Biology subjects

Devor, A.

Publications and source records attributed to Devor, A..

24 records · Page 2Linked to original sources

bioRxiv2021

All-optical electrophysiology in hiPSC-derived neurons with synthetic voltage sensors

Voltage imaging and "all-optical electrophysiology" in human induced pluripotent stem cell (hiPSC)-derived neurons have opened unprecedented opportunities for high-throughput phenotyping of activity in neurons possessing unique genetic backgrounds of individual patients. While prior all-optical electrophysiology studies relied on genetically encoded voltage indicators, viral transduction of human neurons with large or multiple expression vectors can impact cell function and often lead to massive cell death. Here, we demonstrate an alternative protocol using a synthetic voltage sensor and genetically encoded optogenetic actuator that generate robust and reproducible results. We demonstrate the functionality of this method by measuring spontaneous and evoked activity in three independent hiPSC-derived neuronal cell lines with distinct genetic backgrounds.

neuroscience↗

bioRxiv2019

Spatially Resolved Estimation of Metabolic Oxygen Consumption From Optical Measurements in Cortex

The cerebral metabolic rate of oxygen (CMRO2) is an important indicator of brain function and pathology. Knowledge about its magnitude is also required for proper interpretation of the blood oxygenation level dependent (BOLD) signal measured with functional MRI (fMRI). The ability to measure CMRO2 with high spatial and temporal accuracy is thus highly desired. Traditionally the estimation of CMRO2 has been pursued with somewhat indirect approaches combining several different types of measurements with mathematical modeling of the underlying physiological processes. Given the numerous assumptions involved, questions have thus been raised about the accuracy of the resulting CMRO2 estimates. The recent ability to measure the level of oxygen (pO2) in cortex with high spatial resolution in in vivo conditions has provided a more direct way for estimating CMRO2. CMRO2 and pO2 are related via the Poisson partial differential equation. Assuming a constant CMRO2 and cylindrical symmetry around the blood vessel providing the oxygen, the so-called Krogh-Erlang formula relating the spatial pO2 profile to a constant CMRO2 value can be derived. This Krogh-Erlang formula has previously been used to estimate the average CMRO2 close to cortical blood vessels based on pO2 measurements in rats.\n\nHere we introduce a new method, the Laplace method, to provide spatial maps of CMRO2 based on the same measured pO2 profiles. The method has two key steps: First the measured pO2 profiles are spatially smoothed to reduce effects of spatial noise in the measurements. Next, the Laplace operator (a double spatial derivative) in two spatial dimensions is applied on the smoothed pO2 profiles to obtain spatially resolved CMRO2 estimates. The smoothing introduces a bias, and a balance must be found where the effects of the noise are sufficiently reduced without introducing too much bias. In this model-based study we explore this balance in situations where the ground truth, that is, spatial profile of CMRO2 is preset and thus known, and the corresponding pO2 profiles are found by solving the Poisson equation, either numerically or by taking advantage of the Krogh-Erlang formula. MATLAB code for using the Laplace method is provided.

neuroscience↗

bioRxiv2019

Microscale physiological events on the human cortical surface detected with PEDOT:PSS Electrodes

Despite ongoing advancements in our understanding of the local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their intermediate microscale local circuit dynamics. Here, we utilized ultrahigh density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper layers of the grey matter. They were also observed in rodents, non-human primates, and semi-chronic recordings in humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that with the proper combination of high resolution microelectrodes and analytic techniques it is possible to capture neuronal dynamics that lay between somatic action potentials and aggregate population activity and that understanding these intermediate microscale dynamics may reveal important details of the full circuit behavior in human cognition.

