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The breakdown of attentional mechanisms after brain damage can have drastic behavioral consequences, as in patients suffering from spatial neglect. While much research has concentrated on impaired attention to targets contralateral to sites of brain damage, here we report the ipsilateral enhancement of visual attention after repetitive transcranial magnetic stimulation (rTMS) of parietal cortex at parameters known to reduce cortical excitability. Normal healthy subjects received rTMS (1 Hz, 10 mins) over right or left parietal cortex. Subsequently, detection of visual stimuli contralateral to the stimulated hemisphere was consistently impaired when stimuli were also present in the opposite hemifield, mirroring the extinction phenomenon commonly observed in neglect patients. Additionally, subjects’ attention to ipsilateral targets improved significantly over normal levels. These results underline the potential of focal brain dysfunction to produce behavioral improvement and give experimental support to models of interhemispheric competition in the distributed brain network for spatial attention.

Neuroscience students take it for granted that there aremany more glia than neurons in the brain. Neurosciencetextbooks state with confidence: ‘‘Although there are manyneurons in the human brain…, glia outnumber neurons bytenfold’’ (Bear et al. 2006) or, not to be outdone, even by‘‘10–50 times’’, as claimed in another text (Kandel et al.2000). This fact is happily invoked by gliologists to pro-mote the status of their field.Given this well-accepted figure, we were surprised whenour cell counts in the prefrontal cortex of the rhesusmonkey turned up a glia-to-neuron ratio (GNR) of justabout 1 (Dombrowski et al. 2001). There was someregional variation, but no prefrontal area had a GNR largerthan 1.2. Maybe the proportion of glia is very different inother cortical regions or other parts of the brain, so that theoverall ratio for the whole brain is much larger than 1?Classic studies, however, conducted by O’Kusky andColonnier (1982) in the opposite pole of the brain, thevisual cortex, had reported an even lower GNR of 0.5.More recently, Lidow and Song (2001) estimated the GNRacross a whole cortical hemisphere of healthy rhesusmonkeys to be 0.82. And another recent study of neuronand glia numbers in various frontal, parietal, temporal andoccipital cortical regions in the rhesus monkey also found alow average GNR of 0.56 (Christensen et al. 2007).However, the same study also showed an average GNR of1.72 across hippocampal regions CA1 and CA2-3.All these estimates were based on stereologic cellcounting methods (West 1999), which are consideredreliable and are now widely used in neuroscience. Themethods are based on the simple and fundamental principleof unbiased counting, with each cell having an equalchance of being counted once and only once. However, theapproach requires sampling from isotropic cellular popu-lations, which makes it difficult, or at least labor intensive,to apply across many different cortical regions or the wholebrain. Therefore, it is conceivable that the stereologicalapproach may have missed contributions from structureswith high concentrations of glia, such as subcortical nucleior the white matter. In the spinal cord of the rat, forexample, the GNR is about 1.6 (Bjugn and Gundersen1993). The problem of overlooking the true contribution ofglia to the neuraxis was circumvented by a straightforwardapproach for large-scale tissue analysis that was recentlyused by Herculano-Houzel and Lent (2005). Instead ofcounting cells in fixed tissue, they homogenized the brainand then counted cellular nuclei in the isotropic suspension.This approach gives a simple and reliable estimate of totalcell number, assuming that each cell has exactly onenucleus. Neuronal nuclei were identified by NeuN stainingwhich labels neurons but not glia. The remaining unlabeledcells, which included glia but also other non-neuronal cells,provided an upper estimate on the number of glia in thebrain.With the help of this elegant approach Herculano-Houzel and Lent determined total cell numbers in differentlarge-scale brain regions as well as the whole brain. Theyestimated that of all cells in the adult rat brain, 60% (orabout 200 million) are neurons. The ratio of all non-neu-ronal cells to neurons across different primate species was

