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PubMed2004

Parietal cortex and representation of the mental Self.

For a coherent and meaningful life, conscious self-representation is mandatory. Such explicit "autonoetic consciousness" is thought to emerge by retrieval of memory of personally experienced events ("episodic memory"). During episodic retrieval, functional imaging studies consistently show differential activity in medial prefrontal and medial parietal cortices. With positron-emission tomography, we here show that these medial regions are functionally connected and interact with lateral regions that are activated according to the degree of self-reference. During retrieval of previous judgments of Oneself, Best Friend, and the Danish Queen, activation increased in the left lateral temporal cortex and decreased in the right inferior parietal region with decreasing self-reference. Functionally, the former region was preferentially connected to medial prefrontal cortex, the latter to medial parietal. The medial parietal region may, then, be conceived of as a nodal structure in self-representation, functionally connected to both the right parietal and the medial prefrontal cortices. To determine whether medial parietal cortex in this network is essential for episodic memory retrieval with self-representation, we used transcranial magnetic stimulation over the region to transiently disturb neuronal circuitry. There was a decrease in the efficiency of retrieval of previous judgment of mental Self compared with retrieval of judgment of Other with transcranial magnetic stimulation at a latency of 160 ms, confirming the hypothesis. This network is strikingly similar to the network of the resting conscious state, suggesting that self-monitoring is a core function in resting consciousness.

Adult↗

PubMed2004

Astrocytic adrenoceptors: a major drug target in neurological and psychiatric disorders?

Considerable attention has recently been paid to astrocyte functions, which are briefly summarized. A large amount of data is available about adrenoceptor expression and function in astrocytes, some of it dating back to the 1970's and some of it very recent. This material is reviewed in the present paper. The brain is innervated by noradrenergic fibers extending from locus coeruleus in the brain stem, which in turn is connected to a network of adrenergic and noradrenergic nuclei in the medulla and pons, contributing to the control of (nor)adrenergic, serotonergic, dopaminergic and cholinergic function, both in the central nervous system (CNS) and in the periphery. In the CNS astrocytes constitute a major target for noradrenergic innervation, which regulates morphological plasticity, energy metabolism, membrane transport, gap junction permeability and immunological responses in these cells. Noradrenergic effects on astrocytes are essential during consolidation of episodic, long-term memory, which is reinforced by beta-adrenergic activation. Glycogenolysis and synthesis of glutamate and glutamine from glucose, both of which are metabolic processes restricted to astrocytes, occur at several time-specific stages during the consolidation. Astrocytic abnormalities are almost certainly important in the pathogenesis of multiple sclerosis and in all probability contribute essentially to inflammation and malfunction in Alzheimer's disease and to mood disturbances in affective disorders. Noradrenergic function in astrocytes is severely disturbed by chronic exposure to cocaine, which also changes astrocyte morphology. Development of drugs modifying noradrenergic receptor activity and/or down-stream signaling is advocated for treatment of several neurological/psychiatric disorders and for neuroprotection. Astrocytic preparations are suggested for study of mechanism(s) of action of antidepressant drugs and pathophysiology of mood disorders.

Adrenergic Agents↗

PubMed1997

A network of tufted layer 5 pyramidal neurons.

Tufted layer 5 (TL5) pyramidal neurons are important projection neurons from the cerebral cortex to subcortical areas. Recent and ongoing experiments aimed at understanding the computational analysis performed by a network of synaptically connected TL5 neurons are reviewed here. The experiments employed dual and triple whole-cell patch clamp recordings from visually identified and preselected neurons in brain slices of somatosensory cortex of young (14- to 16-day-old) rats. These studies suggest that a local network of TL5 neurons within a cortical module of diameter 300 microns consists of a few hundred neurons that are extensively inter-connected with reciprocal feedback from at least first-, second- and third-order target neurons. A statistical analysis of synaptic innervation suggests that this recurrent network is not randomly arranged and hence each neuron could be functionally unique. Synaptic transmission between these neurons is characterized by use-dependent synaptic depression which confers novel properties to this recurrent network of neurons. First, a range of rates of depression for different synaptic connections enable each TL5 neuron to receive a unique mixture of information about the average firing rates and the temporally correlated action potential (AP) activity in the population of presynaptic TL5 neurons. Second, each AP generated by any neuron in the network induces a change (defined as an iteration step) in the functional coupling of the neurons in the network (defined as network configuration). It is proposed that the network configuration is iterated during a stimulus to achieve an optimally orchestrated network response. Hebbian, anti-Hebbian and neuromodulatory-induced modifications of neurotransmitter release probability change the rates of synaptic depression and thereby alter the iteration step size. These data may be important to understand the dynamics of electrical activity within the network.

