Christopher J. Rennie

Brain maturation in adolescence: concurrent changes in neuroanatomy and neurophysiology.

Adolescence to early adulthood is a period of dramatic transformation in the healthy human brain. However, the relationship between the concurrent structural and functional changes remains unclear. We investigated the impact of age on both neuroanatomy and neurophysiology in the same healthy subjects (n = 138) aged 10 to 30 years using magnetic resonance imaging (MRI) and resting electroencephalography (EEG) recordings. MRI data were segmented into gray and white matter images and parcellated into large‐scale regions of interest. Absolute EEG power was quantified for each lobe for the slow‐wave, alpha and beta frequency bands. Gray matter volume was found to decrease across the age bracket in the frontal and parietal cortices, with the greatest change occurring in adolescence. EEG activity, particularly in the slow‐wave band, showed a similar curvilinear decline to gray matter volume in corresponding cortical regions. An inverse pattern of curvilinearly increasing white matter volume was observed in the parietal lobe. We suggest that the reduction in gray matter primarily reflects a reduction of neuropil, and that the corresponding elimination of active synapses is responsible for the observed reduction in EEG power. Hum Brain Mapp, 2007.

Integrative Neuroscience: The Role of a Standardized Database

Most brain related databases bring together specialized information, with a growing number that include neuroimaging measures. This article outlines the potential use and insights from the first entirely standardized and centralized database, which integrates information from neuroimaging measures (EEG, event related potential (ERP), structural/functional MRI), arousal (skin conductance responses (SCR)s, heart rate, respiration), neuropsychological and personality tests, genomics and demographics: The Brain Resource International Database. It comprises data from over 2,000 “normative” subjects and a growing number of patients with neurological and psychiatric illnesses, acquired from over 50 laboratories (in the USA, United Kingdom, Holland, South Africa, Israel and Australia), all with identical equipment and experimental procedures. Three primary goals of this database are to quantify individual differences in normative brain function, to compare an individuals performance to their database peers, and to provide a robust normative framework for clinical assessment and treatment prediction. We present three example demonstrations in relation to these goals. First, we show how consistent age differences may be quantified when large subject numbers are available, using EEG and ERP data from nearly 2,000 stringently screened normative subjects. Second, the use of a normalization technique provides a means to compare clinical subjects (50 ADHD subjects in this study) to the normative database with the effects of age and gender taken into account. Third, we show how a profile of EEG/ERP and autonomic measures potentially provides a means to predict treatment response in ADHD subjects. The example data consists of EEG under eyes open and eyes closed and ERP data for auditory oddball, working memory and Go-NoGo paradigms. Autonomic measures of skin conductance (tonic skin conductance level, SCL, and phasic skin conductance responses, SCRs) were acquired simultaneously with central EEG/ERP measures. The findings show that the power of large samples, tested using standardized protocols, allows for the quantification of individual differences that can subsequently be used to control such variation and to enhance the sensitivity and specificity of comparisons between normative and clinical groups. In terms of broader significance, the combination of size and multidimensional measures tapping the brains core cognitive competencies, may provide a normative and evidence-based framework for individually-based assessments in “Personalized Medicine.”

Unified neurophysical model of EEG spectra and evoked potentials

Abstract. Evoked potentials – the brains transient electrical responses to discrete stimuli – are modeled as impulse responses using a continuum model of brain electrical activity. Previous models of ongoing brain activity are refined by adding an improved model of thalamic connectivity and modulation, and by allowing for two populations of excitatory cortical neurons distinguished by their axonal ranges. Evoked potentials are shown to be modelable as an impulse response that is a sum of component responses. The component occurring about 100 ms poststimulus is attributed to sensory activation, and this, together with positive and negative feedback pathways between the cortex and thalamus, results in subsequent peaks and troughs that semiquantitatively reproduce those of observed evoked potentials. Modulation of the strengths of positive and negative feedback, in ways consistent with psychological theories of attentional focus, results in d istinct responses resembling those seen in experiments involving attentional changes. The modeled impulse responses reproduce key features of typical experimental evoked response potentials: timing, relative amplitude, and number of peaks. The same model, with further modulation of feedback, also reproduces experimental spectra. Together, these results mean that a broad range of ongoing and transient electrocortical activity can be understood within a common framework, which is parameterized by values that are directly related to physiological and anatomical quantities.

