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The main question driving work in the lab is how the brain constructs our subjective experience of the world as we actively engage with our surroundings. A basic challenge for the brain is to parse continuous and dynamic sensory input into discrete and stable percepts, in order to guide cognition and action. We study this interaction of perception, attention, memory and action within a cognitive neuroscience framework.<\/p>\n
Specifically, our approach can be described as “active cognition”: while most studies of perception are based on responses to an abstract stimulus on a single trial during steady fixation, our work examines the way that perception interacts with context, action (particularly eye movements), memory, emotion and the tasks goals.<\/p>\n
In particular, our research uses behavioral and neuroimaging methods to explore the way that temporal factors in neural processing play a critical role in cognition. Our research suggests that the brain’s time frames play a role in organizing and aligning perception, attention, cognition and action.<\/p>\n
We also explore how Individual and clinical differences in spatial and temporal processing influence how we interact with technology and the natural world and impact development across the lifespan.<\/p>\n
<\/strong><\/p>\n Current projects in the lab fall into the following main themes:<\/strong><\/p>\n 1.\u00a0 How quickly can the brain process information? Individual differences, neural correlates, brain rhythms, clinical applications, stress & sleep, interventions to track and change brain speed.\u00a0 [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Perception andActive Cognition LabPerceptionand ActiveCognition LabBridging Senses and Thought: The Neuroscience of PerceptionThe main question driving work in the lab is how the brain constructs our subjective experience of the world as we actively engage with our surroundings. A basic challenge for the brain is to parse continuous and dynamic sensory input into discrete and […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-13","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/pages\/13","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/comments?post=13"}],"version-history":[{"count":6,"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/pages\/13\/revisions"}],"predecessor-version":[{"id":243,"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/pages\/13\/revisions\/243"}],"wp:attachment":[{"href":"https:\/\/sites.nyuad.nyu.edu\/activecognition\/wp-json\/wp\/v2\/media?parent=13"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
2.\u00a0 Mental imagery: individual differences and neural correlates, computational\/AI models, similarities and differences with visual memory, brain-computer interfaces.
3.\u00a0 How does the brain use past experience to predict the future: neural correlates, individual differences, clinical differences.
4.\u00a0 Arabic word recognition in adults and children: does learning Arabic change the organization of language and cognition in the brain?<\/p>\n