We thank Erin Douglas, Anna Evans, and Carolyn Bellion for their contributions to participant recruitment and clinical assessment. We also thank Michael Casp, Zoe Englander, Justin Woodlief, and James Carter for their contributions to data collection and analysis, and Robert M. Hamer for consultation on statistical analysis and editing of the manuscript. Finally, we thank the individuals and their families who participated in this study. 
This study was supported by Conte center grant P50 MH064065 from the National Institute of Mental Health. Dr. Hart was supported by T32 HD040127 from the National Institute of Child Health and Human Development.

チャペルヒル - この試験中に使用される研究技術は、デューク大学とノースカロライナ大学の機関審査委員会（IRB）により承認されました。 1.イメージングタスクデザイン<ol><li>より頻度の標準刺激（スクランブル画像）のシーケンス内のまれなターゲット刺激を提示し、イベントベースの行動のタスク（円）を生成します。タスクの概略を図1に示されている。CIGALソフトウェア10を使用してタスクを提示します。 </li></ol><img alt="図1" src="/files/ftp_upload/51484/51484fig1.jpg" /> タスク設計の図1の回路図は、この図は、許可を得て、ハートら 20から変更されている。 <a href="https://www.jove.com/files/ftp_upload/51484/51484fig1large.jpg" target="_blank">この図の拡大版をご覧になるにはこちらをクリックしてください。</a> <ol style="margin-left: 40px;"><li>選択嫌悪刺激のらと国際情動写真システムデータベース（IAPS）から中性刺激のセット。 IAPS画像は覚醒と価11のレベルを反映させるために1-9のスケールで評価されています。高い数値は、より高い正の価数と覚醒を示します。そのようなヘビ、クモ、または他の動物の絵のように年齢に応じた研究グループにある画像のセットを選択します。 注意：この研究のために使用されるタスク無関係な嫌悪刺激画像は3.38（SD = 1.78）および6.14（SD = 2.08）の平均覚醒評価の平均価数の評価を持っていました。中性刺激画像は6.21（SD = 0.26）および3.72（SD = 2.15）の平均覚醒評価の平均価数を持っていました。 </li><li>画像は500ミリ秒と1500ミリ秒のための擬似ランダム化された順に表示されるように、プログラムのタスクスクリプトは、刺激間の間隔を意味します。現在の目標刺激とタスク無関係な中立画像なしより頻繁に15秒毎とは、刺激の各約4％を占めています。チ血行動態応答関数の良好な分解能を提供するためにtterイベント開始時間。 </li></ol><ol start="2"><li>画像の8セット、参加者は全8回の過程で40の目標と40のタスク無関係な中立画像の合計が提示されるように、8の機能の実行ごとに1つを作成します。 </li></ol> 2.参加者の設定とスキャン<ol><li>精神病のための家族リスクが高い健康な対照個体またはいずれかである9歳と18との間に子供や青年を募​​集。 <ol><li>健康な個体は全く精神疾患や精神疾患を持つ任意の第一度家族を持っていないことを確認してください。家族のリスク参加者は統合失調症との少なくとも1つの第1度近親者（親や兄弟を）持っていることを確認してください。第一度近親における他の精神疾患の存在のためにそれらを除外しないでください。 </li><li>家族リスクグループの参加者との年齢と性別が一致する健康参加秒。 </li></ol></li><li>未成年者のために18歳以上の参加者からインフォームドコンセントを取得し、親/法定保護者からインフォームドコンセントを取得してください。さらに、この研究に参加している未成年者からの書面による同意を取得します。 </li><li>環境でそれらを理解するために、モックMRIスキャナの参加者を配置します。スキャナノイズの録音を再生し、彼らがタスクの手順を理解していることを確実にするために行動タスクの練習走行を完了しています。 </li><li> MRIスキャナの参加者を配置し、必要な脳のローカリゼーションスキャンおよび/または解剖学的画像を取得します。 </li><li> MRIセーフ入力ボックスを使用して、すべてのターゲット刺激とすべての他の刺激のための彼らの中指と別のボタンに応じて、その人差し指で1ボタンを押して、参加者に伝えます。 </li><li> fMRIのスキャンに続いて、参加者のサブセットからの研究に使用されている画像のための覚醒と価電子の主観的な評価を集めます。カレントンの研究では、15コントロールと家族リスクの高い13から評価を得ました。 </li></ol> 3.画像取得<ol><li> 3.0テスラのMRIスキャナに参加者を配置します。 TE; 5.16ミリ秒：2.04ミリ秒; FOV：まず、（TRスポイル勾配リコール取得パルスシーケンスを使用して、解剖学的T1コントラスト画像に同一平面上に3Dを含む構造画像のセット取得24センチメートルを、画像マトリクス：256×256を、フリップ角度：20;ボクセルサイズ：1.9ミリメートル×0.94ミリメートル×0.94ミリメートル; 68の軸方向のスライス）。 </li><li>フル脳のカバレッジと傾斜エコーエコープラナーイメージングシーケンスを使用して、機能画像データを取得し（TR：2000ミリ秒、TE：27ミリ秒; FOV：24センチメートル;画像マトリクス：64×64;フリップ角：60;ボクセルサイズ：3.75脳活動は、行動のタスクの実行中に測定することができるように34の軸方向スライス）; MMは3.8ミリメートル×3.75ミリメートル×。行動のタスクを実行するたびにこの撮影シーケンスを実行します。各ランは120撮影時間点で構成する必要があります。 </li><li> TAを提示SKは8機能の実行で、それぞれが約4分を持続します。 </li></ol> 4.分析<ol><li>画像前処理：FSL 12で開くfMRIのエキスパート解析ツール（FEAT）。第1レベルの分析と事前統計を選択します。 <ol><li> 「データ」タブで、入力画像の数を選択し、処理しようとしているMR画像のそれぞれへのパスを入力します。出力ディレクトリを設定します。 トータルボリューム、廃棄された買収の数、およびTRを入力してください。 </li><li> 「前の統計情報 」タブで、5 MMSにFWHMを平滑MCFLIRT、空間に動き補正を設定し、 そして、「スライスタイミング補正」。「ベット脳抽出」と「 ハイパス 」時間フィルタリングを選択しますが、B0のunwarpingを選択しない（あなたは傾斜磁場マップを持っているuness）または「私はnormaizationをntensitiy」。12,14。 </li><li> 「登録」タブで、「メインSTRUを選択ctural画像」。。被験者の頭蓋骨ストリッピングT1強調画像へのパスを入力し、少なくとも6自由度で線形通常の検索を使用します。 標準領域のチェックボックスをオンにします。MNIアトラスイメージへのパスを入力します。通常の線形を使用12 DOF。押し移動して検索します。 </li><li> X、Y、またはZ方向に3mmより大きいヘッドの動きに参加者を除外する。 </li></ol></li><li>レベル1：単一のランに作業条件との間でデータを比較してください。オープンFEAT。 「第1レベルの分析」と「統計+ポスト統計」を選択します。 <ol><li> [データ]タブで 、入力の数を設定し、MR画像のそれぞれへのパスを入力します。 。「出力ディレクトリ」のパスを入力して「トータルボリューム」、廃棄された買収の数、およびTRを入力してください。 </li><li> 「 統計 」タブで、「使用フィルムはプリホワイトニング 」のチェックボックス16を選択します。 「フルモデルSEを押しますTUP」ボタンを押します。タスク条件の数に「 元の電気自動車の数」に設定します。各条件について、 コンボリューション 」ドロップダウン・メニュー17,18」からダブルガマHRF「基本形状]ドロップダウンメニューから「 カスタム（3列形式）」を選択し、タスクのタイミングを含むテキストファイルを選択します。 <ol><li>指定されたタイプの各「イベント」ごとに1つのエントリを持つ3列に、このテキストフ​​ァイルをフォーマットします。最初の列は、第二の時間（秒単位）が含まれている必要があり（秒）開始時間が含まれている必要があり、3番目は、イベントの重みを含める必要があります。 コントラスト＆F検定]タブで 、各比較のために、各タスクの状態と1のための1つのコントラストを作成します。 </li></ol></li><li> 「ポスト・統計」タブで、「しきい」ドロップダウン・メニューの 「クラスタ」を選択し、「Zしきい値」とクラスタP Tを設定それぞれ2.3および0.05 8,19にhreshold。 </li><li> 「登録」タブで、「メイン構造画像」を選択します。被験者の頭蓋骨ストリッピングT1強調画像へのパスを入力します。少なくとも6自由度で線形通常の検索を使用します。 「標準容量」チェックボックスを選択します。 MNIアトラスイメージへのパスを入力します。 12自由度ノーマル、線形検索を使用します。押し、「移動」。 </li></ol></li><li>レベル2：各タスク条件の実行間のデータを比較してください。オープンFEAT。ドロップダウンメニューから「より高いレベルの分析」と「統計+ポスト統計」を選択します。 <ol><li> [データ]タブで、「入力が低レベルのFEATのディレクトリです 」を選択します。入力数を設定し、MR画像のそれぞれへのパスを入力します。 「出力ディレクトリ」のパスを入力します。 </li><li>選択ボックス&quot;Eを修正するには：「統計」タブで、「FLAME1は混合効果」に変更ffects「押し」モデルセットアップウィザード単一のグループの平均を&quot;ボタンを押します。選択」」をクリックして「プロセス」ボタンをクリックします。 </li><li> 「ポスト・統計 」タブで、「しきい 」ドロップダウン・メニューの 「クラスタ」を選択し、8,19はそれぞれ2.3と0.05に「Zしきい値 」と「クラスタP」のしきい値を設定します。押し、「移動」。 </li></ol></li><li>レベル3：すべての実行間で、各タスクの状態のための科目間のデータを比較してください。オープンFEAT。ドロップダウンメニューから「より高いレベルの分析 」と「 統計+ポスト統計」を選択します。 <ol><li> [データ]タブで、[入力の数を設定し、MR画像のそれぞれへのパスを入力し、「 入力がFEATディレクトリから画像を対応させていただきます。3Dです 」。 「出力ディレクトリ 」のパスを入力します。 </li><li> 「統計」T ONAB、押して「フルモデルのセットアップ」。各EVのために - このような診断等のグループ、年齢、性別、各被験者の値（入力■入力1）を入力し、グループ変数と共変量の数に等しい電気自動車の数を設定します。あなたはこれらの値のスプレッドシートをコピーするために「貼り付け」ウィンドウを使用することができます。 <ol><li> 「コントラスト＆F検定 」タブで、各テスト変数と各コントラスト（ 例えば、診断グループ）のコントラストを追加します。各試験変数については、該当するEVの下欄に値1を選択することにより、コントラストを設定します。各コントラストのために、1〜-1の第1の値と第2のセット。 「完了」を選択します。 </li></ol></li><li> 「ポスト・統計 」タブで、「しきい」ドロップダウン・メニューの 「クラスタ」を選択し、2.3と0.05に「Zしきい値 」と「クラスタP」のしきい値を設定し、それぞれ8,19 </suP&gt;。押し、「移動」。 </li></ol></li></ol>