neuroscience↗

bioRxiv2019

Making the MOSTest of imaging genetics

Regional brain morphology has a complex genetic architecture, consisting of many common polymorphisms with small individual effects, which has proven challenging for genome-wide association studies to date, despite its high heritability1,2. Given the distributed nature of the genetic signal across brain regions, joint analysis of regional morphology measures in a multivariate statistical framework provides a way to enhance discovery of genetic variants with current sample sizes. While several multivariate approaches to GWAS have been put forward over the past years3-5, none are optimally suited for complex, large-scale data. Here, we applied the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computational design enabling rapid and reliable permutation-based inference, to 171 subcortical and cortical brain morphology measures from 26,502 participants of the UK Biobank (mean age 55.5 years, 52.0% female). At the conventional genome-wide significance threshold of =5x10-8, MOSTest identifies 347 genetic loci associated with regional brain morphology, more than any previous study, improving upon the discovery of established GWAS approaches more than threefold. Our findings implicate more than 5% of all protein-coding genes and provide evidence for gene sets involved in neuron development and differentiation. As such, MOSTest, which we have made publicly available, enhances our understanding of the genetic determinants of regional brain morphology.

neuroscience↗

bioRxiv2018

Homogenization of capillary flow and oxygenation in deeper cortical layers correlates with increased oxygen extraction

Our understanding of how capillary blood flow and oxygen distribute across cortical layers to meet the local metabolic demand is incomplete. We addressed this question by using two-photon imaging of microvascular oxygen partial pressure (PO2) and flow in the whisker barrel cortex in awake mice at rest. Our measurements in layers I-V show that the capillary red-blood-cell flux and oxygenation heterogeneity, and the intracapillary resistance to oxygen delivery, all decrease with depth, reaching a minimum around layer IV, while the depth-dependent oxygen extraction fraction is increased in layer IV, where oxygen demand is presumably the highest. Our findings suggest that homogenization of physiological observables relevant to oxygen transport to tissue is an important part of the microvascular network adaptation to a local brain metabolism increase. These results will inform the biophysical models of layer-specific cerebral oxygen delivery and consumption and improve our understanding of diseases that affect the cerebral microcirculation.\n\nIMPACT STATEMENTHomogenization of cortical capillary blood flow and oxygenation underpins an important mechanism, by which the microvascular network adapts to an increase in the local brain oxidative metabolism.

neuroscience↗

bioRxiv2018

Nested oscillatory dynamics in cortical organoids model early human brain network development

Structural and transcriptional changes during early brain maturation follow fixed developmental programs defined by genetics. However, whether this is true for functional network activity remains unknown, primarily due to experimental inaccessibility of the initial stages of the living human brain. Here, we developed cortical organoids that spontaneously display periodic and regular oscillatory network events that are dependent on glutamatergic and GABAergic signaling. These nested oscillations exhibit cross-frequency coupling, proposed to coordinate neuronal computation and communication. As evidence of potential network maturation, oscillatory activity subsequently transitioned to more spatiotemporally irregular patterns, capturing features observed in preterm human electroencephalography (EEG). These results show that the development of structured network activity in the human neocortex may follow stable genetic programming, even in the absence of external or subcortical inputs. Our approach provides novel opportunities for investigating and manipulating the role of network activity in the developing human cortex.\n\nHIGHLIGHTSO_LIEarly development of human functional neural networks and oscillatory activity can be modeled in vitro.\nC_LIO_LICortical organoids exhibit phase-amplitude coupling between delta oscillation (2 Hz) and high-frequency activity (100-400 Hz) during network-synchronous events.\nC_LIO_LIDifferential role of glutamate and GABA in initiating and maintaining oscillatory network activity.\nC_LIO_LIDevelopmental impairment of MECP2-KO cortical organoids impacts the emergence of oscillatory activity.\nC_LIO_LICortical organoid network electrophysiological signatures correlate with human preterm neonatal EEG features.\nC_LI\n\neTOCBrain oscillations are a candidate mechanism for how neural populations are temporally organized to instantiate cognition and behavior. Cortical organoids initially exhibit periodic and highly regular nested oscillatory network events that eventually transition to more spatiotemporally complex activity, capturing features of late-stage preterm infant electroencephalography. Functional neural circuitry in cortical organoids exhibits emergence and development of oscillatory network dynamics similar to those found in the developing human brain.

neuroscience↗