Biology subjects

Liston, C.

Publications and source records attributed to Liston, C..

22 records · Page 2Linked to original sources

bioRxiv2019

Lateral septum neurotensin neurons link stress and anorexia

Stress and anxiety are precipitating factors for eating disorders, but the neural basis linking stress to alterations in feeding is not well understood. Here we describe a novel population of stress-responsive neurons in the lateral septum (LS) of mice that express neurotensin (LSNTS) in a sexually dimorphic, estrous cycle-dependent manner. We used in vivo imaging to show that LSNTS neurons are activated by stressful experiences when flight is a viable option, but not by a stressful experience associated with freezing or immobility. LSNTS activation leads to a decrease of food intake and body weight in mice, without altering locomotion or other behaviors associated with anxiety. Molecular profiling of LSNTS neurons showed that these neurons co-express Glp1r (glucagon-like peptide 1 receptor), and both pharmacologic and genetic manipulations of Glp1r signaling in the LS recapitulates the behavioral effects of LSNTS activation. Finally, we mapped the outputs of LSNTS neurons and show that activation of LSNTS nerve terminals in the lateral hypothalamus (LH), a well-established feeding center, also decrease food intake. Taken together, these results show that LSNTS neurons link stress and anorexia via effects on hypothalamic pathways regulating food intake.

neuroscience↗

bioRxiv2018

Functional and Optogenetic Approaches to Discovering Stable Subtype-Specific Circuit Mechanisms in Depression

BackgroundUsing canonical correlation analysis (CCA), hierarchical clustering, and machine learning methods, we recently identified four subtypes of depression defined by distinct patterns of abnormal functional connectivity in depression-related brain networks, which in turn predicted differing clinical symptom profiles and individual differences in treatment response. However, whether and how dysfunction in specific circuits may give rise to specific depressive symptoms and behaviors remains unclear. Furthermore, this approach assumes that there are robust and stable canonical correlations between functional connectivity and depressive symptoms--an assumption that was not extensively tested in our earlier work.\n\nMethodsFirst, we comprehensively re-evaluate the stability of canonical correlations between functional connectivity and symptoms, using optimized approaches for large-scale statistical testing, and we validate methods for improving stability. Next, we illustrate one approach to formulating hypotheses regarding subtype-specific circuit mechanisms driving depressive symptoms and behaviors and then testing them in animal models using optogenetic fMRI. We review recent work in this field and describe one example of this approach.\n\nResultsCorrelations between connectivity features and clinical symptoms are robustly significant, and CCA solutions tested repeatedly on held-out data generalize, but they are sensitive to data quality, preprocessing decisions, and clinical sample heterogeneity, which can reduce effect sizes. Generalization can be markedly improved by adding L2-regularization to CCA, which decreases variance, increases canonical correlations in left-out data, and stabilizes feature selection. This approach, in turn, can be used to identify candidate circuits for optogenetic interrogation in rodent models.\n\nConclusionsMulti-view approaches like CCA are a conceptually useful framework for discovering stable patient subtypes by synthesizing multiple clinical and functional measures. Optogenetic fMRI holds substantial promise for testing hypotheses regarding subtype-specific mechanisms driving specific symptoms and behaviors in depression.

neuroscience↗

bioRxiv2018

A Double-Blind Pilot Dosing Study of Low Field Magnetic Stimulation (LFMS) for Treatment-Resistant Depression (TRD)

Low Field Magnetic Stimulation is a potentially rapid-acting treatment for depression with mood-enhancing effects in as little as one 20-minute session. The most convincing data for LFMS has come from treating bipolar depression. We examined whether LFMS also has rapid mood-enhancing effects in treatment-resistant major depressive disorder, and whether these effects are dose-dependent. We hypothesized that a single 20-min session of LFMS would reduce depressive symptom severity and that the magnitude of this change would be greater after three 20-min sessions than after a single 20-min session. In a double-blind randomized controlled trial, 30 participants (age 21-65) with treatment-resistant depression were randomized to three 20-minute active or sham LFMS treatments with 48 hours between treatments. Response was assessed immediately following LFMS treatment using the 6-item Hamilton Depression Rating Scale (HAMD-6), the Positive and Negative Affect Scale (PANAS) and the Visual Analog Scale. Following the third session of LFMS, the effect of LFMS on VAS and HAMD-6 was superior to sham (F(1, 24) = 7.45, p = 0.03, Holm-Bonferroni corrected; F(1,22) = 6.92, p = 0.03, Holm-Bonferroni corrected, respectively). There were no differences between sham and LFMS following the initial or second session with the effect not becoming significant until after the third session. Three 20-minute LFMS sessions were required for active LFMS to have a mood-enhancing effect for individuals with treatment-resistant depression. As this effect may be transient, future work should address dosing schedules of longer treatment course as well as biomarker-based targeting of LFMS to optimize patient selection and treatment outcomes.

clinical trials↗

bioRxiv2017

Identification Of Cellular-Activity Dynamics Across Large Tissue Volumes In The Mammalian Brain

Tracking the coordinated activity of cellular events through volumes of intact tissue is a major challenge in biology that has inspired significant technological innovation. Yet scanless measurement of the high-speed activity of individual neurons across three dimensions in scattering mammalian tissue remains an open problem. Here we develop and validate a computational imaging approach (SWIFT) that integrates high-dimensional, structured statistics with light field microscopy to allow the synchronous acquisition of single-neuron resolution activity throughout intact tissue volumes as fast as a camera can capture images (currently up to 100 Hz at full camera resolution), attaining rates needed to keep pace with emerging fast calcium and voltage sensors. We demonstrate that this large field-of-view, single-snapshot volume acquisition method--which requires only a simple and inexpensive modification to a standard fluorescence microscope--enables scanless capture of coordinated activity patterns throughout mammalian neural volumes. Further, the volumetric nature of SWIFT also allows fast in vivo imaging, motion correction, and cell identification throughout curved subcortical structures like the dorsal hippocampus, where cellular-resolution dynamics spanning hippocampal subfields can be simultaneously observed during a virtual context learning task in a behaving animal. SWIFTs ability to rapidly and easily record from volumes of many cells across layers opens the door to widespread identification of dynamical motifs and timing dependencies among coordinated cell assemblies during adaptive, modulated, or maladaptive physiological processes in neural systems.

neuroscience↗