Brain Activation Maps Research Articles

Brain Activity Mapping inMecp2Mutant Mice Reveals Functional Deficits in Forebrain Circuits, Including Key Nodes in the Default Mode Network, that are Reversed with Ketamine Treatment

Excitatory-inhibitory imbalance has been identified within specific brain microcircuits in models of Rett syndrome (RTT) and other autism spectrum disorders (ASDs). However, macrocircuit dysfunction across the RTT brain as a whole has not been defined. To approach this issue, we mapped expression of the activity-dependent, immediate-early gene product Fos in the brains of wild-type (Wt) and methyl-CpG-binding protein 2 (Mecp2)-null (Null) mice, a model of RTT, before and after the appearance of overt symptoms (3 and 6 weeks of age, respectively). At 6 weeks, Null mice exhibit significantly less Fos labeling than Wt in limbic cortices and subcortical structures, including key nodes in the default mode network. In contrast, Null mice exhibit significantly more Fos labeling than Wt in the hindbrain, most notably in cardiorespiratory regions of the nucleus tractus solitarius (nTS). Using nTS as a model, whole-cell recordings demonstrated that increased Fos expression in Nulls at 6 weeks of age is associated with synaptic hyperexcitability, including increased frequency of spontaneous and miniature EPSCs and increased amplitude of evoked EPSCs in Nulls. No such effect of genotype on Fos or synaptic function was seen at 3 weeks. In the mutant forebrain, reduced Fos expression, as well as abnormal sensorimotor function, were reversed by the NMDA receptor antagonist ketamine. In light of recent findings that the default mode network is hypoactive in autism, our data raise the possibility that hypofunction within this meta-circuit is a shared feature of RTT and other ASDs and is reversible.

Blood oxygenation level‐dependent functional MRI signal turbulence caused by ultrahigh spatial resolution: numerical simulation and theoretical explanation

High-spatial-resolution functional MRI (fMRI) can enhance image contrast and improve spatial specificity for brain activity mapping. As the voxel size is reduced, an irregular magnetic fieldmap will emerge as a result of less local averaging, and will lead to abnormal fMRI signal evolution with respect to the image acquisition TE. In this article, we report this signal turbulence phenomenon observed in simulations of ultrahigh-spatial-resolution blood oxygenation level-dependent (BOLD) fMRI (voxel size of less than 50 × 50 × 50 µm³). We present a four-level coarse-to-fine multiresolution BOLD fMRI signal simulation. Based on the statistical histogram of an intravoxel fieldmap, we reformulate the intravoxel dephasing summation (a form of Riemann sum) into a new formula that is a discrete Fourier transformation of the intravoxel fieldmap histogram (a form of Lebesgue sum). We interpret the BOLD signal formation by relating its magnitude (phase) to the even (odd) symmetry of the fieldmap histogram. Based on multiresolution BOLD signal simulation, we find that the signal turbulence mainly emerges at the vessel boundary, and that there are only a few voxels (less than 10%) in an ultrahigh-resolution image that reveal turbulence in the form of sparse point noise. Our simulation also shows that, for typical human brain imaging of the cerebral cortex with millimeter resolution, TE < 30 ms and B₀ = 3 T, we are unlikely to observe BOLD signal turbulence. Overall, the main causes of voxel signal turbulence include a high spatial resolution, high field, long TE and large vessel.

A Preliminary Report on the Use of Functional Magnetic Resonance Imaging with Simultaneous Urodynamics to Record Brain Activity During Micturition

