Modeling the effect of dendritic input location on MEG and EEG source dipoles

The cerebral sources of magneto- and electroencephalography (MEG, EEG) signals can be represented by current dipoles. We used computational modeling of realistically shaped passive-membrane dendritic trees of pyramidal cells from the human cerebral cortex to examine how the spatial distribution of the synaptic inputs affects the current dipole. The magnitude of the total dipole moment vector was found to be proportional to the vertical location of the synaptic input. The dipole moment had opposite directions for inputs above and below a reversal point located near the soma. Inclusion of shunting-type inhibition either suppressed or enhanced the current dipole, depending on whether the excitatory and inhibitory synapses were on the same or opposite side of the reversal point. Relating the properties of the macroscopic current dipoles to dendritic current distributions can help to provide means for interpreting MEG and EEG data in terms of synaptic connection patterns within cortical areas.National Center for Research Resources (U.S.) (P41RR14075)National Institutes of Health (U.S.) (Grants NS57500 and NS037462

The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes

Neuronal activity in the brain gives rise to transmembrane currents that can be measured in the extracellular medium. Although the major contributor of the extracellular signal is the synaptic transmembrane current, other sources — including Na+ and Ca2+ spikes, ionic fluxes through voltage- and ligand-gated channels, and intrinsic membrane oscillations — can substantially shape the extracellular field. High-density recordings of field activity in animals and subdural grid recordings in humans, combined with recently developed data processing tools and computational modelling, can provide insight into the cooperative behaviour of neurons, their average synaptic input and their spiking output, and can increase our understanding of how these processes contribute to the extracellular signal

Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics

Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain.We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors.The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted.Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales.This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses

An Interneuron Circuit Reproducing Essential Spectral Features of Field Potentials

This document is the Accepted Manuscript version of the following article: Reinoud Maex, ‘An Interneuron Circuit Reproducing Essential Spectral Features of Field Potentials’, Neural Computation, March 2018. Under embargo until 22 June 2018. The final, definitive version of this paper is available online at doi: https://doi.org/10.1162/NECO_a_01068. © 2018 Massachusetts Institute of Technology. Content in the UH Research Archive is made available for personal research, educational, and non-commercial purposes only. Unless otherwise stated, all content is protected by copyright, and in the absence of an open license, permissions for further re-use should be sought from the publisher, the author, or other copyright holder.Recent advances in engineering and signal processing have renewed the interest in invasive and surface brain recordings, yet many features of cortical field potentials remain incompletely understood. In the present computational study, we show that a model circuit of interneurons, coupled via both GABA(A) receptor synapses and electrical synapses, reproduces many essential features of the power spectrum of local field potential (LFP) recordings, such as 1/f power scaling at low frequency (< 10 Hz) , power accumulation in the γ-frequency band (30–100 Hz), and a robust α rhythm in the absence of stimulation. The low-frequency 1/f power scaling depends on strong reciprocal inhibition, whereas the α rhythm is generated by electrical coupling of intrinsically active neurons. As in previous studies, the γ power arises through the amplifica- tion of single-neuron spectral properties, owing to the refractory period, by parameters that favour neuronal synchrony, such as delayed inhibition. The present study also confirms that both synaptic and voltage-gated membrane currents substantially contribute to the LFP, and that high-frequency signals such as action potentials quickly taper off with distance. Given the ubiquity of electrically coupled interneuron circuits in the mammalian brain, they may be major determinants of the recorded potentials.Peer reviewe

Characterization of Neuroimage Coupling Between EEG and FMRI Using Within-Subject Joint Independent Component Analysis

