scholarly journals A qualitative model of the rod photoreceptor in natural context

2016 ◽  
Author(s):  
Timothée T. Dubuc ◽  
Etienne B. Roesch
Keyword(s):  
Large Scale ◽  
Neural Circuit ◽  
Temporal Dynamics ◽  
Continuous Model ◽  
Retinal Function ◽  
Sensitivity Analyses ◽  
Qualitative Behavior ◽  
Rod Photoreceptor ◽  
The Brain

AbstractGiven the intricacies of the retinal neural circuit, which bears a striking resemblance to that of the brain, it is proposed that retinal function goes beyond mere spatiotemporal prefiltering. We hypothesise that aspects related to motion detection and discrimination, anticipation and adaptation to environmental and contextual conditions, which have traditionally been ascribed to the brain, may be supported by neurons in the retina. Such early computations may be dependent on compensative and adaptive mechanisms that stem from qualities intrinsic to the retinal neural circuit and its interaction with the environment (neural transduction time, connectivity patterns, regularities in the input signal, temporal dynamics and light variations).With a view to investigating the contribution of the photoreceptor population to the processing performed by the retina in natural scotopic conditions, we present a continuous model of the rod photoreceptor. Our model permits the reproduction and exploration of a set of qualitative features displayed in vitro, such as excitation-dependent activation level and time-to-membrane current integration. We captured qualitative aspects of key features selected for their presumed importance in early visual function. Further, we subjected our model to extensive parameter sensitivity analyses, aiming to provide a visual representation of their contribution to the observed qualitative behavior.Author SummaryPrimate rod photoreceptor cells constitute the very first processing step in retinal function. This layer influences most of the visual field and presents itself as a tightly packed photosensitive array. Yet, no computational formulation of this neuron is suited for large-scale, time continuous modeling. With a view to studying retinal function in natural contexts, we describe a qualitative, continuous model of the rod. We subject this model to parameter analyses against selected behavioral features. We aim to provide a model that can integrate in further experiments, as well as in large scale network simulation.

scholarly journals Brain network dynamics are hierarchically organized in time

2017 ◽  
Vol 114 (48) ◽  
pp. 12827-12832 ◽  
Author(s):  
Diego Vidaurre ◽  
Stephen M. Smith ◽  
Mark W. Woolrich
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Network ◽  
Specific Measure ◽  
Brain Areas ◽  
Neuronal Populations ◽  
Subject Specific ◽  
Large Scale Networks ◽  
Network Patterns ◽  
The Brain

The brain recruits neuronal populations in a temporally coordinated manner in task and at rest. However, the extent to which large-scale networks exhibit their own organized temporal dynamics is unclear. We use an approach designed to find repeating network patterns in whole-brain resting fMRI data, where networks are defined as graphs of interacting brain areas. We find that the transitions between networks are nonrandom, with certain networks more likely to occur after others. Further, this nonrandom sequencing is itself hierarchically organized, revealing two distinct sets of networks, or metastates, that the brain has a tendency to cycle within. One metastate is associated with sensory and motor regions, and the other involves areas related to higher order cognition. Moreover, we find that the proportion of time that a subject spends in each brain network and metastate is a consistent subject-specific measure, is heritable, and shows a significant relationship with cognitive traits.

Temporal Processing by Intrinsic Neural Network Dynamics

2016 ◽  
Vol 4 (4) ◽  
pp. 399-410 ◽  
Author(s):  
Elijah A. Petter ◽  
Hugo Merchant
Keyword(s):  
Temporal Processing ◽  
Temporal Dynamics ◽  
Brain Structures ◽  
Temporal Perception ◽  
Neural Network Dynamics ◽  
Central Clock ◽  
Cortical Regions ◽  
Local Circuits ◽  
The Brain

It is becoming more apparent that there are rich contributions to temporal processing across the brain. Temporal dynamics have been found from lower brain structures all the way to cortical regions. Specifically,in vitrocortical preparations have been extremely useful in understanding how local circuits can time. While many of these results depict vastly different processing than a traditional central clock metaphor they still leave questions as to how this information is integrated. We therefore review evidence to place the results pertaining to local circuit timers into the larger context of temporal perception and generalization.

