scholarly journals From sounds to words: A neurocomputational model of adaptation, inhibition and memory processes in auditory change detection

NeuroImage ◽  
2011 ◽  
Vol 54 (1) ◽  
pp. 170-181 ◽  
Author(s):  
Max Garagnani ◽  
Friedemann Pulvermüller
Neuroscience ◽  
2017 ◽  
Vol 355 ◽  
pp. 141-148 ◽  
Author(s):  
Marcus Heldmann ◽  
Thomas F. Münte ◽  
Lejla Paracka ◽  
Frederike Beyer ◽  
Norbert Brüggemann ◽  
...  

2015 ◽  
Vol 126 (8) ◽  
pp. e77
Author(s):  
A.-K. Beck ◽  
G. Lütjens ◽  
K. Schwabe ◽  
R. Dengler ◽  
J.K. Krauss ◽  
...  

2013 ◽  
Vol 17 (2) ◽  
pp. 282-297 ◽  
Author(s):  
Vesa Putkinen ◽  
Mari Tervaniemi ◽  
Katri Saarikivi ◽  
Pauliina Ojala ◽  
Minna Huotilainen

2011 ◽  
Vol 81 (3) ◽  
pp. 312-316 ◽  
Author(s):  
Marta Bortoletto ◽  
Giuliano De Min Tona ◽  
Simona Scozzari ◽  
Simone Sarasso ◽  
Luciano Stegagno

NeuroImage ◽  
2002 ◽  
Vol 15 (1) ◽  
pp. 167-174 ◽  
Author(s):  
Bertram Opitz ◽  
Teemu Rinne ◽  
Axel Mecklinger ◽  
D.Yves von Cramon ◽  
Erich Schröger

2009 ◽  
Author(s):  
Koji Inui ◽  
Tomokazu Urakawa ◽  
Koya Yamashiro ◽  
Naofumi Otsuru ◽  
Yasuyuki Takeshima ◽  
...  

2013 ◽  
Vol 25 (5) ◽  
pp. 730-742 ◽  
Author(s):  
Sebastian Puschmann ◽  
Riklef Weerda ◽  
Georg Klump ◽  
Christiane M. Thiel

Psychophysical experiments show that auditory change detection can be disturbed in situations in which listeners have to monitor complex auditory input. We made use of this change deafness effect to segregate the neural correlates of physical change in auditory input from brain responses related to conscious change perception in an fMRI experiment. Participants listened to two successively presented complex auditory scenes, which consisted of six auditory streams, and had to decide whether scenes were identical or whether the frequency of one stream was changed between presentations. Our results show that physical changes in auditory input, independent of successful change detection, are represented at the level of auditory cortex. Activations related to conscious change perception, independent of physical change, were found in the insula and the ACC. Moreover, our data provide evidence for significant effective connectivity between auditory cortex and the insula in the case of correctly detected auditory changes, but not for missed changes. This underlines the importance of the insula/anterior cingulate network for conscious change detection.


2017 ◽  
Vol 118 (5) ◽  
pp. 2526-2536 ◽  
Author(s):  
Bridgette Johnson ◽  
Rebeka Verma ◽  
Manying Sun ◽  
Timothy D. Hanks

A critical component of decision making is determining when to commit to a choice. This involves stopping rules that specify the requirements for decision commitment. Flexibility of decision stopping rules provides an important means of control over decision-making processes. In many situations, these stopping rules establish a balance between premature decisions and late decisions. In this study we use a novel change detection paradigm to examine how subjects control this balance when invoking different decision stopping rules. The task design allows us to estimate the temporal weighting of sensory information for the decisions, and we find that different stopping rules did not result in systematic differences in that weighting. We also find bidirectional post-error alterations of decision strategy that depend on the type of error and effectively reduce the probability of making consecutive mistakes of the same type. This is a generalization to change detection tasks of the widespread observation of unidirectional post-error slowing in forced-choice tasks. On the basis of these results, we suggest change detection tasks as a promising paradigm to study the neural mechanisms that support flexible control of decision rules. NEW & NOTEWORTHY Flexible decision stopping rules confer control over decision processes. Using an auditory change detection task, we found that alterations of decision stopping rules did not result in systematic changes in the temporal weighting of sensory information. We also found that post-error alterations of decision stopping rules depended on the type of mistake subjects make. These results provide guidance for understanding the neural mechanisms that control decision stopping rules, one of the critical components of decision making and behavioral flexibility.


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