The purpose of this dissertation was to apply joint independent component analysis (jICA) to electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to characterize the neuroimage coupling between the two modalities. EEG and fMRI are complimentary imaging techniques which have been used in conjunction to investigate neural activity. Understanding how these two imaging modalities relate to each other not only enables better multimodal analysis, but also has clinical implications as well. In particular, Alzheimer’s, Parkinson’s, hypertension, and ischemic stroke are all known to impact the cerebral blood flow, and by extension alter the relationship between EEG and fMRI. By characterizing the relationship between EEG and fMRI within healthy subjects, it allows for comparison with a diseased population, and may offer ways to detect some of these conditions earlier. The correspondence between fMRI and EEG was first examined, and a methodological approach which was capable of informing to what degree the fMRI and EEG sources corresponded to each other was developed. Once it was certain that the EEG activity observed corresponded to the fMRI activity collected a methodological approach was developed to characterize the coupling between fMRI and EEG. Finally, this dissertation addresses the question of whether the use of jICA to perform this analysis increases the sensitivity to subcortical sources to determine to what degree subcortical sources should be taken into consideration for future studies. This dissertation was the first to propose a way to characterize the relationship between fMRI and EEG signals using blind source separation. Additionally, it was the first to show that jICA significantly improves the detection of subcortical activity, particularly in the case when both physiological noise and a cortical source are present. This new knowledge can be used to design studies to investigate subcortical signals, as well as to begin characterizing the relationship between fMRI and EEG across various task conditions

Neuromagnetic studies on cortical somatosensory functions in infants and children : Normal development and effect of early brain lesions

Until recently, objective investigation of the functional development of the human brain in vivo was challenged by the lack of noninvasive research methods. Consequently, fairly little is known about cortical processing of sensory information even in healthy infants and children. Furthermore, mechanisms by which early brain insults affect brain development and function are poorly understood. In this thesis, we used magnetoencephalography (MEG) to investigate development of cortical somatosensory functions in healthy infants, very premature infants at risk for neurological disorders, and adolescents with hemiplegic cerebral palsy (CP). In newborns, stimulation of the hand activated both the contralateral primary (SIc) and secondary somatosensory cortices (SIIc). The activation patterns differed from those of adults, however. Some of the earliest SIc responses, constantly present in adults, were completely lacking in newborns and the effect of sleep stage on SIIc responses differed. These discrepancies between newborns and adults reflect the still developmental stage of the newborns’ somatosensory system. Its further maturation was demonstrated by a systematic transformation of the SIc response pattern with age. The main early adult­like components were present by age two. In very preterm infants, at term age, the SIc and SIIc were activated at similar latencies as in healthy fullterm newborns, but the SIc activity was weaker in the preterm group. The SIIc response was absent in four out of the six infants with brain lesions of the underlying hemisphere. Determining the prognostic value of this finding remains a subject for future studies, however. In the CP adolescents with pure subcortical lesions, contrasting their unilateral symptoms, the SIc responses of both hemispheres differed from those of controls: For example the distance between SIc representation areas for digits II and V was shorter bilaterally. In four of the five CP patients with cortico­subcortical brain lesions, no normal early SIc responses were evoked by stimulation of the palsied hand. The varying differences in neuronal functions, underlying the common clinical symptoms, call for investigation of more precisely designed rehabilitation strategies resting on knowledge about individual functional alterations in the sensorimotor networks.Lääketieteellisen teknologian kehitys on vasta viime vuosina mahdollistanut lasten aivotoiminnan tarkan, objektiivisen tutkimuksen. Näin ollen esimerkiksi aistiärsykkeiden aivoprosessoinnista vastasyntyneillä tiedetään varsin vähän, samoin kuin monien aivotoimintojen kehittymisestä lapsen kasvaessa. Myös ymmärrys erilaisten aivovaurioiden vaikutuksesta kehittyviin aivoihin on puutteellista. Magnetoenkefalografialla (MEG) tutkitaan aivohermosolujen toimintaa mittaamalla niissä syntyvien sähkövirtojen tuottamia magneettikenttiä pään ulkopuolelta. Väitöskirjassa MEG:n avulla tutkittiin tuntoaivokuoren toimintaa vastasyntyneillä ja tämän toiminnan kehitystä ensimmäisten elinvuosien aikana. Lisäksi tuntoaivokuoren toimintaa tarkasteltiin pikkukeskosena syntyneillä vauvoilla sekä nuorilla, joilla on varhaisen aivovaurion aiheuttama toispuoleinen CP-vamma. Jo vastasyntyneellä useat aivoalueet aktivoituivat käden alueen kosketusärsykkeen jälkeen. Tuntoaivokuoren aktiivisuus poikkesi kuitenkin oleellisesti aikuisesta: tietyt aikuistyyppiset aivovasteet puuttuivat vastasyntyneiltä täysin heijastaen vastasyntyneen vauvan hermoston keskeneräistä kehitysvaihetta. Tuntoaivovasteet kehittyivät iän myötä järjestelmällisesti siten, että kaksivuotiailla ne alkoivat morfologisesti muistuttaa aikuisten vasteita. Pikkukeskosten primaarisen tuntoaivokuoren vaste oli lasketussa ajassa heikompi kuin terveillä täysaikaisilla vauvoilla, mikä voi johtua pienemmästä aktivoituneesta hermosolujoukosta tai aktivaation epäsynkroniasta. Sekundaarisen tuntoaivokuoren vasteen puuttuminen liittyi poikkeaviin ultraääni- ja magneettikuvauslöydöksiin. Tämän havainnon ennusteellista merkitystä selvitetään parhaillaan seurantatutkimuksella. CP-vammaisilla nuorilla tuntoaivovasteissa havaittiin verrokkeihin nähden useita poikkeavuuksia, jotka olivat osin laaja-alaisempia kuin oli pääteltävissä kliinisistä oireista tai aivojen rakenteellisesta vauriosta. Esimerkiksi potilailla, joiden sairauden taustalla oli subkortikaalinen aivovaurio, etu- ja pikkusormien edustusalueet tuntoaivokuorella olivat verrokkeihin nähden lähempänä toisiaan sekä vaurion puoleisessa että vastakkaisessa aivopuoliskossa. Aivojen erilaisten rakenteellisten vaurioiden aiheuttamien toiminnallisten muutosten tarkempi ymmärtäminen voi osoittautua merkittäväksi CP-potilaiden kuntoutuksen ja hoidon yksilöllisessä räätälöinnissä

