Rodent premotor cortex (M2) integrates information from sensory and cognitive networks for action planning during goal-directed decision making. M2 function is regulated by cortical inputs and ascending neuromodulators, including norepinephrine (NE) released from the locus coeruleus (LC). LC-NE has been shown to modulate the signal to noise ratio of neural representations in target cortical regions, increasing the salience of relevant stimuli. Using rats performing a two-alternative forced choice task after administration of a β noradrenergic antagonist (propranolol), we show that β noradrenergic signaling is necessary for effective action plan signals in anterior M2. Loss of β noradrenergic signaling results in failure to suppress irrelevant action plans in anterior M2 disrupting decoding of cue related information, delaying decision times, and increasing trial omissions, particularly in females. Furthermore, we identify a potential mechanism for the sex bias in behavioral and neural changes after propranolol administration via differential expression of β2 noradrenergic receptor RNA across sexes in anterior M2, particularly on local inhibitory neurons. Overall, we show a critical role for β noradrenergic signaling in anterior M2 during decision making by suppressing irrelevant information to enable efficient action planning and decision making.
Data analyzed during this study are included in the supporting file.
- Elena M Vazey
- Ellen M Rodberg
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: All procedures were approved by the Institutional Animal Care and Use Committee at the University of Massachusetts Amherst (#2018-0080) in accordance with the guidelines described in the US National Institutes of Health Guide for the Care and Use of Laboratory Animals (National Research Council 2011). All surgery was performed under isoflurane anesthesia, and every effort was made to minimize suffering.
- Alicia Izquierdo, University of California, Los Angeles, United States
© 2023, Rodberg et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Mathys et al. conducted the first single-nucleus RNA-seq (snRNA-seq) study of Alzheimer’s disease (AD) (Mathys et al., 2019). With bulk RNA-seq, changes in gene expression across cell types can be lost, potentially masking the differentially expressed genes (DEGs) across different cell types. Through the use of single-cell techniques, the authors benefitted from increased resolution with the potential to uncover cell type-specific DEGs in AD for the first time. However, there were limitations in both their data processing and quality control and their differential expression analysis. Here, we correct these issues and use best-practice approaches to snRNA-seq differential expression, resulting in 549 times fewer DEGs at a false discovery rate of 0.05. Thus, this study highlights the impact of quality control and differential analysis methods on the discovery of disease-associated genes and aims to refocus the AD research field away from spuriously identified genes.
The strength of a fear memory significantly influences whether it drives adaptive or maladaptive behavior in the future. Yet, how mild and strong fear memories differ in underlying biology is not well understood. We hypothesized that this distinction may not be exclusively the result of changes within specific brain regions, but rather the outcome of collective changes in connectivity across multiple regions within the neural network. To test this, rats were fear conditioned in protocols of varying intensities to generate mild or strong memories. Neuronal activation driven by recall was measured using c-fos immunohistochemistry in 12 brain regions implicated in fear learning and memory. The interregional coordinated brain activity was computed and graph-based functional networks were generated to compare how mild and strong fear memories differ at the systems level. Our results show that mild fear recall is supported by a well-connected brain network with small-world properties in which the amygdala is well-positioned to be modulated by other regions. In contrast, this connectivity is disrupted in strong fear memories and the amygdala is isolated from other regions. These findings indicate that the neural systems underlying mild and strong fear memories differ, with implications for understanding and treating disorders of fear dysregulation.