[Show abstract][Hide abstract] ABSTRACT: How does the brain integrate multiple sources of information to support normal sensorimotor and cognitive functions? To investigate this question we present an overall brain architecture (called "the dual intertwined rings architecture") that relates the functional specialization of cortical networks to their spatial distribution over the cerebral cortex (or "corticotopy"). Recent results suggest that the resting state networks (RSNs) are organized into two large families: 1) a sensorimotor family that includes visual, somatic, and auditory areas and 2) a large association family that comprises parietal, temporal, and frontal regions and also includes the default mode network. We used two large databases of resting state fMRI data, from which we extracted 32 robust RSNs. We estimated: (1) the RSN functional roles by using a projection of the results on task based networks (TBNs) as referenced in large databases of fMRI activation studies; and (2) relationship of the RSNs with the Brodmann Areas. In both classifications, the 32 RSNs are organized into a remarkable architecture of two intertwined rings per hemisphere and so four rings linked by homotopic connections. The first ring forms a continuous ensemble and includes visual, somatic, and auditory cortices, with interspersed bimodal cortices (auditory-visual, visual-somatic and auditory-somatic, abbreviated as VSA ring). The second ring integrates distant parietal, temporal and frontal regions (PTF ring) through a network of association fiber tracts which closes the ring anatomically and ensures a functional continuity within the ring. The PTF ring relates association cortices specialized in attention, language and working memory, to the networks involved in motivation and biological regulation and rhythms. This "dual intertwined architecture" suggests a dual integrative process: the VSA ring performs fast real-time multimodal integration of sensorimotor information whereas the PTF ring performs multi-temporal integration (i.e., relates past, present, and future representations at different temporal scales).
PLoS ONE 01/2013; 8(7):e67444. · 3.73 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This letter presents a novel unsupervised sensory matching learning technique for the development of an internal representation of three-dimensional information. The representation is invariant with respect to the sensory modalities involved. Acquisition of the internal representation is demonstrated with a neural network model of a sensorimotor system of a simple model creature, consisting of a tactile-sensitive body and a multiple-degrees-of-freedom arm with proprioceptive sensitivity. Acquisition of the 3D representation as well as a distributed representation of the body scheme, occurs through sensorimotor interactions (i.e., the sensory-motor experience of the creature). Convergence of the learning is demonstrated through computer simulations for the model creature with a 7-DoF arm and a spherical body covered by 20 tactile fields.
[Show abstract][Hide abstract] ABSTRACT: This second issue of the French Complex Systems Roadmap is the outcome of the Entretiens de Cargese 2008, an interdisciplinary brainstorming session organized over one week in 2008, jointly by RNSC, ISC-PIF and IXXI. It capitalizes on the first roadmap and gathers contributions of more than 70 scientists from major French institutions. The aim of this roadmap is to foster the coordination of the complex systems community on focused topics and questions, as well as to present contributions and challenges in the complex systems sciences and complexity science to the public, political and industrial spheres.
[Show abstract][Hide abstract] ABSTRACT: About 50% of women declare themselves to have sensitive skin. However, sensitive skin still appears to be a questionable problem not corresponding to a specific physiological pattern. To objectivate the neural basis of sensitive skin, we measured cerebral response to cutaneous provocative tests in self-perceived sensitive and non-sensitive skin subjects using functional magnetic resonance imaging (fMRI).
Subjects were divided into two groups according to their self-perceived characterization by using a dedicated questionnaire about their skin reactivity. Event-related fMRI was used to measure cerebral activation associated with skin discomfort induced by a simultaneous split-face application of lactic acid and of its vehicle.
In both groups, skin discomfort due to lactic acid increased activity in the primary sensorimotor cortex contralateral to application site and in a bilateral fronto-parietal network including parietal cortex, prefrontal areas around the superior frontal sulcus, and the supplementary motor area. However, activity was significantly larger in the sensitive skin group. Most remarkably, in the sensitive skin group only, activity spreaded into the ipsilateral primary sensorimotor cortex and the bilateral peri-insular secondary somatosensory area. Our results demonstrate that, compared with control subjects, self-perceived sensitive skin subjects have a specific cerebral activation during skin irritative test, which allows us to hypothesize that self-perceived sensitive skin is intrinsically linked to a specific neurophysiologic pattern for these subjects.
