Functional brain imaging and human brain function

Updating functional brain units: Insights far beyond Luria

This paper reviews Luria's model of the three functional units of the brain. To meet this objective, several issues were reviewed: the theory of functional systems and the contributions of phylogenesis and embryogenesis to the brain's functional organization. This review revealed several facts. In the first place, the relationship/integration of basic homeostatic needs with complex forms of behavior. Secondly, the multi-scale hierarchical and distributed organization of the brain and interactions between cells and systems. Thirdly, the phylogenetic role of exaptation, especially in basal ganglia and cerebellum expansion. Finally, the tripartite embryogenetic organization of the brain: rhinic, limbic/paralimbic, and supralimbic zones. Obviously, these principles of brain organization are in contradiction with attempts to establish separate functional brain units. The proposed new model is made up of two large integrated complexes: a primordial-limbic complex (Luria's Unit I) and a telencephalic-cortical complex (Luria's Units II and III). As a result, five functional units were delineated: Unit I. Primordial or preferential (brainstem), for life-support, behavioral modulation, and waking regulation; Unit II. Limbic and paralimbic systems, for emotions and hedonic evaluation (danger and relevance detection and contribution to reward/motivational processing) and the creation of cognitive maps (contextual memory, navigation, and generativity [imagination]); Unit III. Telencephalic-cortical, for sensorimotor and cognitive processing (gnosis, praxis, language, calculation, etc.), semantic and episodic (contextual) memory processing, and multimodal conscious agency; Unit IV. Basal ganglia systems, for behavior selection and reinforcement (reward-oriented behavior); Unit V. Cerebellar systems, for the prediction/anticipation (orthometric supervision) of the outcome of an action. The proposed brain units are nothing more than abstractions within the brain's simultaneous and distributed physiological processes. As function transcends anatomy, the model necessarily involves transition and overlap between structures. Beyond the classic approaches, this review includes information on recent systemic perspectives on functional brain organization. The limitations of this review are discussed.

Emerging Roles of Microfluidics in Brain Research: From Cerebral Fluids Manipulation to Brain-on-a-Chip and Neuroelectronic Devices Engineering

Remarkable progress made in the past few decades in brain research enables the manipulation of neuronal activity in single neurons and neural circuits and thus allows the decipherment of relations between nervous systems and behavior. The discovery of glymphatic and lymphatic systems in the brain and the recently unveiled tight relations between the gastrointestinal (GI) tract and the central nervous system (CNS) further revolutionize our understanding of brain structures and functions. Fundamental questions about how neurons conduct two-way communications with the gut to establish the gut-brain axis (GBA) and interact with essential brain components such as glial cells and blood vessels to regulate cerebral blood flow (CBF) and cerebrospinal fluid (CSF) in health and disease, however, remain. Microfluidics with unparalleled advantages in the control of fluids at microscale has emerged recently as an effective approach to address these critical questions in brain research. The dynamics of cerebral fluids (i.e., blood and CSF) and novel in vitro brain-on-a-chip models and microfluidic-integrated multifunctional neuroelectronic devices, for example, have been investigated. This review starts with a critical discussion of the current understanding of several key topics in brain research such as neurovascular coupling (NVC), glymphatic pathway, and GBA and then interrogates a wide range of microfluidic-based approaches that have been developed or can be improved to advance our fundamental understanding of brain functions. Last, emerging technologies for structuring microfluidic devices and their implications and future directions in brain research are discussed.

Regulation of cerebral blood flow in humans: physiology and clinical implications of autoregulation

Brain function critically depends on a close matching between metabolic demands, appropriate delivery of oxygen and nutrients, and removal of cellular waste. This matching requires continuous regulation of cerebral blood flow (CBF), which can be categorized into four broad topics: 1) autoregulation, which describes the response of the cerebrovasculature to changes in perfusion pressure; 2) vascular reactivity to vasoactive stimuli [including carbon dioxide (CO2)]; 3) neurovascular coupling (NVC), i.e., the CBF response to local changes in neural activity (often standardized cognitive stimuli in humans); and 4) endothelium-dependent responses. This review focuses primarily on autoregulation and its clinical implications. To place autoregulation in a more precise context, and to better understand integrated approaches in the cerebral circulation, we also briefly address reactivity to CO2 and NVC. In addition to our focus on effects of perfusion pressure (or blood pressure), we describe the impact of select stimuli on regulation of CBF (i.e., arterial blood gases, cerebral metabolism, neural mechanisms, and specific vascular cells), the interrelationships between these stimuli, and implications for regulation of CBF at the level of large arteries and the microcirculation. We review clinical implications of autoregulation in aging, hypertension, stroke, mild cognitive impairment, anesthesia, and dementias. Finally, we discuss autoregulation in the context of common daily physiological challenges, including changes in posture (e.g., orthostatic hypotension, syncope) and physical activity.

Differential Hemispheric Lateralization of Emotions and Related Display Behaviors: Emotion-Type Hypothesis

There are two well-known hypotheses regarding hemispheric lateralization of emotions. The Right Hemisphere Hypothesis (RHH) postulates that emotions and associated display behaviors are a dominant and lateralized function of the right hemisphere. The Valence Hypothesis (VH) posits that negative emotions and related display behaviors are modulated by the right hemisphere and positive emotions and related display behaviors are modulated by the left hemisphere. Although both the RHH and VH are supported by extensive research data, they are mutually exclusive, suggesting that there may be a missing factor in play that may provide a more accurate description of how emotions are lateralization in the brain. Evidence will be presented that provides a much broader perspective of emotions by embracing the concept that emotions can be classified into primary and social types and that hemispheric lateralization is better explained by the Emotion-type Hypothesis (ETH). The ETH posits that primary emotions and related display behaviors are modulated by the right hemisphere and social emotions and related display behaviors are modulated by the left hemisphere.

Brain Structural Connectivity Differences in Patients with Normal Cognition and Cognitive Impairment

Advances in magnetic resonance imaging, particularly diffusion imaging, have allowed researchers to analyze brain connectivity. Identification of structural connectivity differences between patients with normal cognition, cognitive impairment, and dementia could lead to new biomarker discoveries that could improve dementia diagnostics. In our study, we analyzed 22 patients (11 control group patients, 11 dementia group patients) that underwent 3T MRI diffusion tensor imaging (DTI) scans and the Montreal Cognitive Assessment (MoCA) test. We reconstructed DTI images and used the Desikan-Killiany-Tourville cortical parcellation atlas. The connectivity matrix was calculated, and graph theoretical analysis was conducted using DSI Studio. We found statistically significant differences between groups in the graph density, network characteristic path length, small-worldness, global efficiency, and rich club organization. We did not find statistically significant differences between groups in the average clustering coefficient and the assortativity coefficient. These statistically significant graph theory measures could potentially be used as quantitative biomarkers in cognitive impairment and dementia diagnostics.

