A BOLD search for baseline

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

Intensity patterns at the peaks of brain activity in fMRI and PET are highly correlated with neural models of spatial integration

Spatial integration during the brain's cognitive activity prompts changes in energy used by different neuroglial populations. Nevertheless, the organisation of such integration in 3D ‐brain activity remains undescribed from a quantitative standpoint. In response, we applied a cross‐correlation between brain activity and integrative models, which yielded a deeper understanding of information integration in functional brain mapping. We analysed four datasets obtained via fundamentally different neuroimaging techniques (functional magnetic resonance imaging [fMRI] and positron emission tomography [PET]) and found that models of spatial integration with an increasing input to each step of integration were significantly more correlated with brain activity than models with a constant input to each step of integration. In addition, marking the voxels with the maximal correlation, we found exceptionally high intersubject consistency with the initial brain activity at the peaks. Our method demonstrated for the first time that the network of peaks of brain activity is organised strictly according to the models of spatial integration independent of neuroimaging techniques. The highest correlation with models integrating an increasing at each step input suggests that brain activity reflects a network of integrative processes where the results of integration in some neuroglial populations serve as an input to other neuroglial populations.

Multitask fMRI and machine learning approach improve prediction of differential brain activity pattern in patients with insomnia disorder

We investigated the differential spatial covariance pattern of blood oxygen level-dependent (BOLD) responses to single-task and multitask functional magnetic resonance imaging (fMRI) between patients with psychophysiological insomnia (PI) and healthy controls (HCs), and evaluated features generated by principal component analysis (PCA) for discrimination of PI from HC, compared to features generated from BOLD responses to single-task fMRI using machine learning methods. In 19 patients with PI and 21 HCs, the mean beta value for each region of interest (ROIbval) was calculated with three contrast images (i.e., sleep-related picture, sleep-related sound, and Stroop stimuli). We performed discrimination analysis and compared with features generated from BOLD responses to single-task fMRI. We applied support vector machine analysis with a least absolute shrinkage and selection operator to evaluate five performance metrics: accuracy, recall, precision, specificity, and F2. Principal component features showed the best classification performance in all aspects of metrics compared to BOLD response to single-task fMRI. Bilateral inferior frontal gyrus (orbital), right calcarine cortex, right lingual gyrus, left inferior occipital gyrus, and left inferior temporal gyrus were identified as the most salient areas by feature selection. Our approach showed better performance in discriminating patients with PI from HCs, compared to single-task fMRI.

A Non-cognitive Behavioral Model for Interpreting Functional Neuroimaging Studies

The dominant model for interpreting brain imaging experiments, which we refer to as the Standard Cognitive Model (SCM), assumes that the brain is organized in support of mental processes that control behavior. However, functional neuroimaging experiments of cognitive tasks have not shown clear anatomic segregation between mental processes originally proposed by this model. This failing has been blamed on limitations in imaging technology and non-linearity in the brain's implementation of these processes. However, the validity of the underlying cognitive models used to describe the brain has rarely been questioned or directly tested against imaging results. We propose an alternative model of brain function, that we term the Non-cognitive Behavioral Model (NBM), which correlates observed human behavior directly with measured brain activity without making assumptions about intervening cognitive processes. Our model derives from behavioral psychology but is extended to include brain activity, in addition to behavior, as observables. A further extension is the role of neuroplasticity, as opposed to innate cognitive processes, in developing the brain's support of cognitive behavior. We present the theoretical basis with which the SCM maps cognitive processes onto functional magnetic resonance and positron emission tomography images and compare and contrast with the NBM. We also describe how the NBM can be used experimentally to study how the brain supports behavior. Two applications are presented that support the usefulness of the NBM. In one, the NBM use of the total functional imaging signal (not just the differences between states) provides a stronger correlation of neural activity with the behavioral state of consciousness than the SCM approach in both anesthesia and coma. The second example reviews studies of facial and object recognition that provide evidence for the NBM proposal that neuroplasticity and experience play key roles in the brain's support of recognition and other behaviors. The conclusions regarding neuroplasticity are then generalized to explain the incomplete functional segregation observed in the application of the SCM to neuroimaging.

State-Dependent Changes in Brain Glycogen Metabolism

A fundamental understanding of glycogen structure, concentration, polydispersity and turnover is critical to qualify the role of glycogen in the brain. These molecular and metabolic features are under the control of neuronal activity through the interdependent action of neuromodulatory tone, ionic homeostasis and availability of metabolic substrates, all variables that concur to define the state of the system. In this chapter, we briefly describe how glycogen responds to selected behavioral, nutritional, environmental, hormonal, developmental and pathological conditions. We argue that interpreting glycogen metabolism through the lens of brain state is an effective approach to establish the relevance of energetics in connecting molecular and cellular neurophysiology to behavior.

Advances in Imaging Brain Metabolism

Metabolism is central to neuroimaging because it can reveal pathways by which neuronal and glial cells use nutrients to fuel their growth and function. We focus on advanced magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) methods used in brain metabolic studies. ¹⁷O-MRS and ³¹P-MRS, respectively, provide rates of oxygen use and ATP synthesis inside mitochondria, whereas ¹⁹F-MRS enables measurement of cytosolic glucose metabolism. Calibrated functional MRI (fMRI), an advanced form of fMRI that uses contrast generated by deoxyhemoglobin, provides maps of oxygen use that track neuronal firing across brain regions. ¹³C-MRS is the only noninvasive method of measuring both glutamatergic neurotransmission and cell-specific energetics with signaling and nonsignaling purposes. Novel MRI contrasts, arising from endogenous diamagnetic agents and exogenous paramagnetic agents, permit pH imaging of glioma. Overall, these magnetic resonance methods for imaging brain metabolism demonstrate translational potential to better understand brain disorders and guide diagnosis and treatment.

Calibrated imaging reveals altered grey matter metabolism related to white matter microstructure and symptom severity in multiple sclerosis

Multiple sclerosis (MS) involves damage to white matter microstructures. This damage has been related to grey matter function as measured by standard, physiologically-nonspecific neuroimaging indices (i.e., blood-oxygen-level dependent signal [BOLD]). Here, we used calibrated functional magnetic resonance imaging and diffusion tensor imaging to examine the extent to which specific, evoked grey matter physiological processes were associated with white matter diffusion in MS. Evoked changes in BOLD, cerebral blood flow (CBF), and oxygen metabolism (CMRO₂ ) were measured in visual cortex. Individual differences in the diffusion tensor measure, radial diffusivity, within occipital tracts were strongly associated with MS patients' BOLD and CMRO₂ . However, these relationships were in opposite directions, complicating the interpretation of the relationship between BOLD and white matter microstructural damage in MS. CMRO₂ was strongly associated with individual differences in patients' fatigue and neurological disability, suggesting that alterations to evoked oxygen metabolic processes may be taken as a marker for primary symptoms of MS. This work demonstrates the first application of calibrated and diffusion imaging together and details the first application of calibrated functional MRI in a neurological population. Results lend support for neuroenergetic hypotheses of MS pathophysiology and provide an initial demonstration of the utility of evoked oxygen metabolism signals for neurology research. Hum Brain Mapp 38:5375-5390, 2017. © 2017 Wiley Periodicals, Inc.