We mapped brain activity during micturition using functional magnetic resonance imaging with simultaneous recording of urodynamic properties during slow bladder filling and micturition. We evaluated 12 healthy female volunteers 20 to 68 years old. Eight subjects could urinate while supine. Meaningful data were obtained on 6 of these subjects. Brain activity was recorded continuously during bladder filling and micturition. Functional magnetic resonance imaging measurements made during the micturition phase were used for the final analysis. Using group statistics we identified clusters of brain activity in the parahippocampal gyrus, anterior cingulate gyrus, inferior temporal gyrus and inferior frontal gyrus during micturition. At the individual level we also observed activation in the upper pontine region, thalamus and posterior cingulum. In subjects unable to void brain activation was documented in the frontal lobe and posterior cingulate gyrus but not in the pons, thalamus or anterior cingulate gyrus. In 5 subjects we identified a relevant pattern of brain activity during the terminal portion of the filling phase when the patient reported a strong desire to urinate. This new protocol allows for the localization of brain structures that are active during micturition. Data suggest that additional validation studies are needed. Future studies will test modifications that include more detailed monitoring of bladder sensation, stratifying subjects based on age and gender, and increasing the number of data points by adding subjects and the number of micturitions recorded in a single subject.

Functional magnetic resonance imaging of methamphetamine craving

The study aimed to explore the abnormal activation of special brain areas associated with methamphetamine craving using functional magnetic resonance imaging (fMRI) and to reveal the neurobiological basis of addiction. Twenty-six methamphetamine addicts and 26 healthy subjects were scanned by brain fMRI while watching pictures of happy, sad, or methamphetamine to acquire resource data. SPM5 was used to analyze fMRI data to get related brain activation map, and it was found that methamphetamine addicts had high brain activation in cingulate and low activation in frontal lobe when watching methamphetamine-cue pictures. This study demonstrated that methamphetamine addicts had emotion-related brain activation abnormalities.

The Brain Activity Map Project and the Challenge of Functional Connectomics

The function of neural circuits is an emergent property that arises from the coordinated activity of large numbers of neurons. To capture this, we propose launching a large-scale, international public effort, the Brain Activity Map Project, aimed at reconstructing the full record of neural activity across complete neural circuits. This technological challenge could prove to be an invaluable step toward understanding fundamental and pathological brain processes.

Altered brain functional connectivity in relation to perception of scrutiny in social anxiety disorder

Although the fear of being scrutinized by others in a social context is a key symptom in social anxiety disorder (SAD), the neural processes underlying the perception of scrutiny have not previously been studied by functional magnetic resonance imaging (fMRI). We used fMRI to map brain activation during a perception-of-scrutiny task in 20 SAD patients and 20 controls. A multi-dimensional analytic approach was used. Scrutiny perception was mediated by activation of the medial frontal cortex, insula–operculum region and cerebellum, and the additional recruitment of visual areas and the thalamus in patients. Between-group comparison demonstrated significantly enhanced brain activation in patients in the primary visual cortex and cerebellum. Functional connectivity mapping demonstrated an abnormal connectivity between regions underlying general arousal and attention. SAD patients showed significantly greater task-induced functional connectivity in the thalamo-cortical and the fronto-striatal circuits. A statistically significant increase in task-induced functional connectivity between the anterior cingulate cortex and scrutiny-perception-related regions was observed in the SAD patients, suggesting the existence of enhanced behavior-inhibitory control. The presented data indicate that scrutiny perception in SAD enhances brain activity in arousal–attention systems, suggesting that fMRI may be a useful tool to explore such a behavioral dimension.

Effective connectivity between superior temporal gyrus and Heschl's gyrus during white noise listening: linear versus non-linear models.

Purpose:This fMRI study is about modelling the effective connectivity between Heschl’s gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices.Materials & methods:Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity.Results:Group results indicated significant asymmetrical activation (puncorr < 0.001) in bilateral HG and STG. Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability, r = 0.7830 and exceedance probability, ϕ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p < 0.05). Subsequent model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, ϕ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself.Conclusion:We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with the activity in STG influencing the STG-HG connectivity non-linearly.

