Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference.

Biophysically detailed neural models are a powerful technique to study neural dynamics in health and disease with a growing number of established and openly available models. A major challenge in the use of such models is that parameter inference is an inherently difficult and unsolved problem. Identifying unique parameter distributions that can account for observed neural dynamics, and differences across experimental conditions, is essential to their meaningful use. Recently, simulation based inference (SBI) has been proposed as an approach to perform Bayesian inference to estimate parameters in detailed neural models. SBI overcomes the challenge of not having access to a likelihood function, which has severely limited inference methods in such models, by leveraging advances in deep learning to perform density estimation. While the substantial methodological advancements offered by SBI are promising, their use in large scale biophysically detailed models is challenging and methods for doing so have not been established, particularly when inferring parameters that can account for time series waveforms. We provide guidelines and considerations on how SBI can be applied to estimate time series waveforms in biophysically detailed neural models starting with a simplified example and extending to specific applications to common MEG/EEG waveforms using the the large scale neural modeling framework of the Human Neocortical Neurosolver. Specifically, we describe how to estimate and compare results from example oscillatory and event related potential simulations. We also describe how diagnostics can be used to assess the quality and uniqueness of the posterior estimates. The methods described provide a principled foundation to guide future applications of SBI in a wide variety of applications that use detailed models to study neural dynamics.

Optogenetic spinal stimulation promotes new axonal growth and skilled forelimb recovery in rats with sub-chronic cervical spinal cord injury.

Objective.Spinal cord injury (SCI) leads to debilitating sensorimotor deficits that greatly limit quality of life. This work aims to develop a mechanistic understanding of how to best promote functional recovery following SCI. Electrical spinal stimulation is one promising approach that is effective in both animal models and humans with SCI. Optogenetic stimulation is an alternative method of stimulating the spinal cord that allows for cell-type-specific stimulation. The present work investigates the effects of preferentially stimulating neurons within the spinal cord and not glial cells, termed 'neuron-specific' optogenetic spinal stimulation. We examined forelimb recovery, axonal growth, and vasculature after optogenetic or sham stimulation in rats with cervical SCI.Approach.Adult female rats received a moderate cervical hemicontusion followed by the injection of a neuron-specific optogenetic viral vector ipsilateral and caudal to the lesion site. Animals then began rehabilitation on the skilled forelimb reaching task. At four weeks post-injury, rats received a micro-light emitting diode (µLED) implant to optogenetically stimulate the caudal spinal cord. Stimulation began at six weeks post-injury and occurred in conjunction with activities to promote use of the forelimbs. Following six weeks of stimulation, rats were perfused, and tissue stained for GAP-43, laminin, Nissl bodies and myelin. Location of viral transduction and transduced cell types were also assessed.Main Results.Our results demonstrate that neuron-specific optogenetic spinal stimulation significantly enhances recovery of skilled forelimb reaching. We also found significantly more GAP-43 and laminin labeling in the optogenetically stimulated groups indicating stimulation promotes axonal growth and angiogenesis.Significance.These findings indicate that optogenetic stimulation is a robust neuromodulator that could enable future therapies and investigations into the role of specific cell types, pathways, and neuronal populations in supporting recovery after SCI.

Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference.

Biophysically detailed neural models are a powerful technique to study neural dynamics in health and disease with a growing number of established and openly available models. A major challenge in the use of such models is that parameter inference is an inherently difficult and unsolved problem. Identifying unique parameter distributions that can account for observed neural dynamics, and differences across experimental conditions, is essential to their meaningful use. Recently, simulation based inference (SBI) has been proposed as an approach to perform Bayesian inference to estimate parameters in detailed neural models. SBI overcomes the challenge of not having access to a likelihood function, which has severely limited inference methods in such models, by leveraging advances in deep learning to perform density estimation. While the substantial methodological advancements offered by SBI are promising, their use in large scale biophysically detailed models is challenging and methods for doing so have not been established, particularly when inferring parameters that can account for time series waveforms. We provide guidelines and considerations on how SBI can be applied to estimate time series waveforms in biophysically detailed neural models starting with a simplified example and extending to specific applications to common MEG/EEG waveforms using the the large scale neural modeling framework of the Human Neocortical Neurosolver. Specifically, we describe how to estimate and compare results from example oscillatory and event related potential simulations. We also describe how diagnostics can be used to assess the quality and uniqueness of the posterior estimates. The methods described provide a principled foundation to guide future applications of SBI in a wide variety of applications that use detailed models to study neural dynamics.