Mode of Functional Connectivity in Amygdala Pathways Dissociates Level of Awareness for Signals of Fear

Many of the same regions of the human brain are activated during conscious attention to signals of fear and in the absence of awareness for these signals. The neural mechanisms that dissociate level of awareness from activation in these regions remain unknown. Using functional magnetic resonance imaging with connectivity analysis in healthy human subjects, we demonstrate that level of awareness for signals of fear depends on mode of functional connectivity in amygdala pathways rather than discrete patterns of activation in these pathways. Awareness for fear relied on negative connectivity within both cortical and subcortical pathways to the amygdala, suggesting that reentrant feedback may be necessary to afford such awareness. In contrast, responses to fear in the absence of awareness were supported by positive connections in a direct subcortical pathway to the amygdala, consistent with the view that excitatory feedforward connections along this pathway may be sufficient for automatic responses to “unseen” fear.

Estimation of multiscale neurophysiologic parameters by electroencephalographic means.

It is shown that new model‐based electroencephalographic (EEG) methods can quantify neurophysiologic parameters that underlie EEG generation in ways that are complementary to and consistent with standard physiologic techniques. This is done by isolating parameter ranges that give good matches between model predictions and a variety of experimental EEG‐related phenomena simultaneously. Resulting constraints range from the submicrometer synaptic level to length scales of tens of centimeters, and from timescales of around 1 ms to 1 s or more, and are found to be consistent with independent physiologic and anatomic measures. In the process, a new method of obtaining model parameters from the data is developed, including a Monte Carlo implementation for use when not all input data are available. Overall, the approaches used are complementary to other methods, constraining allowable parameter ranges in different ways and leading to much tighter constraints overall. EEG methods often provide the most restrictive individual constraints. This approach opens a new, noninvasive window on quantitative brain analysis, with the ability to monitor temporal changes, and the potential to map spatial variations. Unlike traditional phenomenologic quantitative EEG measures, the methods proposed here are based explicitly on physiology and anatomy. Hum. Brain Mapping 23:53–72, 2004.

Decomposing skin conductance into tonic and phasic components

Overlapping phasic skin conductance responses (SCRs) obtained using short interstimulus interval (ISI) paradigms such as those employed in cognitive research, confound measurement of each discrete phasic SCR as well as the tonic skin conductance level (SCL). We report a method of resolving this problem using a modelling technique that takes advantage of the stereotyped nature of the within-subject SCR waveform. A four-parameter sigmoid-exponential SCR model that describes the entire response, was developed and extended to five-, six- and eight-parameter skin conductance (SC) models. These SC models were successfully curve-fitted to more than 60 SC segments, each containing one SCR or two overlapping SCRs on a sloping baseline obtained from 20 normal subjects. The SC segments were consequently decomposed into their components: the tail of the previous response, one or two SCRs and the SCL. The SCRs free of the complication of overlap were then quantified. The raw SCRs of the same data set were also measured using a standard method. The standard measurement showed a significant reduction of 15% in amplitude and 140 ms in peak latency compared to our method. The basic four SCR model parameters--onset time, rise time, decay time constant and gain--showed increasing inter-subject variability in that order. These SCR model parameters may be studied as variables in normal and patient groups and as indices of treatment response. This quantitative method also provides a means to assess the relationships between central and autonomic psychophysiologic measures.

