scholarly journals A Connectome-Based, Corticothalamic Model of State- and Stimulation-Dependent Modulation of Rhythmic Neural Activity and Connectivity

2020 ◽  
Vol 14 ◽  
Author(s):  
John D. Griffiths ◽  
Anthony Randal McIntosh ◽  
Jeremie Lefebvre
Keyword(s):  
Functional Connectivity ◽  
Brain Stimulation ◽  
Neural Circuit ◽  
Spatial Scales ◽  
Oscillatory Activity ◽  
Neural Mass Model ◽  
Cognitive State ◽  
Mass Model ◽  
Brain Connectome ◽  
The Impact

Rhythmic activity in the brain fluctuates with behaviour and cognitive state, through a combination of coexisting and interacting frequencies. At large spatial scales such as those studied in human M/EEG, measured oscillatory dynamics are believed to arise primarily from a combination of cortical (intracolumnar) and corticothalamic rhythmogenic mechanisms. Whilst considerable progress has been made in characterizing these two types of neural circuit separately, relatively little work has been done that attempts to unify them into a single consistent picture. This is the aim of the present paper. We present and examine a whole-brain, connectome-based neural mass model with detailed long-range cortico-cortical connectivity and strong, recurrent corticothalamic circuitry. This system reproduces a variety of known features of human M/EEG recordings, including spectral peaks at canonical frequencies, and functional connectivity structure that is shaped by the underlying anatomical connectivity. Importantly, our model is able to capture state- (e.g., idling/active) dependent fluctuations in oscillatory activity and the coexistence of multiple oscillatory phenomena, as well as frequency-specific modulation of functional connectivity. We find that increasing the level of sensory drive to the thalamus triggers a suppression of the dominant low frequency rhythms generated by corticothalamic loops, and subsequent disinhibition of higher frequency endogenous rhythmic behaviour of intracolumnar microcircuits. These combine to yield simultaneous decreases in lower frequency and increases in higher frequency components of the M/EEG power spectrum during states of high sensory or cognitive drive. Building on this, we also explored the effect of pulsatile brain stimulation on ongoing oscillatory activity, and evaluated the impact of coexistent frequencies and state-dependent fluctuations on the response of cortical networks. Our results provide new insight into the role played by cortical and corticothalamic circuits in shaping intrinsic brain rhythms, and suggest new directions for brain stimulation therapies aimed at state-and frequency-specific control of oscillatory brain activity.

scholarly journals A connectome-based, corticothalamic model of state- and stimulation-dependent modulation of rhythmic neural activity and connectivity

2019 ◽  
Author(s):  
John D Griffiths ◽  
Anthony Randal McIntosh ◽  
Jeremie Lefebvre
Keyword(s):  
Functional Connectivity ◽  
Brain Stimulation ◽  
Brain Activity ◽  
Low Frequency ◽  
Rhythmic Activity ◽  
Clinical Applications ◽  
Oscillatory Activity ◽  
Neural Mass Model ◽  
Brain Connectome ◽  
The Impact

