEGE IN SIOUX 47 00:02:00,720 --> 00:02:02,760 FALLS, MINNESOTA. 48 00:02:02,760 --> 00:02:05,880 AND YALE UNIVERSITY OF MEDICINE 49 00:02:05,880 --> 00:02:07,640 GRADUATING IN 2001. 50 00:02:07,640 --> 00:02:10,400 HE REMAINED AT YALE BEFORE 51 00:02:10,400 --> 00:02:12,000 MOVING TO THE WASHINGTON 52 00:02:12,000 --> 00:02:14,880 UNIVERSITY SCHOOL OF MEDICINE IN 53 00:02:14,880 --> 00:02:16,760 ST. LOUIS WHERE HE EARNED HIS 54 00:02:16,760 --> 00:02:18,400 PH.D. IN 2008. 55 00:02:18,400 --> 00:02:20,120 HE ACCEPTED THE POST DOCTORAL 56 00:02:20,120 --> 00:02:23,880 POSITION AT OREGON HEALTH AND 57 00:02:23,880 --> 00:02:25,080 SCIENCE UNIVERSITY AS AN 58 00:02:25,080 --> 00:02:26,520 ASSISTANT AND ASSOCIATE 59 00:02:26,520 --> 00:02:26,800 PROFESSOR. 60 00:02:26,800 --> 00:02:28,760 IN JULY 2020, HE MOVED TO THE 61 00:02:28,760 --> 00:02:30,400 UNIVERSITY OF MINNESOTA TO 62 00:02:30,400 --> 00:02:31,760 ACCEPT HIS CURRENT POSITIONS. 63 00:02:31,760 --> 00:02:34,480 I SHOULD NOTE THAT IN 2018, DR. 64 00:02:34,480 --> 00:02:40,400 FAIR ALSO FOUNDED HIS OWN 65 00:02:40,400 --> 00:02:40,600 COMPANY. 66 00:02:40,600 --> 00:02:44,360 HE IS INVOLVED IN NUMEROUS 67 00:02:44,360 --> 00:02:45,520 EDITORIAL BOARD AND SCIENCE 68 00:02:45,520 --> 00:02:47,200 EDUCATION OUTREACH BOARDS AND 69 00:02:47,200 --> 00:02:48,640 KNOWN AS A WONDERFUL MENTOR. 70 00:02:48,640 --> 00:02:52,480 THE TITLE OF HIS TALK IS THE 71 00:02:52,480 --> 00:02:58,280 FUTURE OF NON-INVASIVE 72 00:02:58,280 --> 00:03:00,240 NEUROIMAGES IN THE ERA OF BIG 73 00:03:00,240 --> 00:03:00,440 DATA. 74 00:03:00,440 --> 00:03:01,320 THANK YOU, DR. FAIR, FOR BEING 75 00:03:01,320 --> 00:03:02,840 WITH US TODAY 76 00:03:02,840 --> 00:03:04,760 THANK YOU ALL FOR HAVING ME. 77 00:03:04,760 --> 00:03:08,360 I'M HONORED TO SPEAK TO YOU 78 00:03:08,360 --> 00:03:09,960 ABOUT SOME OF OUR MOST RECENT 79 00:03:09,960 --> 00:03:10,160 WORK. 80 00:03:10,160 --> 00:03:12,440 I ALWAYS LIKE TO START OFF MY 81 00:03:12,440 --> 00:03:17,240 TALKS BY RECOGNIZING THE MASSIVE 82 00:03:17,240 --> 00:03:22,560 AMOUNTS OF FOLKS AND 83 00:03:22,560 --> 00:03:24,840 COLLABORATION IT TAKES TO DO 84 00:03:24,840 --> 00:03:27,880 WHAT I DO TODAY. 85 00:03:27,880 --> 00:03:29,520 IT IS VERY DIFFERENT WHERE I 86 00:03:29,520 --> 00:03:33,680 TRAINED WHERE A LOT OF EXPERTISE 87 00:03:33,680 --> 00:03:35,600 IS IN ONE LAB. 88 00:03:35,600 --> 00:03:41,160 BECAUSE OF COMPLEXITY OF DATA 89 00:03:41,160 --> 00:03:45,520 AND SYSTEMS IT REQUIRES AN ARMY, 90 00:03:45,520 --> 00:03:49,120 CLINICAL SCIENTISTS, SOCIAL 91 00:03:49,120 --> 00:03:55,800 WORKERS AND INFORMATICISTS AND 92 00:03:55,800 --> 00:03:56,560 PHYSICISTS. 93 00:03:56,560 --> 00:03:58,880 THIS IS A SMALL SAMPLE OF 94 00:03:58,880 --> 00:04:00,600 COLLABORATORS THAT HAVE COME 95 00:04:00,600 --> 00:04:01,920 TOGETHER TO CONDUCT A LOT OF THE 96 00:04:01,920 --> 00:04:05,000 WORK YOU WILL BE HEARING ABOUT 97 00:04:05,000 --> 00:04:05,480 TODAY. 98 00:04:05,480 --> 00:04:08,800 ONE DISCLOSURE WAS ANNOUNCED, I 99 00:04:08,800 --> 00:04:12,720 AM A CO-FOUNDER OF NOWS IMAGING. 100 00:04:12,720 --> 00:04:14,360 I WON'T BE TALKING ABOUT ANY OF 101 00:04:14,360 --> 00:04:16,960 THAT TODAY. 102 00:04:16,960 --> 00:04:18,560 I LIKE TO PUT THAT OUT THERE TO 103 00:04:18,560 --> 00:04:20,560 BE SAFE. 104 00:04:20,560 --> 00:04:22,400 THERE ARE FOUR MAIN GOALS OF THE 105 00:04:22,400 --> 00:04:23,640 TALK TODAY. 106 00:04:23,640 --> 00:04:25,960 ONE IS I WILL BE GOING THROUGH A 107 00:04:25,960 --> 00:04:29,320 BRIEF HISTORY OF COGNITIVE 108 00:04:29,320 --> 00:04:30,400 NEUROSCIENCE, I CONSIDER MYSELF 109 00:04:30,400 --> 00:04:32,480 IN A COGNITIVE NEUROSCIENTIST IN 110 00:04:32,480 --> 00:04:33,560 THE STATE OF OUR FIELD. 111 00:04:33,560 --> 00:04:35,360 I WILL BE TALKING ABOUT OUR NEW 112 00:04:35,360 --> 00:04:36,480 AGE OF BIG DATA. 113 00:04:36,480 --> 00:04:38,360 I PUT IN TWO FORMS, MANY 114 00:04:38,360 --> 00:04:41,320 SUBJECTS AND LESSONS LEARNED 115 00:04:41,320 --> 00:04:41,640 APPLICATIONS. 116 00:04:41,640 --> 00:04:44,840 BIG DATA FEW SUBJECTS, LESSONS 117 00:04:44,840 --> 00:04:46,280 LEARNED AND APPLICATIONS. 118 00:04:46,280 --> 00:04:48,440 AND I WILL END WITH THOUGHTS AND 119 00:04:48,440 --> 00:04:52,080 CONCLUSIONS FOR THE GROUP. 120 00:04:52,080 --> 00:04:53,840 NOW, LIKE I SAID, I CONSIDER 121 00:04:53,840 --> 00:04:55,840 MYSELF A NEUROSCIENTIST. 122 00:04:55,840 --> 00:04:59,000 IT MIGHT BE COGNITIVE 123 00:04:59,000 --> 00:04:59,360 NEUROSCIENTIST. 124 00:04:59,360 --> 00:05:02,640 IT MIGHT BE HARD TO BELIEVE THE 125 00:05:02,640 --> 00:05:04,680 ACTUALLY TERM COGNITIVE 126 00:05:04,680 --> 00:05:07,280 NEUROSCIENTIST BORN OUT OF A 127 00:05:07,280 --> 00:05:09,280 LATE NIGHT CITY TAXI RIDE IN NEW 128 00:05:09,280 --> 00:05:11,200 YORK BY THOSE TWO FOLKS HERE. 129 00:05:11,200 --> 00:05:13,880 THE TERM IS MEANT TO DESCRIBE AN 130 00:05:13,880 --> 00:05:14,800 UNDERSTANDING HOW SPECIFIC 131 00:05:14,800 --> 00:05:17,240 CHARACTERISTICS OF THE PHYSICAL 132 00:05:17,240 --> 00:05:18,600 BRAIN SUPPORT VARIOUS ASPECTS OF 133 00:05:18,600 --> 00:05:23,000 THE MINE. 134 00:05:23,000 --> 00:05:25,600 -- THE MIND. 135 00:05:25,600 --> 00:05:28,720 THE PHRASE EMERGED WITH VERY 136 00:05:28,720 --> 00:05:30,400 BASE NEUROSCIENCE AND 137 00:05:30,400 --> 00:05:30,800 PSYCHOLOGY. 138 00:05:30,800 --> 00:05:32,520 IN THE LAST FIVE DECADES THE 139 00:05:32,520 --> 00:05:37,640 FIELD HAS DEVELOPED IN WAYS ITS 140 00:05:37,640 --> 00:05:38,440 FOUNDERS PROBABLY WOULDN'T 141 00:05:38,440 --> 00:05:38,720 RECOGNIZE. 142 00:05:38,720 --> 00:05:40,680 ONE OF THE ADVANCES THAT REALLY 143 00:05:40,680 --> 00:05:42,960 PUSHED THE FIELD, THAT REALLY, 144 00:05:42,960 --> 00:05:47,480 THE MERGING OF THE FIELD REALLY 145 00:05:47,480 --> 00:05:51,920 BENEFITED FROM IS NON-INVASIVE 146 00:05:51,920 --> 00:05:57,960 IMAGING, P.E.T. IMAGES AND 147 00:05:57,960 --> 00:05:58,160 F.M.R.I. 148 00:05:58,160 --> 00:05:59,920 THE TECHNOLOGIES ESSENTIALLY 149 00:05:59,920 --> 00:06:07,000 CAPITALIZE ON THELIE -- THE 150 00:06:07,000 --> 00:06:09,440 COUPLING OF NEURAL ACTIVITIENED 151 00:06:09,440 --> 00:06:11,120 CHANGES IN THE BLOOD FLOW TO 152 00:06:11,120 --> 00:06:13,480 GIVE US IMAGES INSIDE THE BRAIN 153 00:06:13,480 --> 00:06:14,640 WITHOUT TOUCHING IT. 154 00:06:14,640 --> 00:06:16,280 IT MADE THE GROWTH OF THIS SPACE 155 00:06:16,280 --> 00:06:19,080 OR THIS FIELD REALLY POSSIBLE. 156 00:06:19,080 --> 00:06:22,440 NOW, HERE IS A PICTURE OF A -- 157 00:06:22,440 --> 00:06:25,320 ONE OF MY FIRST STUDIES AS A 158 00:06:25,320 --> 00:06:26,000 GRADUATE STUDENT. 159 00:06:26,000 --> 00:06:30,160 I WAS TRYING TO DO DISSECT 160 00:06:30,160 --> 00:06:34,320 PSYCHOLOGICAL PROCESSES OF 161 00:06:34,320 --> 00:06:37,600 CHILDREN WITH PERINATAL STROKE. 162 00:06:37,600 --> 00:06:39,880 WHEN THEY HAD A STROKE WHEN THEY 163 00:06:39,880 --> 00:06:41,960 WERE FIRST BORN. 164 00:06:41,960 --> 00:06:44,400 AND WHAT WE WERE DOING IS A 165 00:06:44,400 --> 00:06:47,720 TRADITIONAL F.M.R.I. STUDY WHERE 166 00:06:47,720 --> 00:06:50,440 YOU TAKE SEVERAL REPEATED 167 00:06:50,440 --> 00:06:54,760 MEASURES WITHIN AN F.M.R.I. 168 00:06:54,760 --> 00:06:56,360 EXPERIMENT TO DISSECT THESE 169 00:06:56,360 --> 00:06:58,720 SPECIFIC PSYCHOLOGICAL 170 00:06:58,720 --> 00:07:01,360 PROCESSES, IN THIS CASE RELATED 171 00:07:01,360 --> 00:07:04,480 TO LEXICON PROCESSING OR WORD 172 00:07:04,480 --> 00:07:04,760 GENERATION. 173 00:07:04,760 --> 00:07:06,040 NOW, AT THAT TIME -- AND I 174 00:07:06,040 --> 00:07:07,840 PULLED THIS PAPER OUT OF ONE OF 175 00:07:07,840 --> 00:07:10,480 THE PAPERS I READ AS A GRADUATE 176 00:07:10,480 --> 00:07:13,200 STUDENT AND MADE ME SO EXCITED, 177 00:07:13,200 --> 00:07:15,920 THE PROMISE OF THIS NON-INVASIVE 178 00:07:15,920 --> 00:07:18,840 IMAGING, THAT WAS 15 YEARS OLD 179 00:07:18,840 --> 00:07:21,480 OR MAYBE LESS WAS SUPER 180 00:07:21,480 --> 00:07:21,840 PALPABLE. 181 00:07:21,840 --> 00:07:24,200 THIS IS THE EXCITEMENT OF WHAT 182 00:07:24,200 --> 00:07:26,360 YOU COULD POSSIBLY DO WITH THIS 183 00:07:26,360 --> 00:07:27,000 TECHNOLOGY WAS GREAT. 184 00:07:27,000 --> 00:07:32,320 THE DISCUSSIONS OF THE FUTURE OF 185 00:07:32,320 --> 00:07:34,760 FMRI CONJURED UP MIND READING 186 00:07:34,760 --> 00:07:36,800 DEVICES USED AT THE AIRPORT 187 00:07:36,800 --> 00:07:39,360 TERMINAL TO BACK ROOM OF THE 188 00:07:39,360 --> 00:07:41,600 CORPORATE PERSONNEL OFFICE. 189 00:07:41,600 --> 00:07:44,880 ONE RESEARCH FIRM WAS USING FMRI 190 00:07:44,880 --> 00:07:46,480 TO PROBE WHAT CONSUMERS THINK 191 00:07:46,480 --> 00:07:49,080 ABOUT THEIR CLIENT'S PRODUCTS. 192 00:07:49,080 --> 00:07:50,600 THE EXCITEMENT WAS SUPER HIGH. 193 00:07:50,600 --> 00:07:53,240 SINCE THEN WHILE FMRI IS 194 00:07:53,240 --> 00:07:55,920 EXTREMELY VALUABLE IN 195 00:07:55,920 --> 00:07:58,000 CHARACTERIZING BRAIN PATTERNS 196 00:07:58,000 --> 00:07:59,920 AND FUNCTIONAL ACTIVATION 197 00:07:59,920 --> 00:08:02,200 PATTERNS THAT ISOLATE VARIOUS 198 00:08:02,200 --> 00:08:06,280 COGNITIVE PROCESSES I JUST 199 00:08:06,280 --> 00:08:07,760 DESCRIBED, ESSENTIAL A CLINICAL 200 00:08:07,760 --> 00:08:09,640 UTILITY RELATED TO THE EARLY 201 00:08:09,640 --> 00:08:12,080 PROMISE HAS PRIMARILY BEEN 202 00:08:12,080 --> 00:08:15,080 RELEGATED TO PRESURGICAL 203 00:08:15,080 --> 00:08:17,960 PLANNING AND THEN IT IS NOT USED 204 00:08:17,960 --> 00:08:19,600 WIDELY SPREAD IN THOSE DOMAINS. 205 00:08:19,600 --> 00:08:22,640 THE IMPACT HAS BEEN RELATIVELY 206 00:08:22,640 --> 00:08:23,880 SMALL, EVEN THOUGH IT IS A GOOD 207 00:08:23,880 --> 00:08:27,840 FOR A LOT OF THE BASIC SCIENCES. 208 00:08:27,840 --> 00:08:29,320 THAT'S 95. 209 00:08:29,320 --> 00:08:33,440 THIS GUY BY THE NAME OF BRIAN 210 00:08:33,440 --> 00:08:34,960 BISWAL LOOKED AT A DIFFERENT WAY 211 00:08:34,960 --> 00:08:38,920 OF EXAMINING THIS TYPE OF FMRI. 212 00:08:38,920 --> 00:08:40,600 INSTEAD OF DOING A TASK IN THE 213 00:08:40,600 --> 00:08:43,360 SCANNER LOOKING AT PSYCHOLOGICAL 214 00:08:43,360 --> 00:08:45,040 PROCESSES, HE EXAMINED THE BRAIN 215 00:08:45,040 --> 00:08:47,080 WHEN IT WAS AT REST, NOT DOING 216 00:08:47,080 --> 00:08:48,400 ANYTHING AT ALL. 217 00:08:48,400 --> 00:08:50,600 THE SAME SYSTEMS THAT ARE 218 00:08:50,600 --> 00:08:53,880 ACTIVATED DOING A TASK ARE 219 00:08:53,880 --> 00:08:55,080 OSCILLATING WITH EACH OTHER WHEN 220 00:08:55,080 --> 00:08:56,880 YOU ARE AT REST, NOT DOING 221 00:08:56,880 --> 00:08:57,840 ANYTHING AT ALL. 222 00:08:57,840 --> 00:09:00,520 WHAT THIS TOLD US IS A LOT OF 223 00:09:00,520 --> 00:09:02,640 THE ORGANIZATIONAL FEATURES THAT 224 00:09:02,640 --> 00:09:04,480 MAY EXIST WHEN YOU ARE SEEN 225 00:09:04,480 --> 00:09:07,760 DOING A TRADITIONAL FMRI 226 00:09:07,760 --> 00:09:09,320 EXPERIENCE CAN TELL US ABOUT 227 00:09:09,320 --> 00:09:11,080 SIMPLE BRAIN ORGANIZATION. 