https://nova.newcastle.edu.au/vital/access/manager/Index ${session.getAttribute("locale")} 5 https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:48711 Wed 29 Mar 2023 15:53:50 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:45283 Wed 26 Oct 2022 17:34:15 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:11825 Wed 11 Apr 2018 18:58:33 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:4635 CRs) and a centro-parietal late positivity (500-800 msec) with recollection (R Hits > K Hits, CRs). A long-term repetition effect was found for studied items judged "new" (Misses > CRs) in the same time window as the FN400, but with a posterior distribution. Finally, a centrally distributed masked priming effect was visible between 150 and 250 msec and continued into the 300-500 msec time window, where it was topographically dissociable from the FN400. These results suggest that multiple neural signals are associated with repetition and potentially contribute to recognition memory.]]> Wed 11 Apr 2018 15:28:11 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:2975 Wed 11 Apr 2018 14:37:01 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:13471 Wed 11 Apr 2018 14:31:21 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:28127 Wed 11 Apr 2018 11:53:31 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:2628 Wed 11 Apr 2018 11:31:41 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9208 Wed 11 Apr 2018 10:53:40 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9210 Wed 11 Apr 2018 10:18:26 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:31910 Wed 04 Apr 2018 10:53:35 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:54502 Tue 27 Feb 2024 15:19:03 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:34068 PLoS Computational Biology, 11, e1004316, 2015; Carlson, T. A., Ritchie, J. B., Kriegeskorte, N., Durvasula, S., & Ma, J. Reaction time for object categorization is predicted by representational distance. Journal of Cognitive Neuroscience, 26, 132–142, 2014]. Using MEG decoding, we tested if the same relationship holds when a stimulus manipulation (degradation) increases task difficulty, which we predicted would systematically decrease the distance of activation patterns from the decision boundary and increase RTs. In addition, we tested whether distance to the classifier boundary correlates with drift rates in the linear ballistic accumulator [Brown, S. D., & Heathcote, A. The simplest complete model of choice response time: Linear ballistic accumulation. Cognitive Psychology, 57, 153–178, 2008]. We found that distance to the classifier boundary correlated with RT, accuracy, and drift rates in an animacy categorization task. Split by animacy, the correlations between brain and behavior were sustained longer over the time course for animate than for inanimate stimuli. Interestingly, when examining the distance to the classifier boundary during the peak correlation between brain and behavior, we found that only degraded versions of animate, but not inanimate, objects had systematically shifted toward the classifier decision boundary as predicted. Our results support an asymmetry in the representation of animate and inanimate object categories in the human brain.]]> Tue 03 Sep 2019 18:27:13 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:35235 Tue 02 Jul 2019 14:46:42 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:51313 Thu 31 Aug 2023 14:32:38 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:54005 Thu 25 Jan 2024 13:52:36 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:55122 Thu 11 Apr 2024 08:33:31 AEST ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3740 Sat 24 Mar 2018 07:20:54 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3739 Sat 24 Mar 2018 07:20:53 AEDT ]]> https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:31944 intrinsic dimension as a proxy for target dificulty, which is estimated using optimal solutions to a combinatorial optimisation problem known as the Minimum-Feature-Set (minFS) problem. We also demonstrate that the same generalisation gains can be achieved without providing any knowledge of target difficulty.]]> Mon 23 Sep 2019 10:33:03 AEST ]]>