Automated lever task with minimum antigravity movement for rats with cervical spinal cord injury.

BACKGROUND: Although there is currently no cure for paralysis due to spinal cord injury (SCI), the highest treatment priority is restoring arm and hand function for people with cervical SCI. Preclinical animal models provide an opportunity to test innovative treatments, but severe cervical injury models require significant time and effort to assess responses to novel interventions. Moreover, there is no behavioral task that can assess forelimb movement in rats with severe cervical SCI unable to perform antigravity movements. NEW METHOD: We developed a novel lever pressing task for rats with severe cervical SCI. We employed an automated adaptive algorithm to train animals using open-source software and commercially available hardware. We found that using the adaptive training required only 13.3 ± 2.5 training days to achieve behavioral proficiency. The lever press task could quantify immediate and long-term improvements in severely impaired forelimb function effectively. This behavior platform has potential to facilitate rehabilitative training and assess effects of therapeutic modalities following SCI. COMPARISON WITH EXISTING METHODS: There is no existing assessment aiming to quantify forelimb extension movement in rodents without function against gravity. We found that the new lever press task in the antigravity position could assess the severity of cervical SCI as well as the compensatory movement in the proximal forelimb less affected by the injury. CONCLUSIONS: This study demonstrates that the new behavioral task is capable of tracking the functional changes with various therapies in rats with severe forelimb impairments in a cost- and time-efficient manner.

Brain-Computer-Spinal Interface Restores Upper Limb Function After Spinal Cord Injury.

Brain-computer interfaces (BCIs) are an emerging strategy for spinal cord injury (SCI) intervention that may be used to reanimate paralyzed limbs. This approach requires decoding movement intention from the brain to control movement-evoking stimulation. Common decoding methods use spike-sorting and require frequent calibration and high computational complexity. Furthermore, most applications of closed-loop stimulation act on peripheral nerves or muscles, resulting in rapid muscle fatigue. Here we show that a local field potential-based BCI can control spinal stimulation and improve forelimb function in rats with cervical SCI. We decoded forelimb movement via multi-channel local field potentials in the sensorimotor cortex using a canonical correlation analysis algorithm. We then used this decoded signal to trigger epidural spinal stimulation and restore forelimb movement. Finally, we implemented this closed-loop algorithm in a miniaturized onboard computing platform. This Brain-Computer-Spinal Interface (BCSI) utilized recording and stimulation approaches already used in separate human applications. Our goal was to demonstrate a potential neuroprosthetic intervention to improve function after upper extremity paralysis.

CFTR dysregulation drives active selection of the gut microbiome.

Patients with cystic fibrosis (CF) have altered fecal microbiomes compared to those of healthy controls. The magnitude of this dysbiosis correlates with measures of CF gastrointestinal (GI) disease, including GI inflammation and nutrient malabsorption. However, whether this dysbiosis is caused by mutations in the CFTR gene, the underlying defect in CF, or whether CF-associated dysbiosis augments GI disease was not clear. To test the relationships between CFTR dysfunction, microbes, and intestinal health, we established a germ-free (GF) CF mouse model and demonstrated that CFTR gene mutations are sufficient to alter the GI microbiome. Furthermore, flow cytometric analysis demonstrated that colonized CF mice have increased mesenteric lymph node and spleen TH17+ cells compared with non-CF mice, suggesting that CFTR defects alter adaptive immune responses. Our findings demonstrate that CFTR mutations modulate both the host adaptive immune response and the intestinal microbiome.