Animals↗

PubMed1992

Determining the neuronal connectivity of Golgi-impregnated neurons: ultrastructural assessment of functional aspects.

The combined light and electron microscopic analysis of Golgi-impregnated neural tissue is a potent tool for determining the connectivity of neural networks within the brain. In the experimental paradigms commonly applied in these studies, the Golgi-impregnated neurons are typically examined as the postsynaptic neuronal components. The structural characteristics and the pattern of distribution of their synaptic connections with other groups of identified neurons are analyzed. Due to the high power of resolution of the Golgi-electron microscopic technique, the ultrastructural analysis of Golgi-impregnated neurons can be expanded to elucidate activity-dependent structural alterations in their cytoarchitecture. These structural alterations can then be correlated under different physiological conditions with changes in the functional efficacy of the subcellular neuronal components.

Animals↗

PubMed1992

Thalamocortical connections of rat posterior parietal cortex.

The neuronal connections of rat posterior parietal cortex (PPC) have been examined using retrograde fluorescent axonal tracers. We have found that PPC receives thalamic input predominantly from the lateral posterior and lateral dorsal nuclei, and not from the ventrobasal nucleus, which projects to the rostrally adjacent hindlimb cortex, or from the dorsal lateral geniculate nucleus, which projects to the caudally adjacent visual association area. PPC has reciprocal corticocortical connections with medial agranular cortex and orbital cortex; together, these three cortical areas may function as a network for directed attention in rats.

Afferent Pathways↗

PubMed1997

Free recall and recognition in a network model of the hippocampus: simulating effects of scopolamine on human memory function.

Free recall and recognition are simulated in a network model of the hippocampal formation, incorporating simplified simulations of neurons, synaptic connections, and the effects of acetylcholine. Simulations focus on modeling the effects of the acetylcholine receptor blocker scopolamine on human memory. Systemic administration of scopolamine is modeled by blockade of the cellular effects of acetylcholine in the model, resulting in memory impairments replicating data from studies on human subjects. This blockade of cholinergic effects impairs the encoding of new input patterns (as measured by delayed free recall), but does not impair the delayed free recall of input patterns learned before the blockade. The impairment is selective to the free recall but not the recognition of items encoded under the influence of scopolamine. In the model, scopolamine blocks strengthening of recurrent connections in region CA3 to form attractor states for new items (encoding impaired) but allows recurrent excitation to drive the network into previously stored attractor states (retrieval spared). Neuron populations representing items (individual words) have weaker recurrent connections than neuron populations representing experimental context. When scopolamine further weakens the strength of recurrent connections it selectively prevents the subsequent reactivation of item attractor states by context input (impaired free recall) without impairing the subsequent reactivation of context attractor states by item input (spared recognition). This asymmetry in the strength of attractor states also allows simulation of the list-strength effect for free recall but not recognition. Simulation of a paired associate learning paradigm predicts that scopolamine should greatly enhance proactive interference due to retrieval of previously encoded associations during storage of new associations.

Cholinergic Antagonists↗

PubMed2004

Social cognition, brain networks and schizophrenia.

BACKGROUND: A better understanding of the neural basis of social cognition including mindreading (or theory of mind) and empathy might help to explain some deficits in social functioning in people with schizophrenia. Our aim was to review neuroimaging and neuropsychological studies on social cognition, as they may shed light on the neural mechanisms of social cognition and its dysfunction in patients with schizophrenia. METHOD: A selective literature review was undertaken. RESULTS: Neuroimaging and neuropsychological studies suggest convergence upon specific networks for mindreading and empathy (the temporal cortex, amygdala and the prefrontal cortex). The frontal lobe is likely to play a central role in enabling social cognition, but mindreading and empathic abilities may require relatively different weighting of subcomponents within the same frontal-temporal social cognition network. CONCLUSIONS: Disturbances in social cognition may represent an abnormal interaction between frontal lobe and its functionally connected cortical and subcortical areas. Future studies should seek to explore the heterogeneity of social dysfunction within schizophrenia.

