A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

Multiple lines of research provide compelling evidence for a role of the cerebellum in a wide array of cognitive and affective functions, going far beyond ...

Monash University

Serotonergic (SSRI) and noradrenergic (NRI) antidepressants modulate biases in emotional processing such that perceptual bias is shifted away from negative and towards positive emotional material. However, the effects of serotonergic and noradrenergic modulation on the temporal course (occurring in milliseconds) of emotional processing, and in particular, the rapid physiological changes associated with the different stages of emotional processing, are unknown.

Evidence for modulation of facial emotional processing bias during emotional expression decoding by serotonergic and noradrenergic antidepressants: an event-related potential (ERP) study.

Patients with major depressive disorder (MDD) show deficits in processing of facial emotions that persist beyond recovery and cessation of treatment. Abnormalities in neural areas supporting attentional control and emotion processing in remitted depressed (rMDD) patients suggests that there may be enduring, trait-like abnormalities in key neural circuits at the interface of cognition and emotion, but this issue has not been studied systematically.

Abnormal prefrontal activity subserving attentional control of emotion in remitted depressed patients during a working memory task with emotional distracters.

L&#39;Iowa Gambling Task (IGT) est, &agrave; bien des &eacute;gards, l&#39;&eacute;talon-or pour d&eacute;montrer la prise de d&eacute;cision dans les groupes de toxicomanes. Cependant, c&#39;est ne pas clair comment base propri&eacute;t&eacute;s des t&acirc;ches telles que la fr&eacute;quence et l&#39;ampleur des r&eacute;compenses et des pertes affectent le comportement de choix chez les utilisatrices de drogues et m&ecirc;me dans les joueurs sains. Dans cette &eacute;tude, nous avons utilis&eacute; une variante de l&#39;IGT, la Soochow Gambling Task (SGT), pour observer le comportement de choix chez les usagers d&#39;opiac&eacute;s et les d&eacute;cideurs en sant&eacute; dans une t&acirc;che o&ugrave; fr&eacute;quence de r&eacute;compense n&#39;est pas confondue avec les r&eacute;sultats &agrave; long terme de chaque solution de rechange. Dans les deux usagers d&#39;opiac&eacute;s (n = 26) et t&eacute;moins sains (n = 27), nous montrons que la fr&eacute;quence r&eacute;compense influence fortement le comportement de choix dans les IGT et Sgt aucun des deux groupes ont montr&eacute; une pr&eacute;f&eacute;rence coh&eacute;rente dans l&#39;ensemble de t&acirc;ches pour des solutions de rechange avec bons r&eacute;sultats &agrave; long terme, mais plut&ocirc;t les sujets semblaient pr&eacute;f&eacute;rer les alternatives que gagner plus souvent. Nous interpr&eacute;tons cela comme preuve pour sugg&eacute;rer que des joueurs sains effectuent mieux que les usagers d&#39;opiac&eacute;s sur l&#39;IGT parce qu&#39;ils sont capables d&#39;utiliser des fr&eacute;quences de gain-perte pour guider leur comportement de choix sur la t&acirc;che. Il conteste la notion pr&eacute;c&eacute;dente que les moins bons r&eacute;sultats sur l&#39;IGT in drug users est due &agrave; une incapacit&eacute; &agrave; &ecirc;tre guid&eacute; par les cons&eacute;quences futures.

En comparant l&#39;iowa et soochow jeu de t&acirc;ches &agrave; des usagers d&#39;opiac&eacute;s.

