Stimulus-induced Synchronization Research Articles

Attractor dynamics in local neuronal networks

A hallmark feature of cortical networks is the presence of synaptic motifs, defined as ensembles of neurons whose synaptic pattern follows a particular configuration [1]. Simulated networks of neurons whose excitatory synapses follow a three-node motif (Figure ​(Figure1A)-the1A)-the most frequent motif in primate visual cortex- exhibit synchronization with zero time lag [2], a form of activity reported in a spectrum of experiments [3]. Here, using simulations of leaky integrate-and-fire networks (LIF) as well as mean-field stability analyses, we show that this relay motif promotes the emergence of a limit cycle whose period is determined by intrinsic properties of the model (Figure ​(Figure1B).1B). While cortical recordings show evidence of limit-cycle oscillations [4], this behavior is typically transient in non-pathological states. The question thus arises, of how to generate transient yet precise synchronization under different forms of motif connectivity. To address this question, we introduce a mechanism of selective gain inhibition by which cortical circuits may disengage from a strict limit cycle behavior. This mechanism works by tuning the gain inhibition [5] of a selective population of neurons in the model. In a first series of simulations, we show that applying selective gain inhibition to one population of a network (Figure ​(Figure1A,1A, shown in black) disengages the network from a limit cycle behaviour (Figure ​(Figure1C).1C). Next, we examine the effect of selective gain inhibition on a network's response to an incoming stimulus and show that transient synchronization arises in response to a time-delimited input current (Figure ​(Figure1D).1D). Selective gain inhibition enables stimulus-induced synchronization under strong stimulation and suppresses zero-lag synchrony under weak stimulation (Figure ​(Figure1E).1E). Transient synchronization would not be possible without selective gain inhibition, given that a network configured with a motif follows a limit cycle attractor (Figure ​(Figure1B).1B). We conclude that a relay' motif of connectivity imposes strict constraints on the types of dynamics produced by a network under both spontaneous and evoked states. Going further, results of simulations suggest that a mechanism of selective gain inhibition breaks the rigid constraints imposed by synaptic connectivity, providing flexible and transient responses to incoming stimuli. Figure 1 Transient synchronization in LIF networks. A. Three groups of neurons with arrows showing the presence of between-group synapses (1,000 neurons/group; gain inhibition set to 1.5 nS). B. Spike raster of spontaneous activity for network in A. C. Raster ...

Spatiotemporal properties of cortical haemodynamic response to auditory stimuli in sleeping infants revealed by multi-channel near-infrared spectroscopy

Multi-channel near-infrared spectroscopy (NIRS) has been used as a neuroimaging tool to study functional activation of the developing brain in infants. In this paper, we focus on spatiotemporal dynamics of cortical oxygenation changes during sensory processing in young infants. We use a 94-channel NIRS system to assess the activity of wide regions of the cortex in quietly sleeping three-month-old infants. Auditory stimuli composed of a random sequence of pure tones induced haemodynamic changes not only in the temporal auditory regions, but also in the occipital and frontal regions. Analyses of phase synchronization showed that mutual synchronizations of signal changes among the cortical regions were much stronger than the stimulus-induced synchronizations of signal changes. Furthermore, analyses of phase differences among cortical regions revealed phase advancement of the bilateral temporal auditory regions, and phase gradient in a posterior direction from the temporal auditory regions to the occipital regions and in an anterior direction within the frontal regions. We argue that multi-channel NIRS is capable of detecting the precise timing of cortical activation and its flow in the global network of the developing brain.

Pervasive synchronization of local neural networks in the secondary somatosensory cortex of cats during focal cutaneous stimulation.

Extracellular discharges were recorded from 205 neurons in the secondary somatosensory (SII) cortex of isoflurane-anesthetized cats. Cross-correlation analysis was used to characterize the temporal coordination of SII neurons recorded during cutaneous stimulation with a focal air jet that moved back-and-forth across the distal forelimb. Over two-thirds of the recorded neuron pairs ( n=357) displayed significant levels of synchronized activity during one or both directions of air-jet movement. The probability of detecting correlated activity varied according to the distance separating the neurons. Whereas synchronized responses were observed in 82.3% of the pairs in which the neurons were separated by 200-300 micro m, the incidence of synchronization declined to 52.3% for neurons that were separated by 600-800 micro m. The distance between neurons also had a significant effect on the temporal precision of correlated activity. For neurons that were separated by 200-300 micro m, synchronized responses in the cross-correlograms (CCGs) were characterized by narrow (0.5-1.0 ms) peaks at time zero. For SII neurons that were more widely separated, the peak half-widths were substantially broader and more likely to be displaced from time zero. Analysis of directional sensitivity indicated that only 14.2% of the correlated neurons displayed a directional preference for synchronized activity. By comparison, 63.4% of the neurons displayed a directional preference in their discharge rate. These results indicate that stimulus-induced synchronization is a prominent feature among local populations of SII neurons, but synchronization does not appear to play a critical role in coding the direction of stimulus movement. A comparison of these results with those obtained from similar experiments conducted in primary somatosensory (SI) cortex indicates that neuronal synchronization is more likely in SII cortex. This finding is discussed with respect to the known functional differences between the SI and SII cortical areas.

