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At least 505 records · Page 28Linked to original sources
PubMed2003

Axonal injury within language network in primary progressive aphasia.

Primary progressive aphasia (PPA) is characterized by an isolated progressive impairment of word use and comprehension reflecting the distribution of pathological processes within the left hemisphere. We used proton magnetic resonance spectroscopy (1H-MRS) to study in vivo the integrity of axonal fibers connecting perisylvian language areas in 11 patients with PPA, 11 subjects with Alzheimer's disease, and 22 controls. Brain metabolites (N-acetylaspartate, myoinositol, choline, creatine) were measured bilaterally within a volume of interest located in the central portion of the superior longitudinal fasciculus, a long associative bundle connecting Broca's area with Wernicke's area, and other language regions of the temporal lobe. In the PPA group, there was an asymmetrical N-acetylaspartate to creatine ratio reduction compared with Alzheimer's disease and controls, with greater changes on the left side. The myoinositol to creatine ratio was increased in the PPA group bilaterally compared with controls. The choline to creatine ratio did not differ among the three groups. These results indicate an asymmetrical focal axonal injury within the language network in PPA. The marked difference in the distribution of N-acetylaspartate to creatine between PPA and Alzheimer's disease suggests that proton magnetic resonance spectroscopy may help to differentiate between these two conditions.

Aged↗
PubMed1998

Mechanisms of spontaneous activity in developing spinal networks.

Developing networks of the chick spinal cord become spontaneously active early in development and remain so until hatching. Experiments using an isolated preparation of the spinal cord have begun to reveal the mechanisms responsible for this activity. Whole-cell and optical recordings have shown that spinal neurons receive a rhythmic, depolarizing synaptic drive and experience rhythmic elevations of intracellular calcium during spontaneous episodes. Activity is expressed throughout the neuraxis and can be produced by different parts of the cord and by the isolated brain stem, suggesting that it does not depend upon the details of network architecture. Two factors appear to be particularly important for the production of endogenous activity. The first is the predominantly excitatory nature of developing synaptic connections, and the second is the presence of prolonged activity-dependent depression of network excitability. The interaction between high excitability and depression results in an equilibrium in which episodes are expressed periodically by the network. The mechanism of the rhythmic bursting within an episode is not understood, but it may be due to a "fast" form of network depression. Spontaneous embryonic activity has been shown to play a role in neuron and muscle development, but is probably not involved in the initial formation of connections between spinal neurons. It may be important in refining the initial connections, but this possibility remains to be explored.

Action Potentials↗
PubMed2005

Functional interactions between oculomotor regions during prosaccades and antisaccades.

Human behavior reflects a continual negotiation of automatic and directed actions. The oculomotor network is a well-characterized neural system in which to study this balance of behavioral control. For instance, saccades made toward and away from a flashed visual stimulus (prosaccades and antisaccades, respectively) are known to engage different cognitive processes. Brain regions important for such controlled execution include the presupplementary motor area (pre-SMA), frontal eye fields (FEF), and intraparietal sulcus (IPS). Recent work has emphasized various elements of this network but has not explored the functional interactions among regions. We used event-related fMRI to image human brain activity during performance of an interleaved pro/antisaccade task. Since traditional univariate statistics cannot address issues of functional connectivity, a multivariate technique is necessary. Coherence between fMRI time series of the pre-SMA with the FEF and IPS was used to measure functional interactions. The FEF, but not IPS, showed significant differential coherence between pro- and antisaccade trials with pre-SMA. These results suggest that the pre-SMA coordinates with FEF to maintain a controlled, preparatory set for task-appropriate oculomotor execution.

Adult↗
PubMed1999

The right neuron at the wrong place: biology of heterotopic neurons in cortical neuronal migration disorders, with special reference to associated pathologies.

During the development of the neocortex, neurogenesis and neuronal differentiation occur in two separate locations. Thus neurons have to migrate through the future white matter. Arrested or excessive migration leads neurons to differentiate in a heterotopic position. Such neuronal migration disorders (NMDs) occur sporadically in normal development but are markedly increased as a consequence of genetic defects or after exposure to toxic drugs during the period of migration. Anatomofunctional studies in rodents with NMDs have revealed that heterotopic neurons form essentially normal afferent and efferent connections, which has been interpreted as evidence that the connection pattern of cortical neurons is specified prior to migration. In addition, recent data show that heterotopic neurons can be contacted by environmental, that is local, fibres that normally never innervate the neocortex. This dual connectivity leads heterotopias to form bridges between their environmental and original network. Such an abnormal pattern of connectivity could contribute to the pathophysiology of disorders associated with NMDs such as epilepsy.