Attention and Working Memory in Adolescents with Autism Spectrum Disorder: A Functional MRI Study

The present study examined attention and memory load-dependent differences in the brain activation and deactivation patterns between adolescents with autism spectrum disorders (ASDs) and typically developing (TD) controls using functional magnetic resonance imaging. Attentional (0-back) and working memory (WM; 2-back) processing and load differences (0 vs. 2-back) were analysed. WM-related areas activated and default mode network deactivated normally in ASDs as a function of task load. ASDs performed the attentional 0-back task similarly to TD controls but showed increased deactivation in cerebellum and right temporal cortical areas and weaker activation in other cerebellar areas. Increasing task load resulted in multiple responses in ASDs compared to TD and in inadequate modulation of brain activity in right insula, primary somatosensory, motor and auditory cortices. The changes during attentional task may reflect compensatory mechanisms enabling normal behavioral performance. The inadequate memory load-dependent modulation of activity suggests diminished compensatory potential in ASD.

Using fMRI to study reward processing in humans: past, present, and future

Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for1) the corroboration of significant animal findings in the human brain, and2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies.

A Trio of Concerns

This essay assesses the two most significant changes in psychology over the past century: the attempt to localize psychological phenomena in restricted brain sites and the search for genetic contributions to behavior and psychopathology. Although there are advantages to these new developments, they are accompanied by some questionable assumptions. Because the investigators in these domains often relate variation in their biological measures to variation in personality traits evaluated with questionnaires, an analysis of the unique properties of the verbalreport questionnaires is presented. It is suggested that future research on human personality should try to combine semantic reports with behaviors and biological data in order to arrive at more fruitful constructs.

Cortical network models of impulse firing in the resting and active states predict cortical energetics

Measurements of the cortical metabolic rate of glucose oxidation [CMR(glc(ox))] have provided a number of interesting and, in some cases, surprising observations. One is the decline in CMR(glc(ox)) during anesthesia and non-rapid eye movement (NREM) sleep, and another, the inverse relationship between the resting-state CMR(glc(ox)) and the transient following input from the thalamus. The recent establishment of a quantitative relationship between synaptic and action potential activity on the one hand and CMR(glc(ox)) on the other allows neural network models of such activity to probe for possible mechanistic explanations of these phenomena. We have carried out such investigations using cortical models consisting of networks of modules with excitatory and inhibitory neurons, each receiving excitatory inputs from outside the network in addition to intermodular connections. Modules may be taken as regions of cortical interest, the inputs from outside the network as arising from the thalamus, and the intermodular connections as long associational fibers. The model shows that the impulse frequency of different modules can differ from each other by less than 10%, consistent with the relatively uniform CMR(glc(ox)) observed across different regions of cortex. The model also shows that, if correlations of the average impulse rate between different modules decreases, there is a concomitant decrease in the average impulse rate in the modules, consistent with the observed drop in CMR(glc(ox)) in NREM sleep and under anesthesia. The model also explains why a transient thalamic input to sensory cortex gives rise to responses with amplitudes inversely dependent on the resting-state frequency, and therefore resting-state CMR(glc(ox)).

Insights from neuroenergetics into the interpretation of functional neuroimaging: an alternative empirical model for studying the brain's support of behavior

Functional neuroimaging measures quantitative changes in neurophysiological parameters coupled to neuronal activity during observable behavior. These results have usually been interpreted by assuming that mental causation of behavior arises from the simultaneous actions of distinct psychological mechanisms or modules. However, reproducible localization of these modules in the brain using functional magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging has been elusive other than for sensory systems. In this paper, we show that neuroenergetic studies using PET, calibrated functional magnetic resonance imaging (fMRI), (13)C magnetic resonance spectroscopy, and electrical recordings do not support the standard approach, which identifies the location of mental modules from changes in brain activity. Of importance in reaching this conclusion is that changes in neuronal activities underlying the fMRI signal are many times smaller than the high ubiquitous, baseline neuronal activity, or energy in resting, awake humans. Furthermore, the incremental signal depends on the baseline activity contradicting theoretical assumptions about linearity and insertion of mental modules. To avoid these problems, while making use of these valuable results, we propose that neuroimaging should be used to identify observable brain activities that are necessary for a person's observable behavior rather than being used to seek hypothesized mental processes.

Contributions and complexities from the use of in vivo animal models to improve understanding of human neuroimaging signals

Many of the major advances in our understanding of how functional brain imaging signals relate to neuronal activity over the previous two decades have arisen from physiological research studies involving experimental animal models. This approach has been successful partly because it provides opportunities to measure both the hemodynamic changes that underpin many human functional brain imaging techniques and the neuronal activity about which we wish to make inferences. Although research into the coupling of neuronal and hemodynamic responses using animal models has provided a general validation of the correspondence of neuroimaging signals to specific types of neuronal activity, it is also highlighting the key complexities and uncertainties in estimating neural signals from hemodynamic markers. This review will detail how research in animal models is contributing to our rapidly evolving understanding of what human neuroimaging techniques tell us about neuronal activity. It will highlight emerging issues in the interpretation of neuroimaging data that arise from in vivo research studies, for example spatial and temporal constraints to neuroimaging signal interpretation, or the effects of disease and modulatory neurotransmitters upon neurovascular coupling. We will also give critical consideration to the limitations and possible complexities of translating data acquired in the typical animals models used in this area to the arena of human fMRI. These include the commonplace use of anesthesia in animal research studies and the fact that many neuropsychological questions that are being actively explored in humans have limited homologs within current animal models for neuroimaging research. Finally we will highlighting approaches, both in experimental animals models (e.g. imaging in conscious, behaving animals) and human studies (e.g. combined fMRI-EEG), that mitigate against these challenges.

The caudate: a key node in the neuronal network imbalance of insomnia?

