The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

A benchmark test for a quantitative assessment of simple neuron models

Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activity of neurons under temporally structured current injection. It is, however, difficult to compare the advantages of various models and algorithms since each model is designed for a different set of data. Here, we report about one of the first attempts to establish a benchmark test that permits a systematic comparison of methods and performances in predicting the activity of rat cortical pyramidal neurons. We present early submissions to the benchmark test and discuss implications for the design of future tests and simple neurons models

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

As the world turns: short-term human spatial memory in egocentric and allocentric coordinates

We aimed to determine whether human subjects' reliance on different sources of spatial information encoded in different frames of reference (i.e., egocentric versus allocentric) affects their performance, decision time and memory capacity in a short-term spatial memory task performed in the real world. Subjects were asked to play the Memory game (a.k.a. the Concentration game) without an opponent, in four different conditions that controlled for the subjects' reliance on egocentric and/or allocentric frames of reference for the elaboration of a spatial representation of the image locations enabling maximal efficiency. We report experimental data from young adult men and women, and describe a mathematical model to estimate human short-term spatial memory capacity. We found that short-term spatial memory capacity was greatest when an egocentric spatial frame of reference enabled subjects to encode and remember the image locations. However, when egocentric information was not reliable, short-term spatial memory capacity was greater and decision time shorter when an allocentric representation of the image locations with respect to distant objects in the surrounding environment was available, as compared to when only a spatial representation encoding the relationships between the individual images, independent of the surrounding environment, was available. Our findings thus further demonstrate that changes in viewpoint produced by the movement of images placed in front of a stationary subject is not equivalent to the movement of the subject around stationary images. We discuss possible limitations of classical neuropsychological and virtual reality experiments of spatial memory, which typically restrict the sensory information normally available to human subjects in the real world.

Angiotensinergic neurotransmission in the peripheral autonomic nervous system.

Angiotensin (Ang) II has for long been identified as a neuropeptide located within neurons and pathways of the central nervous system involved in the control of thirst and cardio-vascular homeostasis. The presence of Ang II in ganglionic neurons of celiac, dorsal root, and trigeminal ganglia has only recently been described in humans and rats. Ang II-containing fibers were also found in the mesenteric artery and the heart, together with intrinsic Ang II-containing cardiac neurons. Ganglionic neurons express angiotensinogen and co-localize it with Ang II. Its intraneuronal production as a neuropeptide appears to involve angiotensinogen processing enzymes other than renin. Immunocytochemical and gene expression data suggest that neuronal Ang II acts as a neuromodulatory peptide and co-transmitter in the peripheral autonomic, and also sensory nervous system. Neuronal Ang II probably competes with humoral Ang II for effector cell activation. Its functional role, however, still remains to be determined. Angiotensinergic neurotransmission in the autonomic nervous system is a potential new target for therapeutic interventions in many common diseases such as essential hypertension, heart failure, and cardiac arrhythmia.

Research in psychopathology: epistemologic issues.

Etiologic research in psychiatry relies on an objectivist epistemology positing that human cognition is specified by the "reality" of the outer world, which consists of a totality of mind-independent objects. Truth is considered as some sort of correspondence relation between words and external objects, and mind as a mirror of nature. In our view, this epistemology considerably impedes etiologic research. Objectivist epistemology has been recently confronting a growing critique from diverse scientific fields. Alternative models in neurosciences (neuronal selection), artificial intelligence (connectionism), and developmental psychology (developmental biodynamics) converge in viewing living organisms as self-organizing systems. In this perspective, the organism is not specified by the outer world, but enacts its environment by selecting relevant domains of significance that constitute its world. The distinction between mind and body or organism and environment is a matter of observational perspective. These models from empirical sciences are compatible with fundamental tenets of philosophical phenomenology and hermeneutics. They imply consequences for research in psychopathology: symptoms cannot be viewed as disconnected manifestations of discrete localized brain dysfunctions. Psychopathology should therefore focus on how the person's self-coherence is maintained and on the understanding and empirical investigation of the systemic laws that govern neurodevelopment and the organization of human cognition.

A neuron-glia signalling network in the active brain.

Glial cells are active partners of neurons in processing information and synaptic integration. They receive coded signals from synapses and elaborate modulatory responses. The active properties of glia, including long-range signalling and regulated transmitter release, are beginning to be elucidated. Recent insights suggest that the active brain should no longer be regarded as a circuitry of neuronal contacts, but as an integrated network of interactive neurons and glia.

Spontaneous NA+ transients in individual mitochondria of intact astrocytes.

