Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Attention Neural Mechanisms


Science 25 April 2014:  Vol. 344  no. 6182  pp. 424-427

Neural Mechanisms of Object-Based Attention

Daniel Baldauf,  Robert Desimone

McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, 02139 MA, USA.


How we attend to objects and their features that cannot be separated by location is not understood. We presented two temporally and spatially overlapping streams of objects, faces versus houses, and used magnetoencephalography and functional,  magnetic resonance imaging to separate neuronal responses to attended and unattended objects. Attention to faces versus houses enhanced the sensory responses in the fusiform face area (FFA) and parahippocampal place area (PPA)respectively. The increases in sensory responses were accompanied by induced gamma synchrony between the inferior frontal junction, IFJ, and either FFA or PPA, depending on which object was attended. The IFJ appeared to be the driver of the synchrony, as gamma phases were advanced by 20 ms in IFJ compared to FFA or PPA. Thus, the IFJ may direct the flow of visual processing during object-based attention, at least in part through coupled oscillations with specialized areas such as FFA and PPA.

When covertly attending to a location in the periphery, visual processing is biased toward the attended location, and the sources of top-down signals include the frontal eye fields (FEF), and parietal cortex (PC).   FEF may modulate visual processing through a combination of firing rates and gamma frequency synchrony with visual cortex.   For nonspatial attention, the mechanisms of top-down attention are much less clear. When people attend to a feature, such as a particular color or to one of several objects at the same location, activity in the extrastriate areas representing properties of the attended object is enhanced. But where do the attentional biases come from, and how do they enhance object processing when the distractors are not spatially separate?

We combined magnetoencephalography (MEG), supplemented by functional magnetic resonance imaging (fMRI) and diffusion tensor imaging, to optimize both spatial and temporal resolution. In the MEG experiment, two spatially overlapping streams of objects (faces and houses) were tagged at different presentation frequencies (1.5 and 2.0 Hz). The stimuli went in and out of “phase coherence,” so that they were modulated in visibility over time but did not change in luminance or flash on and off. When subjects were cued to attend to one of the streams and to detect occasional targets within the cued stream, frequency analyses allowed identifying brain regions that followed the stimulus oscillations.

Using MEG data only, the strongest activity evoked by the face tag was in the right fusiform gyrus, whereas the activity evoked by the house tag was more medially in the inferior-temporal cortex (IT). These areas were roughly consistent with the locations of fusiform face area (FFA) and parahippocampal place area (PPA) determined previously in fMRI. To increase the accuracy of localization in each subject, we added high-resolution fMRI localizers for FFA and PPA, which were focused at the expected spots.

To identify other areas important for nonspatial attention, we contrasted the brain state when attending to one of the two superimposed object classes with a similarly demanding state that did not require attending to either object class. The attention-related fMRI localizers revealed consistent activation in the inferior frontal junction (IFJ) at the intersection of the inferior-frontal and precentral sulcus, with weaker and less-consistent signals in posterior-parietal and in inferior-temporal cortex. A control experiment confirmed that IFJ's activation was indeed related to nonspatial attention, rather than simply memory.

Each subject's individual fMRI localizers were then used as regions of interest (ROIs) to guide the analysis of the MEG signals.

The neural mechanism that enables attention to an object or feature seems intuitively more complex than spatial attention, which may only require a spatial-biasing signal that targets a relevant location. Yet the present study reveals some striking parallels in neural mechanisms: Prefrontal cortex seems to be a common source of top-down biasing signals,   with FEF supplying signals for spatial attention   and IFJ supplying signals for object or feature attention.   With spatial attention, cells in FEF and visual cortex begin to oscillate together in the gamma frequency range, with FEF the “driver” in these oscillations. Here, we find that IJF—although it has delayed sensory responses—is also the “driver” in coupled gamma oscillations with FFA/PPA. In primates, coherent gamma oscillations in FEF are phase-shifted by about 10 ms compared with oscillations in area V4, which has been argued to account for the axonal conductance time and synaptic delays between the two areas. With the phase shift, spikes of FEF cells presumably affect cells in V4 at a time of maximum depolarization, which increases their impact. Here, a phase shift of 25 ms may allow for longer transmission times from IFJ to FFA and PPA in humans. Thus, spikes originating from IFJ may arrive in FFA and PPA respectively, and vice versa, at a time of maximum depolarization in the receiving area, magnifying their impact. The directing of IFJ signals to the FFA versus PPA may not be inherently more complex than shifting FEF signals between different locations in the visual field.

IFJ may include areas that function as general executive modules. Also, IFJ is close to areas Ba45 and Ba46, homologs of which have been described in nonhuman primate recordings to encode information about object-categories in delayed match-to-sample tasks. Indeed, the “attentional template” that specifies the relevant location or object in spatial or feature attention is hardly distinguishable from working memory for these qualities, which is known to involve prefrontal cortex. Coupled interactions between prefrontal areas and visual areas could underlie many cognitive phenomena in vision, with shared neural mechanisms but variations in the site of origin and the site of termination.



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