Gauging Functional Brain Activity: From Distinguishability to Accessibility

Standard neuroimaging techniques provide non-invasive access not only to human brain anatomy but also to its physiology. The activity recorded with these techniques is generally called functional imaging, but what is observed per se is an instance of dynamics, from which functional brain activity should be extracted. Distinguishing between bare dynamics and genuine function is a highly non-trivial task, but a crucially important one when comparing experimental observations and interpreting their significance. Here we illustrate how neuroimaging's ability to extract genuine functional brain activity is bounded by functional representations' structure. To do so, we first provide a simple definition of functional brain activity from a system-level brain imaging perspective. We then review how the properties of the space on which brain activity is represented induce relations on observed imaging data which allow determining the extent to which two observations are functionally distinguishable and quantifying how far apart they are. It is also proposed that genuine functional distances would require defining accessibility, i.e., how a given observed condition can be accessed from another given one, under the dynamics of some neurophysiological process. We show how these properties result from the structure defined on dynamical data and dynamics-to-function projections, and consider some implications that the way and extent to which these are defined have for the interpretation of experimental data from standard system-level brain recording techniques.

Juvenile Myoclonic Epilepsy Shows Potential Structural White Matter Abnormalities: A TBSS Study

Background: Several studies on patients with juvenile myoclonic epilepsy (JME) showed widespread white matter (WM) abnormalities in the brain. The aim of this study was to investigate potential structural abnormalities in JME patients (1) compared to healthy controls, (2) among JME subgroups with or without photoparoxysmal responses (PPR), and (3) in correlation with clinical variables. Methods: A selection of 31 patients with JME (12 PPR positive) and 27 age and gender matched healthy controls (HC) were studied at a tertiary epilepsy center. Fractional anisotropy (FA) was calculated and intergroup differences analyzed using Tract Based Spatial Statistics (TBSS). Results: Compared to HC the JME group showed reduced FA widespread and bilateral in the longitudinal fasciculus, inferior fronto-occipital fasciculus, corticospinal tract, anterior and posterior thalamic radiation, corona radiata, corpus callosum, cingulate gyrus and external capsule (p < 0.01). Subgroup analysis revealed no significant differences of WM alterations between PPR positive and negative patients and with clinical and epilepsy-related factors. Conclusions: Widespread microstructural abnormalities among patients with JME have been identified.Prior findings of frontal and thalamofrontal microstructural abnormalities have been confirmed. Additionally, microstructural abnormalities were found in widespread extra-frontal regions that may help to validate pathophysiological concepts of JME.

Neuropsychodynamic Approach to Depression: Integrating Resting State Dysfunctions of the Brain and Disturbed Self-Related Processes

A mechanism-based approach was developed focusing on the psychodynamic, psychological and neuronal mechanisms in healthy and depressed persons. In this integrative concept of depression, the self is a core dimension in depression. It is attributed to negative emotions (e.g., failure, guilt). The increased inward focus in depression is connected with a decreased environmental focus. The development of neuropsychodynamic hypotheses of the altered self-reference is based on the investigation of the emotional-cognitive interaction in depressed patients. It may be hypothesized that the increased negative self-attributions—as typical characteristics of an increased self-focus in depression—may result from altered neuronal activity in subcortical-cortical midline structures in the brain, especially from hyperactivity in the cortical-subcortical midline regions and hypoactivity in the lateral regions. The increased resting state activity in depression is especially associated with an increased resting state activity in the default mode network (DMN) and a dysbalance between DMN and executive network (EN) activity. Possible therapeutic consequences of the neuropsychodynamic approach to depression involve the necessary emotional attunement in psychotherapy of depressed patients and the adequate timing of therapeutic interventions. The hypotheses which have been developed in the context of the neuropsychodynamic model of depression may be used for more specific psychotherapeutic interventions, aiming at specific mechanisms of compensation and defence, which are related to the increased resting state activity and the disturbed resting state-stimulus-interaction.

Big Data Analytics for Genomic Medicine

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients’ genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a Big Data infrastructure exhibit challenges, they also provide a feasible opportunity to develop an efficient and effective approach to identify clinically actionable genetic variants for individualized diagnosis and therapy. In this paper, we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. We introduce possible solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data to implement genomic medicine. Additionally, we also present a practical Big Data toolset for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs.

Toward a cumulative science of functional integration: A meta-analysis of psychophysiological interactions

Much of the work in cognitive neuroscience is shifting from a focus on single brain regions to a focus on the connectivity between multiple brain regions. These inter-regional connectivity patterns contribute to a wide range of behaviors and are studied with models of functional integration. The rapid expansion of the literature on functional integration offers an opportunity to scrutinize the consistency and specificity of one of the most popular approaches for quantifying connectivity: psychophysiological interaction (PPI) analysis. We performed coordinate-based meta-analyses on 284 PPI studies, which allowed us to test (a) whether those studies consistently converge on similar target regions and (b) whether the identified target regions are specific to the chosen seed region and psychological context. Our analyses revealed two key results. First, we found that different types of PPI studies-e.g., those using seeds such as amygdala and dorsolateral prefrontal cortex (DLPFC) and contexts such as emotion and cognitive control, respectively-each consistently converge on similar target regions, thus supporting the reliability of PPI as a tool for studying functional integration. Second, we also found target regions that were specific to the chosen seed region and psychological context, indicating distinct patterns of brain connectivity. For example, the DLPFC seed reliably contributed to a posterior cingulate cortex target during cognitive control but contributed to an amygdala target in other contexts. Our results point to the robustness of PPI while highlighting common and distinct patterns of functional integration, potentially advancing models of brain connectivity. Hum Brain Mapp 37:2904-2917, 2016. © 2016 Wiley Periodicals, Inc.

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 Review on the Bioinformatics Tools for Neuroimaging

Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system.

Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis

Objective

Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas.

Methods

Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients.

Results

Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance.

Conclusions

Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.

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Subnetwork of hyperconnectivity in juvenile myoclonic epilepsy

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Hyperconnectivity in primary motor, parietal and subcortical regions

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Network-based statistics is a valuable tool for predicting functional cognitive deficits.

