3 resultados para Visual identification tasks

em Duke University


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Practice can improve performance on visual search tasks; the neural mechanisms underlying such improvements, however, are not clear. Response time typically shortens with practice, but which components of the stimulus-response processing chain facilitate this behavioral change? Improved search performance could result from enhancements in various cognitive processing stages, including (1) sensory processing, (2) attentional allocation, (3) target discrimination, (4) motor-response preparation, and/or (5) response execution. We measured event-related potentials (ERPs) as human participants completed a five-day visual-search protocol in which they reported the orientation of a color popout target within an array of ellipses. We assessed changes in behavioral performance and in ERP components associated with various stages of processing. After practice, response time decreased in all participants (while accuracy remained consistent), and electrophysiological measures revealed modulation of several ERP components. First, amplitudes of the early sensory-evoked N1 component at 150 ms increased bilaterally, indicating enhanced visual sensory processing of the array. Second, the negative-polarity posterior-contralateral component (N2pc, 170-250 ms) was earlier and larger, demonstrating enhanced attentional orienting. Third, the amplitude of the sustained posterior contralateral negativity component (SPCN, 300-400 ms) decreased, indicating facilitated target discrimination. Finally, faster motor-response preparation and execution were observed after practice, as indicated by latency changes in both the stimulus-locked and response-locked lateralized readiness potentials (LRPs). These electrophysiological results delineate the functional plasticity in key mechanisms underlying visual search with high temporal resolution and illustrate how practice influences various cognitive and neural processing stages leading to enhanced behavioral performance.

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Remembering past events - or episodic retrieval - consists of several components. There is evidence that mental imagery plays an important role in retrieval and that the brain regions supporting imagery overlap with those supporting retrieval. An open issue is to what extent these regions support successful vs. unsuccessful imagery and retrieval processes. Previous studies that examined regional overlap between imagery and retrieval used uncontrolled memory conditions, such as autobiographical memory tasks, that cannot distinguish between successful and unsuccessful retrieval. A second issue is that fMRI studies that compared imagery and retrieval have used modality-aspecific cues that are likely to activate auditory and visual processing regions simultaneously. Thus, it is not clear to what extent identified brain regions support modality-specific or modality-independent imagery and retrieval processes. In the current fMRI study, we addressed this issue by comparing imagery to retrieval under controlled memory conditions in both auditory and visual modalities. We also obtained subjective measures of imagery quality allowing us to dissociate regions contributing to successful vs. unsuccessful imagery. Results indicated that auditory and visual regions contribute both to imagery and retrieval in a modality-specific fashion. In addition, we identified four sets of brain regions with distinct patterns of activity that contributed to imagery and retrieval in a modality-independent fashion. The first set of regions, including hippocampus, posterior cingulate cortex, medial prefrontal cortex and angular gyrus, showed a pattern common to imagery/retrieval and consistent with successful performance regardless of task. The second set of regions, including dorsal precuneus, anterior cingulate and dorsolateral prefrontal cortex, also showed a pattern common to imagery and retrieval, but consistent with unsuccessful performance during both tasks. Third, left ventrolateral prefrontal cortex showed an interaction between task and performance and was associated with successful imagery but unsuccessful retrieval. Finally, the fourth set of regions, including ventral precuneus, midcingulate cortex and supramarginal gyrus, showed the opposite interaction, supporting unsuccessful imagery, but successful retrieval performance. Results are discussed in relation to reconstructive, attentional, semantic memory, and working memory processes. This is the first study to separate the neural correlates of successful and unsuccessful performance for both imagery and retrieval and for both auditory and visual modalities.

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Many neurons in the frontal eye field (FEF) exhibit visual responses and are thought to play important roles in visuosaccadic behavior. The FEF, however, is far removed from striate cortex. Where do the FEF's visual signals come from? Usually they are reasonably assumed to enter the FEF through afferents from extrastriate cortex. Here we show that, surprisingly, visual signals also enter the FEF through a subcortical route: a disynaptic, ascending pathway originating in the intermediate layers of the superior colliculus (SC). We recorded from identified neurons at all three stages of this pathway (n=30-40 in each sample): FEF recipient neurons, orthodromically activated from the SC; mediodorsal thalamus (MD) relay neurons, antidromically activated from FEF and orthodromically activated from SC; and SC source neurons, antidromically activated from MD. We studied the neurons while monkeys performed delayed saccade tasks designed to temporally resolve visual responses from presaccadic discharges. We found, first, that most neurons at every stage in the pathway had visual responses, presaccadic bursts, or both. Second, we found marked similarities between the SC source neurons and MD relay neurons: in both samples, about 15% of the neurons had only a visual response, 10% had only a presaccadic burst, and 75% had both. In contrast, FEF recipient neurons tended to be more visual in nature: 50% had only a visual response, none had only a presaccadic burst, and 50% had both a visual response and a presaccadic burst. This suggests that in addition to their subcortical inputs, these FEF neurons also receive other visual inputs, e.g. from extrastriate cortex. We conclude that visual activity in the FEF results not only from cortical afferents but also from subcortical inputs. Intriguingly, this implies that some of the visual signals in FEF are pre-processed by the SC.