Vision Jurnal Club
VSS practice talks and posters: two presentations currently scheduled
This meeting is from 11:30-1 Thursday 1 May in 211 Guthrie Hall. NOTE EARLIER TIME. If others wish to practice their VSS presentations please contact John Palmer. Current presentations: * Serap Yigit presents: "Partially valid cueing and spatial filtering reveal different kinds of selection" * Alec Scharff presents: "Distinguishing serial and parallel models using variations of the simultaneous-sequential paradigm" (05/01/2008) |
Ione Fine presents "V1 Projection Zone Signals in Human Macular Degeneration Depend on Task, not Stimulus"
This meeting is from 12-1 Thursday 6 March in 211 Guthrie Hall. Masuda, Dumoulin, Nakadomari & Wandell (2008). Crebral Cortex We used functional magnetic resonance imaging to assess abnormal cortical signals in humans with juvenile macular degeneration (JMD). These signals have been interpreted as indicating large-scale cortical reorganization. Subjects viewed a stimulus passively or performed a task; the task was either related or unrelated to the stimulus. During passive viewing, or while performing tasks unrelated to the stimulus, there were large unresponsive V1 regions. These regions included the foveal projection zone, and we refer to them as the lesion projection zone (LPZ). In 3 JMD subjects, we observed highly significant responses in the LPZ while they performed stimulus-related judgments. In control subjects, where we presented the stimulus only within the peripheral visual field, there was no V1 response in the foveal projection zone in any condition. The difference between JMD and control responses can be explained by hypotheses that have very different implications for V1 reorganization. In controls retinal afferents carry signals indicating the presence of a uniform (zero-contrast) region of the visual field. Deletion of retinal input may 1) spur the formation of new cortical pathways that carry taskdependent signals (reorganization), or 2) unmask preexisting taskdependent cortical signals that ordinarily are suppressed by the deleted signals (no reorganization). A copy of the article can be found at: http://faculty.washington.edu/jpalmer/files/VisionJournalClub/ (03/06/2008) |
Serap Yigit presents "Attentional mechanisms in visual signal detection: The effects of simultaneous and delayed noise and pattern masks"
This meeting is from 12-1 Thursday 28 Feb in 211 Guthrie Hall. Smith & Wolfgang (2007). Perception & Psychophysics, 69, 1093-1104 The attentional cuing effects in detection and some discrimination tasks depend on the use of backward masks and on the presence of external noise in the display. These effects have been attributed to an interruption masking mechanism, which terminates stimulus processing prematurely, and an external noise exclusion mechanism, which minimizes the perceptual effects of noise. To test whether the dependencies on masking and external noise are expressions of a single mechanism, observers detected grating patch stimuli, masked with noise masks or pattern masks, presented either simultaneously or after a delay of 60_90 msec. Contrary to an external noise exclusion account, but consistent with an interruption masking account, cuing effects were largest when the masks were delayed. However, weaker cuing effects were obtained with simultaneous masks, contrary to an interruption masking account. These results suggest that attentional effects in simple visual judgments are affected by mechanisms of both kinds. A copy of the article can be found at: http://faculty.washington.edu/jpalmer/files/VisionJournalClub/ (02/28/2008) |
Roozbeh Kiani presents "Bayesian inference with probabilistic population codes" by Ma, Beck, Latham and Pouget.
This meeting is from 12-1 Thursday 21 Feb in 211 Guthrie Hall. Bayesian inference with probabilistic population codes. Ma WJ, Beck JM, Latham PE, Pouget A. Nat Neurosci. 2006 Nov;9(11):1432-8. Recent psychophysical experiments indicate that humans perform near-optimal Bayesian inference in a wide variety of tasks, ranging from cue integration to decision making to motor control. This implies that neurons both represent probability distributions and combine those distributions according to a close approximation to Bayes' rule. At first sight, it would seem that the high variability in the responses of cortical neurons would make it difficult to implement such optimal statistical inference in cortical circuits. We argue that, in fact, this variability implies that populations of neurons automatically represent probability distributions over the stimulus, a type of code we call probabilistic population codes. Moreover, we demonstrate that the Poisson-like variability observed in cortex reduces a broad class of Bayesian inference to simple linear combinations of populations of neural activity. These results hold for arbitrary probability distributions over the stimulus, for tuning curves of arbitrary shape and for realistic neuronal variability. A copy of the article can be found at: http://faculty.washington.edu/jpalmer/files/VisionJournalClub/ (02/21/2008) |
Page 1 of 7 | Next | Last
