A classic view of the striatum holds that activity in direct and indirect pathways oppositely modulates motor output. Whether this involves direct control of movement, or reflects a cognitive process underlying movement, has remained unresolved. Here we find that strong, opponent control of behavior by the two pathways of the dorsomedial striatum (DMS) depends on a task's cognitive demands. Furthermore, a latent state model (a hidden markov model with generalized linear model observations) reveals that-even within a single task-the contribution of the two pathways to behavior is state-dependent. Specifically, the two pathways have large contributions in one of two states associated with a strategy of evidence accumulation, compared to a state associated with a strategy of repeating previous choices. Thus, both the cognitive demands imposed by a task, as well as the strategy that mice pursue within a task, determine whether DMS pathways provide strong and opponent control of behavior.

Cerebral ischemia and reperfusion initiate cellular events in brain that lead to neurological disability. Investigating these cellular events provides ample targets for developing new treatments. Despite considerable work, no such therapy has translated into successful stroke treatment. Among other issues—such as incomplete mechanistic knowledge and faulty clinical trial design—a key contributor to prior translational failures may be insufficient scientific rigor during preclinical assessment: nonblinded outcome assessment; missing randomization; inappropriate sample sizes; and preclinical assessments in young male animals that ignore relevant biological variables, such as age, sex, and relevant comorbid diseases. Promising results are rarely replicated in multiple laboratories. We sought to address some of these issues with rigorous assessment of candidate treatments across 6 independent research laboratories. The Stroke Preclinical Assessment Network (SPAN) implements state-of-the-art experimental design to test the hypothesis that rigorous preclinical assessment can successfully reduce or eliminate common sources of bias in choosing treatments for evaluation in clinical studies. SPAN is a randomized, placebo-controlled, blinded, multilaboratory trial using a multi-arm multi-stage protocol to select one or more putative stroke treatments with an implied high likelihood of success in human clinical stroke trials. The first stage of SPAN implemented procedural standardization and experimental rigor. All participating research laboratories performed middle cerebral artery occlusion surgery adhering to a common protocol and rapidly enrolled 913 mice in the first of 4 planned stages with excellent protocol adherence, remarkable data completion and low rates of subject loss. SPAN stage 1 successfully implemented treatment masking, randomization, prerandomization inclusion/exclusion criteria, and blinded assessment to exclude bias. Our data suggest that a large, multilaboratory, preclinical assessment effort to reduce known sources of bias is feasible and practical. Subsequent SPAN stages will evaluate candidate treatments for potential success in future stroke clinical trials using aged animals and animals with comorbid conditions.

BackgroundPost-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE1).MethodsWe performed a multicentre, retrospective case–control study of patients with TBI. 63 PTE1patients were matched with 63 non-PTE1patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities.ResultsIn the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)).ConclusionsEpileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

A classic view of the striatum holds that activity in direct and indirect pathways oppositely modulates motor output. Whether this involves direct control of movement, or reflects a cognitive process underlying movement, has remained unresolved. Here we find that strong, opponent control of behavior by the two pathways of the dorsomedial striatum (DMS) depends on a task's cognitive demands. Furthermore, a latent state model (a hidden markov model with generalized linear model observations) reveals that - even within a single task - the contribution of the two pathways to behavior is state-dependent. Specifically, the two pathways have large contributions in one of two states associated with a strategy of evidence accumulation, compared to a state associated with a strategy of repeating previous choices. Thus, both the cognitive demands imposed by a task, as well as the strategy that mice pursue within a task, determine whether DMS pathways provide strong and opponent control of behavior.