228 00:09:11,080 --> 00:09:12,880 BY THIS RESULT, KIND OF LAY 229 00:09:12,880 --> 00:09:15,520 DORMANT IN THE FIELD FOR MANY 230 00:09:15,520 --> 00:09:15,720 YEARS. 231 00:09:15,720 --> 00:09:17,640 IT REALLY TOOK OFF IN 2005. 232 00:09:17,640 --> 00:09:21,400 BY THIS PAPER BY MY PEER, ONE OF 233 00:09:21,400 --> 00:09:24,360 MY STUDENT PEERS AT THE TIME, 234 00:09:24,360 --> 00:09:26,400 MICHAEL FOX, IN THE LABORATORY 235 00:09:26,400 --> 00:09:28,600 OF -- WHERE HE USED THIS 236 00:09:28,600 --> 00:09:30,480 TECHNOLOGY TO HIGHLIGHT HOW 237 00:09:30,480 --> 00:09:32,280 THESE VERY LARGE SCALE SYSTEMS 238 00:09:32,280 --> 00:09:34,320 AND HOW THEY ARE COUNTERBALANCED 239 00:09:34,320 --> 00:09:40,880 WITH OTHER SYSTEMS EXIST IN THE 240 00:09:40,880 --> 00:09:43,320 BRAIN? 241 00:09:43,320 --> 00:09:44,960 THIS TECHNOLOGY REALLY TOOK 242 00:09:44,960 --> 00:09:45,240 OFF. 243 00:09:45,240 --> 00:09:46,520 IN FACT, WELL, I WILL TALK ABOUT 244 00:09:46,520 --> 00:09:48,440 THIS PART IN A SECOND. 245 00:09:48,440 --> 00:09:50,840 NOW, MY INITIATE FORRAY INTO 246 00:09:50,840 --> 00:09:53,200 THIS WAS BASICALLY FROM THIS 247 00:09:53,200 --> 00:09:55,760 TRADITIONAL FMRI STUDY, TRYING 248 00:09:55,760 --> 00:09:58,000 TO IDENTIFY PARTS OF THE BRAIN 249 00:09:58,000 --> 00:10:00,640 THAT WERE REALLY IMPORTANT FOR 250 00:10:00,640 --> 00:10:03,440 COORDINATING INPUTS, SENSORY 251 00:10:03,440 --> 00:10:05,520 INPUTS THAT COME IN AND OUTPUTS, 252 00:10:05,520 --> 00:10:08,440 HOW WE RESPOND TO THOSE TYPES OF 253 00:10:08,440 --> 00:10:08,680 OUTPUTS. 254 00:10:08,680 --> 00:10:10,720 WE ARE TRYING TO IDENTIFY WHICH 255 00:10:10,720 --> 00:10:13,600 PARTS OF THE BRAIN ARE IMPORTANT 256 00:10:13,600 --> 00:10:16,720 FOR COORDINATING THAT 257 00:10:16,720 --> 00:10:17,040 INFORMATION. 258 00:10:17,040 --> 00:10:19,080 THIS IS ABFMRI STUDY, THESE 259 00:10:19,080 --> 00:10:21,560 BRAIN REGIONS WERE ACTIVE WITH 260 00:10:21,560 --> 00:10:22,760 ANY TASK YOU DO. 261 00:10:22,760 --> 00:10:24,680 WE THOUGHT THIS WAS A NETWORK 262 00:10:24,680 --> 00:10:27,160 IMPORTANT FOR THAT FEATURE. 263 00:10:27,160 --> 00:10:28,320 I STOPPED MY INITIATE 264 00:10:28,320 --> 00:10:30,760 EXPERIMENTS AND STARTED TO DO 265 00:10:30,760 --> 00:10:32,960 THESE CONDUCTIVITY EXPERIMENTS 266 00:10:32,960 --> 00:10:34,400 TO SEE IF THESE PARTS OF THE 267 00:10:34,400 --> 00:10:37,480 BRAIN ARE WHAT WE CALLED 268 00:10:37,480 --> 00:10:38,360 FUNCTIONALLY CONNECTED, TALKING 269 00:10:38,360 --> 00:10:39,880 TO EACH OTHER. 270 00:10:39,880 --> 00:10:43,280 THIS PAPER SHOWING FUNCTIONAL 271 00:10:43,280 --> 00:10:44,480 CONNECTIVITY RESULT THAT IS 272 00:10:44,480 --> 00:10:47,560 TRUE, THESE PARTS OF THE BRAIN 273 00:10:47,560 --> 00:10:50,360 WERE TALKING TO EACH OTHER AT 274 00:10:50,360 --> 00:10:53,120 REST NOT ONLY IN TASKS. 275 00:10:53,120 --> 00:10:56,120 THAT TOOK OFF IN MY OWN FORRAY 276 00:10:56,120 --> 00:10:57,320 TO UNDERSTAND BRAIN 277 00:10:57,320 --> 00:10:57,640 ORGANIZATION. 278 00:10:57,640 --> 00:11:00,440 I WAS A BRIGHT EYED AND BUSHY 279 00:11:00,440 --> 00:11:01,960 TAILED GRADUATE STUDENT AT THE 280 00:11:01,960 --> 00:11:02,440 TIME. 281 00:11:02,440 --> 00:11:04,080 I REALIZED IF I WANTED TO 282 00:11:04,080 --> 00:11:05,600 UNDERSTAND THIS SYSTEM HERE WITH 283 00:11:05,600 --> 00:11:07,440 THIS SEED REGION HERE, I COULD 284 00:11:07,440 --> 00:11:10,640 DO THAT WITH A REGION OVER HERE 285 00:11:10,640 --> 00:11:12,640 OR HERE, I COULD DO IT ALMOST 286 00:11:12,640 --> 00:11:12,880 ANYWHERE. 287 00:11:12,880 --> 00:11:15,440 THAT IS EXACTLY WHAT WE DID. 288 00:11:15,440 --> 00:11:18,160 WE HAD BRAIN MAPS OF EVERYTHING 289 00:11:18,160 --> 00:11:21,640 ALL OVER THE LAB, REALLY UP SET 290 00:11:21,640 --> 00:11:22,800 FOLKS SITTING AROUND US. 291 00:11:22,800 --> 00:11:25,800 WE NEEDED TO FIGURE OUT HOW TO 292 00:11:25,800 --> 00:11:26,640 CONDENSE THAT INFORMATION. 293 00:11:26,640 --> 00:11:30,520 WE APPLIED ALL THESE MAPS TO 294 00:11:30,520 --> 00:11:31,920 GRAPH SERIES. 295 00:11:31,920 --> 00:11:35,800 OLAF SPORNS, CALLED THE 296 00:11:35,800 --> 00:11:37,000 ORGANIZATION DEVELOPMENT OF 297 00:11:37,000 --> 00:11:38,360 COMPLEX BRAIN NETWORKS. 298 00:11:38,360 --> 00:11:41,000 THE IDEA OF GRAPH THEORY. 299 00:11:41,000 --> 00:11:44,160 GRAPH THEORY IS SIMPLY DESCRIBES 300 00:11:44,160 --> 00:11:46,320 A SET OF NODES, THAT NODES CAN 301 00:11:46,320 --> 00:11:48,800 BE ANYTHING FROM PEOPLE TO 302 00:11:48,800 --> 00:11:50,880 LOCATIONS OR WEBPAGES THAT ARE 303 00:11:50,880 --> 00:11:52,640 LINKED BY SOME LINE OR EDGE. 304 00:11:52,640 --> 00:11:55,280 THAT WOULD BE LIKE FRIENDS 305 00:11:55,280 --> 00:11:57,360 BETWEEN PEOPLE, ROADS BETWEEN 306 00:11:57,360 --> 00:11:59,520 CITIES OR LOCATIONS OR LINKING 307 00:11:59,520 --> 00:12:01,920 BETWEEN WEBPAGES. 308 00:12:01,920 --> 00:12:04,120 AND THERE'S LOTS OF DIFFERENT 309 00:12:04,120 --> 00:12:05,840 TYPES OF MEASURES THAT COME OUT 310 00:12:05,840 --> 00:12:08,400 OF THIS TYPE OF MATHEMATICS, BUT 311 00:12:08,400 --> 00:12:10,800 ONE THAT IS REALLY STAYED TRUE 312 00:12:10,800 --> 00:12:13,000 IS THE IDEA OF NETWORKS OR 313 00:12:13,000 --> 00:12:14,720 MODULES WHERE WE TRY TO IDENTIFY 314 00:12:14,720 --> 00:12:16,640 SPECIFIC LOCATIONS IN THE BRAIN 315 00:12:16,640 --> 00:12:19,000 THAT ARE MORE HIGHLY CONNECTED 316 00:12:19,000 --> 00:12:22,160 WITH EACH OTHER THAN OTHER 317 00:12:22,160 --> 00:12:22,360 PARTS. 318 00:12:22,360 --> 00:12:24,120 THERE IS MORE INTRACOMMUNITY 319 00:12:24,120 --> 00:12:26,120 EDGES WITH ONE SPECIFIC -- THESE 320 00:12:26,120 --> 00:12:28,480 REGIONS IN THE BRAIN RELATIVE TO 321 00:12:28,480 --> 00:12:31,640 THE INTERCOMMUNITY EDGES WITH 322 00:12:31,640 --> 00:12:33,600 OTHER REGIONS OF THE BRAIN. 323 00:12:33,600 --> 00:12:35,800 THIS WORKED OVER TIME, OVER THE 324 00:12:35,800 --> 00:12:37,640 COURSE OF THE LAST DECADE AND A 325 00:12:37,640 --> 00:12:39,760 HALF HAVE LED TO MANY 326 00:12:39,760 --> 00:12:43,880 FUNDAMENTAL PROPERTIES OF BRAIN 327 00:12:43,880 --> 00:12:46,440 ORGANIZATION, THAT HAS TAUGHT US 328 00:12:46,440 --> 00:12:49,640 HOW THE BRAIN IS ORGANIZED AND 329 00:12:49,640 --> 00:12:51,800 RELATED TO BRAIN CONDITIONS AND 330 00:12:51,800 --> 00:12:52,840 NEUROLOGICAL DISORDERS. 331 00:12:52,840 --> 00:12:55,880 AND THOUGHTS AROUND THE CLINICAL 332 00:12:55,880 --> 00:12:58,560 UTILITY AND APPLIED REVOLUTION 333 00:12:58,560 --> 00:13:02,880 OF FMRI, DURING THIS PERIOD OF 334 00:13:02,880 --> 00:13:11,640 TIME, USING NEW TEAK -- 335 00:13:11,640 --> 00:13:15,040 TECHNIQUES RIVALED GENERAL FMRI. 336 00:13:15,040 --> 00:13:17,960 IT HASN'T GOTTEN THERE AND THIS 337 00:13:17,960 --> 00:13:21,840 SHIFT HOW WE CONNECT STUDIES TO 338 00:13:21,840 --> 00:13:22,520 RESTING STUDIES AND STRAIGHT 339 00:13:22,520 --> 00:13:25,320 CHARACTER STUDIES FROM THE MORE 340 00:13:25,320 --> 00:13:26,880 TRADITIONAL PSYCHOLOGICAL 341 00:13:26,880 --> 00:13:28,080 DESTINATIONS SHIFTED THE TYPES 342 00:13:28,080 --> 00:13:29,280 OF QUESTIONS WE WERE ASKING 343 00:13:29,280 --> 00:13:31,520 BECAUSE OF THE EASE OF USE WITH 344 00:13:31,520 --> 00:13:33,440 WHICH WE COULD ACQUIRE THE DATA. 345 00:13:33,440 --> 00:13:35,920 A POTENTIAL ISSUE OVER THAT TIME 346 00:13:35,920 --> 00:13:43,560 IS THE STUDY DESIG 347 00:13:43,560 --> 00:13:43,960 CHA 348 00:13:43,960 --> 00:13:44,160 CHANGED. 349 00:13:44,160 --> 00:13:46,040 ALONG THE WAY OVER THE COURSE OF 350 00:13:46,040 --> 00:13:48,360 FIVE OR SIX OR SEVEN YEARS AS 351 00:13:48,360 --> 00:13:50,160 RESTING STATE FUNCTIONAL 352 00:13:50,160 --> 00:13:52,200 ACTIVITY AND NETWORK NEURAL 353 00:13:52,200 --> 00:13:54,120 SCIENCE HAS EXPANDED TO 354 00:13:54,120 --> 00:13:55,040 UNDERSTAND BRAIN ORGANIZATION 355 00:13:55,040 --> 00:13:57,360 AND DEVELOPMENT, THE DATASETS WE 356 00:13:57,360 --> 00:14:02,200 ARE USING TO STUDY THIS STUFF IS 357 00:14:02,200 --> 00:14:04,240 CHANGING IN SAMPLE SIZE OR 358 00:14:04,240 --> 00:14:10,720 COLLECTION FROM A PRODUCT. 359 00:14:10,720 --> 00:14:14,440 THE PROJECT, THE ABCD STUDY, 360 00:14:14,440 --> 00:14:16,960 SEVEN YEARS AGO, 10,000 PEOPLE, 361 00:14:16,960 --> 00:14:21,560 THE SAMPLE SIZES ARE INCREASING 362 00:14:21,560 --> 00:14:21,880 ENORMOUSLY. 363 00:14:21,880 --> 00:14:23,880 WE ARE STARTING TO SEE A LOT 364 00:14:23,880 --> 00:14:26,400 MORE DATA INSTEAD OF SAMPLE SIZE 365 00:14:26,400 --> 00:14:29,200 INCREASE, THE AMOUNT OF DATA ON 366 00:14:29,200 --> 00:14:31,280 PER SUBJECT BASIS INCREASING 367 00:14:31,280 --> 00:14:34,880 QUITE A BIT. 368 00:14:34,880 --> 00:14:41,120 THE MY CONNECTOME PROJECT FROM 369 00:14:41,120 --> 00:14:42,080 WASHINGTON UNIVERSITY WITH MY 370 00:14:42,080 --> 00:14:43,800 FRIENDS AND COLLEAGUES THERE, 371 00:14:43,800 --> 00:14:46,120 LOTS OF DATA WITHIN PARTICIPANTS 372 00:14:46,120 --> 00:14:48,960 HAS BEEN GROWING QUITE A BIT. 373 00:14:48,960 --> 00:14:51,600 ALONG THAT SAME TIME WE STARTED 374 00:14:51,600 --> 00:14:56,920 SEEING SIGNS OF FAILURES AND 375 00:14:56,920 --> 00:14:59,600 REPRODUCEABILITY HAVE BECOME 376 00:14:59,600 --> 00:15:00,960 MORE APPARENT. 377 00:15:00,960 --> 00:15:04,960 PAPERS ARE LEAKING OUT THAT NOT 378 00:15:04,960 --> 00:15:06,400 PRODUCING IN SUBSEQUENT DATASETS 379 00:15:06,400 --> 00:15:08,880 OR STUDIES, IT IS MORE APPARENT 380 00:15:08,880 --> 00:15:11,320 IT IS COMING ALONGSIDE THESE 381 00:15:11,320 --> 00:15:12,560 CHANGES IN OUR SAMPLE SIZE IN 382 00:15:12,560 --> 00:15:16,040 THE ERA OF BIG DATA. 383 00:15:16,040 --> 00:15:18,120 SO THE FIELD CONTINUES TO EVOLVE 384 00:15:18,120 --> 00:15:20,320 AS DATA ARE COLLECTED IN BROADER 385 00:15:20,320 --> 00:15:23,240 POPULATIONS AND AT A FASTER RATE 386 00:15:23,240 --> 00:15:25,960 THAN EVER BEFORE. 387 00:15:25,960 --> 00:15:30,000 NETWORK NEUROSCIENCE EXISTING OF 388 00:15:30,000 --> 00:15:33,400 MULTIPLE SYSTEMS TO WITH COMPLEX 389 00:15:33,400 --> 00:15:35,240 BEHAVIOR HAS ADVANCED THE FIELD. 390 00:15:35,240 --> 00:15:37,360 HOWEVER, THE ARRIVAL OF LARGE 391 00:15:37,360 --> 00:15:40,240 DATASETS AND REPEATED SAMPLING 392 00:15:40,240 --> 00:15:41,440 DATASETS ARE HIGHLIGHTS 393 00:15:41,440 --> 00:15:43,400 IMPORTANT LESSONS WITH REGARD TO 394 00:15:43,400 --> 00:15:45,960 HOW WE SHOULD DESIGN EXPERIMENTS 395 00:15:45,960 --> 00:15:47,920 TO MAXIMIZE IMPACT ON DISCOVERY 396 00:15:47,920 --> 00:15:50,440 AND APPLICATIONS AND APPLIED IN 397 00:15:50,440 --> 00:15:53,400 CLINICAL SCIENCES. 398 00:15:53,400 --> 00:15:57,160 I GET TO DESCRIBE THAT NOW. 399 00:15:57,160 --> 00:16:00,360 # THIS IS, ALL THIS IS BEING 400 00:16:00,360 --> 00:16:03,720 DESCRIBED AS ABCD STUDY, A STUDY 401 00:16:03,720 --> 00:16:07,360 OF 10,000 ADOLESCENTS. 402 00:16:07,360 --> 00:16:11,160 WHO WE STARTED SCANNING 9 OR 10 403 00:16:11,160 --> 00:16:12,880 YEARS OLD. 404 00:16:12,880 --> 00:16:14,200 WE FOLLOW THEM FOR NOW ABOUT 405 00:16:14,200 --> 00:16:18,400 FIVE YEARS OVER THE COURSE OF 10 406 00:16:18,400 --> 00:16:19,520 YEARS. 