<ol>
	<li>Kety, S. S., Rosenthal, D., Wender, P. H., Schulsinger, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mental+illness+in+the+biological+and+adoptive+families+of+adpoted+schizophrenics.">Mental illness in the biological and adoptive families of adpoted schizophrenics.</a> Am J Psyc. 128, 302-306 (1971).</li><li>Weinberger, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Implications+of+normal+brain+development+for+the+pathogenesis+of+schizophrenia.">Implications of normal brain development for the pathogenesis of schizophrenia.</a> Arch Gen Psychia. 44, 660-669 (1987).</li><li>Nuechterlein, K. H., Dawson, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Information+processing+and+attentional+functioning+in+the+developmental+course+of+schizophrenic+disorders.">Information processing and attentional functioning in the developmental course of schizophrenic disorders.</a> Schizophr Bul. 10, 160-203 (1984).</li><li>Nuechterlein, K. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+vulnerability/stress+model+of+schizophrenic+relapse:+a+longitudinal+study.">The vulnerability/stress model of schizophrenic relapse: a longitudinal study.</a> Acta Psychiatr Scand, Supp. 382, 58-64 .</li><li>Keshavan, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Premorbid+cognitive+deficits+in+young+relatives+of+schizophrenia+patients.">Premorbid cognitive deficits in young relatives of schizophrenia patients.</a> Front Hum Neurosc. 3 (62), (2010).</li><li>Kiehl, K. A., Liddle, P. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+event-related+functional+magnetic+resonance+imaging+study+of+an+auditory+oddball+task+in+schizophrenia.">An event-related functional magnetic resonance imaging study of an auditory oddball task in schizophrenia.</a> Schizophr Re. 48, 159-171 (2001).</li><li>Bramon, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Is+the+P300+wave+an+endophenotype+for+schizophrenia?+A+meta-analysis+and+a+family+study.">Is the P300 wave an endophenotype for schizophrenia? A meta-analysis and a family study.</a> Neuroimag. 27, 960-968 (2005).</li><li>Dichter, G. S., Bellion, C., Casp, M., Belger, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impaired+modulation+of+attention+and+emotion+in+schizophrenia.">Impaired modulation of attention and emotion in schizophrenia.</a> Schizophr Bul. 36, 595-606 (2010).</li><li>Fichtenholtz, H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emotion-attention+network+interactions+during+a+visual+oddball+task.">Emotion-attention network interactions during a visual oddball task.</a> Brain Res Cogn Brain Re. 20, 67-80 (2004).</li><li>Voyvodic, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+fMRI+paradigm+control,+physiology,+and+behavior+combined+with+near+real-time+statistical+analysis.">Real-time fMRI paradigm control, physiology, and behavior combined with near real-time statistical analysis.</a> Neuroimag. 10, 91-106 (1999).</li><li>Lang, P. J., Bradley, M. M., Cuthbert, B. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> International affective picture system (IAPS): Digitized photographs, instruction manual and affective ratings. Technical Report A-6. , (2005).</li><li>Smith, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+functional+and+structural+MR+image+analysis+and+implementation+as+FSL.">Advances in functional and structural MR image analysis and implementation as FSL.</a> Neuroimag. 23, 208-219 (2004).</li><li>Smith, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast+robust+automated+brain+extraction.">Fast robust automated brain extraction.</a> Hum Brain Map. 17, 143-155 (2002).</li><li>Jenkinson, M., Bannister, P., Brady, M., Smith, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+optimization+for+the+robust+and+accurate+linear+registration+and+motion+correction+of+brain+images.">Improved optimization for the robust and accurate linear registration and motion correction of brain images.</a> Neuroimag. 17, 825-841 (2002).</li><li>Jenkinson, M., Smith, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+global+optimisation+method+for+robust+affine+registration+of+brain+images.">A global optimisation method for robust affine registration of brain images.</a> Med Image Ana. 5, 143-156 (2001).</li><li>Woolrich, M. W., Ripley, B. D., Brady, M., Smith, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+autocorrelation+in+univariate+linear+modeling+of+FMRI+data.">Temporal autocorrelation in univariate linear modeling of FMRI data.</a> Neuroimag. 14, 1370-1386 (2001).</li><li>Beckmann, C. F., Jenkinson, M., Smith, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=General+multilevel+linear+modeling+for+group+analysis+in+FMRI.">General multilevel linear modeling for group analysis in FMRI.</a> Neuroimag. 20, 1052-1063 (2003).</li><li>Woolrich, M. W., Behrens, T. E., Beckmann, C. F., Jenkinson, M., Smith, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multilevel+linear+modelling+for+FMRI+group+analysis+using+Bayesian+inference.">Multilevel linear modelling for FMRI group analysis using Bayesian inference.</a> Neuroimag. 21, 1732-1747 (2004).</li><li>Genovese, C. R., Lazar, N. A., Nichols, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thresholding+of+statistical+maps+in+functional+neuroimaging+using+the+false+discovery+rate.">Thresholding of statistical maps in functional neuroimaging using the false discovery rate.</a> Neuroimag. 15, 870-878 (2002).</li><li>Hart, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Altered+fronto-limbic+activity+in+children+and+adolescents+with+familial+high+risk+for+schizophrenia..">Altered fronto-limbic activity in children and adolescents with familial high risk for schizophrenia..</a> Psychiatry Re. 212, 19-27 (2013).</li><li>Hariri, A. R., Bookheimer, S. Y., Mazziotta, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modulating+emotional+responses:+effects+of+a+neocortical+network+on+the+limbic+system.">Modulating emotional responses: effects of a neocortical network on the limbic system.</a> Neurorepor. 11, 43-48 (2000).</li><li>Gottesman, I. I., Gould, T. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+endophenotype+concept+in+psychiatry:+etymology+and+strategic+intentions.">The endophenotype concept in psychiatry: etymology and strategic intentions.</a> Am J Psyc. 160, 636-645 (2003).</li><li>Glahn, D. C., Thompson, P. M., Blangero, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuroimaging+endophenotypes:+strategies+for+finding+genes+influencing+brain+structure+and+function.">Neuroimaging endophenotypes: strategies for finding genes influencing brain structure and function.</a> Hum Brain Map. 28, 488-501 (2007).</li></ol>

