Lesions of the inferior temporal (IT) cortex in humans can result in the clinical syndrome termed prosopagnosia, an inability to recognize familiar faces. Single-cell recordings from the IT cortex of monkeys have revealed the existence of neurons that are selectively activated by visual images of faces. More recently, brain imaging studies in both humans and monkeys have demonstrated face-selective regions, in which the fMRI signal evoked by faces is greater compared to that evoked by non-face objects. We have examined the relationship between fMRI-identified face-selective regions in IT cortex of monkeys relative to the selectivity of single neurons, located within vs. outside these regions. Face-preferring neurons were most concentrated in areas corresponding to the fMRI-identified face-selective regions, but were also found, in decreasing concentrations, outside of these regions. Moreover, neurons located within the fMRI-defined face regions showed greater selectivity to faces, compared to those located outside these regions. Thus, fMRI-identified face-selective regions correspond to a high proportion of face-responsive neurons that are highly selective for faces. These findings, accepted for publication, help to clarify the relationship between fMRI-defined regions and the neuronal processes within them. Although face-selective regions have been reported in temporal and prefrontal cortex of both humans and monkeys, the neural circuitry underlying face selectivity remains unclear. To clarify this, we studied the functional connectivity among these face-selective regions in monkeys in the resting, awake state. First, we mapped the face-selective regions by contrasting fMRI activation to images of monkey faces versus non-face objects. Two face-selective regions in the inferior temporal cortex were typically found in each hemisphere: the anterior and posterior face patches. Then, the animals underwent ten minutes of resting-state scans. Resting-state average time courses from the anterior and posterior face patches of each hemisphere were used as seeds for functional connectivity analyses. We found that a seed placed in the posterior face patch of one hemisphere correlated with activity in the posterior face patch of the other hemisphere and in the anterior patch, prefrontal face-selective areas and the amygdala of both hemispheres. A seed placed in the anterior face patch showed similar functional connectivity. These results demonstrate that there is a functional network among the face-selective regions, which can be detected by studying the intrinsic, spontaneous fMRI signal fluctuations. We have also begun to explore whether the distributed face processing network, revealed under the resting state in healthy individuals, differs in individuals with congenital prosopagnosia (CP), a lifelong deficit in face recognition that occurs despite normal intelligence and sensory experience. We first localized key regions of the face network (fusiform face area, occipital face area, superior temporal sulcus, and anterior temporal lobe) using a face localizer paradigm and used these regions as seeds for a whole brain functional connectivity analysis. This revealed in the controls a set of both posterior and anterior cortical areas whose activity was significantly correlated during rest, reflecting the presence of a face-selective resting state network. However, in CP individuals, the network was compromised, with correlated activity in more anterior regions markedly lower. The results provide further support for the notion that impaired connectivity within the face-processing network may underlie congenital prosopagnosia. We had previously shown that facial expressions modulate fMRI activity in face-responsive regions of the monkey's amygdala and visual cortex. Specifically, facial expressions with emotion yield greater activation than neutral faces, a phenomenon known as the valence effect. We next tested the idea that amygdala lesions would eliminate emotional modulatory feedback to the visual cortex, thus disrupting valence effects seen there. We performed selective amygdala lesions in monkeys and then used fMRI to compare the valence effects within the visual cortex in these animals to the effects in normal control animals. Four different facial expressions were tested: neutral, aggressive (open mouth threat), fearful (fear grimace) and appeasing (lipsmack). In controls, faces with emotional expressions relative to neutral faces produced enhanced responses in face-selective regions, as expected. In monkeys with amygdala lesions, although face-selective patches were found in IT cortex, their activity was not modulated by facial expressions. Our data thus demonstrate that the amygdala is the source of the valence modulatory effects seen in the visual cortex. These results, currently being prepared for publication, make a significant contribution to our understanding of the neural processing of faces with emotional content. Conventional neuroanatomical approaches to study brain circuitry require visualizing transported tracers in post-mortem tissue. We have therefore undertaken the development of a new in vivo tract tracer, by testing a compound that conjugates the conventional neuroanatomical tracer CTB with GdDOTA. We have published a paper showing that CTB-GdDOTA allows in vivo MR visualization of mono-synaptically connected brain circuits, that it is target-specific, bi-directional, very reproducible, and stable over a relatively long period of time. This agent opens the possibility for repetitive, chronic, and longitudinal anatomical studies in monkeys, such as those that target face-selective regions. We have also begun to study anatomical connectivity in monkeys by electrically stimulating a targeted structure and measuring the resultant neuronal activation in functionally connected brain areas with fMRI. To date, we have targeted the lateral aspect of the amygdala and observed discrete activations on the ventral bank of the superior temporal sulcus in the posterior inferior temporal cortex, consistent with prior findings with conventional tracers. Our data thus indicate the feasibility of using microstimuation in conjunction with fMRI to map brain connectivity. Although face-selective areas or face patches in the macaque superior temporal sulcus (STS) have now been reported by several groups, the representations supported by faces patches are not yet clear, especially with respect to facial dynamics and emotional expressions. We used multivariate pattern recognition on monkey fMRI data to examine coding of facial expressions in these classically-defined face patches. Further, we investigated a new set of face processing areas located in dorsal STS that were specifically responsive to dynamic faces. We found these latter areas coded information about threat, submissive and neutral facial expressions while, in contrast, the face patches had relatively little information about these expressions. Surprisingly, response patterns within these facial-movement sensitive areas coded expressions equally accurately whether they were dynamic or static, despite decreased overall responses to static faces. These results show that face patches represent only one component of the STS face processing circuit, and that emotional expressions are mostly processed outside the face patches, in areas sensitive to facial movement. This functional organization has implications for models proposing that separate networks process the invariant information of a face, such as identity or the changeable aspects of a face, such as facial expression. A paper reporting these findings has been submitted for publication.
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