Biology subjects

Widge, A. S.

Publications and source records attributed to Widge, A. S..

26 records · Page 2Linked to original sources

bioRxiv2021

Probing Neuro-Endocrine Interactions Through Wireless Magnetothermal Stimulation of Peripheral Organs

Exposure to stress alters hypothalamic-pituitary-adrenal (HPA) axis reactivity; however, it is unclear exactly how or where within the HPA pathway these changes occur. Dissecting these mechanisms requires tools to reliably probe HPA function, particularly the adrenal component, with temporal precision. We previously demonstrated magnetic nanoparticle (MNP) technology to remotely trigger adrenal hormone release by activating thermally sensitive ion channels. Here, we applied adrenal magnetothermal stimulation to probe stress-induced HPA axis changes. MNP and control nanoparticles were injected into the adrenal glands of outbred rats subjected to a tone-shock conditioning/extinction/recall paradigm. We measured MNP-triggered adrenal release before and after conditioning through physiologic (heart rate) and serum (epinephrine, corticosterone) markers. Aversive conditioning altered adrenal function, reducing corticosterone and blunting heart rate increases post-conditioning. MNP-based organ stimulation provides a novel approach to probing the function of HPA and other neuro-endocrine axes and could help elucidate changes across stress and disease models.

bioengineering↗

bioRxiv2021

Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE)

BackgroundClosing the loop between brain activity and behavior is one of the most active areas of development in neuroscience. There is particular interest in developing closed-loop control of neural oscillations. Many studies report correlations between oscillations and functional processes. Oscillation-informed closed-loop experiments might determine whether these relationships are causal and would provide important mechanistic insights which may lead to new therapeutic tools. These closed-loop perturbations require accurate estimates of oscillatory phase and amplitude, which are challenging to compute in real time. New MethodWe developed an easy to implement, fast and accurate Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE). TORTE operates with the open-source Open Ephys GUI (OEGUI) system, making it immediately compatible with a wide range of acquisition systems and experimental preparations. ResultsTORTE efficiently extracts oscillatory phase and amplitude from a target signal and includes a variety of options to trigger closed-loop perturbations. Implementing these tools into existing experiments is easy and adds minimal latency to existing protocols. Comparison with Existing MethodsMost labs use in-house lab-specific approaches, limiting replication and extension of their experiments by other groups. Accuracy of the extracted analytic signal and accuracy of oscillation-informed perturbations with TORTE match presented results by these groups. However, TORTE provides access to these tools in a flexible, easy to use toolkit without requiring proprietary software. ConclusionWe hope that that the availability of a high-quality, open-source, and broadly applicable toolkit will increase the number of labs able to perform oscillatory closed-loop experiments, and will improve the replicability of protocols and data across labs. HighlightsO_LITORTE provides a toolkit to investigate closed loop oscillation-informed experiments. C_LIO_LIThe toolkit is versatile and open-source promoting replicability across scientists. C_LIO_LIThe analytic signal algorithm within TORTE preforms equally to existing algorithms. C_LI

neuroscience↗

bioRxiv2021

A State Space Modeling Approach to Real-Time Phase Estimation

Brain rhythms have been proposed to facilitate brain function, with an especially important role attributed to the phase of low frequency rhythms. Understanding the role of phase in neural function requires interventions that perturb neural activity at a target phase, necessitating estimation of phase in real-time. Current methods for real-time phase estimation rely on bandpass filtering, which assumes narrowband signals and couples the signal and noise in the phase estimate, adding noise to the phase and impairing detections of relationships between phase and behavior. To address this, we propose a state space phase estimator for real-time tracking of phase. By tracking the analytic signal as a latent state, this framework avoids the requirement of bandpass filtering, separately models the signal and the noise, accounts for rhythmic confounds, and provides credible intervals for the phase estimate. We demonstrate in simulations that the state space phase estimator outperforms current state-of-the-art real-time methods in the contexts of common confounds such as broadband rhythms, phase resets and co-occurring rhythms. Finally, we show applications of this approach to in vivo data. The method is available as a ready-to-use plug-in for the OpenEphys acquisition system, making it widely available for use in experiments.

neuroscience↗

bioRxiv2020

Lost in translation: No effect of repeated optogenetic cortico-striatal stimulation on compulsivity in rats

