Scale-free brain functional networks

Functional magnetic resonance imaging (fMRI) is used to extract {\em functional networks} connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that: (a) the distribution of functional connections, and the probability of finding a link vs. distance are both scale-free, (b) the characteristic path length is small and comparable with those of equivalent random networks, and (c) the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small world networks, reflect important functional information about brain states.Comment: 4 pages, 5 figures, 2 table

An associative network with spatially organized connectivity

We investigate the properties of an autoassociative network of threshold-linear units whose synaptic connectivity is spatially structured and asymmetric. Since the methods of equilibrium statistical mechanics cannot be applied to such a network due to the lack of a Hamiltonian, we approach the problem through a signal-to-noise analysis, that we adapt to spatially organized networks. The conditions are analyzed for the appearance of stable, spatially non-uniform profiles of activity with large overlaps with one of the stored patterns. It is also shown, with simulations and analytic results, that the storage capacity does not decrease much when the connectivity of the network becomes short range. In addition, the method used here enables us to calculate exactly the storage capacity of a randomly connected network with arbitrary degree of dilution.Comment: 27 pages, 6 figures; Accepted for publication in JSTA

A model for generating synthetic dendrites of cortical neurons

One of the main challenges in neuroscience is to define the detailed structural design of the nervous system. This challenge is one of the first steps towards understanding how neural circuits contribute to the functional organization of the nervous system. In the cerebral cortex pyramidal neurons are key elements in brain function as they represent the most abundant cortical neuronal type and the main source of cortical excitatory synapses. Therefore, many researchers are interested in the analysis of the microanatomy of pyramidal cells since it constitutes an excellent tool for better understanding cortical processing of information. Computational models of neuronal networks based on real cortical circuits have become useful tools for studying certain aspects of the functional organization of the neocortex. Neuronal morphologies (morphological models) represent key features in these functional models. For these purposes, synthetic or virtual dendritic trees can be generated through a morphological model of a given neuronal type based on real morphometric parameters obtained from intracellularly-filled single neurons. This paper presents a new method to construct virtual dendrites by means of sampling a branching model that represents the dendritic morphology. This method has been contrasted using complete basal dendrites from 374 layer II/III pyramidal neurons of the mouse neocortex

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

The statistical neuroanatomy of frontal networks in the macaque

We were interested in gaining insight into the functional properties of frontal networks based upon their anatomical inputs. We took a neuroinformatics approach, carrying out maximum likelihood hierarchical cluster analysis on 25 frontal cortical areas based upon their anatomical connections, with 68 input areas representing exterosensory, chemosensory, motor, limbic, and other frontal inputs. The analysis revealed a set of statistically robust clusters. We used these clusters to divide the frontal areas into 5 groups, including ventral-lateral, ventral-medial, dorsal-medial, dorsal-lateral, and caudal-orbital groups. Each of these groups was defined by a unique set of inputs. This organization provides insight into the differential roles of each group of areas and suggests a gradient by which orbital and ventral-medial areas may be responsible for decision-making processes based on emotion and primary reinforcers, and lateral frontal areas are more involved in integrating affective and rational information into a common framework

Site fidelity and movement patterns of short-finned pilot whales within the Canary Islands : evidence for resident and transient populations