Photoacoustic Brain Imaging: from Microscopic to Macroscopic Scales

Human brain mapping has become one of the most exciting contemporary research areas, with major breakthroughs expected in the following decades. Modern brain imaging techniques have allowed neuroscientists to gather a wealth of anatomic and functional information about the brain. Among these techniques, by virtue of its rich optical absorption contrast, high spatial and temporal resolutions, and deep penetration, photoacoustic tomography (PAT) has attracted more and more attention, and is playing an increasingly important role in brain studies. In particular, PAT complements other brain imaging modalities by providing high-resolution functional and metabolic imaging. More importantly, PAT's unique scalability enables scrutinizing the brain at both microscopic and macroscopic scales, using the same imaging contrast. In this Review, we present the state-of-the-art PAT techniques for brain imaging, summarize representative neuroscience applications, outline the technical challenges in translating PAT to human brain imaging, and envision potential technological deliverables.

At the centennial of Michaelis and Menten, competing Michaelis-Menten steps explain effect of GLP-1 on blood-brain transfer and metabolism of glucose

Glucagon-like peptide-1 (GLP-1) is a potent insulinotropic incretin hormone with both pancreatic and extrapancreatic effects. Studies of GLP-1 reveal significant effects in regions of brain tissue that regulate appetite and satiety. GLP-1 mimetics are used for the treatment of type 2 diabetes mellitus. GLP-1 interacts with peripheral functions in which the autonomic nervous system plays an important role, and emerging pre-clinical findings indicate a potential neuroprotective role of the peptide, for example in models of stroke and in neurodegenerative disorders. A century ago, Leonor Michaelis and Maud Menten described the steady-state enzyme kinetics that still apply to the multiple receptors, transporters and enzymes that define the biochemical reactions of the brain, including the glucose-dependent impact of GLP-1 on blood-brain glucose transfer and metabolism. This MiniReview examines the potential of GLP-1 as a molecule of interest for the understanding of brain energy metabolism and with reference to the impact on brain metabolism related to appetite and satiety regulation, stroke and neurodegenerative disorders. These effects can be understood only by reference to the original formulation of the Michaelis-Menten equation as applied to a chain of kinetically controlled steps. Indeed, the effects of GLP-1 receptor activation on blood-brain glucose transfer and brain metabolism of glucose depend on the glucose concentration and relative affinities of the steps both in vitro and in vivo, as in the pancreas.

The language of visual representations in the neurosciences — relating past and future

In theoretical accounts of the neurosciences, investigative research programs have often been separated into the morphological and physiological tradition. The morphological tradition is seen as describing the structure and form of the external and interior parts of the brain and spinal cord. The physiological tradition is interpreted as a compilation of those approaches which investigate cerebral functions particularly in their dynamic interactions. It must be regarded as an open question, though, whether the distinction between the morphological and physiological tradition in modern clinical and basic neuroscience has now become obsolete with the most recent neuroimaging techniques, such as fMRI, PET scans, SPECT, etc. Taken at face value, these new imaging techniques seem to relate, overlap, and even identify the anatomical with the functional substrate, when mapping individual patterns of neural activity across the visually delineated morphological structures. The particular focus of this review article is primarily on the morphological tradition, beginning with German neuroanatomist Samuel Thomas Soemmerring and leading to recent approaches in the neurohistological work of neuroscience centres in the United States and morphophysiological neuroimaging techniques in Canada. Following some landmark research steps in neuroanatomy detailed in the first section, this article analyzes the changing trajectories to an integrative theory of the brain in its second section. An examination of the relationship between form and function within the material culture of neuroscience in the third and final part, will further reveal an astonishingly heterogeneous investigative and conceptual terrain.

Enzyme-modified carbon-fiber microelectrode for the quantification of dynamic fluctuations of nonelectroactive analytes using fast-scan cyclic voltammetry

Neurotransmission occurs on a millisecond time scale, but conventional methods for monitoring nonelectroactive neurochemicals are limited by slow sampling rates. Despite a significant global market, a sensor capable of measuring the dynamics of rapidly fluctuating, nonelectroactive molecules at a single recording site with high sensitivity, electrochemical selectivity, and a subsecond response time is still lacking. To address this need, we have enabled the real-time detection of dynamic glucose fluctuations in live brain tissue using background-subtracted, fast-scan cyclic voltammetry. The novel microbiosensor consists of a simple carbon fiber surface modified with an electrodeposited chitosan hydrogel encapsulating glucose oxidase. The selectivity afforded by voltammetry enables quantitative and qualitative measurements of enzymatically generated H2O2 without the need for additional strategies to eliminate interfering agents. The microbiosensors possess a sensitivity and limit of detection for glucose of 19.4 ± 0.2 nA mM(-1) and 13.1 ± 0.7 μM, respectively. They are stable, even under deviations from physiological normoxic conditions, and show minimal interference from endogenous electroactive substances. Using this approach, we have quantitatively and selectively monitored pharmacologically evoked glucose fluctuations with unprecedented chemical and spatial resolution. Furthermore, this novel biosensing strategy is widely applicable to the immobilization of any H2O2 producing enzyme, enabling rapid monitoring of many nonelectroactive enzyme substrates.

Optical detection of brain function: simultaneous imaging of cerebral vascular response, tissue metabolism, and cellular activity in vivo

It is known that a remaining challenge for functional brain imaging is to distinguish the coupling and decoupling effects among neuronal activity, cerebral metabolism, and vascular hemodynamics, which highlights the need for new tools to enable simultaneous measures of these three properties in vivo. Here, we review current neuroimaging techniques and their prospects and potential limitations for tackling this challenge. We then report a novel dual-wavelength laser speckle imaging (DW-LSI) tool developed in our labs that enables simultaneous imaging of cerebral blood flow (CBF), cerebral blood volume, and tissue hemoglobin oxygenation, which allows us to monitor neurovascular and tissue metabolic activities at high spatiotemporal resolutions over a relatively large field of view. Moreover, we report digital frequency ramping Doppler optical coherence tomography (DFR-OCT) that allows for quantitative 3D imaging of the CBF network in vivo. In parallel, we review calcium imaging techniques to track neuronal activity, including intracellular calcium approach using Rhod2 fluorescence technique that we develop to detect neuronal activity in vivo. We report a new multimodality imaging platform that combines DW-LSI, DFR-OCT, and calcium fluorescence imaging for simultaneous detection of cortical hemodynamics, cerebral metabolism, and neuronal activities of the animal brain in vivo, as well as its integration with microprobes for imaging neuronal function in deep brain regions in vivo. Promising results of in vivo animal brain functional studies suggest the potential of this multimodality approach for future awake animal and behavioral studies.

