Synchronous oscillatory activity in sensory systems: new vistas on mechanisms

Ritz, Raphael; Sejnowski, Terrence J.

doi:10.1016/s0959-4388(97)80034-7

Cited by 163 publications

(77 citation statements)

References 92 publications

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“…Cortical structures have a wide range of intrinsic mechanisms that could generate synchronous activity 75 . Inhibitory interneurons might be particularly important.…”

Section: How Neurons Generate Rhythmic Activitymentioning

confidence: 99%

Correlated neuronal activity and the flow of neural information

Salinas¹,

Sejnowski²

2001

Nat Rev Neurosci

1,201

902

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For years we have known that cortical neurons collectively have synchronous or oscillatory patterns of activity, the frequencies and temporal dynamics of which are associated with distinct behavioural states. Although the function of these oscillations has remained obscure, recent experimental and theoretical results indicate that correlated fluctuations might be important for cortical processes, such as attention, that control the flow of information in the brain.Research in systems neuroscience has traditionally focused on how neurons represent the world and on the mechanisms that endow neurons with their response properties or receptive fields. However, an equally important, but less well understood, aspect of brain function is how neurons communicate. For instance, the presence of a red light in the visual field might be irrelevant if in a theatre, but crucial if about to cross a road. The neural representation of the red light might be, at some level, the same in the two situations, but this information is then redirected and prioritized in totally different ways. Little is known about how, depending on the current behavioural requirements, neural signals are routed or assessed in the nervous system. There is evidence that timing is crucial: a recent study 1 showed that whether intracortical microstimulation influences performance in a sensory discrimination task depends on the time at which the microinjected current is delivered relative to the natural stimulus onset. This indicates that even a simple discrimination paradigm is executed according to an internal schedule, such that the information provided by the sensory neurons is effectively transmitted only during a certain time window. So, the temporal dynamics of neuronal interactions seem to be important for the gating processes that control the information that goes through at a given time.On the other hand, networks of neurons show highly complex temporal dynamics. It is well known from electroencephalographic studies 2 that the small voltage signals recorded from the scalp fluctuate at various frequencies, with dominant frequency components shifting according to behaviour. Slow oscillations with a strong 0.75-4-Hz component are associated with certain stages of sleep, whereas oscillations dominated by the 14-40-Hz band are typical of active, awake states 3,4 . Direct measurement of field potentials from the cortex reveals even higherfrequency components in the 40-200-Hz range 5 . At the single-neuron level, collective oscillations in cortical neurons have been documented for several years [6][7][8] . One functional interpretation is that this rhythmic behaviour is, again, related to higher-order sensory representations, but this idea continues to be hotly debated 9,10 . The problem is not that oscillations are not there, but that linking them to behaviour has been difficult.

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“…Cortical structures have a wide range of intrinsic mechanisms that could generate synchronous activity 75 . Inhibitory interneurons might be particularly important.…”

Section: How Neurons Generate Rhythmic Activitymentioning

confidence: 99%

Correlated neuronal activity and the flow of neural information

Salinas¹,

Sejnowski²

2001

Nat Rev Neurosci

1,201

902

View full text Add to dashboard Cite

show abstract

“…In the model of Lisman and Idiart (1995), it is proposed that slow brain rhythms (e.g., theta and alpha) mediate the construction of discrete representations, the content of which would be fleshed out by faster rhythms (see also Ritz and Sejnowski, 1997). Such interactions between slow and fast brain rhythms have been proposed to reflect brain mechanisms that are global (to link distinct brain regions), quasi-periodic (i.e., with an active and an inactive phase) and flexibly adjustable (to adapt their period and amplitudes to constraints, both internal and external, Van Rullen and Koch, 2003).…”

