spatial power spectral density (PSD X), volume conduction

Properties of local synaptic connections in neocortex, studied with dual intracellular recordings in vitro and correlated with cell and synaptic morphology are summarized. The different durations and sensitivities to somatic membrane potential of pyramid–pyramid excitatory postsynaptic potentials (EPSPs) apparently reflect the positions of the synapses on the postsynaptic dendrites. Their time-, frequency- and voltage-dependent properties enable supra-linear summation of several low-frequency inputs arising in the same dendritic region, even if only loosely coincident, but they depress during repetitive firing in any one input. Pyramidal input to classical fast spiking and low threshold spiking interneurones are strikingly different. Here low presynaptic firing rates result in many transmission failures. EPSPs are brief and inputs must be near coincident for summation. However, these synapses display pronounced, frequency-dependent, incrementing facilitation at higher presynaptic frequencies. Once initiated by a brief high-frequency burst, this facilitation is maintained at lower frequencies. GABAA receptormediated inhibitory postsynaptic potentials (IPSPs) arising proximally are of very different durations depending on the type of interneurone activated and can prevent and subsequently synchronize firing in their many postsynaptic partners with very different delays (eg. 10–100 ms). Low threshold spiking interneurones, in contrast, generate brief IPSPs only in more distal dendritic regions and have little effect on somatic excitability, acting to shunt input distally.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder of cognitive function whose cellular pathology and molecular etiology have been increasingly and dramatically unraveled over the last several years. Despite this substantial knowledge base, the disease remains poorly understood due to a basic lack of understanding of how memories are stored and recalled in the brain. We describe a preliminary attempt at constructing a detailed model of these basic neural mechanisms; in particular, the natural dynamics of neuronal activity in hippocampal region CA3 and the modulation and control of these dynamics by subcortical cholinergic and GABAergic input to the hippocampus. We view the construction of such a model, with sufficient detail at the cellular and subcellular level, to be a necessary first step in understanding the effect of AD pathology on the functional behavior of the underlying neural circuitry. The network is based on the 66-compartment hippocampal pyramidal cell mo...

Most cognitive functions are based on highly parallel and distributed information processing by the brain. A paradigmatic example is provided by the vertebrate visual system where numerous cortical areas have been described which analyse different types of visual information. At present, it is unclear how information can be integrated and how coherent representational states can be established in such distributed systems. We suggest that this so-called ‘binding problem ’ may be solved in the temporal domain. The hypothesis is that synchronization of neuronal discharges can serve for the integration of distributed neurons into cell assemblies and that this process may underlie the selection of perceptually and behaviourally relevant information. We review experimental results, mainly obtained in the visual system, which support this temporal binding hypothesis.

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in hybrid neuronal networks of the hippocampal formation. J Neurophysiol 93: 1197–1208, 2005. First published November 3, 2004; doi:10.1152/jn.00982.2004. Understanding the mechanistic bases of neuronal synchronization is a current challenge in quantitative neuroscience. We studied this problem in two putative cellular pacemakers of the mammalian hippocampal theta rhythm: glutamatergic stellate cells (SCs) of the medial entorhinal cortex and GABAergic oriens-lacunosum-moleculare (O-LM) interneurons of hippocampal region CA1. We used two experimental methods. First, we measured changes in spike timing induced by artificial synaptic inputs applied to individual neurons. We then measured responses of free-running hybrid neuronal networks, consisting of biological neurons coupled (via dynamic clamp) to biological or virtual counterparts. Results from the single-cell experiments predicted network behaviors well and are compatible with previous model-based predictions

The electrical activity of neurons in brains fluctuates erratically both in terms of pulse trains of single neurons and the dendritic currents of populations of neurons. Obviously the neurons interact with one another in the production of intelligent behavior, so it is reasonable to expect to find evidence for varying degrees of synchronization of their pulse trains and dendritic currents in relation to behavior. However, synaptic communication between neurons depends on propagation of action potentials between neurons, often with appreciable distances between them, and the transmission delays are not compatible with synchronization in any simple way. Evidence is on hand showing that the principal form of synchrony is by establishment of a low degree of covariance among very large numbers of otherwise autonomous neurons, which allows for rapid state transitions of neural populations between successive chaotic basins of attraction along itinerant trajectories. The small fraction of covariant activity is extracted by spatial integration upon axonal transmission over divergent-convergent pathways, through which a remarkable improvement in signal:noise ratio is achieved. The raw traces of local activity show little evidence for synchrony, other than zero-lag correlation, which appears to be largely a statistical artifact. Brains rely less on tight phase-locking of small numbers of repetitively firing neurons and more on low degrees of cooperativity achieved by order parameters influencing very large numbers of neurons. Brains appear to be indifferent to and undisturbed by widely varying time and phase relations between individual neurons and even large semi-autonomous areas of cortex comprising their cooperative neural masses.

Object recognition might be achieved by the recreation of a meaningful internal image from visual fragments. This recreation might be achieved by neuronal synchronization that has been proposed as a solution for the perceptual binding problem. In this study, we evaluated synchronization between the occipitotemporal regions bilaterally using electroencephalograms during several visual recognition tasks. Conscious recognition of familiar objects spanning the visual midline induced transient interhemispheric electroencephalographic coherence Neuronal synchronization among the spatially distributed cortical visual areas has been proposed as the mechanism for integrating (perceptual binding) the parallel pathways that process the different features of visual objects (Eckhorn et al., 1988; Gray and Singer, 1989; Gray et al., 1989). Previous studies suggested that the coherence between neuronal activities is the physiologic correlate

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A brief review of oscillatory activity in neurons and networks is given. Conditions required for neural oscillations are provided. Three mathematical methods for studying the coupling between neural oscillators are described: (i) weak coupling, (ii) firing time maps, and (iii) leaky integrate-and-fire methods. Several applications from macroscopic motor behavior to slice phenomena are provided.