scholarly journals Decoding of cortex-wide brain activity from local recordings of neural potentials

2021 ◽  
Author(s):  
Xin Liu ◽  
Chi Ren ◽  
Zhisheng Huang ◽  
Madison Wilson ◽  
Jeong-Hoon Kim ◽  
...  
Keyword(s):  
Neural Activity ◽  
Large Scale ◽  
Neural Circuit ◽  
Brain Activity ◽  
Wide Field ◽  
Dorsal Cortex ◽  
Surface Potentials ◽  
Brain Surface ◽  
Neural Activities ◽  
Cortical Regions

Objective. Electrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain-computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions. Approach. To investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings. Main results. The mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials. Significance. These results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.

scholarly journals Miniaturized head-mounted device for whole cortex mesoscale imaging in freely behaving mice

2020 ◽  
Author(s):  
Mathew L Rynes ◽  
Daniel Surinach ◽  
Samantha Linn ◽  
Michael Laroque ◽  
Vijay Rajendran ◽  
...  
Keyword(s):  
Neural Activity ◽  
Glutamate Release ◽  
Wide Field ◽  
Dorsal Cortex ◽  
Perceptual Decision Making ◽  
Calcium Activity ◽  
Calcium Indicators ◽  
Stroboscopic Illumination ◽  
Freely Behaving ◽  
Sensory Evoked

ABSTRACTThe advent of genetically encoded calcium indicators, along with surgical preparations such as thinned skulls or refractive index matched skulls, have enabled mesoscale cortical activity imaging in head-fixed mice. Such imaging studies have revealed complex patterns of coordinated activity across the cortex during spontaneous behaviors, goal-directed behavior, locomotion, motor learning, and perceptual decision making. However, neural activity during unrestrained behavior significantly differs from neural activity in head-fixed animals. Whole-cortex imaging in freely behaving mice will enable the study of neural activity in a larger, more complex repertoire of behaviors not possible in head-fixed animals. Here we present the “Mesoscope,” a wide-field miniaturized, head-mounted fluorescence microscope compatible with transparent polymer skulls recently developed by our group. With a field of view of 8 mm x 10 mm and weighing less than 4 g, the Mesoscope can image most of the mouse dorsal cortex with resolution ranging from 39 to 56 µm. Stroboscopic illumination with blue and green LEDs allows for the measurement of both fluorescence changes due to calcium activity and reflectance signals to capture hemodynamic changes. We have used the Mesoscope to successfully record mesoscale calcium activity across the dorsal cortex during sensory-evoked stimuli, open field behaviors, and social interactions. Finally, combining the mesoscale imaging with electrophysiology enabled us to measure dynamics in extracellular glutamate release in the cortex during the transition from wakefulness to natural sleep.

scholarly journals Rapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior

2021 ◽  
Author(s):  
Hadas Benisty ◽  
Andrew H Moberly ◽  
Sweyta Lohani ◽  
Daniel Barson ◽  
Ronald R Coifman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Neural Activity ◽  
Large Scale ◽  
Analytical Framework ◽  
Network Activity ◽  
Wide Field ◽  
Time Varying ◽  
Cortical Networks ◽  
Novel Approach ◽  
Spontaneous Behavior

Experimental work across a variety of species has demonstrated that spontaneously generated behaviors are robustly coupled to variation in neural activity within the cerebral cortex. Indeed, functional magnetic resonance imaging (fMRI) data suggest that functional connectivity in cortical networks varies across distinct behavioral states, providing for the dynamic reorganization of patterned activity. However, these studies generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior typically observed in awake animals. Here, we took advantage of recent developments in wide-field, mesoscopic calcium imaging to monitor neural activity across the neocortex of awake mice. Applying a novel approach to quantifying time-varying functional connectivity, we show that spontaneous behaviors are more accurately represented by fast changes in the correlational structure versus the magnitude of large-scale network activity. Moreover, dynamic functional connectivity reveals subnetworks that are not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide insight into how behavioral information is represented across the mammalian neocortex and demonstrate a new analytical framework for investigating time-varying functional connectivity in neural networks.

