Focusing on Attention: The Effects of Working Memory Capacity and Load on Selective Attention
AbstractBackground: Working memory (WM) is imperative for effective selective attention. Distractibility is greater under conditions of high (vs. low) concurrent working memory load (WML), and in individuals with low (vs. high) working memory capacity (WMC). In the current experiments, we recorded the flanker task performance of individuals with high and low WMC during low and high WML, to investigate the combined effect of WML and WMC on selective attention.
Methodology/Principal Findings: In
Conclusions/Significance: The current findings show that limitations in WM resources, due to either WML or individual differences in WMC, affect the spatial distribution of attention. The difference in attentional constraining between high and low WMC individuals demonstrated in the current experiments helps characterise the nature of previously established associations between WMC and controlled attention.
CitationPLoS One. 2012 Aug 28; 7(8):e43101
Showing items related by title, author, creator and subject.
Overt Attention and Context Factors: The Impact of Repeated Presentations, Image Type, and Individual MotivationKaspar, Kai; König, Peter; Tsien, Joe Z.; Department of Neurology; College of Graduate Studies (2011-07-5)The present study investigated the dynamic of the attention focus during observation of different categories of complex scenes and simultaneous consideration of individuals' memory and motivational state. We repeatedly presented four types of complex visual scenes in a pseudo-randomized order and recorded eye movements. Subjects were divided into groups according to their motivational disposition in terms of action orientation and individual rating of scene interest.
Fragment-Based Learning of Visual Object Categories in Non-Human PrimatesKromrey, Sarah; Maestri, Matthew; Hauffen, Karin; Bart, Evgeniy; Hegéd, Jay; Brain & Behavior Discovery Institute; Vision Discovery Institute; Department of Ophthalmology (2010-11-24)When we perceive a visual object, we implicitly or explicitly associate it with an object category we know. Recent research has shown that the visual system can use local, informative image fragments of a given object, rather than the whole object, to classify it into a familiar category. We have previously reported, using human psychophysical studies, that when subjects learn new object categories using whole objects, they incidentally learn informative fragments, even when not required to do so. However, the neuronal mechanisms by which we acquire and use informative fragments, as well as category knowledge itself, have remained unclear. Here we describe the methods by which we adapted the relevant human psychophysical methods to awake, behaving monkeys and replicated key previous psychophysical results. This establishes awake, behaving monkeys as a useful system for future neurophysiological studies not only of informative fragments in particular, but also of object categorization and category learning in general.
Double Dissociation of Amygdala and Hippocampal Contributions to Trace and Delay Fear ConditioningRaybuck, Jonathan D.; Lattal, K. Matthew; Tsien, Joe Z.; Department of Neurology (2011-01-19)A key finding in studies of the neurobiology of learning memory is that the amygdala is critically involved in Pavlovian fear conditioning. This is well established in delay-cued and contextual fear conditioning; however, surprisingly little is known of the role of the amygdala in trace conditioning. Trace fear conditioning, in which the CS and US are separated in time by a trace interval, requires the hippocampus and prefrontal cortex. It is possible that recruitment of cortical structures by trace conditioning alters the role of the amygdala compared to delay fear conditioning, where the CS and US overlap. To investigate this, we inactivated the amygdala of male C57BL/6 mice with GABA A agonist muscimol prior to 2-pairing trace or delay fear conditioning. Amygdala inactivation produced deficits in contextual and delay conditioning, but had no effect on trace conditioning. As controls, we demonstrate that dorsal hippocampal inactivation produced deficits in trace and contextual, but not delay fear conditioning. Further, pre- and post-training amygdala inactivation disrupted the contextual but the not cued component of trace conditioning, as did muscimol infusion prior to 1- or 4-pairing trace conditioning. These findings demonstrate that insertion of a temporal gap between the CS and US can generate amygdala-independent fear conditioning. We discuss the implications of this surprising finding for current models of the neural circuitry involved in fear conditioning.