Meta Analysis of Functional Neuroimaging Data via Bayesian Spatial Point Processes

As the discipline of functional neuroimaging grows there is an increasing interest in meta analysis of brain imaging studies. A typical neuroimaging meta analysis collects peak activation coordinates (foci) from several studies and identifies areas of consistent activation. Most imaging meta analysis methods only produce null hypothesis inferences and do not provide an interpretable fitted model. To overcome these limitations, we propose a Bayesian spatial hierarchical model using a marked independent cluster process. We model the foci as offspring of a latent study center process, and the study centers are in turn offspring of a latent population center process. The posterior intensity function of the population center process provides inference on the location of population centers, as well as the inter-study variability of foci about the population centers. We illustrate our model with a meta analysis consisting of 437 studies from 164 publications, show how two subpopulations of studies can be compared and assess our model via sensitivity analyses and simulation studies. Supplemental materials are available online.

Paradigm shift in translational neuroimaging of CNS disorders

During the last two decades, functional neuroimaging technology, especially functional magnetic resonance imaging (fMRI), has improved tremendously, with new attention towards resting-state functional connectivity of the brain. This development has allowed scientists to study changes in brain structure and function, and probe these two properties under conditions of evoked stimulation, disease and drug administration. In the domain of functional imaging, the identification and characterization of central nervous system (CNS) functional networks have emerged as potential biomarkers for CNS disorders in humans. Recent attempts to translate clinical neuroimaging methodology to preclinical studies have also been carried out, which offer new opportunities in translational neuroscience research. In this paper, we review recent developments in structural and functional MRI and their use to probe functional connectivity in various CNS disorders such as schizophrenia, mood disorders, Alzheimer's disease (AD) and pain.

Preoperative and intraoperative brain mapping for the resection of eloquent-area tumors. A prospective analysis of methodology, correlation, and usefulness based on clinical outcomes

BACKGROUND

Localization of brain function is a fundamental requisite for the resection of eloquent-area brain tumors. Preoperative functional neuroimaging and diffusion tensor imaging can display cortical functional organization and subcortical anatomy of major white matter bundles. Direct cortical and subcortical stimulation is widely used in routine practice, however, because of its ability to reveal tissue function in eloquent regions. The role and integration of these techniques is still a matter of debate. The objective of this study was to assess surgical and functional neurological outputs of awake surgery and intraoperative cortical and subcortical electrical stimulation (CSES) and to use CSES to examine the reliability of preoperative functional magnetic resonance (fMRI) and diffusion tensor imaging fiber tracking (DTI-FT) for surgical planning.

PATIENTS AND METHODS

We prospectively studied 27 patients with eloquent-area tumors who were selected to undergo awake surgery and direct brain mapping. All subjects underwent preoperative sensorimotor and language fMRI and DTI tractography of major white matter bundles. Intra- and postoperative complications, stimulation effects, extent of resection, and neurological outcome were determined. We topographically correlated intraoperatively identified sites (cortical and subcortical) with areas of fMRI activation and DTI tractography.

RESULTS

Total plus subtotal resection reached 88.8%. Twenty-one patients (77.7%) suffered transient postoperative worsening, but at 6 months follow-up only three (11.1%) patients had persistent neurological impairment. Sensorimotor cortex direct mapping correlated 92.3% with fMRI activation, while direct mapping of language cortex correlated 42.8%. DTI fiber tracking underestimated the presence of functional fibers surrounding or inside the tumor.

CONCLUSION

Preoperative brain mapping is useful when planning awake surgery to estimate the relationship between the tumor and functional brain regions. However, these techniques cannot directly lead the surgeon during resection. Intraoperative brain mapping is necessary for safe and maximal resection and to guarantee a satisfying neurological outcome. This multimodal approach is more aggressive, leads to better outcomes, and should be used routinely for resection of lesions in eloquent brain regions.

Imaging separation of neuronal from vascular effects of cocaine on rat cortical brain in vivo

MRI techniques to study brain function assume coupling between neuronal activity, metabolism and flow. However, recent evidence of physiological uncoupling between neuronal and cerebrovascular events highlights the need for methods to simultaneously measure these three properties. We report a multimodality optical approach that integrates dual-wavelength laser speckle imaging (measures changes in blood flow, blood volume and hemoglobin oxygenation), digital-frequency-ramping optical coherence tomography (images quantitative 3D vascular network) and Rhod(2) fluorescence (images intracellular calcium for measure of neuronal activity) at high spatiotemporal resolutions (30 μm, 10 Hz) and over a large field of view (3×5 mm(2)). We apply it to assess cocaine's effects in rat cortical brain and show an immediate decrease (3.5±0.9 min, phase 1) in the oxygen content of hemoglobin and the cerebral blood flow followed by an overshoot (7.1±0.2 min, phase 2) lasting over 20 min whereas Ca(2+) increased immediately (peaked at t=4.1±0.4 min) and remained elevated. This enabled us to identify a delay (2.9±0.5 min) between peak neuronal and vascular responses in phase 2. The ability of this multimodality optical approach for simultaneous imaging at high spatiotemporal resolutions permits us to distinguish the vascular versus cellular changes of the brain, thus complimenting other neuroimaging modalities for brain functional studies (e. g., PET, fMRI).

Cerebral localization of functions and the neurology of language: fact versus fiction or is it something else?

Over the last 15 years there has been a burgeoning number of publications using functional brain imaging (>40,000 articles based on an ISI/Web of Science search) to localize behavioral and cognitive processes to specific areas in the human brain that are often not confirmed by traditional, lesion-based studies. Thus, there is a need to reassess what cerebral localization of functions is and is not. Otherwise, there is no rational way to interpret the escalating claims of localization in the functional imaging literature that is taking on the appearance of neurophysiologic "phrenology". This article will present arguments to suggest that functional localization in the brain is a robust but very dynamic, four-dimensional process. It is a learned phenomenon driven over time by large-scale, spatially distributed, neural networks seeking to efficiently maximize the processing, storage, and manipulation of information for cognitive and behavioral operations. Because of historical considerations and space limitations, the main focus will be on localization of language-related functions whose theoretical neurological basis can be generalized for any complex cognitive-behavioral function.