Dr. Perkins is currently receiving grant support from Janssen, and is a consultant to Dainippon. In the past, Dr. Perkins is or has been on speaker's bureau for Eli Lilly and AstraZeneca. Dr. Perkins has previously received grants from AstraZeneca, Bristol-Myers Squibb, Otsuka, Eli Lilly, Janssen and Pfizer; and consulting and educational fees from AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen, Glaxo Smith Kline, Forest Labs, Pfizer and Shire. All other authors declare no biomedical financial interests or potential conflict of interest.

The modified emotional oddball paradigm in the current study has been shown to elicit differences in neural recruitment during selective attention and emotional processing in children and adolescents at risk for schizophrenia. While existing paradigms using the emotional oddball task have been used to investigate neural changes in adult populations with psychiatric illness8, the current paradigm may be particularly useful for measurement of vulnerability markers in younger age groups. 
There are several challenges inherent in performing fMRI studies with children and adolescents, including ensuring that the task is appropriate in terms of difficulty and content and in minimizing motion artifacts. Critical steps in the protocol include step 2.2, which requires that participants have a mock scan and practice session prior to the fMRI session. This step is particularly helpful for improving participants&#8217; comfort and data quality. Additionally, the design of the behavioral task is critical to ensure that the task has an appropriate level of difficulty and that the selection of aversive images is appropriate for younger age groups. The current task design was successful in eliciting significant behavioral differences between the aversive and neutral conditions and had a moderate difficulty level for both high-risk and control groups. 
A limitation of this protocol was that the task did not elicit a significant difference in amygdala activation between the aversive and neutral conditions. There was significant amygdala activation during the aversive condition, but the difference was not significant when contrasted with neutral stimuli. This finding is likely due to the selection of children-appropriate stimuli. Future modifications of the task could examine effects of emotional facial expressions, which may produce more robust differences in amygdala activation between emotional and neutral conditions21. 
Other future applications of this technique include applying it to populations of children and adolescents who may be at risk for other psychiatric illnesses that may similarly affect executive and emotional processing. Several other psychiatric conditions, such as bipolar disorder and mood disorders, have been found to be associated with alterations in brain structure and function that reflect endophenotypes, or heritable markers associated with a disease22,23. This suggests the possibility that these intermediate changes in brain structure or function may potentially precede the onset of pathological symptoms in at-risk individuals. The use of the described paradigm in longitudinal studies and with children and adolescents may help to identify relevant endophenotypes for a particular condition to help to refine risk estimates.

Schizophrenia is a neurodevelopmental disorder with a known genetic component1,2 and with symptoms including deficits in both executive and emotional processing3,4. First-degree relatives are thought to be at an increased risk of developing schizophrenia, and have been shown to share some of these same neurocognitive deficits in both cognitive and social-emotional domains5. We therefore expect that brain activity in regions associated with executive and emotional processing may be altered in at-risk family members preceding the onset of clinical symptoms. 
Previous studies have indicated that both adults with schizophrenia and adults at familial high risk show aberrant activity within executive and emotional processing networks; however it remains unclear how these changes come about during development. Demonstrating that these changes occur early in life will be a critical first step in understanding the pathophysiology of the disorder. Therefore, this study utilizes an emotional oddball paradigm during functional MRI (fMRI) scanning in order to measure brain activity during the completion of a task that requires both executive and emotional processing in adolescents who are at risk for developing schizophrenia. Oddball paradigms are frequently used to examine the function of fronto-striate circuitry in schizophrenia6 and in individuals with familial high risk7 by measuring selective attention processes allocated to task-relevant target stimuli. Here, a standard oddball task has been modified to include task-irrelevant aversive and neutral stimuli that have been shown to elicit changes in brain activity in patients with schizophrenia8. 
This paper measures functional differences between healthy adolescents and adolescents at high familial risk for schizophrenia using an emotional oddball task. The task design is similar to that used by Fichtenholtz and colleagues9, but the selection of aversive emotional images has been modified to be appropriate for children between the ages of 9-18. The use of this task during functional MRI allowed for the identification of specific brain regions that showed patterns of hyperactivation and hypoactivation in children and adolescents with FHR for schizophrenia, in addition to age-related changes in neural activity during adolescent development.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td class="xl63">3T MRI scanner</td>
			<td class="xl63">GE</td>
			<td class="xl63"></td>
			<td class="xl63">BIAC 3T scanner (replaced)</td>
		</tr>
	</tbody>
</table>

measurement of fronto-limbic activity using an emotional oddball task in children with familial high risk for schizophrenia

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with schizophrenia who are at familial high risk (FHR) may show similar cognitive and emotional changes. However, the neurological changes underlying the emergence of these symptoms remain unclear. This study sought to identify differences in frontal, striatal, and limbic regions in children and adolescents with FHR using functional magnetic resonance imaging. Groups of 21 children and adolescents at FHR and 21 healthy controls completed an emotional oddball task that relied on selective attention and the suppression of task-irrelevant emotional information. The standard oddball task was modified to include aversive and neutral distractors in order to examine potential group differences in both emotional and executive processing. This task was designed specifically to allow for children and adolescents to complete by keeping the difficulty and emotional image content age-appropriate. Furthermore, we demonstrate a technique for suitable fMRI registration for children and adolescent participants. This paradigm may also be applied in future studies to measure changes in neural activity in other populations with hypothesized developmental changes in executive and emotional processing.

