temporal resolution

Multi-modal Micro Electrode Fluidic Array (MEFA) Shells for Brain Organoids

Abstract Brain organoids (BOs) derived from human stem cells bridge the gap between monolayer cell culture studies and animal models, which have well-documented limitations. Monolayer cell culture models fail to accurately replicate the 3D interconnectivity in the brain; animal models, while helpful, are limited due to interspecies differences, with most research focusing on rather phenotypical rather than mechanistic aspects. Concurrent with the advancement of BO models is the urgent need to develop 3D micro instrumentation supporting these organoids to investigate brain development and disease in their accurate physiological environment. Conventional microelectrode arrays (MEAs) used for neuronal cell culture studies are planar, which limits recording access to a small fraction of cells on the bottom side of the organoid. Also, conventional microfluidics is inherently planar, and while recent advances in 3D MEAs and 3D microfluidics have enabled electrical and chemical interrogation in 3D, combining both features with tunability and precision to allow independent and simultaneous control is challenging. Recently, we reported new 3D micro instrumentation in the form of 3D shell MEAs and demonstrated its applicability for electrical recording from BOs. They feature lithographically patterned and chip-integrated electrodes and self-folding polymer shells that can be triggered to wrap around BOs to measure electrical activity from the entire organoid surface. The 3D MEA shell system is modeled on and resembles a miniaturized electroencephalography (EEG) cap; the process used to make them is size-scalable, chip-integrated, and mass- producible. In the research, we aim to develop and validate 3D Micro Electrode Fluidic Array (MEFA) shells with multi-modal electrical recording and biochemical control capabilities, offering high spatiotemporal resolution, tunability, and scalability. Since 3D spatiotemporal patterns of neurochemicals play a critical role in molecular and cellular events of neural development and disease, we propose to apply and validate the MEFA shells in two studies that mimic neurodevelopment and monitor the spatiotemporal effects in neurological disorders and their treatments in vitro. We anticipate that the proposed 3D MEFAs would revolutionize brain sciences by permitting real-time, in-situ studies of electrical and chemical stimulation and interrogation of BOs in a high- throughput manner. The proposed 3D scalable, reproducible, and tunable 3D micro instrumentation for BOs has broad relevance to understanding brain development in utero and the development of anatomically accurate drug and toxicity screening platforms for brain sciences and neurological disorders.

Magnetic resonance true temperature imaging with high spatial and temporal resolution

ABSTRACT The knowledge of temperature and temperature distribution within the brain can be critical to understanding the healthy and diseased brain, its response to acute injury, and in monitoring critically important thermal interventions. There are several temperature sensitive properties such relaxation rates and the proton resonance frequency shift (PRFS) that can be measured with magnetic resonance imaging (MRI) methods but these methods can only measure temperature change. The PRFS method, which provides the most accurate measurement of temperature change can only measure true tissue temperature if the starting true temperature distribution is known. Fortunately, MR spectroscopy (MRS) methods have been developed that show great promise in the measurement of true temperature. These methods rely on the detection of a temperature independent spectral peak of protons bound to carbon atoms in high concentration metabolites, such as N- acetylaspartate (NAA), creatine (Cr) and choline (Cho) which can be used as a reference for the temperature dependent spectral peak of water protons. Both single voxel spectroscopy (SVS) methods and MRS imaging (MRSI) methods have been described but are slow because of the long readout time needed to achieve adequate spectral resolution and the need to perform multiple averages due to the low signal being measured. Echo-planar spectroscopic imaging (EPSI) speeds up MRSI by interleaving an oscillating imaging gradient to spatially encode one of the imaging dimensions simultaneously with spectral readout. Unfortunately, SVS, MRSI, and even EPSI are unsuitable for clinical applications because of the low spatial resolution (voxel size 1 cm3) and temporal resolution (multiple minutes). The goal of this project is to develop an MRI technique that can measure true temperature in the whole brain at spatial and temporal resolutions that enable clinical utility for acutely assessing and longitudinally monitoring healthy and diseased brain tissue, and real time monitoring of thermal interventional therapies. This innovative true temperature measurement technique combines EPSI, for low resolution background field measurements, with PRFS for high spatial and temporal resolution water proton measurements. While conventional EPSI methods interleave volumetric acquisitions with and without water suppression, we propose an innovative modification to take advantage of the very strong water signal to obtain a very high resolution, dynamic method for true temperature measurements. The MRI pulse sequence will be refined, validated (Aim 1), applied to healthy subjects and post-surgery patients at risk for infections (Aim 2), and applied to essential tremor (ET) patients during the required delay between repeated focused ultrasound sonications (Aim 3). Successful completion of the aims of this study will result in a clinically practical method to obtain true temperature measurements in the brain with a spatial and temporal resolution sufficiently high to meet the needs of monitoring focal thermal therapy treatments as well as to provide true temperature measurements over the entire brain for assessment of the state of the brain with disease, infection, and injury.