Dynamic searching in the brain

Cognitive functions rely on the extensive use of information stored in the brain, and the searching for the relevant information for solving some problem is a very complex task. Human cognition largely uses biological search engines, and we assume that to study cognitive function we need to understand the way these brain search engines work. The approach we favor is to study multi-modular network models, able to solve particular problems that involve searching for information. The building blocks of these multimodular networks are the context dependent memory models we have been using for almost 20 years. These models work by associating an output to the Kronecker product of an input and a context. Input, context and output are vectors that represent cognitive variables. Our models constitute a natural extension of the traditional linear associator. We show that coding the information in vectors that are processed through association matrices, allows for a direct contact between these memory models and some procedures that are now classical in the Information Retrieval field. One essential feature of context-dependent models is that they are based on the thematic packing of information, whereby each context points to a particular set of related concepts. The thematic packing can be extended to multimodular networks involving input-output contexts, in order to accomplish more complex tasks. Contexts act as passwords that elicit the appropriate memory to deal with a query. We also show toy versions of several 'neuromimetic' devices that solve cognitive tasks as diverse as decision making or word sense disambiguation. The functioning of these multimodular networks can be described as dynamical systems at the level of cognitive variables.

Thermodynamic constraints on neural dimensions, firing rates, brain temperature and size

There have been suggestions that heat caused by cerebral metabolic activity may constrain mammalian brain evolution, architecture, and function. This article investigates physical limits on brain wiring and corresponding changes in brain temperature that are imposed by thermodynamics of heat balance determined mainly by Na(+)/K(+)-ATPase, cerebral blood flow, and heat conduction. It is found that even moderate firing rates cause significant intracellular Na(+) build-up, and the ATP consumption rate associated with pumping out these ions grows nonlinearly with frequency. Surprisingly, the power dissipated by the Na(+)/K(+) pump depends biphasically on frequency, which can lead to the biphasic dependence of brain temperature on frequency as well. Both the total power of sodium pumps and brain temperature diverge for very small fiber diameters, indicating that too thin fibers are not beneficial for thermal balance. For very small brains blood flow is not a sufficient cooling mechanism deep in the brain. The theoretical lower bound on fiber diameter above which brain temperature is in the operational regime is strongly frequency dependent but finite due to synaptic depression. For normal neurophysiological conditions this bound is at least an order of magnitude smaller than average values of empirical fiber diameters, suggesting that neuroanatomy of the mammalian brains operates in the thermodynamically safe regime. Analytical formulas presented can be used to estimate average firing rates in mammals, and relate their changes to changes in brain temperature, which can have important practical applications. In general, activity in larger brains is found to be slower than in smaller brains.

Dynamic imaging of brain function

In recent years, there have been unprecedented methodological advances in the dynamic imaging of brain activities. Electrophysiological, optical, and magnetic resonance methods now allow mapping of functional activation (or deactivation) by measurement of neural activity (e.g., membrane potential, ion flux, neurotransmitter flux), energy metabolism (e.g., glucose consumption, oxygen consumption, creatine kinase flux), and functional hyperemia (e.g., blood oxygenation, blood flow, blood volume). Properties of the glutamatergic synapse are used to model activities at the nerve terminal and their associated changes in energy demand and blood flow. This approach reveals that each method measures different tissue- and/or cell-specific components with characteristic spatiotemporal resolution. While advantages and disadvantages of different methods are apparent and often used to supersede one another in terms of specificity and/or sensitivity, no particular technique is the optimal dynamic brain imaging method because each method is unique in some respect. Since the demand for energy substrates is a fundamental requirement for function, energy-based methods may allow quantitative dynamic imaging in vivo. However, there are exclusive neurobiological insights gained by combining some of these different dynamic imaging techniques.

Metabolic plasticity in the supraspinal pain modulating circuitry after noxious stimulus-induced spinal cord LTP

It has been suggested that spinal cord long-term potentiation (LTP) may contribute to hypersensitivity and hyperalgesia. We have investigated if noxious stimulus-induced spinal cord LTP might have a long lasting effect on supraspinal neuronal activity. First, we verified that spinal LTP was induced by electrical high frequency stimuli (HFS) conditioning applied to the sciatic nerve. The C-fibre response in the dorsal horn reached a twofold increase 150 min after HFS (t-test, p<0.01, n=6). Then, to study the metabolic supraspinal activity following the same stimulation protocol, we used small animal positron emission tomography (PET) and the glucose analog [(18)F]-fluorodeoxyglucose (FDG). With this combined approach we measured changes in regional supraspinal activity at two time points in HFS conditioned and in sham animals; acute (immediately after HFS/sham, n=4) and late phase (150 min after HFS/sham, n=10). Comparisons between HFS and sham groups revealed that induction of spinal LTP was followed by an acute metabolic response in the primary somatosensory cortex (S1), but also various slower metabolic adaptations in brain regions involved in modulation of nociceptive signaling and descending inhibition, i.e., amygdala, periaqueductal gray (PAG), rostral ventromedial medulla (RVM), and the dorsolateral pontomesencephalic tegmentum (DLPT) (t-test, p<0.05). The study demonstrates that PET may be used as an in vivo method to study regional brain metabolic activity between different conditions. It is concluded that noxious sciatic stimuli which induce spinal cord LTP also affect supraspinal metabolic activity. We suggest that these changes might illustrate a supraspinal maladaptive dysfunction involved in pain hypersensitivity and hyperalgesia.

High-frequency (600 Hz) population spikes in human EEG delineate thalamic and cortical fMRI activation sites

Functional magnetic resonance imaging (fMRI) measures neural activity indirectly via its slow vascular/metabolic consequences. At a temporal resolution on the order of seconds, fMRI does not reveal the real 'language of neurons', spelt out by fast electrical discharges ('spikes') which occur on a time scale of milliseconds. In animal studies, these limitations have been addressed by adding invasive electrode measurements to fMRI. Here, we propose to circumvent this 'inverse problem of fMRI' by deriving a noninvasive spike measure from recordings of ultrafast electroencephalography (EEG) signals during fMRI. We demonstrate how in response to median nerve stimulation 600 Hz oscillatory EEG signals can be measured reliably during fMRI. These high-frequency bursts (HFBs) are supposed to reflect population spikes in the thalamus and the somatosensory cortex, respectively. We show that distinct fMRI activations in these two generator structures can be attributed to spontaneous HFB fluctuations. Thus, our approach allowed the noninvasive identification of neural processes along the thalamocortical pathway unfolding at a millisecond time scale.

Domain-specific data sharing in neuroscience: what do we have to learn from each other?

Molecular biology and genomics have made notable strides in the sharing of primary data and resources. In other domains of neuroscience research, however, there has been resistance to adopting formalized strategies for data exchange, archiving, and availability. In this article, we discuss how neuroscience domains might follow the lead of molecular biology on what has been successful and what has failed in active data sharing. This considers not only the technical challenges but also the sociological concerns in making it possible. Though, not a pain-free process, with increased data availability, scientists from multiple fields can enjoy greater opportunity for novel discoveries about the brain in health and disease.

