Eric Halgren - US grants

DESCRIPTION (provided by applicant): Human brain function can be probed by measuring the minute currents produced by active neurons using electroencephalography (EEG) and magnetoencephalography (MEG). Neuronal activity also results in localized changes in blood oxygenation and flow, which can be measured using functional magnetic resonance imaging (fMRI). fMRI provides direct localization of brain activation during cognition, but with poor temporal resolution. Conversely, EEG/MEG provides millisecond accuracy, but the location in the brain where they arise is hard to determine. The first aim of this grant is to combine the spatial resolution of fMRI with the temporal resolution of EEG/MEG to produce spatiotemporal maps of brain activation. The accuracy of these maps will be validated using EEG recordings from directly within the brain (conducted in order to localize the seizure focus in patients with pharmaco-resistant epilepsy). These maps will help reveal where and when brain areas are active during thought. The second aim of the grant is to better understand what kind of neuronal activity these maps represent. Linear microelectrode arrays will be used in the same subjects and tasks to estimate population synaptic currents (neuronal inputs) and neuronal firing (outputs) in different cortical layers. The 'activation'found in the whole-brain studies will thus be characterized as excitation vs inhibition, input vs output, and top-down vs bottom-up interactions. The proposed studies should provide insights into how the different brain imaging modalities view functional brain activity, and how they may be integrated in order to trace the passage of activation through the thinking human brain. This technique should also be useful for localizing pathological activity. In addition, the proposed studies may help in the construction of functional neural models for cognition. Such models are necessary to understand how cognition is disrupted in neuropsychiatric disorders. Finally, more complete knowledge regarding the generators of cognitive potentials should greatly increase their value as functional tests for specific brain systems in patients with neurological or psychiatric disease. Specifically, studies on language and memory will provide a scientific basis for the non-invasive mapping of eloquent cortex prior to surgery.

The long term objective of this research is to investigate the molecular mechanism for the generation of the diversities of immune receptors. The V, (D), and J segments of the Ig and TCR genes are assembled by somatic recombination during the lymphoid differentiation. These recombination processes are mediated by the recombination signal sequences (Rss) and the V (D)J recombinase. To elucidate the molecular mechanisms of the V (D)J recombination, it is essential to characterize lymphoid-specific proteins that bind the Rss. We have cloned the cDNA for a protein, Rc, which is predominantly expressed in thymocytes, by the ability of Rc to bind the Rss. Subsequently, we have shown the Rc binds the kappa B motif and the Ig kappa chain gene enhancer as well. The aim of this project is to investigate the biological role of Rc in V (D)J recombination. The primary structure of Rc will be predicted from its CDNA and possible structural domains will be defined by comparing with p roteins present in the databases. The information may shed light on how Rc can be involved in V (D)J recombination.

proteins; microorganism; biotechnology; biomedical resource; animal tissue;

DESCRIPTION: (provided by applicant) Human brain function can be probed by measuring the minute currents produced by active neurons using electroencephalography (EEG) and magnetoencephalography (MEG). Neuronal activity also results in localized changes in blood flow, which can be measured using functional magnetic resonance imaging (fMRI). fMRI provides direct localization of brain activation during cognition, but with poor temporal resolution. Conversely, EEG/MEG provide millisecond accuracy, but the location in the brain where they arise is hard to determine. The first aim of this grant is to combine the spatial resolution of fMRI with the temporal resolution of BEG/MEG to produce spatiotemporal maps of brain activation. The accuracy of these maps will be validated using EEG recordings from directly within the brain (conducted in order to localize the seizure focus in patients with pharmaco-resistant epilepsy). Maps will be made for a variety of processing stages used in perception, memory, language, and action, including those associated with the event-related potential (ERP) components N2, P3a, P3b, P 170, N400, RP, ERN, ELAN, P600 and CNV. These maps will help reveal where and when brain areas are active during thought. The second aim of the grant is to better understand what kind of neuronal activity these maps represent. Linear microelectrode arrays will be used in the same subjects and tasks to estimate population synaptic currents (neuronal inputs) and neuronal firing (outputs) in different cortical layers. The ?activation? found in the whole-brain studies will thus be characterized as excitation vs inhibition, input vs output, and top-down vs bottom-up interactions. The proposed studies should provide insights into how the different brain imaging modalities view functional brain activity, and how they may be integrated in order to trace the passage of activation through the thinking human brain. This technique should also be useful for localizing pathological activity. In addition, the proposed studies may help in the construction of functional neural models for cognition. Such models are necessary to understand how cognition is disrupted in neuropsychiatric disorders. Finally, more complete knowledge regarding the generators of cognitive potentials should greatly increase their value as functional tests for specific brain systems in patients with neurological or psychiatric disease.

