In contrast to visual object processing, relatively little is known about how the human brain processes everyday real-world sounds, transforming highly complex acoustic signals into representations of meaningful events or auditory objects. We recently reported a fourfold cortical dissociation for representing action (nonvocalization) sounds correctly categorized as having been produced by human, animal, mechanical, or environmental sources. However, it was unclear how consistent those network representations were across individuals, given potential differences between each participant's degree of familiarity with the studied sounds. Moreover, it was unclear what, if any, auditory perceptual attributes might further distinguish the four conceptual sound-source categories, potentially revealing what might drive the cortical network organization for representing acoustic knowledge. Here, we used functional magnetic resonance imaging to test participants before and after extensive listening experience with action sounds, and tested for cortices that might be sensitive to each of three different high-level perceptual attributes relating to how a listener associates or interacts with the sound source. These included the sound's perceived concreteness, effectuality (ability to be affected by the listener), and spatial scale. Despite some variation of networks for environmental sounds, our results verified the stability of a fourfold dissociation of category-specific networks for real-world action sounds both before and after familiarity training. Additionally, we identified cortical regions parametrically modulated by each of the three high-level perceptual sound attributes. We propose that these attributes contribute to the network-level encoding of category-specific acoustic knowledge representations.

Previously, we and others have shown that attention can enhance visual processing in a spatially specific manner that is retinotopically mapped in the occipital cortex. However, it is difficult to appreciate the functional significance of the spatial pattern of cortical activation just by examining the brain maps. In this study, we visualize the neural representation of the “spotlight” of attention using a back-projection of attention-related brain activation onto a diagram of the visual field. In the two main experiments, we examine the topography of attentional activation in the occipital and parietal cortices. In retinotopic areas, attentional enhancement is strongest at the locations of the attended target, but also spreads to nearby locations and even weakly to restricted locations in the opposite visual field. The dispersion of attentional effects around an attended site increases with the eccentricity of the target in a manner that roughly corresponds to a constant area of spread within the cortex. When averaged across multiple observers, these patterns appear consistent with a gradient model of spatial attention. However, individual observers exhibit complex variations that are unique but reproducible. Overall, these results suggest that the topography of visual attention for each individual is composed of a common theme plus a personal variation that may reflect their own unique “attentional style.”

Our ability to manipulate and understand the use of a wide range of tools is a feature that sets humans apart from other animals. In right-handers, we previously reported that hearing hand-manipulated tool sounds preferentially activates a left hemisphere network of motor-related brain regions hypothesized to be related to handedness. Using functional magnetic resonance imaging, we compared cortical activation in strongly right-handed versus left-handed listeners categorizing tool sounds relative to animal vocalizations. Here we show that tool sounds preferentially evoke activity predominantly in the hemisphere “opposite” the dominant hand, in specific high-level motor-related and multisensory cortical regions, as determined by a separate task involving pantomiming tool-use gestures. This organization presumably reflects the idea that we typically learn the “meaning” of tool sounds in the context of using them with our dominant hand, such that the networks underlying motor imagery or action schemas may be recruited to facilitate recognition.

We present a new method for generating two-dimensionnl maps of the cerebral cortex. Our computerized, two-stage flattening method takes as its input any well-defined representation of a surface within the three-dimensional cortex. The first stage rapidly converts this surface to a topologically correct two-dimensional map. without regard for the amount of distortion introduced. The second stage reduces distortions using a multiresolution strategy that makes gross shape changes on a coarsely sampled map and further shape refinements on progressively finer resolution maps. We demonstrate the utility of this approach by creating flat maps of the entire cerebral cortex in the macaque monkey and by displaying various types of experimental data on such maps. We also introduce a surface-based coordinate system that has advantages over conventional stereotaxic coordinates and is relevant to studies of cortical organization in humans as well as non-human primates. Together, these methods provide an improved basis for quantitative studies of individual variability in cortical organization.