Face-Specific Resting Functional Connectivity between the Fusiform Gyrus and Posterior Superior Temporal Sulcus

Faces activate specific brain regions in fMRI, including the fusiform gyrus (FG) and the posterior superior temporal sulcus (pSTS). The fact that the FG and pSTS are frequently co-activated suggests that they may interact synergistically in a distributed face processing network. Alternatively, the functions implemented by these regions may be encapsulated from each other. It has proven difficult to evaluate these two accounts during visual processing of face stimuli. However, if the FG and pSTS interact during face processing, the substrate for such interactions may be apparent in a correlation of the BOLD timeseries from these two regions during periods of rest when no faces are present. To examine face-specific resting correlations, we developed a new partial functional connectivity approach in which we removed variance from the FG that was shared with other category-selective and control regions. The remaining face-specific FG resting variance was then used to predict resting signals throughout the brain. In two experiments, we observed face-specific resting functional connectivity between FG and pSTS, and importantly, these correlations overlapped precisely with the face-specific pSTS region obtained from independent localizer runs. Additional region-of-interest and pattern analyses confirmed that the FG–pSTS resting correlations were face-specific. These findings support a model in which face processing is distributed among a finite number of connected, but nevertheless face-specialized regions. The discovery of category-specific interactions in the absence of visual input suggests that resting networks may provide a latent foundation for task processing

Babies and Brains: Habituation in Infant Cognition and Functional Neuroimaging

Many prominent studies of infant cognition over the past two decades have relied on the fact that infants habituate to repeated stimuli – i.e. that their looking times tend to decline upon repeated stimulus presentations. This phenomenon had been exploited to reveal a great deal about the minds of preverbal infants. Many prominent studies of the neural bases of adult cognition over the past decade have relied on the fact that brain regions habituate to repeated stimuli – i.e. that the hemodynamic responses observed in fMRI tend to decline upon repeated stimulus presentations. This phenomenon has been exploited to reveal a great deal about the neural mechanisms of perception and cognition. Similarities in the mechanics of these two forms of habituation suggest that it may be useful to relate them to each other. Here we outline this analogy, explore its nuances, and highlight some ways in which the study of habituation in functional neuroimaging could yield novel insights into the nature of habituation in infant cognition – and vice versa

Neurocognitive therapeutics: from concept to application in the treatment of negative attention bias

There is growing interest in the use of neuroimaging for the direct treatment of mental illness. Here, we present a new framework for such treatment, neurocognitive therapeutics. What distinguishes neurocognitive therapeutics from prior approaches is the use of precise brain-decoding techniques within a real-time feedback system, in order to adapt treatment online and tailor feedback to individuals’ needs. We report an initial feasibility study that uses this framework to alter negative attention bias in a small number of patients experiencing significant mood symptoms. The results are consistent with the promise of neurocognitive therapeutics to improve mood symptoms and alter brain networks mediating attentional control. Future work should focus on optimizing the approach, validating its effectiveness, and expanding the scope of targeted disorders

Attention Stabilizes Representations in the Human Hippocampus

Attention and memory are intricately linked, but how attention modulates brain areas that subserve memory, such as the hippocampus, is unknown. We hypothesized that attention may stabilize patterns of activity in human hippocampus, resulting in distinct but reliable activity patterns for different attentional states. To test this prediction, we utilized high-resolution functional magnetic resonance imaging and a novel "art gallery" task. On each trial, participants viewed a room containing a painting, and searched a stream of rooms for a painting from the same artist (art state) or a room with the same layout (room state). Bottom-up stimulation was the same in both tasks, enabling the isolation of neural effects related to top-down attention. Multivariate analyses revealed greater pattern similarity in all hippocampal subfields for trials from the same, compared with different, attentional state. This stability was greater for the room than art state, was unrelated to univariate activity, and, in CA2/CA3/DG, was correlated with behavior. Attention therefore induces representational stability in the human hippocampus, resulting in distinct activity patterns for different attentional states. Modulation of hippocampal representational stability highlights the far-reaching influence of attention outside of sensory systems

Flexible weighting of diverse inputs makes hippocampal function malleable

Classic theories of hippocampal function have emphasized its role as a dedicated memory system, but recent research has shown that it contributes broadly to many aspects of cognition, including attention and perception. We propose that the reason the hippocampus plays such a broad role in cognition is that its function is particularly malleable. We argue that this malleability arises because the hippocampus receives diverse anatomical inputs and these inputs are flexibly weighted based on behavioral goals. We discuss examples of how hippocampal representations can be flexibly weighted, focusing on hippocampal modulation by attention. Finally, we suggest some general neural mechanisms and core hippocampal computations that may enable the hippocampus to support diverse cognitive functions, including attention, perception, and memory. Together, this work suggests that great progress can and has been made in understanding the hippocampus by considering how the domain-general computations it performs allow it to dynamically contribute to many different behaviors