[unreadable] DESCRIPTION (provided by applicant): [unreadable] The spatiotemporal dynamics of human brain activation can be non-invasively imaged by combining functional Magnetic Resonance Imaging (fMRI) with magneto- and electro-encephalography (M/EEG). fMRI locates altered cerebral hemodynamics with good spatial accuracy but poor temporal resolution. Conversely, M/EEG are instantaneous measures of population synaptic activity, but are hard to localize because of spatiotemporal cancellation. Furthermore, the transfer functions from cortical neuronal synaptic currents and cell-firing, to extracranial hemodynamic and electromagnetic signals, are unknown. The potential variability of the relationships of hemodynamic and electromagnetic signals to each other, and to their underlying neural substrates, make it necessary to explore and define these relations in behaving humans. We propose to measure neuronal activity using linear arrays of micro-electrodes. Optical measurements will quantify hemodynamics using cortical point spectroscopy and laser Doppler. Simultaneous measures within the same cortical micro-domain will be made during spontaneous activity, calibration states, and a variety of cognitive tasks. If successful, this research will reveal, at an unprecedented level of quantification and certainty, the relations between hemodynamic and electromagnetic measures, and the underlying activity of neuronal populations, during cognition in humans. [unreadable] [unreadable]

Almost as remarkable as the ability to know one language is the ability to learn a second. However, current understanding of how the human brain acquires, organizes, and processes multiple languages is highly limited. A fundamental issue is whether multiple languages are represented in common brain areas. When monolinguals read, words enter the cortex at its posterior tip, and work their way forward. Within two-tenths of a second, the words are encoded visually, and then in the next three-tenths of a second they are encoded for meaning in specialized areas of the left temporal and frontal lobes. With support from the National Science Foundation, Dr. Eric Halgren and Dr. Jeffrey Elman of the University of California at San Diego, with their colleagues, will study word encoding in young adults reading words in their native Spanish, or in their second language, English, which most have been using since they started school. Cortical neurons process information using electrical currents, which in turn produce minute magnetic fields. These will be detected using arrays of superconducting quantum interference devices as the magnetoencephalogram, and then mapped to particular cortical areas using magnetic resonance imaging. Experiments will determine if the English and Spanish words are encoded in the same areas. Specifically, experiments will test a model that hypothesizes that the second language does engage the same areas as the first, but in addition accesses the corresponding areas in the right hemisphere. Experiments will also attempt to confirm the suggestion that the second language uses brain areas which are otherwise engaged in high level vision, and explore if the second language is characterized by perceptual representations of words. Experiments will test how early in the processing stream English and Spanish words diverge, and whether this divergence is due to top-down strategic control or quick categorization. Subjects will vary in how well they know English and when they began learning it, so that the effects of age of acquisition, order of acquisition, and proficiency can be determined.

This research brings together neural, cognitive, language and imaging sciences, providing interdisciplinary training, especially for bilingual Spanish-English students, and introducing neuroimaging to a societal problem previously approached mainly behaviorally. Over two-thirds of the global population is multi-lingual. Bilingualism binds together the multiple American subcultures, being essential for socioeconomic integration of recent immigrants, and for the access of American goods and services to a global marketplace. Yet, second language education is often ineffective. A clearer picture of how the brain organizes multiple languages will form part of the scientific basis for developing effective second language teaching methodologies.

