Extensive sampling of neural activity during rich cognitive phenomena is critical for robust understanding of brain function. We present the Natural Scenes Dataset (NSD), in which high-resolution fMRI responses to tens of thousands of richly annotated natural scenes are measured while participants perform a continuous recognition task. To optimize data quality, we develop and apply novel estimation and denoising techniques. Simple visual inspections of the NSD data reveal clear representational transformations along the ventral visual pathway. Further exemplifying the inferential power of the dataset, we use NSD to build and train deep neural network models that predict brain activity more accurately than state-of-the-art models from computer vision. NSD also includes substantial resting-state and diffusion data, enabling network neuroscience perspectives to constrain and enhance models of perception and memory. Given its unprecedented scale, quality, and breadth, NSD opens new avenues of inquiry in cognitive and computational neuroscience..

Stimulation of the tragus activates the cerebral afferents of the vagal pathway and combined with our review of the literature suggest that taVNS is a promising form of VNS. Future taVNS/fMRI studies should systematically explore various parameters and alternative stimulation targets aimed to optimize this novel form of neuromodulation.

Vulnerability to drug related cues is one of the leading causes for continued use and relapse among substance dependent individuals. Using drugs in the face of cues may be associated with dysfunction in at least two frontal-striatal neural circuits: (1) elevated activity in medial and ventral areas that govern limbic arousal (including the medial prefrontal cortex (MPFC) and ventral striatum) or (2) depressed activity in dorsal and lateral areas that govern cognitive control (including the dorsolateral prefrontal cortex (DLPFC) and dorsal striatum). Transcranial magnetic stimulation (TMS) is emerging as a promising new tool for the attenuation of craving among multiple substance dependent populations. To date however, nearly all repetitive TMS studies in addiction have focused on amplifying activity in frontal-striatal circuits that govern cognitive control. This manuscript reviews recent work using TMS as a tool to decrease craving for multiple substances and provides a theoretical model for how clinical researchers might approach target and frequency selection for TMS of addiction. To buttress this model, preliminary data from a single-blind, sham-controlled, crossover study of 11 cocaine-dependent individuals is also presented. These results suggest that attenuating MPFC activity through theta burst stimulation decreases activity in the striatum and anterior insula. It is also more likely to attenuate craving than sham TMS. Hence, while many TMS studies are focused on applying LTP-like stimulation to the DLPFC, the MPFC might be a new, efficacious, and treatable target for craving in cocaine dependent individuals.

Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impact. Here we introduce a denoising technique that selectively suppresses the thermal noise contribution to the fMRI experiment. Using 7-Tesla, high-resolution human brain data, we demonstrate improvements in key metrics of functional mapping (temporal-SNR, the detection and reproducibility of stimulus-induced signal changes, and accuracy of functional maps) while leaving the amplitude of the stimulus-induced signal changes, spatial precision, and functional point-spread-function unaltered. We demonstrate that the method enables the acquisition of ultrahigh resolution (0.5 mm isotropic) functional maps but is also equally beneficial for a large variety of fMRI applications, including supra-millimeter resolution 3- and 7-Tesla data obtained over different cortical regions with different stimulation/task paradigms and acquisition strategies.