Applying fMRI complexity analyses to the single subject: a case study for proposed neurodiagnostics.

Nonlinear dynamic tools have been statistically validated at the group level to identify subtle differences in system wide regulation of brain meso-circuits, often increasing clinical sensitivity over conventional analyses alone. We explored the feasibility of extracting information at the single-subject level, illustrating two pairs of healthy individuals with psychological differences in stress reactivity. We applied statistical and nonlinear dynamic tools to capture key characteristics of the prefrontal-limbic loop. We compared single subject results with statistical results for the larger group. We concluded that complexity analyses may identify important differences at the single-subject level, supporting their potential towards neurodiagnostic applications.

Human gender differences in the perception of conspecific alarm chemosensory cues.

It has previously been established that, in threatening situations, animals use alarm pheromones to communicate danger. There is emerging evidence of analogous chemosensory "stress" cues in humans. For this study, we collected alarm and exercise sweat from "donors," extracted it, pooled it and presented it to 16 unrelated "detector" subjects undergoing fMRI. The fMRI protocol consisted of four stimulus runs, with each combination of stimulus condition and donor gender represented four times. Because olfactory stimuli do not follow the canonical hemodynamic response, we used a model-free approach. We performed minimal preprocessing and worked directly with block-average time series and step-function estimates. We found that, while male stress sweat produced a comparably strong emotional response in both detector genders, female stress sweat produced a markedly stronger arousal in female than in male detectors. Our statistical tests pinpointed this gender-specificity to the right amygdala (strongest in the superficial nuclei). When comparing the olfactory bulb responses to the corresponding stimuli, we found no significant differences between male and female detectors. These imaging results complement existing behavioral evidence, by identifying whether gender differences in response to alarm chemosignals are initiated at the perceptual versus emotional level. Since we found no significant differences in the olfactory bulb (primary processing site for chemosensory signals in mammals), we infer that the specificity in responding to female fear is likely based on processing meaning, rather than strength, of chemosensory cues from each gender.

Power spectrum scale invariance identifies prefrontal dysregulation in paranoid schizophrenia.

Theory and experimental evidence suggest that complex living systems function close to the boundary of chaos, with erroneous organization to an improper dynamical range (too stiff or chaotic) underlying system-wide dysregulation and disease. We hypothesized that erroneous organization might therefore also characterize paranoid schizophrenia, via optimization abnormalities in the prefrontal-limbic circuit regulating emotion. To test this, we acquired fMRI scans from 35 subjects (N = 9 patients with paranoid schizophrenia and N = 26 healthy controls), while they viewed affect-valent stimuli. To quantify dynamic regulation, we analyzed the power spectrum scale invariance (PSSI) of fMRI time-courses and computed the geometry of time-delay (Poincaré) maps, a measure of variability. Patients and controls showed distinct PSSI in two clusters (k(1) : Z = 4.3215, P = 0.00002 and k(2) : Z = 3.9441, P = 0.00008), localized to the orbitofrontal/medial prefrontal cortex (Brodmann Area 10), represented by ß close to white noise in patients (ß ≈ 0) and in the pink noise range in controls (ß ≈ -1). Interpreting the meaning of PSSI differences, the Poincaré maps indicated less variability in patients than controls (Z = -1.9437, P = 0.05 for k(1) ; Z = -2.5099, P = 0.01 for k(2) ). That the dynamics identified Brodmann Area 10 is consistent with previous schizophrenia research, which implicates this area in deficits of working memory, executive functioning, emotional regulation and underlying biological abnormalities in synaptic (glutamatergic) transmission. Our results additionally cohere with a large body of work finding pink noise to be the normal range of central function at the synaptic, cellular, and small network levels, and suggest that patients show less supple responsivity of this region.

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model.

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.

A principal component network analysis of prefrontal-limbic functional magnetic resonance imaging time series in schizophrenia patients and healthy controls.

We investigated neural regulation of emotional arousal. We hypothesized that the interactions between the components of the prefrontal-limbic system determine the global trajectories of the individual's brain activation, with the strengths and modulations of these interactions being potentially key components underlying the differences between healthy individuals and those with schizophrenia. Using affect-valent facial stimuli presented to 11 medicated schizophrenia patients and 65 healthy controls, we activated neural regions associated with the emotional arousal response during functional magnetic resonance imaging (fMRI). Performing first a random effects analysis of the fMRI data to identify activated regions, we obtained 352 data-point time series for six brain regions: bilateral amygdala, hippocampus and two prefrontal regions (Brodmann Areas 9 and 45). Since standard statistical methods are not designed to capture system features and evolution, we used principal component analyses on two types of pre-processed data: contrasts and group averages. We captured an important characteristic of the evolution of our six-dimensional brain network: all subject trajectories are almost embedded in a two-dimensional plane. Moreover, the direction of the largest principal component was a significant differentiator between the control and patient populations: the left and right amygdala coefficients were substantially higher in the case of patients, and the coefficients of Brodmann Area 9 were, to a lesser extent, higher in controls. These results are evidence that modulations between the regions of interest are the important determinant factors for the system's dynamical behavior. We place our results within the context of other principal component analyses used in neuroimaging, as well as of our existing theoretical model of prefrontal-limbic dysregulation.

A systems approach to prefrontal-limbic dysregulation in schizophrenia.

INTRODUCTION: Using a prefrontal-limbic dysregulation model for schizophrenia, we tested whether a dynamic control systems approach in conjunction with neuroimaging might increase detection sensitivity in characterizing the illness. Our analyses were modeled upon diagnostic tests for other dysregulatory diseases, such as diabetes, in which trajectories for the excitatory and inhibitory components of the negative feedback loops that reestablish homeostasis are measured after system perturbation. We hypothesized that these components would show distinct coupling dynamics within the patient population, as compared to healthy controls, and that these coupling dynamics could be quantified statistically using cross-correlations between excitatory and inhibitory time series using fMRI. METHODS: As our perturbation, we activated neural regions associated with the emotional arousal response, using affect-valent facial stimuli presented to 11 schizophrenic patients (all under psychotropic medication) and 65 healthy controls (including 11 individuals age- and sex-matched to the patients) during fMRI scanning. We first performed a random-effects analysis of the fMRI data to identify activated regions. Those regions were then analyzed for group differences, using both standard analyses with respect to the time series peaks, as well as a dynamic analysis that looked at cross-correlations between excitatory and inhibitory time series and group differences over the entire time series. RESULTS: Patients and controls showed significant differences in signal dynamics between excitatory and inhibitory components of the negative feedback loop that controls emotional arousal, specifically between the right amygdala and Brodmann area 9 (BA9), when viewing angry facial expressions (p = 0.002). Further analyses were performed with respect to activation amplitudes for these areas in response to angry faces, both over the entire time series as well as for each time point along the time series. While the amygdala responses were not significantly different between groups, patients showed significantly lower BA9 activation during the beginning of the response (0.000