Person:

Kosslyn, Stephen

Spatial imagery may be useful in such tasks as interpreting graphs and solving geometry problems, and even in performing surgery. This study provides evidence that spatial imagery is not a single faculty; rather, visualizing spatial location and mentally transforming location rely on distinct neural networks. Using 3-T functional magnetic resonance imaging, we tested 16 participants (8 male, 8 female) in each of two spatial imagery tasks--one that required visualizing location and one that required mentally rotating stimuli. The same stimuli were used in the two tasks. The location-based task engendered more activation near the occipito-parietal sulcus, medial posterior cingulate, and precuneus, whereas the transformation task engendered more activation in superior portions of the parietal lobe and in the postcentral gyrus. These differences in activation provide evidence that there are at least two different types of spatial imagery.

Emotions have been shown to modulate low-level visual processing of simple stimuli. In this study, we investigate whether emotions only modulate processing of visual representations created from direct visual inputs or whether they also modulate representations that underlie visual mental images. Our results demonstrate that when participants visualize or look at the global shape of written words (low-spatial-frequency visual information), the prior brief presentation of fearful faces enhances processing, whereas when participants visualize or look at details of written words (high-spatial-frequency visual information), the prior brief presentation of fearful faces impairs processing. This study demonstrates that emotions have similar effects on low-level processing of visual percepts and of internal representations created on the basis of information stored in long-term memory.

The two studies reported in this article are an extension of the neuroimaging study by Ganis et al. (2003), which provided evidence that different types of lies arise from different cognitive processes. We examined the initial response times (IRTs) to questions answered both deceptively and truthfully. We considered four types of deceptive responses: a coherent set of rehearsed, memorized lies about a life experience; a coherent set of lies spontaneously created about a life experience; a set of isolated lies involving self-knowledge; and a set of isolated lies involving knowledge of another person. We assessed the difference between truthful and deceptive IRTs. Scores from cognitive tasks included in the MiniCog Rapid Assessment Battery (MRAB) were significant predictors of IRT differences. Each type of lie was predicted by a distinct set of MRAB scores. These results provide further evidence that deception is a multifaceted process and that different kinds of lies arise from the operation of different cognitive processes.

We distinguish between strong and weak cognitive neuropsychology, with the former attempting to provide direct insights into the nature of information processing and the latter having the more modest goal of providing constraints on such theories. We argue that strong cognitive neuropsychology, although possible, is unlikely to succeed and that researchers will fare better by combining behavioral, computational, and neural investigations. Arguments offered by Caramazza (1992) in defense of strong neuropsychology are analyzed, and examples are offered to illustrate the power of alternative points of view.

Stephen M. Kosslyn is Professor of Psychology at Harvard University and an Associate Psychologist in the Department of Neurology at the Massachusetts General Hospital. He received his B.A. in 1970 from UCLA and his Ph.D. from Stanford University in 1974, both in psychology, and taught at Johns Hopkins, Harvard, and Brandeis Universities before joining the Harvard Faculty as Professor of Psychology in 1983. His work focuses on the nature of visual mental imagery and high-level vision, as well as applications of psychological principles to visual display design. He has published over 125 papers on these topics, co-edited five books, and authored or co-authored five books. His books include Image and Mind (1980), Ghosts in the Mind's Machine (1983), Wet Mind: The New Cognitive Neuroscience (with 0. Koenig, 1992), Elements of Graph Design (1994), and Image and Brain: The Resolution of the Imagery Debate (1994). Dr. Kosslyn has received numerous honors, including the National Academy of Sciences Initiatives in Research Award, is currently on the editorial boards of many professional journals, and has served on several National Research Council committees to advise the government on new technologies.

Although it is largely accepted that visual-mental imagery and perception draw on many of the same neural structures, the existence and nature of neural processing in the primary visual cortex (or area V1) during visual imagery remains controversial. We tested two general hypotheses: The first was that V1 is activated only when images with many details are formed and used, and the second was that V1 is activated whenever images are formed, even if they are not necessarily used to perform a task. We used event-related functional magnetic resonance imaging (ER-fMRI) to detect and characterize the activity in the calcarine sulcus (which contains the primary visual cortex) during single instances of mental imagery. The results revealed reproducible transient activity in this area whenever participants generated or evaluated a mental image. This transient activity was strongly enhanced when participants evaluated characteristics of objects, whether or not details actually needed to be extracted from the image to perform the task. These results show that visual imagery processing commonly involves the earliest stages of the visual system.