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.

scholarly journals Impairments of neural circuit function in Alzheimer's disease

2016 ◽  
Vol 371 (1700) ◽  
pp. 20150429 ◽  
Author(s):  
Marc Aurel Busche ◽  
Arthur Konnerth
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Hippocampal Neurons ◽  
Large Scale ◽  
Neural Circuit ◽  
Essential Feature ◽  
Amyloid Β ◽  
Amyloid Plaque ◽  
Aβ Oligomers ◽  
The Brain

An essential feature of Alzheimer's disease (AD) is the accumulation of amyloid-β (Aβ) peptides in the brain, many years to decades before the onset of overt cognitive symptoms. We suggest that during this very extended early phase of the disease, soluble Aβ oligomers and amyloid plaques alter the function of local neuronal circuits and large-scale networks by disrupting the balance of synaptic excitation and inhibition ( E / I balance) in the brain. The analysis of mouse models of AD revealed that an Aβ-induced change of the E / I balance caused hyperactivity in cortical and hippocampal neurons, a breakdown of slow-wave oscillations, as well as network hypersynchrony. Remarkably, hyperactivity of hippocampal neurons precedes amyloid plaque formation, suggesting that hyperactivity is one of the earliest dysfunctions in the pathophysiological cascade initiated by abnormal Aβ accumulation. Therapeutics that correct the E / I balance in early AD may prevent neuronal dysfunction, widespread cell loss and cognitive impairments associated with later stages of the disease. This article is part of the themed issue ‘Evolution brings Ca 2+ and ATP together to control life and death’.

scholarly journals Cerebral cartography and connectomics

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140173 ◽  
Author(s):  
Olaf Sporns
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Network Science ◽  
Temporal Dynamics ◽  
Functional Organization ◽  
Brain Connectivity ◽  
Hierarchical Organization ◽  
Large Scale Networks ◽  
Definition Of ◽  
The Brain

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics.

scholarly journals Investigation of Copper, Zinc and Strontium Doping on Electrochemical Properties of Titanium Dioxide Nanotubes for In Vitro Neural Recording

2021 ◽  
Author(s):  
Dhurgham Khudhair ◽  
Julie Gaburro ◽  
Hoda Amani Hamedani ◽  
Anders Barlow ◽  
Hamid Garmestai ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Natural Habitat ◽  
Direct Interaction ◽  
Biological Properties ◽  
Biologically Active ◽  
Nanotube Arrays ◽  
Metallic Ions ◽  
The Brain

Direct interaction with the neuronal cells is a prerequisite to deciphering useful information in understanding the underlying causes of diseases and functional abnormalities in the brain. Precisely fabricated nanoelectrodes provide the capability to interact with the brain in its natural habitat without compromising its functional integrity. Considerable research has been focused on the employment of vertical nanotubes as nanoelectrodes due to large-scale intracellular recording capability and longer-term intracellular access that arise from their unique geometry. Despite many types of nanotube structures reported in the literature, a limited subset of the nanotubes has been investigated for neural interfacing. This work reports on the fabrication and optimisation of vertically oriented titania nanotube arrays as a scalable electrode platform for neural interface application. To this end, the doping was performed by incorporating a selected group of biologically active metallic ions, including zinc, strontium, and copper, into TiO2 lattice and its effect was studied with respect to the structural, electrochemical and biological properties of the nanotube arrays. It was found that doping can change the length, diameter and wall thickness of the nanotubes. Among pure and doped samples, the copper-doped TiO2 nanotubes demonstrated the highest electrochemical and biological performance. Our results suggest that the doping can be used as a promising method to optimise the properties of nanotube arrays for the development of high-performance neural electrodes.