Neuroimaging as a New Tool in the Toolbox of Psychological Science

During the past quarter century, advances in imaging technology have helped transform scientific fields. As important as the data made available by these new technologies have been, equally important have been the guides provided by existing theories and the converging evidence provided by other methodologies. The field of psychological science is no exception. Neuroimaging is an important new tool in the toolbox of psychological science, but it is most productive when its use is guided by psychological theories and complemented by converging methodologies including (but not limited to) lesion, electrophysiological, computational, and behavioral studies. Based on this approach, the articles in this special issue specify neural mechanisms involved in perception, attention, categorization, memory, recognition, attitudes, social cognition, language, motor coordination, emotional regulation, executive function, decision making, and depression. Understanding the contributions of individual and functionally connected brain regions to these processes benefits psychological theory by suggesting functional representations and processes, constraining these processes, producing means of falsifying hypotheses, and generating new hypotheses. From this work, a view is emerging in which psychological processes represent emergent properties of a widely distributed set of component processes.

Telencephalon: Neocortex

The neocortex is an ultracomplex, six-layered structure that develops from the dorsal palliai sector of the telencephalic hemispheres (Figs. 2.24, 2.25, 11.1). All mammals, including monotremes and marsupials, possess a neocortex, but in reptiles, i.e. the ancestors of mammals, only a three-layered neocortical primordium is present [509, 511]. The term neocortex refers to its late phylogenetic appearance, in comparison to the “palaeocortical” olfactory cortex and the “archicortical” hippocampal cortex, both of which are present in all amniotes [509].

Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia

BACKGROUND

It is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons.

MODEL

The constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle), lipid metabolism, reactive oxygen species (ROS) detoxification, amino acid metabolism (synthesis and catabolism), the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism. This is, to our knowledge, the most comprehensive attempt at stoichiometric modeling of brain metabolism to date in terms of its coverage of a wide range of metabolic pathways. We then attempted to model the basal physiological behaviour and hypoxic behaviour of the brain cells where astrocytes and neurons are tightly coupled.

RESULTS

The reconstructed stoichiometric reaction model included 217 reactions (184 internal, 33 exchange) and 216 metabolites (183 internal, 33 external) distributed in and between astrocytes and neurons. Flux balance analysis (FBA) techniques were applied to the reconstructed model to elucidate the underlying cellular principles of neuron-astrocyte coupling. Simulation of resting conditions under the constraints of maximization of glutamate/glutamine/GABA cycle fluxes between the two cell types with subsequent minimization of Euclidean norm of fluxes resulted in a flux distribution in accordance with literature-based findings. As a further validation of our model, the effect of oxygen deprivation (hypoxia) on fluxes was simulated using an FBA-derivative approach, known as minimization of metabolic adjustment (MOMA). The results show the power of the constructed model to simulate disease behaviour on the flux level, and its potential to analyze cellular metabolic behaviour in silico.

CONCLUSION

The predictive power of the constructed model for the key flux distributions, especially central carbon metabolism and glutamate-glutamine cycle fluxes, and its application to hypoxia is promising. The resultant acceptable predictions strengthen the power of such stoichiometric models in the analysis of mammalian cell metabolism.

Brain temperature fluctuations during physiological and pathological conditions

This review discusses brain temperature as a physiological parameter, which is determined primarily by neural metabolism, regulated by cerebral blood flow, and affected by various environmental factors and drugs. First, we consider normal fluctuations in brain temperature that are induced by salient environmental stimuli and occur during motivated behavior at stable normothermic conditions. Second, we analyze changes in brain temperature induced by various drugs that affect brain and body metabolism and heat dissipation. Third, we consider how these physiological and drug-induced changes in brain temperature are modulated by environmental conditions that diminish heat dissipation. Our focus is psychomotor stimulant drugs and brain hyperthermia as a factor inducing or potentiating neurotoxicity. Finally, we discuss how brain temperature is regulated, what changes in brain temperature reflect, and how these changes may affect neural functions under normal and pathological conditions. Although most discussed data were obtained in animals and several important aspects of brain temperature regulation in humans remain unknown, our focus is on the relevance of these data for human physiology and pathology.

Nonlinear neurovascular coupling in rat sensory cortex by activation of transcallosal fibers

Functional neuroimaging and normal brain function rely on the robust coupling between neural activity and cerebral blood flow (CBF), that is neurovascular coupling. We examined neurovascular coupling in rat sensory cortex in response to direct stimulation of transcallosal pathways, which allows examination of brain regions inaccessible to peripheral stimulation techniques. Using laser-Doppler flowmetry to record CBF and electrophysiologic recordings of local field potentials (LFPs), we show an exponential relation between CBF responses and summed LFP amplitudes. Hemodynamic responses were dependent on glutamate receptor activation. CNQX, an AMPA receptor blocker, strongly attenuated evoked CBF responses and LFP amplitudes at all stimulation frequencies. In comparison, N-methyl D-aspartate (NMDA) receptor blockade by MK801 attenuated CBF responses at high (>7 Hz) but not low (<7 Hz) stimulation frequencies, without affecting evoked LFP amplitudes. This shows the limitation of using LFP amplitudes as indicators of synaptic activity. 7-Nitroindazole, a neuronal nitric oxide synthase inhibitor, and indomethacin, a nonspecific cyclooxygenase inhibitor, attenuated the hemodynamic responses by 50%+/-1% and 48%+/-1%, respectively, without affecting LFP amplitudes. The data suggest that preserved activity of both AMPA and NMDA receptors is necessary for the full CBF response evoked by stimulation of rodent interhemispheric connections. AMPA receptor activation gives rise to a measurable LFP, but NMDA receptor activation does not. The lack of a measurable LFP from neural processes that contribute importantly to CBF may explain some of the difficulties in transforming extracellular current or voltage measurements to a hemodynamic response.

Sensory-evoked intrinsic optical signals in the olfactory bulb are coupled to glutamate release and uptake

Functional imaging signals arise from metabolic and hemodynamic activity, but how these processes are related to the synaptic and electrical activity of neurons is not well understood. To provide insight into this issue, we used in vivo imaging and simultaneous local pharmacology to study how sensory-evoked neural activity leads to intrinsic optical signals (IOS) in the well-defined circuitry of the olfactory glomerulus. Odor-evoked IOS were tightly coupled to release of glutamate and were strongly modulated by activation of presynaptic dopamine and GABA-B receptors. Surprisingly, IOS were independent of postsynaptic transmission through ionotropic or metabotropic glutamate receptors, but instead were inhibited when uptake by astrocytic glutamate transporters was blocked. These data suggest that presynaptic glutamate release and uptake by astrocytes form a critical pathway through which neural activity is linked to metabolic processing and hence to functional imaging signals.

