The understanding of the relationship between attention and normal language processing can provide insight into the underpinnings of language disorders. Dual-task experiments can be used to understand the allocation of attention during different stages of word production. The central bottleneck model posits that while the central (response selection) stage of any cognitive task is being carried out, the same stage of any other task cannot be simultaneously carried out. The central bottleneck model permits the testing of specific hypotheses about the attentional requirements of particular elements of competing tasks. One purpose of the current study was to determine if the process of lemma selection can be said to require central attention. ...
Recent research into situation model representations has demonstrated the neglect of the temporal di...
The phenomenon of attentional capture by a unique yet irrelevant "singleton" distractor has typicall...
Computer vision tasks have seen recent improvements thanks to the development of deep learning and h...
The experiments reported in this thesis examine the time-course of talker-specificity and lexical co...
This thesis describes an investigation into a proposed theory of AI. The theory postulates that a ma...
The present study was designed to compare lexical decision latencies in visual and auditory modaliti...
Four eye-tracking experiments were conducted to understand how sentential context and lexical factor...
Verbal working memory (VWM) is the ability to dynamically preserve and manipulate verbal information...
This thesis has established the effects of perceptual load and working memory load on the conscious ...
Numerous theories have been put forth to explain the mnemonic benefits of retrieval practice relativ...
The process by which the initially attention-requiring task of transforming scribbles into meaningfu...
Brain Computer Interface (BCI) technology can be important for those unable to communicate due loss ...
The ability for humans to extract information from their environment with no more than brief glimpse...
Second language (L2) learners often state a desire to produce speech as fluently as first language (...
When speakers of gendered languages hear determiners, they anticipate nouns that share the determine...
Recent research into situation model representations has demonstrated the neglect of the temporal di...
The phenomenon of attentional capture by a unique yet irrelevant "singleton" distractor has typicall...
Computer vision tasks have seen recent improvements thanks to the development of deep learning and h...
The experiments reported in this thesis examine the time-course of talker-specificity and lexical co...
This thesis describes an investigation into a proposed theory of AI. The theory postulates that a ma...
The present study was designed to compare lexical decision latencies in visual and auditory modaliti...
Four eye-tracking experiments were conducted to understand how sentential context and lexical factor...
Verbal working memory (VWM) is the ability to dynamically preserve and manipulate verbal information...
This thesis has established the effects of perceptual load and working memory load on the conscious ...
Numerous theories have been put forth to explain the mnemonic benefits of retrieval practice relativ...
The process by which the initially attention-requiring task of transforming scribbles into meaningfu...
Brain Computer Interface (BCI) technology can be important for those unable to communicate due loss ...
The ability for humans to extract information from their environment with no more than brief glimpse...
Second language (L2) learners often state a desire to produce speech as fluently as first language (...
When speakers of gendered languages hear determiners, they anticipate nouns that share the determine...
Recent research into situation model representations has demonstrated the neglect of the temporal di...
The phenomenon of attentional capture by a unique yet irrelevant "singleton" distractor has typicall...
Computer vision tasks have seen recent improvements thanks to the development of deep learning and h...