BACKGROUNDThe orbitofrontal cortex-ventromedial striatum (OFC-VMS) circuitry is widely believed to drive compulsive behavior. Hyperactivating this pathway in inbred mice produces excessive and persistent self-grooming, which has been considered a model for human compulsivity. We aimed to replicate these findings in outbred rats, where there are few reliable compulsivity models. METHODS27 male Long-Evans rats implanted with optical-fibers into VMS and with opsins delivered into OFC received optical stimulation at parameters that produce OFC-VMS plasticity and compulsive grooming in mice. We then evaluated rats for compulsive self-grooming at six timepoints: before, during, immediately after and one hour after each stimulation, one and two weeks after the ending of a 6-day stimulation protocol. To further test for effects of OFC-VMS hyperstimulation, we ran animals in three standard compulsivity assays: marble burying, nestlet shredding, and operant attentional setshifting. RESULTSOFC-VMS stimulation did not increase self-grooming or induce significant changes in nestlet shredding, marble burying, or set-shifting in rats. Follow-on evoked potential studies verified that the mouse protocol did alter OFC-VMS synaptic weighting. CONCLUSIONSIn sum, although physiological changes were observed in the OFC-VMS circuitry, we could not reproduce in a strongly powered study in rats a model of compulsive behavior previously reported in mice. If optogenetic effects on behavior do not reliably transfer between rodent species, this may have important implications for designing rodent-to-human translational pipelines.

neuroscience↗

bioRxiv2020

Closed loop enhancement and neural decoding of human cognitive control

Cognitive control is the ability to withhold a default, prepotent response in favor of a more adaptive choice. Control deficits are common across mental disorders, including depression, anxiety, and addiction. Thus, a method for improving cognitive control could be broadly useful in disorders with few effective treatments. Here, we demonstrate closed-loop enhancement of one aspect of cognitive control by direct brain stimulation in humans. We stimulated internal capsule/striatum in participants undergoing intracranial epilepsy monitoring as they performed a cognitive control/conflict task. Stimulation enhanced performance, with the strongest effects from dorsal capsule/striatum stimulation. We then developed a framework to detect control lapses and stimulate in response. This closed-loop approach produced larger behavioral changes than open-loop stimulation, with a slight improvement in performance change per unit of energy delivered. Finally, we decoded task performance directly from activity on a small number of electrodes, using features compatible with existing closed-loop brain implants. Our findings are proof of concept for a new approach to treating severe mental disorders, based on directly remediating underlying cognitive deficits.

bioengineering↗

bioRxiv2019

Bidirectional modulation of human emotional conflict resolution using intracranial stimulation

The ability to regulate emotions in the service of meeting ongoing goals and task demands is a key aspect of adaptive human behavior in our volatile social world. Consequently, difficulties in processing and responding to emotional stimuli underlie many psychiatric diseases ranging from depression to anxiety, the common thread being effects on behavior. Behavior, which is made up of shifting, difficult to measure hidden states such as attention and emotion reactivity, is a product of integrating external input and latent mental processes. Directly measuring, and differentiating, separable hidden cognitive, emotional, and attentional states contributing to emotion conflict resolution, however, is challenging, particularly when only using task-relevant behavioral measures such as reaction time. State-space representations are a powerful method for investigating hidden states underlying complex systems. Using state-space modeling of behavior, we identified relevant hidden cognitive states and predicted behavior in a standardized emotion regulation task. After identifying and validating models which best fit the behavior and narrowing our focus to one model, we used targeted intracranial stimulation of the emotion regulation-relevant neurocircuitry, including prefrontal structures and the amygdala, to causally modulate separable states. Finally, we focused on this one validated state-space model to perform real-time, bidirectional closed-loop adaptive stimulation in a subset of participants. These approaches enable an improved understanding of how to sample and understand emotional processing in a way which could be leveraged in neuromodulatory therapy for disorders of emotional regulation.

neuroscience↗

bioRxiv2019

A statistical modeling framework to assess cross-frequency coupling while accounting for confounding effects

Cross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate how CFC evolves during seizures and is affected by electrical stimuli.

neuroscience↗

bioRxiv2018

COMPASS: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry

Mathematical modeling of behavior during psychophysical tasks, referred to as \"computational psychiatry\", could greatly improve our understanding of mental disorders. One barrier to broader adoption of computational methods is that they often require advanced programming skills. We developed the Computational Psychiatry Adaptive State-Space (COMPASS) toolbox, an open-source MATLAB-based software package. After specifying a few parameters in a small set of user-friendly functions, COMPASS allows the user to efficiently fit of a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data, and can be tested using goodness-of-fit methods. Here, we demonstrate that COMPASS can replicate two computational behavior analyses from different groups. COMPASS replicates and, in one case, slightly improves on the original modeling results. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.

bioengineering↗