Section: Functional Interpretation Of Information State Transitionsmentioning

confidence: 99%

From a face to its category via a few information processing states in the brain

2007

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Cognitive neuroscience assumes a correspondence between specific spatio-temporal patterns of neural activity and the states of a mechanism that processes cognitive information. Mechanistic explanations of cognition should therefore translate patterns of neural activity into the components of a formal mechanism: a set of information processing states and their transitions. For the first time, we carried out this research programme with four naive observers instructed to categorise randomly presented face information. With classification image techniques, we revealed the diagnostic features that the brain requires to produce correct behaviour (i.e., two eyes for gender categorisation in one session; the mouth for expression in the other session). With the same techniques applied to brain signals, we revealed the features processing states associated with modulations of oscillatory EEG energy (measured on occipito-temporal face-sensitive electrodes). Here we show how transitions between distinct feature processing states in the theta/alpha [4-12 Hz] oscillatory bands implement two face categorisations. On the left and right occipito-temporal electrodes of each observer, processing of the contra-lateral eye precedes bilateral integration of the features required for behaviour. For the first time, we relate stimulus information to behaviour via sequences of categorisation-specific feature processing states in the brain. © 2007 Elsevier Inc. All rights reserved.To study face categorisation mechanisms in an information system such as the brain, automata theory (Hopcroft and Ullman, 1979) specifies three generic questions that must be addressed to relate brain activity to the states of an information processing mechanism (i.e., a formal automaton). The first question is that of form: what is the nature of the brain activity supporting face processing-i.e., the states of the brain correlated with face processing? The second question is that of content: what is the information content processed in these brain states? The third question is that of transition: how does information flow from one brain state to the next between stimulus onset and behavioural response? So far, cognitive neuroimaging studies have not simultaneously addressed these three questions. Until this is resolved, inferences about cognitive information processing mechanisms will be severely restricted.To illustrate the problem, researchers have proposed that slow brain rhythms could form distinct states of information processing, on the basis of considerable evidence of a consistent relationship between low frequency, theta (4-8 Hz) and alpha (8-12 Hz), oscillatory EEG activity of the neural substrate and behavioural variables (Van Rullen and Koch, 2003;Ward, 2003, for reviews). However, definitive evidence is lacking in part because it has been proven difficult to identify precisely the information content of these states from the parametric modulations (i.e., phase and amplitude) of slow brain rhythms. Consequently, little is known about the detailed f...

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“…These oscillations are thought to provide temporally and spatially coherent clock signals for temporal encoding of information in principal neuron ensembles (for review, see Buzsáki and Chrobak, 1995;Ritz and Sejnowski, 1997;Traub et al, 1999). Although theta frequency oscillations are driven by septal and entorhinal inputs, gamma oscillations are thought to be generated intrinsically.…”

Section: Abstract: Gabaergic Interneurons; Basket Cells; Dentate Gyrmentioning

confidence: 99%

Rapid Signaling at Inhibitory Synapses in a Dentate Gyrus Interneuron Network

Bartos¹,

et al. 2001

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Mutual synaptic interactions between GABAergic interneurons are thought to be of critical importance for the generation of network oscillations and for temporal encoding of information in the hippocampus. However, the functional properties of synaptic transmission between hippocampal interneurons are largely unknown. We have made paired recordings from basket cells (BCs) in the dentate gyrus of rat hippocampal slices, followed by correlated light and electron microscopical analysis. Unitary GABA A receptor-mediated IPSCs at BC-BC synapses recorded at the soma showed a fast rise and decay, with a mean decay time constant of 2.5 Ϯ 0.2 msec (32°C). Synaptic transmission at BC-BC synapses showed paired-pulse depression (PPD) (32 Ϯ 5% for 10 msec interpulse intervals) and multiple-pulse depression during repetitive stimulation. Detailed passive cable model simulations based on somatodendritic morphology and localization of synaptic contacts further indicated that the conductance change at the postsynaptic site was even faster, decaying with a mean time constant of 1.8 Ϯ 0.6 msec. Sequential triple recordings revealed that the decay time course of IPSCs at BC-BC synapses was approximately twofold faster than that at BC-granule cell synapses, whereas the extent of PPD was comparable. To examine the consequences of the fast postsynaptic conductance change for the generation of oscillatory activity, we developed a computational model of an interneuron network. The model showed robust oscillations at frequencies Ͼ60 Hz if the excitatory drive was sufficiently large. Thus the fast conductance change at interneuron-interneuron synapses may promote the generation of high-frequency oscillations observed in the dentate gyrus in vivo.

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Synchronous oscillatory activity in sensory systems: new vistas on mechanisms

Cited by 163 publications

References 92 publications

Correlated neuronal activity and the flow of neural information

Correlated neuronal activity and the flow of neural information

From a face to its category via a few information processing states in the brain

Rapid Signaling at Inhibitory Synapses in a Dentate Gyrus Interneuron Network

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