Distinct Gamma-Band Evoked Responses to Speech and Non-Speech Sounds in Humans

To understand spoken language, the human brain must have fast mechanisms for the representation and identification of speech sounds. Stimulus-induced synchronization of neural activity at gamma frequencies (20-80 Hz), occurring in humans at 200-300 msec from stimulus onset, has been suggested to be a possible mechanism for neural object representation. Auditory and visual stimuli also evoke an earlier (peak <100 msec) gamma oscillation, but its dependence on high-level stimulus parameters and, thereby, its involvement in object representation has remained unclear. Using whole-scalp magnetoencephalography, we show here that responses evoked by speech and non-speech sounds differed in the gamma-frequency but not in the low-frequency (0.1-20 Hz) band as early as 40-60 msec from stimulus onset. The gamma-band responses to the speech sound peaked earlier in the left than in the right hemisphere, whereas those to the non-speech sound peaked earlier in the right hemisphere. For the speech sound, there was no difference in the response amplitude between the hemispheres at low (20-45 Hz) gamma frequencies, whereas for the non-speech sound, the amplitude was larger in the right hemisphere. These results suggest that evoked gamma-band activity may indeed be sensitive to high-level stimulus properties and may hence reflect the neural representation of speech sounds. Consequently, speech-specific neuronal processing may commence no later than 40-60 msec from stimulus onset, possibly in the form of activation of language-specific memory traces.

Cognition, Gamma Oscillations and Neuronal Synchrony

Neuroanatomical and electrophysiological evidence emphasizes the distributed nature of brain processes. There is no single convergence center in the brain for the representation of the final results of cognitive operations and for the coordination of executive functions. This raises the question how the numerous, simultaneously occurring subprocesses are bound together in order to permit coherent interpretations ofpolymodal sensory signals and coordination of adapted behaviour. At a smaller scale the same problems arise in sensory processing and motor coordination because representations of perceptual objects and movements appear to consist of ensembles of widely distributed interacting neurons rather than of individual, object-specific cells and movement specific command neurons (1). Following the discovery of stimulus-induced synchronization and oscillatory patterning of sensory responses in the visual cortex (2) it has been suggested that binding of distributed responses into coherent representations is achieved by precise synchronization of neuronal responses. Since then numerous experiments in anesthetized and awake animals have shown that this synchronization results from cooperative interactions among selectively coupled cortical neurons and changes in a context-dependent way. Evidence indicates that synchronization correlates with feature binding in sensory processing, with shifts in attention and with the preparation and execution of movements, suggesting that it serves as a general mechanism for the definition of functional relations among distributed neuronal responses. A conspicuous feature of these processing related synchronization phenomena is that they very often go along with an oscillatory patterning of the synchronized neuronal discharges in the betaand gamma-frequency range (20 60 Hz), in particular when synchronization is established over larger distances. This suggests that oscillatory patterning supports the establishment of precise temporal relations among neuronal responses. Fortunately, these synchronization phenomena are sufficiently robust so that epochs of synchronized oscillatory activity can be detected in EEG and MEG recordings that average over large populations of neurons. This permitted examination of hypotheses derived from animal experiments in human subjects. Evidence accumulated over the past years suggests close relations between the occurrence and interareal coherence of gamma oscillations on the one hand and a variety of cognitive processes on the other. These processes include feature binding, sensory-motor coordination, target selection by attention, short-term memory and associative learning, suggesting again that synchronization processes in the gamma frequency range play an important and rather general role in the coordination of distributed processes in the brain.

Precisely timed transient synchronization by depressing synapses

We study the dynamical effects of depressing synapses on stimulus-induced synchronization in a simple network of inhibitory and excitatory neurons, assuming that the recurrent excitation is mediated by depressing synapses. It is demonstrated that depressing synapses greatly contribute to suppressing the influences of noise in afferent stimuli on the stimulus-specific temporal patterns of synchronous firing. In cooperation with synaptic depression, the timing-based Hebbian learning suggested by physiological experiments improves the stability of the temporal patterns. Thus, the times at which synchronous firing occurs can be a reliable information career in the presence of synaptic depression.

Neural dynamics modelled by one-dimensional circle maps

The single Bonhoeffer-van der Pol (BvP) neuron, driven by a sinusodial external stimulus shows periodic, quasiperiodic and chaotic states. Frequency-lockings, followed by period doubling cascades to chaos, suggest a relation to the universal behaviour of one-dimensional circle maps. We present a method to describe the membrane potential activity of single neurons with a circle map. Furthermore, we show that this equivalence can be found in networks of coupled BvP elements. In dependence of the interaction strength we always observe a region, where a stimulus-induced synchronization can be understood in terms of coupled one-dimensional circle maps.