Faculty Bibliography

Interactions between the prefrontal cortex (PFC) and mediodorsal thalamus are critical for cognitive flexibility, yet the underlying computations are unknown. To investigate frontothalamic substrates of cognitive flexibility, we developed a behavioral task in which mice switched between different sets of learned cues that guided attention toward either visual or auditory targets. We found that PFC responses reflected both the individual cues and their meaning as task rules, indicating a hierarchical cue-to-rule transformation. Conversely, mediodorsal thalamus responses reflected the statistical regularity of cue presentation and were required for switching between such experimentally specified cueing contexts. A subset of these thalamic responses sustained context-relevant PFC representations, while another suppressed the context-irrelevant ones. Through modeling and experimental validation, we find that thalamic-mediated suppression may not only reduce PFC representational interference but could also preserve unused cortical traces for future use. Overall, our study provides a computational foundation for thalamic engagement in cognitive flexibility.

OBJECTIVE:The clinical use of microsignals recorded over broad cortical regions is largely limited by the chronic reliability of the implanted interfaces. APPROACH/METHODS:We evaluated the chronic reliability of novel 61-channel micro-electrocorticographic (µECoG) arrays in rats chronically implanted for over one year and using accelerated aging. Devices were encapsulated with polyimide (PI) or liquid crystal polymer (LCP), and fabricated using commercial manufacturing processes. In vitro failure modes and predicted lifetimes were determined from accelerated soak testing. Successful designs were implanted epidurally over the rodent auditory cortex. Trends in baseline signal level, evoked responses and decoding performance were reported for over one year of implantation. MAIN RESULTS/RESULTS:Devices fabricated with LCP consistently had longer in vitro lifetimes than PI encapsulation. Our accelerated aging results predicted device integrity beyond 3.4 years. Five implanted arrays showed stable performance over the entire implantation period (247-435 days). Our regression analysis showed that impedance predicted signal quality and information content only in the first 31 days of recordings and had little predictive value in the chronic phase (> 31 days). In the chronic phase, site impedances slightly decreased yet decoding performance became statistically uncorrelated with impedance. We also employed an improved statistical model of spatial variation to measure sensitivity to locally varying fields, which is typically concealed in standard signal power calculations. SIGNIFICANCE/CONCLUSIONS:These findings show that µECoG arrays can reliably perform in chronic applications in vivo for over one year, which facilitates the development of a high-density, clinically viable interface.

A potential bottleneck to improving speech perception performance in cochlear implant (CI) users is that some of their electrodes may poorly encode speech information. Several studies have examined the effect of deactivating poorly encoding electrodes on speech perception with mixed results. Many of these studies focused on identifying poorly encoding electrodes by some measure (e.g. electrode discrimination, pitch ordering, threshold, CT-guided, masked modulation detection), but provide inconsistent criteria about which electrodes, and how many, should be deactivated, and without considering how speech information becomes distributed across the electrode array. The present simulation study addresses this issue using computational approaches. Previously validated models were used to generate predictions of speech scores as a function of all possible combinations of active electrodes in a 22-electrode array in three groups of hypothetical subjects representative of relatively better, moderate, and poorer performing CI users. Using high-performance computing, over 500 million predictions were generated. Although deactivation of the poorest encoding electrodes sometimes resulted in predicted benefit, this benefit was significantly less relative to predictions resulting from model-optimized deactivations. This trend persisted when using novel stimuli (i.e. other than those used for optimization) and when using different processing strategies. Optimum electrode deactivation patterns produced an average predicted increase in word scores of 10% with some scores increasing by more than 20%. Optimum electrode deactivation patterns typically included 11 to 19 (out of 22) active electrodes, depending on the performance group. Optimal active electrode combinations were those that maximized discrimination of speech cues, maintaining 80%-100% of the physical span of the array. The present study demonstrates the potential for further improving CI users' speech scores with appropriate selection of active electrodes.

PURPOSE/OBJECTIVE:To explore the motion sensitivity of magnetic resonance fingerprinting (MRF), we performed experiments with different types of motion at various time intervals during multiple scans. Additionally, we investigated the possibility to correct the motion artifacts based on redundancy in MRF data. METHODS:A radial version of the FISP-MRF sequence was used to acquire one transverse slice through the brain. Three subjects were instructed to move in different patterns (in-plane rotation, through-plane wiggle, complex movements, adjust head position, and pretend itch) during different time intervals. The potential to correct motion artifacts in MRF by removing motion-corrupted data points from the fingerprints and dictionary was evaluated. RESULTS:values (-10% on average). CONCLUSION/CONCLUSIONS:Our experimental results showed that different kinds of motion have distinct effects on the precision and effective resolution of the parametric maps measured with MRF. Although MRF-based acquisitions can be relatively robust to motion effects occurring at the beginning or end of the sequence, relying on redundancy in the data alone is not sufficient to assure the accuracy of the multi-parametric maps in all cases.

Aggression is a crucial survival behavior: it is employed to defend territory, compete for food and mating opportunities, protect kin, and resolve disputes. Although widely differing in its behavioral expression, aggression is observed across many species. The neural substrates of aggression have been investigated for nearly a century and two highly conserved circuitries emerge as critical substrates for generating and modulating aggression. One circuitry centers on the medial hypothalamus. Activity of the medial hypothalamic cells closely correlates with attacks and can bi-directionally modulate aggressive behaviors. The other aggression-related circuit involves the mesolimbic dopamine cells. Dopaminergic antagonists are the most commonly used treatment for suppressing human aggression in psychotic patients. Animal studies support essential roles of dopaminergic signaling in the nucleus accumbens in assessing the reward value of aggression and reinforcing the aggressive behaviors. In this review, we will provide an overview regarding the functions of medial hypothalamus and dopaminergic system in mediating aggressive behaviors and the potential interactions between these two circuitries.

Following stimulation, pancreatic β-cells must orchestrate a plethora of signalling events to ensure the appropriate release of insulin and maintenance of normal glucose homeostasis. Failure at any point in this cascade leads to impaired insulin secretion, elevated blood levels of glucose and eventually type 2 diabetes mellitus. Likewise, β-cell replacement or regeneration strategies for the treatment of both type 1 and type 2 diabetes mellitus might fail if the correct cell signalling phenotype cannot be faithfully recreated. However, current understanding of β-cell function is complicated because of the highly dynamic nature of their intracellular and intercellular signalling as well as insulin release itself. β-Cells must precisely integrate multiple signals stemming from multiple cues, often with differing intensities, frequencies and cellular and subcellular localizations, before converging these signals onto insulin exocytosis. In this respect, optical approaches with high resolution in space and time are extremely useful for properly deciphering the complexity of β-cell signalling. An increased understanding of β-cell signalling might identify new mechanisms underlying insulin release, with relevance for future drug therapy and de novo stem cell engineering of functional islets.