Project IV. Neuroimaging of Social Brain Circuitry This project builds on prior results to better characterize the neural substrate of WS, and in particular the structural and neurophysiological characteristics that may underlie its striking social phenotype. Our first aim focuses on structural changes in WS, utilizing comprehensive, validated, automated and quantitative analyses of MRI and DTI, based on segmentation of the cerebral volume, reconstruction and parcellation of the cortical surface, and tractography of the white matter. In addition to confirming previous results (such as increased amygdala volume) with different techniques in an independent population of WS, we will test hypotheses derived from previous behavioral and functional imaging results, suggesting changes in the posterior fusiform and anteroventral temporal, subgenual, orbital and anterior insular cortices. We will also quantify the fiber tracts connecting the amygdala to ventral prefrontal and fusiform face areas. Our second aim examines the functional bases of sociability changes in WS using magnetoencephalography (MEG). Anatomically-constrained distributed procedures will estimate cortical activation patterns with excellent temporal and good spatial accuracies. We will test the hypothesized neural substrates for the sensitivity of WS to faces compared to control stimuli, and especially to happy compared to sad faces. The strength and direction of functional communication between different parts of the system processing facial emotions will be examined with event-related spectral measures. In the third aim, we will examine the inter-relation of structural, functional and genetic bases of sociability in WS. For example, we will test if face-selective MEG responses correlate with fusiform structural measures, emotional with amygdala and its connections in orbital, ventral, medial and opercular prefrontal cortices. In addition, we will test if the ERP and psychophysical data from Project 5 correlate with specific structural measures, and compare our anatomical results with direct histological examination of the same locations in Project 3. In summary, this project aims to identify anatomical and physiological circuits linking the genetic deletion to the social-behavioral RELEVANCE (See instructions): These studies may help identify the neural circuits underlying specific social behaviors in WS, and thus by extension, in the healthy population. In addition to the specific application of these studies to WS, a relatively common source of genetically-caused retardation, these insights may contribute to the neurobiological understanding necessary to design biological treatments for neuropsychiatric disorders of social behavior.

DESCRIPTION (provided by applicant): Language is central to human experience, but we know very little regarding its neural substrate during early development because existing techniques for observing brain activity in infants have low anatomical or temporal resolution, an indirect relationship to neural activity, require more behavioral maturity, or deposit ionizing radiation. In contrast, magnetoencephalography (MEG) is silent and well tolerated by infants. MEG directly and instantaneously measures intraneuronal currents underlying cognitive information processing. We propose to record whole-head 306 channel MEG during word processing by infants. Good anatomical resolution will be obtained by constraining the sources to lie in the cortex of the same individual, reconstructed from MRI performed while the infant is asleep. Our initial focus is on ~14 month old infants, who typically understand a few tens of words, the minimum needed for testing. We will then extend these methods to ~18 month old infants, whose burgeoning expressive vocabularies permit correlation of brain responses with individual differences in language development. In the basic task, infants listen to words they understand, and to noise matched for amplitude, contour and spectral density to each word. In preliminary data, this comparison reliably evokes MEG activity at ~400ms localized to classical language regions. In latency and localization, this activity resembles the N400m evoked by words in adults. Confirmation of this homology will be sought by testing if the infant N400m shares key cognitive characteristics with the adult N400m, specifically sensitivity to repetition and semantic priming. Semantic priming will be examined by presenting a picture and then an auditory word which either matches the picture or not. Preliminary data indicates that the infant N400m, like the adult N400m, is depressed by semantic congruence. The proposed studies will establish a basic pattern of neural activity evoked by words in infants, dissociate it from sensory responses, and demonstrate its relationship to semantic understanding. This would help reveal the neural circuits and synaptic mechanisms used to acquire language understanding, and allow their measurement in infants at risk for language disorders. PUBLIC HEALTH RELEVANCE: Disorders of language acquisition are common and can severely limit psychosocial development. This research will develop a method to safely measure the brain activity underlying infant word-processing, to be used to study the neural basis of language development in both normal and atypically developing infants. Future applications of these methods may include the assessment of children at-risk for delayed language.