This study demonstrates that fMRI is an effective objective method for measuring cerebral processes underlying skin reactivity and contributes to a better understanding of the neural basis of the sensitive skin phenomenon.
Skin Research and Technology 12/2008; 14(4):454-61. · 1.41 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We ask the question whether the coding of categorical versus coordinate spatial relations depends on different neural networks showing hemispheric specialization or whether there is continuity between these two coding types. The 'continuous spatial coding' hypothesis would mean that the two coding types rely essentially on the same neural network consisting of more general-purpose processes, such as visuo-spatial attention, but with a different weighting of these general processes depending on exact task requirements. With event-related fMRI, we have studied right-handed male subjects performing a grid/no-grid visuo-spatial working memory task inducing categorical and coordinate spatial relations coding. Our data support the 'continuous spatial coding' hypothesis, indicating that, while based on the same fronto-parieto-occipital neural network than categorical spatial relations coding, the coding of coordinate spatial relations relies more heavily on attentional and executive processes, which could induce hemispheric differences similar to those described in the literature. The results also show that visuo-spatial working memory consists of a short-term posterior store with a capacity of up to three elements in the parietal and extrastriate cortices. This store depends on the presence of a visible space categorization and thus can be used for the coding of categorical spatial relations. When no visible space categorization is given or when more than three elements have to be coded, additional attentional and executive processes are recruited, mainly located in the dorso-lateral prefrontal cortex.
[Show abstract][Hide abstract] ABSTRACT: In recent years, advances and improvements in engineering and robotics have in part been due to strengthened interactions with the biological sciences. Robots that mimic the complexity and adaptability of biological systems have become a central goal in research and development in robotics. Usually, such a collaboration is addressed to a 2-fold perspective of (i) setting up anthropomorphic platforms as test beds for studies in neuroscience and (ii) promoting new mechatronic and robotic technologies for the development of bio-inspired or humanoid high-performance robotic platforms. This paper provides a brief overview of recent studies on sensorimotor coordination in human motor control and proposes a novel paradigm of adaptive learning for sensorimotor control, based on a multi-network high-level control architecture. The proposed neurobiologically inspired model has been applied to a robotic platform, purposely designed to provide anthropomorphic solutions to neuroscientific requirements. The goal of this work is to use the bio-inspired robotic platform as a test bed for validating the proposed model of high-level sensorimotor control, with the aim of demonstrating adaptive and modular control based on acquired competences, with a higher degree of flexibility and generality than conventional robotic controllers, while preserving their robustness. To this purpose, a set of object-dependent, visually guided reach-and-grasp tasks and the associated training phases were first implemented in a multi-network control architecture in simulation. Subsequently, the offline learning realized in simulation was used to produce the input command of reach-and-grasp to the low-level position control of the robotic platform. Experimental trials demonstrated that the adaptive and modular high-level control allowed reaching and grasping of objects located at different positions and objects of variable size, shape and orientation. A future goal would be to address autonomous and progressive learning based on growing competences.
[Show abstract][Hide abstract] ABSTRACT: The convolutions of the mammalian cortex are one of its most intriguing characteristics. Their pattern is very distinctive for different species, and there seems to be a remarkable relationship between convolutions and the architectonic and functional regionalization of the cerebral cortex. Yet the mechanisms behind the development of convolutions and their association with the cortical regionalization are poorly understood. Here we propose a morphogenetic model for the development of cortical convolutions based on the structure of the cortex as a closed surface with glial and axonal fibres pulling radially, the fundamental mechanical properties of cortex and fibres (elasticity and plasticity), and the growth of the cortical surface. The computer simulations of this model suggest that convolutions are a natural consequence of cortical growth. The model reproduces several aspects of convolutional development, such as the relationship between cortical surface and brain volume among mammals, the period of compensation in the degree of convolution observed in gyrencephalic brains and the dependence of the degree of convolution on cortical thickness. We have also studied the effect of early cortical regionalization on the development of convolutions by introducing geometric, mechanic and growth asymmetries in the model. The morphogenetic model is thus able to reproduce the gradients in the degree of convolution, the development of primary, secondary and tertiary convolution, and the overproduction of sulci observed in animals with altered afferent cortical connections.