AbstractRhythmic activity in the brain fluctuates with behaviour and cognitive state, through a combination of coexisting and interacting frequencies. At large spatial scales such as those studied in human M/EEG, measured oscillatory dynamics are believed to arise primarily from a combination of cortical (intracolumnar) and corticothalamic rhythmogenic mechanisms. Whilst considerable progress has been made in characterizing these two types of neural circuit separately, relatively little work has been done that attempts to unify them into a single consistent picture. This is the aim of the present paper. We present and examine a whole-brain, connectome-based neural mass model with detailed long-range cortico-cortical connectivity and strong, recurrent corticothalamic circuitry. This system reproduces a variety of known features of human M/EEG recordings, including a 1/f spectral profile, spectral peaks at canonical frequencies, and functional connectivity structure that is shaped by the underlying anatomical connectivity. Importantly, our model is able to capture state-(e.g. idling/active) dependent fluctuations in oscillatory activity and the coexistence of multiple oscillatory phenomena, as well as frequency-specific modulation of functional connectivity. We find that increasing the level of sensory or neuromodulatory drive to the thalamus triggers a suppression of the dominant low frequency rhythms generated by corticothalamic loops, and subsequent disinhibition of higher frequency endogenous rhythmic behaviour of intra-columnar microcircuits. These combine to yield simultaneous decreases in lower frequency and increases in higher frequency components of the M/EEG power spectrum during states of high sensory or cognitive drive. Building on this, we also explored the effect of pulsatile brain stimulation on ongoing oscillatory activity, and evaluated the impact of coexistent frequencies and state-dependent fluctuations on the response of cortical networks. Our results provide new insight into the role played by cortical and corticothalamic circuits in shaping intrinsic brain rhythms, and suggest new directions for brain stimulation therapies aimed at state-and frequency-specific control of oscillatory brain activity.Author SummaryOne of the most distinctive features of brain activity is that it is highly rhythmic. Developing a better understanding of how these rhythms are generated, and how they can be controlled in clinical applications, is a central goal of modern neuroscience. Here we have developed a computational model that succinctly captures several key aspects of the rhythmic brain activity most easily measurable in human subjects. In particular, it provides both a conceptual and a concrete mathematical framework for understanding the well-established experimental observation of antagonism between high- and low-frequency oscillations in human brain recordings. This dynamic has important implications for how we understand the modulation of rhythmic activity in diverse cognitive states relating to arousal, attention, and cognitive processing. As we demonstrate, our model also provides a tool for investigating and improving the use of rhythmic brain stimulation in clinical applications.

scholarly journals Structural and functional control of surface-patch to hillslope runoff and sediment connectivity in Mediterranean dry reclaimed slope systems

2020 ◽  
Vol 24 (5) ◽  
pp. 2855-2872
Author(s):  
Mariano Moreno-de-las-Heras ◽  
Luis Merino-Martín ◽  
Patricia M. Saco ◽  
Tíscar Espigares ◽  
Francesc Gallart ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Sediment Yield ◽  
Rainfall Intensity ◽  
Spatial Scales ◽  
Structural Connectivity ◽  
Surface Patch ◽  
Practical Applications ◽  
Sediment Connectivity ◽  
Development Levels ◽  
The Impact

Abstract. Connectivity has emerged as a useful concept for exploring the movement of water and sediments between landscape locations and across spatial scales. In this study, we examine the structural and functional controls of surface-patch to hillslope runoff and sediment connectivity in three Mediterranean dry reclaimed mining slope systems that have different long-term development levels of vegetation and rill networks. Structural connectivity was assessed using flow path analysis of coupled vegetation distribution and surface topography, providing field indicators of the extent to which surface patches that facilitate runoff and sediment production are physically linked to one another in the studied hillslopes. Functional connectivity was calculated using the ratio of patch-scale to hillslope-scale observations of runoff and sediment yield for 21 monitored hydrologically active rainfall events. The impact of the dynamic interactions between rainfall conditions and structural connectivity on functional connectivity were further analysed using general linear models with a backward model structure selection approach. Functional runoff connectivity during precipitation events was found to be dynamically controlled by antecedent precipitation conditions and rainfall intensity and strongly modulated by the structural connectivity of the slopes. On slopes without rills, both runoff and sediments for all events were largely redistributed within the analysed hillslopes, resulting in low functional connectivity. Sediment connectivity increased with rainfall intensity, particularly in the presence of rill networks where active incision under high-intensity storm conditions led to large non-linear increases in sediment yield from the surface-patch to the hillslope scales. Overall, our results demonstrate the usefulness of applying structural- and functional-connectivity metrics for practical applications and for assessing the complex links and controlling factors that regulate the transference of both surface water and sediments across different landscape scales.

scholarly journals Understanding the role of alterations in cortical D1 receptor sensitivity in shaping working memory maintenance through mesocortical dynamics

2018 ◽  
Author(s):  
Melissa Reneaux ◽  
Rahul Gupta
Keyword(s):  
Working Memory ◽  
Firing Frequency ◽  
D1 Receptor ◽  
Neural Mass Model ◽  
Mass Model ◽  
Neural Mass ◽  
The Impact ◽  
Neuropsychiatric Conditions ◽  
Higher Sensitivity