Data on connections between the areas of the cerebral cortex and nuclei of the thalamus are too complicated to analyse with naked intuition. Indeed, the complexity of connection data is one of the major challenges facing neuroanatomy. Recently, systematic methods have been developed and applied to the analysis of the connectivity in the cerebral cortex. These approaches have shed light on the gross organization of the cortical network, have made it possible to test systematically theories of cortical organization, and have guided new electrophysiological studies. This paper extends the approach to investigate the organization of the entire cortico-thalamic network. An extensive collation of connection tracing studies revealed approximately 1500 extrinsic connections between the cortical areas and thalamic nuclei of the cat cerebral hemisphere. Around 850 connections linked 53 cortical areas with each other, and around 650 connections linked the cortical areas with 42 thalamic nuclei. Non-metric multidimensional scaling, optimal set analysis and non-parametric cluster analysis were used to study global connectivity and the 'place' of individual structures within the overall scheme. Thalamic nuclei and cortical areas were in intimate connectional association. Connectivity defined four major thalamo-cortical systems. These included three broadly hierarchical sensory or sensory/motor systems (visual and auditory systems and a single system containing both somatosensory and motor structures). The highest stations of these sensory/motor systems were associated with a fourth processing system composed of prefrontal, cingulate, insular and parahippocampal cortex and associated thalamic nuclei (the 'fronto-limbic system'). The association between fronto-limbic and somato-motor systems was particularly close.

Publisher Summary The results show that the frequently perplexing and counter-intuitive patterns of intact, lesioned, and paradoxically restored orienting behavior can be explained quite comprehensively by a simple mathematical model based on the aspects of real connectivity. The connectivity structure employed in the model, and the dynamic behavior the model exhibits, make it clear that competition among brain structures is an important mechanism for spatial attention in the cat and potentially also in humans. The model also demonstrates that paradoxical lesion effects, which present a surprising set of phenomena, need by no means be mysterious. Paradoxical restoration of spatial orienting can be easily understood from the mechanism of competition across the midline among bilateral brain structures. Normal function arises from balanced competition, and restoration of attentional function after primary lesions is achieved by redressing the level of bilateral competition, such that the system can be efficiently influenced by external visual input. However, in the cat, the experimental results from the behavioral effects of brain lesions, the connectional neuroanatomy, and the behavior of the model, suggest that the principal mechanism for competition is a subcortical one, particularly involving the superior colliculi and the basal ganglia. These sub-cortical mechanisms are informed and influenced by cortical processes and representations (as in the spatially dependent aspects of the model), but the principal mechanism appears nonetheless to be direct mutual inhibition across the midline, involving sub-cortical structures.

Information about the numerous connections among the many cortical areas in mammalian brains has been published extensively. The organization of the cortical systems that these connections define, however, is still poorly understood. We analyzed this complex connectivity structure with the help of mathematical and computational tools in order to better understand cortical processing. Here we present the results of a number of different analyses that we used to decide whether cortical areas in the brains of the cat and the Macaque monkey can be grouped into separate clusters, based on the organization and strength of connections between the areas. We employed non-parametric cluster analysis together with multi-dimensional scaling, as well as a new computational tool based on the global stochastic optimization of interconnected structures. Our results revealed a well-defined clustered organization, which was particularly clear in the primate visual system. The identified clusters largely agreed with suspected functional sub-divisions of cortical regions. Our results provide a basis for modeling studies, for the interpretation of functional studies of the brain; as well as for predicting future anatomical experiments.

Neuroanatomical data describing the numerous connections between brain structures contain valuable information about the organization of nervous systems. This information, however, cannot be assessed readily since the data are numerous, confusingly cross-referential, incomplete, contradictory, and of varying reliability. The classification of such data, moreover, allows vast numbers of different, equally possible interpretations that have to be evaluated. We have developed a computational approach that effectively deals with these difficulties by using stochastic optimization. We represented cortical connectivity data as ‘black-box’ objects that are linked with each other through a network of anatomical relations. This network can be arranged optimally according to suspected structuring principles. The approach makes it possible to analyze large amounts of complex anatomical data in a number of ways. We have successfully applied this technique to the analysis of processing clusters and hierarchies in cat and monkey cortical systems.