Mitochondria in intact cells maintain low Na(+) levels despite the large electrochemical gradient favoring cation influx into the matrix. In addition, they display individual spontaneous transient depolarizations. The authors report here that individual mitochondria in living astrocytes exhibit spontaneous increases in their Na(+) concentration (Na(mit)(+) spiking), as measured using the mitochondrial probe CoroNa Red. In a field of view with approximately 30 astrocytes, up to 1,400 transients per minute were typically detected under resting conditions. Na(mit)(+) spiking was also observed in neurons, but was scarce in two nonneural cell types tested. Astrocytic Na(mit)(+) spikes averaged 12.2 +/- 0.8 s in duration and 35.5 +/- 3.2 mM in amplitude and coincided with brief mitochondrial depolarizations; they were impaired by mitochondrial depolarization and ruthenium red pointing to the involvement of a cation uniporter. Na(mit)(+) spiking activity was significantly inhibited by mitochondrial Na(+)/H(+) exchanger inhibition and sensitive to cellular pH and Na(+) concentration. Ca(2+) played a permissive role on Na(mit)(+) spiking activity. Finally, the authors present evidence suggesting that Na(mit)(+) spiking frequency was correlated with cellular ATP levels. This study shows that, under physiological conditions, individual mitochondria in living astrocytes exhibit fast Na(+) exchange across their inner membrane, which reveals a new form of highly dynamic and localized functional regulation.

Selective neurodegeneration induced in rotation-mediated aggregate cell cultures by a transient switch to stationary culture conditions: a potential model to study ischemia-related pathogenic mechanisms.

Aggregating brain cell cultures at an advanced maturational stage (20-21 days in vitro) were subjected for 1-3 h to anaerobic (hypoxic) and/or stationary (ischemic) conditions. After restoration of the normal culture conditions, cell loss was estimated by measuring the release of lactate dehydrogenase as well as the irreversible decrease of cell type-specific enzyme activities, total protein and DNA content. Ischemia for 2 h induced significant neuronal cell death. Hypoxia combined with ischemia affected both neuronal and glial cells to different degrees (GABAergic neurons>cholinergic neurons>astrocytes). Hypoxic and ischemic conditions greatly stimulated the uptake of 2-deoxy-D-glucose, indicating increased glucose consumption. Furthermore, glucose restriction (5.5 mM instead of 25 mM) dramatically increased the susceptibility of neuronal and glial cells to hypoxic and ischemic conditions. Glucose media concentrations below 2 mM caused selective neuronal cell death in otherwise normal culture conditions. GABAergic neurons showed a particularly high sensitivity to glucose restriction, hypoxia, and ischemia. The pattern of ischemia-induced changes in vitro showed many similarities to in vivo findings, suggesting that aggregating brain cell cultures provide a useful in vitro model to study pathogenic mechanisms related to brain ischemia.

Mapping the structural core of human cerebral cortex.

Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.

Sweet sixteen for ANLS.

Since its introduction 16 years ago, the astrocyte-neuron lactate shuttle (ANLS) model has profoundly modified our understanding of neuroenergetics by bringing a cellular and molecular resolution. Praised or disputed, the concept has never ceased to attract attention, leading to critical advances and unexpected insights. Here, we summarize recent experimental evidence further supporting the main tenets of the model. Thus, evidence for distinct metabolic phenotypes between neurons (mainly oxidative) and astrocytes (mainly glycolytic) have been provided by genomics and classical metabolic approaches. Moreover, it has become clear that astrocytes act as a syncytium to distribute energy substrates such as lactate to active neurones. Glycogen, the main energy reserve located in astrocytes, is used as a lactate source to sustain glutamatergic neurotransmission and synaptic plasticity. Lactate is also emerging as a neuroprotective agent as well as a key signal to regulate blood flow. Characterization of monocarboxylate transporter regulation indicates a possible involvement in synaptic plasticity and memory. Finally, several modeling studies captured the implications of such findings for many brain functions. The ANLS model now represents a useful, experimentally based framework to better understand the coupling between neuronal activity and energetics as it relates to neuronal plasticity, neurodegeneration, and functional brain imaging.

Comment on recent modeling studies of astrocyte-neuron metabolic interactions.

Recent years have seen a surge in mathematical modeling of the various aspects of neuron-astrocyte interactions, and the field of brain energy metabolism is no exception in that regard. Despite the advent of biophysical models in the field, the long-lasting debate on the role of lactate in brain energy metabolism is still unresolved. Quite the contrary, it has been ported to the world of differential equations. Here, we summarize the present state of this discussion from the modeler's point of view and bring some crucial points to the attention of the non-mathematically proficient reader.

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

A surface-based approach to quantify local cortical gyrification.

The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.

Seizure semiology: an overview of the 'inverse problem'.

In clinical practice, a classification of seizures based on clinical signs and symptoms leads to an improved understanding of epilepsy-related issues and therefore strongly contributes to a better patient care. The inverse problem involves inferring the anatomical brain localization of a seizure from the scalp surface EEG, a concept we apply here to correlate seizure origin with seizure semiology. The spheres of sensorium, motor features, consciousness changes and autonomic alterations during ictal and postictal manifestations are reviewed, including several subdivisions used to better categorize particular features. Particular attention is given to behavioral features, as well as to features occurring in idiopathic generalized epileptic syndromes and psychogenic nonepileptic spells.