AbstractThe dopamine (DA) hypothesis of cognitive deficits suggests that too low or too high extracellular DA concentration in the prefrontal cortex (PFC) can severely impair the working memory (WM) maintenance during delay period. Thus, there exists only an optimal range of DA where the sustained-firing activity, the neural correlate of WM maintenance, in the cortex possesses optimal firing frequency as well as robustness against noisy distractions. Empirical evidences demonstrate changes even in the D1 receptor (D1R)-sensitivity to extracellular DA, collectively manifested through D1R density and DA-binding affinity, in the PFC under neuropsychiatric conditions such as ageing and schizophrenia. However, the impact of alterations in the cortical D1R-sensitivity on WM maintenance has yet remained poorly addressed. Using a quantitative neural mass model of the prefronto-mesoprefrontal system, the present study reveals that higher D1R-sensitivity may not only effectuate shrunk optimal DA range but also shift of the range to lower concentrations. Moreover, higher sensitivity may significantly reduce the WM-robustness even within the optimal DA range and exacerbates the decline at abnormal DA levels. These findings project important clinical implications, such as dosage precision and variability of DA-correcting drugs across patients, and failure in acquiring healthy WM maintenance even under drug-controlled normal cortical DA levels.

scholarly journals Asynchronous and Coherent Dynamics in Balanced Excitatory-Inhibitory Spiking Networks

2021 ◽  
Vol 15 ◽  
Author(s):  
Hongjie Bi ◽  
Matteo di Volo ◽  
Alessandro Torcini
Keyword(s):  
Spatial Scales ◽  
Spatial Coherence ◽  
Mean Field ◽  
Period Doubling ◽  
Structural Heterogeneity ◽  
Neural Mass Model ◽  
Current Fluctuations ◽  
Mass Model ◽  
Frequency Locking ◽  
Neural Mass

Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable in the brain. The analysis is performed by combining extensive simulations of sparse E-I networks composed of N spiking neurons with analytical investigations of low dimensional neural mass models. The bifurcation diagrams, derived for the neural mass model, allow us to classify the possible asynchronous and coherent behaviors emerging in balanced E-I networks with structural heterogeneity for any finite in-degree K. Analytic mean-field (MF) results show that both supra and sub-threshold balanced asynchronous regimes are observable in our system in the limit N >> K >> 1. Due to the heterogeneity, the asynchronous states are characterized at the microscopic level by the splitting of the neurons in to three groups: silent, fluctuation, and mean driven. These features are consistent with experimental observations reported for heterogeneous neural circuits. The coherent rhythms observed in our system can range from periodic and quasi-periodic collective oscillations (COs) to coherent chaos. These rhythms are characterized by regular or irregular temporal fluctuations joined to spatial coherence somehow similar to coherent fluctuations observed in the cortex over multiple spatial scales. The COs can emerge due to two different mechanisms. A first mechanism analogous to the pyramidal-interneuron gamma (PING), usually invoked for the emergence of γ-oscillations. The second mechanism is intimately related to the presence of current fluctuations, which sustain COs characterized by an essentially simultaneous bursting of the two populations. We observe period-doubling cascades involving the PING-like COs finally leading to the appearance of coherent chaos. Fluctuation driven COs are usually observable in our system as quasi-periodic collective motions characterized by two incommensurate frequencies. However, for sufficiently strong current fluctuations these collective rhythms can lock. This represents a novel mechanism of frequency locking in neural populations promoted by intrinsic fluctuations. COs are observable for any finite in-degree K, however, their existence in the limit N >> K >> 1 appears as uncertain.

scholarly journals Roads constrain movement across behavioural processes in a partially migratory ungulate

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Gioele Passoni ◽  
Tim Coulson ◽  
Nathan Ranc ◽  
Andrea Corradini ◽  
A. J. Mark Hewison ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Home Range ◽  
Clustering Algorithm ◽  
Animal Movement ◽  
Roe Deer ◽  
Spatial Scales ◽  
Forested Areas ◽  
And Migration ◽  
The Impact ◽  
Road Avoidance