Neurobarrier coupling in the brain: Adjusting glucose entry with demand

Glucose transport over the blood-brain barrier (BBB) is a nonrate-limiting step and has therefore received little attention as a possible adjustment point within the transport reaction cascade from blood glucose to brain cell glycolysis. Considerations of the normal working point of facilitated BBB glucose shuttling via the GLUT-1 protein indicate that the transport is working at about one-third of T(max) under basal conditions. Substitution of T(max) estimates indicates that the transport is then just enough to keep up with glucose consumption, maintaining the steady state. After brain activation, glucose transport has to be stimulated, and this can be accomplished by increasing the driving force or changing the T(max) and/or K(t) parameters of BBB transport. The first possibility involves a decrease of brain interstitial glucose with subsequent flow stimulation according to the law of mass action (LMA), whereas the second possibility involves signaling from activated neurons to the BBB, a regulation loop that we propose to be called "neurobarrier coupling" (NBC). Theoretical analysis of the LMA effect and comparison with data on glucose dynamics during brain activation suggest that this factor alone only covers about half of the stimulation necessary to bring glucose delivery into line with the elevated glucose consumption during activation. Adjusting glucose entry with demand thus probably involves both LMA and NBC effects, depending on the degree of brain activation. Further work is needed to demonstrate NBC effects following physiological brain activation in vivo and to identify the signals that lead to NBC in in vitro experiments.

Physiological and pathological brain hyperthermia

While brain temperature is usually considered a stable, tightly regulated parameter, recent animal research revealed relatively large and rapid brain temperature fluctuations (approximately 3 degrees C) during various forms of naturally occurring physiological and behavioral activities. This work demonstrates that physiological brain hyperthermia has an intra-brain origin, resulting from enhanced neural metabolism and increased intra-brain heat production, and discusses its possible mechanisms and functional consequences. This work also shows that brain hyperthermia may also be induced by various drugs of abuse. While each individual drug (i.e., heroin, cocaine, meth-amphetamine, MDMA) has its own, dose-dependent effects on brain and body temperatures, these effects are strongly modulated by the individual's activity state and environmental conditions, showing dramatic alterations during the development of drug-taking behavior. While brain temperatures may also increase due to environmental overheating and diminished heat dissipation from the brain, adverse environmental conditions and physiological activation strongly potentiate thermal effects of psychomotor stimulant drugs, resulting in dangerous brain overheating. Since hyperthermia exacerbates drug-induced toxicity and is destructive to neural cells and brain functions, use of these drugs under conditions that restrict heat loss may pose a significant health risk, resulting in both acute life-threatening complications and chronic destructive CNS changes. We argue that brain temperature is an important physiological parameter, affecting various neural functions, and show the potential of brain temperature monitoring for studying alterations in metabolic neural activity under physiological and pathological conditions. Finally, we discuss brain temperature as a factor affecting various neuronal and neurochemical evaluations made in different animal preparations (in vitro slices, general anesthesia, awake, freely moving conditions) and consider a possible contribution of temperature fluctuations to behavior-related and drug-induced alterations in neuronal and neurochemical parameters.

Emotion and Pain: A Functional Cerebral Systems Integration

Emotion and pain are psychological constructs that have received extensive attention in neuropsychological research. However, neuropsychological models of emotional processing have made more progress in describing how brain regions interact to process emotion. Theories of emotional processing can describe inter-hemispheric and intra-hemispheric interactions during emotional processing. Due to similarities between emotion and pain, it is thought that emotional models can be applied to pain. The following review examines the neuropsychology of emotion and pain using a functional cerebral systems approach. Specific comparisons are made between pain and anger. Attention is given to differences in cerebral function and physiology that may contribute to the processing of emotion and pain. Suggestions for future research in emotion and pain are given.

Elevated lactate suppresses neuronal firing in vivo and inhibits glucose metabolism in hippocampal slice cultures

Glucose is well accepted as the major fuel for neuronal activity, while it remains controversial whether lactate also supports neural activity. In hippocampal slice cultures, synaptic transmission supported by glucose was reversibly suppressed by lactate. To test whether lactate had a similar inhibitory effect in vivo, lactate was perfused into the hippocampi of unanesthetized rats while recording the firing of nearby pyramidal cells. Lactate perfusion suppressed pyramidal cell firing by 87.5+/-8.3% (n=6). Firing suppression was slow in onset and fully reversible and was associated with increased lactate concentration at the site of the recording electrode. In vivo suppression of neural activity by lactate occurred in the presence of glucose; therefore we tested whether suppression of neural firing was due to lactate interference with glucose metabolism. Competition between glucose and lactate was measured in hippocampal slice cultures. Lactate had no effect on glucose uptake. Lactate suppressed glucose oxidation when applied at an elevated, pathological concentration (10 mM), but not at its physiological concentration (1 mM). Pyruvate (10 mM) also inhibited glucose oxidation but was significantly less effective than lactate. The greater suppressive effect of lactate as compared to pyruvate suggests that alteration of the NAD(+)/NADH ratio underlies the suppression of glucose oxidation by lactate. ATP in slice culture was unchanged in glucose (1 mM), but significantly reduced in lactate (1 mM). ATP in slice culture was significantly increased by combination of glucose (1 mM) and lactate (1 mM). These data suggest that alteration of redox ratio underlies the suppression of neural discharge and glucose metabolism by lactate.

Stability of substantia nigra pars reticulata neuronal discharge rates during dopamine receptor blockade and its possible mechanisms

It is hypothesized that substantia nigra pars reticulata neurons become overactive during a deficit of dopamine transmission. In this study, we examined how acute dopamine receptor blockade (SCH23390 and eticlopride) affects impulse activity of substantia nigra pars reticulata neurons and their response to iontophoretic gamma-amino-n-butyric acid in awake, unrestrained rats. No changes in discharge rate were found during complete dopamine receptor blockade, but these neurons showed a diminished response to gamma-amino-n-butyric acid, suggesting gamma-amino-n-butyric acid receptor hyposensitivity. This may result from tonic increase in gamma-amino-n-butyric acid input from the striatum and globus pallidus, which are activated during dopamine receptor blockade. As substantia nigra pars reticulata neurons are autoactive and resistant to tonic increases in gamma-amino-n-butyric acid input, changes in their responsiveness to phasic gamma-amino-n-butyric acid inputs, not tonic increase discharge rate, may underlie movement disturbance following dopamine deficit.