scholarly journals Temporal dynamics of neural activity in macaque frontal cortex assessed with large-scale recordings

2020 ◽  
Author(s):  
Thomas Decramer ◽  
Elsie Premereur ◽  
Irene Caprara ◽  
Tom Theys ◽  
Peter Janssen
Keyword(s):  
Frontal Cortex ◽  
Large Scale ◽  
Primary Motor Cortex ◽  
Temporal Dynamics ◽  
Peripheral Vision ◽  
Premotor Cortex ◽  
Hand Movement ◽  
The Gaze ◽  
Hand Coordination ◽  
The Brain

AbstractWe make eye movements to objects before grasping these objects, and the gaze direction generally indicates where the object will be grasped. Hence, the brain has to coordinate eye-, arm- and hand movements. We performed large-scale recordings (more than 2000 responsive sites) in frontal cortex of monkeys during a saccade-reach-grasp task. When an object appeared in peripheral vision, the first burst of activity emerged in prearcuate areas (the FEF and area 45B), followed by dorsal and ventral premotor cortex, and a buildup of activity in primary motor cortex. After the saccade, prearcuate activity remained elevated while primary motor and premotor activity rose in anticipation of the upcoming arm and hand movement. Some premotor and prearcuate sites were equally active when the object appeared in peripheral vision and at the fovea, suggesting a role in eye-hand coordination. Thus, a large part of lateral frontal cortex is active during a saccade-reach-grasp task.

scholarly journals Intersubject brain connectivity dynamics encode the stream of affect at multiple timescales

2020 ◽  
Author(s):  
Giada Lettieri ◽  
Giacomo Handjaras ◽  
Emiliano Ricciardi ◽  
Pietro Pietrini ◽  
Luca Cecchetti
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Connectivity ◽  
Multiple Timescales ◽  
Control Networks ◽  
Past Experiences ◽  
And Control ◽  
The Relationship ◽  
The Brain ◽  
Connectivity Strength

AbstractThe stream of affect is the result of a constant interaction between past experiences, motivations, expectations and the unfolding of events. How the brain represents the relationship between time and affect has been hardly explored, as it requires modeling the complexity of everyday life in the laboratory. Movies condense into hours a multitude of emotional responses, synchronized across subjects and characterized by temporal dynamics alike real-world experiences.Here, using naturalistic stimulation, time-varying intersubject brain connectivity and behavioral reports, we demonstrate that connectivity strength of large-scale brain networks tracks changes in affect. The default mode network represents the pleasantness of the experience, whereas attention and control networks encode its intensity. Interestingly, these orthogonal descriptions of affect converge in right temporoparietal and fronto-polar cortex. Within these regions, the stream of affect is represented at multiple timescales by chronotopic maps, where connectivity of adjacent areas preferentially maps experiences in 3- to 11-minute segments.

scholarly journals Modelling the impact of clot fragmentation on the microcirculation after thrombectomy

2020 ◽  
Author(s):  
Wahbi K. El-Bouri ◽  
Andrew MacGowan ◽  
Tamás I. Józsa ◽  
Matthew J. Gounis ◽  
Stephen J. Payne
Keyword(s):  
Blood Flow ◽  
Ischaemic Stroke ◽  
Computational Model ◽  
In Silico ◽  
Large Scale ◽  
In Vitro Experiments ◽  
Mechanical Removal ◽  
The Impact ◽  
The Brain