Abstract Background Human disturbance alters animal movement globally and infrastructure, such as roads, can act as physical barriers that impact behaviour across multiple spatial scales. In ungulates, roads can particularly hamper key ecological processes such as dispersal and migration, which ensure functional connectivity among populations, and may be particularly important for population performance in highly human-dominated landscapes. The impact of roads on some aspects of ungulate behaviour has already been studied. However, potential differences in response to roads during migration, dispersal and home range movements have never been evaluated. Addressing these issues is particularly important to assess the resistance of European landscapes to the range of wildlife movement processes, and to evaluate how animals adjust to anthropogenic constraints. Methods We analysed 95 GPS trajectories from 6 populations of European roe deer (Capreolus capreolus) across the Alps and central Europe. We investigated how roe deer movements were affected by landscape characteristics, including roads, and we evaluated potential differences in road avoidance among resident, migratory and dispersing animals (hereafter, movement modes). First, using Net Squared Displacement and a spatio-temporal clustering algorithm, we classified individuals as residents, migrants or dispersers. We then identified the start and end dates of the migration and dispersal trajectories, and retained only the GPS locations that fell between those dates (i.e., during transience). Finally, we used the resulting trajectories to perform an integrated step selection analysis. Results We found that roe deer moved through more forested areas during the day and visited less forested areas at night. They also minimised elevation gains and losses along their movement trajectories. Road crossings were strongly avoided at all times of day, but when they occurred, they were more likely to occur during longer steps and in more forested areas. Road avoidance did not vary among movement modes and, during dispersal and migration, it remained high and consistent with that expressed during home range movements. Conclusions Roads can represent a major constraint to movement across modes and populations, potentially limiting functional connectivity at multiple ecological scales. In particular, they can affect migrating individuals that track seasonal resources, and dispersing animals searching for novel ranges.

scholarly journals An individualized Neural Mass Model of ictal activity based on GABA-A pathology for personalization of brain stimulation protocols in epilepsy

2021 ◽  
Vol 14 (6) ◽  
pp. 1677
Author(s):  
Edmundo Lopez-Sola ◽  
Roser Sanchez-Todo ◽  
Elia Lleal ◽  
Elif Köksal-Ersöz ◽  
Maxime Yochum ◽  
...  
Keyword(s):  
Brain Stimulation ◽  
Neural Mass Model ◽  
Mass Model ◽  
Gaba A ◽  
Neural Mass ◽  
Ictal Activity

14 Pathological oscillatory activity in Parkinson’s disease; what does it mean and how should we treat it?

2020 ◽  
Vol 91 (8) ◽  
pp. e6.1-e6
Author(s):  
Peter Brown
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Basal Ganglia ◽  
Side Effects ◽  
Brain Stimulation ◽  
Neural Circuit ◽  
Symptom Control ◽  
Oscillatory Activity ◽  
Deep Brain

Professor Peter Brown is Professor of Experimental Neurology and Director of the Medical Research Council Brain Network Dynamics Unit at the University of Oxford. Prior to 2010 he was a Professor of Neurology at University College London.For decades we have had cardiac pacemakers that adjust their pacing according to demand and yet therapeutic adaptive stimulation approaches for the central nervous system are still not clinically available. Instead, to treat patients with advanced Parkinson’s disease we stimulate the basal ganglia with fixed regimes, unvarying in frequency or intensity. Although effective, this comes with side-effects and in terms of sophistication this treatment approach could be compared to having central heating system on all the time, regardless of temperature. This talk will describe recent steps being taken to define the underlying circuit dysfunction in Parkinson’s and to improve deep brain stimulation by controlling its delivery according to the state of pathological activity.Evidence is growing that motor symptoms in Parkinson’s disease are due, at least in part, to excessive synchronisation between oscillating neurons. Recordings confirm bursts of oscillatory synchronisation in the basal ganglia centred around 20 Hz. The bursts of 20 Hz activity are prolonged in patients withdrawn from their usual medication and the dominance of these long duration bursts negatively correlates with motor impairment. Longer bursts attain higher amplitudes, indicative of more pervasive oscillatory synchronisation within the neural circuit. In contrast, in heathy primates and in treated Parkinson’s disease bursts tend to be short. Accordingly, it might be best to use closed-loop controlled deep brain stimulation to selectively terminate longer, bigger, pathological beta bursts to both save power and to spare the ability of underlying neural circuits to engage in more physiological processing between long bursts. It is now possible to record and characterise bursts on-line during stimulation of the same site and trial adaptive stimulation. Thus far, this has demonstrated improvements in efficiency and side-effects over conventional continuous stimulation, with at least as good symptom control in Parkinsonian patients.