Animals↗
PubMed2006

Spatial representation and the architecture of the entorhinal cortex.

It has recently been recognized that the entorhinal cortex has a crucial role in spatial representation and navigation. How the position of an animal is computed within the entorhinal circuitry remains to be determined, but the architectural organization of this brain area might provide some clues. Here, we review three organizational principles--recurrent connectivity, interlaminar connectivity and modular organization--and propose how each of them might contribute to the emergence and maintenance of positional representations in entorhinal neural networks.

Animals↗
PubMed2001

Noninvasive neuroelectronic interfacing with synaptically connected snail neurons immobilized on a semiconductor chip.

A hybrid circuit of a semiconductor chip and synaptically connected neurons was implemented and characterized. Individual nerve cells from the snail Lymnaea stagnalis were immobilized on a silicon chip by microscopic picket fences of polyimide. The cells formed a network with electrical synapses after outgrowth in brain conditioned medium. Pairs of neurons were electronically interfaced for noninvasive stimulation and recording. Voltage pulses were applied to a capacitive stimulator on the chip to excite the attached neuron. Signals were transmitted in the neuronal net and elicited an action potential in a second neuron. The postsynaptic excitation modulated the current of a transistor on the chip. The implementation of the silicon-neuron-neuron-silicon circuit constitutes a proof-of-principle experiment for the development of neuroelectronic systems to be used in studies on neuronal signal processing, neurocomputation, and neuroprosthetics.

Animals↗
PubMed2004

Changes in functional connectivity of human MT/V5 with visual motion input.

The neural basis of human mental function is characterized by interactions between brain regions. Temporal correlations in MR signals between areas may provide one method for investigating these interactions. This approach was used to examine functional connectivity in the motion processing system of the human brain. Correlations between MT/V5 and other brain regions were examined in a resting state (without visual stimulation) and in an active state produced by viewing moving concentric circles. A network of regions consistent with the known functional anatomy of visual processing was correlated with MT/V5 during rest. When subjects were viewing motion, a more limited network was correlated with MT/V5, suggesting MT/V5 was acting in concert with a smaller network specific to the task.

Brain Mapping↗
PubMed1996

Networks with lateral connectivity. I. dynamic properties mediated by the balance of intrinsic excitation and inhibition.

1. We studied the rapid dynamic changes of neuron response properties in the somatosensory cortex by the use of computer simulations. The model consists of three feedforward layers of spiking neurons, corresponding to skin, subcortex, and cortex structures. Measurements and analysis of model activity throughout this work are similar to those used in neurophysiological experiments. 2. The effects of various parameters on response properties of model neurons were investigated. The most important parameters were the lateral excitation and inhibition in the simulated cortical network. 3. The balance between excitation and inhibition is a key factor in determining the stability of the network model. There is a large excitation-inhibition (E-I) parameter region within which the model can stably respond to inputs. 4. The input-output relations and receptive field (RF) sizes of simulated neurons are modifiable by the E-I balance. The shapes of RFs are determined by both feedforward projections and the spatial distribution of lateral connections. 5. We simulated changes in temporal and spatial properties of neurons in response to manipulations that mimic bicuculine methiodide or glutamate application to the cortex. Simulation results agreed well with experimental data, suggesting that cortical transmitter levels play an important role in the dynamic responses of the neural net through their effects on E-I balance. 6. With parameters of the model set to an inhibition-dominant scheme, the model was able to reproduce experimentally observed rapid RF expansions that follow cortical lesion or input denervation. Simulation results also suggested that spontaneous inputs to a sensory system can serve as a source of tonic inhibition in the cortex. 7. We conclude that lateral connections could produce and maintain a cortical network having dynamic properties without the need to invoke synaptic plasticity. Individual neuron properties could be modified by changing the balance of cortical layer excitation and inhibition. In a real brain, this could be achieved either by changing levels of cortical transmitter (gamma-aminobutyric acid. for example) or by changing tonic background input to the cortical network.

Afferent Pathways↗
PubMed1997

Synaptic connectivity in cultured hypothalamic neuronal networks.