Brain Mapping↗

PubMedDate not supplied

Autocorrelation method adapted to generate new atomic environments: application for the prediction of 13-C chemical shifts of alkanes.

The concept of the multifunctional autocorrelation method governing global description of molecules was changed in order to take into account the structural environment of each atom. New atomic environments are generated as possible descriptors in QSARs and can be useful for database characterization. The principles of this approach are widely explained through a case study dealing with the design of a model allowing the simulation of the carbon-13 nuclear magnetic spectra for alkanes. Carbon atoms in alkanes are described by using as structural descriptors a vector corresponding to only four components vectors of the multifunctional autocorrelation method. The statistical method used for deriving the model was a classical three-layer feedforward neural network trained by the back-propagation algorithm and multilinear regression (MLR). The predictive ability of the ANN model was tested by -10%-out(L10%O) cross-validation method, demonstrating the superior quality of the neural model. The established model allows us the prediction of the 13-C chemical shifts with success because since all types of carbons are taken into account without distinction of connectivity. The neural network possessed a 4:7:1 architecture with a sigmoid shape as a activation function. The model produced a cross-validation standard coefficient r between delta(exp) and delta(calc) about 0.99, while the cross-validation standard s and the mean error are equal to 0.87 and 0.60 ppm, respectively.

Journal Article↗

PubMed1990

Neural network model of visual cortex for determining surface curvature from images of shaded surfaces.

The visual system can extract information about shape from the pattern of light and dark surface shading on an object. Very little is known about how this is accomplished. We have used a learning algorithm to construct a neural network model that computes the principal curvatures and orientation of elliptic paraboloids independently of the illumination direction. Our chief finding is that receptive fields developed by units of such model network are surprisingly similar to some found in the visual cortex. It appears that neurons that can make use of the continuous gradations of shading have receptive fields similar to those previously interpreted as dealing with contours (i.e. 'bar' detectors or 'edge' detectors). This study illustrates the difficulty of deducing neuronal function within a network solely from receptive fields. It is also important to consider the pattern of connections a neuron makes with subsequent stages, which we call the 'projective field'.

Algorithms↗

PubMed2005

Localization transition on complex networks via spectral statistics.

The spectral statistics of complex networks are numerically studied. The features of the Anderson metal-insulator transition are found to be similar for a wide range of different networks. A metal-insulator transition as a function of the disorder can be observed for different classes of complex networks for which the average connectivity is small. The critical index of the transition corresponds to the mean field expectation. When the connectivity is higher, the amount of disorder needed to reach a certain degree of localization is proportional to the average connectivity, though a precise transition cannot be identified. The absence of a clear transition at high connectivity is probably due to the very compact structure of the highly connected networks, resulting in a small diameter even for a large number of sites.

Journal Article↗

PubMed2004

Primitive roles for inhibitory interneurons in developing frog spinal cord.

Understanding the neuronal networks in the mammal spinal cord is hampered by the diversity of neurons and their connections. The simpler networks in developing lower vertebrates may offer insights into basic organization. To investigate the function of spinal inhibitory interneurons in Xenopus tadpoles, paired whole-cell recordings were used. We show directly that one class of interneuron, with distinctive anatomy, produces glycinergic, negative feedback inhibition that can limit firing in motoneurons and interneurons of the central pattern generator during swimming. These same neurons also produce inhibitory gating of sensory pathways during swimming. This discovery raises the possibility that some classes of interneuron, with distinct functions later in development, may differentiate from an earlier class in which these functions are shared. Preliminary evidence suggests that these inhibitory interneurons express the transcription factor engrailed, supporting a probable homology with interneurons in developing zebrafish that also express engrailed and have very similar anatomy and functions.

Action Potentials↗

PubMed2001

[Diffusion tensor imaging (DTI) and functional magnetic resonance tomography (fMRI) expand methodological spectrum in psychiatric research].