Poster #27 NEURAL CORRELATES OF TOM IN SCHIZOPHRENIA: A META-ANALYSIS OF FUNCTIONAL NEUROIMAGING STUDIES

The world is aging and, as the elderly population increases, age-related cognitive decline emerges as a major concern. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), allow the investigation of the neural bases of age-related cognitive changes in vivo. Typically, fMRI studies map brain activity while subjects perform cognitive tasks, but such paradigms are often difficult to implement on a wider basis. Resting-state fMRI (rs-fMRI) has emerged as an important alternative modality of fMRI data acquisition, during which no specific task is required. Due to such simplicity and the reliability of rs-fMRI data, this modality presents increased feasibility and potential for clinical application in the future. With rs-fMRI, fluctuations in regional brain activity can be detected across separate brain regions and the patterns of intercorrelation between the functioning of these regions are measured, affording quantitative indices of resting-state functional connectivity (RSFC). This review article summarizes the results of recent rs-fMRI studies that have documented a variety of aging-related RSFC changes in the human brain, discusses the neurophysiological hypotheses proposed to interpret such findings, and provides an overview of the future, highly promising perspectives in this field.

2198 BRAIN ACTIVITY DURING MICTURITION MEASURED BY FUNCTIONAL MAGNETIC RESONANCE IMAGING

You have accessJournal of UrologyImaging/Radiology: Uroradiology II1 Apr 20122198 BRAIN ACTIVITY DURING MICTURITION MEASURED BY FUNCTIONAL MAGNETIC RESONANCE IMAGING Jan Krhút, Jaroslav Tintera, Petr Holý, Roman Zachoval, and Peter Zvara Jan KrhútJan Krhút Ostrava, Czech Republic More articles by this author , Jaroslav TinteraJaroslav Tintera Prague, Czech Republic More articles by this author , Petr HolýPetr Holý Prague, Czech Republic More articles by this author , Roman ZachovalRoman Zachoval Prague, Czech Republic More articles by this author , and Peter ZvaraPeter Zvara Burlington, VT More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.2372AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The use of functional magnetic resonance imaging (fMRI) in elucidation of central neuroregulation of various organs and systems grew explosively during the last decade, but only a small number of original research papers focused on brain control of lower urinary tract. Functional MRI studies performed to date focused on brain activity during the storage phase. The goal of this study was to to map brain activity during micturition using fMRI performed simultaneously with urodynamics and slow bladder filling. METHODS We evaluated 12 healthy female volunteers aged 20 – 68 years. The measurements consisted of 210 dynamics, each scanning the brain in 35 slices. The urinary bladder was filled at a rate of 50 mL/min until a strong desire to void was reported at which point the patient was instructed to void. Brain activity was recorded continuously during bladder filling and micturition (Figure). Functional MRI measurements during the micturition phase and during the adjacent portions of the filling phase were used in the final analysis. RESULTS Clusters of brain activity during micturition were identified in the pons, thalamus, cingulate gyrus and the medial prefrontal gyrus. In patients who were unable to void, brain activation was documented in the frontal lobe and posterior cingulate gyrus but not in the pons, thalamus or anterior cingulate gyrus. In 5 patients we identified a reproducible pattern of brain activity during the terminal portion of the filling phase when the patient reported a strong desire to urinate. Due to the anatomical proximity of the brain regions activated during period when a strong desire to urinate was reported and during micturition, it proved impossible to separate them functionally. CONCLUSIONS This new protocol allows for localization of brain structures regulating micturition. Our data suggest that by increasing the number of recordings and monitoring bladder sensation in a more detailed manner will allow precise identification of the brain structures involved in neuroregulation of the lower urinary tract during bladder filling and micturition. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e886 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jan Krhút Ostrava, Czech Republic More articles by this author Jaroslav Tintera Prague, Czech Republic More articles by this author Petr Holý Prague, Czech Republic More articles by this author Roman Zachoval Prague, Czech Republic More articles by this author Peter Zvara Burlington, VT More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy.