&#x7231;&#x8377;&#x534E;&#x5DDE;&#x8D4C;&#x535A;&#x4EFB;&#x52A1; (IGT) &#x5728;&#x8BB8;&#x591A;&#x65B9;&#x9762;&#x662F;&#x8868;&#x660E;&#x836F;&#x7269;&#x4F7F;&#x7528;&#x7FA4;&#x4F53;&#x51B3;&#x7B56;&#x7684;&#x9EC4;&#x91D1;&#x6807;&#x51C6;&#x3002;&#x7136;&#x800C;&#xFF0C;&#x5C1A;&#x4E0D;&#x6E05;&#x695A;&#x5982;&#x4F55;&#x57FA;&#x672C;&#x4EFB;&#x52A1;&#x5C5E;&#x6027;&#xFF0C;&#x5982;&#x7684;&#x9891;&#x7387;&#x548C;&#x4E25;&#x91CD;&#x7A0B;&#x5EA6;&#x5956;&#x52B1;&#x548C;&#x635F;&#x5931;&#x5F71;&#x54CD;&#x9009;&#x62E9;&#x884C;&#x4E3A;&#x5728;&#x5438;&#x6BD2;&#x8005;&#x3001; &#x751A;&#x81F3;&#x5728;&#x5065;&#x5EB7;&#x7684;&#x7403;&#x5458;&#x3002;&#x5728;&#x8FD9;&#x9879;&#x7814;&#x7A76;&#xFF0C;&#x6211;&#x4EEC;&#x7528;&#x4E8E;&#x7CD6;&#x8010;&#x91CF;&#x51CF;&#x4F4E;&#xFF0C;&#x4E1C;&#x5434;&#x8D4C;&#x535A;&#x4EFB;&#x52A1; (SGT) &#x7684;&#x53D8;&#x4F53;&#xFF0C;&#x89C2;&#x5BDF;&#x9E26;&#x7247;&#x5242;&#x7528;&#x6237;&#x9009;&#x62E9;&#x884C;&#x4E3A;&#x4E0E;&#x5065;&#x5EB7;&#x51B3;&#x7B56;&#x8005;&#x5728;&#x4EFB;&#x52A1;&#x4E2D;&#x7684;&#x51E1;&#x5956;&#x52B1;&#x9891;&#x7387;&#x4E0D;&#x4E0E;&#x6BCF;&#x4E2A;&#x66FF;&#x4EE3;&#x65B9;&#x6848;&#x7684;&#x957F;&#x671F;&#x7ED3;&#x679C;&#x76F8;&#x6DF7;&#x6DC6;&#x3002;&#x5728;&#x8FD9;&#x4E24;&#x4E2A;&#x9E26;&#x7247;&#x5242;&#x7528;&#x6237; &#xFF08;n = 26) &#x548C;&#x5065;&#x5EB7;&#x5BF9;&#x7167;&#x7EC4; (n = 27)&#xFF0C;&#x6211;&#x4EEC;&#x8868;&#x660E;&#x5956;&#x52B1;&#x9891;&#x7387;&#x5F3A;&#x70C8;&#x5730;&#x5F71;&#x54CD;&#x6211;&#x4EEC;&#x7684;&#x7CD6;&#x8010;&#x91CF;&#x51CF;&#x4F4E;&#x548C;&#x4E2D;&#x58EB;&#x4E00;&#x81F4;&#x503E;&#x5411;&#x4E8E;&#x8DE8;&#x4EFB;&#x52A1;&#x5177;&#x6709;&#x826F;&#x597D;&#x7684;&#x957F;&#x671F;&#x7ED3;&#x679C;&#xFF0C;&#x66FF;&#x4EE3;&#x8FD9;&#x4E24;&#x7EC4;&#x4E2D;&#x7684;&#x9009;&#x62E9;&#x884C;&#x4E3A;&#xFF0C;&#x4F46;&#x76F8;&#x53CD;&#xFF0C;&#x4E3B;&#x4F53;&#x4F3C;&#x4E4E;&#x66F4;&#x559C;&#x6B22;&#x8D62;&#x5F97;&#x6700;&#x9891;&#x7E41;&#x7684;&#x66FF;&#x4EE3;&#x54C1;&#x3002;&#x6211;&#x4EEC;&#x5C06;&#x8FD9;&#x89E3;&#x91CA;&#x4E3A;&#x8BC1;&#x636E;&#x8868;&#x660E;&#x5065;&#x5EB7;&#x7403;&#x5458;&#x6BD4;&#x7CD6;&#x8010;&#x91CF;&#x51CF;&#x4F4E;&#x5BF9;&#x9E26;&#x7247;&#x5242;&#x7528;&#x6237;&#x66F4;&#x597D;&#x5730;&#x6267;&#x884C;&#x56E0;&#x4E3A;&#x4ED6;&#x4EEC;&#x53EF;&#x4EE5;&#x5229;&#x7528;&#x6536;&#x76CA;&#x635F;&#x5931;&#x9891;&#x7387;&#x6765;&#x6307;&#x5BFC;&#x5176;&#x9009;&#x62E9;&#x884C;&#x4E3A;&#x7684;&#x4EFB;&#x52A1;&#x3002;&#x8FD9;&#x6311;&#x6218;&#x524D;&#x4E00;&#x79CD;&#x89C2;&#x5FF5;&#xFF0C;&#x5373;&#x5728;&#x5438;&#x6BD2;&#x8005;&#x4E2D;&#x7CD6;&#x8010;&#x91CF;&#x51CF;&#x4F4E;&#x5BF9;&#x6027;&#x80FD;&#x8F83;&#x5DEE;&#x662F;&#x7531;&#x4E8E;&#x4E0D;&#x80FD;&#x4EE5;&#x672A;&#x6765;&#x540E;&#x679C;&#x4E3A;&#x6307;&#x5BFC;&#x3002;