In psychiatric research, there is a growing interest in the microstructural and functional characteristics of brain networks, which often form the basis of current etiological concepts. As a result of novel magnetic resonance imaging techniques, the pathogenic characteristics of neuronal activity and connectivity can be examined in a noninvasive, safe, and repeatable manner. Functional magnetic resonance imaging (fMRI) uses blood oxygenation level-dependent (BOLD) measures for identifying the gray matter contribution to cognition. Diffusion tensor imaging (DTI) reveals the course and structural integrity of white matter projections. Because DTI does not require special motivation and performance, group differences in psychiatry are more easily interpreted in terms of underlying pathology. To date few studies have tried to investigate both, i.e. dynamic and microstructural data in the sense of a modern multi-dimensional investigation approach. The combination of both techniques, however, seems to offer a promising vehicle to further extent our current understanding of mental disorders and to identify populations at risk. In addition to addressing findings in psychiatric research, the present article presents a technical overview of DTI and examines the limitations and potential applications of both techniques.

Anisotropy↗

PubMed1997

Organization of intrinsic connections in owl monkey area MT.

Area MT (middle temporal) is a well-defined visual representation common to all primates, which shows a clear selectivity to the analysis of visual motion. In the present study we examined the architecture of the intrinsic connections in area MT in an attempt to reveal its organizing principles and its potential relationship to the functional domains in area MT. Intrinsic connections were studied by placing small injections of the tracer biocytin in area MT of seven adult owl monkeys (Aotus nancymae). The injections were targeted at well-defined orientation domains revealed using optical imaging of intrinsic signals. The distribution of axons labeled by these injections was related both to the cytochrome oxidase histochemistry and to the layout of functional domains in area MT and surrounding tissue. Tracer injections in the superficial layers of area MT produced a complex network of extrinsic and intrinsic axonal connections. Clear instances of extrinsic connections were observed between area MT proper and the MT crescent situated postero-medially to it. The intrinsic connections were laterally spread and organized in patch-like clusters with an average distance from injection center to the furthest patch of 1.8 +/- 0.55 mm (+/-SD, n = 9). The overall axonal distribution tended to be anisotropic, i.e. the patches were distributed within an elongated ellipse [average anisotropy ratio: 1.86 +/- 0.66 (+/-SD)] and were asymmetrically distributed about either side of the injection site [average asymmetry ratio: 2.3 +/- 0.7 (+/-SD)]. Finally, there was a tendency for the intrinsic connections to connect to functional domains of similar orientation preference in area MT. However, this tendency varied substantially between individual cases. The highly specific nature of MT lateral connections puts clear constraints on models of surround influences in the receptive fields of MT neurons.

Animals↗

PubMed1987

Transient morphological features of identified ganglion cells in living fetal and neonatal retina.

The function and morphology of retinal ganglion cells in the adult mammalian visual system has been well studied, but little is known about how the adult state is achieved. To address this question, the morphological changes that retinal ganglion cells undergo during development were studied. Ganglion cells were first identified by retrograde labeling with rhodamine latex microspheres deposited in retinorecipient targets in fetal and early postnatal cats. The structure of ganglion cells was then revealed by intracellular injection of Lucifer yellow in living retinas removed and maintained in vitro. As early as 2 weeks before birth, a morphologically diverse assortment of ganglion cells is present, some of which resemble the alpha, beta, and gamma classes found in the adult. However, in contrast to the adult, developing ganglion cells exhibit several transient features, including excessive axonal and dendritic branching and exuberant somatic and dendritic spines. These morphological features indicate that there is a transient network of connectivity that could play an important role in the final determination of retinal ganglion cell form and function.

Animals↗

PubMed1992

Changes in brain functional connectivity in Alzheimer-type and multi-infarct dementia.

Clinical and neuropathological evaluation of elderly subjects with dementia has traditionally concentrated upon the focal distribution of brain disease, ignoring changes in the complex connections that link brain areas and that are crucial for cognition. We examined subjects with the two most common forms of dementia in the elderly (dementia of the Alzheimer type or DAT, and multi-infarct dementia or MID); and used electroencephalographic (EEG) coherence to examine the effects of these illnesses on the functional connections between brain areas. We studied coherence between brain areas known to be linked by two different types of connections: (i) dense narrow bands of long corticocortical fibres; (ii) broad complex networks of corticocortical and corticosubcortical fibres. Areas that were linked by dense narrow bands of long corticocortical fibres showed greatly diminished coherence in subjects with DAT; among MID subjects, this coherence was not significantly affected. Areas that were linked by broad connective networks showed the largest decreases in coherence among MID subjects. These findings are consistent with neuropathological evidence that Alzheimer's disease is a neocortical 'disconnection syndrome' in which there is a loss of structural and functional integrity of long corticocortical tracts. The findings further suggest that the vascular disease of MID most prominently affects broad fibre networks that may be more vulnerable to diffuse subcortical vascular damage. A ratio of coherence from complex corticocortical-corticosubcortical networks divided by coherence from long corticocortical tracts correctly classified 76% of subjects into DAT and MID categories. Overall, these results indicate that EEG coherence detects basic pathophysiological differences between subjects with DAT and MID, and that these differences may be clinically useful.