Brain work and brain imaging

Functional brain imaging with positron emission tomography and magnetic resonance imaging has been used extensively to map regional changes in brain activity. The signal used by both techniques is based on changes in local circulation and metabolism (brain work). Our understanding of the cell biology of these changes has progressed greatly in the past decade. New insights have emerged on the role of astrocytes in signal transduction as has an appreciation of the unique contribution of aerobic glycolysis to brain energy metabolism. Likewise our understanding of the neurophysiologic processes responsible for imaging signals has progressed from an assumption that spiking activity (output) of neurons is most relevant to one focused on their input. Finally, neuroimaging, with its unique metabolic perspective, has alerted us to the ongoing and costly intrinsic activity within brain systems that most likely represents the largest fraction of the brain's functional activity.

The role of peripheral and central sodium channels in mediating brain temperature fluctuations induced by intravenous cocaine

While cocaine's interaction with the dopamine (DA) transporter and subsequent increase in DA transmission are usually considered key factors responsible for its locomotor stimulatory and reinforcing properties, many centrally mediated physiological and psychoemotional effects of cocaine are resistant to DA receptor blockade, suggesting the importance of other non-DA mechanisms. To explore the role of cocaine's interaction with Na+ channels, rats were used to compare locomotor stimulatory and temperature (NAcc, temporal muscle and skin) effects of repeated iv injections of cocaine (1 mg/kg) with those induced by procaine (PRO 5 mg/kg), a short-acting local anesthetic with negligible effect on the DA transporter, and cocaine methiodide (COC-MET 1.31 mg/kg), a quaternary cocaine derivative that is unable to cross the blood-brain barrier. While PRO, unlike cocaine, did not induce locomotor activation, it mimicked cocaine in its ability to increase brain temperature following the initial injection and to induce biphasic, down-up fluctuations following repeated injections. This similarity suggests that both these effects of cocaine may be driven by its action on Na+ channels, a common action of both drugs. While COC-MET also did not affect locomotor activity, it shared with cocaine and PRO their ability to increase brain temperature but failed to induce temperature decreases after repeated injections. These findings point toward activation of peripheral Na+ channels as the primary mechanism of rapid excitatory effects of cocaine and inhibition of centrally located Na+ channels as the primary mechanism for transient inhibitory effects of cocaine. DA receptor blockade (SCH23390+eticlopride) fully eliminated locomotor stimulatory and temperature-increasing effects of cocaine, but its temperature-decreasing effects remained intact. Surprisingly, DA receptor blockade also altered the temperature fluctuations caused by PRO and COC-MET, suggesting that some of the central effects triggered via Na+ channels are in fact DA-dependent. Finally, repeated administration of PRO to animals that had previous cocaine experience led to conditioned locomotion and potentiated temperature-increasing effects of this drug. It appears, therefore, that, in addition to the central effects of cocaine mediated via interaction with the DA transporter and potentiation of DA uptake, interaction with peripheral and central Na+ channels is important for the initial physiological and, perhaps, affective effects of cocaine, likely contributing to the unique abuse potential of this drug.

Spatial flow-volume dissociation of the cerebral microcirculatory response to mild hypercapnia

The spatial and temporal response of the cerebral microcirculation to mild hypercapnia was investigated via two-photon laser-scanning microscopy. Cortical vessels, traversing the top 200 microm of somatosensory cortex, were visualized in alpha-chloralose-anesthetized Sprague-Dawley rats equipped with a cranial window. Intraluminal vessel diameters, transit times of fluorescent dextrans and red blood cells (RBC) velocities in individual capillaries were measured under normocapnic (PaCO2= 32.6 +/- 2.6 mm Hg) and slightly hypercapnic (PaCO2= 45 +/- 7 mm Hg) conditions. This gentle increase in PaCO2 was sufficient to produce robust and significant increases in both arterial and venous vessel diameters, concomitant to decreases in transit times of a bolus of dye from artery to venule (14%, P < 0.05) and from artery to vein (27%, P < 0.05). On the whole, capillaries exhibited a significant increase in diameter (16 +/- 33%, P < 0.001, n = 393) and a substantial increase in RBC velocities (75 +/- 114%, P < 0.001, n = 46) with hypercapnia. However, the response of the cerebral microvasculature to modest increases in PaCO2 was spatially heterogeneous. The maximal relative dilatation (range: 5-77%; mean +/- SD: 25 +/- 34%, P < 0.001, n = 271) occurred in the smallest capillaries (1.6 microm-4.0 microm resting diameter), while medium and larger capillaries (4.4 microm-6.8 microm resting diameter) showed no significant changes in diameter (P > 0.08, n = 122). In contrast, on average, RBC velocities increased less in the smaller capillaries (39 +/- 5%, P < 0.002, n = 22) than in the medium and larger capillaries (107 +/- 142%, P < 0.003, n = 24). Thus, the changes in capillary RBC velocities were spatially distinct from the observed volumetric changes and occurred to homogenize cerebral blood flow along capillaries of all diameters.

Extrinsic and intrinsic systems in the posterior cortex of the human brain revealed during natural sensory stimulation

When exposing subjects to a continuous segment of an audiovisual movie, a large expanse of human cortex, especially in the posterior half of the cerebral cortex, shows stimulus-driven activity. However, embedded within this widespread activity, there are cortical regions whose activity is dissociated from the external stimulation. These regions are intercorrelated among themselves, forming a functional network, which largely overlaps with cortical areas previously shown to be deactivated by task-oriented paradigms. Moreover, the network of areas whose neuronal dynamics are associated with external inputs and the network of areas that appears to be intrinsically driven complement each other, providing coverage of most of the posterior cortex. Thus, we propose that naturalistic stimuli reveal a fundamental neuroanatomical partition of the human posterior cortex into 2 global networks: an "extrinsic" system, comprising areas associated with the processing of external inputs, and an "intrinsic" system, largely overlapping with the task-negative, default-mode network, comprising areas associated with--as yet not fully understood--intrinsically oriented functions.

Computational hyperspectral interferometry for studies of brain function: proof of concept

Hyperspectral interferometric microscopy uses a unique combination of optics and algorithm design to extract information. Local brain activity rapidly changes local blood flow and red blood cell concentration (absorption) and oxygenation (color). We demonstrate that brain activity evoked during whisker stimulation can be detected with hyperspectral interferometric microscopy to identify the active whisker-barrel cortex in the rat brain. Information about constituent components is extracted across the entire spectral band. Algorithms can be flexibly optimized to discover, detect, quantify, and visualize a wide range of significant biological events, including changes relevant to the diagnosis and treatment of disease.