人口統計学的特性20に基づいてグループ間の差は認められませんでした。行動データは、ターゲット検出タスクは9-18歳の小児および青年のための難しさの適切なレベルであることを示しました。現在の研究では、正しくターゲット（SD = 0.14）の82.36パーセントを同定し、および家族のリスクグループは、正しくターゲット（SD = 0.17）の76.8パーセントを同定し制御します。両グループは、中性の写真に比べて感情的な絵を識別する際の精度を低下が示された（F（1,40）= 5.63、P = 0.03）。 撮像データは、実験条件は幹部と感情的処理中に動員されることが予想領域において有意な活性化を導いたことを示しました。活性化は、目標試験中、右扁桃体、二国間の眼窩前頭皮質、紡錘状皮質と視覚CORで前頭前野、前部尾状、島、および後部頭頂領域に見られました両群ともに嫌悪試験中ticalエリア。表1は、各条件のコントロールに有意な活性化の領域を示しています。 このパラダイムはまた、コントロールと統合失調症の家族リスクが高い個人間の活性化に有意な差を誘発しました。家族ハイリスクグループは、刺激をターゲットに応じて前頭線条回路内の活性化を減少を示しました。コントロールは、対照的に、中前頭回と島でより活性化を示しました。条件間の群差は、表2及び図2に示されている家族性高リスク群は、標的に応答してコントロールと嫌悪刺激（ 図3）と比較して、年齢に関連した活性化の異なるパターンを示しました。 <img alt="図2" src="/files/ftp_upload/51484/51484fig2.jpg" /> 群間差の2アクティベーションマップ図。（A）家族性高リスク群（n = 21）は、ターゲット処理中に制御した（n = 21）よりも大きな活性化を示した領域は。 CAUD =尾状。 IFG =下前頭回。 ITG =下側頭回。コントロールは、ターゲットの処理中に家族性高リスク群よりも高い活性化を示した（B）の分野。 INS =島。 MFG =ミドル前頭回。 MTGは=中側頭回。 （C） 家族ハイリスクグループは嫌悪&gt;ニュートラルコントラストの間にコントロールよりももっと活性化領域。 COC =中央ふたの皮質。コントロールは嫌悪&gt;ニュートラルコントラストの間に家族ハイリスク群よりも活性化（D）分野。 ACC =前帯状皮質; PC =楔前部。この図は、ハートらから変更されている。20、許可を得て。 <a href="https://www.jove.com/files/ftp_upload/51484/51484fig2large.jpg" target="_blank">このFの拡大版を表示するには、こちらをクリックしてください</a>igure。 <img alt="図3" src="/files/ftp_upload/51484/51484fig3.jpg" /> 図3.加齢群差の活性化マップ。ターゲット処理中に対照よりも家族高リスク群では年齢とともに大きく正の相関を持つ（A）エリア。 ACC =前帯状皮質; INS =島。 OFC =眼窩前頭皮質; TH =視床。嫌悪&gt;ニュートラルコントラスト時の家族高リスク群よりも対照の加齢に伴う大きな正の相関を持つ（B）エリア。 IFG =下前頭回。 PostCG =中心後回。 PreCG =中心前回。この図は、許可を得て、ハートら20から変更されている。 <a href="https://www.jove.com/files/ftp_upload/51484/51484fig3large.jpg" target="_blank">この図の拡大版をご覧になるにはこちらをクリックしてください。</a> <table border="0" cellpadding="0" cellspacing="0"> &lt;TBODY&gt; <tr><td> ST1。群内の活性化巣のコントロールで（N = 21） </td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td colspan="3"> MNI座標</td><td></td><td></td></tr><tr><td>領域</td><td>半球</td><td> X </td><td> Y </td><td> Z </td><td>最大Z値</td><td>最大p値1 </td></tr><tr><td>活性化した（p &lt;0.05、偽発見率補正された）を標的</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ミドル前頭回/前頭極</td><td> B </td><td> -30 </td><td> -2 </td><td> 50 </td><td> 5.57 </td><td> &lt;0.0000001 </td></tr><tr><td>下前頭回</td><td> B </td><td> 46 </td><td> 12 </td><td> 32 </td><td> 5.41 </td><td> &lt;0.0000001 </td></tr><tr><td>島</td><td> B </td><td> -32 </td><td> 24 </TD&gt; <td> 0 </td><td> 5.4 </td><td> &lt;0.0000001 </td></tr><tr><td>中心前回</td><td> B </td><td> -40 </td><td> -22 </td><td> 48 </td><td> 5.53 </td><td> &lt;0.0000001 </td></tr><tr><td>視床</td><td> B </td><td> -12 </td><td> -16 </td><td> 12 </td><td> 5.03 </td><td> &lt;0.0000001 </td></tr><tr><td>尾状</td><td> B </td><td> -12 </td><td> 12 </td><td> 4 </td><td> 4.07 </td><td> 0.000003 </td></tr><tr><td>被殻</td><td> B </td><td> 18 </td><td> 8 </td><td> 2 </td><td> 4.27 </td><td> 0.00009 </td></tr><tr><td>前帯状/ Paracingulate状回</td><td> B </td><td> 0 </td><td> 12 </td><td> 46 </td><td> 5.6 </td><td> &lt;0.0000001 </td></tr><tr><td>後部帯状回</td><td> B </td><td> 8 </td><td> -16 </td><td> 28 </td><td> 5.2 </td><td> &lt;0.0000001 </td></tr><tr><td>スーペリア/中側頭回</td> &lt;TD&gt; B </td><td> 48 </td><td> -46 </td><td> 10 </td><td> 5.88 </td><td> &lt;0.0000001 </td></tr><tr><td>紡錘/下側頭回</td><td> B </td><td> -30 </td><td> -50 </td><td> -12 </td><td> 5.64 </td><td> &lt;0.0000001 </td></tr><tr><td>上頭頂小葉/縁上回/中心後回</td><td> B </td><td> 30 </td><td> -44 </td><td> 44 </td><td> 6 </td><td> &lt;0.0000001 </td></tr><tr><td>横後頭部皮質</td><td> B </td><td> 48 </td><td> -62 </td><td> 12 </td><td> 6.12 </td><td> &lt;0.0000001 </td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>嫌悪&gt;中性活性化（p &lt;0.05、補正後の偽発見率） </td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>下前頭回</td><td> L </td><td> -44 </td><td> 14 </TD&gt; <td> 14 </td><td> 3.16 </td><td> 0.0004 </td></tr><tr><td>前頭極/内側前頭皮質</td><td> B </td><td> -2 </td><td> 64 </td><td> 0 </td><td> 3.42 </td><td> 0.0005 </td></tr><tr><td>中心後回</td><td> L </td><td> -62 </td><td> -22 </td><td> 34 </td><td> 3.12 </td><td> 0.0004 </td></tr><tr><td>前帯状皮質</td><td> B </td><td> -4 </td><td> 34 </td><td> 8 </td><td> 3.27 </td><td> 0.0002 </td></tr><tr><td>後部帯状回</td><td> B </td><td> 0 </td><td> -44 </td><td> 28 </td><td> 3.26 </td><td> 0.0002 </td></tr><tr><td>下側頭葉/紡錘状回</td><td> B </td><td> -44 </td><td> -44 </td><td> -14 </td><td> 3.03 </td><td> 0.0006 </td></tr><tr><td>角回</td><td> B </td><td> 46 </td><td> -64 </td><td> 8 </td><td> 3.42 </td><td> 0.0001 </td></tr><tr><td>縁上回</td><td> L </td><td> -40 </td><td> -56 </td><td> 20 </td><td> 3.59 </td><td> 0.00005 </td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>嫌悪活性化（p &lt;0.05、補正後の偽発見率） </td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>扁桃体</td><td> R </td><td> 22 </td><td> -4 </td><td> -18 </td><td> 2.86 </td><td> 0.001 </td></tr><tr><td>眼窩前頭皮質/島</td><td> B </td><td> 36 </td><td> 22 </td><td> -4 </td><td> 4.93 </td><td> &lt;0.0000001 </td></tr><tr><td>ミドル前頭回</td><td> B </td><td> 32 </td><td> 4 </td><td> 40 </td><td> 4.7 </td><td> &lt;0.0000001 </td></tr><tr><td>前頭極</td><td> B </td><td> -38 </td><td> 36 </td><td> 10 </td><td> 4.95 </td><td> &lt;0.0000001 </td></tr><tr><td>前帯状/paracingulate状回</td><td> B </td><td> 6 </td><td> 16 </td><td> 50 </td><td> 4.85 </td><td> &lt;0.0000001 </td></tr><tr><td>後部帯状回</td><td> B </td><td> 2 </td><td> -28 </td><td> 24 </td><td> 5.88 </td><td> &lt;0.0000001 </td></tr><tr><td>視床</td><td> B </td><td> 18 </td><td> -26 </td><td> 2 </td><td> 5.44 </td><td> &lt;0.0000001 </td></tr><tr><td>中心前回</td><td> B </td><td> -44 </td><td> 8 </td><td> 34 </td><td> 4.54 </td><td> &lt;0.0000001 </td></tr><tr><td>上頭頂小葉</td><td> B </td><td> -20 </td><td> -56 </td><td> 54 </td><td> 6.05 </td><td> &lt;0.0000001 </td></tr><tr><td>横後頭部皮質</td><td> B </td><td> -36 </td><td> -82 </td><td> 4 </td><td> 6.05 </td><td> &lt;0.0000001 </td></tr><tr><td>後頭極</td><td> B </td><td> -16 </td><td> -90 </td><td> 18 </td><td> 5.18 </td&gt; <td> &lt;0.0000001 </td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> B、​​二国間</td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td></tr><tr><td> 1報告p値は、FDR-補正値&lt;0.05で有意で、補正していません</td></tr></tbody></table> コントロール（N = 21）で群内の活性化巣表1は、このテーブルは、許可を得て、ハートら20から変更されています。 <table border="0" cellpadding="0" cellspacing="0"><tbody><tr><td>表2群間のアクティベーションの違い</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td colspan="3"> MNI座標</td><td></td><td></td></TR&gt; <tr><td></td><td>半球</td><td> X </td><td> Y </td><td> Z </td><td>最大Z値</td><td>最大p値1 </td></tr><tr><td>ターゲット</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>家族性リスク&gt;コントロール（P &lt;0.05、偽発見率補正しました） </td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>前頭極</td><td> B </td><td> 16 </td><td> 76 </td><td> 6 </td><td> 3.52 </td><td> 0.00007 </td></tr><tr><td>下前頭回</td><td> L </td><td> -58 </td><td> 16 </td><td> 18 </td><td> 3.37 </td><td> 0.0001 </td></tr><tr><td>尾状</td><td> B </td><td> -14 </td><td> 20 </td><td> 10 </td><td> 3.2 </td><td> 0.0003 </td></tr><tr><td>下側頭回</td><td> L </td><td> -52 </td><td> -44 </td><td> -20 </td><td> 2.94 </td><td> 0.0009 </td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>コントロール&gt;家族高リスク（P &lt;0.05、偽発見率を修正） </td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ミドル前頭回/中心前回</td><td> R </td><td> 48 </td><td> 8 </td><td> 34 </td><td> 3 </td><td> 0.0007 </td></tr><tr><td>前頭蓋皮質</td><td> L </td><td> -46 </td><td> 16 </td><td> -4 </td><td> 2.94 </td><td> 0.0009 </td></tr><tr><td>補足運動野</td><td> R </td><td> 18 </td><td> -16 </td><td> 40 </td><td> 3.02 </td><td> 0.0007 </td></tr><tr><td>島</td><td> L </td><td> -34 </td><td> -18 </td><td> 4 </td><td> 2.94 </td><td> 0.0009 </td></tr><tr><td>中心前回</td><td> B </td><td> 10 </td><td> -26 </td><td> 60 </td&gt; <td> 3.29 </td><td> 0.0002 </td></tr><tr><td>中心後回</td><td> B </td><td> 14 </td><td> -38 </td><td> 54 </td><td> 3.57 </td><td> 0.0001 </td></tr><tr><td>上側頭回</td><td> R </td><td> 54 </td><td> -6 </td><td> -4 </td><td> 3.18 </td><td> 0.0003 </td></tr><tr><td>中側頭回</td><td> R </td><td> 48 </td><td> -46 </td><td> 8 </td><td> 3.65 </td><td> 0.00004 </td></tr><tr><td>楔前部</td><td> R </td><td> 2 </td><td> -40 </td><td> 46 </td><td> 2.89 </td><td> 0.001 </td></tr><tr><td>横後頭部皮質</td><td> B </td><td> -20 </td><td> -74 </td><td> 36 </td><td> 3.36 </td><td> 0.0002 </td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>嫌悪 - ニュートラル</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><tD&gt;家族性リスク&gt;コントロール（P &lt;0.05、偽発見率を修正） </td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> Centralふたの皮質</td><td> R </td><td> 50 </td><td> -2 </td><td> 6 </td><td> 3.01 </td><td> 0.0007 </td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>コントロール&gt;家族高リスク（P &lt;0.05、偽発見率を修正） </td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>前帯状皮質</td><td> L </td><td> -6 </td><td> 38 </td><td> 8 </td><td> 2.68 </td><td> 0.002 </td></tr><tr><td>楔前部</td><td> L </td><td> -10 </td><td> -54 </td><td> 36 </td><td> 2.7 </td><td> 0.002 </td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> B、​​二国間</td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td></tr><tr><td> 1報告p値は、FDR-補正値&lt;0.05で有意で、補正していません</td></tr></tbody></table> 表2は、群間の活性化病巣の違い。このテーブルには、許可を得て、ハートら20から変更されています。

