Leah Hachigian, Heiman Lab

Title: Understanding differential vulnerability in neurodegenerative disease

Abstract: Huntington’s disease (HD), the most common inherited neurodegenerative disorder, is caused by mutations in the huntingtin (HTT) gene, which encodes a poly-glutamine (polyQ) repeat protein. Despite widespread expression of the HTT gene, HD presents with massive neuronal cell loss in the striatum and deep layers of the cortex. Using the cell-type specific translating ribosome affinity purification (TRAP) methodology, we found that deep-layer cortical pyramidal neurons and striatal medium spiny neurons demonstrate a high level of expression of genes encoding non-HTT polyQ repeat proteins, as compared to neuronal cell types found in other, less vulnerable brain regions. Since polyQ peptides can influence HTT protein aggregation and cellular toxicity, and polyQ proteins can be sequestered into mutant HTT aggregates, we reasoned that a higher level of expression of polyQ-encoding genes in vulnerable neurons may be linked to those cell types’ enhanced cellular vulnerability in HD. Specifically, we looked at the expression patterns of these polyQ proteins to identify one with an expression pattern that most closely mimicked the neuronal vulnerability seen in HD. Foxp2, an essential transcription factor, was highly expressed in striatum and deep layer cortex but not in unaffected regions in HD. Combined with evidence that Foxp2 is important for motor function and regulating striatal-enriched genes, we hypothesized that Foxp2 loss of function due to coaggregation with mutant HTT might underlie HD pathophysiology. Our data suggest that Foxp2 does, in fact, coaggregate with mutant HTT, resulting in a loss of soluble Foxp2 in vulnerable regions in HD. If loss of Foxp2 function leads to some of the pathophysiology observed in mouse models, removing Foxp2 from wildtype animals should recapitulate the HD phenotype. Interestingly, we were able to mimic the behavioral phenotype of HD mouse models by knocking down Foxp2 using viral shRNA injections. Moreover, we were able to rescue the behavioral deficits in HD model mice by overexpressing Foxp2. Future work will illuminate the molecular underpinnings of these findings and elucidate the role of Foxp2 in deep layer cortical and striatal cell function.

Richard Futrell, Gibson Lab

Title: Efficiency in Human Language

Abstract: I explore the hypothesis that the properties of human languages can be explained in terms of efficient communication given fixed high-level information processing constraints. First, I show corpus evidence from 37 languages that word order in grammar and usage is shaped by working memory and planning complexity constraints in the form of dependency locality: a pressure for syntactically linked words to be close to one another in linear order. Next, I present evidence that word lengths are optimized to convey information efficiently while taking context into account. Finally, I present evidence that systems of color words across many languages and cultures are optimized to convey information about salient objects in typical environments.

Emily Mackevicius, Fee Lab

Title: Learning the simple building blocks of a complex motor program

Abstract: How does the brain learn complex behaviors? Does it break them into simpler pieces? How are goals represented, and translated into actions that produce those goals? Songbirds learn to imitate the songs of tutors they heard as juveniles. From unstructured babbling, repeatable syllables emerge. My work focuses on how the brain of a young bird learns to produce each new syllable. My neural recordings and modeling work suggest a simple mechanism by which timing learned in one domain (listening to a tutor) could be transferred to support learning in a new domain (singing).