407 00:16:19,520 --> 00:16:20,920 ACROSS A POPULATION-BASE SAMPLE 408 00:16:20,920 --> 00:16:23,960 ACROSS THE U.S. 409 00:16:23,960 --> 00:16:26,760 WE ARE USING DATA THAT HAVE BEEN 410 00:16:26,760 --> 00:16:28,160 PROVIDED, YOU KNOW, FREELY FOR 411 00:16:28,160 --> 00:16:29,960 THE PUBLIC TO BE USED. 412 00:16:29,960 --> 00:16:35,760 THIS ONE IS BY ONE OF THE NOUS 413 00:16:35,760 --> 00:16:38,360 PROFESSORS AT UNIVERSITY OF 414 00:16:38,360 --> 00:16:42,200 MINNESOTA, ERIC FESCO, TO MAKE 415 00:16:42,200 --> 00:16:44,840 USE OF THIS DATA MUCH EASIER. 416 00:16:44,840 --> 00:16:49,120 -- ERIC FECZKO. 417 00:16:49,120 --> 00:16:50,880 THIS CAME OUT IN NATURE AND HAS 418 00:16:50,880 --> 00:16:53,920 CAUSED A BIG STIR BECAUSE IT IS 419 00:16:53,920 --> 00:16:55,040 TELLING US SOME FUNDAMENTAL 420 00:16:55,040 --> 00:16:57,120 ISSUES WE NEED TO HANDLE TO 421 00:16:57,120 --> 00:16:59,680 MAXIMIZE THE UTILITY OF THESE 422 00:16:59,680 --> 00:17:03,520 TECHNIQUES USING NON-INVASIVE 423 00:17:03,520 --> 00:17:06,200 IMAGING TO ITS FULLEST. 424 00:17:06,200 --> 00:17:09,000 IT WAS THOUGHT UP BY AMAZING 425 00:17:09,000 --> 00:17:13,280 COLLEAGUE SCOTT MAREK AND 426 00:17:13,280 --> 00:17:22,640 BRENDEN TERVO-CLEMMENS AND NICO 427 00:17:22,640 --> 00:17:22,880 DOSENBACH. 428 00:17:22,880 --> 00:17:24,440 THE BASIC QUESTION OF THE STUDY 429 00:17:24,440 --> 00:17:25,920 IS THIS. 430 00:17:25,920 --> 00:17:29,920 WHAT ARE THE EFFECT SIZES OF 431 00:17:29,920 --> 00:17:34,200 BRAIN CORRELATION AND 432 00:17:34,200 --> 00:17:35,560 NEUROIMAGING PROVIDE EXPLANATION 433 00:17:35,560 --> 00:17:39,400 FOR REPLICATION FAILURES WE 434 00:17:39,400 --> 00:17:41,880 MIGHT SEE IN BRAINWIDE 435 00:17:41,880 --> 00:17:44,720 ASSOCIATION STUDY AND IF SO, WHY 436 00:17:44,720 --> 00:17:45,720 IS THAT? 437 00:17:45,720 --> 00:17:47,200 THE STUDY WAS DONE IN A FULL 438 00:17:47,200 --> 00:17:50,440 SAMPLE ALL TYPES OF WAYS. 439 00:17:50,440 --> 00:17:52,560 I'M GOING TO SHOW YOU PRIMARILY 440 00:17:52,560 --> 00:17:55,360 THE BASE RESULTS, 400 441 00:17:55,360 --> 00:17:57,520 PARTICIPANTS AND THE CLEANEST 442 00:17:57,520 --> 00:17:59,200 ASPECT OF THE DATA. 443 00:17:59,200 --> 00:18:01,440 USING FUNCTIONAL IMAGING OR 444 00:18:01,440 --> 00:18:07,760 STRUCTURAL IMAGES, MEASURES OF 445 00:18:07,760 --> 00:18:08,520 PSYCHOPATHOLOGY, THE RESULT IS 446 00:18:08,520 --> 00:18:10,920 VERY CLOSELY THE SAME. 447 00:18:10,920 --> 00:18:11,120 OKAY? 448 00:18:11,120 --> 00:18:13,160 NOW, WHAT I'M SHOWING YOU HERE 449 00:18:13,160 --> 00:18:15,680 IS A DISTRIBUTION OF THE EFFECT 450 00:18:15,680 --> 00:18:18,400 SIZES THAT YOU GET FROM THIS 451 00:18:18,400 --> 00:18:23,160 BIG, LARGE STUDY ON MEASURES OF 452 00:18:23,160 --> 00:18:23,640 PSYCHOPATHOLOGY. 453 00:18:23,640 --> 00:18:24,560 THIS IS DISTRIBUTION. 454 00:18:24,560 --> 00:18:26,840 THESE ARE THE EFFECT SIZES AND 455 00:18:26,840 --> 00:18:28,600 THE ANATOMY POPS UP HERE. 456 00:18:28,600 --> 00:18:30,360 THE POINT HERE NO MATTER, 457 00:18:30,360 --> 00:18:32,640 LOOKING AT NETWORKS OR EDGES OR 458 00:18:32,640 --> 00:18:34,920 SPECIFIC COMPONENTS OF THE DATA 459 00:18:34,920 --> 00:18:38,480 IS YOU CAN SEE THE DISTRIBUTION 460 00:18:38,480 --> 00:18:41,280 OF THE EFFECT SIZE LOOKS TO BE 461 00:18:41,280 --> 00:18:43,200 RELATIVELY SMALL. 462 00:18:43,200 --> 00:18:44,840 THIS IS THE INITIATE 463 00:18:44,840 --> 00:18:46,680 CONDUCTIVITY MEASURE. 464 00:18:46,680 --> 00:18:48,840 THIS LOOKS FOR COGNITIVE 465 00:18:48,840 --> 00:18:50,520 ABILITY, DISTRIBUTION A LITTLE 466 00:18:50,520 --> 00:18:51,600 BIGGER, BUT ABOUT THE SAME. 467 00:18:51,600 --> 00:18:53,160 THIS IS LOOKING AT BRAIN 468 00:18:53,160 --> 00:18:56,120 STRUCTURE WITH THE SAME 469 00:18:56,120 --> 00:18:56,920 MEASURES. 470 00:18:56,920 --> 00:18:58,520 THE LARGEST EFFECT SIZE, IF YOU 471 00:18:58,520 --> 00:19:01,480 HAVE A SAMPLE THIS LARGE IS .16. 472 00:19:01,480 --> 00:19:03,080 THE POINT IS THE EFFECT SIZES 473 00:19:03,080 --> 00:19:06,640 THAT WE ARE SEEING HERE ON THE 474 00:19:06,640 --> 00:19:10,040 RELATIONSHIPS ARE RELATIVELY 475 00:19:10,040 --> 00:19:10,560 SMALL. 476 00:19:10,560 --> 00:19:12,920 NOW, DOES THE RELIANCE ON THIS 477 00:19:12,920 --> 00:19:14,520 TYPICAL NEUROIMAGING SAMPLE 478 00:19:14,520 --> 00:19:16,080 SIZES PROVIDE A REASON WHY YOU 479 00:19:16,080 --> 00:19:21,040 MIGHT SEE IN SOME CASES AN 480 00:19:21,040 --> 00:19:24,880 EXPLANATION OR REPLICATING 481 00:19:24,880 --> 00:19:27,120 PROBLEM IN BWAS. 482 00:19:27,120 --> 00:19:28,840 THE SAMPLING VARIABILITY TELLS 483 00:19:28,840 --> 00:19:32,920 YOU HOW MUCH AN EFFECT SIZE 484 00:19:32,920 --> 00:19:34,040 VARIES BETWEEN DIFFERENT 485 00:19:34,040 --> 00:19:34,240 SAMPLES. 486 00:19:34,240 --> 00:19:35,440 SCOTT LIKES TO SAY IT IS 487 00:19:35,440 --> 00:19:37,440 SOMETHING YOU HAVE DONE IN YOUR 488 00:19:37,440 --> 00:19:39,560 TRADITIONAL EARLY STATISTICS 101 489 00:19:39,560 --> 00:19:42,480 COURSES, BUT IT IS SUBJECTIVELY 490 00:19:42,480 --> 00:19:44,320 BORING, RARELY CONSIDERED, BUT 491 00:19:44,320 --> 00:19:46,280 IS EXTREMELY IMPORTANT NO MATTER 492 00:19:46,280 --> 00:19:48,520 WHAT TYPE OF DATA WE ARE LOOKING 493 00:19:48,520 --> 00:19:48,680 AT. 494 00:19:48,680 --> 00:19:49,600 THIS IS AN EXAMPLE. 495 00:19:49,600 --> 00:19:51,400 THE SAME STUDY THAT USUALLY 496 00:19:51,400 --> 00:19:52,320 PROVIDES THE CASE. 497 00:19:52,320 --> 00:19:53,960 WHAT IF I WAS TRYING TO 498 00:19:53,960 --> 00:19:57,680 UNDERSTAND THE RELATIONSHIP 499 00:19:57,680 --> 00:20:01,240 BETWEEN AGE, IN THIS CASE YOU 500 00:20:01,240 --> 00:20:03,400 CAN SEE 108 TO 130 MONTHS OF AGE 501 00:20:03,400 --> 00:20:05,240 AND HOW TAL SOMEONE IS? 502 00:20:05,240 --> 00:20:08,680 I CAN GO IN THE ABCD STUDY AND 503 00:20:08,680 --> 00:20:10,080 GET A SAMPLE THAT MAY LOOK LIKE 504 00:20:10,080 --> 00:20:10,360 THIS. 505 00:20:10,360 --> 00:20:13,560 YOU SEE A RELATIONSHIP BETWEEN 506 00:20:13,560 --> 00:20:15,240 HEIGHT AND AGE ABOUT .85. 507 00:20:15,240 --> 00:20:17,120 I CAN GO BACK IN AND DO A 508 00:20:17,120 --> 00:20:18,800 DIFFERENT 25 KIDS AND I MIGHT 509 00:20:18,800 --> 00:20:22,520 SEE A SAMPLE LIKE THIS, WHERE 510 00:20:22,520 --> 00:20:29,240 THERE IS ENOUGH VARABILITY WHERE 511 00:20:29,240 --> 00:20:31,200 THE RELATIONSHIP COULD BE 0. 512 00:20:31,200 --> 00:20:33,640 IF I RESAMPLE AND RESAMPLE AND 513 00:20:33,640 --> 00:20:35,040 RESAMPLE OVER AND OVER AND OVER 514 00:20:35,040 --> 00:20:36,800 AGAIN, THIS IS THE DISTRIBUTION 515 00:20:36,800 --> 00:20:38,560 YOU GET EVEN WITH SOMETHING SO 516 00:20:38,560 --> 00:20:39,960 SIMPLE AS HEIGHT AND AGE. 517 00:20:39,960 --> 00:20:41,760 YOU CAN SEE WITH SMALL SAMPLES 518 00:20:41,760 --> 00:20:44,160 YOU CAN GET ALMOST A PERFECT 519 00:20:44,160 --> 00:20:45,480 RELATIONSHIP BETWEEN HEIGHT AND 520 00:20:45,480 --> 00:20:48,360 AGE, BUT YOU ALSO MAY GET A 521 00:20:48,360 --> 00:20:51,160 RELATIONSHIP BETWEEN 0 OR EVEN 522 00:20:51,160 --> 00:20:52,440 NEGATIVE BETWEEN THOSE TWO 523 00:20:52,440 --> 00:20:54,720 VARIABLES. 524 00:20:54,720 --> 00:20:57,240 IT IS ONLY WHEN YOU -- INSTEAD 525 00:20:57,240 --> 00:20:59,600 OF SAMPLING 25 SUBJECTS AT THE 526 00:20:59,600 --> 00:21:07,960 TIME, 500, 1,000 SUBJECTS AT A 527 00:21:07,960 --> 00:21:11,600 TIME YOU GET THE TRUE EFFECT THE 528 00:21:11,600 --> 00:21:14,240 CORRELATION OF ABOUT .5. 529 00:21:14,240 --> 00:21:17,040 INCREASING SAMPLE SIZE IS 530 00:21:17,040 --> 00:21:22,680 DECREASING SAMPLING 531 00:21:22,680 --> 00:21:23,280 VARIABLEABILITY. 532 00:21:23,280 --> 00:21:24,720 IT IS A DIFFERENT SOURCE OF 533 00:21:24,720 --> 00:21:29,960 ERROR WE SEE IN OUR FIELD. 534 00:21:29,960 --> 00:21:32,160 METHODS OF VARABILITY, PREBIAS, 535 00:21:32,160 --> 00:21:35,320 HEAD MOTION AND STUFF LIKE THAT. 536 00:21:35,320 --> 00:21:37,960 WHAT DOES THIS MEAN FOR SMALL 537 00:21:37,960 --> 00:21:39,600 SAMPLE STUDIES? 538 00:21:39,600 --> 00:21:40,960 IT IS PRETTY SIMPLE. 539 00:21:40,960 --> 00:21:43,760 IF I HAVE ONE LAB DOING A STUDY 540 00:21:43,760 --> 00:21:46,640 ON NEUROIMAGING AND STRUCTURE 541 00:21:46,640 --> 00:21:49,080 AND COGNITIVE ABILITY ARE 542 00:21:49,080 --> 00:21:51,920 RELATIVELY SMALL AND THEY DO A 543 00:21:51,920 --> 00:21:54,600 SAMPLE OF 25 PARTICIPANTS, THEY 544 00:21:54,600 --> 00:21:56,720 DO EVERYTHING PERFECTLY RIGHT 545 00:21:56,720 --> 00:21:58,520 AND THEY MIGHT FIND A 546 00:21:58,520 --> 00:21:59,560 RELATIONSHIP THAT IS HIGH, 547 00:21:59,560 --> 00:22:01,200 STRONG AND POSITIVE. 548 00:22:01,200 --> 00:22:04,080 I MIGHT GO WITH MY LAB AND DO 549 00:22:04,080 --> 00:22:06,280 THE EXACT SAME EXPERIMENT, GET A 550 00:22:06,280 --> 00:22:11,800 SAMPLE OF 25 PARTICIPANTS FOR MY 551 00:22:11,800 --> 00:22:12,480 CORD HERE. 552 00:22:12,480 --> 00:22:14,320 I WOULD GET A COMPLETELY 553 00:22:14,320 --> 00:22:15,720 OPPOSITE EFFECT. 554 00:22:15,720 --> 00:22:22,160 THIS IS JUST TO SHOW THAT SAME 555 00:22:22,160 --> 00:22:24,280 SCENARIO COULD HAPPEN ANY WAY 556 00:22:24,280 --> 00:22:25,960 YOU CUT THE DATA. 557 00:22:25,960 --> 00:22:27,680 THIS BY ITSELF IS NOT 558 00:22:27,680 --> 00:22:29,920 NECESSARILY A HUE AMONG GOUS 559 00:22:29,920 --> 00:22:31,080 PROBLEM, BUT BECAUSE OF OUR 560 00:22:31,080 --> 00:22:34,720 CULTURE AND THE WAY WE PUBLISH 561 00:22:34,720 --> 00:22:36,560 FINDINGS, IT TURNS OUT TO BE A 562 00:22:36,560 --> 00:22:38,200 VERY BIG ONE. 563 00:22:38,200 --> 00:22:40,080 THIS IS A DISTRIBUTION, A FIGURE 564 00:22:40,080 --> 00:22:44,200 THAT HIGHLIGHTS THE DISTRIBUTION 565 00:22:44,200 --> 00:22:51,240 FROM 1 MILLION MED VALUES FROM Z 566 00:22:51,240 --> 00:22:51,800 LIFE. 567 00:22:51,800 --> 00:22:53,320 THIS IS THE SAME PICTURE HOW 568 00:22:53,320 --> 00:22:56,320 PEOPLE WERE DESCRIBING IT ON 569 00:22:56,320 --> 00:22:56,560 TWITTER. 570 00:22:56,560 --> 00:22:59,840 BECAUSE OF THE WAY WE PUBLISH 571 00:22:59,840 --> 00:23:00,920 RESULTS ONLY SIGNIFICANT THINGS 572 00:23:00,920 --> 00:23:03,480 GET PUBLISHED AND NOT VALUING 573 00:23:03,480 --> 00:23:05,840 NULL FINDINGS, THE DISTRIBUTION 574 00:23:05,840 --> 00:23:06,640 GETS SKEWED. 575 00:23:06,640 --> 00:23:09,320 THAT MEANS IF PEOPLE ARE ONLY 576 00:23:09,320 --> 00:23:10,360 PUBLISHING THE SIGNIFICANT 577 00:23:10,360 --> 00:23:13,160 RESULTS FROM SMALL SAMPLES, THE 578 00:23:13,160 --> 00:23:15,960 LITERATURE WILL BE RIPE WITH 579 00:23:15,960 --> 00:23:18,360 INFLATED EFFECTS BECAUSE YOU 580 00:23:18,360 --> 00:23:22,040 CAN'T DO A META ANALYSIS WITHOUT 581 00:23:22,040 --> 00:23:23,840 THE NULL TO GET THE TRUE EFFECT 582 00:23:23,840 --> 00:23:24,240 SIZE. 583 00:23:24,240 --> 00:23:27,560 THIS IS A BIG PROBLEM AND PART 584 00:23:27,560 --> 00:23:29,080 OF OUR STRUCTURE AND 585 00:23:29,080 --> 00:23:30,280 INSTITUTIONS FUNCTION THAT ARE 586 00:23:30,280 --> 00:23:32,360 ASSISTING WITH US BEING FOOLED A 587 00:23:32,360 --> 00:23:34,480 LITTLE BIT ON TRUE EFFECT SIZES. 