SUMMARY Inferior temporal (IT) object representations have been intensively studied in monkeys and humans, but representations of the same particular objects have never been compared between the species. Moreover, IT’s role in categorization is not well understood. Here, we presented monkeys and humans with the same images of real-world objects and measured the IT response pattern elicited by each image. In order to relate the representations between the species and to computational models, we compare response-pattern dissimilarity matrices. IT response patterns form category clusters, which match between man and monkey. The clusters correspond to animate and inanimate objects; within the animate objects, faces and bodies form subclusters. Within each category, IT distinguishes individual exemplars, and the within-category exemplar similarities also match between the species. Our findings suggest that primate IT across species may host a common code, which combines a categorical and a continuous representation of objects.

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Although early sensory cortex is organized along dimensions encoded by receptor organs, little is known about the organization of higher areas in which different modalities are integrated. We investigated multisensory integration in human superior temporal sulcus using recent advances in parallel imaging to perform functional magnetic resonance imaging (fMRI) at very high resolution. These studies suggest a functional architecture in which information from different modalities is brought into close proximity via a patchy distribution of inputs, followed by integration in the intervening cortex.

Real-time functional magnetic resonance imaging (rtfMRI) with neurofeedback allows investigation of human brain neuroplastic changes that arise as subjects learn to modulate neurophysiological function using real-time feedback regarding their own hemodynamic responses to stimuli. We investigated the feasibility of training healthy humans to self-regulate the hemodynamic activity of the amygdala, which plays major roles in emotional processing. Participants in the experimental group were provided with ongoing information about the blood oxygen level dependent (BOLD) activity in the left amygdala (LA) and were instructed to raise the BOLD rtfMRI signal by contemplating positive autobiographical memories. A control group was assigned the same task but was instead provided with sham feedback from the left horizontal segment of the intraparietal sulcus (HIPS) region. In the LA, we found a significant BOLD signal increase due to rtfMRI neurofeedback training in the experimental group versus the control group. This effect persisted during the Transfer run without neurofeedback. For the individual subjects in the experimental group the training effect on the LA BOLD activity correlated inversely with scores on the Difficulty Identifying Feelings subscale of the Toronto Alexithymia Scale. The whole brain data analysis revealed significant differences for Happy Memories versus Rest condition between the experimental and control groups. Functional connectivity analysis of the amygdala network revealed significant widespread correlations in a fronto-temporo-limbic network. Additionally, we identified six regions — right medial frontal polar cortex, bilateral dorsomedial prefrontal cortex, left anterior cingulate cortex, and bilateral superior frontal gyrus — where the functional connectivity with the LA increased significantly across the rtfMRI neurofeedback runs and the Transfer run. The findings demonstrate that healthy subjects can learn to regulate their amygdala activation using rtfMRI neurofeedback, suggesting possible applications of rtfMRI neurofeedback training in the treatment of patients with neuropsychiatric disorders.

Objective Patients with depression show blunted amygdala hemodynamic activity to positive stimuli, including autobiographical memories. The authors examined the therapeutic efficacy of real-time functional MRI neurofeedback (rtfMRI-nf) training aimed at increasing the amygdala’s he-modynamic response to positive memories in patients with depression. Method In a double-blind, placebo-controlled, randomized clinical trial, unmedicated adults with depression (N=36) were randomly assigned to receive two sessions of rtfMRI-nf either from the amygdala (N=19) or from a parietal control region not involved in emotional processing (N=17). Clinical scores and autobiographical memory performance were assessed at baseline and 1 week after the final rtfMRI-nf session. The primary outcome measure was change in score on the Montgomery-Åsberg Depression Rating Scale (MADRS), and the main analytic approach consisted of a linear mixed-model analysis. Results In participants in the experimental group, the hemo-dynamic response in the amygdala increased relative to their own baseline and to the control group. Twelve participants in the amygdala rtfMRI-nf group, compared with only two in the control group, had a >50% decrease in MADRS score. Six participants in the experimental group, compared with one in the control group, met conventional criteria for remission at study end, resulting in a number needed to treat of 4. In participants receiving amygdala rtfMRI-nf, the percent of positive specific memories recalled increased relative to baseline and to the control group. Conclusions rtfMRI-nf training to increase the amygdala hemo-dynamic response to positive memories significantly decreased depressive symptoms and increased the percent of specific memories recalled on an autobiographical memory test. These data support a role of the amygdala in recovery from depression.