We have developed a novel approach to analyze the synaptic connectivity of spontaneously active networks of hypothalamic neurons in culture. Synaptic connections were identified by recording simultaneously from pairs of neurons using the whole cell configuration of the patch-clamp technique and testing for evoked postsynaptic current responses to electrical stimulation of one of the neurons. Excitatory and inhibitory responses were distinguished on the basis of their voltage and time dependence. The distribution of latencies between presynaptic stimulation and postsynaptic response showed multiple peaks at regular intervals, suggesting that responses via both monosynaptic and polysynaptic paths were recorded. The probability that an excitatory event is transmitted to another excitatory neuron and results in an above-threshold stimulation was found to be only one in three to four. This low value indicates that in addition to evoked synaptic responses other sources of excitatory drive must contribute to the spontaneous activity observed in these networks. The various types of synaptic connections (excitatory and inhibitory, monosynaptic, and polysynaptic) were counted, and the observations analyzed using a probabilistic model of the network structure. This analysis provides estimates for the ratio of inhibitory to excitatory neurons in the network (1:1.5) and for the ratio of postsynaptic cells receiving input from a single GABAergic or glutamatergic neuron (3:1). The total number of inhibitory synaptic connections was twice that of excitatory connections. Cell pairs mutually connected by an excitatory and an inhibitory synapse occurred significantly more often than predicted by a random process. These results suggests that the formation of neuronal networks in vitro is controlled by cellular mechanisms that favor inhibitory connections in general and specifically enhance the formation of reciprocal connections between pairs of excitatory and inhibitory neurons. These mechanisms may contribute to network formation and function in vivo.

Animals↗
PubMed2006

Cell adhesion molecules at the synapse.

Synapses are specialized intercellular junctions whose specificity and plasticity provide the structural and functional basis for the formation and maintenance of the complex neural network in the brain. The number, location, and type of synapses formed are well controlled, since synaptic circuits are formed in a highly reproducible way. This implies the existence of cellular and molecular properties that determine the connectivity of each neuron in the nervous system. Recent evidence has elucidated that these key features of the synapse are regulated by several families of cell-adhesion molecules (CAMs) enriched at synaptic junctions, including neuroligins, SynCAM, NCAM, L1-CAM, cadherins, protocadherins, and integrins. In this review we will discuss the various stages of synaptogenesis from the perspective of CAMs: Contact initiation, recruitment of presynaptic and postsynaptic proteins, synapse maturation/stabilization or elimination, and synaptic plasticity. We will also highlight some of the factors that regulate the function of these CAMs at the synapse, and discuss how dysfunction of these adhesive systems may contribute to several neurological disorders.

Cell Adhesion Molecules↗
PubMed2000

On the computational power of winner-take-all.

This article initiates a rigorous theoretical analysis of the computational power of circuits that employ modules for computing winner-take-all. Computational models that involve competitive stages have so far been neglected in computational complexity theory, although they are widely used in computational brain models, artificial neural networks, and analog VLSI. Our theoretical analysis shows that winner-take-all is a surprisingly powerful computational module in comparison with threshold gates (also referred to as McCulloch-Pitts neurons) and sigmoidal gates. We prove an optimal quadratic lower bound for computing winner-take-all in any feedforward circuit consisting of threshold gates. In addition we show that arbitrary continuous functions can be approximated by circuits employing a single soft winner-take-all gate as their only nonlinear operation. Our theoretical analysis also provides answers to two basic questions raised by neurophysiologists in view of the well-known asymmetry between excitatory and inhibitory connections in cortical circuits: how much computational power of neural networks is lost if only positive weights are employed in weighted sums and how much adaptive capability is lost if only the positive weights are subject to plasticity.

Animals↗
PubMed1996

Detection of ligands in regions anatomically connected to neurons expressing the Eph receptor Bsk: potential roles in neuron-target interaction.

Neuron-target interaction is a key feature in the establishment of neuronal networks. However, the underlying mechanism remains unclear. We have shown that at the time of target innervation, Bsk, an eph family receptor, is expressed at high levels in several brain regions including the hippocampus, olfactory bulb, and retina. To study whether the ligands are expressed in the target tissues, we investigated the expression of Bsk ligands using a ligand-affinity probe, Bsk-AP, which consisted of the extracellular domain of Bsk fused in frame with a human placental alkaline phosphatase. These analyses showed that the ligands were expressed at high levels in the developing septum, hypothalamus, olfactory neural epithelium, and tectum. In situ hybridization studies revealed that at least three different factors were responsible for the Bsk-AP binding. In the septum, Elf-1, Lerk3 (Eff-2), and AL-1/Lerk7 were transcribed. In the hypothalamus, AL-1/Lerk7 was the ligand detected by Bsk-AP. In the olfactory system, high levels of Lerk3 were detected in the sensory neurons. Both Elf-1 and AL-1/Lerk7 were present in the tectum. These ligand-positive areas are known to be anatomically connected to Bsk-expressing regions. These observations strongly suggest that Bsk and the ligands participate in neuron-target interactions in multiple systems and provide support for their involvement in topographic projection.