Insomnia is prevalent, severe and partially heritable. Unfortunately, its neuronal correlates remain enigmatic, hampering the development of mechanistic models and rational treatments. Consistently reported impairments concern fragmented sleep, hyper-arousal and executive dysfunction. Because fronto-striatal networks could well play a role in sleep, arousal regulation and executive functioning, the present series of studies used an executive task to evaluate fronto-striatal functioning in disturbed sleep. Patients with insomnia showed reduced recruitment of the head of the left caudate nucleus during executive functioning, which was not secondary to altered performance or baseline perfusion. Individual differences in caudate recruitment were associated with hyper-arousal severity. Seed-based functional connectivity analysis suggested that attenuated input from a projecting orbitofrontal area with reduced grey matter density contributes to altered caudate recruitment in patients with insomnia. Attenuated caudate recruitment persisted after successful treatment of insomnia, warranting evaluation as a potential vulnerability trait. A similar selective reduction in caudate recruitment could be elicited in participants without sleep complaints by slow-wave sleep fragmentation, providing a model to facilitate investigation of the causes and consequences of insomnia.

Poststimulus undershoots in cerebral blood flow and BOLD fMRI responses are modulated by poststimulus neuronal activity

fMRI is the foremost technique for noninvasive measurement of human brain function. However, its utility is limited by an incomplete understanding of the relationship between neuronal activity and the hemodynamic response. Though the primary peak of the hemodynamic response is modulated by neuronal activity, the origin of the typically negative poststimulus signal is poorly understood and its amplitude assumed to covary with the primary response. We use simultaneous recordings of EEG with blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF) fMRI during unilateral median nerve stimulation to show that the poststimulus fMRI signal is neuronally modulated. We observe high spatial agreement between concurrent BOLD and CBF responses to median nerve stimulation, with primary signal increases in contralateral sensorimotor cortex and primary signal decreases in ipsilateral sensorimotor cortex. During the poststimulus period, the amplitude and directionality (positive/negative) of the BOLD signal in both contralateral and ipsilateral sensorimotor cortex depends on the poststimulus synchrony of 8-13 Hz EEG neuronal activity, which is often considered to reflect cortical inhibition, along with concordant changes in CBF and metabolism. Therefore we present conclusive evidence that the fMRI time course represents a hemodynamic signature of at least two distinct temporal phases of neuronal activity, substantially improving understanding of the origin of the BOLD response and increasing the potential measurements of brain function provided by fMRI. We suggest that the poststimulus EEG and fMRI responses may be required for the resetting of the entire sensory network to enable a return to resting-state activity levels.

Self-specific stimuli interact differently than non-self-specific stimuli with eyes-open versus eyes-closed spontaneous activity in auditory cortex

Previous studies suggest that there may be a distinct relationship between spontaneous neural activity and subsequent or concurrent self-specific stimulus-induced activity. This study aims to test the impact of spontaneous activity as recorded in an eyes-open (EO) resting state as opposed to eyes-closed (EC) on self-specific versus non-self-specific auditory stimulus-induced activity in fMRI. In our first experiment we used self-specific stimuli comprised of the subject's own name and non-self-specific stimuli comprised of a friend's name and an unknown name, presented during EO versus EC baselines in a 3 name condition × 2 baseline design. In Experiment 2 we directly measured spontaneous activity in the absence of stimuli during EO versus EC to confirm a modulatory effect of the two baseline conditions in the regions found to show an interaction effect in Experiment 1. Spontaneous activity during EO was significantly higher than during EC in bilateral auditory cortex and non-self-specific names yielded stronger signal changes relative to EO baseline than to EC. In contrast, there was no difference in response to self-specific names relative to EO baseline than to EC despite the difference between spontaneous activity levels. These results support an impact of spontaneous activity on stimulus-induced activity, moreover an impact that depends on the high-level stimulus characteristic of self-specificity.

The change of functional connectivity specificity in rats under various anesthesia levels and its neural origin

Spatiotemporal correlations of spontaneous blood oxygenation level dependent (BOLD) signals measured in the resting brain have been found to imply many resting-state coherent networks under both awake/conscious and anesthetized/unconscious conditions. To understand the resting-state brain networks in the unconscious state, spontaneous BOLD signals from the rat sensorimotor cortex were studied across a wide range of anesthesia levels induced by isoflurane. Distinct resting-state networks covering functionally specific sub-regions of the sensorimotor system were observed under light anesthesia with 1.0% isoflurane; however, they gradually merged into a highly synchronized and spatially less-specific network under deep anesthesia with 1.8% isoflurane. The EEG power correlations recorded using three electrodes from a separate group of rats showed similar dependency on anesthesia depth, suggesting the neural origin of the change in functional connectivity specificity. The specific-to-less-specific transition of resting-state networks may reflect a functional reorganization of the brain at different anesthesia levels or brain states.

A BOLD Perspective on Age-Related Neurometabolic-Flow Coupling and Neural Efficiency Changes in Human Visual Cortex

Age-related performance declines in visual tasks have been attributed to reductions in processing efficiency. The neural basis of these declines has been explored by comparing the blood-oxygen-level-dependent (BOLD) index of neural activity in older and younger adults during visual task performance. However, neural activity is one of many factors that change with age and lead to BOLD signal differences. We investigated the origin of age-related BOLD changes by comparing blood flow and oxygen metabolic constituents of BOLD signal. Subjects periodically viewed flickering annuli and pressed a button when detecting luminance changes in a central fixation cross. Using magnetic resonance dual-echo arterial spin labeling and CO2 ingestion, we observed age-equivalent (i.e., similar in older and younger groups) fractional cerebral blood flow (ΔCBF) in the presence of age-related increases in fractional cerebral metabolic rate of oxygen (ΔCMRO2). Reductions in ΔCBF responsiveness to increased ΔCMRO2 in elderly led to paradoxical age-related BOLD decreases. Age-related ΔCBF/ΔCMRO2 ratio decreases were associated with reaction times, suggesting that age-related slowing resulted from less efficient neural activity. We hypothesized that reduced vascular responsiveness to neural metabolic demand would lead to a reduction in ΔCBF/ΔCMRO2. A simulation of BOLD relative to ΔCMRO2 for lower and higher neurometabolic-flow coupling ratios (approximating those for old and young, respectively) indicated less BOLD signal change in old than young in relatively lower CMRO2 ranges, as well as greater BOLD signal change in young compared to old in relatively higher CMRO2 ranges. These results suggest that age-comparative studies relying on BOLD signal might be misinterpreted, as age-related BOLD changes do not merely reflect neural activity changes. Age-related declines in neurometabolic-flow coupling might lead to neural efficiency reductions that can adversely affect visual task performance.

