Biology subjects

Power, J.

Publications and source records attributed to Power, J..

6 recordsLinked to original sources

bioRxiv2025

Knock-out of Tpm4.2/actin filaments alters neuronal signaling, neurite outgrowth and behavioral phenotypes in mice.

Tropomyosins (Tpm) are master regulators of actin dynamics through forming co-polymers with filamentous actin. Despite the well-understood function of muscle Tpms in the contractile apparatus of muscle cells, much less is known about the diverse physiological function of cytoplasmic Tpms in eukaryotic cells. Here, we investigated the role of the Tpm4.2 isoform in neuronal processes including signaling, neurite outgrowth and receptor recycling using primary neurons from Tpm4.2 knock-out mice. Live imaging of calcium and electro-physiology data demonstrated increased frequency, yet reduced strength of single neuron spikes. Calcium imaging further showed increase in neuronal networks. In vitro assays of Tpm4.2 knock-out neurons displayed impaired recycling of the AMPA neurotransmitter receptor subunit GluA1. Morphometric analysis of neurite growth showed increased dendritic complexity and altered dendritic spine morphology in Tpm4.2 knock-out primary neurons. Behavioral analysis of Tpm4.2 knock-out mice displayed heightened anxiety in Open field test whilst Elevated Plus maze displayed heightened anxiety only in females. A sex-dependent phenotype was also seen in the Social Preference test with impaired social memory and socialization in female Tpm4.2 knock-out mice, whilst male and female knock-out mice had impaired recognition memory in a Novel Object Recognition test. Our study depicts the multi-faceted role of the Tpm4.2 isoform and its co-polymer F-actin population in neurons, with potential implications for better understanding diseases of the nervous system which involve actin cytoskeleton dys-function.

neuroscience↗

bioRxiv2024

Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales

Intrinsic neural timescale (INT) is a resting-state fMRI (rs-fMRI) measure that reflects the time window of neural integration within a brain region. Despite the potential relevance of INT to cognition, brain organization, and neuropsychiatric illness, the influences of physiological artifacts on INT have not been systematically considered. Two artifacts, head motion and respiration, pose serious issues in rs-fMRI studies. Here, we described their impact on INT estimation and tested the ability of two denoising strategies for mitigating these artifacts, high-motion frame censoring and global signal regression (GSR). We used a subset of the HCP Young Adult dataset with runs annotated for breathing patterns (Lynch et al., 2020) and at least one "clean" (reference) run that had minimal head motion and no respiration artifacts; other runs from the same participants (n = 46) were labeled as "non-clean." We found that non-clean runs exhibited brain-wide increases in INT compared to their respective clean runs and the magnitude of error in INT between non-clean and clean runs correlated with the amount of head motion. Importantly, effect sizes were comparable to INT effects reported in the clinical literature. GSR and high-motion frame censoring improved the similarity between INT maps from non-clean runs and their respective clean run. Using a pseudo-random frame-censoring approach, there was a relationship between the amount of censored frames and both the mean INT and mean error, suggesting that frame censoring itself biases INT estimation. A group-level correction procedure reduced this bias and improved similarity between non-clean runs and their respective clean run. Based on our findings, we offer recommendations for rs-fMRI INT studies, which include implementing GSR and high-motion frame censoring with Lomb-Scargle interpolation of censored data, and performing group-level correction of the bias introduced by frame censoring.

neuroscience↗

bioRxiv2021

Rapid appetitive transitions are sculpted by amygdala to accumbens pathways

Foraging, pursuit, and predation rapidly transition into behavioral quiescence during reward capture and consumption. While appetitive-consummatory dissociations are embedded at both psychological and neural levels, the mechanisms controlling switches or transitions between appetitive seeking and consummatory behaviors remain poorly understood. Here we identify the BLA[->]AcbSh pathway as critical to these transitions by showing that this pathway inhibits the appetitive seeking response in the presence of consummatory demands. Using an appetitive cue-discrimination task in male rats, we show that reward delivery is a significant driver of seeking inhibition and that a BLA[->]AcbSh pathway mediates this inhibition. This role in suppressing seeking responses during periods of consumption was not due to a general suppression of behavior because responding to other cues during the same test was unaffected. Moreover, it was specific to the BLA[->]AcbSh pathway, because the contribution of the BLA[->]AcbC pathway to appetitive switching was distinct and modest. State-dependent silencing of BLA[->]AcbSh revealed that the modulation of seeking before and after reward delivery are co-dependent. Finally, we found that BLA terminals in AcbSh have functional connectivity to LH-projecting AcbSh neurons, thereby identifying a BLA[->]AcbSh[->]LH pathway as a putative route for the rapid regulation of appetitive behaviors. Taken together, these findings suggest that the BLA[->]AcbSh pathway is a core component of an appetitive switching system, recruited under conditions requiring rapid or dynamic shifts in appetitive behavior, and that this pathway enables these shifts by actively inhibiting seeking. Significance statementForaging, pursuit, and predation quickly transition into behavioral quiescence during reward capture and consumption. These transitions are critical for flexible and responsive sequences of behavior. Here we show that behavioral transitions are actively controlled at the limbic-striatal interface. We identify reward receipt as a proximal trigger for transition between reward seeking and taking, we identify active inhibition as the functional operation of this transition, and we identify the basolateral amygdala[->]accumbens shell pathway as critical to this functional operation.

neuroscience↗

bioRxiv2020

Basolateral amygdala parvalbumin neurons report aversive prediction error to constrain fear learning