scholarly journals Resting-state connectivity predicts patient-specific effects of deep brain stimulation for Parkinson’s disease

2017 ◽  
Author(s):  
Xiaoyu Chen ◽  
Chencheng Zhang ◽  
Yuxin Li ◽  
Pei Huang ◽  
Qian Lv ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Neural Circuit ◽  
Patient Specific ◽  
Neural Network Modeling ◽  
Brain Connectome ◽  
Diffusion Dynamics ◽  
Deep Brain

AbstractNeural circuit-based guidance for optimizing patient screening, target selection and parameter tuning for deep brain stimulation (DBS) remains limited. To this end, we propose a functional brain connectome-based modeling approach that simulates network-spreading effects of stimulating different brain regions and quantifies rectification of abnormal network topology in silico. We validate these analyses by predicting nuclei in basal-ganglia circuits as top-ranked targets for 43 local patients with Parkinson’s disease and 90 patients from public database. However, individual connectome-based predictions demonstrate that globus pallidus and subthalamic nucleus (STN) constituted as the best choice for 21.1% and 19.5% of patients, respectively. Notably, the priority rank of STN significantly correlated with motor symptom severity in the local cohort. By introducing whole-brain network diffusion dynamics, these findings unfold a new dimension of brain connectomics and underscore the importance of neural network modeling for personalized DBS therapy, which warrants experimental investigation to validate its clinical utility.

scholarly journals Cannabis Vapour Exposure Alters Neural Circuit Oscillatory Activity In A Neurodevelopmental Model Of Schizophrenia: Exploring The Differential Impact Of Cannabis Constituents

2021 ◽  
Author(s):  
Bryan W. Jenkins ◽  
Shoshana Buckhalter ◽  
Melissa L. Perreault ◽  
Jibran Y. Khokhar
Keyword(s):  
Neural Circuit ◽  
Dorsal Hippocampus ◽  
Field Potential ◽  
Oscillatory Activity ◽  
Sprague Dawley ◽  
High Gamma ◽  
Oscillatory Power ◽  
Gamma Power ◽  
Gamma Coherence ◽  
The Impact

AbstractCannabis use is highly prevalent in patients with schizophrenia and worsens the course of the disorder. To understand the causal impacts of cannabis on schizophrenia-related oscillatory disruptions, we herein investigated the impact of exposure to cannabis vapour (containing delta-9-tetrahydrocannabinol [THC] or balanced THC and cannabidiol [CBD]) on oscillatory activity in the neonatal ventral hippocampal lesion (NVHL) rat model of schizophrenia. Male Sprague Dawley rats underwent NVHL or sham surgeries on postnatal day 7. In adulthood, electrodes were implanted targeting the cingulate cortex (Cg), the prefrontal cortex (PFC), the dorsal hippocampus (HIP), and the nucleus accumbens (NAc). Local field potential recordings were obtained following exposure to two strains of vapourized cannabis flower (with ~10% THC or ~10% balanced THC:CBD) in a cross-over design with a two-week wash-out period between exposures. Compared to controls, NVHL rats had reduced baseline gamma power in the Cg, dHIP, and NAc, and reduced high-gamma coherence between the dHIP-Cg. THC-only vapour broadly suppressed oscillatory power and coherence, even beyond the baseline suppressions observed in NHVL rats. Balanced THC:CBD vapour appeared to ameliorate the THC-induced impacts on power and coherence in both sham and NVHL rats. For NVHL rats, THC-only vapour also normalized the baseline dHIP-Cg high-gamma coherence deficits. NHVL rats also demonstrated a 20ms delay in dHIP theta to high-gamma phase coupling, which was ameliorated by both exposures in the PFC and NAc. In conclusion, THC-only cannabis vapour suppressed oscillatory activity in NVHL and sham rats, while balanced THC:CBD vapour may ameliorate some of these effects.

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