Repetitive transcranial magnetic stimulation (rTMS) in ‘offline’ experiments is commonly administered to participants that are in a relaxed ’resting state’. Clearly, this approach leads to an ill controlled baseline state of the participants’ brain, in face of evidence that the mental baseline influences how the brain is affected by TMS (e.g., Silvanto and Pascual-Leone (2008) Brain Topography 21). The aim of the present study was to assess the effect of uncontrolled vs. controlled behavior during rTMS administration on participants’ performance in a subsequent visual localization task. We compared the offline effects of 10 Hz rTMS for standard TMS administration (uncontrolled ‘resting’ behavior without task) to 10 Hz rTMS administered while the participants were performing a visual localization task (controlled behavior with task). Tasks during the online and offline period were identical, testing the participants’ ability to allocate attention to the detection of peripheral unilateral (left or right) or bilateral (left and right) peri-threshold visual stimuli. rTMS or sham stimulation (by vertically tilted coil) were applied to the 10–20 coordinate P4, located in the right posterior parietal cortex. Performance after rTMS in the ‘resting’ condition appeared similar to the performance in the ‘with task’ condition. Importantly, however, when compared to sham stimulation conditions, rTMS induced a deterioration of offline performance relative to sham stimulation in the ‘resting’ condition, whereas it led to better performance relative to sham in the ‘with task’ condition ( Fig. 1 ). We conclude that in the present paradigm, the manipulation ‘with task’ versus ‘resting’ during the administration of rTMS might be too weak to induce brain states that are distinct enough to induce different levels of performance in the subsequent task. From this perspective, controlling the participants’ behavior during rTMS administration does not appear to matter for their offline behavior after rTMS. However, the results of the study also demonstrate that whether rTMS leads to a deterioration or improvement of performance critically depends on the baseline to which the offline performance is compared. Offline performance after rTMS or sham stimulation applied to participants during a behavioral task or at rest. Performance was evaluated as inverse efficiency, computed as reaction time/ proportion of correct trials. Shown are the results for bilateral visual stimuli. Within-subject error bars were created using the method of Cousineau (2005).

The classic view of how the brain areas that control vision are connected is a complicated wiring diagram devised by manual sorting on the basis of existing anatomical data [D. J. Felleman and D. C. Van Essen, Cereb. Cortex 1 , 1 (1991)]. Now, in this issue9s Enhanced Perspective, Hilgetag and co-workers have used a computer algorithm to test whether there is a better way to organize the connections. They find that the brain is surprisingly indeterminate, and that no single hierarchy can satisfactorily represent the order implied by the anatomical data. A more detailed explanation of their analysis and a list of predictions derived from their hierarchies that will be particularly informative to test experimentally can be found on the home page of the authors.

In the modelling of biochemical reaction systems, analysis of steady states plays an important role, because virtually stationary regimes are frequently encountered in experimental settings and under in-vivo conditions. Since in steady states, all intermediates have to be balanced with respect to inputs and outputs, the vector, V, of stationary reaction rates (called fluxes below) has to be situated in the null-space (kernel)of the stoichiometry matrix, N (cf. Clarke, 1980, 1988; Thomas and Fell, 1993).

It has been suggested that neural systems across several scales of organization show optimal component placement, in which any spatial rearrangement of the components would lead to an increase of total wiring. Using extensive connectivity datasets for diverse neural networks combined with spatial coordinates for network nodes, we applied an optimization algorithm to the network layouts, in order to search for wire-saving component rearrangements. We found that optimized component rearrangements could substantially reduce total wiring length in all tested neural networks. Specifically, total wiring among 95 primate (Macaque) cortical areas could be decreased by 32%, and wiring of neuronal networks in the nematode Caenorhabditis elegans could be reduced by 48% on the global level, and by 49% for neurons within frontal ganglia. Wiring length reductions were possible due to the existence of long-distance projections in neural networks. We explored the role of these projections by comparing the original networks with minimally rewired networks of the same size, which possessed only the shortest possible connections. In the minimally rewired networks, the number of processing steps along the shortest paths between components was significantly increased compared to the original networks. Additional benchmark comparisons also indicated that neural networks are more similar to network layouts that minimize the length of processing paths, rather than wiring length. These findings suggest that neural systems are not exclusively optimized for minimal global wiring, but for a variety of factors including the minimization of processing steps., Comment: 11 pages, 5 figures