Odor representation in the olfactory bulb under different brain states revealed by intrinsic optical signals imaging

The olfactory system responds to the same stimulus with great variability according to the current state of the brain. At the levels of multi-unit activity and local field potentials, the response of the olfactory bulb (OB) to a given olfactory stimulus during a state of lower background activity is stronger than the response that occurs during higher background activity, but the distribution pattern of activity remains similar. However, these results have only been established at the individual neuron and neuron cluster scales in previous studies. It remains unclear whether these results are consistent at a larger scale (e.g., OB regions); therefore, intrinsic optical signals imaging was employed in the present study to clarify this issue. The basal brain states of rats were manipulated by using different levels of anesthesia. Under a state of low basal brain activity, the intensity of the activity pattern elicited in the dorsal OB by a given odorant was significantly higher than that under high basal brain activity, but the topography was highly similar across different brain states. These results were consistent across the levels of individual neurons, neuron clusters, glomeruli, and the OB regions, which suggest that the OB contains as yet unknown neural mechanisms that ensure the high-fidelity representation of the same olfactory stimulation under different brain states.

Mapping preictal and ictal haemodynamic networks using video-electroencephalography and functional imaging

Ictal patterns on scalp-electroencephalography are often visible only after propagation, therefore rendering localization of the seizure onset zone challenging. We hypothesized that mapping haemodynamic changes before and during seizures using simultaneous video-electroencephalography and functional imaging will improve the localization of the seizure onset zone. Fifty-five patients with ≥2 refractory focal seizures/day, and who had undergone long-term video-electroencephalography monitoring were included in the study. 'Preictal' (30 s immediately preceding the electrographic seizure onset) and ictal phases, 'ictal-onset'; 'ictalestablished' and 'late ictal', were defined based on the evolution of the electrographic pattern and clinical semiology. The functional imaging data were analysed using statistical parametric mapping to map ictal phase-related haemodynamic changes consistent across seizures. The resulting haemodynamic maps were overlaid on co-registered anatomical scans, and the spatial concordance with the presumed and invasively defined seizure onset zone was determined. Twenty patients had typical seizures during functional imaging. Seizures were identified on video-electroencephalography in 15 of 20, on electroencephalography alone in two and on video alone in three patients. All patients showed significant ictal-related haemodynamic changes. In the six cases that underwent invasive evaluation, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone for all patients. The most statistically significant haemodynamic cluster within the presumed seizure onset zone was between 1.1 and 3.5 cm from the invasively defined seizure onset zone, which was resected in two of three patients undergoing surgery (Class I post-surgical outcome) and was not resected in one patient (Class III post-surgical outcome). In the remaining 14 cases, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone in six of eight patients with structural-lesions and five of six non-lesional patients. The most statistically significant haemodynamic cluster was localizable at sub-lobar level within the presumed seizure onset zone in six patients. The degree of concordance of haemodynamic maps was significantly better (P < 0.05) for the ictal-onset phase [entirely concordant/concordant plus (13/20; 65%) + some concordance (4/20; 20%) = 17/20; 85%] than ictal-established [entirely concordant/concordant plus (5/13; 38%) + some concordance (4/13; 31%) = 9/13; 69%] and late ictal [concordant plus (1/9; 11%) + some concordance (4/9; 44%) = 5/9; 55%] phases. Ictal propagation-related haemodynamic changes were also seen in symptomatogenic areas (9/20; 45%) and the default mode network (13/20; 65%). A common pattern of preictal changes was seen in 15 patients, starting between 98 and 14 s before electrographic seizure onset, and the maps had a degree of concordance with the presumed seizure onset zone in 10 patients. In conclusion, preictal and ictal haemodynamic changes in refractory focal seizures can non-invasively localize seizure onset at sub-lobar/gyral level when ictal scalp-electroencephalography is not helpful.

Role of ongoing, intrinsic activity of neuronal populations for quantitative neuroimaging of functional magnetic resonance imaging-based networks

A primary objective in neuroscience is to determine how neuronal populations process information within networks. In humans and animal models, functional magnetic resonance imaging (fMRI) is gaining increasing popularity for network mapping. Although neuroimaging with fMRI-conducted with or without tasks-is actively discovering new brain networks, current fMRI data analysis schemes disregard the importance of the total neuronal activity in a region. In task fMRI experiments, the baseline is differenced away to disclose areas of small evoked changes in the blood oxygenation level-dependent (BOLD) signal. In resting-state fMRI experiments, the spotlight is on regions revealed by correlations of tiny fluctuations in the baseline (or spontaneous) BOLD signal. Interpretation of fMRI-based networks is obscured further, because the BOLD signal indirectly reflects neuronal activity, and difference/correlation maps are thresholded. Since the small changes of BOLD signal typically observed in cognitive fMRI experiments represent a minimal fraction of the total energy/activity in a given area, the relevance of fMRI-based networks is uncertain, because the majority of neuronal energy/activity is ignored. Thus, another alternative for quantitative neuroimaging of fMRI-based networks is a perspective in which the activity of a neuronal population is accounted for by the demanded oxidative energy (CMR(O2)). In this article, we argue that network mapping can be improved by including neuronal energy/activity of both the information about baseline and small differences/fluctuations of BOLD signal. Thus, total energy/activity information can be obtained through use of calibrated fMRI to quantify differences of ΔCMR(O2) and through resting-state positron emission tomography/magnetic resonance spectroscopy measurements for average CMR(O2).

Impact of global normalization in FMRI acupuncture studies

Global normalization is often used as a preprocessing step for dispelling the “nuisance effects.” However, it has been shown in cognitive and emotion tasks that this preprocessing step might greatly distort statistical results when the orthogonality assumption of global normalization is violated. The present study examines this issue in fMRI acupuncture studies. Thirty healthy subjects were recruited to evaluate the impacts of the global normalization on the BOLD responses evoked by acupuncture stimulation during De-qi sensation and tactile stimulation during nonpainful sensations. To this end, we compared results by conducting global normalization (PSGS) and not conducting global normalization (NO PSGS) based on a proportional scaling model. The orthogonality assumption of global normalization was violated, and significant changes between BOLD responses for NO PSGS and PSGS were shown in most subjects. Extensive deactivations of acupuncture in fMRI were the non-specifically pernicious consequences of global normalization. The central responses of acupuncture during De-qi are non-specifically activation-dominant at the somatosensory-related brain network, whose statistical power is specifically enhanced by PSGS. In conclusion, PSGS should be unjustified for acupuncture studies in fMRI. The differences including the global normalization or not may partly contribute to conflicting results and interpretations in previous fMRI acupuncture studies.

