A mosaic adeno-associated virus vector as a versatile tool that exhibits high levels of transgene expression and neuron specificity in primate brain.

Recent emphasis has been placed on gene transduction mediated through recombinant adeno-associated virus (AAV) vector to manipulate activity of neurons and their circuitry in the primate brain. In the present study, we created a novel vector of which capsid was composed of capsid proteins derived from both of the AAV serotypes 1 and 2 (AAV1 and AAV2). Following the injection into the frontal cortex of macaque monkeys, this mosaic vector, termed AAV2.1 vector, was found to exhibit the excellence in transgene expression (for AAV1 vector) and neuron specificity (for AAV2 vector) simultaneously. To explore its applicability to chemogenetic manipulation and in vivo calcium imaging, the AAV2.1 vector expressing excitatory DREADDs or GCaMP was injected into the striatum or the visual cortex of macaque monkeys, respectively. Our results have defined that such vectors secure intense and stable expression of the target proteins and yield conspicuous modulation and imaging of neuronal activity.

Microscale visualization of cellular features in adult macaque visual cortex.

Expansion microscopy and light sheet imaging enable fine-scale resolution of intracellular features that comprise neural circuits. Most current techniques visualize sparsely distributed features across whole brains or densely distributed features within individual brain regions. Here, we visualize dense distributions of immunolabeled proteins across early visual cortical areas in adult macaque monkeys. This process may be combined with multiphoton or magnetic resonance imaging to produce multimodal atlases in large, gyrencephalic brains.

Processing of visual statistics of naturalistic videos in macaque visual areas V1 and V4.

Natural scenes are characterized by diverse image statistics, including various parameters of the luminance histogram, outputs of Gabor-like filters, and pairwise correlations between the filter outputs of different positions, orientations, and scales (Portilla-Simoncelli statistics). Some of these statistics capture the response properties of visual neurons. However, it remains unclear to what extent such statistics can explain neural responses to natural scenes and how neurons that are tuned to these statistics are distributed across the cortex. Using two-photon calcium imaging and an encoding-model approach, we addressed these issues in macaque visual areas V1 and V4. For each imaged neuron, we constructed an encoding model to mimic its responses to naturalistic videos. By extracting Portilla-Simoncelli statistics through outputs of both filters and filter correlations, and by computing an optimally weighted sum of these outputs, the model successfully reproduced responses in a subpopulation of neurons. We evaluated the selectivities of these neurons by quantifying the contributions of each statistic to visual responses. Neurons whose responses were mainly determined by Gabor-like filter outputs (low-level statistics) were abundant at most imaging sites in V1. In V4, the relative contribution of higher order statistics, such as cross-scale correlation, was increased. Preferred image statistics varied markedly across V4 sites, and the response similarity of two neurons at individual imaging sites gradually declined with increasing cortical distance. The results indicate that natural scene analysis progresses from V1 to V4, and neurons sharing preferred image statistics are locally clustered in V4.