Faculty Bibliography

For the past half-century, cognitive and social scientists have struggled with the irrationalities of human choice behavior; people consistently make choices that are logically inconsistent. Is human choice behavior evolutionarily adaptive or is it an inefficient patchwork of competing mechanisms? In this review, I present an interdisciplinary synthesis arguing for a novel interpretation: choice is efficiently irrational. Connecting findings across disciplines suggests that observed choice behavior reflects a precise optimization of the trade-off between the costs of increasing the precision of the choice mechanism and the declining benefits that come as precision increases. Under these constraints, a rationally imprecise strategy emerges that works toward optimal efficiency rather than toward optimal rationality. This approach rationalizes many of the puzzling inconsistencies of human choice behavior, explaining why these inconsistencies arise as an optimizing solution in biological choosers.

The present study seeks to examine individuals' stream of thought in real time. Specifically, we asked participants to speak their thoughts freely out loud during a typical resting-state condition. We first examined the feasibility and reliability of the method and found that the oral reporting method did not significantly change the frequency or content characteristics of self-generated thoughts; moreover, its test-retest reliability was high. Based on methodological feasibility, we combined natural language processing (NLP) with the Bidirectional Encoder Representation from Transformers (BERT) model to directly quantify thought content. We analyzed the divergence of self-generated thought content and expressions of sadness and empirically verified the validity and behavioral significance of the metrics calculated by BERT. Furthermore, we found that reflection and brooding could be differentiated by detecting the divergence of self-generated thought content and expressions of sadness, thus deepening our understanding of rumination and depression and providing a way to distinguish adaptive from maladaptive rumination. Finally, this study provides a new framework to examine self-generated thoughts in a resting state with NLP, extending research on the continuous content of instant self-generated thoughts with applicability to resting-state functional brain imaging.

Vocalizations are often elaborate, rhythmically structured behaviors. Vocal motor patterns require close coordination of neural circuits governing the muscles of the larynx, jaw, and respiratory system. In the elaborate vocalization of Alston's singing mouse (Scotinomys teguina) each note of its rapid, frequency-modulated trill is accompanied by equally rapid modulation of breath and gape. To elucidate the neural circuitry underlying this behavior, we introduced the polysynaptic retrograde neuronal tracer pseudorabies virus (PRV) into the cricothyroid and digastricus muscles, which control frequency modulation and jaw opening, respectively. Each virus singly labels ipsilateral motoneurons (nucleus ambiguus for cricothyroid, and motor trigeminal nucleus for digastricus). We find that the two isogenic viruses heavily and bilaterally colabel neurons in the gigantocellular reticular formation, a putative central pattern generator. The viruses also show strong colabeling in compartments of the midbrain including the ventrolateral periaqueductal gray and the parabrachial nucleus, two structures strongly implicated in vocalizations. In the forebrain, regions important to social cognition and energy balance both exhibit extensive colabeling. This includes the paraventricular and arcuate nuclei of the hypothalamus, the lateral hypothalamus, preoptic area, extended amygdala, central amygdala, and the bed nucleus of the stria terminalis. Finally, we find doubly labeled neurons in M1 motor cortex previously described as laryngeal, as well as in the prelimbic cortex, which indicate these cortical regions play a role in vocal production. The progress of both viruses is broadly consistent with vertebrate-general patterns of vocal circuitry, as well as with circuit models derived from primate literature.

Dopamine (DA) is a critical regulator of striatal network activity and is essential for motor activation and reward-associated behaviors. Previous work has shown that DA is influenced by the reward value of food, as well as by hormonal factors implicated in the regulation of food intake and energy expenditure. Changes in striatal DA signaling also have been linked to aberrant eating patterns. Here we test the effect of leptin, an adipocyte-derived hormone involved in feeding and energy homeostasis regulation, on striatal DA release and uptake. Immunohistochemical evaluation identified leptin receptor expression throughout mouse striatum, including on striatal cholinergic interneurons and their extensive processes. Using fast-scan cyclic voltammetry, we found that leptin causes a concentration-dependent increase in evoked extracellular DA concentration ([DA]_o) in dorsal striatum and nucleus accumbens (NAc) core and shell in male mouse striatal slices, and also an increase in the rate of DA uptake. Further, we found that leptin increases cholinergic interneuron excitability, and that the enhancing effect of leptin on evoked [DA]_o is lost when nicotinic acetylcholine (ACh) receptors are antagonized or when examined in striatal slices from mice lacking ACh synthesis. Evaluation of signaling pathways underlying leptin's action revealed a requirement for intracellular Ca²⁺, and the involvement of different downstream pathways in dorsal striatum and NAc core versus NAc shell. These results provide the first evidence for dynamic regulation of DA release and uptake by leptin within brain motor and reward pathways, and highlight the involvement of cholinergic interneurons in this process.SIGNIFICANCE STATEMENTGiven the importance of striatal dopamine in reward, motivation, motor behavior and food intake, identifying the actions of metabolic hormones on dopamine release in striatal subregions should provide new insight into factors that influence dopamine-dependent motivated behaviors. We find that one of these hormones, leptin, boosts striatal dopamine release through a process involving striatal cholinergic interneurons and nicotinic acetylcholine receptors. Moreover, we find that the intracellular cascades downstream from leptin receptor activation underlying enhanced dopamine release differ among striatal subregions. Thus, we not only show that leptin regulates dopamine release, but also identify characteristics of this process that could be harnessed to alter pathological eating behaviors.

