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Vasculature architecture of the brain can provide revealing information about mental and neurological function and disease. Fluorescence imaging in the second near-infrared (NIR-II) regime with less light scattering is a more promising method for detecting cortical vessels than traditional visible and NIR-I modes. : Clinically approved dye indocyanine green (ICG) was used for NIR-II fluorescence imaging. Here, for the first time, we developed two NIR-II fluorescence microscopy systems for brain vasculature imaging in macaque monkeys. The first is a wide-field microscope with high temporal resolution for measuring blood flow velocity and cardiac impulse period, while the second is a high spatial resolution confocal microscope producing three-dimensional maps of the cortical microvascular network. Both were designed with flexibility to image various cortical locations on the head. : Here, ICG was proved to have high brightness in NIR-II region and an 8-fold QY increase in serum than in water. We achieved cerebrovascular functional imaging of monkey with high temporal resolution (25 frames/second) with wide-field microscope. The blood flow velocity of capillaries can be precisely calculated and the cardiac impulse period can be monitored as well. structural imaging of cerebrovasculature was accomplished with both high spatial lateral resolution (~8 µm) and high signal to background ratio (SBR). Vivid 3D reconstructed NIR-II fluorescence confocal microscopic images up to depth of 470 μm were also realized. : This work comprises an important advance towards studies of neurovascular coupling, stroke, and other diseases relevant to neurovascular health in humans.

Ultra‐high Field (≥7T) functional magnetic resonance imaging (UHF‐fMRI) provides opportunities to resolve fine‐scale features of functional architecture such as cerebral cortical columns and layers, in vivo. While the nominal resolution of modern fMRI acquisitions may appear to be sufficient to resolve these features, several common data preprocessing steps can introduce unwanted spatial blurring, especially those that require interpolation of the data. These resolution losses can impede the detection of the fine‐scale features of interest. To examine quantitatively and systematically the sources of spatial resolution losses occurring during preprocessing, we used synthetic fMRI data and real fMRI data from the human visual cortex—the spatially interdigitated human V2 “thin” and “thick” stripes. The pattern of these cortical columns lies along the cortical surface and thus can be best appreciated using surface‐based fMRI analysis. We used this as a testbed for evaluating strategies that can reduce spatial blurring of fMRI data. Our results show that resolution losses can be mitigated at multiple points in preprocessing pathway. We show that unwanted blur is introduced at each step of volume transformation and surface projection, and can be ameliorated by replacing multi‐step transformations with equivalent single‐step transformations. Surprisingly, the simple approaches of volume upsampling and of cortical mesh refinement also helped to reduce resolution losses caused by interpolation. Volume upsampling also serves to improve motion estimation accuracy, which helps to reduce blur. Moreover, we demonstrate that the level of spatial blurring is nonuniform over the brain—knowledge which is critical for interpreting data in high‐resolution fMRI studies. Importantly, our study provides recommendations for reducing unwanted blurring during preprocessing as well as methods that enable quantitative comparisons between preprocessing strategies. These findings highlight several underappreciated sources of a spatial blur. Individually, the factors that contribute to spatial blur may appear to be minor, but in combination, the cumulative effects can hinder the interpretation of fine‐scale fMRI and the detectability of these fine‐scale features of functional architecture. In order to evaluate the strategies to reduce spatial resolution losses during fMRI data preprocessing for high resolution surface‐based columnar mapping, we quantified inadvertent blur using both synthetic fMRI data and real fMRI data from human visual cortex, the spatially interdigitated V2 “thin” and “thick” stripes. Results surprisingly show that the simple method of volume upsampling can effectively preserve spatial resolution, and we also highlight less well‐known sources of spatial nonuniform blur that are present during acquisition. These findings uncover several underappreciated sources of the spatial blur, which can hinder the interpretation of submillimeter fMRI and the detectability of these fine‐scale features of functional architecture.

Understanding brain networks is important for many fields, including neuroscience, psychology, medicine, and artificial intelligence. To address this fundamental need, there are multiple ongoing connectome projects in the United States, Europe, and Asia producing brain connection maps with resolutions at macro- and microscales. However, still lacking is a mesoscale connectome. This viewpoint (1) explains the need for a mesoscale connectome in the primate brain (the columnar connectome), (2) presents a new method for acquiring such data rapidly on a large scale, and (3) proposes how one might use such data to achieve a mathematics of brain function.

Mammals rely heavily on their auditory system to perceive environmental threats, socially communicate, and care for the young. As an extension of the multiple sensory system including the auditory system, the amygdala evaluates the emotional salience of acoustic stimuli, and mediates its impact on sensory, cognitive, and physiological aspects of emotional processing via the lateral amygdala (LA), basal amygdala (BA), and central amygdala (CeA) nuclei of the amygdala in acoustic domain. However, the functional connections of LA, BA, and CeA with the auditory cortex (AC) and the prefrontal cortex (PFC) remain unclear, particularly at the mesoscale level. Here we employed a novel method called INS-fMRI (Infrared Neural Stimulation combined with high-resolution functional magnetic resonance imaging) in Macaque monkeys, this method permits stimulation of multiple sites within single animals in vivo, so that the relative organization of auditory networks can be studied. We found that: (1) Focal INS stimulation of the amygdala elicited robust and reliable responses in both the AC and the PFC; (2) Amygdala stimulation mainly activated ipsilateral AC and PFC; (3) The stimulation of the amygdala mainly activated the secondary AC, and the dorsolateral PFC; (4) The connection between the amygdala and the cortex is mainly mediated by neurons in LA and BA connection area. Our study further revealed the functional connectivity among the amygdala subnucleus, the auditory cortex and the prefrontal cortex, and will shed light on the research for processing biologically meaningful complex sounds.