Alkaline Phosphatase↗
PubMed2005

The HVC microcircuit: the synaptic basis for interactions between song motor and vocal plasticity pathways.

Synaptic interactions between telencephalic neurons innervating descending motor or basal ganglia pathways are essential in the learning, planning, and execution of complex movements. Synaptic interactions within the songbird telencephalic nucleus HVC are implicated in motor and auditory activity associated with learned vocalizations. HVC contains projection neurons (PNs) (HVC(RA)) that innervate song premotor areas, other PNs (HVC(X)) that innervate a basal ganglia pathway necessary for vocal plasticity, and interneurons (HVC(INT)). During singing, HVC(RA) fire in temporally sparse bursts, possibly because of HVC(INT)-HVC(RA) interactions, and a corollary discharge can be detected in the basal ganglia pathway, likely because of synaptic transmission from HVC(RA) to HVC(X) cells. During song playback, local interactions, including inhibition onto HVC(X) cells, shape highly selective responses that distinguish HVC from its auditory afferents. To better understand the synaptic substrate for the motor and auditory properties of HVC, we made intracellular recordings from pairs of HVC neurons in adult male zebra finch brain slices and used spike-triggered averages to assess synaptic connectivity. A major synaptic interaction between the PNs was a disynaptic inhibition from HVC(RA) to HVC(X), which could link song motor signals in the two outputs of HVC and account for some of the song playback-evoked inhibition in HVC(X) cells. Furthermore, single interneurons made divergent connections onto PNs of both types, and either PN type could form reciprocal connections with interneurons. In these two regards, the synaptic architecture of HVC resembles that described in some pattern-generating networks, underscoring features likely to be important to singing and song learning.

2-Amino-5-phosphonovalerate↗
PubMed1994

Deviation in cerebral excitability: possible clinical implications.

Schizophrenia, a chemical signaling disorder in the brain, is also a deteriorating neurological disorder. The deficit in cerebral excitability, and associated reduced synaptic density, imply a risk of cortical breakdown of circuitry accompanied by an insufficient fill-in mechanism, and persistent silent spots, but no total loss of function, only dysfunction. This is subjectively experienced as deficiencies of cognition, perception and sensorimotor phenomena depending upon localization and connections of the disconnected circuitry. Considering the adversity inherent in this neural network, both the fast Hebbian pre-post form of learning and the slow pre-modulatory coincidence form of learning are probably impaired. The use of Feed Back Loops which usually govern our behaviour might also be impaired. In addition, we have to consider the daily problem of insufficient drive and motivation. Manic depressive psychosis, a chemical signaling disorder in the brain, is a true functional psychosis. The raised excitatory drive and raised synaptic density imply raised risk of uncoupling of circadian rhythms via the direct glutamatergic input to the suprachiasmatic nucleus of hypothalamus (SCN). This episodic brain stem dysfunction illustrates how a deficit in inhibition renders the brain unstable. The requirements of the fast Hebbian form of learning should easily be met, and neither should the slow forms of learning present a problem in networks characterized by excessive density.(ABSTRACT TRUNCATED AT 250 WORDS)

Cerebral Cortex↗
PubMed2000

Generic modeling of chemotactic based self-wiring of neural networks.