The anatomical wiring of the brain is a central focus in network neuroscience. Diffusion MRI tractography offers the unique opportunity to investigate the brain fiber architecture in vivo and noninvasively. However, its reliability is still highly debated. Here, we explored the ability of diffusion MRI tractography to match invasive anatomical tract-tracing connectivity data of the ferret brain. We also investigated the influence of several state-of-the-art tractography algorithms on this match to ground truth connectivity data. Tract-tracing connectivity data were obtained from retrograde tracer injections into the occipital, parietal, and temporal cortices of adult ferrets. We found that the relative densities of projections identified from the anatomical experiments were highly correlated with the estimates from all the studied diffusion tractography algorithms (Spearman’s rho ranging from 0.67 to 0.91), while only small, nonsignificant variations appeared across the tractography algorithms. These results are comparable to findings reported in mouse and monkey, increasing the confidence in diffusion MRI tractography results. Moreover, our results provide insights into the variations of sensitivity and specificity of the tractography algorithms, and hence into the influence of choosing one algorithm over another., [Author Summary]: In this article we used tract-tracing data as a gold standard to validate the use of diffusion MRI tractography for inferring structural connectivity in the ferret brain as well as for assessing the influence of several state-of-the-art tractography algorithms on the inferred connections. We found high correspondence between diffusion MRI tractography and tract-tracing with little differences between the explored algorithms. We conclude that diffusion MRI tractography provides a worthwhile whole-brain estimate of structural connectivity that can be employed in further anatomical, developmental, and computational studies of the ferret brain., Claus C. Hilgetag, Deutsche Forschungsgemeinschaft (http://dx.doi.org/10.13039/501100001659), Award ID: SFB 936/A1/Z3 and SPP 2041 / HI 1286/6-1. Claus C. Hilgetag, Human Brain Project, Award ID: HBP-SGA2 (785907)/ SGA2. Roberto Toro, Agence Nationale de la Recherche (http://dx.doi.org/10.13039/501100001665), Award ID: ANR-15-HBPR-0005

Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a ‘map of stroke’., Highlights • We apply a novel lesion inference technique (MSA) to a large brain lesion dataset. • Data comprises lesion patterns of 148 stroke patients and clinical scores (NIHSS). • MSA reveals essential functional contributions, mainly by subcortical regions. • The analysis provides a first approximation of a causal functional ‘map of stroke’.

Information processing in the brain is strongly constrained by anatomical connectivity. However, the principles governing the organization of corticocortical connections remain elusive. Here, we tested three models of relationships between the organization of cortical structure and features of connections linking 49 areas of the cat cerebral cortex. Factors taken into account were relative cytoarchitectonic differentiation (‘structural model’), relative spatial position (‘distance model’), or relative hierarchical position (‘hierarchical model’) of the areas. Cytoarchitectonic differentiation and spatial distance (themselves uncorrelated) correlated strongly with the existence of inter-areal connections, whereas no correlation was found with relative hierarchical position. Moreover, a strong correlation was observed between patterns of laminar projection origin or termination and cytoarchitectonic differentiation. Additionally, cytoarchitectonic differentiation correlated with the absolute number of corticocortical connections formed by areas, and varied characteristically between different cortical subnetworks, including a ‘rich-club’ module of hub areas. Thus, connections between areas of the cat cerebral cortex can, to a large part, be explained by the two independent factors of relative cytoarchitectonic differentiation and spatial distance of brain regions. As both the structural and distance model were originally formulated in the macaque monkey, their applicability in another mammalian species suggests a general principle of global cortical organization. Electronic supplementary material The online version of this article (doi:10.1007/s00429-014-0849-y) contains supplementary material, which is available to authorized users.