Aged↗

PubMed2002

The identification of functional modules from the genomic association of genes.

By combining the pairwise interactions between proteins, as predicted by the conserved co-occurrence of their genes in operons, we obtain protein interaction networks. Here we study the properties of such networks to identify functional modules: sets of proteins that together are involved in a biological process. The complete network contains 3,033 orthologous groups of proteins in 38 genomes. It consists of one giant component, containing 1,611 orthologous groups, and of 516 small disjointed clusters that, on average, contain only 2.7 orthologous groups. These small clusters have a homogeneous functional composition and thus represent functional modules in themselves. Analysis of the giant component reveals that it is a scale-free, small-world network with a high degree of local clustering (C = 0.6). It consists of locally highly connected subclusters that are connected to each other by linker proteins. The linker proteins tend to have multiple functions, or are involved in multiple processes and have an above average probability of being essential. By splitting up the giant component at these linker proteins, we identify 265 subclusters that tend to have a homogeneous functional composition. The rare functional inhomogeneities in our subclusters reflect the mixing of different types of (molecular) functions in a single cellular process, exemplified by subclusters containing both metabolic enzymes as well as the transcription factors that regulate them. Comparative genome analysis, thus, allows identification of a level of functional interaction between that of pairwise interactions, and of the complete genome.

Animals↗

PubMed2005

The rewards of music listening: response and physiological connectivity of the mesolimbic system.

Although the neural underpinnings of music cognition have been widely studied in the last 5 years, relatively little is known about the neuroscience underlying emotional reactions that music induces in listeners. Many people spend a significant amount of time listening to music, and its emotional power is assumed but not well understood. Here, we use functional and effective connectivity analyses to show for the first time that listening to music strongly modulates activity in a network of mesolimbic structures involved in reward processing including the nucleus accumbens (NAc) and the ventral tegmental area (VTA), as well as the hypothalamus and insula, which are thought to be involved in regulating autonomic and physiological responses to rewarding and emotional stimuli. Responses in the NAc and the VTA were strongly correlated pointing to an association between dopamine release and NAc response to music. Responses in the NAc and the hypothalamus were also strongly correlated across subjects, suggesting a mechanism by which listening to pleasant music evokes physiological reactions. Effective connectivity confirmed these findings, and showed significant VTA-mediated interaction of the NAc with the hypothalamus, insula, and orbitofrontal cortex. The enhanced functional and effective connectivity between brain regions mediating reward, autonomic, and cognitive processing provides insight into understanding why listening to music is one of the most rewarding and pleasurable human experiences.

Acoustic Stimulation↗

PubMed1990

Pattern-recognition by an artificial network derived from biologic neuronal systems.

A novel artificial neural network, derived from neurobiological observations, is described and examples of its performance are presented. This DYnamically STable Associative Learning (DYSTAL) network associatively learns both correlations and anticorrelations, and can be configured to classify or restore patterns with only a change in the number of output units. DYSTAL exhibits some particularly desirable properties: computational effort scales linearly with the number of connections, i.e., it is O(N) in complexity; performance of the network is stable with respect to network parameters over wide ranges of their values and over the size of the input field; storage of a very large number of patterns is possible; patterns need not be orthogonal; network connections are not restricted to multi-layer feed-forward or any other specific structure; and, for a known set of deterministic input patterns, the network weights can be computed, a priori, in closed form. The network has been associatively trained to perform the XOR function as well as other classification tasks. The network has also been trained to restore patterns obscured by binary or analog noise. Neither global nor local feedback connections are required during learning; hence the network is particularly suitable for hardware (VLSI) implementation.

Animals↗