The proper functioning of the nervous system depends critically on the intricate network of synaptic connections that are generated during the system development. During the network formation, the growth cones migrate through the embryonic environment to their targets using chemical communication. A major obstacle in the elucidation of fundamental principles underlying this self-wiring is the complexity of the system being analyzed. Hence much effort is devoted to in vitro experiments of simpler (two-dimensional) 2D model systems. In these experiments neurons are placed on Poly-L-Lysine (PLL) surfaces, so it is easier to monitor their self-wiring. We developed a model to reproduce the salient features of the 2D systems, inspired by the study of the growth of bacterial colonies and the aggregation of amoebae. We represent the neurons (each composed of cell's soma, neurites and growth cones) by active elements that capture the generic features of the real neurons. The model also incorporates stationary units representing the cells' soma and communicating walkers representing the growth cones. The stationary units send neurites one at a time, and respond to chemical signaling. The walkers migrate in response to chemotaxis substances emitted by the soma and communicate with each other and with the soma by means of chemotactic "feedback". The interplay between the chemo-repulsive and chemo-attractive responses is determined by the dynamics of the walker's internal energy which is controlled by the soma. These features enable the neurons to perform the complex task of self-wiring. We present numerical experiments of the model to demonstrate its ability to form fine structures in simple networks of few neurons. Our results raise two fundamental issues: (1) one needs to develop characterization methods (beyond number of connections per neuron) to distinguish the various possible networks; (2) what are the relations between the network organization and its computational properties and efficiency?

Animals↗
PubMed1996

Brown-Séquard and cerebral localization as illustrated by his ideas on aphasia.

Brown-Séquard's concept of localization was built on the phenomena of inhibition and dynamogenesis, constituting a dynamic system in which reflex mechanisms, that played a part not only in the spinal cord but in the brain as well, were considered of particular importance. The use of this concept is considered in Brown-Séquard's discussion of the subject of cerebral localization, and especially of aphasia. The origin and development of Brown-Séquard's ideas on aphasia from 1861 onwards are discussed, as is the part he possibly played in the transfer of knowledge from Paris to London (Broca and Jackson). In the 1870's Brown-Séquard debated on cerebral localization with Charcot before the Société de Biologie. Opposing the cluster theory of localization, Brown-Séquard developed the theory of "réseau de cellules anastomosées", a kind of network theory in which scattered cells subserving the same function are connected by nerve fibers. This was to him a plausible theory, with which he was able to explain the fact that damage in several locations may produce the same effect, and, to account for observations that some functions remain unimpaired despite extensive brain-injury. Although Brown-Séquard's arguments were not always valid, because they were based on imprecise observations, his dynamic model, nowadays, seems valuable. He influenced "anti-localizers" such as Goltz, but also Jackson and probably Von Monakow and Sherrington.

Aphasia↗
PubMed2005

Parallel networks operating across attentional deployment and motion processing: a multi-seed partial least squares fMRI study.

Anticipatory deployment of attention may operate through networks of brain areas that modulate the representations of to-be-attended items in advance of their occurrence through top-down control. Luks and Simpson (2004) (Luks, T.L., Simpson, G.V., 2004. Preparatory deployment of attention to motion activates higher order motion-processing brain regions. NeuroImage 22, 1515-1522) found activations in both control areas and sensory areas during anticipatory deployment of attention to visual motion in the absence of stimuli. In the present follow-up analysis, we tested which network activity during anticipatory deployment of attention is functionally connected with task-related network activity during subsequent selective processing of motion stimuli. Following a cue (anticipatory phase), participants monitored a sequence of complex motion stimuli for a target motion pattern (task phase). We analyzed fMR signal using a partial least squares analysis with previously identified cue- and motion-related voxels as seed regions. The method identified two networks that covaried with the activity of seed regions during the cue and motion-stimulus-processing phases of the task. We suggest that the first network, involving ventral intraparietal sulcus, superior parietal lobule and motor areas, is related to anticipatory and sustained visuomotor attention. Operating in parallel to this visuomotor attention network, there is a second network, involving visual occipital areas, frontal areas as well as angular and supramarginal gyri, that may underlie anticipatory and sustained visual attention processes.

Adult↗
PubMed1994

An artificial neural network analogue of learning in autism.

An artificial neural network is simulated that shares formal qualitative similarities with the selective attention and generalization deficits seen in people with autism. The model is based on neuropathological studies which suggest that affected individuals have either too few or too many neuronal connections in various regions of the brain. In simulations where the model was taught to discriminate children with autism from children with mental retardation, having too few simulated neuronal connections led to relatively inferior discrimination of the two groups in a training set and, consequently, relatively inferior generalization of the discrimination to a novel test set. Too many connections produced excellent discrimination but inferior generalization because of overemphasis on details unique to the training set. It is concluded that, within the context of the current model, the neuropathological observations that have been described in the literature are sufficient to explain some of the unique pattern recognition and discrimination learning abilities seen in some people with autism as well as their problems with generalization and concept acquisition. The model generates testable hypotheses that have implications for understanding the pathogenesis, treatment, and phenomenology of autism.

Analysis of Variance↗