scholarly journals Cortex-wide neural interfacing via transparent polymer skulls

2018 ◽  
Author(s):  
Leila Ghanbari ◽  
Russell E. Carter ◽  
Matthew L. Rynes ◽  
Judith Dominguez ◽  
Gang Chen ◽  
...  
Keyword(s):  
Neural Activity ◽  
Brain Regions ◽  
Two Photon ◽  
Neural Activities ◽  
Neural Computations ◽  
Brain Structure And Function ◽  
Cortical Regions ◽  
And Function ◽  
Subcellular Resolution

ABSTRACTNeural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating cognition, perception and sensorimotor behaviors. Enormous progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. To fill this need, we have engineered “See-Shells” – digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (>200 days) optical access to 45 mm2 of the dorsal cerebral cortex in the mouse. We demonstrate the ability to perform mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm through the See-Shells. See-Shells implanted on transgenic mice expressing genetically encoded calcium (Ca2+) indicators allow tracking of neural activities from multiple, non-contiguous regions spread across millimeters of the cortex. Further, neural probes can access the brain through perforated See-Shells, either for perturbing or recording neural activity from localized brain regions simultaneously with whole cortex imaging. As See-Shells can be constructed using readily available desktop fabrication tools and modified to fit a range of skull geometries, they provide a powerful tool for investigating brain structure and function.

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

Simulation of an anatomically defined local circuit: The cone-horizontal cell network in cat retina

1995 ◽  
Vol 12 (3) ◽  
pp. 545-561 ◽  
Author(s):  
Robert G. Smith
Keyword(s):  
Receptive Field ◽  
Large Scale ◽  
Neural Circuit ◽  
Horizontal Cell ◽  
Wide Field ◽  
Chemical Synapse ◽  
Gabaergic Synapse ◽  
Central Dome ◽  
Field Type ◽  
Optical Blur

AbstractThe outer plexiform layer of the retina contains a neural circuit in which cone synaptic terminals are electrically coupled and release glutamate onto wide-field and narrow-field horizontal cells. These are also electrically coupled and feed back through a GABAergic synapse to cones. In cat this circuit's structure is known in some detail, and much of the chemical architecture and neural responses are also known, yet there has been no attempt to synthesize this knowledge. We constructed a large-scale compartmental model (up to 50,000 compartments) to incorporate the known anatomical and biophysical facts. The goal was to discover how the various circuit components interact to form the cone receptive field, and thereby what possible function is implied. The simulation reproduced many features known from intracellular recordings: (1) linear response of cone and horizontal cell to intensity, (2) some aspects of temporal responses of cone and horizontal cell, (3) broad receptive field of the wide-field horizontal cell, and (4) center-surround cone receptive field (derived from a “deconvolution model"). With the network calibrated in this manner, we determined which of its features are necessary to give the cone receptive field a Gaussian center-surround shape. A Gaussian-like center that matches the center derived from the ganglion cell requires both optical blur and cone coupling: blur alone is too narrow, coupling alone gives an exponential shape without a central dome-shaped peak. A Gaussian-like surround requires both types of horizontal cell: the narrow-field type for the deep, proximal region and the wide-field type for the shallow, distal region. These results suggest that the function of the cone-horizontal cell circuit is to reduce the influence of noise by spatio-temporally filtering the cone signal before it passes through the first chemical synapse on the pathway to the brain.

scholarly journals The asynchronous state's relation to large-scale potentials in cortex

2019 ◽  
Vol 122 (6) ◽  
pp. 2206-2219 ◽  
Author(s):  
A. Alishbayli ◽  
J. G. Tichelaar ◽  
U. Gorska ◽  
M. X. Cohen ◽  
B. Englitz
Keyword(s):  
Firing Rate ◽  
Clinical Diagnosis ◽  
Neural Activity ◽  
Large Scale ◽  
Cortical Activity ◽  
Spike Count ◽  
Cortical Dynamics ◽  
Brain States ◽  
Asynchronous State ◽  
Cortical Regions