Animals, including humans, use prediction error to guide learning about danger in the environment. The basolateral amygdala (BLA) is obligatory for this learning and BLA excitatory projection neurons are instructed by aversive prediction error to form fear associations. Complex networks of inhibitory interneurons, dominated by parvalbumin (PV) expressing GABAergic neurons, form the intrinsic microcircuitry of the BLA to control projection neuron activity. Whether BLA PV interneurons are also sensitive to prediction error and how they use this error to control fear learning remains unknown. We used PV cell-type specific recording and manipulation approaches in male transgenic PV-Cre rats to address these issues. We show that BLA PV neurons control fear learning about aversive events but not learning about their omission. Furthermore, during fear learning BLA PV neurons express the activity signatures of aversive prediction error: greater activity to unexpected than expected aversive events and greater activity to better rather than poorer predictors of these events. Crucially, we show that BLA PV neurons act to limit fear learning across these variations in prediction error. Together, this demonstrates that prediction error instructs and regulates BLA fear association formation in a cell-type specific manner. Whereas BLA projection neurons use prediction error signals to form and store fear associations, BLA PV interneurons use prediction error signals to constrain fear association formation. Significance StatementThe capacity to predict sources of danger in the environment is essential for survival. This capacity is supported by associative learning mechanisms that are triggered when the danger experienced is greater than the danger expected. Here we show that the activity of parvalbumin positive GABAergic interneurons in the rat basolateral amygdala neurons report this difference between the danger expected and the danger experienced and that they use this difference to limit the amount of fear which is learned.

neuroscience↗

bioRxiv2019

Characteristics of respiratory measures in young adults scanned at rest, including systematic changes and \"missed\" respiratory events

Breathing rate and depth influence the concentration of carbon dioxide in the blood, altering cerebral blood flow and thus functional magnetic resonance imaging (fMRI) signals. Such respiratory fluctuations can have substantial influence in studies of fMRI signal covariance in subjects at rest, the so-called \"resting state functional connectivity\" technique. If respiration is monitored during fMRI scanning, it is typically done using a belt about the subjects abdomen to record abdominal circumference. Several measures have been derived from these belt records, including the windowed envelope of the waveform (ENV), the windowed variance in the waveform (respiration variation, RV), and a measure of the amplitude of each breath divided by the cycle time of the breath (respiration volume per time, RVT). Any attempt to gauge respiratory contributions to fMRI signals requires a respiratory measure, but little is known about how these measures compare to each other, or how they perform beyond the small studies in which they were initially proposed. In this paper, we examine the properties of these measures in hundreds of healthy young adults scanned for an hour each at rest, a subset of the Human Connectome Project chosen for having high-quality physiological records. We find: 1) ENV, RV, and RVT are all similar, though ENV and RV are more similar to each other than to RVT; 2) respiratory events like deep breaths exhibit characteristic fMRI signal changes, head motions, and image quality abnormalities time-locked to deep breaths evident in the belt traces; 3) all measures can \"miss\" respiratory events evident in the belt traces; 4) RVT \"misses\" deep breaths (i.e., yawns and sighs) more than ENV or RV; 5) all respiratory measures change systematically over the course of a 14.4-minute scan, decreasing in mean value. We discuss the implication of these findings for the literature, and ways to move forward in modeling respiratory influences on fMRI scans.\n\nHighlights- Examines 3 respiratory measures in resting state fMRI scans of healthy young adults\n- All respiratory measures \"miss\" respiratory events, some more than others\n- Respiration volume per time (RVT) frequently \"misses\" deep breaths\n- All respiratory measures decrease systematically over 14.4 minute scans\n- Systematic decreases are due to decreased breathing depth and rate

neuroscience↗

bioRxiv2019

Distinctions among real and apparent respiratory motions in human fMRI data

Head motion estimates in functional magnetic resonance imaging (fMRI) scans appear qualitatively different with sub-second image sampling rates compared to the multi-second sampling rates common in the past. Whereas formerly the head appeared still for much of a scan with brief excursions from baseline, the head now appears to be in constant motion, and motion estimates often seem to divulge little information about what is happening in a scan. This constant motion has been attributed to respiratory oscillations that do not alias at faster sampling rates, and investigators are divided on the extent to which such motion is \"real\" motion or only \"apparent\" pseudomotion. Some investigators have abandoned the use of motion estimates entirely due to these considerations. Here we investigate the properties of motion in several fMRI datasets sampled at rates between 720-1160 ms, and describe 5 distinct kinds of respiratory motion: 1) constant real respiratory motion in the form of head nodding most evident in vertical position and pitch, which can be very large; 2) constant pseudomotion at the same respiratory rate as real motion, occurring only in the phase encode direction; 3) punctate real motions occurring at times of very deep breaths; 4) a low-frequency pseudomotion in only the phase encode direction following very deep breaths; 5) slow modulation of vertical and anterior-posterior head position by the respiratory envelope. We reformulate motion estimates in light of these considerations and obtain good concordance between motion estimates, physiologic records, image quality measures, and events evident in the fMRI signals.\n\nHighlights- Examines several fast-TR datasets with sampling rates of 720-1160 ms\n- Identifies 7 kinds of motion in fMRI scans, 5 of them related to respiration\n- Identifies 2 forms of pseudomotion occurring only in phase encode direction\n- Pseudomotion is a function of soft tissue mass, not lung volume\n- Reformulates motion estimates to draw out particular kinds of motion

neuroscience↗