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• Blood lactate does not strongly contribute to the initial dip in neuronal lactate. • Astrocyte-neuron lactate shuttle conditionally provides lactate to the neurons. • Existence and strength of lactate shuttle depends on transporter properties. • Lactate shuttling also depends on the astrocytic lactate production. Emerging evidence emphasizes lactate's involvement in both physiological processes (energy metabolism, memory, etc.) and disease (traumatic brain injury, epilepsy, etc.). Furthermore, the usefulness of mathematical modeling in deciphering underlying dynamics of the brain to investigate lactate roles and mechanisms of action has been well established. Here, we analyze a novel mathematical model of brain lactate exchanges between four compartments: neurons, astrocytes, capillaries, and extracellular space. A system of four ordinary differential equations is proposed to explain interactions between these compartments. We first optimize and analyze the model's parameters under normal, resting state conditions, and then use it to simulate changes linked to elevated arterial lactate. Our results show that even though increased arterial lactate results in increased uptake by astrocytes and release to the extracellular space, it cannot strongly recover the initial drop in neuronal lactate concentration. Also, we show that the direction of lactate transport between the compartments is influenced by the maximum astrocyte production rate and the transport rate between astrocytes and extracellular space. [ABSTRACT FROM AUTHOR]

When walking on a split-belt treadmill, where each leg is driven at a different speed, a temporary change is made to the typical steady-state walking pattern. The exact ways in which the brain controls these temporary changes to walking are still unknown. Ten young adults (23±3y) walked on a split-belt treadmill for 30 min on 2 separate occasions: tied-belt control with both belts at comfortable walking speed, and continuous adjustment where speed ratio between belts changed every 15 seconds. 18F-fluorodeoxyglucose (18FDG) positron emission tomography (PET) imaging measured whole brain glucose metabolism distribution, or activation, during each treadmill walking condition. The continuous adjustment condition, compared to the tied-belt control, was associated with increased activity of supplementary motor areas (SMA), posterior parietal cortex (PPC), anterior cingulate cortex and anterior lateral cerebellum, and decreased activity of posterior cingulate and medial prefrontal cortex. In addition, peak activation of the PPC, SMA and PFC were correlated with cadence and temporal gait variability. We propose that a "fine-tuning" network for human locomotion exists which includes brain areas for sensorimotor integration, motor planning and goal directed attention. These findings suggest that distinct regions govern the inherent flexibility of the human locomotor plan to maintain a successful and adjustable walking pattern. • 18FDG PET imaging measured brain activation during split-belt treadmill walking. • A "fine-tuning" network increased activity: SMA, PPC, ACC and Cerebellar Lobule VI. • Aspects of the DMN (PCC, mPFC) decreased activity compared to typical walking. • Unplanned locomotor plan updates require a widespread network of brain areas. [ABSTRACT FROM AUTHOR]

Abstract Awake rat brain positron emission tomography (PET) has previously been developed to avoid the influence of anesthesia on the rat brain response. In the present work, we further the awake rat brain scanning methodology to establish simultaneous scanning of two interacting rats in a high resolution, large field of view PET scanner. Awake rat imaging methodology based on point source tracking was adapted to be used in a dedicated human brain scanner, the ECAT high resolution research tomograph (HRRT). Rats could freely run on a horizontal platform of 19.4 × 23 cm placed inside the HRRT. The developed methodology was validated using a motion resolution phantom experiment, 3 awake single rat [18F]FDG scans as well as an [18F]FDG scan of 2 interacting rats. The precision of the point source based motion tracking was 0.359 mm (standard deviation). Minor loss of spatial resolution was observed in the motion corrected reconstructions (MC) of the resolution phantom compared to the motion-free reconstructions (MF). The full-width-at-half-maximum of the phantom rods were increased by on average 0.37 mm in the MC compared to the MF. During the awake scans, extensive motion was observed with rats moving throughout the platform area. The average rat head motion speed was 1.69 cm/s. Brain regions such as hippocampus, cortex and cerebellum could be recovered in the motion corrected reconstructions. Relative regional brain uptake of MC and MF was strongly correlated (Pearson's r ranging from 0.82 to 0.95, p < 0.0001). Awake rat brain PET imaging of interacting rats was successfully implemented on the HRRT scanner. The present method allows a large range of motion throughout a large field of view as well as to image two rats simultaneously opening the way to novel rat brain PET study designs. Highlights • Brain PET scans of two interacting rats were performed in a large FOV scanner. • High speed, accurate motion tracking without additional hardware. • Motion corrected images with good spatial resolution and accurate quantification. • The method enables to study the animal brain response in a social context. [ABSTRACT FROM AUTHOR]

Abstract: [18F]fluoroethoxybenzovesamicol ([18F]FEOBV) is one of the most promising radioligands for imaging the vesicular ACh transporter (VAChT) with positron emission tomography (PET). We report here that this method can detect subtle cholinergic terminals losses such as those associated with aging, or those following a partial lesion of the nucleus basalis magnocellularis (NBM). Twenty-one adult rats were evenly distributed in three groups including 1) aged rats (18months); 2) young rats (3months); and 3) rats with unilateral lesion of the NBM, following a local stereotaxic infusion of 192 IgG-saporin. In both normal and lesioned rats, our results revealed the highest [18F]FEOBV binding to be in the striatum, followed by similar values in both frontal cortex and thalamus, while lower values were observed in both hippocampus and temporo-parietal cortex. This binding distribution is consistent with the known anatomy of brain cholinergic systems. In the lesioned rats, [18F]FEOBV binding was found to be reduced mostly in the ventral frontal cortex on the side of the lesion, but some reductions were also observed in the homologous region of the contralateral hemisphere. Aging was found to be associated with a [18F]FEOBV binding reduction limited to the hippocampus of both hemispheres. [18F]FEOBV appears to be a very promising marker for the in vivo quantification of the brain VAChT; PET imaging of this agent allows in vivo detection of both physiological and pathological reductions of cholinergic terminals density. [Copyright &y& Elsevier]

Visual assessment, with significant inter- or intraobserver variability, is still the norm for the evaluation of Single Photon Emission Computerized Tomography (SPECT) cerebral perfusion studies. We present in this paper an automated method for screening SPECT studies to detect diffuse disseminated abnormalities based on a computerized atlas of normal regional cerebral blood flow (rCBF). To generate the atlas, a set of normal brain SPECT studies are registered together. The atlas contains the intensity mean, the nonlinear displacement mean, and the variance of the activity pattern. A patient is then evaluated by registering his or her SPECT volume to the atlas and computing the nonlinear 3-D displacement of each voxel needed for the best shape fit to it. A voxel is counted as “abnormal” if the intensity difference between the atlas and the registered patient (or if the 3-D motion necessary to move the voxel to its registered position) is superior to 3 SD of normal mean. The number of abnormal voxels is used to classify studies. We validated this approach on 24 SPECT perfusion studies selected visually for having clear diffuse anomalies and 21 normal studies. A Markovian segmentation algorithm is also used to identify the white and gray matters for regional analysis. Based on the number of abnormal voxels, two supervised classifiers were tested: (1) minimum distance-to-mean and (2) Bayesian. The analysis of the intensity and displacement “abnormal” voxels allow one to achieve an 80% correct classification rate for the whole brain and a 93% rate if we consider only voxels in the segmented gray matter region. [Copyright &y& Elsevier]