Understanding the relation between large-scale potentials (M/EEG) and their underlying neural activity can improve the precision of research and clinical diagnosis. Recent insights into cortical dynamics highlighted a state of strongly reduced spike count correlations, termed the asynchronous state (AS). The AS has received considerable attention from experimenters and theorists alike, regarding its implications for cortical dynamics and coding of information. However, how reconcilable are these vanishing correlations in the AS with large-scale potentials such as M/EEG observed in most experiments? Typically the latter are assumed to be based on underlying correlations in activity, in particular between subthreshold potentials. We survey the occurrence of the AS across brain states, regions, and layers and argue for a reconciliation of this seeming disparity: large-scale potentials are either observed, first, at transitions between cortical activity states, which entail transient changes in population firing rate, as well as during the AS, and, second, on the basis of sufficiently large, asynchronous populations that only need to exhibit weak correlations in activity. Cells with no or little spiking activity can contribute to large-scale potentials via their subthreshold currents, while they do not contribute to the estimation of spiking correlations, defining the AS. Furthermore, third, the AS occurs only within particular cortical regions and layers associated with the currently selected modality, allowing for correlations at other times and between other areas and layers.

scholarly journals Multiple timescales of sensory-evidence accumulation across the dorsal cortex

2020 ◽  
Author(s):  
Lucas Pinto ◽  
David W. Tank ◽  
Carlos D. Brody
Keyword(s):  
Virtual Reality ◽  
Large Scale ◽  
Temporal Integration ◽  
List Type ◽  
Dorsal Cortex ◽  
Evidence Accumulation ◽  
Cortical Areas ◽  
Sensory Evidence ◽  
Per Se ◽  
Cortical Regions

SUMMARYDecisions requiring the gradual accrual of sensory evidence appear to recruit widespread cortical areas. However, the nature of the contributions of different regions remains unclear. Here we trained mice to accumulate evidence over seconds while navigating in virtual reality, and optogenetically silenced the activity of many cortical areas during different brief trial epochs. We found that the inactivation of different areas primarily affected the evidence-accumulation computation per se, rather than other decision-related processes. Specifically, we observed selective changes in the weighting of evidence over time, such that frontal inactivations led to deficits on longer timescales than posterior cortical ones. Likewise, large-scale cortical Ca2+ activity during task performance displayed different temporal integration windows matching the effects of inactivation. Our findings suggest that distributed cortical areas accumulate evidence following their hierarchy of intrinsic timescales.HighlightsMice navigated in virtual reality while accumulating evidence over secondsWe briefly inactivated dorsal cortical regions at different points in the trialsInactivation of different regions resulted in accumulation deficits on distinct timescalesDorsal cortical regions displayed a hierarchy of activity timescales

scholarly journals Spatiotemporal structure of sensory-evoked and spontaneous activity revealed by mesoscale imaging in anesthetized and awake mice

2020 ◽  
Author(s):  
Navvab Afrashteh ◽  
Samsoon Inayat ◽  
Edgar Bermudez Contreras ◽  
Artur Luczak ◽  
Bruce L. McNaughton ◽  
...  
Keyword(s):  
Spontaneous Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Sensory Stimulation ◽  
Wide Field ◽  
Evoked Responses ◽  
Evoked Activity ◽  
Cortical Regions ◽  
The One ◽  
Sensory Evoked

AbstractBrain activity propagates across the cortex in diverse spatiotemporal patterns, both as a response to sensory stimulation and during spontaneous activity. Despite been extensively studied, the relationship between the characteristics of such patterns during spontaneous and evoked activity is not completely understood. To investigate this relationship, we compared visual, auditory, and tactile evoked activity patterns elicited with different stimulus strengths and spontaneous activity motifs in lightly anesthetized and awake mice using mesoscale wide-field voltage-sensitive dye and glutamate imaging respectively. The characteristics of cortical activity that we compared include amplitude, speed, direction, and complexity of propagation trajectories in spontaneous and evoked activity patterns. We found that the complexity of the propagation trajectories of spontaneous activity, quantified as their fractal dimension, is higher than the one from sensory evoked responses. Moreover, the speed and direction of propagation, are modulated by the amplitude during both, spontaneous and evoked activity. Finally, we found that spontaneous activity had similar amplitude and speed when compared to evoked activity elicited with low stimulus strengths. However, this similarity gradually decreased when the strength of stimuli eliciting evoked responses increased. Altogether, these findings are consistent with the fact that even primary sensory areas receive widespread inputs from other cortical regions, and that, during rest, the cortex tends to reactivate traces of complex, multi-sensory experiences that may have occurred in a range of different behavioural contexts.