588 00:23:34,480 --> 00:23:36,720 SO THE OBSERVED EFFECT SIZES, IF 589 00:23:36,720 --> 00:23:42,680 YOU ARE GETTING IT RIGHT FROM 590 00:23:42,680 --> 00:23:53,200 THE FIRST TIME CONSORTIA-LEVEL 591 00:23:53,760 --> 00:23:55,600 DATA ARE REQUIRED. 592 00:23:55,600 --> 00:23:56,880 SO DOES THIS PROVIDE IS 593 00:23:56,880 --> 00:23:58,440 EXPLANATION FOR REPLICATION 594 00:23:58,440 --> 00:23:59,760 FAILURES YOU MIGHT SEE IN THE 595 00:23:59,760 --> 00:24:01,120 LITERATURE AND IF SO, WHY? 596 00:24:01,120 --> 00:24:11,520 THE ANSWER IS YES. -- 597 00:24:56,960 --> 00:24:59,880 THIS IS NOT AN FMRI STUDY. 598 00:24:59,880 --> 00:25:01,840 IT IS A STUDY DESCRIBING OUR 599 00:25:01,840 --> 00:25:02,160 DATA. 600 00:25:02,160 --> 00:25:04,960 THE SAME FINDINGS HAVE BEEN 601 00:25:04,960 --> 00:25:05,880 FOUND WITH THE BEHAVIORAL DATA 602 00:25:05,880 --> 00:25:07,840 IN SOME OF THESE STUDIES. 603 00:25:07,840 --> 00:25:10,120 ONE OF THE THINGS THIS OFTEN 604 00:25:10,120 --> 00:25:11,520 REMINDS US OF AND WE ARE 605 00:25:11,520 --> 00:25:13,320 LEARNING LESSONS FROM IS 606 00:25:13,320 --> 00:25:13,680 GENETICS. 607 00:25:13,680 --> 00:25:16,640 THIS IS A CRITICAL REVIEW OF 608 00:25:16,640 --> 00:25:18,440 GENETICS FROM ABOUT 10 YEARS 609 00:25:18,440 --> 00:25:18,640 AGO. 610 00:25:18,640 --> 00:25:20,640 I DIDN'T PULL IT OUT BECAUSE IT 611 00:25:20,640 --> 00:25:24,200 WAS THE BEST PAPER AT THE TIME 612 00:25:24,200 --> 00:25:27,320 AT THIS PAPER, BUT IT HAD GOOD 613 00:25:27,320 --> 00:25:28,320 ILLUSTRATIONS THAT DESCRIBE THE 614 00:25:28,320 --> 00:25:31,320 ISSUE THAT GENETICS WAS HAVING 615 00:25:31,320 --> 00:25:32,360 ABOUT OVER A DECADE AGO. 616 00:25:32,360 --> 00:25:34,080 THIS IS A CRITICAL REVIEW OF THE 617 00:25:34,080 --> 00:25:38,040 FIRST 10 YEARS OF CANDIDATE JEAN 618 00:25:38,040 --> 00:25:44,240 BY ENVIRONMENTAL RESEARCH AND 619 00:25:44,240 --> 00:25:44,600 PSYCHIATRY. 620 00:25:44,600 --> 00:25:47,080 THIS IS A SAMPLE SIZE AND THIS 621 00:25:47,080 --> 00:25:49,680 IS POWER AND THE DIFFERENT 622 00:25:49,680 --> 00:25:51,840 COLORS ARE DIFFERENT, YOU KNOW, 623 00:25:51,840 --> 00:25:54,120 MODERATE, LARGE, AND VERY LARGE 624 00:25:54,120 --> 00:25:54,360 EFFECTS. 625 00:25:54,360 --> 00:25:56,960 THE SAMPLE SIZE IS REQUIRED TO 626 00:25:56,960 --> 00:26:00,760 HIT A CERTAIN LEVEL OF POWER. 627 00:26:00,760 --> 00:26:02,800 WHAT YOU CAN SEE HERE IS UNLESS 628 00:26:02,800 --> 00:26:05,280 YOU HAVE EXTREMELY LARGE EFFECT 629 00:26:05,280 --> 00:26:10,000 SIZES, RIGHT, THAT IN THESE 630 00:26:10,000 --> 00:26:11,960 CANDIDATE GENE STUDIES, YOU NEED 631 00:26:11,960 --> 00:26:13,640 THOUSANDS OF PARTICIPANTS TO 632 00:26:13,640 --> 00:26:16,080 HAVE ENOUGH POWER TO SEE A TRUE 633 00:26:16,080 --> 00:26:16,320 EFFECT. 634 00:26:16,320 --> 00:26:20,280 DOWN HERE YOU SEE AT THE TIME 635 00:26:20,280 --> 00:26:22,320 WHAT THE PUBLISHED SAMPLE SIZES, 636 00:26:22,320 --> 00:26:23,160 HIGHLIGHTING THE DISTRIBUTIONS 637 00:26:23,160 --> 00:26:25,240 WAY ON THE END HERE AND LIKELY 638 00:26:25,240 --> 00:26:35,800 NOT LARGE ENOUGH TO GET PROPER 639 00:26:39,160 --> 00:26:39,640 POWER TO SEE TRUE EFFECTS. 640 00:26:39,640 --> 00:26:40,200 WHICH IS LEADING TO SOME 641 00:26:40,200 --> 00:26:40,720 REPLICATION ERRORS THERE. 642 00:26:40,720 --> 00:26:41,400 THIS NEW ERA OF BIG DATA OR SOME 643 00:26:41,400 --> 00:26:42,840 PARTS OF IMAGING AND SMALL 644 00:26:42,840 --> 00:26:44,800 EFFECTS ARE RECALIBRATION OF 645 00:26:44,800 --> 00:26:45,840 EFFECTS AND GROUNDBREAKING 646 00:26:45,840 --> 00:26:48,160 FINDINGS IS ACTUALLY REALLY 647 00:26:48,160 --> 00:26:48,760 IMPORTANT. 648 00:26:48,760 --> 00:26:51,160 NOW, OF COURSE, IN THE GENETICS 649 00:26:51,160 --> 00:26:54,400 WORLD, IN THE GWAS WORLD, THE 650 00:26:54,400 --> 00:26:55,800 WORK DIDN'T STOP, RIGHT? 651 00:26:55,800 --> 00:26:59,240 THE WORK WENT ON AND THE FIELD 652 00:26:59,240 --> 00:27:01,480 GOT VERY CREATIVE ABOUT HOW TO 653 00:27:01,480 --> 00:27:04,000 HANDLE THE RELATIONSHIPS OF SOME 654 00:27:04,000 --> 00:27:05,960 OF OUR GENES AND COMPLEX 655 00:27:05,960 --> 00:27:07,960 BEHAVIORS IN SMALL EFFECTS. 656 00:27:07,960 --> 00:27:12,880 THEY STARTED DOING LOTS OF 657 00:27:12,880 --> 00:27:23,080 MULTIVARIATE 658 00:27:52,000 --> 00:27:54,760 IT IS STARTING TO USE SOME OF 659 00:27:54,760 --> 00:27:57,440 THE LESSONS LEARNED THAT APPLY 660 00:27:57,440 --> 00:27:59,080 TO MIRROR IMAGING. 661 00:27:59,080 --> 00:28:01,120 IN THIS CASE I'M GIVING YOU ONE 662 00:28:01,120 --> 00:28:03,800 BRIEF EXAMPLE OF HOW WE CAN 663 00:28:03,800 --> 00:28:06,680 HIGHLIGHTING HOW WE CAN LEVERAGE 664 00:28:06,680 --> 00:28:09,120 BIG STUDIES LIKE ABCD STUDIES 665 00:28:09,120 --> 00:28:17,480 AND USING A SAMPLE OF ABOUT 666 00:28:17,480 --> 00:28:20,800 480ADHD, GENERATING POLYRISK 667 00:28:20,800 --> 00:28:27,600 SCORES FOR THE POLYGENIC RISK 668 00:28:27,600 --> 00:28:29,080 SCORES AROUND EXECUTIVE FUNCTION 669 00:28:29,080 --> 00:28:36,480 AND MOBILITY. 670 00:28:36,480 --> 00:28:37,600 HAVING AN OPPORTUNITY TO EXPLAIN 671 00:28:37,600 --> 00:28:40,440 COMPLEX BEHAVIORS EVEN IN ADHD 672 00:28:40,440 --> 00:28:41,600 SYMPTOMS WHICH WE ARE SHOWING 673 00:28:41,600 --> 00:28:42,000 HERE. 674 00:28:42,000 --> 00:28:48,600 WHAT IS INTERESTING AND IS 675 00:28:48,600 --> 00:28:51,480 REALLY IMPORTANT, IN ORDER TO 676 00:28:51,480 --> 00:28:57,640 GET EFFECTS, THERE IS LOTS OF 677 00:28:57,640 --> 00:28:58,760 VARIABILITY IN THE BRAIN. 678 00:28:58,760 --> 00:29:01,240 WHAT YOU REALIZE IS SOME OF OUR 679 00:29:01,240 --> 00:29:07,120 THEORIES AROUND SPECIFIC 680 00:29:07,120 --> 00:29:09,840 NETWORKS OR SPECIFIC CIRCUITS 681 00:29:09,840 --> 00:29:11,920 BEING HIGHLY RELATED, THAT WE 682 00:29:11,920 --> 00:29:15,080 ARE SEEING NOW, THAT IN ESSENCE, 683 00:29:15,080 --> 00:29:16,840 DISTRIBUTIONS OF CIRCUITS ACROSS 684 00:29:16,840 --> 00:29:18,760 THE ENTIRE BRAIN THAT SEEM TO BE 685 00:29:18,760 --> 00:29:20,760 MOST HIGHLY CONTRIBUTING TO 686 00:29:20,760 --> 00:29:23,000 DISORDERS LIKE ADHD. 687 00:29:23,000 --> 00:29:25,400 WHICH IS A COMPLETELY NEW TREND 688 00:29:25,400 --> 00:29:27,960 OR NEW DIRECTION AND WAY TO 689 00:29:27,960 --> 00:29:37,360 THINK ABOUT BRAIN ORGANIZE AND 690 00:29:37,360 --> 00:29:43,000 COMPLEX DISORDERS LIKE ADHD. 691 00:29:43,000 --> 00:29:46,560 THERE ARE SOME IMPORTANT THINGS 692 00:29:46,560 --> 00:29:48,960 WE NEED TO NOT DUPLICATING. 693 00:29:48,960 --> 00:29:51,000 WE NEED TO MAKE SURE THEY ARE 694 00:29:51,000 --> 00:29:54,760 MAX MALI INCLUSIVE, WHICH IS 695 00:29:54,760 --> 00:29:55,040 CRITICAL. 696 00:29:55,040 --> 00:29:56,200 WE HAVE ESSENTIALLY LEARNED FROM 697 00:29:56,200 --> 00:30:01,360 THE GENETICS WORLD THAT NOT 698 00:30:01,360 --> 00:30:04,920 BEING MAXIMUM INCLUSIVE CAN LEAD 699 00:30:04,920 --> 00:30:07,120 TO HIGHER OR LOWER PREDICTIONS. 700 00:30:07,120 --> 00:30:09,920 THE ERA OF BIG DATA HAS NOT BEEN 701 00:30:09,920 --> 00:30:15,560 KIND TO THE SHIFTS IN OUR STUDY 702 00:30:15,560 --> 00:30:16,520 DESIGNS AND DEVELOPMENTAL 703 00:30:16,520 --> 00:30:17,960 NEUROSCIENCE AND IMAGING, 704 00:30:17,960 --> 00:30:20,000 BUILDING OFF THE GROWING PAINS 705 00:30:20,000 --> 00:30:24,360 IN GENETICS AND MULTIVARIATE 706 00:30:24,360 --> 00:30:26,640 WAYS TO LOOK AT THE DATA SEEMED 707 00:30:26,640 --> 00:30:28,280 IMPORTANT TO MOVE IN THE 708 00:30:28,280 --> 00:30:29,880 DIRECTION OF POPULATION STUDIES. 709 00:30:29,880 --> 00:30:31,760 THE WORK IS RESOURCE INTENSETIVE 710 00:30:31,760 --> 00:30:33,000 AND CAN'T BE NECESSARILY 711 00:30:33,000 --> 00:30:34,720 CONDUCTED BY ONE GROUP ALONE 712 00:30:34,720 --> 00:30:37,520 WHICH REQUIRES LOTS OF 713 00:30:37,520 --> 00:30:39,360 COLLABORATION, WAYS TO RETHINK 714 00:30:39,360 --> 00:30:48,360 OF HOW WE ARE DOING OUR WORK. 715 00:30:48,360 --> 00:30:52,960 JUST LIKE SOME OF THESE GWAS, IT 716 00:30:52,960 --> 00:30:54,840 IS ENTRY INTO DIRECT CLINICAL 717 00:30:54,840 --> 00:30:56,720 UTILITY IS LIKELY TO TAKE SOMEM 718 00:30:56,720 --> 00:30:56,800 TI 719 00:30:56,800 --> 00:30:58,760 THERE IS MAYBE A SHORTER AVENUE 720 00:30:58,760 --> 00:31:06,120 INTO THAT SPACE WHICH IS REALLY 721 00:31:06,120 --> 00:31:08,600 BEEN A HUGE SHIFT, BIG DATA, FEW 722 00:31:08,600 --> 00:31:16,080 SUBJECTS AND LESSONS LEARNED 723 00:31:16,080 --> 00:31:17,120 APPLICATIONS. 724 00:31:17,120 --> 00:31:19,160 IT IS VAST OR WIDESPREAD. 725 00:31:19,160 --> 00:31:20,800 EVERYONE HAS HAD AN MRI OR KNOW 726 00:31:20,800 --> 00:31:23,320 OF IT IN CLINICAL APPLICATIONS. 727 00:31:23,320 --> 00:31:25,880 THE QUESTION IS HOW DID THAT 728 00:31:25,880 --> 00:31:28,120 HAPPEN AND WHY HASN'T FUNCTIONAL 729 00:31:28,120 --> 00:31:31,280 BRAIN IMAGING FOLLOWED 730 00:31:31,280 --> 00:31:33,120 TRADITIONAL IMAGING? 731 00:31:33,120 --> 00:31:34,360 STRUCTURAL MRI IN INDIVIDUALS 732 00:31:34,360 --> 00:31:36,640 CAN BE USED EFFECTIVELY TO 733 00:31:36,640 --> 00:31:38,400 DETECT VARIATIONS FROM PERSON TO 734 00:31:38,400 --> 00:31:42,040 PERSON, TUMORS, SWELLING, 735 00:31:42,040 --> 00:31:44,040 INFLAMMATION, STROKE, OTHER 736 00:31:44,040 --> 00:31:44,280 AILMENTS. 737 00:31:44,280 --> 00:31:46,440 IT CAN ASSIST IN ADJUSTING 738 00:31:46,440 --> 00:31:46,720 TREATMENT. 739 00:31:46,720 --> 00:31:51,120 THE EFFORT TO COLLECT THE DATA 740 00:31:51,120 --> 00:31:53,920 IS NOT SUPER LOW, BUT IT IS NOT 741 00:31:53,920 --> 00:31:55,200 UNTENABLE, SO IT IS RELATIVELY 742 00:31:55,200 --> 00:32:00,200 LOW IN A PATIENT. 743 00:32:00,200 --> 00:32:02,920 IN MANY CASES SOME SORT OF 744 00:32:02,920 --> 00:32:03,240 INTERVENTION. 745 00:32:03,240 --> 00:32:04,600 NOW, THE MAJORITY OF THE WORK 746 00:32:04,600 --> 00:32:05,560 TRYING TO UNDERSTOOD THE 747 00:32:05,560 --> 00:32:07,280 TOPOLOGY OF THE BRAIN AND 748 00:32:07,280 --> 00:32:09,240 NETWORK ORGANIZATION USING SOME 749 00:32:09,240 --> 00:32:11,600 OF THESE TECHNIQUES LIKE 750 00:32:11,600 --> 00:32:12,520 FUNCTIONAL CONNECTIVE MRI IS 751 00:32:12,520 --> 00:32:14,200 BASED ON THE AVERAGE. 752 00:32:14,200 --> 00:32:24,720 THE SIGNAL TO NOISE IS SO LOW 753 00:33:11,840 --> 00:33:14,360 ALL THE 14 HOURS OF DATA WITH 754 00:33:14,360 --> 00:33:16,280 ONE INDIVIDUAL WHAT IT LOOKED 755 00:33:16,280 --> 00:33:18,440 LIKE IN THIS INDIVIDUAL AND THE 756 00:33:18,440 --> 00:33:18,840 GROUP AVERAGE. 757 00:33:18,840 --> 00:33:20,880 HERE IS A PICTURE BELOW AND WHAT 758 00:33:20,880 --> 00:33:23,040 YOU CAN SEE IS THE PATTERNS, THE 759 00:33:23,040 --> 00:33:24,560 GENERAL PATTERNS YOU SEE IN THE 760 00:33:24,560 --> 00:33:26,640 GROUP STRUCTURE IS MAINTAINED, 761 00:33:26,640 --> 00:33:29,120 OKAY, BUT LOTS OF SPECIFIC 762 00:33:29,120 --> 00:33:31,040 PATTERNS THAT EXIST WITHIN THIS 763 00:33:31,040 --> 00:33:31,600 INDIVIDUAL. 764 00:33:31,600 --> 00:33:34,000 MEANING THERE'S LOTS OF 765 00:33:34,000 --> 00:33:36,120 DEVIATION FROM THE GROUP IN MANY 766 00:33:36,120 --> 00:33:36,320 WAYS. 767 00:33:36,320 --> 00:33:38,640 LOTS OF THESE ISLANDS AND 768 00:33:38,640 --> 00:33:40,440 SPECIFIC CHARACTERISTICS THAT 769 00:33:40,440 --> 00:33:41,080 EXIST IN THIS INDIVIDUAL 770 00:33:41,080 --> 00:33:43,320 RELATIVE TO OTHERS. 