&#x6BD4;&#x8F83;&#x7684;&#x7231;&#x8377;&#x534E;&#x5DDE;&#x548C;&#x4E1C;&#x5434;&#x8D4C;&#x535A;&#x4E2D;&#x9E26;&#x7247;&#x7C7B;&#x7528;&#x6237;&#x7684;&#x4EFB;&#x52A1;&#x3002;

The Iowa Gambling Task (IGT) is in many respects the gold standard for demonstrating decision making in drug using groups. However, it is not clear how basic task properties such as the frequency and magnitude of rewards and losses affect choice behavior in drug users and even in healthy players. In this study, we used a variant of the IGT, the Soochow Gambling Task (SGT), to observe choice behavior in opiate users and healthy decision makers in a task where reward frequency is not confounded with the long-term outcome of each alternative. In both opiate users (nâ€‰=â€‰26) and healthy controls (nâ€‰=â€‰27), we show that reward frequency strongly influences choice behavior in the IGT and SGT. Neither group showed a consistent preference across tasks for alternatives with good long-term outcomes, but rather, subjects appeared to prefer alternatives that win most frequently. We interpret this as evidence to suggest that healthy players perform better than opiate users on the IGT because they are able to utilize gain-loss frequencies to guide their choice behavior on the task. This challenges the previous notion that poorer performance on the IGT in drug users is due to an inability to be guided by future consequences.

Comparing the iowa and soochow gambling tasks in opiate users.

Die Iowa Gambling Task (IGT) ist in vielerlei Hinsicht den Goldstandard f&uuml;r den Nachweis der Entscheidungsfindung in der Droge, die Verwendung von Gruppen. Jedoch ist unklar, wie einfache Task-Eigenschaften wie die Frequenz und die H&ouml;he der Pr&auml;mien und Verluste Wahl Verhalten bei Drogenkonsumenten und sogar in gesunde Spieler auswirken. In dieser Studie haben wir eine Variante des IGT, Soochow Gambling Task (SGT) Wahl Verhalten in Opiatkonsumenten und gesunde Entscheidungstr&auml;ger in einer Aufgabe beobachten, wo die Belohnung Frequenz nicht mit langfristigen Verlauf der einzelnen Alternativen verwirrt ist. In beiden Opiatkonsumenten (n = 26) und gesunden Kontrollen (n = 27), wir zeigen, dass die Belohnung Frequenz stark beeinflusst Wahl Verhalten im IGT und SGT keine der beiden Gruppen zeigte eine konsequente Einstellung mehrere Vorg&auml;nge nach Alternativen mit guten langfristigen Ergebnissen, sondern vielmehr Themen erschien Alternativen zu bevorzugen, die am h&auml;ufigsten zu gewinnen. Wir interpretieren dies als Hinweise darauf, dass gesunde Spieler besser als Opiatkonsumenten auf die IGT durchgef&uuml;hrt werden, da sie nutzen, Gewinn-Verlust-Frequenzen um die Aufgabe ihrer Wahl-Verhalten f&uuml;hren k&ouml;nnen. Dies fordert die vorherige Vorstellung, dass schlechter Leistung auf die IGT bei Drogenkonsumenten aufgrund einer Unf&auml;higkeit von zuk&uuml;nftigen Folgen leiten lassen.

Vergleich von Iowa und Soochow Gl&uuml;cksspiel Aufgaben in Opiatkonsumenten.

