Bruss Lima

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

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.

Gamma-Phase Shifting in Awake Monkey Visual Cortex

Gamma-band synchronization is abundant in nervous systems. Typically, the strength or precision of gamma-band synchronization is studied. However, the precise phase with which individual neurons are synchronized to the gamma-band rhythm might have interesting consequences for their impact on further processing and for spike timing-dependent plasticity. Therefore, we investigated whether the spike times of individual neurons shift systematically in the gamma cycle as a function of the neuronal activation strength. We found that stronger neuronal activation leads to spikes earlier in the gamma cycle, i.e., we observed gamma-phase shifting. Gamma-phase shifting occurred on very rapid timescales. It was particularly pronounced for periods in which gamma-band synchronization was relatively weak and for neurons that were only weakly coupled to the gamma rhythm. We suggest that gamma-phase shifting is brought about by an interplay between overall excitation and gamma-rhythmic synaptic input and has interesting consequences for neuronal coding, competition, and plasticity.

Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect?

The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting generalized linear models on the neural responses, incorporating effects of the neurons’ self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks’ observed small-world ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings.

Synchronization Dynamics in Response to Plaid Stimuli in Monkey V1

Gamma synchronization has generally been associated with grouping processes in the visual system. Here, we examine in monkey V1 whether gamma oscillations play a functional role in segmenting surfaces of plaid stimuli. Local field potentials (LFPs) and spiking activity were recorded simultaneously from multiple sites in the opercular and calcarine regions while the monkeys were presented with sequences of single and superimposed components of plaid stimuli. In accord with the previous studies, responses to the single components (gratings) exhibited strong and sustained gamma-band oscillations (30–65 Hz). The superposition of the second component, however, led to profound changes in the temporal structure of the responses, characterized by a drastic reduction of gamma oscillations in the spiking activity and systematic shifts to higher frequencies in the LFP (∼10% increase). Comparisons between cerebral hemispheres and across monkeys revealed robust subject-specific spectral signatures. A possible interpretation of our results may be that single gratings induce strong cooperative interactions among populations of cells that share similar response properties, whereas plaids lead to competition. Overall, our results suggest that the functional architecture of the cortex is a major determinant of the neuronal synchronization dynamics in V1.

Orientation selectivity and noise correlation in awake monkey area V1 are modulated by the gamma cycle

Gamma-band synchronization adjusts the timing of excitatory and inhibitory inputs to a neuron. Neurons in the visual cortex are selective for stimulus orientation because of dynamic interactions between excitatory and inhibitory inputs. We hypothesized that these interactions and hence also orientation selectivity vary during the gamma cycle. We determined for each spike its phase relative to the gamma cycle. As a function of gamma phase, we then determined spike rates and their orientation selectivity. Orientation selectivity was modulated by gamma phase. The firing rate of spiking activity that occurred close to a neurons mean gamma phase of firing was most orientation selective. This stimulus-selective signal could best be conveyed to postsynaptic neurons if it were not corrupted by noise correlations. Noise correlations between firing rates were modulated by gamma phase such that they were not statistically detectable for the spiking activity occurring close to a neurons mean gamma phase of firing. Thus, gamma-band synchronization produces spiking activity that carries maximal stimulus selectivity and minimal noise correlation in its firing rate, and at the same time synchronizes this spiking activity for maximal impact on postsynaptic targets.

Gamma Responses Correlate with Temporal Expectation in Monkey Primary Visual Cortex

Gamma oscillations have been linked to selective attention. Here, we investigate the effects of expecting a behaviorally relevant event (a change in the fixation point) on the oscillatory patterning of the local field potential and spiking responses in V1. Three protocols were used. In the first protocol, fixation point change occurred at a fixed time point, enabling predictions on task timing. In the second, fixation point change occurred in trial blocks either early or late in the trial, allowing us to compare responses during epochs of low and high expectation. Finally, we used a cue to indicate the upcoming fixation point change. All protocols led to an increase in gamma oscillations associated with alpha suppression when the monkeys expected an event in time. These effects were spatially widespread, since comparable results were observed for both central and peripheral visual representations in V1. Our findings indicate that expectations associated with perceptual decisions, motor responses, or upcoming reward may have a strong effect on the primary visual cortex, causing global, spatially nonselective modulation of gamma activity.