Transmembrane domain length is responsible for the ability of a plant reticulon to shape endoplasmic reticulum tubules in vivo.

Reticulons are integral endoplasmic reticulum (ER) membrane proteins that have the ability to shape the ER into tubules. It has been hypothesized that their unusually long conserved hydrophobic regions cause reticulons to assume a wedge-like topology that induces membrane curvature. Here we provide proof of this hypothesis. When over-expressed, an Arabidopsis thaliana reticulon (RTNLB13) localized to, and induced constrictions in, cortical ER tubules. Ectopic expression of RTNLB13 was sufficient to induce ER tubulation in an Arabidopsis mutant (pah1 pah2) whose ER membrane is mostly present in a sheet-like form. By sequential shortening of the four transmembrane domains (TMDs) of RTNLB13, we show that the length of the transmembrane regions is directly correlated with the ability of RTNLB13 to induce membrane tubulation and to form low-mobility complexes within the ER membrane. We also show that full-length TMDs are necessary for the ability of RTNLB13 to reside in the ER membrane.

Five Arabidopsis reticulon isoforms share endoplasmic reticulum location, topology, and membrane-shaping properties.

The cortical endoplasmic reticulum (ER) in tobacco (Nicotiana tabacum) epidermal cells is a network of tubules and cisternae undergoing dramatic rearrangements. Reticulons are integral membrane proteins involved in shaping ER tubules. Here, we characterized the localization, topology, effect, and interactions of five Arabidopsis thaliana reticulons (RTNs), isoforms 1-4 and 13, in the cortical ER. Our results indicate that RTNLB13 and RTNLB1-4 colocate to and constrict the tubular ER membrane. All five RTNs preferentially accumulate on ER tubules and are excluded from ER cisternae. All isoforms share the same transmembrane topology, with N and C termini facing the cytosol and four transmembrane domains. We show by Förster resonance energy transfer and fluorescence lifetime imaging microscopy that several RTNs have the capacity to interact with themselves and each other, and we suggest that oligomerization is responsible for their residence in the ER membrane. We also show that a complete reticulon homology domain is required for both RTN residence in high-curvature ER membranes and ER tubule constriction, yet it is not necessary for homotypic interactions.

The plant endoplasmic reticulum: a cell-wide web.

The ER (endoplasmic reticulum) in higher plants forms a pleomorphic web of membrane tubules and small cisternae that pervade the cytoplasm, but in particular form a polygonal network at the cortex of the cell which may be anchored to the plasma membrane. The network is associated with the actin cytoskeleton and demonstrates extensive mobility, which is most likely to be dependent on myosin motors. The ER is characterized by a number of domains which may be associated with specific functions such as protein storage, or with direct interaction with other organelles such as the Golgi apparatus, peroxisomes and plastids. In the present review we discuss the nature of the network, the role of shape-forming molecules such as the recently described reticulon family of proteins and the function of some of the major domains within the ER network.

Overexpression of a plant reticulon remodels the lumen of the cortical endoplasmic reticulum but does not perturb protein transport.

We have cloned a member of the reticulon (RTN) family of Arabidopsis thaliana (RTNLB13). When fused to yellow fluorescent protein (YFP) and expressed in tobacco leaf epidermal cells, RTNLB13 is localized in the endoplasmic reticulum (ER). Coexpression of a soluble ER luminal marker reveals that YFP-tagged, myc-tagged or untagged RTNLB13 induces severe morphological changes to the lumen of the ER. We show, using fluorescence recovery after photobleaching (FRAP) analysis, that RTNLB13 overexpression greatly reduces diffusion of soluble proteins within the ER lumen, possibly by introducing constrictions into the membrane. In spite of this severe phenotype, Golgi shape, number and dynamics appear unperturbed and secretion of a reporter protein remains unaffected.