Trends in NeuroAI - Meta's MEG-to-image reconstruction

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). This will be an informal journal club presentation, we do not have an author of the paper joining us. Title: Brain decoding: toward real-time reconstruction of visual perception Abstract: In the past five years, the use of generative and foundational AI systems has greatly improved the decoding of brain activity. Visual perception, in particular, can now be decoded from functional Magnetic Resonance Imaging (fMRI) with remarkable fidelity. This neuroimaging technique, however, suffers from a limited temporal resolution (≈0.5 Hz) and thus fundamentally constrains its real-time usage. Here, we propose an alternative approach based on magnetoencephalography (MEG), a neuroimaging device capable of measuring brain activity with high temporal resolution (≈5,000 Hz). For this, we develop an MEG decoding model trained with both contrastive and regression objectives and consisting of three modules: i) pretrained embeddings obtained from the image, ii) an MEG module trained end-to-end and iii) a pretrained image generator. Our results are threefold: Firstly, our MEG decoder shows a 7X improvement of image-retrieval over classic linear decoders. Second, late brain responses to images are best decoded with DINOv2, a recent foundational image model. Third, image retrievals and generations both suggest that MEG signals primarily contain high-level visual features, whereas the same approach applied to 7T fMRI also recovers low-level features. Overall, these results provide an important step towards the decoding - in real time - of the visual processes continuously unfolding within the human brain. Speaker: Dr. Paul Scotti (Stability AI, MedARC) Paper link: https://arxiv.org/abs/2310.19812

In vivo direct imaging of neuronal activity at high temporospatial resolution

Advanced noninvasive neuroimaging methods provide valuable information on the brain function, but they have obvious pros and cons in terms of temporal and spatial resolution. Functional magnetic resonance imaging (fMRI) using blood-oxygenation-level-dependent (BOLD) effect provides good spatial resolution in the order of millimeters, but has a poor temporal resolution in the order of seconds due to slow hemodynamic responses to neuronal activation, providing indirect information on neuronal activity. In contrast, electroencephalography (EEG) and magnetoencephalography (MEG) provide excellent temporal resolution in the millisecond range, but spatial information is limited to centimeter scales. Therefore, there has been a longstanding demand for noninvasive brain imaging methods capable of detecting neuronal activity at both high temporal and spatial resolution. In this talk, I will introduce a novel approach that enables Direct Imaging of Neuronal Activity (DIANA) using MRI that can dynamically image neuronal spiking activity in milliseconds precision, achieved by data acquisition scheme of rapid 2D line scan synchronized with periodically applied functional stimuli. DIANA was demonstrated through in vivo mouse brain imaging on a 9.4T animal scanner during electrical whisker-pad stimulation. DIANA with milliseconds temporal resolution had high correlations with neuronal spike activities, which could also be applied in capturing the sequential propagation of neuronal activity along the thalamocortical pathway of brain networks. In terms of the contrast mechanism, DIANA was almost unaffected by hemodynamic responses, but was subject to changes in membrane potential-associated tissue relaxation times such as T2 relaxation time. DIANA is expected to break new ground in brain science by providing an in-depth understanding of the hierarchical functional organization of the brain, including the spatiotemporal dynamics of neural networks.