Directional responses of visual wulst neurones to grating and plaid patterns in the awake owl

The avian retinothalamofugal pathway reaches the telencephalon in an area known as visual wulst. A close functional analogy between this area and the early visual cortex of mammals has been established in owls. The goal of the present study was to assess quantitatively the directional selectivity and motion integration capability of visual wulst neurones, aspects that have not been previously investigated. We recorded extracellularly from a total of 101 cells in awake burrowing owls. From this sample, 88% of the units exhibited modulated directional responses to sinusoidal gratings, with a mean direction index of 0.74 ± 0.03 and tuning bandwidth of 28 ± 1.16°. A direction index higher than 0.5 was observed in 66% of the cells, thereby qualifying them as direction selective. Motion integration was tested with moving plaids, made by adding two sinusoidal gratings of different orientations. We found that 80% of direction‐selective cells responded optimally to the motion direction of the component gratings, whereas none responded to the global motion of plaids, whose direction was intermediate to that of the gratings. The remaining 20% were unclassifiable. The strength of component motion selectivity rapidly increased over a 200 ms period following stimulus onset, maintaining a relatively sustained profile thereafter. Overall, our data suggest that, as in the mammalian primary visual cortex, the visual wulst neurones of owls signal the local orientated features of a moving object. How and where these potentially ambiguous signals are integrated in the owl brain might be important for understanding the mechanisms underlying global motion perception.

Context Matters: The Illusive Simplicity of Macaque V1 Receptive Fields

Even in V1, where neurons have well characterized classical receptive fields (CRFs), it has been difficult to deduce which features of natural scenes stimuli they actually respond to. Forward models based upon CRF stimuli have had limited success in predicting the response of V1 neurons to natural scenes. As natural scenes exhibit complex spatial and temporal correlations, this could be due to surround effects that modulate the sensitivity of the CRF. Here, instead of attempting a forward model, we quantify the importance of the natural scenes surround for awake macaque monkeys by modeling it non-parametrically. We also quantify the influence of two forms of trial to trial variability. The first is related to the neuron’s own spike history. The second is related to ongoing mean field population activity reflected by the local field potential (LFP). We find that the surround produces strong temporal modulations in the firing rate that can be both suppressive and facilitative. Further, the LFP is found to induce a precise timing in spikes, which tend to be temporally localized on sharp LFP transients in the gamma frequency range. Using the pseudo R2 as a measure of model fit, we find that during natural scene viewing the CRF dominates, accounting for 60% of the fit, but that taken collectively the surround, spike history and LFP are almost as important, accounting for 40%. However, overall only a small proportion of V1 spiking statistics could be explained (R2∼5%), even when the full stimulus, spike history and LFP were taken into account. This suggests that under natural scene conditions, the dominant influence on V1 neurons is not the stimulus, nor the mean field dynamics of the LFP, but the complex, incoherent dynamics of the network in which neurons are embedded.

Mapping of visual receptive fields by tomographic reconstruction

The moving bar experiment is a classic paradigm for characterizing the receptive field (RF) properties of neurons in primary visual cortex (V1). Current approaches for analyzing neural spiking activity recorded from these experiments do not take into account the point-process nature of these data and the circular geometry of the stimulus presentation. We present a novel analysis approach to mapping V1 receptive fields that combines point-process generalized linear models (PPGLM) with tomographic reconstruction computed by filtered-back projection. We use the method to map the RF sizes and orientations of 251 V1 neurons recorded from two macaque monkeys during a moving bar experiment. Our cross-validated goodness-of-fit analyses show that the PPGLM provides a more accurate characterization of spike train data than analyses based on rate functions computed by the methods of spike-triggered averages or first-order Wiener-Volterra kernel. Our analysis leads to a new definition of RF size as the spatial area over which the spiking activity is significantly greater than baseline activity. Our approach yields larger RF sizes and sharper orientation tuning estimates. The tomographic reconstruction paradigm further suggests an efficient approach to choosing the number of directions and the number of trials per direction in designing moving bar experiments. Our results demonstrate that standard tomographic principles for image reconstruction can be adapted to characterize V1 RFs and that two fundamental properties, size and orientation, may be substantially different from what is currently reported.

Two frequency bands contain the most stimulus-related information in visual cortex

Sensory cortices represent the world through the activity of diversely tuned cells. How the activity of single cells is coordinated within populations and across sensory hierarchies is largely unknown. Cortical oscillations may coordinate local and distributed neuronal groups. Using datasets from intracortical multi-electrode recordings and from large-scale electrocorticography (ECoG) grids, we investigated how visual features could be extracted from the local field potential (LFP) and how this compared with the information available from multi-unit activity (MUA). MUA recorded from macaque V1 contained comparable amounts of information as simultaneously recorded LFP power in two frequency bands, one in the alpha-beta band and the other in the gamma band. ECoG-LFP contained information in the same bands as microelectrode-LFP, even when identifying natural scenes. The fact that information was contained in the same bands in both intracortical and ECoG recordings suggests that oscillatory activity could play similar roles at both spatial scales.