Recent analyses of association fibre networks in the primate cerebral cortex have revealed a small number of densely intra–connected and hierarchically organized structural systems. Corresponding analyses of data on functional connectivity are required to establish the significance of these structural systems. W e therefore built up a relational database by systematically collating published data on the spread of activity after strychnine–induced disinhibition in the macaque cerebral cortex in vivo . After mapping these data to two different parcellation schemes, we used three independent methods of analysis which demonstrate that the cortical network of functional interactions is not homogeneous, but shows a clear segregation into functional assemblies of mutually interacting areas. The assemblies suggest a principal division of the cortex into visual, somatomotor and orbito–temporo–insular systems, while motor and somatosensory areas are inseparably interrelated. These results are largely compatible with corresponding analyses of structural data of mammalian cerebral cortex, and deliver the first functional evidence for ‘small–world’ architecture of primate cerebral cortex.

The pattern of anatomical connections between areas of the primate visual system is organized hierarchically. However, onset latencies in parietal and occipital stations are often simultaneous, and this seems to contradict hierarchical organization in its simplest interpretation, as serial organization. To understand the reasons for this contradiction, we simulated the cortical network for which there is onset data, including the network's hierarchical structure. The network's dynamics reproduced the simultaneous onset latencies reported in several dorsal areas. These results show that a strictly hierarchical visual system is compatible with much more complex dynamics than serial processing, and that hodological and biophysical properties, are more closely related to onset dynamics than is hierarchical organisation.

The present study describes the ipsilateral and contralateral cortico-cortical and cortico-thalamic connectivity of the temporal visual areas 20a and 20b in the ferret using standard anatomical tract-tracing methods. The two temporal visual areas are strongly interconnected, but area 20a is primarily connected to the occipital visual areas, whereas area 20b maintains more widespread connections with the occipital, parietal and suprasylvian visual areas and the secondary auditory cortex. The callosal connectivity, although homotopic, consists mainly of very weak anterograde labelling which was more widespread in area 20a than area 20b. Although areas 20a and 20b are well connected with the visual dorsal thalamus, the injection into area 20a resulted in more anterograde label, whereas more retrograde label was observed in the visual thalamus following the injection into area 20b. Most interestingly, comparisons to previous connectional studies of cat areas 20a and 20b reveal a common pattern of connectivity of the temporal visual cortex in carnivores, where the posterior parietal cortex and the central temporal region (PMLS) provide network points required for dorsal and ventral stream interaction enroute to integration in the prefrontal cortex. This pattern of network connectivity is not dissimilar to that observed in primates, which highlights the ferret as a useful animal model to understand visual sensory integration between the dorsal and ventral streams. This data will contribute to the Ferretome (www.ferretome.org) to facilitate cross species analysis of brain connectomes and wiring principles of the brain.

International audience; The study of brain-function relationships is undergoing a conceptual and methodological transformation due to the emergence of network neuroscience and the development of multivariate methods for lesion-deficit inferences. Anticipating this process, in 1998 Godefroy and co-workers conceptualized the potential of four elementary typologies of brain-behaviour relationships named 'brain modes' (unicity, equivalence, association, summation) as building blocks able to describe the association between intact or lesioned brain regions and cognitive processes or neurological deficits. In the light of new multivariate lesion inference and network approaches, we critically revisit and update the original theoretical notion of brain modes, and provide real-life clinical examples that support their existence. To improve the characterization of elementary units of brain-behavioural relationships further, we extend such conceptualization with a fifth brain mode (mutual inhibition/masking summation). We critically assess the ability of these five brain modes to account for any type of brain-function relationship, and discuss past versus future contributions in redefining the anatomical basis of human cognition. We also address the potential of brain modes for predicting the behavioural consequences of lesions and their future role in the design of cognitive neurorehabilitation therapies.; L'étude des relations cerveau-fonction subit une transformation conceptuelle et méthodologique due à l'émergence des neurosciences de réseau et au développement de méthodes multivariées pour les inférences déficit-lésion. Anticipant ce processus, en 1998, Godefroy et ses collègues ont conceptualisé le potentiel de quatre typologies élémentaires de relations cerveau-comportement appelées «modes cérébraux» (unicité, équivalence, association, sommation) comme éléments constitutifs capables de décrire l'association entre cerveau intact ou lésé. régions et processus cognitifs ou déficits neurologiques. À la lumière de nouvelles inférences de lésions multivariées et de nouvelles approches en réseau, nous revisitons et mettons à jour de manière critique la notion théorique originale des modes cérébraux et fournissons des exemples cliniques réels qui soutiennent leur existence. Pour améliorer encore la caractérisation des unités élémentaires des relations cerveau-comportement, nous étendons cette conceptualisation avec un cinquième mode cérébral (inhibition mutuelle / sommation de masquage). Nous évaluons de manière critique la capacité de ces cinq modes cérébraux à prendre en compte tout type de relation cerveau-fonction, et discutons des contributions passées et futures dans la redéfinition de la base anatomique de la cognition humaine. Nous abordons également le potentiel des modes cérébraux pour prédire les conséquences comportementales des lésions et leur rôle futur dans la conception de thérapies de neuroréhabilitation cognitives.

Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barab\'asi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks.

Background Various strategies have been used for inferring brain functions from stroke lesions. We explored a new mathematical approach based on game theory, the so-called multi-perturbation Shapley value analysis (MSA), to assess causal function localizations and interactions from multiple perturbation data. We applied MSA to a dataset composed of lesion patterns of 148 acute stroke patients and their National Institutes of Health Stroke Scale (NIHSS) scores, to systematically investigate the influence of different parameter settings on the outcomes of the approach. Specifically, we investigated aspects of MSA methodology including the choice of the predictor algorithm (typology and kernel functions), training dataset (original versus binary), as well as the influence of lesion thresholds. We assessed the suitability of MSA for processing real clinical lesion data and established the central parameters for this analysis. Results We derived general recommendations for the analysis of clinical datasets by MSA and showed that, for the studied dataset, the best approach was to use a linear-kernel support vector machine predictor, trained with a binary training dataset, where the binarization was implemented through a median threshold of lesion size for each region. We demonstrated that the results obtained with different MSA variants lead to almost identical results as the basic MSA. Conclusions MSA is a feasible approach for the multivariate lesion analysis of clinical stroke data. Informed choices need to be made to set parameters that may affect the analysis outcome.

Visual spatial attention is an essential brain function that is produced through the interactions of several cortical and subcortical regions. Using the reversible deactivation technique of transcranial magnetic stimulation (TMS) in combination with a visual stimulus detection task, we demonstrated that parietal as well as occipito-parietal cortices in the human brain contribute to spatial attentional behavior. The functional role of left- and right-hemispheric regions appeared to be mirror-symmetric, although the strength of contributions from left and right cortices might differ. Reaction times for baseline and experimental conditions suggested that TMS interfered with an early stage of attentional processing. The experiments also demonstrated an ipsilateral enhancement of spatial attention after unilateral TMS. This observation supports a theoretical model for inter-hemispheric competition in the attentional network.