Watch this Scientific Journal Video about Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia at JoVE.com

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

This paper describes how to use the emotional oddball task and fMRI to measure brain activation in children and adolescents at familial high risk for schizophrenia (FHR).&#160;FMRI was used to measure differences in fronto-striato-limbic regions during an emotional oddball task. Children with FHR exhibited abnormal functional activation during adolescence.

統合失調症のための家族ハイリスク児の感情オドボール課題を用いて前頭辺縁系の活性の測定

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with ...

measurement-fronto-limbic-activity-using-an-emotional-oddball-task

Nanyang Technological University

Research

JoVE Journal

Behavior

8.8K ビュー.  University of North Carolina at Chapel Hill School of Medicine. This paper describes how to use the emotional oddball task and fMRI to measure brain activation in children and adolescents at familial high risk for schizophrenia (FHR). FMRI was used to measure differences in fronto-striato-limbic regions during an emotional oddball task. Children with FHR exhibited abnormal functional activation during adolescence.

ビデオ: Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant. The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. These are infants who are at increased risk for poor developmental outcome because of insults during prenatal development, such as substance exposure or prematurity or factors such as poverty, poor nutrition or lack of prenatal care that can have adverse effects on the intrauterine environment and affect the developing fetus. The NNNS assesses the full range of infant neurobehavioral performance including neurological integrity, behavioral functioning, and signs of stress/abstinence. The NNNS is a noninvasive neonatal assessment tool with demonstrated validity as a predictor, not only of medical outcomes such as cerebral palsy diagnosis, neurological abnormalities, and diseases with risks to the brain, but also of developmental outcomes such as mental and motor functioning, behavior problems, school readiness, and IQ. The NNNS can identify infants at high risk for abnormal developmental outcome and is an important clinical tool that enables medical researchers and health practitioners to identify these infants and develop intervention programs to optimize the development of these infants as early as possible. The video shows the NNNS procedures, shows examples of normal and abnormal performance and the various clinical populations in which the exam can be used.

The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. The purpose of this article is to describe the NNNS, provide video examples of the NNNS procedures and discuss the ways in which the exam has been used.

NICUネットワーク神経行動スケール：ハイリスク新生児の評価と評価

There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant.  The NICU Network Neurobehavioral Scale ...

行動学

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Na&#239;ve Adolescents at High Risk for Psychosis

Growing evidence suggests that movement abnormalities are a core feature of psychosis. One marker of movement abnormality, dyskinesia, is a result of impaired neuromodulation of dopamine in fronto-striatal pathways. The traditional methods for identifying movement abnormalities include observer-based reports and force stability gauges. The drawbacks of these methods are long training times for raters, experimenter bias, large site differences in instrumental apparatus, and suboptimal reliability. Taking these drawbacks into account has guided the development of better&#160;standardized and more efficient procedures to examine movement abnormalities through handwriting analysis software and tablet. Individuals at&#160;risk for psychosis showed significantly more dysfluent pen movements (a proximal measure for dyskinesia) in a handwriting task. Handwriting kinematics offers a great advance over previous methods of assessing dyskinesia, which could clearly be beneficial for understanding the etiology of psychosis.

Handwriting analysis software significantly improves upon existing instruments measuring movement disorders. Individuals at&#160;risk for psychosis and healthy controls completed handwriting tasks to test for dyskinesia. Results suggest that youth at&#160;risk for psychosis exhibit dyskinesia and that handwriting analysis could significantly contribute to wider dissemination of early identification efforts

手書きの分析は精神病のリスクが高い神経弛緩ナイーブ青年の自発ジスキネジアを示し

Growing evidence suggests that movement abnormalities are a core feature of psychosis. One marker of movement abnormality, dyskinesia, is a result of ...

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess children&#39;s cortical processing of light touch, speech sounds and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing children discomfort. To accomplish this we developed a dual channel, time and strength calibrated air puff stimulator that allows both tactile stimulation and sham control. We combined this with the use of event-related potential methodology to allow for high temporal resolution of signals from the primary and secondary somatosensory cortices as well as higher order processing. This methodology also allowed us to measure a multisensory response to auditory-tactile stimulation.

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess infants and children&#39;s cortical processing of light touch, speech sounds, and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing discomfort in vulnerable patients.

障害児における皮質聴覚、触覚情報処理の定量的評価

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology ...

Cortical Source Analysis of High-Density EEG Recordings in Children

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.&#160;
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how&#160;EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.&#160;

In recent years, there has been increasing interest in estimating the cortical sources of scalp measured electrical activity for cognitive neuroscience experiments. This article describes how high density EEG is acquired and how recordings are processed for cortical source estimation in children from the age of 2 years at the London Baby Lab.

子供高密度脳波記録の皮質ソース解析

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and ...

Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression

Ruminative brooding is associated with increased vulnerability to major depression. Individuals who regularly ruminate will often try to reduce the frequency of their negative thoughts by actively suppressing them. We aim to identify the neural correlates underlying thought suppression in at-risk and depressed individuals. Three groups of women were studied; a major depressive disorder group, an at-risk group (having a first degree relative with depression) and controls. Participants performed a mixed block-event fMRI paradigm involving thought suppression, free thought and motor control periods. Participants identified the re-emergence of &#8220;to-be-suppressed&#8221; thoughts (&#8220;popping&#8221; back into conscious awareness) with a button press. During thought suppression the control group showed the greatest activation of the dorsolateral prefrontal cortex, followed by the at-risk, then depressed group. During the re-emergence of intrusive thoughts compared to successful re-suppression of those thoughts, the control group showed the greatest activation of the anterior cingulate cortices, followed by the at-risk, then depressed group. At-risk participants displayed anomalies in the neural regulation of thought suppression resembling the dysregulation found in depressed individuals. The predictive value of these changes in the onset of depression remains to be determined.

We aim to identify the neural correlates underlying sustained and transient thought suppression, and thought re-emergence in controls, at-risk and depressed individuals. Activation was greatest for controls compared to the at-risk and the depressed group in the dorsolateral prefrontal cortex during thought suppression and anterior cingulate cortex during thought re-emergence.

fMRIの研究は、うつ病のため、と若い女性に思考抑制を調べると、アットリスクの設計と実装

Ruminative brooding is associated with increased vulnerability to major depression. Individuals who regularly ruminate will often try to reduce the ...

