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. 2009 Jul 30:3:17.
doi: 10.3389/neuro.07.017.2009. eCollection 2009.

Neural synchrony in cortical networks: history, concept and current status

Peter J Uhlhaas  1 , Gordon Pipa, Bruss Lima, Lucia Melloni, Sergio Neuenschwander, Danko Nikolić, Wolf Singer
Affiliations

Neural synchrony in cortical networks: history, concept and current status

Peter J Uhlhaas et al. Front Integr Neurosci. .

Abstract

Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, the role of neural synchrony in cortical networks has been expanded to provide a general mechanism for the coordination of distributed neural activity patterns. In the current paper, we present an update of the status of this hypothesis through summarizing recent results from our laboratory that suggest important new insights regarding the mechanisms, function and relevance of this phenomenon. In the first part, we present recent results derived from animal experiments and mathematical simulations that provide novel explanations and mechanisms for zero and nero-zero phase lag synchronization. In the second part, we shall discuss the role of neural synchrony for expectancy during perceptual organization and its role in conscious experience. This will be followed by evidence that indicates that in addition to supporting conscious cognition, neural synchrony is abnormal in major brain disorders, such as schizophrenia and autism spectrum disorders. We conclude this paper with suggestions for further research as well as with critical issues that need to be addressed in future studies.

Keywords: cognition; cortex; gamma; oscillations; synchrony.

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Figures

Figure 1
Figure 1
Dynamics of three networks of excitatory and inhibitory neurons interacting through dynamical relaying. (A) Topology of the relaying motif. Here, three networks 1, 2, 3 each composed of 20 inhibitory (red) and 80 excitatory (blue) neurons. To control the activity level of each population external Poisson input is used (grey spikes). The conductions delays are 12 ms and therefore significant compared to the period of the oscillation. (B) Raster plot of the activity of each neuron of population 1 (neurons 1–100), population 2 (neurons 101–200) and population 3 (neurons 201–300). Blue spikes are from the excitatory and red spike from the inhibitory neurons. At coupling ton at 100 ms the coupling between the populations was activated. After 90 ms of activated coupling P1 and P3 start being zero-phase synchronized. The whole synchronization period lasts about 130 ms. Note that the activity of the relaying population P2, gets less synchronized due to individual phase adaptations of P2 neurons during the synchronization period between 160 and 230 ms. This indicates that the relaying population P2 is not acting as a master that entrains P1 and P3, but that synchronization is established between P1 and P3 via relaying of activity through P2. (C) Average cross-correlation between population P1 or P3 and the relaying population P2. (D) Average cross correlation between the outer populations P1 and P3.
Figure 2
Figure 2
Detection and comparison of neuronal firing sequences and the relationship between psychophysical measurements and strength of synchrony. (A) An example cross-correlogram (CCH) that indicates a shifted centre peak. The magnitude of shift is estimated by fitting a Gabor function. (B) An apparently complex network of the directions (arrows) and the magnitudes of phase offsets (in milliseconds) extracted from all possible pair-wise CCHs as in (A). The arrangements of the units within the 4 × 4 matrices reflect the spatial positions of the recording sites on the 16-channel recording probes. The delays are segregated into two panels because otherwise the representation would be overcrowded. The upper panel indicates only the delays between the pairs of units that preferred similar stimulus orientations and the lower panel between the pairs that preferred different stimulus orientations. The orientations of the corresponding receptive fields are schematized on the far left and the bar stimulus illustrated on the top. (C) Excerpt from (B) indicating a case of additivity across three units precise to two-tenths of a millisecond. (D) For the example in (C), the extraction of the relative firing sequence is illustrated. (E) Graphical presentation of the results in (D). (F) Examples four-unit networks with transitive (black) and non-transitive (red) directions of delays in CCHs. Adapted from Nikolić (2007).
Figure 3
Figure 3
(A) A firing sequence extracted for a network of 14 units. The dots denote the estimated positions of the units, the number their identities, and the black curves indicate the localization errors. (B) The relative firing sequence in (A) estimated for two repetitions of the same stimuli. Gray lines parallel to the diagonal indicate error limits of two standard deviations. Unit identities are indicated on the right side of the panel. (C) Changes in firing sequences as a function of a change in stimulus properties. Stimuli are sketched in the corners of the graph. Units outside the error lines change significantly their preferred firing times. Adapted from Schneider et al. (2006).
Figure 4
Figure 4
The role of synchrony for perception of brightness. (A) In the two centre-surround stimuli, the gratings in the centre are physical identical. Nevertheless, most observers report seeing stronger contrast on the right where the centre is offset for 180° relative to the surround. (B) Experimental results obtained with stimuli shown in (A). Red: Human psychophysical judgments of changes in perceived contrast as a function of phase offset between the centre and surround. Blue: Changes in the strength of synchronization between neurons in cat area 17 whose receptive fields were covered by the centre stimuli and whose orientation preferences matched the orientation of the grating. Adapted from Biederlack et al. (2006).
Figure 5
Figure 5
Perceptual readiness modulates gamma power in V1 of the monkey. (A) Average response histogram for a single cell to a Gabor element centered over its receptive field. The orientation of the Gabor element changes at 400 ms steps. Notice the strong responses for the epochs of orientation match. Analysis windows are indicated by the shadowed rectangles on the plot. Direction tuning is shown on the left. Spontaneous activity is represented by the central circle, maximum average rate is indicated at the bottom right of the plot. (B) Sliding window autocorrelation for the responses shown above. Plots are aligned in time. Autocorrelation functions were computed for 200 ms windows at steps of 50 ms. (C) Corresponding power spectra obtained for the local field potential (LFP) and spiking activity recorded from the same electrode. Thin line: window of match in the middle of the trial. Thick line: window of match prior to the behavioral response (in this example, coincides with the appearance of the embedded figure). Multitaper spectral analysis was obtained using the Chronux analysis software. Power was normalized by the firing rate. Thin lines around the mean indicate 95% confidence intervals.
Figure 6
Figure 6
Spectral power and phase synchrony to visible and invisible words. Words were flashed for 33 ms and surrounded by masks that depending on their luminance rendered the stimuli either visible or invisible. After around 500 ms a second word was presented and subjects had to determine whether it was the same or different from the previously presented word. (A) Time-frequency plot and (B) Phase synchrony plot shows the grand average for all the electrode pairs. White lines depict the time when the first and second word were presented. Color scale corresponds to amplitude expressed in SD, calculated over a 500-ms baseline. (A) Time-frequency plot: Two increments in gamma oscillations are visible. The first, only present in the visible condition, the second in both conditions. (B) Phase locked synchrony: The first peak is only present during the visible condition, whereas the second one is observed for both conditions.
Figure 7
Figure 7
(A) An upright image of a Mooney face and an inverted version of the same image. (B) Behavioral data for chronic patients with schizophrenia (N = 17) and matched healthy controls (N = 17); detection rates in percent (left) and reactions times (right). (C) Normalized evoked and induced spectral power for correct responses to upright Mooney faces in the frequency range 25–200 Hz over parietal sensors; Top: normal controls, Bottom: patients with schizophrenia. (D) Time course for gamma-power (60-120 Hz) for parietal sensors during the perception of upright Mooney faces (red: schizophrenia patients; black: controls).
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