Oral cancer pain is attributed to the release from cancers of mediators that sensitize and activate sensory neurons. Intraplantar injection of conditioned media (CM) from human tongue cancer cell line HSC-3 or OSC-20 evokes nociceptive behavior. By contrast, CM from noncancer cell lines, DOK, and HaCaT are non-nociceptive. Pain mediators are carried by extracellular vesicles (EVs) released from cancer cells. Depletion of EVs from cancer cell line CM reverses mechanical allodynia and thermal hyperalgesia. CM from non-nociceptive cell lines become nociceptive when reconstituted with HSC-3 EVs. Two miRNAs (hsa-miR-21-5p and hsa-miR-221-3p) are identified that are present in increased abundance in EVs from HSC-3 and OSC-20 CM compared to HaCaT CM. The miRNA target genes suggest potential involvement in oral cancer pain of the toll like receptor 7 (TLR7) and 8 (TLR8) pathways, as well as signaling through interleukin 6 cytokine family signal transducer receptor (gp130, encoded by IL6ST) and colony stimulating factor receptor (G-CSFR, encoded by CSF3R), Janus kinase and signal transducer and activator of transcription 3 (JAK/STAT3). These studies confirm the recent discovery of the role of cancer EVs in pain and add to the repertoire of algesic and analgesic cancer pain mediators and pathways that contribute to oral cancer pain.

Immune checkpoint blockade (ICB) has transformed the treatment of metastatic cancer but is hindered by variable response rates. A key unmet need is the identification of biomarkers that predict treatment response. To address this, we analyzed six whole exome sequencing cohorts with matched disease outcomes to identify genes and pathways predictive of ICB response. To increase detection power, we focus on genes and pathways that are significantly mutated following correction for epigenetic, replication timing, and sequence-based covariates. Using this technique, we identify several genes (BCLAF1, KRAS, BRAF, and TP53) and pathways (MAPK signaling, p53 associated, and immunomodulatory) as predictors of ICB response and develop the Cancer Immunotherapy Response CLassifiEr (CIRCLE). Compared to tumor mutational burden alone, CIRCLE led to superior prediction of ICB response with a 10.5% increase in sensitivity and a 11% increase in specificity. We envision that CIRCLE and more broadly the analysis of recurrently mutated cancer genes will pave the way for better prognostic tools for cancer immunotherapy.

Vocal communication is a critical feature of social interaction across species; however, the relation between such behavior in humans and nonhumans remains unclear. To enable comparative investigation of this topic, we review the literature pertinent to interactive language use and identify the superset of cognitive operations involved in generating communicative action. We posit these functions comprise three intersecting multistep pathways: (a) the Content Pathway, which selects the movements constituting a response; (b) the Timing Pathway, which temporally structures responses; and (c) the Affect Pathway, which modulates response parameters according to internal state. These processing streams form the basis of the Convergent Pathways for Interaction framework, which provides a conceptual model for investigating the cognitive and neural computations underlying vocal communication across species. Expected final online publication date for the Annual Review of Neuroscience, Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Modern optical neuroimaging approaches are expanding the ability to elucidate complex brain function. Diverse imaging contrasts enable direct observation of neural activity with functional sensors along with the induced hemodynamic responses. To date, decoupling the complex interplay of neurovascular coupling and dynamical physiological states has remained challenging when employing single-modality functional neuroimaging readings. A hybrid fluorescence optoacoustic tomography platform combined with a custom data processing pipeline based on statistical parametric mapping is devised, attaining the first noninvasive observation of simultaneous calcium and hemodynamic activation patterns using optical contrasts. Correlated changes in the oxy- and deoxygenated hemoglobin, total hemoglobin, oxygen saturation, and rapid GCaMP6f fluorescence signals are observed in response to peripheral sensory stimulation. While the concurrent epifluorescence serves to corroborate and complement the functional optoacoustic observations, the latter further aids in decoupling the rapid calcium responses from the slowly varying background in the fluorescence recordings mediated by hemodynamic changes. The hybrid imaging platform expands the capabilities of conventional neuroimaging methods to provide more comprehensive functional readings for studying neurovascular and neurometabolic coupling mechanisms and related diseases.