Coupling between resting cerebral perfusion and EEG

While several studies have investigated interactions between the electroencephalography (EEG) and functional magnetic resonance imaging BOLD signal fluctuations, less is known about the associations between EEG oscillations and baseline brain haemodynamics, and few studies have examined the link between EEG power outside the alpha band and baseline perfusion. Here we compare whole-brain arterial spin labelling perfusion MRI and EEG in a group of healthy adults (n = 16, ten females, median age: 27 years, range 21-48) during an eyes closed rest condition. Correlations emerged between perfusion and global average EEG power in low (delta: 2-4 Hz and theta: 4-7 Hz), middle (alpha: 8-13 Hz), and high (beta: 13-30 Hz and gamma: 30-45 Hz) frequency bands in both cortical and sub-cortical regions. The correlations were predominately positive in middle and high-frequency bands, and negative in delta. In addition, central alpha frequency positively correlated with perfusion in a network of brain regions associated with the modulation of attention and preparedness for external input, and central theta frequency correlated negatively with a widespread network of cortical regions. These results indicate that the coupling between average EEG power/frequency and local cerebral blood flow varies in a frequency specific manner. Our results are consistent with longstanding concepts that decreasing EEG frequencies which in general map onto decreasing levels of activation.

Pitfalls in Fractal Time Series Analysis: fMRI BOLD as an Exemplary Case

This article will be positioned on our previous work demonstrating the importance of adhering to a carefully selected set of criteria when choosing the suitable method from those available ensuring its adequate performance when applied to real temporal signals, such as fMRI BOLD, to evaluate one important facet of their behavior, fractality. Earlier, we have reviewed on a range of monofractal tools and evaluated their performance. Given the advance in the fractal field, in this article we will discuss the most widely used implementations of multifractal analyses, too. Our recommended flowchart for the fractal characterization of spontaneous, low frequency fluctuations in fMRI BOLD will be used as the framework for this article to make certain that it will provide a hands-on experience for the reader in handling the perplexed issues of fractal analysis. The reason why this particular signal modality and its fractal analysis has been chosen was due to its high impact on today’s neuroscience given it had powerfully emerged as a new way of interpreting the complex functioning of the brain (see “intrinsic activity”). The reader will first be presented with the basic concepts of mono and multifractal time series analyses, followed by some of the most relevant implementations, characterization by numerical approaches. The notion of the dichotomy of fractional Gaussian noise and fractional Brownian motion signal classes and their impact on fractal time series analyses will be thoroughly discussed as the central theme of our application strategy. Sources of pitfalls and way how to avoid them will be identified followed by a demonstration on fractal studies of fMRI BOLD taken from the literature and that of our own in an attempt to consolidate the best practice in fractal analysis of empirical fMRI BOLD signals mapped throughout the brain as an exemplary case of potentially wide interest.

Quantitative fMRI and oxidative neuroenergetics

The discovery of functional magnetic resonance imaging (fMRI) has greatly impacted neuroscience. The blood oxygenation level-dependent (BOLD) signal, using deoxyhemoglobin as an endogenous paramagnetic contrast agent, exposes regions of interest in task-based and resting-state paradigms. However the BOLD contrast is at best a partial measure of neuronal activity, because the functional maps obtained by differencing or correlations ignore the total neuronal activity in the baseline state. Here we describe how studies of brain energy metabolism at Yale, especially with (13)C magnetic resonance spectroscopy and related techniques, contributed to development of quantitative functional brain imaging with fMRI by providing a reliable measurement of baseline energy. This narrative takes us on a journey, from molecules to mind, with illuminating insights about neuronal-glial activities in relation to energy demand of synaptic activity. These results, along with key contributions from laboratories worldwide, comprise the energetic basis for quantitative interpretation of fMRI data.

Interpreting magnetic resonance imaging findings in bipolar disorder

The episodic nature of bipolar disorder together with the ostensibly polar extremes of mania and depression have favored the acceptance of a functional model postulating regionally disturbed brain activity returning to normal with time or treatment. Seemingly contrary to that view, anatomical imaging studies have demonstrated abnormalities in brain structure which could reflect neurodegeneration or represent disturbed neuronal development. Resolution may come from an appreciation of adult neurogenesis, especially given the neuroprotective properties of drugs, such as lithium and their effects on brain volume. The brain regions vulnerable to structural changes also show evidence of dysfunction, giving rise to corticolimbic dysregulation interpretations of bipolar disorder. This article reviews the structural and functional magnetic resonance imaging data in bipolar disorder. Its focus is on the interpretation of findings in light of recent developments in the fields of neurobiology and image analysis, with particular attention paid to both the confounding effects of medication and the baseline energy state of the brain.

Arterial Spin Labeling (ASL) fMRI: advantages, theoretical constrains, and experimental challenges in neurosciences

Cerebral blood flow (CBF) is a well-established correlate of brain function and therefore an essential parameter for studying the brain at both normal and diseased states. Arterial spin labeling (ASL) is a noninvasive fMRI technique that uses arterial water as an endogenous tracer to measure CBF. ASL provides reliable absolute quantification of CBF with higher spatial and temporal resolution than other techniques. And yet, the routine application of ASL has been somewhat limited. In this review, we start by highlighting theoretical complexities and technical challenges of ASL fMRI for basic and clinical research. While underscoring the main advantages of ASL versus other techniques such as BOLD, we also expound on inherent challenges and confounds in ASL perfusion imaging. In closing, we expound on several exciting developments in the field that we believe will make ASL reach its full potential in neuroscience research.

Default mode network activity and connectivity in psychopathology

Neuropsychiatric disorders are associated with abnormal function of the default mode network (DMN), a distributed network of brain regions more active during rest than during performance of many attention-demanding tasks and characterized by a high degree of functional connectivity (i.e., temporal correlations between brain regions). Functional magnetic resonance imaging studies have revealed that the DMN in the healthy brain is associated with stimulus-independent thought and self-reflection and that greater suppression of the DMN is associated with better performance on attention-demanding tasks. In schizophrenia and depression, the DMN is often found to be hyperactivated and hyperconnected. In schizophrenia this may relate to overly intensive self-reference and impairments in attention and working memory. In depression, DMN hyperactivity may be related to negative rumination. These findings are considered in terms of what is known about psychological functions supported by the DMN, and alteration of the DMN in other neuropsychiatric disorders.

Source imaging of P300 auditory evoked potentials and clinical correlations in patients with posttraumatic stress disorder

OBJECTIVE

Posttraumatic stress disorder (PTSD) is associated with abnormal information processing. The P300 component of event-related potentials (ERPs) is known to be a useful marker of information processing. The purposes of this study were to determine the P300 current source density in PTSD patients, and its relationship with symptom severity.