Multiscale brain modelling

A central difficulty of brain modelling is to span the range of spatio-temporal scales from synapses to the whole brain. This paper overviews results from a recent model of the generation of brain electrical activity that incorporates both basic microscopic neurophysiology and large-scale brain anatomy to predict brain electrical activity at scales from a few tenths of a millimetre to the whole brain. This model incorporates synaptic and dendritic dynamics, nonlinearity of the firing response, axonal propagation and corticocortical and corticothalamic pathways. Its relatively few parameters measure quantities such as synaptic strengths, corticothalamic delays, synaptic and dendritic time constants, and axonal ranges, and are all constrained by independent physiological measurements. It reproduces quantitative forms of electroencephalograms seen in various states of arousal, evoked response potentials, coherence functions, seizure dynamics and other phenomena. Fitting model predictions to experimental data enables underlying physiological parameters to be inferred, giving a new non-invasive window into brain function that complements slower, but finer-resolution, techniques such as fMRI. Because the parameters measure physiological quantities relating to multiple scales, and probe deep structures such as the thalamus, this will permit the testing of a range of hypotheses about vigilance, cognition, drug action and brain function. In addition, referencing to a standardized database of subjects adds strength and specificity to characterizations obtained.

Neurophysical Modeling of Brain Dynamics

A recent neurophysical model of brain electrical activity is outlined and applied to EEG phenomena. It incorporates single-neuron physiology and the large-scale anatomy of corticocortical and corticothalamic pathways, including synaptic strengths, dendritic propagation, nonlinear firing responses, and axonal conduction. Small perturbations from steady states account for observed EEGs as functions of arousal. Evoked response potentials (ERPs), correlation, and coherence functions are also reproduced. Feedback via thalamic nuclei is critical in determining the forms of these quantities, the transition between sleep and waking, and stability against seizures. Many disorders correspond to significant changes in EEGs, which can potentially be quantified in terms of the underlying physiology using this theory. In the nonlinear regime, limit cycles are often seen, including a regime in which they have the characteristic petit mal 3 Hz spike-and-wave form.

Does the N100 evoked potential really habituate? Evidence from a paradigm appropriate to a clinical setting

This study examined the N100 component of the event related potential in a habituation paradigm with short interstimulus intervals. The paradigm was designed to be relatively brief in duration (approx. 4 min for each of two conditions), so that it could be used for clinical populations with cognitive dysfunction, in which compliance may be a problem with long paradigms. Two conditions - Ignore and Attend - were employed with normal subjects. In each condition, 15 stimulus trains, each consisting of 10 innocuous tones, were presented. The eighth tone was a change stimulus. There was a fixed interstimulus interval of 1.1 s and an inter-train interval of 5 s. From the perspective of traditional Orienting Response theory, evidence was sought for within-train habituation in terms of diminished N100 amplitude to repeated stimuli, response recovery to the change stimulus, and dishabituation of the response to the following standard stimuli. Habituation was suggested by significant decreases of approx. 50% with stimulus repetition, and response recovery to the change stimulus in both conditions. However, there was no evidence of dishabituation following the change stimulus. These results confirm that N100 fails to meet the formal requirements of response habituation, suggesting instead that it may index an earlier process than the Orienting Response.

Dynamics of SCR, EEG, and ERP activity in an oddball paradigm with short interstimulus intervals

Studies of concurrent central, and autonomic activity using a conventional event-related potential (ERP) oddball paradigms, are considered useful in elucidating the relationship between central and autonomic responses, but the autonomic response tends to overlap. A new method was used to decompose and score overlapping skin conductance responses (SCR). This method enabled examination of dynamic relationships of phasic SCR, prestimulus electroencephalogram (EEG), and ERP to auditory target stimuli in 50 normal adults. SCR amplitude was negatively correlated to EEG and N200 amplitude. The SCR amplitude changes over time exhibited an exponential decline opposite to those of N200, alpha, and beta. All the fitted exponential functions had a time constant of 1-2 min. The findings suggest that a N200 component, active in the auditory sensory discrimination, is concomitant with the SCR. The narrow range of the time constant may provide a clue to the conjoint processes underlying central and autonomic adaptive functions.