[Show abstract][Hide abstract] ABSTRACT: For gradient descent learning to yield connectivity consistent with real biological networks, the simulated neurons would have to include more realistic intrinsic properties such as frequency adaptation. However, gradient descent learning cannot be used straightforwardly with adapting rate-model neurons because the derivative of the activation function depends on the activation history. The objectives of this study were to (1) develop a simple computational approach to reproduce mathematical gradient descent and (2) use this computational approach to provide supervised learning in a network formed of rate-model neurons that exhibit frequency adaptation. The results of mathematical gradient descent were used as a reference in evaluating the performance of the computational approach. For this comparison, standard (nonadapting) rate-model neurons were used for both approaches. The only difference was the gradient calculation: the mathematical approach used the derivative at a point in weight space, while the computational approach used the slope for a step change in weight space. Theoretically, the results of the computational approach should match those of the mathematical approach, as the step size is reduced but floating-point accuracy formed a lower limit to usable step sizes. A systematic search for an optimal step size yielded a computational approach that faithfully reproduced the results of mathematical gradient descent. The computational approach was then used for supervised learning of both connection weights and intrinsic properties of rate-model neurons to convert a tonic input into a phasic-tonic output pattern. Learning produced biologically realistic connectivity that essentially used a monosynaptic connection from the tonic input neuron to an output neuron with strong frequency adaptation as compared to a complex network when using nonadapting neurons. Thus, more biologically realistic connectivity was achieved by implementing rate-model neurons with more realistic intrinsic properties. Our computational approach could be applied to learning of other neuron properties.
[Show abstract][Hide abstract] ABSTRACT: In this letter we describe a hippocampo-cortical model of spatial processing and navigation based on a cascade of increasingly complex associative processes that are also relevant for other hippocampal functions such as episodic memory. Associative learning of different types and the related pattern encoding-recognition take place at three successive levels: (1) an object location level, which computes the landmarks from merged multimodal sensory inputs in the parahippocampal cortices; (2) a subject location level, which computes place fields by combination of local views and movement-related information in the entorhinal cortex; and (3) a spatiotemporal level, which computes place transitions from contiguous place fields in the CA3-CA1 region, which form building blocks for learning temporospatial sequences. At the cell population level, superficial entorhinal place cells encode spatial, context-independent maps as landscapes of activity; populations of transition cells in the CA3-CA1 region encode context-dependent maps as sequences of transitions, which form graphs in prefrontal-parietal cortices. The model was tested on a robot moving in a real environment; these tests produced results that could help to interpret biological data. Two different goal-oriented navigation strategies were displayed depending on the type of map used by the system. Thanks to its multilevel, multimodal integration and behavioral implementation, the model suggests functional interpretations for largely unaccounted structural differences between hippocampo-cortical systems. Further, spatiotemporal information, a common denominator shared by several brain structures, could serve as a cognitive processing frame and a functional link, for example, during spatial navigation and episodic memory, as suggested by the applications of the model to other domains, temporal sequence learning and imitation in particular.
[Show abstract][Hide abstract] ABSTRACT: In recent years, advances and improvements in engineering and robotics have been strengthening interactions between biological science and robotics in the goal of mimicking the complexity of biological systems. In this paper, motor control paradigms inspired by human mechanisms of sensory-motor coordination are applied to a biologically-inspired, purpose-designed robotic platform. The goal was to define and implement a multi-network architecture and to demonstrate that progressive learning of object grasping and manipulation can greatly increase performance of a robotic system in terms of adaptability, flexibility, growing competences and generalization, while preserving the robustness of traditional control. The paper presents the neural approach to sensory-motor coordination and shows preliminary results of the integration with the robotic system by means of simulation tests and experimental trials.
Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on; 05/2005
[Show abstract][Hide abstract] ABSTRACT: PURPOSE AND MATERIALS: To evaluate the cortical response to visual stimulation in patients with age-related macular degeneration (ARMD), we conducted a functional MRI study in ten patients presenting unilateral or bilateral ARMD and five age-matched controls, using white flashes during activation phases (see Part I).
After anatomical conformation, eight patients and four controls showed significant cortical hemodynamic response to monocular stimulations. Individual analysis was preferred to group evaluation, because of the differences in visual loss in a small number of patients. In controls, we observed cortical response in the primary visual cortex, especially at occipital poles corresponding to the macula. Patients showed a qualitative and quantitative restriction in cortical response and exclusion of occipital poles after stimulation of the affected eye, whereas activation was found in the peripheral striate and peristriate cortex. Cortical response showed hemispheric asymmetry in some patients.
