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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01kp78gg41x
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dc.contributor.advisorBrody, Carlos Den_US
dc.contributor.authorBrunton, Bingni Wenen_US
dc.contributor.otherMolecular Biology Departmenten_US
dc.date.accessioned2012-08-01T19:33:27Z-
dc.date.available2012-08-01T19:33:27Z-
dc.date.issued2012en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01kp78gg41x-
dc.description.abstractGradual accumulation of evidence is thought to be a fundamental component of decision-making. However, the mechanisms and properties of the accumulation remain unclear. Although most models have assumed a noisy accumulation process, the properties of this noise have never been isolated and measured. Here we described a decision-making task in which sensory evidence is delivered in brief, isolated pulses whose precisely-controlled timing varies within and across trials. The task is amenable to quantitative analysis that distinguishes between different decision-making dynamics and mechanisms. The task allowed us to measure, for the first time, the magnitude of noise in the accumulator's memory, separately from noise associated with the incoming sensory evidence. Remarkably, we found that the accumulator is essentially perfect: its memory is long (>1 sec) and noiseless. In contrast, the process of adding new sensory evidence is noisy and is the primary source of variability in decision-making. These results put important constraints on mechanisms underlying accumulation of evidence for decision-making.en_US
dc.language.isoenen_US
dc.publisherPrinceton, NJ : Princeton Universityen_US
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the <a href=http://catalog.princeton.edu> library's main catalog </a>en_US
dc.subjectAccumulation of evidenceen_US
dc.subjectDecision-makingen_US
dc.subjectRaten_US
dc.subject.classificationNeurosciencesen_US
dc.titleOptimal accumulation of evidence for decision-making in ratsen_US
dc.typeAcademic dissertations (Ph.D.)en_US
pu.projectgrantnumber690-2143en_US
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