Age-dependent differences in human brain activity using a face- and location-matching task: An fMRI study

Purpose: To evaluate the differences of cortical activation patterns in young and elderly healthy subjects for object and spatial visual processing using a face- and location-matching task. Materials and Methods: We performed a face- and a location-matching task in 15 young (mean age: 28 +/- 9 years) and 19 elderly (mean age: 71 +/- 6 years) subjects. Each experiment consisted of 7 blocks alternating between activation and control condition. For face matching, the subjects had to indicate whether two displayed faces were identical or different. For location matching, the subjects had to press a button whenever two objects had an identical position. For control condition, we used a perception task with abstract images. Functional imaging was performed on a 1.5-tesla scanner using an EPI sequence. Results: In the face-matching task, the young subjects showed bilateral (right 1 left) activation in the occipito-temporal pathway (occipital gyrus, inferior and middle temporal gyrus). Predominantly right hemispheric activations were found in the fusiform gyrus, the right dorsolateral prefrontal cortex (inferior and middle frontal gyrus) and the superior parietal gyrus. In the elderly subjects, the activated areas in the right fronto-lateral cortex increased. An additional activated area could be found in the medial frontal gyrus (right > left). In the location-matching task, young subjects presented increased bilateral (right > left) activation in the superior parietal lobe and precuneus compared with face matching. The activations in the occipito-temporal pathway, in the right fronto-lateral cortex and the fusiform gyrus were similar to the activations found in the face-matching task. In the elderly subjects, we detected similar activation patterns compared to the young subjects with additional activations in the medial frontal gyrus. Conclusion: Activation patterns for object-based and spatial visual processing were established in the young and elderly healthy subjects. Differences between the elderly and young subjects could be evaluated, especially by using a face-matching task. Copyright (c) 2007 S. Karger AG, Basel

Explicit and Implicit Processes in Human Aversive Conditioning

The ability to adapt to a changing environment is central to an organism’s success. The process of associating two stimuli (as in associative conditioning) requires very little in the way of neural machinery. In fact, organisms with only a few hundred neurons show conditioning that is specific to an associated cue. This type of learning is commonly referred to as implicit learning. The learning can be performed in the absence of the subject’s ability to describe it. One example of learning that is thought to be implicit is delay conditioning. Delay conditioning consists of a single cue (a tone, for example) that starts before, and then overlaps with, an outcome (like a pain stimulus). In addition to associating sensory cues, humans routinely link abstract concepts with an outcome. This more complex learning is often described as explicit since subjects are able to describe the link between the stimulus and outcome. An example of conditioning that requires this type of knowledge is trace conditioning. Trace conditioning includes a separation of a few seconds between the cue and outcome. Explicit learning is often proposed to involve a separate system, but the degree of separation between implicit associations and explicit learning is still debated. We describe aversive conditioning experiments in human subjects used to study the degree of interaction that takes place between explicit and implicit systems. We do this in three ways. First, if a higher order task (in this case a working memory task) is performed during conditioning, it reduces not only explicit learning but also implicit learning. Second, we describe the area of the brain involved in explicit learning during conditioning and confirm that it is active during both trace and delay conditioning. Third, using functional magnetic resonance imaging (fMRI), we describe hemodynamic activity changes in perceptual areas of the brain that occur during delay conditioning and persist after the learned association has faded. From these studies, we conclude that there is a strong interaction between explicit and implicit learning systems, with one often directly changing the function of the other.</p

Motion processing deficits in migraine are related to contrast sensitivity

Background: There are conflicting reports concerning the ability of people with migraine to detect and discriminate visual motion. Previous studies used different displays and none adequately assessed other parameters that could affect performance, such as those that could indicate precortical dysfunction. Methods: Motion-direction detection, discrimination and relative motion thresholds were compared from participants with and without migraine. Potentially relevant visual covariates were included (contrast sensitivity; acuity; stereopsis; visual discomfort, stress, triggers; dyslexia). Results: For each task, migraine participants were less accurate than a control group and had impaired contrast sensitivity, greater visual discomfort, visual stress and visual triggers. Only contrast sensitivity correlated with performance on each motion task; it also mediated performance. Conclusions: Impaired performance on certain motion tasks can be attributed to impaired contrast sensitivity early in the visual system rather than a deficit in cortical motion processing per se. There were, however, additional differences for global and relative motion thresholds embedded in noise, suggesting changes in extrastriate cortex in migraine. Tasks to study the effects of noise on performance at different levels of the visual system and across modalities are recommended. A battery of standard visual tests should be included in any future work on the visual system and migraine