1AbstractMany ischaemic stroke patients who have a mechanical removal of their clot (thrombectomy) do not get reperfusion of tissue despite the thrombus being removed. One hypothesis for this ‘no-reperfusion’ phenomenon is micro-emboli fragmenting off the large clot during thrombectomy and occluding smaller blood vessels downstream of the clot location. This is impossible to observe in-vivo and so we here develop an in-silico model based on in-vitro experiments to model the effect of micro-emboli on brain tissue. Through in-vitro experiments we obtain, under a variety of clot consistencies and thrombectomy techniques, micro-emboli distributions post-thrombectomy. Blood flow through the microcirculation is modelled for statistically accurate voxels of brain microvasculature including penetrating arterioles and capillary beds. A novel micro-emboli algorithm, informed by the experimental data, is used to simulate the impact of micro-emboli successively entering the penetrating arterioles and the capillary bed. Scaled-up blood flow parameters – permeability and coupling coefficients – are calculated under various conditions. We find that capillary beds are more susceptible to occlusions than the penetrating arterioles with a 4x greater drop in permeability per volume of vessel occluded. Individual microvascular geometries determine robustness to micro-emboli. Hard clot fragmentation leads to larger micro-emboli and larger drops in blood flow for a given number of micro-emboli. Thrombectomy technique has a large impact on clot fragmentation and hence occlusions in the microvasculature. As such, in-silico modelling of mechanical thrombectomy predicts that clot specific factors, interventional technique, and microvascular geometry strongly influence reperfusion of the brain. Micro-emboli are likely contributory to the phenomenon of no-reperfusion following successful removal of a major clot.2Author summaryAfter an ischaemic stroke - one where a clot blocks a major artery in the brain - patients can undergo a procedure where the clot is removed mechanically with a stent - a thrombectomy. This reopens the blocked vessel, yet some patients don’t achieve blood flow returning to their tissue downstream. One hypothesis for this phenomenon is that the clot fragments into smaller clots (called micro-emboli) which block smaller vessels downstream. However, this can’t be measured in patients due to the inability of clinical imaging resolving the micro-scale. We therefore develop a computational model here, based on experimental thrombectomy data, to quantify the impact of micro-emboli on blood flow in the brain after the removal of a clot. With this model, we found that micro-emboli are a likely contributor to the no-reflow phenomenon after a thrombectomy. Individual blood vessel geometries, clot composition, and thrombectomy technique all impacted the effect of micro-emboli on blood flow and should be taken into consideration to minimise the impact of micro-emboli in the brain. Furthermore, the computational model developed here allows us to now build large-scale models of blood flow in the brain, and hence simulate stroke and the impact of micro-emboli on the entire brain.

scholarly journals New Modalities of 3D Pluripotent Stem Cell-Based Assays in Cardiovascular Toxicity

2021 ◽  
Vol 12 ◽  
Author(s):  
Barbara Orsolits ◽  
Zsófia Kovács ◽  
János Kriston-Vizi ◽  
Béla Merkely ◽  
Gábor Földes
Keyword(s):  
Stem Cell ◽  
Pluripotent Stem Cell ◽  
Large Scale ◽  
Disease Modeling ◽  
Temporal Dynamics ◽  
3D Culture ◽  
Induced Pluripotent Stem Cell ◽  
Culture Techniques ◽  
Cellular Environment

The substantial progress of the human induced pluripotent stem cell (hiPSC) technologies over the last decade has provided us with new opportunities for cardiovascular drug discovery, regenerative medicine, and disease modeling. The combination of hiPSC with 3D culture techniques offers numerous advantages for generating and studying physiological and pathophysiological cardiac models. Cells grown in 3D can overcome many limitations of 2D cell cultures and animal models. Furthermore, it enables the investigation in an architecturally appropriate, complex cellular environment in vitro. Yet, generation and study of cardiac organoids—which may contain versatile cardiovascular cell types differentiated from hiPSC—remain a challenge. The large-scale and high-throughput applications require accurate and standardised models with highly automated processes in culturing, imaging and data collection. Besides the compound spatial structure of organoids, their biological processes also possess different temporal dynamics which require other methods and technologies to detect them. In this review, we summarise the possibilities and challenges of acquiring relevant information from 3D cardiovascular models. We focus on the opportunities during different time-scale processes in dynamic pharmacological experiments and discuss the putative steps toward one-size-fits-all assays.

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