L&#39;Iowa Gambling Task (IGT) &egrave; per molti aspetti il gold standard per dimostrare il processo decisionale nella droga utilizzando gruppi. Tuttavia, non &egrave; chiaro come base Propriet&agrave; attivit&agrave; come la frequenza e la grandezza delle ricompense e perdite influiscono sul comportamento di scelta in tossicodipendenti ed anche nei giocatori sani. In questo studio, abbiamo usato una variante di IGT, il Soochow Gambling Task (SGT), per osservare comportamento scelta di oppiacei e decisori sano in un&#39;attivit&agrave; dove frequenza ricompensa non &egrave; confuso con l&#39;esito a lungo termine di ogni alternativa. In entrambi di oppiacei (n = 26) e controlli sani (n = 27), mostriamo che frequenza ricompensa fortemente influenza il comportamento di scelta nella IGT e Sgt n&eacute; gruppo ha mostrato una preferenza costante attraverso attivit&agrave; alternative con buoni risultati a lungo termine, ma piuttosto, soggetti sembravano preferire alternative che vincere pi&ugrave; spesso. Dobbiamo interpretare questo come prova per suggerire che i giocatori sani meglio di oppiacei sull&#39;IGT eseguono perch&eacute; sono in grado di utilizzare le frequenze di guadagno-perdita per orientare il proprio comportamento di scelta sull&#39;attivit&agrave;. Questa sfida la precedente nozione che pi&ugrave; povere prestazioni su IGT nei tossicodipendenti sono dovuta all&#39;incapacit&agrave; di essere guidati da conseguenze future.

Confrontando l&#39;iowa e soochow compiti di oppiacei per il gioco d&#39;azzardo.

