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A challenging goal in neuroscience is to be able to read out, or decode, mental content from brain activity. Recent functional magnetic resonance imaging (fMRI) studies have decoded orientation, position and object category from activity in visual cortex. However, these studies typically used relatively simple stimuli (for example, gratings) or images drawn(More)
Recent studies have used fMRI signals from early visual areas to reconstruct simple geometric patterns. Here, we demonstrate a new Bayesian decoder that uses fMRI signals from early and anterior visual areas to reconstruct complex natural images. Our decoder combines three elements: a structural encoding model that characterizes responses in early visual(More)
In the present study, we investigated how directional tuning of putative pyramidal cells is sharpened by inhibition from neighboring interneurons. First, different functional and electrophysiological criteria were used to identify putative pyramidal and interneuronal subtypes in a large database of motor cortical cells recorded during performance of the(More)
Quantitative modeling of human brain activity can provide crucial insights about cortical representations [1, 2] and can form the basis for brain decoding devices [3-5]. Recent functional magnetic resonance imaging (fMRI) studies have modeled brain activity elicited by static visual patterns and have reconstructed these patterns from brain activity [6-8].(More)
During natural vision, humans categorize the scenes they encounter: an office, the beach, and so on. These categories are informed by knowledge of the way that objects co-occur in natural scenes. How does the human brain aggregate information about objects to represent scene categories? To explore this issue, we used statistical learning methods to learn(More)
Directional tuning is a basic functional property of cell activity in the motor cortex. Previous work has indicated that cells with similar preferred directions are organized in columns perpendicular to the cortical surface. Here we show that these columns are organized in an orderly fashion in the tangential dimension on the cortical surface. Based on a(More)
The representations of animate and inanimate objects appear to be anatomically and functionally dissociated in the primate brain. How much of the variation in object-category tuning across cortical locations can be explained in terms of the animate/inanimate distinction? How is the distinction between animate and inanimate reflected in the arrangement of(More)
Over the past decade fMRI researchers have developed increasingly sensitive techniques for analyzing the information represented in BOLD activity. The most popular of these techniques is linear classification, a simple technique for decoding information about experimental stimuli or tasks from patterns of activity across an array of voxels. A more recent(More)
Functional MRI (fMRI) has become the most common method for investigating the human brain. However, fMRI data present some complications for statistical analysis and modeling. One recently developed approach to these data focuses on estimation of computational encoding models that describe how stimuli are transformed into brain activity measured in(More)
We used statistical methods for spherical density estimation to evaluate the distribution of preferred directions of motor cortical cells recorded from monkeys making reaching movements in 3D space. We found that this distribution, although broad enough to represent the entire 3D continuum of reaching directions, exhibited an enrichment for reaching forward(More)