Our study demonstrated an activation defect in the macular projected striate cortex, corresponding to visual impairment in ARMD patients. Nevertheless, at a given visual acuity, cortical response may vary among subjects. Patients' subjective apprehension may account for such variations, as well as objective visual capacity stemming from residual functional retinal areas within the affected macula. The hemispheric asymmetry in cortical activation may result from gaze deviation onto the new fixation area in the perimacular retina, thus altering the global visual field. Enhancement in the peripheral striate and peristriate areas suggests changes in cortical interactions, possibly by a lowering of the feedback from macular projected V1. Finally, cortical evaluations must take into account degenerative phenomena delaying the hemodynamic response in the elderly.
Aiming at a specific population of weakened patients with a serious visual impairment, we obtained significant results concerning cortical plasticity for visual perception in central vision deletion. Our preliminary findings must be confirmed in a larger population and correlated with other techniques exploring vision, in particular with multifocal electroretinography for retinal evaluation.
Journal Français d Ophtalmologie 12/2004; 27(9 Pt 2):3S72-86. · 0.44 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: To evaluate the cortical response to visual stimulation in patients with age-related macular degeneration (ARMD).
We conducted a prospective functional MRI study at 1.5 Testa in ten patients presenting with unilateral or bilateral ARMD and five age-matched controls. The visual stimulus was a sequence of resting phase (presentation of a fixation point on a black background) followed by an activation phase (flashes at 2 Hz). Functional data were recorded with anatomy; significant hemodynamic response secondary to neuronal activation was statistically determined using the SPM 99 software.
The first objective was to estimate the feasibility of a functional study in the elderly. Controls and patients complained about the duration of the examination, although each of the two active functional sessions lasted only 4.5 min. The central point fixation was impaired for the patients; some deviated their gaze to center the fixation point on a perimacular retinal area. Because of substantial movement during MRI acquisitions, the data from two patients and one control were withdrawn from statistic processing.
This study is one of the few evaluations reported on functional MRI in the elderly, because of technical constraints, patient fragility and their ophthalmologic pathology. Optimizing the visual stimulus and the paradigm of stimulation, repeating patient information and support have helped demonstrate significant cortical hemodynamic response in most subjects, even in the most affected patients. Evaluation of the visual cortex by functional MRI appears feasible in the ophthalmologic pathology of the elderly, providing an adapted management of the subject's conditions.
Journal Français d Ophtalmologie 12/2004; 27(9 Pt 2):3S65-71. · 0.44 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Brain imaging studies in TEP, functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have shown that visuospatial short-term memory tasks depend on dorsal parietofrontal networks. Knowing the spatiotemporal dynamics of this network would provide further understanding of the neural bases of the encoding process. We combined magnetoencephalography (MEG) with EEG and fMRI techniques to study this network in a task, in which participants had to judge the symmetry in position of two dots, presented either simultaneously ("immediate comparison") or successively ("memorization" of a first dot and "delayed comparison", after 3 s, with a second dot). With EEG, larger amplitude was observed in the parietocentral P3b component (350-500 ms) in the immediate and "delayed comparisons" than in "memorization" condition, where topography at this time was more anterior and right lateralized. MEG provided a more accurate localization and temporal variations of sources, revealing a strong M4 component at 450 ms in the "memorization" condition, with two sources localized in parietal and right premotor regions. These localizations are consistent with both fMRI foci and EEG cortical current source densities (CSD), but only MEG revealed the strong increase in premotor region at 450 ms related to "memorization". These combined results suggest that EEG P3B and MEG M4 components reflect two different dynamics in parietofrontal networks: the parietocentral P3b indexes a decision mechanism during the immediate and "delayed comparisons", whereas the MEG M4 component, with a larger right premotor source, reflects the encoding process in visuospatial short-term memory.
