NFTsim: Theory and Simulation of Multiscale Neural Field Dynamics.

A user ready, portable, documented software package, NFTsim, is presented to facilitate numerical simulations of a wide range of brain systems using continuum neural field modeling. NFTsim enables users to simulate key aspects of brain activity at multiple scales. At the microscopic scale, it incorporates characteristics of local interactions between cells, neurotransmitter effects, synaptodendritic delays and feedbacks. At the mesoscopic scale, it incorporates information about medium to large scale axonal ranges of fibers, which are essential to model dissipative wave transmission and to produce synchronous oscillations and associated cross-correlation patterns as observed in local field potential recordings of active tissue. At the scale of the whole brain, NFTsim allows for the inclusion of long range pathways, such as thalamocortical projections, when generating macroscopic activity fields. The multiscale nature of the neural activity produced by NFTsim has the potential to enable the modeling of resulting quantities measurable via various neuroimaging techniques. In this work, we give a comprehensive description of the design and implementation of the software. Due to its modularity and flexibility, NFTsim enables the systematic study of an unlimited number of neural systems with multiple neural populations under a unified framework and allows for direct comparison with analytic and experimental predictions. The code is written in C++ and bundled with Matlab routines for a rapid quantitative analysis and visualization of the outputs. The output of NFTsim is stored in plain text file enabling users to select from a broad range of tools for offline analysis. This software enables a wide and convenient use of powerful physiologically-based neural field approaches to brain modeling. NFTsim is distributed under the Apache 2.0 license.

Integrating "brain" and "body" measures: correlations between EEG and metabolic changes over the human lifespan.

AIMS: This study investigated the relationship between electroencephalograph (EEG) power and basal metabolic rate (BMR) over the human lifespan, to better understand the mechanisms involved in the decline of neural activity with age. METHODS: Eyes-open EEG power was calculated in standard frequency bands and averaged across recording sites in 1831 healthy subjects aged 6 to 86 years, from the Brain Resource International Database. In a subset of 175 subjects, structural MRI scans were also undertaken to determine the role of grey matter. Cerebral metabolic rate (CMR) was estimated using two models of EEG power, based on: (1) normalization of BMR by total body mass, and (2) scaling by cortical grey matter. RESULTS: Regression analysis revealed a linear relationship between the CMR estimates and EEG power under both models. In the full sample, CMR explained 65% of the variance in delta power, and 53% of the variance in theta power over the age span. DISCUSSION: The results demonstrate that the large EEG signals in early childhood are associated with a higher BMR during that age. INTEGRATIVE SIGNIFICANCE: The use of cross-modal measurements in this study highlights the utility of capturing data in an integrative framework to reveal fundamental physiological relationships.

Integrating objective gene-brain-behavior markers of psychiatric disorders.

There is little consensus about which objective markers should be used to assess major psychiatric disorders, and predict/evaluate treatment response for these disorders. Clinical practice relies instead on subjective signs and symptoms, such that there is a "translational gap" between research findings and clinical practice. This gap arises from: a) a lack of integrative theoretical models which provide a basis for understanding links between gene-brain-behavior mechanisms and clinical entities; b) the reliance on studying one measure at a time so that linkages between markers are their specificity are not established; and c) the lack of a definitive understanding of what constitutes normative function. Here, we draw on a standardized methodology for acquiring multiple sources of genomic, brain and behavioral data in the same subjects, to propose candidate markers of selected psychiatric disorders: depression, post-traumatic stress disorder, schizophrenia, attention-deficit/hyperactivity disorder and dementia disorders. This methodology has been used to establish a standardized international database which provides a comprehensive framework and the basis for testing hypotheses derived from an integrative theoretical model of the brain. Using this normative base, we present preliminary findings for a number of disorders in relation to the proposed markers. Establishing these objective markers will be the first step towards determining their sensitivity, specificity and treatment prediction in individual patients.

The impact of melancholia versus non-melancholia on resting-state, EEG alpha asymmetry: electrophysiological evidence for depression heterogeneity.

While depression has been associated with relatively greater right than left frontal cortical activity - a neurophysiological marker reflecting greater activation of the withdrawal system - contradictory findings have been reported. It was hypothesised that melancholia would be associated with relative right frontal activation, in comparison to non-melancholia and controls. We collected 2-min of resting-state, eyes closed, electroencephalographic activity from a total of 237 participants including 117 patients with major depressive disorder (57 with melancholia, 60 with non-melancholia) and 120 healthy controls. In contrast to hypotheses, patients with non-melancholia displayed relative left frontal activation in comparison to controls and those with melancholia. These findings were associated with a small to moderate effect size (Cohen's d=0.30-0.34). Critically, patients with melancholic subtype did not differ from controls despite increased severity - relative to those with non-melancholia - on clinical measures. These results may reflect an increase in approach tendencies in patients with non-melancholia including reassurance seeking, anger or irritable aggression. Findings highlight the need for further research on the heterogeneity MDD.