&#x30A2;&#x30A4;&#x30AA;&#x30EF;&#x5DDE;&#x30AE;&#x30E3;&#x30F3;&#x30D6;&#x30EB; &#x30BF;&#x30B9;&#x30AF; (IGT) &#x591A;&#x304F;&#x306E;&#x70B9;&#x3067;&#x30B0;&#x30EB;&#x30FC;&#x30D7;&#x3092;&#x4F7F;&#x7528;&#x3057;&#x3066;&#x85AC;&#x7269;&#x306E;&#x610F;&#x601D;&#x3092;&#x793A;&#x3059;&#x305F;&#x3081;&#x306E;&#x30B4;&#x30FC;&#x30EB;&#x30C9; &#x30B9;&#x30BF;&#x30F3;&#x30C0;&#x30FC;&#x30C9;&#x3067;&#x3059;&#x3002;&#x3057;&#x304B;&#x3057;&#x3001;&#x305D;&#x308C;&#x306F;&#x5468;&#x6CE2;&#x6570;&#x3068;&#x5927;&#x304D;&#x3055;&#x306E;&#x5831;&#x916C;&#x3068;&#x640D;&#x5931;&#x306E;&#x85AC;&#x7269;&#x4F7F;&#x7528;&#x8005;&#x3068;&#x5065;&#x5168;&#x306A;&#x30D7;&#x30EC;&#x30FC;&#x30E4;&#x30FC;&#x306E;&#x9078;&#x629E;&#x884C;&#x52D5;&#x306B;&#x5F71;&#x97FF;&#x3092;&#x4E0E;&#x3048;&#x308B;&#x306A;&#x3069;&#x3001;&#x3069;&#x306E;&#x3088;&#x3046;&#x306B;&#x57FA;&#x672C;&#x7684;&#x306A;&#x30BF;&#x30B9;&#x30AF;&#x306E;&#x30D7;&#x30ED;&#x30D1;&#x30C6;&#x30A3;&#x3092;&#x30AA;&#x30D5;&#x306B;&#x3057;&#x306A;&#x3044;&#x3067;&#x3059;&#x3002;&#x672C;&#x7814;&#x7A76;&#x3067;&#x306F;&#x3001;&#x3042;&#x3078;&#x3093;&#x5264;&#x306E;&#x30E6;&#x30FC;&#x30B6;&#x30FC;&#x306E;&#x9078;&#x629E;&#x884C;&#x52D5;&#x3068;&#x5065;&#x5EB7;&#x7684;&#x306A;&#x610F;&#x601D;&#x6C7A;&#x5B9A;&#x30BF;&#x30B9;&#x30AF;&#x3067;&#x3069;&#x3053;&#x5831;&#x916C;&#x5468;&#x6CE2;&#x6570;&#x306E;&#x5404;&#x4EE3;&#x66FF;&#x6848;&#x306E;&#x9577;&#x671F;&#x7684;&#x306A;&#x7D50;&#x679C;&#x3068;&#x6DF7;&#x540C;&#x3057;&#x306A;&#x3044;&#x89B3;&#x5BDF;&#x3059;&#x308B;&#x306E;&#x306B; IGT&#x3001;&#x6771;&#x5449;&#x30AE;&#x30E3;&#x30F3;&#x30D6;&#x30EB; &#x30BF;&#x30B9;&#x30AF; (SGT) &#x306E;&#x30D0;&#x30EA;&#x30A2;&#x30F3;&#x30C8;&#x3092;&#x4F7F;&#x7528;&#x3057;&#x307E;&#x3057;&#x305F;&#x3002;&#x4E21;&#x65B9;&#x306E;&#x3042;&#x3078;&#x3093;&#x5264;&#x306E;&#x30E6;&#x30FC;&#x30B6;&#x30FC;&#x3067; (n = 26) &#x3068;&#x5065;&#x5168;&#x306A;&#x30B3;&#x30F3;&#x30C8;&#x30ED;&#x30FC;&#x30EB; (n = 27)&#x3001;&#x79C1;&#x9054;&#x306F;&#x5831;&#x916C;&#x5468;&#x6CE2;&#x6570;&#x5F37;&#x304F;&#x9078;&#x629E;&#x884C;&#x52D5; IGT &#x3068;&#x30B1;&#x30ED;&#x30ED;&#x306E;&#x826F;&#x3044;&#x9577;&#x671F;&#x7684;&#x306A;&#x6210;&#x679C;&#x3092;&#x4EE3;&#x66FF;&#x306E;&#x305F;&#x3081;&#x306E;&#x30BF;&#x30B9;&#x30AF;&#x306E;&#x9593;&#x3067;&#x4E00;&#x8CAB;&#x3057;&#x305F;&#x597D;&#x307F;&#x3092;&#x793A;&#x3057;&#x305F;&#x3069;&#x3061;&#x3089;&#x306E;&#x30B0;&#x30EB;&#x30FC;&#x30D7;&#x306B;&#x5F71;&#x97FF;&#x3092;&#x4E0E;&#x3048;&#x308B;&#x304C;&#x3001;&#x3080;&#x3057;&#x308D;&#x3001;&#x88AB;&#x9A13;&#x8005;&#x304C;&#x6700;&#x3082;&#x983B;&#x7E41;&#x306B;&#x52DD;&#x5229;&#x306E;&#x9078;&#x629E;&#x80A2;&#x3092;&#x597D;&#x3080;&#x767B;&#x5834;&#x3092;&#x793A;&#x3057;&#x307E;&#x3059;&#x3002;&#x6211;&#x3005; &#x306F;&#x3053;&#x306E;&#x30BF;&#x30B9;&#x30AF;&#x306E;&#x5F7C;&#x3089;&#x306E;&#x9078;&#x629E;&#x306E;&#x632F;&#x308B;&#x821E;&#x3044;&#x3092;&#x30AC;&#x30A4;&#x30C9;&#x3059;&#x308B;&#x5229;&#x76CA;&#x640D;&#x5931;&#x306E;&#x5468;&#x6CE2;&#x6570;&#x3092;&#x4F7F;&#x7528;&#x3059;&#x308B;&#x3053;&#x3068;&#x304C;&#x3067;&#x304D;&#x308B;&#x306E;&#x3067;&#x5065;&#x5EB7;&#x306A;&#x30D7;&#x30EC;&#x30FC;&#x30E4;&#x30FC;&#x3001;IGT &#x306E;&#x3042;&#x3078;&#x3093;&#x5264;&#x30E6;&#x30FC;&#x30B6;&#x30FC;&#x3088;&#x308A;&#x5B9F;&#x884C;&#x3092;&#x793A;&#x5506;&#x3059;&#x308B;&#x8A3C;&#x62E0;&#x3068;&#x3057;&#x3066;&#x89E3;&#x91C8;&#x3057;&#x307E;&#x3059;&#x3002;&#x3053;&#x308C;&#x306F;&#x3001;&#x8CA7;&#x3057;&#x3044;&#x30D1;&#x30D5;&#x30A9;&#x30FC;&#x30DE;&#x30F3;&#x30B9;&#x85AC;&#x7269;&#x4F7F;&#x7528;&#x8005;&#x306E; IGT &#x306B;&#x4ECA;&#x5F8C;&#x306E;&#x5F71;&#x97FF;&#x306B;&#x3088;&#x3063;&#x3066;&#x5C0E;&#x304B;&#x308C;&#x308B;&#x3053;&#x3068;&#x304C;&#x3067;&#x304D;&#x306A;&#x3044;&#x3053;&#x3068;&#x304C;&#x539F;&#x56E0;&#x3067;&#x3059;&#x524D;&#x306E;&#x6982;&#x5FF5;&#x306B;&#x6311;&#x6226;&#x3057;&#x307E;&#x3059;&#x3002;

