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1. Cell-Type Specific Connectivity of Whisker-Related Sensory and Motor Cortical Input to Dorsal Striatum

   https://doi.org/10.1523/ENEURO.0503-23.2023  

   Sanabria, Branden D.; Baskar, Sindhuja S.; Yonk, Alex J.; Linares-Garcia, Iván; Abraira, Victoria E.; Lee, Christian R.; Margolis, David J. (December 2023, eneuro)

   The anterior dorsolateral striatum (DLS) is heavily innervated by convergent excitatory projections from the primary motor (M1) and sensory cortex (S1) and considered an important site of sensorimotor integration. M1 and S1 corticostriatal synapses have functional differences in their connection strength with striatal spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS and, as a result, exert distinct influences on sensory-guided behaviors. In the present study, we tested whether M1 and S1 inputs exhibit differences in the subcellular anatomical distribution of striatal neurons. We injected adeno-associated viral vectors encoding spaghetti monster fluorescent proteins (sm.FPs) into M1 and S1 in male and female mice and used confocal microscopy to generate 3D reconstructions of corticostriatal inputs to single identified SPNs and FSIs obtained through ex vivo patch clamp electrophysiology. We found that M1 and S1 dually innervate SPNs and FSIs; however, there is a consistent bias towards the M1 input in SPNs that is not found in FSIs. In addition, M1 and S1 inputs were distributed similarly across the proximal, medial, and distal regions of SPN and FSI dendrites. Notably, closely localized M1 and S1 clusters of inputs were more prevalent in SPNs than FSIs, suggesting that cortical inputs are integrated through cell-type specific mechanisms. Our results suggest that the stronger functional connectivity from M1 to SPNs compared to S1, as previously observed, is due to a higher quantity of synaptic inputs. Our results have implications for how sensorimotor integration is performed in the striatum through cell-specific differences in corticostriatal connections. 

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2. Developmentally regulated pathways for motor skill learning in songbirds

   https://doi.org/10.1002/cne.25276  

   Chung, Jin Hyung; Bottjer, Sarah W. (December 2021, Journal of Comparative Neurology)

   Abstract Vocal learning in songbirds is mediated by cortico‐basal ganglia circuits that govern diverse functions during different stages of development. We investigated developmental changes in axonal projections to and from motor cortical regions that underlie learned vocal behavior in juvenile zebra finches (Taeniopygia guttata). Neurons in LMAN‐core project to RA, a motor cortical region that drives vocal output; these RA‐projecting neurons send a transient collateral projection to AId, a region adjacent to RA, during early vocal development. Both RA and AId project to a region of dorsal thalamus (DLM), which forms a feedback pathway to cortico‐basal ganglia circuitry. These projections provide pathways conveying efference copy and a means by which information about vocal motor output could be reintegrated into cortico‐basal ganglia circuitry, potentially aiding in the refinement of juvenile vocalizations during learning. We used tract‐tracing techniques to label the projections of LMAN‐core to AId and of RA to DLM in juvenile songbirds. The volume and density of terminal label in the LMAN‐core→AId projection declined substantially during early stages of sensorimotor learning. In contrast, the RA→DLM projection showed no developmental change. The retraction of LMAN‐core→AId axon collaterals indicates a loss of efference copy to AId and suggests that projections that are present only during early stages of sensorimotor learning mediate unique, temporally restricted processes of goal‐directed learning. Conversely, the persistence of the RA→DLM projection may serve to convey motor information forward to the thalamus to facilitate song production during both learning and maintenance of vocalizations. 

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3. Neural systems underlying reward cue processing in early adolescence: The role of puberty and pubertal hormones

   https://doi.org/doi: 10.1016/j.psyneuen.2018.12.016.  