METHODS

ERPs were recorded in 30 PTSD patients and 33 healthy controls while participants were performing the auditory oddball task. We compared P300 current source density data--obtained by standardized low-resolution brain electromagnetic tomography (sLORETA)--between the two groups. The correlation between P300 current source density and clinical symptoms (as evaluated using the Korean version of the Structured Interview for PTSD--K-SIPS and Davidson Trauma Scale--K-DTS) was conducted.

RESULTS

In PTSD patients, the current source density of P300 is significantly reduced in the inferior frontal gyrus, precentral gyrus, insula, and anterior cingulate compared to healthy controls. Total K-DTS scores were correlated with the P300 current source density in the posterior cingulate gyrus. The K-SIP B items (re-experiencing) and K-SIB D items (increased arousal) were positively correlated with P300 current source densities in several brain regions located in the frontal, parietal, and temporal lobe (p<0.05). Conversely, the K-SIP C items (avoidance and numbing) were negatively correlated with P300 current source densities in the superior and middle frontal gyri in the frontal lobes (p<0.05).

CONCLUSION

The P300 current source densities reflected the pathophysiology of PTSD patients. PTSD symptoms were related to different neural activities, depending on their symptom characteristics.

Brain-state-independent neural representation of peripheral stimulation in rat olfactory bulb

It is critical for normal brains to perceive the external world precisely and accurately under ever-changing operational conditions, yet the mechanisms underlying this fundamental brain function in the sensory systems are poorly understood. To address this issue in the olfactory system, we investigated the responses of olfactory bulbs to odor stimulations under different brain states manipulated by anesthesia levels. Our results revealed that in two brain states, where the spontaneous baseline activities differed about twofold based on the local field potential (LFP) signals, the levels of neural activities reached after the same odor stimulation had no significant difference. This phenomenon was independent of anesthetics (pentobarbital or chloral hydrate), stimulating odorants (ethyl propionate, ethyl butyrate, ethyl valerate, amyl acetate, n-heptanal, or 2-heptanone), odor concentrations, and recording sites (the mitral or granular cell layers) for LFPs in three frequency bands (12-32 Hz, 33-64 Hz, and 65-90 Hz) and for multiunit activities. Furthermore, the activity patterns of the same stimulation under these two brain states were highly similar at both LFP and multiunit levels. These converging results argue the existence of mechanisms in the olfactory bulbs that ensure the delivery of peripheral olfactory information to higher olfactory centers with high fidelity under different brain states.

Methodological problems in FMRI studies on acupuncture: a critical review with special emphasis on visual and auditory cortex activations

Functional magnetic resonance imaging (fMRI) has been used for more than a decade to investigate possible supraspinal mechanisms of acupuncture stimulation. More than 60 studies and several review articles have been published on the topic. However, till now some acupuncture-fMRI studies have not adopted all methodological standards applied to most other fMRI studies. In this critical review, we comment on some of the problems including the choice of baseline, interpretation of deactivations, attention control and implications of different group statistics. We illustrate the possible impact of these problems by focussing on some early findings, namely activations of visual and auditory cortical areas, when acupoints were stimulated that are believed to have a therapeutic effect on vision or hearing in traditional Chinese medicine. While we are far from questioning the validity of using fMRI for the study of acupuncture effects, we think that activations reported by some of these studies were probably not a direct result of acupuncture stimulation but rather attributable to one or more of the methodological problems covered here. Finally, we try to offer solutions for these problems where possible.

Neural origin of spontaneous hemodynamic fluctuations in rats under burst-suppression anesthesia condition

Spontaneous hemodynamic signals fluctuate coherently within many resting-brain functional networks not only in awake humans and lightly anesthetized primates but also in animals under deep anesthesia characterized by burst-suppression electroencephalogram (EEG) activity and unconsciousness. To understand the neural origin of spontaneous hemodynamic fluctuations under such a deep anesthesia state, epidural EEG and cerebral blood flow (CBF) were simultaneously recorded from the bilateral somatosensory cortical regions of rats with isoflurane-induced burst-suppression EEG activity. Strong neurovascular coupling was observed between spontaneous EEG "bursts" and CBF "bumps," both of which were also highly synchronized across the 2 hemispheres. Functional magnetic resonance imaging (fMRI) was used to image spontaneous blood oxygen level-dependent (BOLD) signals under the same anesthesia conditions and showed similar BOLD "bumps" and dependence on anesthesia depth as the CBF signals. The spatiotemporal BOLD correlations indicate a strong but less-specific coherent network covering a wide range of cortical regions. The overall findings reveal that the spontaneous CBF/BOLD fluctuations under unconscious burst-suppression anesthesia conditions originate mainly from underlying neural activity. They provide insights into the neurophysiological basis for the use of BOLD- and CBF-based fMRI signals for noninvasively imaging spontaneous and synchronous brain activity under various brain states.

The 'resting-state hypothesis' of major depressive disorder-a translational subcortical-cortical framework for a system disorder

Major depressive disorder (MDD) has traditionally been characterized by various psychological symptoms, involvement of diverse functional systems (e.g., somatic, affect, cognition, reward, etc.), and with progress in neuroscience, an increasing number of brain regions. This has led to the general assumption that MDD is a stress-responsive brain 'system disorder' where either one or several alterations infiltrate a large number of functional systems in the brain that control the organism's somatic, affective, and cognitive life. However, while the effects or consequences of the abnormal changes in the functional systems of, for instance affect, cognition or reward have been investigated extensively, the underlying core mechanism(s) underlying MDD remain unknown. Hypotheses are proliferating rapidly, though. Based on recent findings, we will entertain an abnormality in the resting-state activity in MDD to be a core feature. Based on both animal and human data, we hypothesize that abnormal resting-state activity levels may impact stimulus-induced neural activity in medially situated core systems for self-representation as well as external stimulus (especially stress, specifically separation distress) interactions. Moreover, due to nested hierarchy between subcortical and cortical regions, we assume 'highjacking' of higher cortical affective and cognitive functions by lower subcortical primary-process emotional systems. This may account for the predominance of negative affect in somatic and cognitive functional system operations with the consecutive generation of the diverse symptoms in MDD. We will here focus on the neuroanatomical and biochemical basis of resting-state abnormalities in MDD including their linkage to the diverse psychopathological symptoms in depression. However, our 'resting-state hypothesis' may go well beyond that by being sufficiently precise to be linked to genetic, social, immunological, and endocrine dimensions and hypotheses as well as to clinical dimensions like endophenotypes and various diagnostic-prognostic biomarkers. Taken together, our 'resting-state hypothesis' may be considered a first tentative framework for MDD that integrates translational data, the various dimensions, and subcortical-cortical systems while at the same time providing the link to the clinical level of symptoms, endophenotypes and biomarkers.