DESCRIPTION (provided by applicant): Mammalian cortex operates in two fundamentally different modes. One, dominant during waking, is termed the upstate because of relatively high neuronal firing rates and synaptic activity. The other, oscillating with the upstate in the deepest stages of non-rapid eye-movement sleep, is characterized by a profound suppression of cell-firing and is termed the downstate. This slow oscillation (SO) has been intensively studied in animals with intracellular recordings, especially in model systems in vitro and in vivo under anesthesia. The basic phenomena have been reproduced from channel properties and synaptic connectivity in realistic Hodgkin-Huxley (H-H) computational models with limited numbers of cells4,6. Recent multi-microelectrode recordings in humans have demonstrated that the SO corresponds to .5-2Hz delta activity prominent in the stage 3 and 4 sleep EEG2, and further, that the downstate can occur in relative isolation as the K-Complex (KC) of stage 2 sleep1. These studies have established the basic local mechanisms of upstates and downstates, and their correspondence to prominent EEG phenomena that are easily observable in non-invasive recordings. However, important aspects of how they are triggered and synchronized remain unknown and controversial. Do SO and KC occur in all parts of the cortex? If so, do they preferentially occur in some areas? Do different SO and KC involve different cortical areas? Do they occur in all areas simultaneously or do they spread across the cortex? If they spread, is there a characteristic speed or point of origin? Do upstates and downstates differ in how they are triggered or synchronized? These are very complex questions regarding how billions of neurons are coordinated. Although empirical recordings are necessary to provide clues, these must be processed and interpreted with computational methods to make real headway. Biophysical and statistical forward and inverse computations are necessary to relate the microelectrode data to mesoscopic recordings (ECOG- electrocorticography) and non-invasive measures (MEG- magnetoencephalography and EEG). Neural modeling is necessary to test if specific hypothesized mechanisms for the origin and spread of the upstate and downstate correspond to the microscopic and mesoscopic recordings. Combined neural modeling and forward computations are needed to relate hypothesized mechanisms to EEG and MEG recordings. The proposed studies will yield a deep understanding of these fundamental states of the human cortex, computationally integrating animal with human recordings made at the channel, neuronal, circuit, system, and non-invasive whole-brain levels. Although the specific goal of this research proposal is to understand fundamental cortical functional states, further research based on the models could be applied to abnormal EEG/MEG from patients with sleep disorders, to predict the mechanisms that may be responsible for the observed abnormalities. The KC may function to prevent awakening; knowing its neural basis could lead to better treatment of insomnia. Most evidence suggests that the SO is the essential activity underlying the restorative processes of sleep. The SO also appears to play a central role in the consolidation of memories acquired in the preceding day. Sleep disorders have a causal relationship with reduced neurocognitive functions as well as variety of adverse physiologic and long-term health outcomes including all-cause mortality, diabetes, and cardiovascular disease. Over 30% of the general population complains about sleep-related problems. Sleep disorders - notably sleep apnea, sleep deprivation and sleepiness - affect 70 million Americans, resulting in $16 billion in annual healthcare expenses and $50 billion in lost productivity. In addition to significant economic benefits from healthcare, educational benefits include the training of graduate students and undergraduates who will be participating in the research. All of the software for running the models will be shared with other researchers and will be available through the internet in accordance with University policies. The new cross-disciplinary collaborations that will be established by the proposed research will lead to cross-disciplinary training of graduate students and postdoctoral fellows and will involve underrepresented groups and minorities. In addition to scientific presentations at meetings and lectures, the results of th research will be incorporated into teaching modules that could be used by K-12 teachers, in conjunction with the NSF sponsored Science of Learning Center at UCSD co-directed by Sejnowski. Intracranial recordings from humans are performed at Massachusetts General Hospital (MGH- Cash), New York Univ. (NYU- Thesen), Marseille (Chauvel), and Budapest (Ulbert). MEG/EEG recordings occur at UCSD (Halgren). Analysis and modeling occur at UC Riverside (UCR- Bazhenov), Paris (Destexhe), and UCSD (the central site- Halgren, Sejnowski, Dale and Hagler).

Abstract
Nontechnical:
Electrophysiological clinical mapping of brain activity has high spatial resolution and high sensitivity that supersedes other noninvasive techniques such as functional magnetic resonance imaging (fMRI). This clinical procedure is important for a large population of patients with neurological disorders that either do not respond to drugs or have adverse side effects such as in medically intractable epilepsy. It also has promising applications in brain-machine interfaces. The majority of electrophysiological devices utilize noble metals as the contact interface with brain tissue, and these metal electrodes detect ionic currents and potentials by either surface redox reactions or capacitive charge screening. Organic electrodes on the other hand are permeable to ions and allow volumetric redox reactions and capacitive coupling of brain activity. This superior electrochemical performance allows organic electrodes to resolve minute potentials from the brain which has implications for better understanding and treatment of neurological diseases. But their superior characteristics fade with time due to instability of the bonding interface between the organic electrode and the underlying metal pads that carry the signals to the outside world. This project aims at improving the stability of these organic electrodes by developing novel fabrication procedures that can extend their superior performance for several years.