Versatile treadmill system for measuring locomotion and neural activity in head-fixed mice

Here, we present a protocol for using a versatile treadmill system to measure locomotion and neural activity at high temporal resolution in head-fixed mice. We first describe the assembly of the treadmill system. We then detail surgical implantation of the headplate on the mouse skull, followed by habituation of mice to locomotion on the treadmill system. The system is compact, movable, and simple to synchronize with other data streams, making it ideal for monitoring brain activity in diverse behavioral frameworks. https://dx.doi.org/10.1016/j.xpro.2022.101701

Time as its own representation? Exploring a link between timing of cognition and time perception

The way we represent and perceive time has crucial implications for studying temporality in conscious experience. Contrasting positions posit that temporal information is separately abstracted out like any other perceptual property, or that time is represented through representations having temporal properties themselves. To add to this debate, we investigated alterations in felt time in conditions where only conscious visual experience is altered while a bistable figure remains physically unchanged. In this talk, I will discuss two studies that we have done in relation to answering this question. In study 1, we investigated whether perceptual switches in fixed intervals altered felt time. In three experiments we showed that a break in visual experience (via a perceptual switch) also leads to a break in felt time. In study 2, we are currently looking at figure-ground perception in ambigous displays. Here, in experiment 1 we show that differences in flicker frequencies on ambigous regions can induce figure-ground segregation. To see if a reverse complementarity exists for felt time, we ask participants to view ambigous regions as figure/ground and show that they have different temporal resolutions for the same region based on whether it is seen as figure or background. Overall, the two studies provide evidence for temporal mirroring and isomorphism in visual experience, arguing for a link between the timing of experience and time perception.

Functional ultrasound imaging during behavior

The dream of a systems neuroscientist is to be able to unravel neural mechanisms that give rise to behavior. It is increasingly appreciated that behavior involves the concerted distributed activity of multiple brain regions so the focus on single or few brain areas might hinder our understanding. There have been quite a few technological advancements in this domain. Functional ultrasound imaging (fUSi) is an emerging technique that allows us to measure neural activity from medial frontal regions down to subcortical structures up to a depth of 20 mm. It is a method for imaging transient changes in cerebral blood volume (CBV), which are proportional to neural activity changes. It has excellent spatial resolution (~100 μm X 100 μm X 400 μm); its temporal resolution can go down to 100 milliseconds. In this talk, I will present its use in two model systems: marmoset monkeys and rats. In marmoset monkeys, we used it to delineate a social – vocal network involved in vocal communication while in rats, we used it to gain insights into brain wide networks involved in evidence accumulation based decision making. fUSi has the potential to provide an unprecedented access to brain wide dynamics in freely moving animals performing complex behavioral tasks.

Interpreting the Mechanisms and Meaning of Sensorimotor Beta Rhythms with the Human Neocortical Neurosolver (HNN) Neural Modeling Software

Electro- and magneto-encephalography (EEG/MEG) are the leading methods to non-invasively record human neural dynamics with millisecond temporal resolution. However, it can be extremely difficult to infer the underlying cellular and circuit level origins of these macro-scale signals without simultaneous invasive recordings. This limits the translation of E/MEG into novel principles of information processing, or into new treatment modalities for neural pathologies. To address this need, we developed the Human Neocortical Neurosolver (HNN: https://hnn.brown/edu ), a new user-friendly neural modeling tool designed to help researchers and clinicians interpret human imaging data. A unique feature of HNN’s model is that it accounts for the biophysics generating the primary electric currents underlying such data, so simulation results are directly comparable to source localized data. HNN is being constructed with workflows of use to study some of the most commonly measured E/MEG signals including event related potentials, and low frequency brain rhythms. In this talk, I will give an overview of this new tool and describe an application to study the origin and meaning of 15-29Hz beta frequency oscillations, known to be important for sensory and motor function. Our data showed that in primary somatosensory cortex these oscillations emerge as transient high power ‘events’. Functionally relevant differences in averaged power reflected a difference in the number of high-power beta events per trial (“rate”), as opposed to changes in event amplitude or duration. These findings were consistent across detection and attention tasks in human MEG, and in local field potentials from mice performing a detection task. HNN modeling led to a new theory on the circuit origin of such beta events and suggested beta causally impacts perception through layer specific recruitment of cortical inhibition, with support from invasive recordings in animal models and high-resolution MEG in humans. In total, HNN provides an unpresented biophysically principled tool to link mechanism to meaning of human E/MEG signals.

Does temporal predictability enhance auditory temporal resolution ? Behavioral results from a gap detection paradigm

Somatosensory evoked BOLD signals with ultra-high temporal resolution

FENS Forum 2024