BOLD signal changes preceding negative responses in EEG-fMRI in patients with focal epilepsy

PURPOSE

In simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), increased neuronal activity from epileptiform spikes commonly elicits positive blood oxygenation level-dependent (BOLD) responses. Negative responses are also occasionally seen and have not been explained. Recent studies describe BOLD signal changes before focal EEG spikes. We aimed to systematically study if the undershoot of a preceding positive response might explain the negative BOLD seen in the focus.

METHODS

Eighty-two patients with focal epilepsy who underwent EEG-fMRI at 3T were retrospectively studied. Studies with a focal negative BOLD response in the region of the spike field were reanalyzed using models with hemodynamic response functions (HRFs) peaking from -9 to +9 s around the spike.

RESULTS

Eight patients met the inclusion criteria, showing negative BOLD responses in the spike field on standard analysis. None had positive BOLD responses immediately adjacent to the areas of deactivation. Regions of deactivation were found to have congruent preceding positive responses in two cases. These early activations were seen at the combined maps of -5 to -9 s.

DISCUSSION

This study indicates that in a small proportion of patients with focal epilepsy in whom the standard analysis reveals focal negative responses, an earlier positive BOLD response is probably the cause. The origin of negative BOLD signal changes in the focus as a result of an epileptic event remains, however, unexplained in most of the patients in whom it occurs.

How to test for dual-task-specific effects in brain imaging studies--an evaluation of potential analysis methods

The study of the concurrent performance of two tasks allows deep insights into the human cognitive system and, accordingly, an increasing number of brain imaging studies are conducted to identify the neuroanatomical correlates of such dual-task performance. In this overview we present currently used approaches to identify dual-task-specific activations in fMRI and PET studies. A comparison is made in order to identify the approaches which have the potential to validly detect dual-task-specific activation patterns, i.e. activation which cannot be explained by the individual performance of the component tasks alone. We demonstrate that while all approaches suffer from at least some drawbacks, the best (although potentially over-conservative) approach is to compare the dual task with the sum of the single tasks, the second-best is an interaction contrast, and the third-best a conjunction analysis. Comparisons of the dual task with the mean of single-task activity or with only one single task should be avoided except for a few specific situations. We generalize our conclusions to related research areas, such as multisensory integration or divided attention.

Glutamatergic and resting-state functional connectivity correlates of severity in major depression - the role of pregenual anterior cingulate cortex and anterior insula

Glutamatergic mechanisms and resting-state functional connectivity alterations have been recently described as factors contributing to major depressive disorder (MDD). Furthermore, the pregenual anterior cingulate cortex (pgACC) seems to play an important role for major depressive symptoms such as anhedonia and impaired emotion processing. We investigated 22 MDD patients and 22 healthy subjects using a combined magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (fMRI) approach. Severity of depression was rated using the 21-item Hamilton depression scale (HAMD) and patients were divided into severely and mildly depressed subgroups according to HAMD scores. Because of their hypothesized role in depression we investigated the functional connectivity between pgACC and left anterior insular cortex (AI). The sum of Glutamate and Glutamine (Glx) in the pgACC, but not in left AI, predicted the resting-state functional connectivity between the two regions exclusively in depressed patients. Furthermore, functional connectivity between these regions was significantly altered in the subgroup of severely depressed patients (HAMD > 15) compared to healthy subjects and mildly depressed patients. Similarly the Glx ratios, relative to Creatine, in the pgACC were lowest in severely depressed patients. These findings support the involvement of glutamatergic mechanisms in severe MDD which are related to the functional connectivity between pgACC and AI and depression severity.

Rest-stimulus interaction in the brain: a review

Studies in animals and humans have demonstrated intrinsic activity in the brain during the resting state. The concept of the default-mode network (DMN) - a set of brain regions in which resting-state activity (RSA) activity is reduced in response to external stimuli - recently raised much controversy concerning the psychological correlates of RSA. However, it remains unclear how RSA interacts with stimulus-induced activity. Here we review studies in humans and animals that address how RSA interacts with stimulus-induced activity; we also discuss, conversely, how stimulus-induced activity can modulate RSA. Psychologically, the rest-stimulus interaction is relevant to predicting subsequent behavioral and mental states. We conclude that a better understanding of the rest-stimulus interaction is likely to be crucial to the elucidation of the brain's contribution to mental states.

The neural origins of superficial and individuated judgments about ingroup and outgroup members

We often form impressions of others based on superficial information, such as a mere glimpse of their face. Given the opportunity to get to know someone, however, our judgments are allowed to become more individuated. The neural origins of these two types of social judgment remain unknown. We used functional magnetic resonance imaging to dissociate the neural mechanisms underlying superficial and individuated judgments. Given behavioral evidence demonstrating impairments in individuating others outside one's racial group, we additionally examined whether these neural mechanisms are race-selective. Superficial judgments recruited the amygdala. Individuated judgments engaged a cortical network implicated in mentalizing and theory of mind. One component of this mentalizing network showed selectivity to individuated judgments, but exclusively for targets of one's own race. The findings reveal the distinct-and race-selective-neural bases of our everyday superficial and individuated judgments of others.

Focal BOLD fMRI changes in bicuculline-induced tonic-clonic seizures in the rat

Generalized tonic-clonic seizures cause widespread physiological changes throughout the cerebral cortex and subcortical structures in the brain. Using combined blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) at 9.4 T and electroencephalography (EEG), these changes can be characterized with high spatiotemporal resolution. We studied BOLD changes in anesthetized Wistar rats during bicuculline-induced tonic-clonic seizures. Bicuculline, a GABA(A) receptor antagonist, was injected systemically and seizure activity was observed on EEG as high-amplitude, high-frequency polyspike discharges followed by clonic paroxysmal activity of lower frequency, with mean electrographic seizure duration of 349 s. Our aim was to characterize the spatial localization, direction, and timing of BOLD signal changes during the pre-ictal, ictal and post-ictal periods. Group analysis was performed across seizures using paired t-maps of BOLD signal superimposed on high-resolution anatomical images. Regional analysis was then performed using volumes of interest to quantify BOLD timecourses. In the pre-ictal period we found focal BOLD increases in specific areas of somatosensory cortex (S1, S2) and thalamus several seconds before seizure onset. During seizures we observed BOLD increases in cortex, brainstem and thalamus and BOLD decreases in the hippocampus. The largest ictal BOLD increases remained in the focal regions of somatosensory cortex showing pre-ictal increases. During the post-ictal period we observed widespread BOLD decreases. These findings support a model in which "generalized" tonic-clonic seizures begin with focal changes before electrographic seizure onset, which progress to non-uniform changes during seizures, possibly shedding light on the etiology and pathophysiology of similar seizures in humans.