Technical:
This project combines expertise in electronic materials processing, electrophysiological recording from humans, and data analysis in order to develop new geometries of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate microelectrodes. Device geometries that can result in the lowest electrochemical impedances and highest electrochemical stability will be developed and characterized with accelerated aging experiments in-vitro. Impedance and cyclic current-voltage characterization will be monitored over the course of several weeks while the microelectrodes are immersed in saline solution at high temperatures. Surface and cross-section scanning electron microscopy and atomic force microscopy will be utilized to assess the morphological stability of these microelectrodes and will inform the device fabrication to develop stable interfaces. The research is integrated with an educational plan for students with a central focus on biomedical implant devices as well as on the burgeoning field of neuro-technology. The plan includes extensive education and training programs for undergraduate and graduate students, with an emphasis on minority, female, and other underrepresented groups. If successful, the devices will broadly impact how we understand the brain, diagnose diseased regions of the brain, and advance the development of brain implants potentially opening access to such information to broader societal populations.

Project Summary/Abstract The electroencephalogram (EEG) and magnetoencephalogram (MEG) are directly and instantaneously coupled to the currents across cortical neuronal membranes which mediate information processing. They are widely used for both clinical diagnosis and for investigating the neural mechanisms of cognition with excellent temporal resolution. The goal of this application is to advance our understanding of the relationships between brain imaging signals at the macroscopic levels ? EEG and MEG - and the underlying circuits and cellular activity at the fine-grained scales. To address this goal, we propose to develop sophisticated computational neural models that are consistent with the large amount of data we already have concerning the synaptic and active currents in cortical neurons, their connections with each other and with the thalamus and the other brain structures, their organization in layers and columns, and areas, and their interconnections between areas (Bazhenov). This model will generate characteristic sleep and wake activity including oscillations and less organized rhythms. We will combine the neural model with biophysical models to calculate the consequent population phenomena (Halgren, Bazhenov). At a local level, transmembrane currents combined with cellular architecture and arrangement result in current source density, local field potentials and equivalent current dipoles, whose spatial arrangement, correlation and phase produce MEG and EEG. Transmembrane currents are calculated using populations of realistic multi-compartment neurons (Bazhenov), which are realistically mapped to actual reconstructed cortical surfaces, and propagated to extracranial sensors using realistic biophysical models (Halgren). We will refine and test the model using novel empirical analyses of large numbers of intracranial micro- and macro-array recordings, quantifying their amplitude, coherence, and phase-lag (Cash, Davis and Pati). To complete the loop, we will develop a novel inverse solution approach to acquire local level population activity from EEG/MEG data (Halgren, Dale) and we will link this activity back to the neuron and synapse level processes using computer models (Bazhenov). By establishing bidirectional links between circuits and cellular level activity generated by the model and predicted EEG and MEG signals validated by data, we will derive a set of predictions regarding what human EEG and MEG measurements can tell us about underlying cellular and synaptic level activity in empirical studies. We propose to use combined neural and biophysical modeling, confirmed with extensive intracranial recordings, as a framework allowing the principled quantitative integration of the many pertinent anatomical, physiological and neurobiological findings. The articulated model will thus embody our best current understanding of how EEG and MEG are generated. In addition, we will obtain for the first time the essential cortical information needed to empirically model the neural origins of EEG and MEG.

Project Abstract Electrical stimulation is widely used to activate and/or disrupt neuronal activity. Despite its critical importance in experimental and clinical neuroscience, at present, there is no validated method to predict which neural elements of the brain will be activated by a given stimulation regime. Based on our pilot studies, we propose here to develop a novel computational approach for predicting the specific neurons which will be activated by a given stimulation protocol, based on neuron shape, location, type and connectivity. We will use biophysical modeling to calculate the spatial distribution of activating currents, and then convolve this distribution with the spatial distribution and orientation of the axons and dendrites of the major pyramidal and interneuron cell types to determine their probability of firing. We will then propagate this activity through the cortical circuitry. We will model different species (rats, mice, humans) and cortical areas (primary sensory and associative). We will examine the effects of sleep stage and background activity, including characteristic sleep rhythms, on the evoked thalamocortical network activity. The predictions of the model will be validated with extensive empirical measurements, primarily calcium imaging in mice using advanced microscopy methods that allow the entire relevant cortical volume to be characterized at high resolution. Cell type specific labeling and anatomical reconstructions will permit identification of different neuronal populations and measurement of their activation probability. This will be supplemented by voltage-sensitive dye imaging and laminar electrophysiological recordings to provide temporal resolution. The laminar recordings will be repeated in humans, in both acute intraoperative and semi-chronic settings. The models will be modified in light of the validation studies. The integrated biophysical and neural model with documentation and tutorials will be made available on the web.