771 00:33:43,320 --> 00:33:45,360 NOW, THAT WAS THOUGHT UP BY 772 00:33:45,360 --> 00:33:47,600 ANOTHER EXPERIMENT CALLED THE 773 00:33:47,600 --> 00:33:49,840 MIDNIGHT SCAN CLUB, STARTED BY 774 00:33:49,840 --> 00:33:54,360 OUR OWN STEVE NELSON AT THE 775 00:33:54,360 --> 00:33:58,240 UNIVERSITY OF MINNESOTA AND NICO 776 00:33:58,240 --> 00:33:59,400 DOSENBACH, TO COLLECT FIVE 777 00:33:59,400 --> 00:34:00,240 HOURS, 10 PEOPLE. 778 00:34:00,240 --> 00:34:03,600 IT WAS CALLED THE MIDNIGHT 779 00:34:03,600 --> 00:34:05,480 SCANNING CLUB DATA BECAUSE THEY 780 00:34:05,480 --> 00:34:07,360 WERE VERY POOR AND THE ONLY TIME 781 00:34:07,360 --> 00:34:10,240 THEY COULD GET CHEAP SCANNING IS 782 00:34:10,240 --> 00:34:10,560 MIDNIGHT. 783 00:34:10,560 --> 00:34:12,080 $25 AN HOUR. 784 00:34:12,080 --> 00:34:14,120 SO THEY STARTED SCANNING FOLKS 785 00:34:14,120 --> 00:34:16,960 TO GET FOUR HOURS OF DATA IN THE 786 00:34:16,960 --> 00:34:18,400 MIDDLE OF THE NIGHT SO THEY 787 00:34:18,400 --> 00:34:19,200 COULD AFFORD IT. 788 00:34:19,200 --> 00:34:21,400 THAT IS WHY IT IS CALLED THE 789 00:34:21,400 --> 00:34:24,000 MIDNIGHT SCANNING CLUB. 790 00:34:24,000 --> 00:34:27,200 THIS PAPER HIGHLIGHTED PERSON TO 791 00:34:27,200 --> 00:34:29,400 PERSON TO PERSON THE GENERAL 792 00:34:29,400 --> 00:34:30,800 STRUCTURE IS THERE, THE 793 00:34:30,800 --> 00:34:31,840 SPECIFICS IN BRAIN ORGANIZATION 794 00:34:31,840 --> 00:34:33,640 IS HIGHLY UNIQUE. 795 00:34:33,640 --> 00:34:35,560 NOW, WHAT WE'VE LEARNED FROM 796 00:34:35,560 --> 00:34:36,800 THIS DATA COLLECTION, WE HAVE 797 00:34:36,800 --> 00:34:38,760 HOURS OF DATA ON THIS PERSON IS 798 00:34:38,760 --> 00:34:41,120 THE RELIABILITY AND SIGNAL TO 799 00:34:41,120 --> 00:34:43,160 NOISE IN FUNCTIONAL MRI CAN BE 800 00:34:43,160 --> 00:34:45,200 JUST AS HIGH IN STRUCTURAL MRI 801 00:34:45,200 --> 00:34:45,480 AS WELL. 802 00:34:45,480 --> 00:34:49,360 HERE IS A CASE OF A CHILD OR AN 803 00:34:49,360 --> 00:34:53,480 ADOLESCENT WHO CAME INTO NICO'S 804 00:34:53,480 --> 00:34:55,480 OFFICE WHO IS A STARTING PITCHER 805 00:34:55,480 --> 00:34:57,720 ON HIS BASEBALL TEAM WHO WAS 806 00:34:57,720 --> 00:35:00,120 HAVING SOME HEADACHES AND HAD 807 00:35:00,120 --> 00:35:04,640 TURNED OUT HAD A VERY LARGE 808 00:35:04,640 --> 00:35:09,480 MASSIVE PERINATAL STROKE THE KID 809 00:35:09,480 --> 00:35:11,880 AND THE FAMILY DIDN'T KNOW 810 00:35:11,880 --> 00:35:12,320 EXISTED. 811 00:35:12,320 --> 00:35:15,720 USING THIS TYPE OF IMAGING, YOU 812 00:35:15,720 --> 00:35:18,720 CAN IDENTIFY VERY PRECISELY, 813 00:35:18,720 --> 00:35:20,840 HIGHLY RELIABLE, EXACTLY HOW 814 00:35:20,840 --> 00:35:23,880 ORGANIZATION TO BE A STARTING 815 00:35:23,880 --> 00:35:26,040 PITCHER CAN BE ORGANIZED IN THIS 816 00:35:26,040 --> 00:35:28,080 PARTICULAR CHILD RELATIVE TO 817 00:35:28,080 --> 00:35:30,800 TYPICAL CONTROLS, WHAT MAKES HIS 818 00:35:30,800 --> 00:35:31,480 FUNCTION ACTUALLY FUNCTION THIS 819 00:35:31,480 --> 00:35:33,120 WAY? 820 00:35:33,120 --> 00:35:39,560 IN A WAY THAT IS HIGHLY PRECISE 821 00:35:39,560 --> 00:35:40,880 WITH HIGH --. 822 00:35:40,880 --> 00:35:42,880 NOW YOU HAVE THIS WAY WHERE YOU 823 00:35:42,880 --> 00:35:44,960 CAN KNOCK OFF AT LEAST ONE OF 824 00:35:44,960 --> 00:35:46,680 THESE ISSUES THAT MADE 825 00:35:46,680 --> 00:35:48,920 TRADITIONAL MRI FEASIBLE IN 826 00:35:48,920 --> 00:35:49,920 CLINICAL SETTINGS. 827 00:35:49,920 --> 00:35:53,760 ANOTHER EXPERIMENT, IN THIS CASE 828 00:35:53,760 --> 00:35:56,400 NOW, IN ESSENCE, CASTING AN ARM, 829 00:35:56,400 --> 00:35:58,160 DOING A SPECIFIC INTERVENTION 830 00:35:58,160 --> 00:36:04,000 WITH FMRI, INDUCING SENSORY 831 00:36:04,000 --> 00:36:05,360 DEPRIVATION, AND MOTOR 832 00:36:05,360 --> 00:36:08,200 DEPRIVATION IN THREE INDIVIDUALS 833 00:36:08,200 --> 00:36:10,360 WHERE YOU CAST AN ARM, THEIR 834 00:36:10,360 --> 00:36:12,040 DOMINANT ARM AND YOU DO THAT 835 00:36:12,040 --> 00:36:13,800 CASTING FOR TWO WEEKS. 836 00:36:13,800 --> 00:36:17,280 YOU DO REPEATED SAMPLING OF THE 837 00:36:17,280 --> 00:36:20,240 SCANNING 45 TO 65 TIMES TO GET 838 00:36:20,240 --> 00:36:21,480 ENORMOUS AMOUNTS OF DATA WITH 839 00:36:21,480 --> 00:36:21,760 INDIVIDUALS. 840 00:36:21,760 --> 00:36:24,080 ALL OF A SUDDEN YOU CAN SEE 841 00:36:24,080 --> 00:36:27,520 EXACTLY HOW THE BRAIN IS 842 00:36:27,520 --> 00:36:38,080 REORGANIZING DURING A SPECIFIC 843 00:37:40,880 --> 00:37:44,040 A PERFECT CIRCUIT REQUIRED FOR 844 00:37:44,040 --> 00:37:45,200 IMPROVED TREATMENT IN 845 00:37:45,200 --> 00:37:46,640 DEPRESSION, WITH PRECISION 846 00:37:46,640 --> 00:37:57,200 MAPPING THAT YOU GET IMPROVED, 847 00:38:00,640 --> 00:38:01,080 YOU GET IMPROVED OUTCOMES. 848 00:38:01,080 --> 00:38:01,720 YOU CAN TAILOR YOUR INTERVENTION 849 00:38:01,720 --> 00:38:02,320 TO BE ABLE TO IMPROVE ON THE 850 00:38:02,320 --> 00:38:02,920 TREATMENT AS LONG AS YOU HAVE 851 00:38:02,920 --> 00:38:03,520 THE DATA THAT IS NECESSARY TO 852 00:38:03,520 --> 00:38:04,160 GET THE RIGHT LOCATION FOR THE 853 00:38:04,160 --> 00:38:04,920 TARGETING AS OPPOSED TO WHAT IS 854 00:38:04,920 --> 00:38:08,400 CURRENTLY DONE, WHICH IS JUST 855 00:38:08,400 --> 00:38:10,240 ONE SIZE FITS ALL LOCATION FOR 856 00:38:10,240 --> 00:38:10,440 FOLKS. 857 00:38:10,440 --> 00:38:13,000 NOW YOU HAVE A WAY WHERE YOU CAN 858 00:38:13,000 --> 00:38:14,120 NOW USE THE TECHNIQUE TO ADJUST 859 00:38:14,120 --> 00:38:15,640 TREATMENT. 860 00:38:15,640 --> 00:38:16,560 THE PROBLEM, OF COURSE, IS THE 861 00:38:16,560 --> 00:38:17,000 LAST ONE. 862 00:38:17,000 --> 00:38:19,400 THE EFFORT IS LOW ON COLLECTION 863 00:38:19,400 --> 00:38:20,960 IN THE PATIENT. 864 00:38:20,960 --> 00:38:21,160 RIGHT? 865 00:38:21,160 --> 00:38:23,520 IF YOU NEED TO GET FIVE TO 14 866 00:38:23,520 --> 00:38:26,640 HOURS OF DATA IN A GIVEN PERSON, 867 00:38:26,640 --> 00:38:30,560 YOU -- IT IS GOING TO BE HARD TO 868 00:38:30,560 --> 00:38:32,040 DEPLOY THIS IN A WAY THAT WOULD 869 00:38:32,040 --> 00:38:35,040 BE USEFUL IN A CLINICAL SETTING. 870 00:38:35,040 --> 00:38:37,000 WELL, IN FACT, LIKE I SAID, IN 871 00:38:37,000 --> 00:38:39,840 ORDER TO EVEN GET 90% 872 00:38:39,840 --> 00:38:41,200 RELIABILITY IN THE CASE FROM 873 00:38:41,200 --> 00:38:43,200 SOME OF THESE EARLY PAPERS, WE 874 00:38:43,200 --> 00:38:44,880 NEED UPWARDS OF AN HOUR TO TWO 875 00:38:44,880 --> 00:38:48,120 HOURS OF DATA. 876 00:38:48,120 --> 00:38:50,040 NOW, THERE'S LOTS OF EFFORTS 877 00:38:50,040 --> 00:39:00,560 THAT HAVE BEEN GOING ON HERE, 878 00:39:01,040 --> 00:39:05,680 CONNOR LYNCH'S LAB IS DOING THIS 879 00:39:05,680 --> 00:39:06,320 WORK. 880 00:39:06,320 --> 00:39:07,880 WE ARE TRYING TO WORK TO CHANGE 881 00:39:07,880 --> 00:39:09,400 THE WAY WE COLLECT THE DATA. 882 00:39:09,400 --> 00:39:11,520 THIS IS SOME OF THIS, THIS IS 883 00:39:11,520 --> 00:39:15,120 WORK STARTED OUT OF NIH. 884 00:39:15,120 --> 00:39:16,400 TO REDUCE THE AMOUNT OF TIME 885 00:39:16,400 --> 00:39:18,160 THAT IS REQUIRED TO GET THAT 886 00:39:18,160 --> 00:39:21,080 LEVEL OF RELIABILITY. 887 00:39:21,080 --> 00:39:22,480 EVEN DOWN TO 15 MINUTES OF DATA 888 00:39:22,480 --> 00:39:29,960 COLLECTION. 889 00:39:29,960 --> 00:39:32,080 WE ARE NOW WORKING ON HUMAN 890 00:39:32,080 --> 00:39:33,560 FUNCTIONAL BRAIN NETWORKS MAY 891 00:39:33,560 --> 00:39:35,400 HELP WITH SOME OF THESE ISSUES, 892 00:39:35,400 --> 00:39:37,080 EVEN WHEN YOU DON'T HAVE ACCESS 893 00:39:37,080 --> 00:39:38,520 TO AN MRI. 894 00:39:38,520 --> 00:39:41,680 HERE IS JUST A PICTURE. 895 00:39:41,680 --> 00:39:44,480 200 SUBJECTS FROM THE ABCD 896 00:39:44,480 --> 00:39:46,720 STUDY, APPLYING PRECISION 897 00:39:46,720 --> 00:39:48,480 MAPPING FROM PERSON TO PERSON, 898 00:39:48,480 --> 00:39:50,080 THE SAME TRENDS HOLD. 899 00:39:50,080 --> 00:39:53,360 I PUT A BOX AROUND THE DLPFC, 900 00:39:53,360 --> 00:39:56,080 AROUND THE AREA YOU WOULD WANT 901 00:39:56,080 --> 00:39:57,760 TO TARGET FOR THE TREATMENT 902 00:39:57,760 --> 00:39:58,600 RESISTANT DEPRESSION. 903 00:39:58,600 --> 00:40:00,520 AND HIGHLIGHTING THE VARIABILITY 904 00:40:00,520 --> 00:40:02,440 YOU CAN SEE FROM PERSON TO 905 00:40:02,440 --> 00:40:02,640 PERSON. 906 00:40:02,640 --> 00:40:04,280 BUT IT IS ALSO BECAUSE WE KNOW 907 00:40:04,280 --> 00:40:05,920 THERE ARE SOME CHARACTERISTICS 908 00:40:05,920 --> 00:40:07,000 SIMILAR FROM PERSON TO PERSON, 909 00:40:07,000 --> 00:40:09,280 YOU CAN SEE IT AS WE ARE LOOKING 910 00:40:09,280 --> 00:40:10,840 HERE. 911 00:40:10,840 --> 00:40:13,280 WE MIGHT BE ABLE TO LEVERAGE 912 00:40:13,280 --> 00:40:15,080 THAT TECHNIQUE TO IDENTIFY AT 913 00:40:15,080 --> 00:40:25,520 LEAST A PROBLEM ACCESS 914 00:41:04,680 --> 00:41:06,800 TO MRI YOU WANT TO DO A 915 00:41:06,800 --> 00:41:09,040 TREATMENT IN THIS CASE AND DON'T 916 00:41:09,040 --> 00:41:14,880 HAVE ACCESS TO MRI TO IMPROVE. 917 00:41:14,880 --> 00:41:16,960 THESE HAVE SHOWN HIGHER ABILITY. 918 00:41:16,960 --> 00:41:20,560 THIS IS A COMPARISON OF LOOKING 919 00:41:20,560 --> 00:41:26,960 AT THESE DATA WITH THESE 920 00:41:26,960 --> 00:41:28,920 PROBABLISTIC AND GROUP SETS THAT 921 00:41:28,920 --> 00:41:31,160 ARE HIGHLY COMMON IN THE FIELD. 922 00:41:31,160 --> 00:41:34,240 AND, AGAIN, JUST HIGHLIGHTING 923 00:41:34,240 --> 00:41:35,480 RELATIVE TO THESE COMMON 924 00:41:35,480 --> 00:41:38,600 DATASETS THAT THE RELIABILITY OF 925 00:41:38,600 --> 00:41:42,440 THE FINDINGS INCREASE QUITE A 926 00:41:42,440 --> 00:41:48,080 BIT USING THESE PROBABLISTIC 927 00:41:48,080 --> 00:41:50,080 MAPS AND STUDIES IN THE FIELD. 928 00:41:50,080 --> 00:41:51,520 IN THIS LAST SLIDE I'M GOING TO 929 00:41:51,520 --> 00:41:54,000 SHOW YOU HERE IS JUST, AGAIN, 930 00:41:54,000 --> 00:41:56,800 POINTING OUT THAT FOR, IN THE 931 00:41:56,800 --> 00:41:58,600 CASE OF TREATMENT RESISTANT 932 00:41:58,600 --> 00:41:59,720 DEPRESSION, WE ARE ESSENTIALLY 933 00:41:59,720 --> 00:42:02,200 TRYING TO HIT A CIRCUIT IN AN 934 00:42:02,200 --> 00:42:03,840 INDIVIDUAL THAT TARGETS THE SUB 935 00:42:03,840 --> 00:42:04,360 GENERAL ZONE. 936 00:42:04,360 --> 00:42:06,880 AT LEAST THAT IS ONE OF THE 937 00:42:06,880 --> 00:42:07,280 THEORIES. 938 00:42:07,280 --> 00:42:11,400 AND USING THESE PROBABLISTIC 939 00:42:11,400 --> 00:42:12,960 TARGETS, 10 SUBJECTS ACROSS 940 00:42:12,960 --> 00:42:16,200 ADULTS AND KIDS, SHOWING ABILITY 941 00:42:16,200 --> 00:42:18,000 TO HIT THE SUB GENERAL ZONE 942 00:42:18,000 --> 00:42:20,960 QUITE EASILY WITH THIS 943 00:42:20,960 --> 00:42:22,040 PROBABLISTIC TARGET AND MOVING 944 00:42:22,040 --> 00:42:24,760 SLIGHTLY AWAY FROM THAT TARGET 945 00:42:24,760 --> 00:42:26,600 SHOWS MORE VARIABILITY IN YOUR 946 00:42:26,600 --> 00:42:29,360 ABILITY TO HIT THE PRECISE ZONE. 947 00:42:29,360 --> 00:42:31,440 LOTS OF POTENTIAL FOR USING 948 00:42:31,440 --> 00:42:35,320 THESE TYPES OF TECHNIQUES AND 949 00:42:35,320 --> 00:42:37,920 DATA SOURCES FOR LOW RESOURCE 950 00:42:37,920 --> 00:42:41,720 SETTINGS IN CASES YOU CAN'T 951 00:42:41,720 --> 00:42:42,040 OBTAIN AN MRI. 952 00:42:42,040 --> 00:42:44,440 SO THAT'S THE LAST LITTLE BIT, 953 00:42:44,440 --> 00:42:47,040 WHICH PUTS US ON A REALLY GOOD 954 00:42:47,040 --> 00:42:48,560 FOOTING FOR THE FUTURE. 