Cutting edge advances in electrical visual cortical prosthetics have evoked perception of shapes, motion, and letters in the blind. Here, we present an alternative optical approach using pulsed infrared neural stimulation. To interface with dense arrays of cortical columns with submillimeter spatial precision, both linear array and 100-fiber bundle array optical fiber interfaces were devised. We deliver infrared stimulation through these arrays in anesthetized cat visual cortex and monitor effects by optical imaging in contralateral visual cortex. Infrared neural stimulation modulation of response to ongoing visual oriented gratings produce enhanced responses in orientation-matched domains and suppressed responses in non-matched domains, consistent with a known higher order integration mediated by callosal inputs. Controls include dynamically applied speeds, directions and patterns of multipoint stimulation. This provides groundwork for a distinct type of prosthetic targeted to maps of visual cortical columns. Visual perception is achieved by a chain of specific neural activations in the brain. Here, the authors show that infrared neural stimulation of selected early nodes in the chain leads to predictable shape response in higher areas, providing groundwork for targeted approach to vision restoration.

An important aspect of visual object recognition is the ability to perceive object shape. Two basic components of complex shapes are straight and curved contours. A large body of evidence suggests a modular hierarchy for shape representation progressing from simple and complex orientation in early areas V1 and V2, to increasingly complex stages of curvature representation in V4, TEO, and TE. Here, we reinforce and extend the concept of modular representation. Using intrinsic signal optical imaging in Macaque area V4, we find sub-millimeter sized modules for curvature representation that are organized from low to high curvatures as well as domains with complex curvature preference. We propose a possible ‘curvature hypercolumn’ within V4. In combination with previous studies, we suggest that the key emergent functions at each stage of cortical processing are represented in systematic, modular maps.

In primates, visual perception is mediated by brain circuits composed of submillimeter nodes linked together in specific networks that process different types of information, such as eye specificity and contour orientation. We hypothesized that optogenetic stimulation targeted to cortical nodes could selectively activate such cortical networks. We used viral transfection methods to confer light sensitivity to neurons in monkey primary visual cortex. Using intrinsic signal optical imaging and single-unit electrophysiology to assess effects of targeted optogenetic stimulation, we found that (i) optogenetic stimulation of single ocular dominance columns (eye-specific nodes) revealed preferential activation of nearby same-eye columns but not opposite-eye columns, and (ii) optogenetic stimulation of single orientation domains increased visual response of matching orientation domains and relatively suppressed nonmatching orientation selectivity. These findings demonstrate that optical stimulation of single nodes leads to modulation of functionally specific cortical networks related to underlying neural architecture.

We have previously shown that INS-fMRI is a rapid method for mapping mesoscale brain networks in the macaque monkey brain. Focal stimulation of single cortical sites led to the activation of connected cortical locations, resulting in a global connectivity map. Here, we have extended this method for mapping brainwide networks following stimulation of single subcortical sites. As a testbed, we focused on the basal nucleus of the amygdala in the macaque monkey. We describe methods to target basal nucleus locations with submillimeter precision, pulse train stimulation methods, and statistical tests for assessing non-random nature of activations. Using these methods, we report that stimulation of precisely targeted loci in the basal nucleus produced sparse and specific activations in the brain. Activations were observed in the insular and sensory association cortices as well as activations in the cingulate cortex, consistent with known anatomical connections. What is new here is that the activations were focal and, in some cases, exhibited shifting topography with millimeter shifts in stimulation site. The precision of the method enables networks mapped from different nearby sites in the basal nucleus to be distinguished. While further investigation is needed to improve the sensitivity of this method, our analyses do support the reproducibility and non-random nature of some of the activations. We suggest that INS-fMRI is a promising method for mapping large-scale cortical and subcortical networks at high spatial resolution.

Spatial frequency (SF) is an important attribute in the visual scene and is a defining feature of visual processing channels. However, there remain many unsolved questions about how extrastriate areas in primate visual cortex code this fundamental information. Here, using intrinsic signal optical imaging in visual areas of V2 and V4 of macaque monkeys, we quantify the relationship between SF maps and (1) visual topography and (2) color and orientation maps. We find that in orientation regions, low to high SF is mapped orthogonally to orientation; in color regions, which are reported to contain orthogonal axes of color and lightness, low SFs tend to be represented more frequently than high SFs. This supports a population-based SF fluctuation related to the ‘color/orientation’ organizations. We propose a generalized hypercolumn model across cortical areas, comprised of two orthogonal parameters with additional parameters.