scholarly journals Wide-Field Calcium Imaging of Dynamic Cortical Networks During Locomotion

2020 ◽  
Author(s):  
Sarah L. West ◽  
Justin Aronson ◽  
Laurentiu S. Popa ◽  
Russell E. Carter ◽  
Aditya Shekhar ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Functional Connectivity ◽  
Premotor Cortex ◽  
Brain Regions ◽  
Wide Field ◽  
Dorsal Cortex ◽  
Eigenvector Centrality ◽  
Functional Interactions ◽  
Cortical Regions ◽  
Premotor Areas

ABSTRACTBehavior results in widespread activation of the cerebral cortex. To fully understanding the cerebral cortex’s role in behavior therefore requires a mesoscopic level description of the cortical regions engaged and their functional interactions. Mesoscopic imaging of Ca2+ fluorescence through transparent polymer skulls implanted on transgenic Thy1-GCaMP6f mice reveals widespread activation of the cerebral cortex during locomotion, including not just primary motor and somatosensory regions but also premotor, auditory, retrosplenial, and visual cortices. To understand these patterns of activation, we used spatial Independent Component Analysis (sICA) that segmented the dorsal cortex of individual mice into 20-22 Independent Components (ICs). The resulting ICs are highly consistent across imaging sessions and animals. Using the time series of Ca2+ fluorescence in each IC, we examined the changes in functional connectivity from rest to locomotion. Compared to rest, functional connectivity increases prior to and at the onset of locomotion. During continued walking, a global decrease in functional connectivity develops compared to rest that uncovers a distinct, sparser network in which ICs in secondary motor areas increase their correlations with more posterior ICs in somatosensory, motor, visual, and retrosplenial cortices. Eigenvector centrality analysis demonstrates that ICs located in premotor areas increase their influence on the network during locomotion while ICs in other regions, including somatosensory and primary motor, decrease in importance. We observed sequential changes in functional connectivity across transitions between rest and locomotion, with premotor areas playing an important role in coordination of computations across cortical brain regions.SIGNIFICANCEBehavior such as locomotion requires the coordination of multiple cerebral cortical regions to accurately navigate the external environment. However, it is unclear how computations from various regions are integrated to produce a single, coherent behavioral output. Here, wide-field, epifluorescence Ca2+ imaging across the dorsal cerebral cortex reveals the changing functional interactions among cortical regions during the transition from rest to locomotion. While functional connectivity among most cortical nodes primarily decreases from rest to locomotion, a well-defined network of increased correlations emerges between premotor and other cortical regions with an increase in the importance of the premotor cortex to the network. The results suggest that the role of the premotor areas in locomotion involves coordinating interactions among different cortical regions.

scholarly journals From Neurons to Cognition: Technologies for Precise Recording of Neural Activity Underlying Behavior

BME Frontiers ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Richard H. Roth ◽  
Jun B. Ding
Keyword(s):  
Neuronal Activity ◽  
Neural Activity ◽  
Large Scale ◽  
Technological Development ◽  
Brain Activity ◽  
Complex Problem ◽  
Machine Learning Algorithms ◽  
Current State ◽  
Electrophysiological Methods

Understanding how brain activity encodes information and controls behavior is a long-standing question in neuroscience. This complex problem requires converging efforts from neuroscience and engineering, including technological solutions to perform high-precision and large-scale recordings of neuronal activity in vivo as well as unbiased methods to reliably measure and quantify behavior. Thanks to advances in genetics, molecular biology, engineering, and neuroscience, in recent decades, a variety of optical imaging and electrophysiological approaches for recording neuronal activity in awake animals have been developed and widely applied in the field. Moreover, sophisticated computer vision and machine learning algorithms have been developed to analyze animal behavior. In this review, we provide an overview of the current state of technology for neuronal recordings with a focus on optical and electrophysiological methods in rodents. In addition, we discuss areas that future technological development will need to cover in order to further our understanding of the neural activity underlying behavior.

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