955 00:42:48,560 --> 00:42:51,440 SO WITH THE RIGHT CONDITIONS, 956 00:42:51,440 --> 00:42:54,880 FMRI, CONDUCTIVITY MRI, CAN BE 957 00:42:54,880 --> 00:42:57,440 HIGHLY RELIABLE IN LARGE SUBJECT 958 00:42:57,440 --> 00:42:58,600 EFF 959 00:42:58,600 --> 00:43:00,680 EFFECTS, STUDIES TO MONITOR 960 00:43:00,680 --> 00:43:03,720 EFFICACY FOR TARGETING CERTAIN 961 00:43:03,720 --> 00:43:05,080 INTERVENTIONS IN THE CASE 962 00:43:05,080 --> 00:43:07,000 EXAMPLES I GAVE WITH 963 00:43:07,000 --> 00:43:09,760 NEUROMODULATION OR DETAILED 964 00:43:09,760 --> 00:43:11,880 ASPECTS OF THE THE 965 00:43:11,880 --> 00:43:13,760 NEUROPHYSIOLOGY ARE OBTAINABLE 966 00:43:13,760 --> 00:43:15,200 IN SMALL SAMPLES AS LONG AS THE 967 00:43:15,200 --> 00:43:16,320 DATA ARE BEING COLLECTED IN THE 968 00:43:16,320 --> 00:43:17,240 RIGHT WAY. 969 00:43:17,240 --> 00:43:19,000 NOW WE UNDERSTAND THE PARAMETERS 970 00:43:19,000 --> 00:43:29,080 ON HOW TO CONDUCT THESE RELIABLE 971 00:43:29,080 --> 00:43:31,480 REPLICATING STUDIES, WE WILL 972 00:43:31,480 --> 00:43:34,080 MASSIVELY CELEBRATE 973 00:43:34,080 --> 00:43:36,120 SIGNIFICANTLY IN THE NEXT DECADE 974 00:43:36,120 --> 00:43:37,280 AS LONG AS WE ARE THINKING, ALL 975 00:43:37,280 --> 00:43:39,240 OF OUR INSTITUTIONS, INCLUDING 976 00:43:39,240 --> 00:43:43,120 THE SCIENTISTS, THE FUNDERS, THE 977 00:43:43,120 --> 00:43:45,640 JOURNAL EDITORS, THAT WE ARE ALL 978 00:43:45,640 --> 00:43:46,720 THINKING ABOUT THIS STUFF IN THE 979 00:43:46,720 --> 00:43:47,440 RIGHT WAY. 980 00:43:47,440 --> 00:43:54,000 THERE IS A REALLY NICE PAPER BY 981 00:43:54,000 --> 00:44:01,120 KATARINA GRATTON, STEVE NELSON, 982 00:44:01,120 --> 00:44:02,840 GORDON ON THESE DIFFERENT ROADS 983 00:44:02,840 --> 00:44:07,040 TO TAKE TO DO HIGHLY RELIABLE 984 00:44:07,040 --> 00:44:09,440 SUCCESSFUL STUDIES. 985 00:44:09,440 --> 00:44:12,520 FOR FOLKS WHO DO MRIs, I WOULD 986 00:44:12,520 --> 00:44:13,520 SUGGEST THE READ. 987 00:44:13,520 --> 00:44:22,800 AT THE END, I'M GOING TO GO OVER 988 00:44:22,800 --> 00:44:23,920 SOMETHING THAT DOES USUALLY LEAD 989 00:44:23,920 --> 00:44:25,000 TO INTERESTING DISCUSSION. 990 00:44:25,000 --> 00:44:27,320 ONE OF THE THINGS WE DO IN THE 991 00:44:27,320 --> 00:44:30,280 BUSINESS WORLD. 992 00:44:30,280 --> 00:44:30,600 O 993 00:44:30,600 --> 00:44:33,640 I'M NOT IN THE BUSINESS WORLD, 994 00:44:33,640 --> 00:44:37,760 BUT I FOLLOW AND PLAY ONE ON TV. 995 00:44:37,760 --> 00:44:39,640 STRENGTHS, WEAKNESSES, 996 00:44:39,640 --> 00:44:41,120 OPPORTUNITIES AND THREATS TO 997 00:44:41,120 --> 00:44:42,560 SMAK SURE YOU HAVE OPTIMAL 998 00:44:42,560 --> 00:44:43,920 STRATEGY FOR STRATEGIC PLAN. 999 00:44:43,920 --> 00:44:45,640 IT IS VERY COMMON. 1000 00:44:45,640 --> 00:44:46,920 YOU LEARN IN BUSINESS SCHOOL 1001 00:44:46,920 --> 00:44:47,120 101. 1002 00:44:47,120 --> 00:44:48,760 WE DON'T TYPICALLY DO THAT IN 1003 00:44:48,760 --> 00:44:50,120 OUR OWN FIELD SO ONE OF THE 1004 00:44:50,120 --> 00:44:52,840 THINGS I HAVE DONE, WE RECENTLY 1005 00:44:52,840 --> 00:44:54,760 PUBLISHED IN ANNUAL REVIEWS IS 1006 00:44:54,760 --> 00:45:00,160 DO A SWAT ANALYSIS IN COGNITIVE 1007 00:45:00,160 --> 00:45:01,760 NEUROSCIENCE AND SCIENCE IN 1008 00:45:01,760 --> 00:45:03,920 GENERAL TO HELP THINK 1009 00:45:03,920 --> 00:45:05,640 STRATEGICALLY ABOUT WHAT WE, 1010 00:45:05,640 --> 00:45:08,000 WHAT ARE OUR STRENGTHS, WHAT ARE 1011 00:45:08,000 --> 00:45:08,640 OUR WEAKNESSES? 1012 00:45:08,640 --> 00:45:11,080 WHAT ARE THE THREATS THAT 1013 00:45:11,080 --> 00:45:12,080 PREVENT TRUE PROGRESS AND 1014 00:45:12,080 --> 00:45:12,880 OPPORTUNITIES WE NEED TO TAKE 1015 00:45:12,880 --> 00:45:13,880 CARE OF. 1016 00:45:13,880 --> 00:45:15,200 WE MIGHT WANT TO TAKE ON. 1017 00:45:15,200 --> 00:45:17,320 SO I'M GOING TO DO THAT LITTLE 1018 00:45:17,320 --> 00:45:17,560 EXERCISE. 1019 00:45:17,560 --> 00:45:20,040 IT IS NOT THE FULL THING, BUT 1020 00:45:20,040 --> 00:45:22,400 YOU WILL GET A SENSE OF WHAT 1021 00:45:22,400 --> 00:45:23,840 SOME OF THOSE THINGS ARE AND 1022 00:45:23,840 --> 00:45:25,560 WITH THE GROUP HERE AND WHAT THE 1023 00:45:25,560 --> 00:45:26,760 FIELD NEEDS TO THINK THROUGH. 1024 00:45:26,760 --> 00:45:28,560 SO STRENGTHS. 1025 00:45:28,560 --> 00:45:30,040 SO ONE IS THAT WE, PARTICULARLY 1026 00:45:30,040 --> 00:45:32,320 IN OUR FIELD, THERE IS A GROWING 1027 00:45:32,320 --> 00:45:34,560 NUMBER OF SCIENTIFIC DISCIPLINES 1028 00:45:34,560 --> 00:45:35,920 IN OUR FIELD. 1029 00:45:35,920 --> 00:45:38,640 WE HAVE NEW ACCESS TO BIG DATA 1030 00:45:38,640 --> 00:45:40,720 RESOURCES AND DATA AND CODE AND 1031 00:45:40,720 --> 00:45:42,400 REALLY A LOT OF INFRASTRUCTURE 1032 00:45:42,400 --> 00:45:45,800 ON COMPUTING HAS BEEN DEVELOPED 1033 00:45:45,800 --> 00:45:48,440 THAT MAKE A LOT OF THE WORK I'M 1034 00:45:48,440 --> 00:45:49,400 TALKING ABOUT TODAY POSSIBLE AT 1035 00:45:49,400 --> 00:45:50,200 ALL. 1036 00:45:50,200 --> 00:45:53,360 THERE IS A TON OF CROSS SPECIES 1037 00:45:53,360 --> 00:45:55,600 WORK TO BRIDGE FINDINGS, 1038 00:45:55,600 --> 00:45:58,040 INDIRECT MEASURE OF NEUROBIOLOGY 1039 00:45:58,040 --> 00:46:01,520 AND THE CIRCUITS DIRECTLY TO THE 1040 00:46:01,520 --> 00:46:02,680 NEUROBIOLOGY THAT EXISTS. 1041 00:46:02,680 --> 00:46:06,400 WE HAVE A LOT OF PUBLIC-PRIVATE 1042 00:46:06,400 --> 00:46:09,360 PARTNERSHIPS AND NON-PROFIT 1043 00:46:09,360 --> 00:46:10,440 ORGANIZATIONS UNDERSTANDING THE 1044 00:46:10,440 --> 00:46:11,800 IMPORTANCE OF NEUROSCIENCE FOR 1045 00:46:11,800 --> 00:46:13,400 OUR EVERYDAY LIVES. 1046 00:46:13,400 --> 00:46:16,800 AND WE HAVE A LOT OF JUNIOR 1047 00:46:16,800 --> 00:46:18,080 INVESTIGATORS WHO APPEAR TO BE 1048 00:46:18,080 --> 00:46:19,480 OPEN TO ENTERTAINING THE 1049 00:46:19,480 --> 00:46:21,360 WEAKNESSES AND THREATS TO OUR 1050 00:46:21,360 --> 00:46:22,800 FIELD THAT IS EXTREMELY 1051 00:46:22,800 --> 00:46:26,960 IMPORTANT FOR OUR FUTURE. 1052 00:46:26,960 --> 00:46:27,320 OKAY. 1053 00:46:27,320 --> 00:46:30,520 SO HOW ABOUT SOME OF THE 1054 00:46:30,520 --> 00:46:30,800 WEAKNESSES? 1055 00:46:30,800 --> 00:46:32,640 THERE'S ALWAYS ISSUES, AND I 1056 00:46:32,640 --> 00:46:34,800 THINK THIS IS WITH EVERY FIELD 1057 00:46:34,800 --> 00:46:37,160 DEPENDING WHERE YOU ARE AT, IN 1058 00:46:37,160 --> 00:46:40,240 PARTICULARLY IN COGNITIVE 1059 00:46:40,240 --> 00:46:42,240 NEUROSCIENCE AND BEHAVIOR AND 1060 00:46:42,240 --> 00:46:43,800 PSYCHOLOGY, THERE IS OFTENTIMES 1061 00:46:43,800 --> 00:46:45,280 ISSUES OF DATA QUALITY THAT 1062 00:46:45,280 --> 00:46:49,760 CONTINUE TO MUTE SOME PROGRESS. 1063 00:46:49,760 --> 00:46:51,200 WE NEED TO CONTINUE TO GET 1064 00:46:51,200 --> 00:46:53,520 BETTER AT THAT. 1065 00:46:53,520 --> 00:46:55,040 A BROADENING OF EXPERTISE AND 1066 00:46:55,040 --> 00:46:57,360 DISCIPLINES IS GREAT FOR 1067 00:46:57,360 --> 00:46:58,720 COGNITIVE NEUROSCIENCE FOLKS 1068 00:46:58,720 --> 00:47:00,400 LIKE ME, BUT MOVES THE FIELD 1069 00:47:00,400 --> 00:47:02,080 AWAY FROM GROUNDING IN 1070 00:47:02,080 --> 00:47:02,400 NEUROSCIENCE. 1071 00:47:02,400 --> 00:47:03,880 IT IS IMPORTANT WE MAINTAIN 1072 00:47:03,880 --> 00:47:04,880 THAT. 1073 00:47:04,880 --> 00:47:09,080 EFFECT SIZES SOMETIMES ARE SMALL 1074 00:47:09,080 --> 00:47:10,240 WHEN EXAMINING COMPLEX 1075 00:47:10,240 --> 00:47:10,520 BEHAVIORS. 1076 00:47:10,520 --> 00:47:11,600 IT IS WHAT IT IS? 1077 00:47:11,600 --> 00:47:13,040 HOW DO YOU HANDLE THAT? 1078 00:47:13,040 --> 00:47:16,040 WHAT DOES IT MEAN? 1079 00:47:16,040 --> 00:47:19,120 MANY OF OUR MEASURES ARE NOISY, 1080 00:47:19,120 --> 00:47:29,520 THEY ARE A LOW SIGNAL. 1081 00:47:34,920 --> 00:47:35,520 GENERAL WEAKNESSES EXIST IN OUR 1082 00:47:35,520 --> 00:47:35,720 SPACE. 1083 00:47:35,720 --> 00:47:36,320 WHAT ARE SOME OF THE THREATS? 1084 00:47:36,320 --> 00:47:36,960 WE ARE SEEING SOME THREATS THAT 1085 00:47:36,960 --> 00:47:37,560 WE IGNORE THE WEAKNESSES AND 1086 00:47:37,560 --> 00:47:38,160 CARRY ON THE WAY WE HAVE ALWAYS 1087 00:47:38,160 --> 00:47:38,480 DONE THINGS. 1088 00:47:38,480 --> 00:47:39,160 THERE IS A LACK OF UNDERSTANDING 1089 00:47:39,160 --> 00:47:49,640 OF HETEROGENEITY PROBLEM. 1090 00:47:50,280 --> 00:47:54,520 I HIGHLIGHTED THIS BRIEFLY, WE 1091 00:47:54,520 --> 00:48:00,640 HAVE A PROBLEM REPORTING IN THE 1092 00:48:00,640 --> 00:48:02,880 LABS BECAUSE WE NEED TO PUBLISH 1093 00:48:02,880 --> 00:48:05,400 THINGS QUICKLY AND HAVE 1094 00:48:05,400 --> 00:48:07,520 SIGNIFICANT VALUE WE TRY TO KEEP 1095 00:48:07,520 --> 00:48:09,120 RUNNING EXPERIMENTS UNTIL WE 1096 00:48:09,120 --> 00:48:10,440 FIND THAT. 1097 00:48:10,440 --> 00:48:10,960 '-HACKING. 1098 00:48:10,960 --> 00:48:14,320 A LOT OF TIMES THE ONLY THING 1099 00:48:14,320 --> 00:48:17,560 ACCEPTED ARE HIGHLY SIGNIFICANT 1100 00:48:17,560 --> 00:48:19,080 IN THE LITERATURE WHICH LEADS TO 1101 00:48:19,080 --> 00:48:23,080 THE SKEWS WE ARE SEEING. 1102 00:48:23,080 --> 00:48:24,960 OUR ACADEMIC INFRASTRUCTURE 1103 00:48:24,960 --> 00:48:26,480 REWARDS SELECTIVE REPORTING. 1104 00:48:26,480 --> 00:48:28,200 ONLY POSITIVE FINDINGS ARE 1105 00:48:28,200 --> 00:48:30,480 TYPICALLY ACCEPTED IN MOST CITED 1106 00:48:30,480 --> 00:48:30,720 JOURNALS. 1107 00:48:30,720 --> 00:48:34,080 THAT IS WHAT WE WANT TO SEE IN 1108 00:48:34,080 --> 00:48:37,120 OUR PRELIMINARY STUDIES, THIS IS 1109 00:48:37,120 --> 00:48:42,080 HIGH P-VALUES TO FEED INTO THE 1110 00:48:42,080 --> 00:48:42,560 CULTURE. 1111 00:48:42,560 --> 00:48:48,440 THE FUNDING MECHANISMS ARE NOT 1112 00:48:48,440 --> 00:48:49,800 SET UP TO OPTIMIZE STUDY 1113 00:48:49,800 --> 00:48:51,800 DESIGNS. 1114 00:48:51,800 --> 00:48:56,840 SET UP ACROSS LABS IS SOMETIMES 1115 00:48:56,840 --> 00:48:58,320 EXTREMELY IMPORTANT THAN AN 1116 00:48:58,320 --> 00:49:01,080 INDIVIDUAL LAB DOING ONE STUDY 1117 00:49:01,080 --> 00:49:01,280 ALONE. 1118 00:49:01,280 --> 00:49:03,880 MECHANISMS -- I MEAN, IT ALREADY 1119 00:49:03,880 --> 00:49:07,600 EXISTS BUT INCREASING MECHANISMS 1120 00:49:07,600 --> 00:49:09,480 THAT REWARD LOTS OF 1121 00:49:09,480 --> 00:49:10,320 COLLABORATION ACROSS SPECIFIC 1122 00:49:10,320 --> 00:49:13,760 STUDIES IS IMPORTANT. 1123 00:49:13,760 --> 00:49:16,240 OUR ACADEMIC ACHIEVEMENT CULL 1124 00:49:16,240 --> 00:49:17,680 CULTURE. 1125 00:49:17,680 --> 00:49:18,560 PROMOTION IS NOT NECESSARILY SET 1126 00:49:18,560 --> 00:49:20,240 UP TO HANDLE WHAT WE ARE 1127 00:49:20,240 --> 00:49:22,160 LEARNING AND HOW TO CONDUCT THE 1128 00:49:22,160 --> 00:49:22,360 SCIENCE. 