A subset of visually sensitive neurons in the parietal lobe apparently can encode the locations of stimuli, whereas visually sensitive neurons in the inferotemporal cortex (area IT) cannot. This finding is puzzling because both sorts of neurons have large receptive fields, and yet location can be encoded in one case, but not in the other. The experiments reported here investigated the hypothesis that a crucial difference between the IT and parietal neurons is the spatial distribution of their response profiles. In particular, IT neurons typically respond maximally when stimuli are presented at the fovea, whereas parietal neurons do not. We found that a parallel-distributed-processing network could map a point in an array to a coordinate representation more easily when a greater proportion of its input units had response peaks off the center of the input array. Furthermore, this result did not depend on potentially implausible assumptions about the regularity of the overlap in receptive fields or the homogeneity of the response profiles of different units. Finally, the internal representations formed within the network had receptive fields resembling those found in area 7a of the parietal lobe.

Sixteen subjects closed their eyes and visualized uppercase letters of the alphabet at two sizes, as small as possible or as large as possible while remaining “visible.” Subjects evaluated a shape characteristic of each letter (e.g., whether it has any curved lines), and responded as quickly as possible. Cerebral blood flow was normalized to the same value for each subject, and relative blood flow was computed for a set of regions of interest. The mean response time for each subject in the task was regressed onto the blood flow values. Blood flow in area 17 was negatively correlated with response time (r = -0.65), as was blood flow in area 19 (r = -0.66), whereas blood flow in the inferior parietal lobe was positively correlated with response time (r = 0.54). The first two effects persisted even when variance due to the other correlations was removed. These findings suggest that individual differences in the activation of specific brain loci are directly related to performance of tasks that rely on processing in those loci.

Cerebral blood flow was measured using positron emission tomography (PET) in three experiments while subjects performed mental imagery or analogous perceptual tasks. In Experiment 1, the subjects either visualized letters in grids and decided whether an X mark would have fallen on each letter if it were actually in the grid, or they saw letters in grids and decided whether an X mark fell on each letter. A region identified as part of area 17 by the Talairach and Tournoux (1988) atlas, in addition to other areas involved in vision, was activated more in the mental imagery task than in the perception task. In Experiment 2, the identical stimuli were presented in imagery and baseline conditions, but subjects were asked to form images only in the imagery condition; the portion of area 17 that was more active in the imagery condition of Experiment 1 was also more activated in imagery than in the baseline condition, as was part of area 18. Subjects also were tested with degraded perceptual stimuli, which caused visual cortex to be activated to the same degree in imagery and perception. In both Experiments 1 and 2, however, imagery selectively activated the extreme anterior part of what was identified as area 17, which is inconsistent with the relatively small size of the imaged stimuli. These results, then, suggest that imagery may have activated another region just anterior to area 17. In Experiment 3, subjects were instructed to close their eyes and evaluate visual mental images of upper case letters that were formed at a small size or large size. The small mental images engendered more activation in the posterior portion of visual cortex, and the large mental images engendered more activation in anterior portions of visual cortex. This finding is strong evidence that imagery activates topographically mapped cortex. The activated regions were also consistent with their being localized in area 17. Finally, additional results were consistent with the existence of two types of imagery, one that rests on allocating attention to form a pattern and one that rests on activating stored visual memories.

This study investigated the relationship between 3 ability-based cognitive styles (verbal deductive, spatial imagery, and object imagery) and performance on geometry problems that provided different types of clues. The purpose was to determine whether students with a specific cognitive style outperformed other students, when the geometry problems provided clues compatible with their cognitive style. Students were identified as having a particular cognitive style when they scored equal to or above the median on the measure assessing this ability. A geometry test was developed in which each problem could be solved on the basis of verbal reasoning clues (matching verbal deductive cognitive style), mental rotation clues (matching spatial imagery cognitive style), or shape memory clues (matching object imagery cognitive style). Straightforward cognitive style–clue-compatibility relationships were not supported. Instead, for the geometry problems with either mental rotation or shape memory clues, students with a combination of both verbal and spatial cognitive styles tended to do the best. For the problems with verbal reasoning clues, students with either a verbal or a spatial cognitive style did well, with each cognitive style contributing separately to success. Thus, both spatial imagery and verbal deductive cognitive styles were important for solving geometry problems, whereas object imagery was not. For girls, a spatial imagery cognitive style was advantageous for geometry problem solving, regardless of type of clues provided.