The cytoarchitectonic organization of the brain and its connectivity are important substrates for brain function and behavior. A disruption in the structural organization (cytoarchitecture or connectivity) can cause neurological impairments (e.g. stroke). Moreover, early brain development is a period during which the brain is very plastic and a disruption in its structural development can cause neurodevelopmental disorders such as autism spectrum disorders or schizophrenia. The development of brain structure occurs at different scales. In this work we examined the whole brain, regional and laminar/cellular levels. The interactions within these levels can also be reported using different modalities. We focused on tract-tracing at the microscopic scale and diffusion MRI at the macroscale scale. We used these methods to study the structural connectivity between different brain areas at the different scales. We adopted a multi-scale and multimodal approach to characterize the ferret brain development, structural connectivity and cytoarchitecture. We used diffusion MRI to describe structural brain connectivity and histological Nissl slices, to describe the cellular organization. The ferret was specifically chosen as the animal model because during their first days postnatally, they provide an opportunity to witness processes which occur during the last trimester of gestation in humans. To summarize, (1) we validated the use of non-invasive diffusion MRI in the adult ferret by comparing its results to the precise quantifications obtained by tract-tracing. (2) We developed a semi-automated pipeline for extracting whole brain quantifications from microimages of Nissl stained slices, informing us about the development of the cytoarchitectonic organization.These quantifications allowed us to identify a laterodorsal gradient of maturation of the cortical lamination. This gradient is present up until 4 weeks postnatally, after which all the layers are formed. (3) The histological slices were registered to the MRI dataset in order to investigate the relationship between the maturation of cortical lamination and the development of cortico-cortical connectivity. We observed that the similarity of cytoarchitectonic organization of two brain areas of ferrets as young as 4 postnatal days (P4), indicated a higher likelihood of interconnection at P32 and at the adult stage. This relationship was, however, not maintained when predicting the connectivity likelihood at earlier stages (from P4 to P16). This indicates that the footprint of the mature cytoarchitectonic organization is already present early in development (P4) and prior to the one of mature connectivity which appears around P32.; L’organisation cytoarchitectonique du cerveau et sa connectivité sont des éléments essentiels pour le fonctionnement du cerveau et le comportement. Une perturbation de l’organisation structurelle du cerveau (cytoarchitectonie ou connectivité) peut entraîner des troubles neurologiques (comme, par exemple, un accident vasculaire cérébrale). Le développement précoce du cerveau est une période durant laquelle le cerveau est très plastique et une perturbation de son développement structurel peut provoquer des troubles neurodéveloppementaux tels que des troubles du spectre autistique ou de la schizophrénie. Le développement de la structure cérébrale se produit à différentes échelles. Dans ces travaux, nous avons analysé le cerveau à l’échelle du cerveau entier, à l’échelle régionale et laminaire/cellulaire. Les interactions entre ces différents niveaux peuvent également être capturés en utilisant différentes modalités d’acquisition. Nous avons utilisé des traceurs à l’échelle microscopique et l’IRM de diffusion à l’échelle macroscopique. Ces méthodes nous ont permis d’étudier la connectivité structurelle entre différentes régions cérébrales à différentes échelles.Grâce à notre approche multi-échelle et multimodale nous avons caractérisé le développement cérébral du ferret, sa connectivité structurelle et son organisation cellulaire. Nous avons utilisé l’IRM de diffusion pour décrire la connectivité structurelle et des coupes histologiques marquées au Nissl pour décrire l’organisation cellulaire. Le furet a été spécifiquement choisi comme animal modèle car pendant les premiers jours après la naissance, il permet d’étudier des phénomènes qui se produisent au cours du dernier mois de gestation chez l’Homme. En résumé, (1) nous avons validé l’utilisation de l’IRM de diffusion non-invasive chez le furet adulte en comparant ses résultats aux quantifications précises obtenues par les traceurs. (2) Nous avons développé une pipeline semi-automatisée pour extraire les quantifications de micro-images de coupes histologiques marquées au Nissl pour le cerveau entier, nous informant sur le développement de l’organisation cytoarchitectonique. Ces quantifications nous ont permis d’identifier un gradient latéro-dorsal de maturation de la stratification corticale.Ce gradient est présent jusqu’à 4 semaines après la naissance, après quoi toutes les couches sont formées. (3) Les coupes histologiques ont été recalées aux données d’IRM afin d’étudier la relation entre la maturation de la stratification corticale et le développement de la connectivité cortico-corticale. Nous avons observé que la similitude de l’organisation cytoarchitectonique de deux régions cérébrales de furets à partir de 4 jours postnatals (P4), indiquait une probabilité plus élevée d’interconnexion à P32 et à l’âge adulte. Cette relation n’était cependant pas maintenue lors de la prédiction de la probabilité de connectivité aux stades antérieurs (de P4 à P16). Cela indique que l’empreinte de l’organisation cytoarchitectonique mature est déjà présente au début du développement (P4) et précède celle de la connectivité mature qui apparaît autour de P32.