1129 00:49:22,360 --> 00:49:24,560 WE TALK ABOUT THIS OFTEN. 1130 00:49:24,560 --> 00:49:26,200 EVEN IN MY OWN EXPERIENCE, YOU 1131 00:49:26,200 --> 00:49:29,040 KNOW, MY ABILITY TO COLLABORATE 1132 00:49:29,040 --> 00:49:30,720 AS A YOUNG INVESTIGATOR WITH 1133 00:49:30,720 --> 00:49:32,560 SENIOR FOLK WAS A NEGATIVE, AS 1134 00:49:32,560 --> 00:49:36,080 PART OF MY PROMOTION, GETTING 1135 00:49:36,080 --> 00:49:36,400 P 1136 00:49:36,400 --> 00:49:38,600 PROMOTED MY FIRST TIME. 1137 00:49:38,600 --> 00:49:40,280 BECAUSE I WAS NOT DOING 1138 00:49:40,280 --> 00:49:42,240 EVERYTHING ALL BY MYSELF I WAS 1139 00:49:42,240 --> 00:49:43,360 BRINGING TOGETHER THESE LARGE 1140 00:49:43,360 --> 00:49:48,120 GROUPS TO DO BIG STUFF, THAT WAS 1141 00:49:48,120 --> 00:49:51,200 A NOT IN MY PROMOTION CULTURE, 1142 00:49:51,200 --> 00:49:52,720 MY ABILITY TO GET PROMOTED. 1143 00:49:52,720 --> 00:49:57,840 A LOT OF FOLKS -- I VALUE THE 1144 00:49:57,840 --> 00:49:59,600 DIVERSITY IN MY OWN LAB AND MY 1145 00:49:59,600 --> 00:50:01,120 OWN WORK AND MY OWN STAFF 1146 00:50:01,120 --> 00:50:10,280 BECAUSE I THINK THAT VARIABILITY 1147 00:50:10,280 --> 00:50:12,280 DRIVES THAT, THAT DOESN'T EXIST 1148 00:50:12,280 --> 00:50:14,880 SO WE ARE REWARDED. 1149 00:50:14,880 --> 00:50:19,120 WE END UP FALLING INTO THE SAME 1150 00:50:19,120 --> 00:50:21,320 CULTURE AND LEAD TO MISLEADING 1151 00:50:21,320 --> 00:50:23,760 FINDINGS AND NOT MAXIMIZE OUR 1152 00:50:23,760 --> 00:50:24,040 POTENTIAL. 1153 00:50:24,040 --> 00:50:26,120 OUR TRAINING ENVIRONMENTS ARE 1154 00:50:26,120 --> 00:50:27,440 NOT NECESSARILY EQUIPPED TO 1155 00:50:27,440 --> 00:50:28,480 HANDLE THIS DATA. 1156 00:50:28,480 --> 00:50:31,520 IT IS SUPER COMPLEX AND WHILE WE 1157 00:50:31,520 --> 00:50:32,840 ARE GOOD AT TRAINING BASE 1158 00:50:32,840 --> 00:50:34,600 KNOWLEDGE IN THE FIELDS WE ARE 1159 00:50:34,600 --> 00:50:36,920 IN, THE CROSS DISCIPLINE 1160 00:50:36,920 --> 00:50:39,640 KNOWLEDGE IS A LOT HARDER AND 1161 00:50:39,640 --> 00:50:42,680 NOT NECESSARILY SET UP FOR 1162 00:50:42,680 --> 00:50:44,280 TODAY'S WORLD. 1163 00:50:44,280 --> 00:50:45,680 I ALREADY HIGHLIGHTED SOME OF 1164 00:50:45,680 --> 00:50:47,640 THE LACK OF DIVERSITY IN SUBJECT 1165 00:50:47,640 --> 00:50:48,080 POPULATIONS AND IN 1166 00:50:48,080 --> 00:50:50,560 INVESTIGATORS. 1167 00:50:50,560 --> 00:50:53,400 LAST THING IS THERE'S JUST AN 1168 00:50:53,400 --> 00:50:54,120 ENORMOUS AMOUNT OF OPPORTUNITY 1169 00:50:54,120 --> 00:50:54,760 RIGHT NOW. 1170 00:50:54,760 --> 00:50:56,520 LIKE THIS IS THE TIME, RIGHT? 1171 00:50:56,520 --> 00:50:57,960 THERE IS AN OPPORTUNITY TO 1172 00:50:57,960 --> 00:51:01,000 EXPAND OUR ENTHUSIASM FOR THE 1173 00:51:01,000 --> 00:51:03,200 TYPE OF SCIENCE, THESE NEW 1174 00:51:03,200 --> 00:51:09,040 APPROACHES TO IMPROVE SNR AND 1175 00:51:09,040 --> 00:51:11,640 GET SCIENCE THAT CAN REALLY 1176 00:51:11,640 --> 00:51:12,640 CHANGE OUR WORLD. 1177 00:51:12,640 --> 00:51:13,640 NOW WE ARE THERE. 1178 00:51:13,640 --> 00:51:16,920 WE UNDERSTAND HOW TO DO IT. 1179 00:51:16,920 --> 00:51:18,560 OPEN SCIENCE DATA SHARING OR 1180 00:51:18,560 --> 00:51:20,760 RESOURCE SHARING. 1181 00:51:20,760 --> 00:51:21,960 THERE IS AN OPPORTUNITY, THE 1182 00:51:21,960 --> 00:51:23,600 INFRASTRUCTURE IS THERE, IF WE 1183 00:51:23,600 --> 00:51:25,400 CAN CHANGE OUR CULTURE TO BE 1184 00:51:25,400 --> 00:51:26,920 MORE OPEN WITH OUR DATA AND 1185 00:51:26,920 --> 00:51:28,800 SCIENCE, IT CAN TAKE US A LONG 1186 00:51:28,800 --> 00:51:29,360 WAY. 1187 00:51:29,360 --> 00:51:30,800 OPPORTUNITY TO GROW AND SUPPORT 1188 00:51:30,800 --> 00:51:33,760 AND MOTIVATION OF A DIVERSE WORK 1189 00:51:33,760 --> 00:51:36,000 FORCE FOR A NEW ERA. 1190 00:51:36,000 --> 00:51:40,160 THERE'S CLEARLY A MOVE RIGHT NOW 1191 00:51:40,160 --> 00:51:50,480 TO IMPROVE DE.I. IN OUR 1192 00:51:50,480 --> 00:51:50,840 INSTITUTIONS. 1193 00:51:50,840 --> 00:51:52,080 ENTHUSIASM IS ALLOWING THE 1194 00:51:52,080 --> 00:51:54,920 GROWTH OF BIG DATA RESOURCES. 1195 00:51:54,920 --> 00:51:57,720 POST PEAK, MORE OUTREACH TO 1196 00:51:57,720 --> 00:51:59,960 MOBILE TECHNOLOGIES AND WE HAVE 1197 00:51:59,960 --> 00:52:04,320 AN OPPORTUNITY TO LEVERAGE, WHAT 1198 00:52:04,320 --> 00:52:07,480 I CAN SEE IS JUST AN INCREDIBLE 1199 00:52:07,480 --> 00:52:09,680 BATCH OF JUNIOR SCIENTISTS WHO 1200 00:52:09,680 --> 00:52:12,040 COULD REALLY, REALLY BEND THE 1201 00:52:12,040 --> 00:52:14,960 CURVE IF WE TAKE THE ISSUES AND 1202 00:52:14,960 --> 00:52:16,240 OPPORTUNITIES I HAVE BEEN 1203 00:52:16,240 --> 00:52:17,520 HIGHLIGHTING TODAY SERIOUSLY. 1204 00:52:17,520 --> 00:52:19,040 I'M GOING TO END THERE. 1205 00:52:19,040 --> 00:52:20,440 I WANT TO THANK YOU ALL FOR 1206 00:52:20,440 --> 00:52:21,880 HAVING ME. 1207 00:52:21,880 --> 00:52:23,080 I ENJOYED THE OPPORTUNITY TO 1208 00:52:23,080 --> 00:52:25,320 GIVE THIS PARTICULAR LECTURE. 1209 00:52:25,320 --> 00:52:27,560 HERE IS A QUICK SNAPSHOT OF MY 1210 00:52:27,560 --> 00:52:29,800 LAB AND THE FOLKS INVOLVED WITH 1211 00:52:29,800 --> 00:52:30,400 THE WORK. 1212 00:52:30,400 --> 00:52:32,680 AND OF COURSE TO ALL THE FUNDING 1213 00:52:32,680 --> 00:52:34,560 THAT HAS COME MY WAY TO BE ABLE 1214 00:52:34,560 --> 00:52:38,760 TO DO THE SCIENCE THAT EXCITES 1215 00:52:38,760 --> 00:52:41,040 ME AND ALLOWS ME TO DO THE WORK 1216 00:52:41,040 --> 00:52:42,720 THAT I JUST REALLY LOVE TO DO. 1217 00:52:42,720 --> 00:52:43,600 I APPRECIATE IT AND THANK YOU 1218 00:52:43,600 --> 00:52:45,920 VERY MUCH. 1219 00:52:45,920 --> 00:52:48,480 >> THANK YOU, DR. FAIR. 1220 00:52:48,480 --> 00:52:49,080 WHAT A WONDERFUL TALK. 1221 00:52:49,080 --> 00:52:50,720 THE QUESTIONS ARE STREAMING IN. 1222 00:52:50,720 --> 00:52:53,440 BEFORE I GET TO THEM, I WANT TO 1223 00:52:53,440 --> 00:52:54,720 REPEAT THE CONTINUING MEDICAL 1224 00:52:54,720 --> 00:52:56,680 EDUCATION CODE SO THAT CODE IS 1225 00:52:56,680 --> 00:52:59,720 37949. 1226 00:52:59,720 --> 00:53:01,040 SO SOME OF THE FIRST QUESTIONS 1227 00:53:01,040 --> 00:53:02,880 THAT CAME IN ARE REALLY TRYING 1228 00:53:02,880 --> 00:53:05,720 TO DIG IN AND EXPLAIN THE 1229 00:53:05,720 --> 00:53:06,000 VARABILITY. 1230 00:53:06,000 --> 00:53:08,120 I THINK YOU TOUCHED ON SOME OF 1231 00:53:08,120 --> 00:53:09,840 THIS BUT MAYBE YOU CAN OFFER 1232 00:53:09,840 --> 00:53:10,680 FURTHER REFLECTION. 1233 00:53:10,680 --> 00:53:13,640 A TWO-PART QUESTION. 1234 00:53:13,640 --> 00:53:16,800 IS THE SAMPLING VARABILITY 1235 00:53:16,800 --> 00:53:20,440 REFLECTED NATURAL HETEROGENITY 1236 00:53:20,440 --> 00:53:23,440 AND SPECIFIC TO FMRI AND CAN THE 1237 00:53:23,440 --> 00:53:26,600 DIFFERENCES BE EXPLAINED BY 1238 00:53:26,600 --> 00:53:29,040 DIFFERENT FMRI APPROACHES IN 1239 00:53:29,040 --> 00:53:30,280 DIFFERENT LABS? 1240 00:53:30,280 --> 00:53:32,200 >> THE ANSWER TO ALL OF THAT IS 1241 00:53:32,200 --> 00:53:33,240 YES. 1242 00:53:33,240 --> 00:53:43,720 IT IS REFLECTING SOME HET 1243 00:53:45,360 --> 00:53:45,600 HETEROGENEITY. 1244 00:53:45,600 --> 00:53:53,760 WE ARE TRYING TO GET HOMOGENEOUS 1245 00:53:53,760 --> 00:53:55,000 SAMPLES SO THAT IS LIKELY PART 1246 00:53:55,000 --> 00:53:55,600 OF IT. 1247 00:53:55,600 --> 00:53:56,160 HOW MUCH? 1248 00:53:56,160 --> 00:53:57,760 WE DON'T KNOW. 1249 00:53:57,760 --> 00:53:59,440 WHAT WAS THE SECOND QUESTION 1250 00:53:59,440 --> 00:53:59,640 AGAIN? 1251 00:53:59,640 --> 00:54:02,040 >> IS SOME OF IT EXPLAINED IN 1252 00:54:02,040 --> 00:54:04,680 DIFFERENCES IN APPROACH BETWEEN 1253 00:54:04,680 --> 00:54:06,040 LABS, MEASUREMENT DIFFERENCES 1254 00:54:06,040 --> 00:54:09,480 >> ABSOLUTELY LIKELY TO BE SOME 1255 00:54:09,480 --> 00:54:11,800 APPROACH BETWEEN LABS, BUT THE 1256 00:54:11,800 --> 00:54:13,800 BULK, NO. 1257 00:54:13,800 --> 00:54:16,560 CERTAINLY YOU ARE GOING TO, IN 1258 00:54:16,560 --> 00:54:18,360 FACT, I SAID WE DID THIS IN A 1259 00:54:18,360 --> 00:54:19,560 MILLION WAYS, DIFFERENT 1260 00:54:19,560 --> 00:54:21,520 APPROACHES FROM OTHER LABS, DATA 1261 00:54:21,520 --> 00:54:22,920 PROCESSES FROM OTHER PLACES IS 1262 00:54:22,920 --> 00:54:25,360 THAT THERE'S -- THERE IS 1263 00:54:25,360 --> 00:54:27,160 ABSOLUTELY -- I DID TOUCH ON 1264 00:54:27,160 --> 00:54:28,480 THIS, ABSOLUTELY OPPORTUNITIES 1265 00:54:28,480 --> 00:54:31,840 TO INCREASE THE EFFECT SIZES AND 1266 00:54:31,840 --> 00:54:34,440 WHAT NOT OF WHAT I SHOWED TODAY. 1267 00:54:34,440 --> 00:54:36,600 HOW MUCH IS NOT CLEAR, BUT 1268 00:54:36,600 --> 00:54:38,000 LIKELY TO BE MARGINAL UNTIL WE 1269 00:54:38,000 --> 00:54:43,920 TACKLE THE HETEROGENEITY FINDING 1270 00:54:43,920 --> 00:54:44,960 OR MASSIVE FINDING. 1271 00:54:44,960 --> 00:54:47,920 A LOT OF TIMES THESE 1272 00:54:47,920 --> 00:54:48,960 RELATIONSHIPS ARE REALLY 1273 00:54:48,960 --> 00:54:51,160 COMPLEX, TO DEFINE A CIRCUIT OR 1274 00:54:51,160 --> 00:54:55,160 A THING OR THE REGION THAT WILL 1275 00:54:55,160 --> 00:54:56,880 EXPLAIN SO MUCH VARIANCE IS 1276 00:54:56,880 --> 00:54:57,160 UNLIKELY. 1277 00:54:57,160 --> 00:55:00,480 SO IT IS SOME, BUT NOT PROBABLY 1278 00:55:00,480 --> 00:55:00,640 ALL. 1279 00:55:00,640 --> 00:55:03,000 THE LAST QUESTION WAS REAL 1280 00:55:03,000 --> 00:55:03,920 QUICK, I DON'T WANT TO GET IT 1281 00:55:03,920 --> 00:55:07,880 WRONG. 1282 00:55:07,880 --> 00:55:09,680 >> YOU GOT THE TWO PARTS. 1283 00:55:09,680 --> 00:55:11,280 >> OKAY. 1284 00:55:11,280 --> 00:55:13,160 >> SO WE'LL GO ON TO THE NEXT 1285 00:55:13,160 --> 00:55:13,680 QUESTION. 1286 00:55:13,680 --> 00:55:14,960 THE NEXT QUESTION IS DO YOU HAVE 1287 00:55:14,960 --> 00:55:17,720 ANY ADVICE FOR THE NIH ABOUT HOW 1288 00:55:17,720 --> 00:55:20,160 TO ADVANCE REPRODUCEABLE SCIENCE 1289 00:55:20,160 --> 00:55:22,560 AND NEUROIMAGING. 1290 00:55:22,560 --> 00:55:24,120 THE EXAMPLE IS SHOULD 1291 00:55:24,120 --> 00:55:25,920 PREREGISTRATION BE ENCOURAGED OR 1292 00:55:25,920 --> 00:55:27,120 REQUIRED FOR THESE STUDIES? 1293 00:55:27,120 --> 00:55:29,120 >> IT IS FUNDY, I GOT THIS 1294 00:55:29,120 --> 00:55:33,000 QUESTION -- I DID THE NIMH 1295 00:55:33,000 --> 00:55:34,240 LECTURE WITH JOSH GORDON. 1296 00:55:34,240 --> 00:55:36,160 I SAID YOU NEED TO GIVE US MORE 1297 00:55:36,160 --> 00:55:41,360 MONEY, JOSH. 1298 00:55:41,360 --> 00:55:43,840 NO, DO THINK -- I PERSONALLY 1299 00:55:43,840 --> 00:55:45,560 THINK THERE NEEDS TO BE A 1300 00:55:45,560 --> 00:55:47,440 RETHINK IN HOW WE EMPHASIZE THE 1301 00:55:47,440 --> 00:55:49,160 WAY THAT WE ARE CONDUCTING 1302 00:55:49,160 --> 00:55:51,560 STUDIES AND A CRITICAL REVIEW OF 1303 00:55:51,560 --> 00:55:58,160 WHAT ARE THE BEST DESIGNS FOR 1304 00:55:58,160 --> 00:56:00,400 SPECIFIC MECHANISMS, YOU KNOW? 1305 00:56:00,400 --> 00:56:01,960 THAT IS THE HARD PART. 1306 00:56:01,960 --> 00:56:03,160 THAT DOESN'T MEAN YOU CAN'T DO 1307 00:56:03,160 --> 00:56:04,240 SMALL STUDIES. 