Funding: co-funded by the Canary Government (Consejería de Política Territorial, Sostenibilidad y Seguridad), the Spanish Government (Fundación Biodiversidad and Ministerio de Medio Ambiente, Medio Rural y Marino), Fundación La Caixa, and by a number of international projects funded by EU programmes MACETUS (FEDER/INTERREG III-B MAC/4.2/M10), EMECETUS (FEDER/INTERREG III-B56105/MAC/4.2/M10), LIFE (LIFE03NAT0062), INDEMARES LIFE+ (LIFE07/NAT/E/00732).1. The geographic location and oceanographic, physical, and chemical water properties make the Canary Islands one of the planet's biodiversity hotspots. The short‐finned pilot whale (Globicephala macrorhynchus) is one of the archipelago's most commonly encountered species and is potentially vulnerable to a range of anthropogenic pressures, including habitat degradation, acoustic pollution, fishing, whale‐watching operations, and shipping. Assessment of impact has not been possible because of a lack of even basic information about occurrence and distribution. 2. Spatial and temporal distributions, ranging behaviour, and residence patterns of short‐finned pilot whales were explored for the first time using survey and photo‐identification data collected in the Canary Islands between 1999 and 2012. In total, 1,081 pilot whale sightings were recorded during 70,620 km of search effort over 1,782 survey days. 3. Pilot whales were detected year round and distributed non‐uniformly within the archipelago, with greater densities concentrated in patchy areas mainly on the leeward side of the main islands. In total, 1,320 well‐marked individuals were identified, which exhibited a large degree of variability in site fidelity. 4. Different but not isolated subpopulations of pilot whales that share ranges and maintain social interactions were apparently present in the Canary Islands. Strong evidence of an island‐associated subpopulation was found, with a group of 50 ‘core resident’ individuals associated particularly with Tenerife. There were also ‘transient’ individuals or temporary migrants, which, probably driven by inter‐ and intra‐specific competition, may travel long distances whilst using the archipelago as part of a larger range. 5. These findings fill a major gap in the knowledge of this species’ occurrence, distribution, movements, and site fidelity in the archipelago and provide much needed data to allow the initiation of informed conservation assessments and management actions.PostprintPeer reviewe

Exogenous spatial precuing reliably modulates object processing but not object substitution masking

Object substitution masking (OSM) is used in behavioral and imaging studies to investigate processes associated with the formation of a conscious percept. Reportedly, OSM occurs only when visual attention is diffusely spread over a search display or focused away from the target location. Indeed, the presumed role of spatial attention is central to theoretical accounts of OSM and of visual processing more generally (Di Lollo, Enns, & Rensink, Journal of Experimental Psychology: General 129:481–507, 2000). We report a series of five experiments in which valid spatial precuing is shown to enhance the ability of participants to accurately report a target but, in most cases, without affecting OSM. In only one experiment (Experiment 5) was a significant effect of precuing observed on masking. This is in contrast to the reliable effect shown across all five experiments in which precuing improved overall performance. The results are convergent with recent findings from Argyropoulos, Gellatly, and Pilling (Journal of Experimental Psychology: Human Perception and Performance 39:646–661, 2013), which show that OSM is independent of the number of distractor items in a display. Our results demonstrate that OSM can operate independently of focal attention. Previous claims of the strong interrelationship between OSM and spatial attention are likely to have arisen from ceiling or floor artifacts that restricted measurable performance

Qualia: The Geometry of Integrated Information

According to the integrated information theory, the quantity of consciousness is the amount of integrated information generated by a complex of elements, and the quality of experience is specified by the informational relationships it generates. This paper outlines a framework for characterizing the informational relationships generated by such systems. Qualia space (Q) is a space having an axis for each possible state (activity pattern) of a complex. Within Q, each submechanism specifies a point corresponding to a repertoire of system states. Arrows between repertoires in Q define informational relationships. Together, these arrows specify a quale—a shape that completely and univocally characterizes the quality of a conscious experience. Φ— the height of this shape—is the quantity of consciousness associated with the experience. Entanglement measures how irreducible informational relationships are to their component relationships, specifying concepts and modes. Several corollaries follow from these premises. The quale is determined by both the mechanism and state of the system. Thus, two different systems having identical activity patterns may generate different qualia. Conversely, the same quale may be generated by two systems that differ in both activity and connectivity. Both active and inactive elements specify a quale, but elements that are inactivated do not. Also, the activation of an element affects experience by changing the shape of the quale. The subdivision of experience into modalities and submodalities corresponds to subshapes in Q. In principle, different aspects of experience may be classified as different shapes in Q, and the similarity between experiences reduces to similarities between shapes. Finally, specific qualities, such as the “redness” of red, while generated by a local mechanism, cannot be reduced to it, but require considering the entire quale. Ultimately, the present framework may offer a principled way for translating qualitative properties of experience into mathematics

Mapping Human Whole-Brain Structural Networks with Diffusion MRI

Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world