A major methodological challenge of functional near-infrared spectroscopy (fNIRS) is its high sensitivity to haemodynamic fluctuations in the scalp. Superficial fluctuations contribute on the one hand to the physiological noise of fNIRS, impairing the signal-to-noise ratio, and may on the other hand be erroneously attributed to cerebral changes, leading to false positives in fNIRS experiments. Here we explore the localisation, time course and physiological origin of task-evoked superficial signals in fNIRS and present a method to separate them from cortical signals. We used complementary fNIRS, fMRI, MR-angiography and peripheral physiological measurements (blood pressure, heart rate, skin conductance and skin blood flow) to study activation in the frontal lobe during a continuous performance task. The General Linear Model (GLM) was applied to analyse the fNIRS data, which included an additional predictor to account for systemic changes in the skin.We found that skin blood volume strongly depends on the cognitive state and that sources of task-evoked systemic signals in fNIRS are co-localized with veins draining the scalp. Task-evoked superficial artefacts were mainly observed in concentration changes of oxygenated haemoglobin and could be effectively separated from cerebral signals by GLM analysis. Based on temporal correlation of fNIRS and fMRI signals with peripheral physiological measurements we conclude that the physiological origin of the systemic artefact is a task-evoked sympathetic arterial vasoconstriction followed by a decrease in venous volume.Since changes in sympathetic outflow accompany almost any cognitive and emotional process, we expect scalp vessel artefacts to be present in a wide range of fNIRS settings used in neurocognitive research. Therefore a careful separation of fNIRS signals originating from activated brain and from scalp is a necessary precondition for unbiased fNIRS brain activation maps.

Large Enhancement of Perfusion Contribution on fMRI Signal

The perfusion contribution to the total functional magnetic resonance imaging (fMRI) signal was investigated using a rat model with mild hypercapnia at 9.4 T, and human subjects with visual stimulation at 4 T. It was found that the total fMRI signal change could be approximated as a linear superposition of 'true' blood oxygenation level-dependent (BOLD; T(2)/T(2)(*)) effect and the blood flow-related (T(1)) effect. The latter effect was significantly enhanced by using short repetition time and large radiofrequency pulse flip angle and became comparable to the 'true' BOLD signal in response to a mild hypercapnia in the rat brain, resulting in an improved contrast-to-noise ratio (CNR). Bipolar diffusion gradients suppressed the intravascular signals but had no significant effect on the flow-related signal. Similar results of enhanced fMRI signal were observed in the human study. The overall results suggest that the observed flow-related signal enhancement is likely originated from perfusion, and this enhancement can improve CNR and the spatial specificity for mapping brain activity and physiology changes. The nature of mixed BOLD and perfusion-related contributions in the total fMRI signal also has implication on BOLD quantification, in particular, the BOLD calibration model commonly used to estimate the change of cerebral metabolic rate of oxygen.

Biophysical and Physiological Origins of Blood Oxygenation Level-Dependent fMRI Signals

After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O(2) utilization (CMRO(2)), (5) dynamic responses of BOLD, CBF, CMRO(2), and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means.

Cortical brain imaging by adaptive filtering of NIRS signals

This paper presents an online brain imaging framework for cognitive tasks conducted with functional near-infrared spectroscopy (fNIRS). The measured signal at each channel is regarded as the output from a linear system with unknown coefficients. The unknown coefficients are estimated by using the recursive least squares estimation (RLSE) method. The validity of the estimated parameters is tested using the t-statistics. Contrary to the classical approach that is offline and applies the same preprocessing scheme to all channels, the proposed RLSE method for a linear model formulation provides an independent robust adaptive process for individual channels. The experiments carried out with two fNIRS instruments (continuous-wave and frequency-domain) have verified the potential of the proposed methodology which can facilitate a prompt medical diagnostics by providing real-time brain activation maps.