The contribution of fMRI in the study of visual categorization and expertise

No description supplie

Goal-directed attention alters the tuning of object-based representations in extrastriate cortex

Humans survive in environments that contain a vast quantity and variety of visual information. All items of perceived visual information must be represented within a limited number of brain networks. The human brain requires mechanisms for selecting only a relevant fraction of perceived information for more in-depth processing, where neural representations of that information may be actively maintained and utilized for goal-directed behavior. Object-based attention is crucial for goal-directed behavior and yet remains poorly understood. Thus, in the study we investigate how neural representations of visual object information are guided by selective attention. The magnitude of activation in human extrastriate cortex has been shown to be modulated by attention; however, object-based attention is not likely to be fully explained by a localized gain mechanism. Thus, we measured information coded in spatially distributed patterns of brain activity with fMRI while human participants performed a task requiring selective processing of a relevant visual object category that differed across conditions. Using pattern classification and spatial correlation techniques, we found that the direction of selective attention is implemented as a shift in the tuning of object-based information representations within extrastriate cortex. In contrast, we found that representations within lateral prefrontal cortex (PFC) coded for the attention condition rather than the concrete representations of object category. In sum, our findings are consistent with a model of object-based selective attention in which representations coded within extrastriate cortex are tuned to favor the representation of goal-relevant information, guided by more abstract representations within lateral PFC

Primary visual cortex activity along the apparent-motion trace reflects illusory perception

The illusion of apparent motion can be induced when visual stimuli are successively presented at different locations. It has been shown in previous studies that motion-sensitive regions in extrastriate cortex are relevant for the processing of apparent motion, but it is unclear whether primary visual cortex (V1) is also involved in the representation of the illusory motion path. We investigated, in human subjects, apparent-motion-related activity in patches of V1 representing locations along the path of illusory stimulus motion using functional magnetic resonance imaging. Here we show that apparent motion caused a blood-oxygenation-level-dependent response along the V1 representations of the apparent-motion path, including regions that were not directly activated by the apparent-motion-inducing stimuli. This response was unaltered when participants had to perform an attention-demanding task that diverted their attention away from the stimulus. With a bistable motion quartet, we confirmed that the activity was related to the conscious perception of movement. Our data suggest that V1 is part of the network that represents the illusory path of apparent motion. The activation in V1 can be explained either by lateral interactions within V1 or by feedback mechanisms from higher visual areas, especially the motion-sensitive human MT/V5 complex

Contour extracting networks in early extrastriate cortex

Neurons in the visual cortex process a local region of visual space, but in order to adequately analyze natural images, neurons need to interact. The notion of an ?association field? proposes that neurons interact to extract extended contours. Here, we identify the site and properties of contour integration mechanisms. We used functional magnetic resonance imaging (fMRI) and population receptive field (pRF) analyses. We devised pRF mapping stimuli consisting of contours. We isolated the contribution of contour integration mechanisms to the pRF by manipulating the contour content. This stimulus manipulation led to systematic changes in pRF size. Whereas a bank of Gabor filters quantitatively explains pRF size changes in V1, only V2/V3 pRF sizes match the predictions of the association field. pRF size changes in later visual field maps, hV4, LO-1, and LO-2 do not follow either prediction and are probably driven by distinct classical receptive field properties or other extraclassical integration mechanisms. These pRF changes do not follow conventional fMRI signal strength measures. Therefore, analyses of pRF changes provide a novel computational neuroimaging approach to investigating neural interactions. We interpreted these results as evidence for neural interactions along co-oriented, cocircular receptive fields in the early extrastriate visual cortex (V2/V3), consistent with the notion of a contour association field

Interactions between motion and form processing in the human visual system

The predominant view of motion and form processing in the human visual system assumes that these two attributes are handled by separate and independent modules. Motion processing involves filtering by direction-selective sensors, followed by integration to solve the aperture problem. Form processing involves filtering by orientation-selective and size-selective receptive fields, followed by integration to encode object shape. It has long been known that motion signals can influence form processing in the well-known Gestalt principle of common fate; texture elements which share a common motion property are grouped into a single contour or texture region. However, recent research in psychophysics and neuroscience indicates that the influence of form signals on motion processing is more extensive than previously thought. First, the salience and apparent direction of moving lines depends on how the local orientation and direction of motion combine to match the receptive field properties of motion-selective neurons. Second, orientation signals generated by “motion-streaks” influence motion processing; motion sensitivity, apparent direction and adaptation are affected by simultaneously present orientation signals. Third, form signals generated by human body shape influence biological motion processing, as revealed by studies using point-light motion stimuli. Thus, form-motion integration seems to occur at several different levels of cortical processing, from V1 to STS