1308 00:56:04,240 --> 00:56:06,360 THIS IS A FIELD THAT SHIFTED SO 1309 00:56:06,360 --> 00:56:07,880 FAR INTO THIS ONE DOMAIN IN THE 1310 00:56:07,880 --> 00:56:10,240 WAY WE CONDUCT STUDIES, IT HAS 1311 00:56:10,240 --> 00:56:12,960 TAKEN AWAY THE THINGS THAT FIT 1312 00:56:12,960 --> 00:56:18,200 NICELY WITH TRADITIONAL RO1s AND 1313 00:56:18,200 --> 00:56:20,280 IGNORING THE THINGS THAT WOULD 1314 00:56:20,280 --> 00:56:27,960 BE BETTER AND MORE COLLABORATIVE 1315 00:56:27,960 --> 00:56:30,320 STUDIES PREREGISTRATION IS A 1316 00:56:30,320 --> 00:56:32,160 GREAT IDEA TO SOME EXTENT. 1317 00:56:32,160 --> 00:56:33,560 I THINK -- I TALK ABOUT THIS ALL 1318 00:56:33,560 --> 00:56:34,440 THE TIME. 1319 00:56:34,440 --> 00:56:37,000 EVEN IF YOU DO A SMALL STUDY, IT 1320 00:56:37,000 --> 00:56:38,800 NEEDS TO BE -- YOU NEED TO 1321 00:56:38,800 --> 00:56:40,360 PUBLISH ALL OF IT. 1322 00:56:40,360 --> 00:56:42,720 WE NEED TO BE ABLE TO VALUE NULL 1323 00:56:42,720 --> 00:56:43,000 FINDINGS. 1324 00:56:43,000 --> 00:56:44,080 THAT IS THE PROBLEM. 1325 00:56:44,080 --> 00:56:48,560 WE DON'T VALUE IT AS BEING 1326 00:56:48,560 --> 00:56:48,960 ACADEMIC. 1327 00:56:48,960 --> 00:56:51,320 SOME PEOPLE WON'T PUBLISH IT. 1328 00:56:51,320 --> 00:56:52,960 IF PEOPLE DON'T PUBLISH IT THEN 1329 00:56:52,960 --> 00:56:55,240 YOU GET THESE INFLATED EFFECTS, 1330 00:56:55,240 --> 00:56:55,440 RIGHT? 1331 00:56:55,440 --> 00:56:58,120 SO IT IS A COMPLETE CHANGE IN 1332 00:56:58,120 --> 00:56:59,800 CULTURE AND HOW WE VALUE THE 1333 00:56:59,800 --> 00:57:00,600 WORK, RIGHT? 1334 00:57:00,600 --> 00:57:02,200 AND THEN HOW WE GO ABOUT IT. 1335 00:57:02,200 --> 00:57:03,960 LIKE I SAID EARLIER, IF IT IS 1336 00:57:03,960 --> 00:57:06,920 THE CASE WE VALUED NULL FINDINGS 1337 00:57:06,920 --> 00:57:08,280 EQUALLY TO SOMETHING 1338 00:57:08,280 --> 00:57:10,200 SIGNIFICANT, WE WOULDN'T BE IN 1339 00:57:10,200 --> 00:57:10,400 HERE. 1340 00:57:10,400 --> 00:57:13,400 WE WOULD BE ABLE TO DO OUR META 1341 00:57:13,400 --> 00:57:14,600 ANALYSIS AND GET THE RIGHT 1342 00:57:14,600 --> 00:57:16,200 EFFECT AND KNOW WHAT IT IS. 1343 00:57:16,200 --> 00:57:18,800 IT IS NOT HOW WE ARE SET UP. 1344 00:57:18,800 --> 00:57:19,840 PREREGISTERED REPORTS ARE NICE 1345 00:57:19,840 --> 00:57:21,440 BECAUSE THEY DO ALLOW A LITTLE 1346 00:57:21,440 --> 00:57:23,520 BIT OF THAT FLEXIBILITY. 1347 00:57:23,520 --> 00:57:25,360 SO I DO THINK THAT IS PART OF 1348 00:57:25,360 --> 00:57:27,600 THE SOLUTION, PROBABLY NOT ALL 1349 00:57:27,600 --> 00:57:28,720 OF IT. 1350 00:57:28,720 --> 00:57:28,880 # 1351 00:57:28,880 --> 00:57:30,640 >> SO THE NEXT QUESTION IS 1352 00:57:30,640 --> 00:57:32,120 MOVING KIND OF AWAY FROM THE 1353 00:57:32,120 --> 00:57:33,880 SCIENCE OF SCIENCE DOWN TO SOME 1354 00:57:33,880 --> 00:57:34,440 MORE SPECIFICS. 1355 00:57:34,440 --> 00:57:36,000 SO IT IS I'M CURIOUS ABOUT 1356 00:57:36,000 --> 00:57:38,560 WHETHER YOU CAN TELL FROM YOUR 1357 00:57:38,560 --> 00:57:41,160 IMAGING WHETHER AUTISM AND ADHD 1358 00:57:41,160 --> 00:57:46,400 IS A MATTER OF GENETICS, EPI 1359 00:57:46,400 --> 00:57:47,720 GENETICS OR SOMETHING IN 1360 00:57:47,720 --> 00:57:48,200 BETWEEN? 1361 00:57:48,200 --> 00:57:50,400 >> YES. 1362 00:57:50,400 --> 00:57:52,920 YOU KNOW, THE -- IN FACT, WE 1363 00:57:52,920 --> 00:57:55,280 HAVE ONGOING, PRECISION MAPPING 1364 00:57:55,280 --> 00:57:57,920 STUDIES IN BOTH ADHD AND AUTISM, 1365 00:57:57,920 --> 00:58:00,640 CONNECTING A LOT OF GENETICS. 1366 00:58:00,640 --> 00:58:02,080 THE DATA SEEMED TO SUGGEST IN 1367 00:58:02,080 --> 00:58:04,360 SOME CASES IT IS VERY HEAVILY 1368 00:58:04,360 --> 00:58:07,400 LEANED ON THE GENETICS, IT IS 1369 00:58:07,400 --> 00:58:09,440 VERY CLEAR PARTICULARLY FROM THE 1370 00:58:09,440 --> 00:58:12,200 RARE VARIANCE STUDIES IN ADHD 1371 00:58:12,200 --> 00:58:13,320 AND IN AUTISM. 1372 00:58:13,320 --> 00:58:17,920 MORE IN AUTISM THAN ADHD. 1373 00:58:17,920 --> 00:58:19,600 THEY ARE HIGHLY RELATED SO THERE 1374 00:58:19,600 --> 00:58:22,800 ARE LOTS OF THESE FINDINGS, 1375 00:58:22,800 --> 00:58:25,320 UPWARDS OF THE FOLKS HAVE ADHD 1376 00:58:25,320 --> 00:58:28,160 AS WELL, NOT NECESSARILY VICE 1377 00:58:28,160 --> 00:58:28,360 VERSA. 1378 00:58:28,360 --> 00:58:32,560 IT IS BECAUSE THE DISEASE IS SO 1379 00:58:32,560 --> 00:58:36,320 HETEROGENEOUS, THE BEHAVIORAL 1380 00:58:36,320 --> 00:58:39,440 PHENOTYPE LOOKS THE SAME, 1381 00:58:39,440 --> 00:58:40,600 REGIONS IN THE BRAIN ARE 1382 00:58:40,600 --> 00:58:42,920 DIFFERENT AND SOME WILL INCLUDE 1383 00:58:42,920 --> 00:58:44,640 MORE ENVIRONMENTAL FACTORS AND 1384 00:58:44,640 --> 00:58:48,920 LESS RELIANCE ON GENETICS. 1385 00:58:48,920 --> 00:58:52,880 SO THAT HAS TO BE NOT KNOWN FOR 1386 00:58:52,880 --> 00:58:54,480 SURE YET BUT CERTAINLY BEING 1387 00:58:54,480 --> 00:58:57,240 INVESTIGATED. 1388 00:58:57,240 --> 00:58:58,160 >> THANKS. 1389 00:58:58,160 --> 00:59:01,560 I KNOW WE ARE BUMPING UP AGAINST 1390 00:59:01,560 --> 00:59:03,480 TIME BUT ANOTHER QUESTION IS 1391 00:59:03,480 --> 00:59:05,320 MANY THREAT IDENTIFIED ARE NOT 1392 00:59:05,320 --> 00:59:06,440 UNIQUE TO NEUROSCIENCE. 1393 00:59:06,440 --> 00:59:07,760 >> THAT'S RIGHT. 1394 00:59:07,760 --> 00:59:10,480 >> ARE THERE ANY AFFECTS 1395 00:59:10,480 --> 00:59:12,480 PARTICULARLY CHALLENGING FOR THE 1396 00:59:12,480 --> 00:59:13,080 NEUROSCIENCE COMMUNITY THAT 1397 00:59:13,080 --> 00:59:16,200 SHOULD HAVE A SPECIAL ATTENTION 1398 00:59:16,200 --> 00:59:17,880 THAT IS DIFFERENT IN OTHER AREAS 1399 00:59:17,880 --> 00:59:19,800 WHERE WE ARE GRAPPLING WITH ALL 1400 00:59:19,800 --> 00:59:20,360 THESE ISSUES? 1401 00:59:20,360 --> 00:59:21,800 >> YEAH, I DO. 1402 00:59:21,800 --> 00:59:24,880 THAT IS KIND OF A LITTLE BIT BY 1403 00:59:24,880 --> 00:59:25,120 DESIGN. 1404 00:59:25,120 --> 00:59:27,200 THE SAME THINGS WE ARE DEALING 1405 00:59:27,200 --> 00:59:29,480 WITH IN THE COGNITIVE 1406 00:59:29,480 --> 00:59:31,440 NEUROSCIENCES ARE NOT UNIQUE. 1407 00:59:31,440 --> 00:59:34,640 THIS IS NOT AN FMRI STUDY, I 1408 00:59:34,640 --> 00:59:34,840 REPEAT. 1409 00:59:34,840 --> 00:59:36,320 IT IS NOT UNIQUE. 1410 00:59:36,320 --> 00:59:37,480 YOU CAN SEE IT RAMPANT THROUGH 1411 00:59:37,480 --> 00:59:39,440 ALL OF OUR WORK, RIGHT? 1412 00:59:39,440 --> 00:59:41,720 IF YOU WANT TO ACCELERATE 1413 00:59:41,720 --> 00:59:42,840 MAXIMUM POTENTIAL YOU HAVE TO 1414 00:59:42,840 --> 00:59:43,920 CHANGE SOME THINGS. 1415 00:59:43,920 --> 00:59:45,920 I THINK TO BE HONEST, I TALKED 1416 00:59:45,920 --> 00:59:48,640 ABOUT IT, I WAS ABLE TO DO ONE 1417 00:59:48,640 --> 00:59:51,960 QUOTE FROM WHEN I WON THE 1418 00:59:51,960 --> 00:59:53,640 MacARTHUR AWARD A YEAR AND A 1419 00:59:53,640 --> 00:59:54,240 HALF AGO. 1420 00:59:54,240 --> 00:59:55,840 I THINK ONE OF THE BIGGEST 1421 00:59:55,840 --> 00:59:58,080 CHALLENGES I CAN SEE IS 1422 00:59:58,080 --> 01:00:00,400 DIVERSIFYING OUR WORKFORCE. 1423 01:00:00,400 --> 01:00:03,280 I THINK IT IS A HUGE MISSED 1424 01:00:03,280 --> 01:00:03,600 OPPORTUNITY. 1425 01:00:03,600 --> 01:00:06,000 A LOT OF THINGS WE HAVE SEEN 1426 01:00:06,000 --> 01:00:08,640 HERE WOULD HAVE BEEN DISCOVERED 1427 01:00:08,640 --> 01:00:11,320 A LONG TIME AGO IF WE HAD 1428 01:00:11,320 --> 01:00:15,680 DIFFERENT VOICES IN THE MIX. 1429 01:00:15,680 --> 01:00:16,960 VARIABILITY IS FUNDAMENTAL 1430 01:00:16,960 --> 01:00:17,920 PROGRESS, BUT WE DON'T VALUE 1431 01:00:17,920 --> 01:00:19,600 THAT AS WE DO WITH OTHER THINGS 1432 01:00:19,600 --> 01:00:22,200 LIKE HOW IMPORTANT IT IS FOR 1433 01:00:22,200 --> 01:00:24,680 ACTUALLY MAXIMIZING DISCOVERY. 1434 01:00:24,680 --> 01:00:28,760 THAT IS A BIG BOTTLENECK, A HUGE 1435 01:00:28,760 --> 01:00:30,680 ONE THAT IS VERY DIFFICULT TO 1436 01:00:30,680 --> 01:00:30,960 OVERCOME. 1437 01:00:30,960 --> 01:00:34,080 BUT WE NEED TO DO BETTER. 1438 01:00:34,080 --> 01:00:35,800 I DO THINK THAT OUR -- THE 1439 01:00:35,800 --> 01:00:38,440 SPECIFIC ASPECTS OF OUR CULTURE, 1440 01:00:38,440 --> 01:00:40,040 I MEAN, IF YOU THINK ABOUT THE 1441 01:00:40,040 --> 01:00:44,560 BASICS OF PROMOTION AND OUR -- 1442 01:00:44,560 --> 01:00:48,960 THERE ARE SOME CHANGES IN WHAT 1443 01:00:48,960 --> 01:00:51,800 WE, AS KIND OF WHAT GETS IN THE 1444 01:00:51,800 --> 01:00:52,640 HIGH-PROFILE JOURNAL AND WHAT 1445 01:00:52,640 --> 01:00:54,400 DOESN'T AND THINGS LIKE THAT, 1446 01:00:54,400 --> 01:00:57,080 THOSE ASPECTS, WHAT GETS FUNDED, 1447 01:00:57,080 --> 01:01:00,160 HOW PEOPLE ARE REVIEWING THINGS. 1448 01:01:00,160 --> 01:01:01,960 EVEN IF YOU, IN MANY CASES, 1449 01:01:01,960 --> 01:01:03,800 BASED ON WHAT I JUST SHOWED YOU, 1450 01:01:03,800 --> 01:01:06,280 IF YOU START -- IF YOU DO A 1451 01:01:06,280 --> 01:01:09,400 BUNCH OF PRELIMINARY DATA WITH 1452 01:01:09,400 --> 01:01:11,920 SMALL SAMPLES AND ONLY SEE 1453 01:01:11,920 --> 01:01:13,160 HIGHLY SIGNIFICANT THINGS IT 1454 01:01:13,160 --> 01:01:14,440 ALMOST HAS TO BE WRONG. 1455 01:01:14,440 --> 01:01:17,080 IF IT IS UNDERPOWERED, IT CAN'T 1456 01:01:17,080 --> 01:01:17,840 BE RIGHT. 1457 01:01:17,840 --> 01:01:20,280 SO BUT THAT IS NOT HOW WE REVIEW 1458 01:01:20,280 --> 01:01:21,280 THE LITERATURE. 1459 01:01:21,280 --> 01:01:23,720 THAT IS NOT HOW WE REVIEW THE 1460 01:01:23,720 --> 01:01:24,920 GRANTS. 1461 01:01:24,920 --> 01:01:26,320 THESE ASPECTS OF OUR CULTURE 1462 01:01:26,320 --> 01:01:28,280 THAT FEED INTO THE BASIC, 1463 01:01:28,280 --> 01:01:30,440 RELATIVELY BASIC STATISTICS WE 1464 01:01:30,440 --> 01:01:33,120 ALL LEARNED IN OUR EARLY CLASSES 1465 01:01:33,120 --> 01:01:34,440 NEED TO CHANGE. 1466 01:01:34,440 --> 01:01:37,080 I THINK ON THE PROMOTION FRONT 1467 01:01:37,080 --> 01:01:42,200 IS MOVING PAST THE TRADITIONAL, 1468 01:01:42,200 --> 01:01:45,200 YOU KNOW, AGAIN, ALL ABOUT 1469 01:01:45,200 --> 01:01:45,480 INCENTIVES. 1470 01:01:45,480 --> 01:01:46,560 WHAT ARE THE INCENTIVES? 1471 01:01:46,560 --> 01:01:48,640 I THINK THERE ARE SOME THINGS WE 1472 01:01:48,640 --> 01:01:54,080 HAVE HAD TO STRUCTURE FOR 1473 01:01:54,080 --> 01:01:57,120 TEACHING SERVICE AND ACADEMY IN 1474 01:01:57,120 --> 01:02:00,680 OUR PROMOTION STRUCTURE DECADES 1475 01:02:00,680 --> 01:02:03,760 UPON DECADES UPON DECADES. 1476 01:02:03,760 --> 01:02:05,320 THERE ARE NEW THINGS WE NEED TO 1477 01:02:05,320 --> 01:02:08,320 CHANGE THAT CHANGE SOME OF THE 1478 01:02:08,320 --> 01:02:09,600 UNDERLYING ISSUES THAT ARE 1479 01:02:09,600 --> 01:02:11,800 SLOWING US DOWN A LITTLE BIT. 1480 01:02:11,800 --> 01:02:12,440 >> THANK YOU. 1481 01:02:12,440 --> 01:02:15,600 I KNOW WE ARE OVER TIME, BUT WE 1482 01:02:15,600 --> 01:02:16,800 REALLY APPRECIATE YOUR BEING 1483 01:02:16,800 --> 01:02:20,920 WITH US THIS OFTEN AND YOUR 1484 01:02:20,920 --> 01:02:21,720 THOUGHT-PROVOKING TALK. 1485 01:02:21,720 --> 01:02:24,080 AND I THINK THE LAST ANSWER IS A 1486 01:02:24,080 --> 01:02:26,480 GREAT ONE TO END ON BECAUSE IT 1487 01:02:26,480 --> 00:00:00,000 GIVES GREAT FOOD FOR THOUGHT.