&#x30A2;&#x30A4;&#x30AA;&#x30EF;&#x5DDE;&#x3001;&#x3042;&#x3078;&#x3093;&#x5264;&#x306E;&#x30E6;&#x30FC;&#x30B6;&#x30FC;&#x306E;&#x30BF;&#x30B9;&#x30AF;&#x3092;&#x30AE;&#x30E3;&#x30F3;&#x30D6;&#x30EB;&#x5449;&#x3092;&#x6BD4;&#x8F03;&#x3057;&#x307E;&#x3059;&#x3002;

&#xC544;&#xC774;&#xC624;&#xC640; &#xB3C4;&#xBC15; &#xC791;&#xC5C5; (IGT)&#xB294; &#xC5EC;&#xB7EC; &#xCE21;&#xBA74;&#xC5D0;&#xC11C; &#xC2DC;&#xC5F0; &#xADF8;&#xB8F9;&#xC744; &#xC0AC;&#xC6A9; &#xD558;&#xB294; &#xC57D;&#xBB3C;&#xC5D0; &#xC758;&#xC0AC; &#xACB0;&#xC815;&#xC5D0; &#xB300; &#xD55C; &#xD669;&#xAE08; &#xD45C;&#xC900;&#xC785;&#xB2C8;&#xB2E4;. &#xADF8;&#xB7EC;&#xB098;, &#xC8FC;&#xD30C;&#xC218;&#xC640; &#xBCF4;&#xC0C1; &#xBC0F; &#xC190;&#xC2E4; &#xADDC;&#xBAA8; &#xB9C8;&#xC57D; &#xC0AC;&#xC6A9;&#xC790;&#xC640; &#xAC74;&#xAC15; &#xD55C; &#xC120;&#xC218;&#xC5D0;&#xB3C4; &#xC120;&#xD0DD; &#xB3D9;&#xC791;&#xC5D0; &#xC601;&#xD5A5;&#xC744; &#xAC19;&#xC740; &#xAE30;&#xBCF8; &#xC791;&#xC5C5; &#xC18D;&#xC131;&#xC744; &#xD655;&#xC2E4; &#xD558;&#xC9C0; &#xC54A;&#xC2B5;&#xB2C8;&#xB2E4;. &#xC774; &#xC5F0;&#xAD6C;&#xC5D0;&#xC11C;&#xB294; &#xAC01; &#xB300;&#xC548;&#xC758; &#xC7A5;&#xAE30; &#xACB0;&#xACFC;&#xC640; &#xBCF4;&#xC0C1; &#xC8FC;&#xD30C;&#xC218; &#xD558;&#xC9C0; &#xD63C;&#xB3D9; &#xD588;&#xB2E4; &#xAC74;&#xAC15; &#xD55C; &#xC758;&#xC0AC; &#xACB0;&#xC815;&#xC790; &#xC791;&#xC5C5;&#xC5D0; &#xC544;&#xD3B8; &#xC0AC;&#xC6A9;&#xC790;&#xC5D0;&#xC11C; &#xC120;&#xD0DD; &#xB3D9;&#xC791;&#xC744; &#xAD00;&#xCC30; &#xD558;&#xB294; Soochow &#xB3C4;&#xBC15; &#xC791;&#xC5C5; (SGT), IGT&#xC758; variant&#xB97C; &#xC0AC;&#xC6A9; &#xD588;&#xC2B5;&#xB2C8;&#xB2E4;. &#xC544;&#xD3B8; &#xC0AC;&#xC6A9;&#xC790; &#xBAA8;&#xB450;&#xC5D0;&#xC11C; (n = 26)&#xC640; &#xAC74;&#xAC15; &#xD55C; &#xCEE8;&#xD2B8;&#xB864; (n = 27), &#xBCF4;&#xC0C1; &#xC8FC;&#xD30C;&#xC218; &#xAC15;&#xB825; &#xD558; &#xAC8C; IGT&#xC640; &#xC911;&#xC0AC; &#xBCF4;&#xC5EC;&#xC900; &#xC88B;&#xC740; &#xC7A5;&#xAE30; &#xACB0;&#xACFC;&#xC640; &#xB300;&#xC548;&#xC5D0; &#xB300; &#xD55C; &#xC791;&#xC5C5;&#xC5D0; &#xAC78;&#xCCD0; &#xC77C;&#xAD00; &#xB41C; &#xD658;&#xACBD; &#xC124;&#xC815;&#xB3C4; &#xADF8;&#xB8F9; &#xC120;&#xD0DD; &#xB3D9;&#xC791;&#xC5D0; &#xC601;&#xD5A5;&#xC744; &#xBBF8;&#xCE69;&#xB2C8;&#xB2E4; &#xD558;&#xC9C0;&#xB9CC; &#xAC00;&#xC7A5; &#xC790;&#xC8FC; &#xC2B9;&#xB9AC; &#xD558;&#xB294; &#xB300;&#xC548;&#xC744; &#xC120;&#xD638; &#xD558;&#xB294; &#xACFC;&#xBAA9; &#xB4F1;&#xC7A5; &#xD558;&#xB294; &#xC624;&#xD788;&#xB824; &#xC6B0;&#xB9AC;&#xAC00; &#xBCF4;&#xC5EC;. &#xC6B0;&#xB9AC;&#xAC00; &#xC81C;&#xC548; &#xD558;&#xB294; &#xC791;&#xC5C5;&#xC5D0; &#xADF8;&#xB4E4;&#xC758; &#xC120;&#xD0DD; &#xD589;&#xB3D9;&#xC744; &#xAC00;&#xC774;&#xB4DC;&#xB97C; &#xC774;&#xB4DD; &#xC190;&#xC2E4; &#xC8FC;&#xD30C;&#xC218;&#xB97C; &#xD65C;&#xC6A9;&#xD560; &#xC218; &#xC788;&#xAE30; &#xB54C;&#xBB38;&#xC5D0; &#xAC74;&#xAC15; &#xD55C; &#xC120;&#xC218;&#xB294; IGT&#xC5D0; &#xC544;&#xD3B8; &#xC0AC;&#xC6A9;&#xC790; &#xBCF4;&#xB2E4; &#xB354; &#xB098;&#xC740; &#xC2E4;&#xC801;&#xC744; &#xC99D;&#xAC70;&#xB85C;&#xC774; &#xD574;&#xC11D;. &#xC774; &#xB3C4;&#xC804; &#xC774;&#xC804; &#xAC1C;&#xB150; &#xC57D;&#xBB3C; &#xC0AC;&#xC6A9;&#xC790;&#xC5D0;&#xC11C; IGT&#xC5D0; &#xAC00;&#xB09C;&#xD55C; &#xC131;&#xB2A5;&#xC744; &#xBBF8;&#xB798;&#xC758; &#xACB0;&#xACFC; &#xC758;&#xD574; &#xC720;&#xB3C4; &#xB420; &#xC218; &#xC5C6;&#xAE30; &#xB54C;&#xBB38; &#xC774;&#xB2E4;.

