Striatal activity reflects cortical activity patterns, bioRxiv, 2019-07-16

The dorsal striatum is organized into domains that drive characteristic behaviors1–7, and receive inputs from different parts of the cortex8,9 which modulate similar behaviors10–12. Striatal responses to cortical inputs, however, can be affected by changes in connection strength13–15, local striatal circuitry16,17, and thalamic inputs18,19. Therefore, it is unclear whether the pattern of activity across striatal domains mirrors that across the cortex20–23 or differs from it24–28. Here we use simultaneous large-scale recordings in the cortex and the striatum to show that striatal activity can be accurately predicted by spatiotemporal activity patterns in the cortex. The relationship between activity in the cortex and the striatum was spatially consistent with corticostriatal anatomy, and temporally consistent with a feedforward drive. Each striatal domain exhibited specific sensorimotor responses that predictably followed activity in the associated cortical regions, and the corticostriatal relationship remained unvaried during passive states or performance of a task probing visually guided behavior. However, the task’s visual stimuli and corresponding behavioral responses evoked relatively more activity in the striatum than in associated cortical regions. This increased striatal activity involved an additive offset in firing rate, which was independent of task engagement but only present in animals that had learned the task. Thus, striatal activity largely reflects patterns of cortical activity, deviating from them in a simple additive fashion for learned stimuli or actions.

biorxiv neuroscience 100-200-users 2019

Reconciling Dimensional and Categorical Models of Autism Heterogeneity a Brain Connectomics & Behavioral Study, bioRxiv, 2019-07-04

AbstractBackgroundHeterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide ASD individuals into non-overlapping (categorical) subgroups. However, continuous inter-individual variation in ASD suggests the need for a dimensional approach.MethodsA Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of ASD individuals into multiple abnormal RSFC patterns, i.e., categorical subtypes henceforth referred to as “factors”. Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 ASD individuals (age 5.2-57 years) from two multisite repositories. Posthoc analyses associated factors with symptoms and demographics.ResultsAnalyses yielded three factors with dissociable whole-brain hypohyper RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default network, but the directionality (hypohyper RSFC) differed across factors. Factor 1 was associated with core ASD symptoms, while factor 2 was associated with comorbid symptoms. Older males preferentially expressed factor 3. Factors were robust across multiple control analyses and not associated with IQ, nor head motion.ConclusionsThere exist at least three ASD factors with dissociable patterns of whole-brain RSFC, behaviors and demographics. Heterogeneous default network hypohyper RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms - a less appreciated domain of heterogeneity in ASD. These factors are co-expressed in ASD individuals with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

biorxiv neuroscience 100-200-users 2019

NINscope a versatile miniscope for multi-region circuit investigations, bioRxiv, 2019-07-01

AbstractMiniaturized fluorescence microscopes (miniscopes) have been instrumental to monitor neural activity during unrestrained behavior and their open-source versions have helped to distribute them at an affordable cost. Generally, the footprint and weight of open-source miniscopes is sacrificed for added functionality. Here, we present NINscope a light-weight, small footprint, open-source miniscope that incorporates a high-sensitivity image sensor, an inertial measurement unit (IMU), and an LED driver for an external optogenetic probe. We highlight the advantages of NINscope by performing the first simultaneous cellular resolution (dual scope) recordings from cerebellum and cerebral cortex in unrestrained mice, revealing that the activity of both regions generally precedes the onset of behavioral acceleration. We further demonstrate the optogenetic stimulation capabilities of NINscope and show that cerebral cortical activity can be driven strongly by cerebellar stimulation. To validate the performance of our miniscope to image from deep-brain regions, we recorded in the dorsal striatum and, using the IMU to assess turning movements, replicate previous studies that show encoding of action space in this subcortical region. Finally, we combine optogenetic stimulation of distinct cortical regions projecting to the dorsal striatum, to probe functional connectivity. In combination with cross-platform control software, NINscope is a versatile addition to the expanding toolbox of open-source miniscopes and will aid multi-region circuit investigations during unrestrained behavior.

biorxiv neuroscience 0-100-users 2019

 

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