BackgroundAmygdala hemodynamic responses to positive stimuli are attenuated in major depressive disorder (MDD), and normalize with remission. Real-time functional MRI neurofeedback (rtfMRI-nf) offers a non-invasive method to modulate this regional activity. We examined whether depressed participants can use rtfMRI-nf to enhance amygdala responses to positive autobiographical memories, and whether this ability alters symptom severity.MethodsUnmedicated MDD subjects were assigned to receive rtfMRI-nf from either left amygdala (LA; experimental group, n = 14) or the horizontal segment of the intraparietal sulcus (HIPS; control group, n = 7) and instructed to contemplate happy autobiographical memories (AMs) to raise the level of a bar representing the hemodynamic signal from the target region to a target level. This 40s Happy condition alternated with 40s blocks of rest and counting backwards. A final Transfer run without neurofeedback information was included.ResultsParticipants in the experimental group upregulated their amygdala responses during positive AM recall. Significant pre-post scan decreases in anxiety ratings and increases in happiness ratings were evident in the experimental versus control group. A whole brain analysis showed that during the transfer run, participants in the experimental group had increased activity compared to the control group in left superior temporal gyrus and temporal polar cortex, and right thalamus.ConclusionsUsing rtfMRI-nf from the left amygdala during recall of positive AMs, depressed subjects were able to self-regulate their amygdala response, resulting in improved mood. Results from this proof-of-concept study suggest that rtfMRI-nf training with positive AM recall holds potential as a novel therapeutic approach in the treatment of depression.

Relatively discrete experimental literatures have grown to support the insula's role in the domains of interoception, focal exteroceptive attention and cognitive control, and the experience of anxiety, even as theoretical accounts have asserted that the insula is a critical zone for integrating across these domains. Here we provide the first experimental demonstration that there exists a functional topography across the insula, with distinct regions in the same participants responding in a highly selective fashion for interoceptive, exteroceptive, and affective processing. Although each insular region is associated with areas of differential resting state functional connectivity relative to the other regions, overall their functional connectivity profiles are quite similar, thereby providing a map of how interoceptive, exteroceptive, and emotional awareness are integrated within the insular cortex.

Recent advances in MRI receiver and coil technologies have significantly improved image signalto-noise ratios (SNR) and thus temporal SNR (TSNR). These gains in SNR and TSNR have allowed the detection of fMRI signal changes at higher spatial resolution and therefore have increased the potential to localize small brain structures such as cortical layers and columns. The majority of current fMRI processing strategies employ multi-subject averaging and therefore require spatial smoothing and normalization, effectively negating these gains in spatial resolution higher than about 10mm 3 . Reliable detection of activation in single subjects at high resolution is becoming a more common desire among fMRI researchers who are interested in comparing individuals rather than populations. Since TSNR decreases with voxel volume, detection of activation at higher resolutions requires longer scan durations. The relationship between TSNR, voxel volume and detectability is highly nonlinear. In this study, the relationship between TSNR and the necessary fMRI scan duration required to obtain significant results at varying P values is determined both experimentally and theoretically. The results demonstrate that, with a TSNR of 50, detection of activation of above 2% requires at most 350 scan volumes (when steps are taken to remove the influence of physiological noise from the data). Importantly, these results also demonstrate that, for activation magnitude on the order of 1%, the scan duration required is more sensitive to the TSNR level than at 2%. This study showed that with voxel volumes of ~10mm 3 at 3T, and a corresponding TSNR of ~50, the required number of time points that guarantees detection of signal changes of 1% is about 860, but if TSNR increases by only 20%, the time for detection decreases by more than 30%. More than just being an exercise in numbers, these results imply that imaging of columnar resolution (effect size = 1% and assuming a TR of 1sec) at 3T will require either 10 minutes for a TSNR of 60 or 40 minutes for a TSNR of 30. The implication is that at these resolutions, TSNR is likely to be critical for determining success or failure of an experiment.