Acquisition of a High-precision Skilled Forelimb Reaching Task in Rats

Movements are the main measurable output of central nervous system function. Developing behavioral paradigms that allow detailed analysis of motor learning and execution is of critical importance in order to understand the principles and processes that underlie motor function. Here we present a paradigm to study movement acquisition within a daily session of training (within-session) representing the fast learning component and primary acquisition as well as skilled motor learning over several training sessions (between-session) representing the slow learning component and consolidation of the learned task. This behavioral paradigm increases the degree of difficulty and complexity of the motor skill task due to two features: First, the animal realigns its body prior to each pellet retrieval forcing renewed orientation and preventing movement execution from the same angle. Second, pellets are grasped from a vertical post that matches the diameter of the pellet and is placed in front of the cage. This requires a precise grasp for successful pellet retrieval and thus prevents simple pulling of the pellet towards the animal. In combination with novel genetics, imaging and electrophysiological technologies, this behavioral method will aid to understand the morphological, anatomical and molecular underpinnings of motor learning and memory.

A paradigm is presented to analyze the acquisition of a high-precision skilled forelimb reaching task in rats.

ラットでのタスクに到達高精度熟練前肢の取得

Movements are the main measurable output of central nervous system function. Developing behavioral paradigms that allow detailed analysis of motor ...

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. Delay discounting tasks are used to identify indifference points, which reflect equal preference for two dichotomous reward alternatives differing in both delay and magnitude. Indifference points are key to assessing the shape of a delay-discounting gradient because they allow us to isolate the effect of delay on value. For example, if at a 1 week delay and a maximum of $1,000, the indifference point is at $700 we know that, for that participant, a 1-week delay corresponds to a 30% reduction in value. This video outlines an adjusting amount delay-discounting task that identifies indifference points relatively quickly and is inexpensive and easy to administer. Once data have been collected, non-linear regression techniques are typically used to generate discounting curves. The steepness of the discounting curve reflects the degree of impulsive choice of a group or individual. These techniques have been used with a wide range of commodities and have identified populations that are relatively impulsive. For example, people with substance abuse problems discount delayed rewards more steeply than control participants. Although degree of discounting varies as a function of the commodity examined, discounting of one commodity correlates with discounting of other commodities, which suggests that discounting may be a persistent pattern of behavior1.

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. We outline a computer-based delay discounting task that is easy to implement and allows for the quantification of the degree of delay discounting in human participants.

遅延測定は、調整量のタスクを使用した人間で割引します

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. Delay discounting tasks ...

The Emotional Stroop Task: Assessing Cognitive Performance under Exposure to Emotional Content

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than to ink colors of neutral words. The difference shows that people are affected by the emotional content conveyed by the carrier words even though they are irrelevant to the color-naming task at hand. The ESE has been widely deployed with patient populations, as well as with non-selected populations, because the emotion words can be selected to match the tested pathology. The ESE is a powerful tool, yet it is vulnerable to various threats to its validity. This report refers to potential sources of confounding and includes a modal experiment that provides the means to control for them. The most prevalent threat to the validity of existing ESE studies is sustained effects and habituation wrought about by repeated exposure to emotion stimuli. Consequently, the order of exposure to emotion and neutral stimuli is of utmost importance. We show that in the standard design, only one specific order produces the ESE.

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than those of neutral words. This report refers to potential sources of confounding and includes a modal experiment that provides the means to control for them.

情動ストループ課題：感情的なコンテンツへの曝露下での認知能力を評価します

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than to ink colors of neutral words. The ...

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery

Human pain models are useful in the assessing the analgesic effect of drugs, providing information about a drug&#39;s pharmacology and identify potentially suitable therapeutic populations. The need to use a comprehensive battery of pain models is highlighted by studies whereby only a single pain model, thought to relate to the clinical situation, demonstrates lack of efficacy. No single experimental model can mimic the complex nature of clinical pain. The integrated, multi-modal pain task&#160;battery presented here encompasses the electrical stimulation task, pressure stimulation task, cold pressor task, the UVB inflammatory model which includes a thermal task and a paradigm for inhibitory conditioned pain modulation. These human pain models have been tested for predicative validity and reliability both in their own right and in combination, and can be used repeatedly, quickly, in short succession, with minimum burden for the subject and with a modest quantity of equipment. This allows a drug to be fully characterized and profiled for analgesic effect which is especially useful for drugs with a novel or untested mechanism of action.

Human pain models are valuable tools used to assess the analgesic potential of novel compounds and predict their clinical efficacy, especially when used in an integrated manner. Although implementation of these models is complex, with proper execution, the pain models described in this protocol can provide predictive and reliable results.

統合された、マルチモーダル痛みタスクのバッテリーを使用痛みの検出と許容閾値を決定

Human pain models are useful in the assessing the analgesic effect of drugs, providing information about a drug&#39;s pharmacology and identify ...

A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting

Involvement of patients and the public is now recognized to be essential for the good conduct of research. Patient and public involvement in research priority setting and funding decisions is only beginning to be recognized as important, and methods for doing so are nascent. This protocol describes the Research Prioritization by Affected Communities (RPAC) protocol and findings from its use with women at high socio-demographic risk for preterm birth. The goal was to directly involve these women in identifying and prioritizing their unanswered questions about pregnancy, birth and neonatal care, and treatment so that their views could be included in research priority setting by funders and researchers. The RPAC protocol may be used to meaningfully involve under-represented groups at high-risk for specific health problems, or those who face disproportionate burden of disease, in research strategy and funding priority setting.

This manuscript describes the Research Prioritization by Affected Communities (RPAC) protocol and findings from its use with women at risk for preterm birth. Using the protocol, women identified and prioritized their unanswered questions about pregnancy, birth and neonatal care aimed at influencing research priority setting by funders and researchers.

研究の優先順位設定で早産の危険性が高い色の女性を含む手法

Involvement of patients and the public is now recognized to be essential for the good conduct of research. Patient and public involvement in research ...