Shaw, L. H. | bioRxiv Science

bioRxiv2025

Projection-Specific Intersectional Optogenetics for Precise Excitation and Inhibition in the Marmoset Brain

The primate cerebral cortex relies on long-range connections to integrate information across spatially distributed and functionally specialized areas, yet tools for selectively modulating these pathways remain limited. Here, we present an optimized intersectional viral and optogenetic strategy for precisely exciting and inhibiting projection-specific neurons in the common marmoset. Building on a mouse-to-marmoset pipeline, we first validated that optogenetic activation of inhibitory neurons (via AAV9-Dlx-ChR2) enables robust local cortical inhibition. We then combined retrograde delivery of Cre-recombinase (AAVretro-Cre) with locally injected Cre-dependent vectors encoding excitatory or inhibitory opsins (AAV8-FLEx-ChR2 or Jaws) to achieve directionally selective expression in callosal and frontoparietal pathways. Dual-opsin co-expression enabled precise stimulation or suppression of projection neurons in vivo with minimal off-target labeling. These results establish a scalable framework for projection-specific optogenetic interrogation of distributed circuits in primates, expanding the experimental toolkit for causal studies of higher-order brain function with enhanced anatomical precision and functional specificity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/660378v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1b88c22org.highwire.dtl.DTLVardef@f831fdorg.highwire.dtl.DTLVardef@9a1403org.highwire.dtl.DTLVardef@197d351_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2022

Fast prediction in marmoset reach-to-grasp movements for dynamic prey

Primates have evolved sophisticated visually guided reaching behaviors for interacting with dynamic objects, such as insects during foraging(P. S. Archambault, Ferrari-Toniolo, & Battaglia-Mayer, 2011; Bicca-Marques, 1999; Ngo et al., 2022; Smith & Smith, 2013; Sustaita et al., 2013). Reaching control in dynamic natural conditions requires active prediction of the targets future position to compensate for visuo-motor processing delays and enhance online movement adjustments(Catania, 2009; Desmurget & Grafton, 2000; Fujioka, Aihara, Sumiya, Aihara, & Hiryu, 2016; Merchant & Georgopoulos, 2006; Mischiati et al., 2015; R. Shadmehr, Smith, & Krakauer, 2010; Wolpert & Kawato, 1998). Past reaching research in non-human primates mainly focused on seated subjects engaged in repeated ballistic arm movements to either stationary targets, or targets that instantaneously change position during the movement(Philippe S. Archambault, Caminiti, & Battaglia-Mayer, 2009; Battaglia-Mayer et al., 2013; Dickey, Amit, & Hatsopoulos, 2013; Georgopoulos, Kalaska, Caminiti, & Massey, 1983; Georgopoulos, Kalaska, & Massey, 1981). However, those approaches impose task constraints that limit the natural dynamics of reaching. A recent field study in marmoset monkeys highlights predictive aspects of visually-guided reaching during insect prey capture among wild marmoset monkeys(Ngo et al., 2022). To examine the complementary dynamics of similar natural behavior within a laboratory context we developed an ecologically motivated unrestrained reach-to-grasp task involving live crickets. We used multiple high-speed video cameras to capture the movements of marmosets and crickets stereoscopically and applied machine vision algorithms for marker-free object and hand tracking. Contrary to estimates under traditional constrained reaching paradigms, we find that reaching for dynamic targets can operate at incredibly short visuo-motor delays around 80 milliseconds, rivaling the speeds that are typical of the oculomotor systems during closed-loop visual pursuit(Cloherty, Yates, Graf, DeAngelis, & Mitchell, 2020). Multivariate linear regression modeling of the kinematic relationships between the hand and cricket velocity revealed that predictions of the expected future location can compensate for visuo-motor delays during fast reaching. These results suggest a critical role of visual prediction facilitating online movement adjustments for dynamic prey.

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