A Review of Epilepsy Diagnosis Using PET Parameters

Epilepsy is caused by abnormal excessive electric discharges from the neurons in the brain. Epileptic seizures are non- specific responses of the brain to many types of insults. The structural abnormalities causing epilepsy can be identified using various state of art imaging methods. Through a combination of brain activity monitoring, imaging and mapping techniques, physicians can locate the specific area in the brain causing epileptic discharges and identify its location in relation to those areas in the brain controlling vital functions. Positron Emission Tomography (PET) has emerged as a useful tool to identify abnormal metabolic activity of the epileptogenic foci. Parameters like asymmetric index, stan- dard uptake value (SUV) etc obtained by PET are processed and analyzed for identifying the origin of epileptic sei- zures. This paper discuss the techniques used to diagnose in general and to localize the epileptogenic regions using post-processing other features on PET imaging.

Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity

Inverse inference, or reading, is a recent paradigm for analyzing functional magnetic resonance imaging (fMRI) data, based on pattern recognition and statistical learning. By predicting some cognitive variables related to brain activation maps, this approach aims at decoding brain activity. Inverse inference takes into account the multivariate information between voxels and is currently the only way to assess how precisely some cognitive information is encoded by the activity of neural populations within the whole brain. However, it relies on a prediction function that is plagued by the curse of dimensionality, since there are far more features than samples, i.e., more voxels than fMRI volumes. To address this problem, different methods have been proposed, such as, among others, univariate feature selection, feature agglomeration and regularization techniques. In this paper, we consider a sparse hierarchical structured regularization. Specifically, the penalization we use is constructed from a tree that is obtained by spatially-constrained agglomerative clustering. This approach encodes the spatial structure of the data at different scales into the regularization, which makes the overall prediction procedure more robust to inter-subject variability. The regularization used induces the selection of spatially coherent predictive brain regions simultaneously at different scales. We test our algorithm on real data acquired to study the mental representation of objects, and we show that the proposed algorithm not only delineates meaningful brain regions but yields as well better prediction accuracy than reference methods.

Effect of frequency deviance direction on performance and mismatch negativity

The mismatch negativity (MMN) component of the auditory event-related potential is associated with automatic perceptual inference concerning changes in auditory stimulation. Recent studies have addressed the question whether performance and MMN is affected by the direction of frequency deviance. In the present study, the frequency MMN and performance is investigated during an auditory identification task. Specifically, we examined the effect of positive and negative differences between the present stimulus and the previous response frequencies on performance as well as on the characteristics of stimulus-locked ERPs and brain activation maps. The results show that frequency deviants creating mismatch conditions increase the likelihood of error commission. The decrease in performance achieves statistical significance in the case of positive frequency deviants. In the latter case, ERP amplitude values of the Fz electrode at 164 ms after stimulus onset are statistically larger for mismatch as opposed to no-mismatch condition. This corresponds to significance differences in the activation maps at Brodmann area 11, superior frontal gyrus, and the frontal lobe. The present findings revealed dissociations in behavioral and ERP responses in the processing of positive and negative frequency deviance, lending support to the notion that MMN is more sensitive to increments than to decrements in frequency.

Central Nervous System and Computation

Computational systems are useful in neuroscience in many ways. For instance, they may be used to construct maps of brain structure and activation, or to describe brain processes mathematically. Furthermore, they inspired a powerful theory of brain function, in which the brain is viewed as a system characterized by intrinsic computational activities or as a "computational information processor. "Although many neuroscientists believe that neural systems really perform computations, some are more cautious about computationalism or reject it. Thus, does the brain really compute? Answering this question requires getting clear on a definition of computation that is able to draw a line between physical systems that compute and systems that do not, so that we can discern on which side of the line the brain (or parts of it) could fall. In order to shed some light on the role of computational processes in brain function, available neurobiological data will be summarized from the standpoint of a recently proposed taxonomy of notions of computation, with the aim of identifying which brain processes can be considered computational. The emerging picture shows the brain as a very peculiar system, in which genuine computational features act in concert with noncomputational dynamical processes, leading to continuous self-organization and remodeling under the action of external stimuli from the environment and from the rest of the organism.

Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo

Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we have developed new devices integrating ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors connected using many fewer wires. We used this system to record novel spatial properties of brain activity in vivo, including sleep spindles, single-trial visual evoked responses, and electrographic seizures. Our electrode array allowed us to discover that seizures may manifest as recurrent spiral waves which propagate in the neocortex. The developments reported here herald a new generation of diagnostic and therapeutic brain-machine interface (BMI) devices.

Effects of manganese injected into rat nostrils: implications for in vivo functional study of olfaction using MEMRI

Manganese-enhanced magnetic resonance imaging (MEMRI) is a powerful tool for visualizing neuronal pathways and mapping brain activity modulation. A potential drawback of MEMRI lies in the toxic effects of manganese (Mn), which also depend on its administration route. The aim of this study was to analyze the effects of Mn doses injected into the nostrils of rats on both olfactory perception and MRI contrast enhancement. For this purpose, doses in the range 0–8 μmol MnCl 2 were tested. Behavioral items were quantified with and without odor stimulation during the first 2 h following Mn injection. The MRI study was performed after 16 h of intermittent olfactory stimulations. Behavioral results showed that, during the early period following Mn administration, spontaneous motor activity was not affected, while odor-related behaviors were dose-dependently reduced. MRI results showed that, in the primary olfactory cortex, contrast was rapidly enhanced for Mn doses up to 0.3 μmol and very slowly above. This dose of 0.3 μmol Mn can thus be taken as the optimal dose for injection into rat nostrils to ensure a reproducible contrast in MRI studies while sparing olfactory perception.

Imaging Odor-Evoked Activities in the Mouse Olfactory Bulb using Optical Reflectance and Autofluorescence Signals

In the brain, sensory stimulation activates distributed populations of neurons among functional modules which participate to the coding of the stimulus. Functional optical imaging techniques are advantageous to visualize the activation of these modules in sensory cortices with high spatial resolution. In this context, endogenous optical signals that arise from molecular mechanisms linked to neuroenergetics are valuable sources of contrast to record spatial maps of sensory stimuli over wide fields in the rodent brain. Here, we present two techniques based on changes of endogenous optical properties of the brain tissue during activation. First the intrinsic optical signals (IOS) are produced by a local alteration in red light reflectance due to: (i) absorption by changes in blood oxygenation level and blood volume (ii) photon scattering. The use of in vivo IOS to record spatial maps started in the mid 1980's with the observation of optical maps of whisker barrels in the rat and the orientation columns in the cat visual cortex1. IOS imaging of the surface of the rodent main olfactory bulb (OB) in response to odorants was later demonstrated by Larry Katz's group2. The second approach relies on flavoprotein autofluorescence signals (FAS) due to changes in the redox state of these mitochondrial metabolic intermediates. More precisely, the technique is based on the green fluorescence due to oxidized state of flavoproteins when the tissue is excited with blue light. Although such signals were probably among the first fluorescent molecules recorded for the study of brain activity by the pioneer studies of Britton Chances and colleagues3, it was not until recently that they have been used for mapping of brain activation in vivo. FAS imaging was first applied to the somatosensory cortex in rodents in response to hindpaw stimulation by Katsuei Shibuki's group4. The olfactory system is of central importance for the survival of the vast majority of living species because it allows efficient detection and identification of chemical substances in the environment (food, predators). The OB is the first relay of olfactory information processing in the brain. It receives afferent projections from the olfactory primary sensory neurons that detect volatile odorant molecules. Each sensory neuron expresses only one type of odorant receptor and neurons carrying the same type of receptor send their nerve processes to the same well-defined microregions of ˜100μm3 constituted of discrete neuropil, the olfactory glomerulus (Fig. 1). In the last decade, IOS imaging has fostered the functional exploration of the OB5, 6, 7 which has become one of the most studied sensory structures. The mapping of OB activity with FAS imaging has not been performed yet. Here, we show the successive steps of an efficient protocol for IOS and FAS imaging to map odor-evoked activities in the mouse OB.