   Ladouceur CD, Kerestes R (April 2019, Psychoneuroendocrinology)

   Affective neuroscience research suggests that maturational changes in reward circuitry during adolescence present opportunities for new learning, but likely also contribute to increases in vulnerability for psychiatric disorders such as depression and substance abuse. Basic research in animal models and human neuroimaging has made progress in understanding the normal development of reward circuitry in adolescence, yet, few functional neuroimaging studies have examined puberty-related influences on the functioning of this circuitry. The goal of this study was to address this gap by examining the extent to which striatal activation and cortico-striatal functional connectivity to cues predicting upcoming rewards would be positively associated with pubertal status and levels of pubertal hormones (dehydroepiandrosterone, testosterone, estradiol). Participants included 79 adolescents (10-13 year olds; 47 girls) varying in pubertal status who performed a novel reward cue processing task during fMRI. Pubertal maturation was assessed using sex-specific standardized composite measures based on Tanner staging (self-report and clinical assessment) and scores from the Pubertal Development Scale. These composite measures were computed to index overall pubertal maturation as well as maturation of the adrenal and gonadal axes separately for boys and girls. Basal levels of circulating pubertal hormones were measured using immunoassays from three samples collected weekly upon awakening across a three-week period. Results indicated greater striatal activation and functional connectivity between nucleus accumbens (NAcc) and medial prefrontal cortex (mPFC) to reward cue (vs. no reward cue) on this task. Also, girls with higher levels of estradiol showed reduced activation in left and right caudate and greater NAcc-putamen connectivity. Girls with higher levels of testosterone showed greater NAcc connectivity with the anterior cingulate cortex and the insula. There were no significant associations in boys. Findings suggest that patterns of activation and connectivity in cortico-striatal regions are associated with reward cue processing, particularly in girls. Longitudinal follow-up neuroimaging studies are needed to fully characterize puberty-specific effects on the development of these neural regions and how such changes may contribute to pathways of risk or resilience in adolescence. 

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4. The Visual Cortex in Context

   https://doi.org/10.1146/annurev-vision-091517-034407  

   Froudarakis, Emmanouil; Fahey, Paul G.; Reimer, Jacob; Smirnakis, Stelios M.; Tehovnik, Edward J.; Tolias, Andreas S. (September 2019, Annual Review of Vision Science)

   null (Ed.)

   In this article, we review the anatomical inputs and outputs to the mouse primary visual cortex, area V1. Our survey of data from the Allen Institute Mouse Connectivity project indicates that mouse V1 is highly interconnected with both cortical and subcortical brain areas. This pattern of innervation allows for computations that depend on the state of the animal and on behavioral goals, which contrasts with simple feedforward, hierarchical models of visual processing. Thus, to have an accurate description of the function of V1 during mouse behavior, its involvement with the rest of the brain circuitry has to be considered. Finally, it remains an open question whether the primary visual cortex of higher mammals displays the same degree of sensorimotor integration in the early visual system. 

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5. Enhancing reinforcement learning models by including direct and indirect pathways improves performance on striatal dependent tasks

   https://doi.org/10.1371/journal.pcbi.1011385  

   Blackwell, Kim T.; Doya, Kenji (August 2023, PLOS Computational Biology)

   Cai, Ming Bo (Ed.)

   A major advance in understanding learning behavior stems from experiments showing that reward learning requires dopamine inputs to striatal neurons and arises from synaptic plasticity of cortico-striatal synapses. Numerous reinforcement learning models mimic this dopamine-dependent synaptic plasticity by using the reward prediction error, which resembles dopamine neuron firing, to learn the best action in response to a set of cues. Though these models can explain many facets of behavior, reproducing some types of goal-directed behavior, such as renewal and reversal, require additional model components. Here we present a reinforcement learning model, TD2Q, which better corresponds to the basal ganglia with two Q matrices, one representing direct pathway neurons (G) and another representing indirect pathway neurons (N). Unlike previous two-Q architectures, a novel and critical aspect of TD2Q is to update the G and N matrices utilizing the temporal difference reward prediction error. A best action is selected for N and G using a softmax with a reward-dependent adaptive exploration parameter, and then differences are resolved using a second selection step applied to the two action probabilities. The model is tested on a range of multi-step tasks including extinction, renewal, discrimination; switching reward probability learning; and sequence learning. Simulations show that TD2Q produces behaviors similar to rodents in choice and sequence learning tasks, and that use of the temporal difference reward prediction error is required to learn multi-step tasks. Blocking the update rule on the N matrix blocks discrimination learning, as observed experimentally. Performance in the sequence learning task is dramatically improved with two matrices. These results suggest that including additional aspects of basal ganglia physiology can improve the performance of reinforcement learning models, better reproduce animal behaviors, and provide insight as to the role of direct- and indirect-pathway striatal neurons. 

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