[Show abstract][Hide abstract] ABSTRACT: A neural network model of intrahippocampal and hippocampo-cortico-gangliobasal loops allows the robotic implementation of the spatial information contained within cognitive maps in neural space, into temporo-spatial sequences of movements during goal-oriented navigation in outer space. At the representation level, the intrahippocampal loop features place cells in entorhinal cortex and transition cells in CA3-CA1 which constitute, as a population, spatial and contextual maps, respectively. Path integration converges with place cell information in the subiculum. The spatial representation in deep and superficial layers of the entorhinal cortex are dissociated; the unidirectional connections between these two layers close the intrahippocamal loop. The prefrontal cortex, at the junction between representation and implementation, receives from three hippocampal subsystems and stores a global graph-map of an environment and the goal locations on this map. The diffusion of activation from active goals through the graph allows path selection in the motivational limbic prefrontal cortex and planning in the executive lateral part. The top-down output from prefrontal cortex and the bottom-up output from the hippocampus combine onto the accumbens the first stage for the stepwise selection and implementation of the optimal actions in the direction of the goal. Proactive and reactive functioning modes are dissociated.
[Show abstract][Hide abstract] ABSTRACT: Neuroimaging studies concerning the human cerebral cortex are increasingly numerous. The enormous variability of the human cortical anatomy is a major problem for the representation and comparison of these data and one of the main difficulties for the exploitation of neuroimaging data bases. We propose a simple geometric model that is able to capture the main traits of the cortical anatomy. The geometric model can be used as a unified coordinate system for representing neuroimaging data and as a common substrate for meta-analyses. We introduce the methods necessary to project neuroimaging results over the geometric model. We describe methods for handling data reported in Talairach coordinates (the most frequent way in which results are reported) and three-dimensional statistical maps (the most frequent form in which results are obtained).
Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, USA, 15-18 April 2004; 01/2004
[Show abstract][Hide abstract] ABSTRACT: Recent atlases of the cortical surface are based on a modelization of the cerebral cortex as a topological sphere. This captures effectively its organization as a regular bidimensional sheet of layers parallel to the surface and with perpendicular cortical columns. Yet, while in the vertical direction cortices are almost the same throughout phylia, in the sense of its surface the cerebral cortex is one of the most variable and distinctive parts of the nervous system. Indeed, gyri and sulci appear to have a crucial organizing role in an architectonic, connectional, and functional sense. This organization is not explicitly captured by the surface model of the cortex. We propose a geometric model of the cortical anatomy based on flat representations of principal sulci obtained from surface reconstructions of MRI data, and on neuroanatomical and theoretical considerations concerning the folding patterns of the cortex. The cortex is modeled by a sphere where primary sulci are included as axes. The arrangement of the axes is a simplification of the arrangement of principal sulci observed in flat stereographic representations of the whole cortical surface. The position of secondary and tertiary sulci is then defined by a field of orientations parallel and orthogonal to the axes. We consider the use of the geometric model as a synthetic reference cortex for addressing reconstructions of cortical surfaces. We present a method which establishes a bijection between the geometric model and a cortical surface reconstruction by using the axes of the model as boundary conditions for a set of partial differential equations solved over both surfaces. Using the geometric model as atlas provides a natural parameterization of the cortical surface that, unlike angular coordinates, allows for a localization based on the surface distance to its main organizing landmarks and folding patterns.
[Show abstract][Hide abstract] ABSTRACT: The brain plays a central role in sexual motivation. To identify cerebral areas whose activation was correlated with sexual desire, eight healthy male volunteers were studied with functional magnetic resonance imaging (fMRI). Visual stimuli were sexually stimulating photographs (S condition) and emotionally neutral photographs (N condition). Subjective responses pertaining to sexual desire were recorded after each condition. To image the entire brain, separate runs focused on the upper and the lower parts of the brain. Statistical Parametric Mapping was used for data analysis. Subjective ratings confirmed that sexual pictures effectively induced sexual arousal. In the S condition compared to the N condition, a group analysis conducted on the upper part of the brain demonstrated an increased signal in the parietal lobes (superior parietal lobules, left intraparietal sulcus, left inferior parietal lobule, and right postcentral gyrus), the right parietooccipital sulcus, the left superior occipital gyrus, and the precentral gyri. In addition, a decreased signal was recorded in the right posterior cingulate gyrus and the left precuneus. In individual analyses conducted on the lower part of the brain, an increased signal was found in the right and/or left middle occipital gyrus in seven subjects, and in the right and/or left fusiform gyrus in six subjects. In conclusion, fMRI allows to identify brain responses to visual sexual stimuli. Among activated regions in the S condition, parietal areas are known to be involved in attentional processes directed toward motivationally relevant stimuli, while frontal premotor areas have been implicated in motor preparation and motor imagery. Further work is needed to identify those specific features of the neural responses that distinguish sexual desire from other emotional and motivational states.