Showing papers by "David J. Heeger published in 2002"

What does fMRI tell us about neuronal activity

Abstract: In recent years, cognitive neuroscientists have taken great advantage of functional magnetic resonance imaging (fMRI) as a non-invasive method of measuring neuronal activity in the human brain. But what exactly does fMRI tell us? We know that its signals arise from changes in local haemodynamics that, in turn, result from alterations in neuronal activity, but exactly how neuronal activity, haemodynamics and fMRI signals are related is unclear. It has been assumed that the fMRI signal is proportional to the local average neuronal activity, but many factors can influence the relationship between the two. A clearer understanding of how neuronal activity influences the fMRI signal is needed if we are correctly to interpret functional imaging data.

Retinotopy and functional subdivision of human areas MT and MST.

Abstract: We performed a series of functional magnetic resonance imaging experiments to divide the human MT+ complex into subregions that may be identified as homologs to a pair of macaque motion-responsive visual areas: the middle temporal area (MT) and the medial superior temporal area (MST). Using stimuli designed to tease apart differences in retinotopic organization and receptive field size, we established a double dissociation between two distinct MT+ subregions in 8 of the 10 hemispheres studied. The first subregion exhibited retinotopic organization but did not respond to peripheral ipsilateral stimulation, indicative of smaller receptive fields. Conversely, the second subregion within MT+ did not demonstrate retinotopic organization but did respond to peripheral stimuli in both the ipsilateral and contralateral visual hemifields, indicative of larger receptive fields. We tentatively identify these subregions as the human homologues of macaque MT and MST, respectively. Putative human MT and MST were typically located on the posterior/ventral and anterior/dorsal banks of a dorsal/posterior limb of the inferior temporal sulcus, similar to their relative positions in the macaque superior temporal sulcus.

A Synaptic Explanation of Suppression in Visual Cortex

Abstract: The responses of neurons in the primary visual cortex (V1) are suppressed by mask stimuli that do not elicit responses if presented alone. This suppression is widely believed to be mediated by intracortical inhibition. As an alternative, we propose that it can be explained by thalamocortical synaptic depression. This explanation correctly predicts that suppression is monocular, immune to cortical adaptation, and occurs for mask stimuli that elicit responses in the thalamus but not in the cortex. Depression also explains other phenomena previously ascribed to intracortical inhibition. It explains why responses saturate at high stimulus contrast, whereas selectivity for orientation and spatial frequency is invariant with contrast. It explains why transient responses to flashed stimuli are nonlinear, whereas spatial summation is primarily linear. These results suggest that the very first synapses into the cortex, and not the cortical network, may account for important response properties of V1 neurons.

Pattern-motion responses in human visual cortex

Abstract: Physiological models of visual motion processing posit that 'pattern-motion cells' represent the direction of moving objects independent of their particular spatial pattern. We performed fMRI experiments to identify neuronal activity in the human brain selective for pattern motion. A protocol using adaptation to moving 'plaid' stimuli allowed us to separate pattern-motion responses from other types of motion-related activity within the same brain structures, and revealed strong pattern-motion selectivity in human visual area MT+. Reducing the perceptual coherence of the plaids yielded a corresponding decrease in pattern-motion responsivity, providing evidence that percepts of coherent motion are closely linked to the activity of pattern-motion cells in human MT+.

Spatiotemporal mechanisms for detecting and identifying image features in human vision

Abstract: Our visual system constantly selects salient features in the environment, so that only those features are attended and targeted by further processing efforts to identify them. Models of feature detection hypothesize that salient features are localized based on contrast energy (local variance in intensity) in the visual stimulus. This hypothesis, however, has not been tested directly. We used psychophysical reverse correlation to study how humans detect and identify basic image features (bars and short line segments). Subjects detected a briefly flashed 'target bar' that was embedded in 'noise bars' that randomly changed in intensity over space and time. By studying how the intensity of the noise bars affected performance, we were able to dissociate two processing stages: an early 'detection' stage, whereby only locations of high-contrast energy in the image are selected, followed (after ∼100 ms) by an 'identification' stage, whereby image intensity at selected locations is used to determine the identity (whether bright or dark) of the target.

Motion Processing in Human Visual Cortex

Abstract: Acknowledgments. The authors thank David Heeger, Alex Huk, Nestor Matthews and Mark Nawrot for comments on sections of this chapter. David Bloom helped greatly with manuscript formatting and references. During preparation of this chapter RB and EG were supported by research grants from the National Institutes of Health (EY07760) and the National Science Foundation (BCS0121962) and by a Core Grant from the National Institutes of Health (EY01826) awarded to the Vanderbilt Vision Research Center.