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Neuroimaging studies have shown that brain activity is variable and changes according to stimuli and the environmental context, reflecting brain coding or information representations at different processing levels. However, little is known about activity organization that reflects coding strategies. Here, we explored and compared two different coding approaches, spatial via cross-correlation and intensity-based coding using mutual information. Using two fMRI datasets and different seeds, we searched for the spatial and intensity-based similarities with the seeds in brain activity. Our results showed that, apart from the seed regions, significant regions detected by intensity-based similarity analysis differ completely from those found using cross-correlation. These findings may indicate that information shared through spatial coding differs from that transmitted via non-spatial coding processes. Our results suggest that brain coding is organized in several different ways to optimize information processing.

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

We created a volumetric template of the marmoset (Callithrix jacchus) brain, which enables localization of the cortical areas defined in the Paxinos et al. (The marmoset brain in stereotaxic coordinates. Elsevier Academic Press, Cambridge, 2012) marmoset brain atlas, as well as seven broader cortical regions (occipital, temporal, parietal, prefrontal, motor, limbic, insular), different brain compartments (white matter, gray matter, cerebro-spinal fluid including ventricular spaces), and various other structures (brain stem, cerebellum, olfactory bulb, hippocampus). The template was designed from T1-weighted MR images acquired using a 3 T MRI scanner. It was based on a single fully segmented marmoset brain image, which was transported onto the mean of 13 adult marmoset brain images using a diffeomorphic strategy that fully preserves the brain topology. In addition, we offer an automatic segmentation pipeline which fully exploits the proposed template. The segmentation pipeline was quantitatively assessed by comparing the results of manual and automated segmentations. An associated program, written in Python, can be used from a command-line interface, or used interactively as a module of the 3DSlicer software. This program can be applied to the analysis of multimodal images, to map specific cortical areas in lesions or to define the seeds for further tractography analyses.

It is well established that human life expectancy increases considerably with an ever-growing number of people suffering from age-related cognitive decline and degenerative brain diseases. This necessitates the development of animal models to counteract or stop the progression of the decline early enough. Presently, primate models are few, and many studies argue for the marmoset as an interesting primate model presenting a short life span and being easily available in research laboratories. In this article, we propose the marmoset as a valid model for cognitive decline. Using a computer touch screen, we trained 35 marmosets from 2 to 14 years of age to perform reversal learning and delayed-matching-to-position tasks. We found typical age-related cognitive deficits related to executive functions and spatial working memory. Applying a recursive algorithm, we detected 2 critical periods from which deficits appear. Mainly, response strategy deficits appear from age 4, whereas impairments in inhibitory control appear from age 7–8. Furthermore, the presence of outliers, sometimes at an early age, suggests pathological cognitive deficits that would require imaging exploration in parallel to behavior.

Modern neuroimaging represents three-dimensional brain activity, which varies across brain regions. It remains unknown whether activity within brain regions is organized in spatial configurations to reflect perceptual and cognitive processes. We developed a rotational cross-correlation method allowing a straightforward analysis of spatial activity patterns for the precise detection of the spatially correlated distributions of brain activity. Using several statistical approaches, we found that the seed patterns in the fusiform face area were robustly correlated to brain regions involved in face-specific representations. These regions differed from the non-specific visual network meaning that activity structure in the brain is locally preserved in stimulation-specific regions. Our findings indicate spatially correlated perceptual representations in cerebral activity and suggest that the 3D coding of the processed information is organized in locally preserved activity patterns. More generally, our results provide the first demonstration that information is represented and transmitted as local spatial configurations of brain activity.

International audience; Modern neuroimaging represents three-dimensional brain activity, which varies across brain regions. It remains unknown whether activity of different brain regions has similar spatial organization to reflect similar cognitive processes. We developed a rotational cross-correlation method allowing a straightforward analysis of spatial activity patterns distributed across the brain in stimulation specific contrast images. Results of this method were verified using several statistical approaches on real and simulated random datasets. We found, for example, that the seed patterns in the fusiform face area were robustly correlated to brain regions involved in face-specific representations. These regions differed from the non-specific visual network meaning that activity structure in the brain is locally preserved in stimulus-specific regions. Our findings indicate spatially correlated perceptual representations in cerebral activity and suggest that the 3D coding of the processed information is organized using locally preserved activity patterns across the brain. More generally, our results demonstrate that information is represented and shared in the local spatial configurations of brain activity.

The presence of cysts is a rare occurrence for intracranial meningiomas in adults. We report our experience in a large consecutive series of cystic meningiomas. We prospectively collected data for a dedicated database of cystic meningioma cases between January 2004 and December 2011 in two tertiary neurosurgical centers. Studied data included preoperative imaging, surgical records, and pathology reports. Among 1214 surgeries for intracranial meningioma, we identified 43 cases of cystic meningioma, corresponding to an incidence of 3.5 %. The most common localization was the hemispheric convexity (17/43 cases). Twenty-eight patients had intratumoral cysts, nine peritumoral, and five mixed intra and extratumoral. In 29 patients with available diffusion imaging, ADC coefficients were significantly lower in grade II-III tumors compared to grade I (p = 0.01). Complete resection of the cystic components was possible in 27/43 patients (63 %); partial resection in 4/43 (9 %); in 6/43 (14 %) cyst resection was not possible but multiple biopsies were performed from the cystic walls; in another 6/43 (14 %) the cystic wall was not identified during surgery. Cells with neoplastic features were identified within the cyst walls at pathology in 26/43 cases (60 %). All patients were followed-up for 24 months; long-term follow-up was available only in 32 patients for an average period of 49 months (range, 36–96 months). No recurrence requiring surgery was observed. Cystic meningiomas are rare. Cells with neoplastic features are often identified within the cyst walls. Complete cyst resection is recommendable when considered technically feasible and safe.

The number of studies that use the common marmoset (Callithrix jacchus) in various fields of neurosciences is increasing dramatically. In general, animals enter the study when their health status is considered satisfactory on the basis of classical clinical investigations. In behavioral studies, variations of score between individuals are frequently observed, some of them being considered as poor performers or outliers. Experimenters rarely consider the fact that it could be related to some brain anomaly. This raises the important issue of the reliability of such classical behavioral approaches without using complementary imaging, especially in animals lacking striking external clinical signs. Here we report the case of a young marmoset which presented a set of cognitive impairments in two different tasks compared to other age-matched animals. Brain imaging revealed a patent right lateral ventricular enlargement with a mild hippocampal atrophy. This abnormality could explain the cognitive impairments of this animal. Such a case points to the importance of complementing behavioral studies by imaging explorations to avoid experimental bias.