&#xC544;&#xC774;&#xC624;&#xC640; soochow &#xB3C4;&#xBC15; &#xC544;&#xD3B8; &#xC0AC;&#xC6A9;&#xC790;&#xC758; &#xC791;&#xC5C5;&#xC744; &#xBE44;&#xAD50;.

El Iowa Gambling Task (IGT) es en muchos aspectos el est&aacute;ndar de oro para demostrar la toma de decisiones en grupos que consumen drogas. Sin embargo, no est&aacute; claro c&oacute;mo b&aacute;sica propiedades de la tarea como la frecuencia y magnitud de las recompensas y las p&eacute;rdidas afectan el comportamiento de la elecci&oacute;n en usuarios de drogas e incluso en los jugadores sanos. En este estudio, se utiliz&oacute; una variante de la IGT, la Soochow Gambling Task (SGT), para observar el comportamiento de la elecci&oacute;n de los usuarios de opi&aacute;ceos y tomadores de decisiones saludables en una tarea donde la frecuencia de la recompensa no se confunde con el resultado a largo plazo de cada alternativa. En ambos usuarios de opi&aacute;ceos (n = 26) y controles sanos (n = 27), nos muestran que la frecuencia recompensa influye fuertemente el comportamiento de elecci&oacute;n en la IGT y SGT. ni grupo mostr&oacute; una preferencia constante a trav&eacute;s de tareas alternativas con buenos resultados a largo plazo, pero m&aacute;s bien temas parec&iacute;an prefieren alternativas que ganan m&aacute;s con frecuencia. Interpretamos esto como evidencia para sugerir que jugadores sanos se desempe&ntilde;an mejor que los usuarios de opi&aacute;ceos en el IGT porque son capaces de utilizar las frecuencias de las p&eacute;rdidas para guiar su comportamiento de elecci&oacute;n en la tarea. Esto desaf&iacute;a la noci&oacute;n anterior que es m&aacute;s pobre desempe&ntilde;o en la IGT en usuarios de drogas debido a una incapacidad para guiarse por las consecuencias futuras.