Computational Characterization of the Cellular Origins of Electroencephalography

Electroencephalography (EEG) is a non-invasive technique used to measure brain activity. Despite its near ubiquitous presence in neuroscience, very little research has gone into connecting the electrical potentials it measures on the scalp to the underlying network activity which generates those signals. This results in most EEG analyses being more macroscopically focused (e.g. coherence and correlation analyses). Despite the many uses of macroscopically focuses analyses, limiting research to only these analyses neglects the insights which can be gained from studying network and microcircuit architecture. The ability to study these things through non-invasive techniques like EEG depends upon the ability to understand how the activity of individual neurons affect the electrical potentials recorded by EEG electrodes on the scalp. The research presented here is designed to take the first steps towards providing that link.Current dipole moments generated by multiple multi-compartment, morphologically accurate, three-dimensional neuron models were characterized into a single time series called a dipole response function (DRF). We found that when the soma of a neuron is directly stimulated to threshold, the resulting action potential caused an excess of current which backpropagated up the dendritic tree activating voltage gated ion channels along the way. This backpropigation created a dipole which had a magnitude and duration greater than the current dipoles created by neurons that were synaptically activated to near threshold. Additionally, we presented a novel technique, where, through the combination of the DRFs with point source network activity via convolution, dipoles generated by populations of neurons can be simulated. We validated this technique at multiple spatial scales using data from both animal models and human subjects. Our results show that this technique can provide a reasonable representation of the extracellular fields and EEG signals generated in their physiological counterparts. Finally, analysis of a simulated evoked potential generated via the convolutional methodology proposed showed that ∼ 98% of the variability of simulated signal could be accounted for by the dipoles originating from DRFs of spiking pyramidal cells