Baseline brain energy supports the state of consciousness

An individual, human or animal, is defined to be in a conscious state empirically by the behavioral ability to respond meaningfully to stimuli, whereas the loss of consciousness is defined by unresponsiveness. PET measurements of glucose or oxygen consumption show a widespread approximately 45% reduction in cerebral energy consumption with anesthesia-induced loss of consciousness. Because baseline brain energy consumption has been shown by (13)C magnetic resonance spectroscopy to be almost exclusively dedicated to neuronal signaling, we propose that the high level of brain energy is a necessary property of the conscious state. Two additional neuronal properties of the conscious state change with anesthesia. The delocalized fMRI activity patterns in rat brain during sensory stimulation at a higher energy state (close to the awake) collapse to a contralateral somatosensory response at lower energy state (deep anesthesia). Firing rates of an ensemble of neurons in the rat somatosensory cortex shift from the gamma-band range (20-40 Hz) at higher energy state to <10 Hz at lower energy state. With the conscious state defined by the individual's behavior and maintained by high cerebral energy, measurable properties of that state are the widespread fMRI patterns and high frequency neuronal activity, both of which support the extensive interregional communication characteristic of consciousness. This usage of high brain energies when the person is in the "state" of consciousness differs from most studies, which attend the smaller energy increments observed during the stimulations that form the "contents" of that state.

Neurophysiology of functional imaging

The successes of PET and fMRI in non-invasively localizing sensory functions had encouraged efforts to transform the subjective concepts of cognitive psychology into objective physical measures. The assumption was that mental functions could be decomposed into non-overlapping, context-independent modules that are operated on by separable areas of a computer-like brain. The failures of cognitive modularity and of a very localized phrenology are generally, but not universally, accepted; but in their place, and usually not distinguished from the original revolutionary hopes of clarification, experimental results are being interpreted in terms of rather flexible definitions of both cognitive concepts and the degree of localization. In an alternative approach, we have connected fMRI, (13)C MRS, and electrophysiology measurements of brain energy to connect with observable properties of mental life (i.e., awareness). We illustrate this approach with a sensory stimulation experiment; the degree of localization found in BOLD signals was related to the global energy of the brain which, when manipulated by anesthetics, affected the degree of awareness. The influence of brain energy upon functional imaging maps is changing the interpretations of neuroimaging experiments, from psychological concepts generating computer-like responses to empirical responses dominated by the high brain energy and signaling at rest. In our view "baseline" is an operational term, an adjective that defines a property of a state of the system before it is perturbed by a stimulus. Given the dependence of observable psychological properties upon the "baseline" energy, we believe that it is unnecessarily limiting to define a particular state as the baseline.

Alterations in default network connectivity in posttraumatic stress disorder related to early-life trauma

BACKGROUND

The "default network" consists of a number of brain regions that exhibit correlated low-frequency activity at rest and that have been suggested to be involved in the processing of self-relevant stimuli. Activity in many of these areas has also been shown to be altered in individuals with posttraumatic stress disorder (PTSD). We hypothesized that the posterior cingulate cortex (PCC)/precuneus, part of the default network, would exhibit altered connectivity at rest with other areas of the default network and regions associated with PTSD.

METHODS

Seventeen medicated and unmedicated female patients with chronic posttraumatic stress disorder (PTSD) related to early-life trauma and 15 healthy female controls underwent a 5.5-minute functional magnetic resonance imaging scan with their eyes closed. We assessed areas of the brain whose activity positively and negatively correlated with that of the PCC/precuneus in both groups.

RESULTS

At rest, spontaneous low-frequency activity in the PCC/precuneus was more strongly correlated with activity in other areas of the default network in healthy controls than in patients with PTSD. Direct comparison of the 2 groups showed that PCC/ precuneus connectivity was also greater in healthy controls than in patients with PTSD in a number of areas previously associated with PTSD, including the right amygdala and the hippocampus/parahippocampal gyrus.

LIMITATIONS

Because our PTSD sample comprised only women with chronic early-life trauma exposure, our results may not be generalizeable to male patients, to a population with single trauma exposure or to those who were adults when the trauma occurred. In addition, our sample included patients taking medication and it is not yet clear how altered connectivity is affected by medication.

CONCLUSION

Spontaneous activity in the default network during rest, as measured using PCC correlations, is altered in patients with PTSD. The potential effects of psychotropic medications on default network connectivity in the present sample remain unknown. In this patient population, the observed alterations may be associated with the disturbances in self-referential processing often observed in patients with chronic PTSD related to early-life trauma.

Prefrontal cortex dysfunction during cognitive tests evidenced by functional near-infrared spectroscopy

Prefrontal cortex oxygenation changes in response to a verbal fluency task and a visual spatial working memory task were investigated by functional near-infrared spectroscopy (fNIRS) on nine patients with schizophrenia. Four patients were reactive to both tests; five reactive to only one of the two tests, suggesting the importance of reporting fNIRS results for each individual.

New insights into central roles of cerebral oxygen metabolism in the resting and stimulus-evoked brain

The possible role of oxygen metabolism in supporting brain activation remains elusive. We have used a newly developed neuroimaging approach based on high-field in vivo (17)O magnetic resonance spectroscopic (MRS) imaging to noninvasively image cerebral metabolic rate of oxygen (CMRO(2)) consumption in cats at rest and during visual stimulation. It was found that CMRO(2) increases significantly (32.3%+/-10.8%, n=6) in the activated visual cortical region as depicted in blood oxygenation level dependence functional maps; this increase is also accompanied by a CMRO(2) decrease in surrounding cortical regions, resulting a smaller increase (9.7%+/-1.9%) of total CMRO(2) change over a larger cortical region displaying either a positive or negative CMRO(2) alteration. Moreover, a negative correlation between stimulus-evoked percent CMRO(2) increase and resting CMRO(2) was observed, indicating an essential impact of resting brain metabolic activity level on stimulus-evoked percent CMRO(2) change and neuroimaging signals. These findings provide new insights into the critical roles of oxidative metabolism in supporting brain activation and function. They also suggest that in vivo (17)O MRS imaging should provide a sensitive neuroimaging modality for mapping CMRO(2) and its change induced by brain physiology and/or pathologic alteration.