Comparando el iowa y soochow juego tareas en los usuarios de opi&aacute;ceos.

Abnormalities in the response of the orbitofrontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC) to negative emotional stimuli have been reported in acutely depressed patients. However, there is a paucity of studies conducted in unmedicated individuals with major depressive disorder in remission (rMDD) to assess whether these are trait abnormalities. To address this issue, 19 medication-free rMDD individuals and 20 healthy comparison (HC) participants were scanned using functional magnetic resonance imaging while performing an implicit emotion processing task in which they labeled the gender of faces depicting negative (fearful), positive (happy) and neutral facial expressions. The rMDD and HC groups were compared using a region-of-interest approach for two contrasts: fear vs. neutral and happy vs. neutral. Relative to HC, rMDD showed reduced activation in left OFC and DLPFC to fearful (vs. neutral) faces. Right DLPFC activation to fearful (vs. neutral) faces in the rMDD group showed a significant positive correlation with duration of euthymia. The findings support deficits in left OFC and DLPFC responses to negative emotional stimuli during euthymic periods of MDD, which may reflect trait markers of the illness or a 'scar' due to previous depression. Recovery may also be associated with compensatory increases in right DLPFC functioning.

Prefrontal cortical response to emotional faces in individuals with major depressive disorder in remission.

The Iowa Gambling Task (IGT) and the Soochow Gambling Task (SGT) are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning (EVL) model and the prospect valence learning (PVL) model, have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL models and, in addition, produce more consistent parameter estimates across the IGT and SGT. Twenty-six opiate users (mean age 34.23; SD 8.79) and 27 control participants (mean age 35; SD 10.44) completed both tasks. Eighteen cognitive models varying in evaluation, updating, and choice rules were fit to individual data and their performances were compared to that of a statistical baseline model to find a best fitting model. The results showed that the model combining the prospect utility function treating gains and losses separately, the decay-reinforcement updating rule, and the trial-independent choice rule performed the best in both tasks. Furthermore, the winning model produced more consistent individual parameter estimates across the two tasks than any of the other models. 

An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency.

Few studies have examined the neural correlates of emotion regulation across adolescence and young adulthood. Existing studies of cognitive reappraisal indicate that improvements in regulatory efficiency may develop linearly across this period, in accordance with maturation of prefrontal cortical systems. However, there is also evidence for adolescent differences in reappraisal specific to the activation of "social-information processing network" regions, including the amygdala and temporal-occipital cortices. Here, we use fMRI to examine the neural correlates of emotional reactivity and reappraisal in response to aversive social imagery in a group of 78 adolescents and young adults aged 15-25 years. Within the group, younger participants exhibited greater activation of temporal-occipital brain regions during reappraisal in combination with weaker suppression of amygdala reactivity-the latter being a general correlate of successful reappraisal. Further analyses demonstrated that these age-related influences on amygdala reactivity were specifically mediated by activation of the fusiform face area. Overall, these findings suggest that enhanced processing of salient social cues (i.e., faces) increases reactivity of the amygdala during reappraisal and that this relationship is stronger in younger adolescents. How these relationships contribute to well-known vulnerabilities of emotion regulation during this developmental period will be an important topic for ongoing research.

Rebecca Kerestes

Department of Neuroscience,
Central Clinical School,
Department of Neuroscience, Central Clinical School

Monash University

A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

Rebecca Kerestes

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Neuroscience,Central Clinical School,Department of Neuroscience, Central Clinical School

Monash University

A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

Department of Neuroscience,
Central Clinical School,
Department of Neuroscience, Central Clinical School