Predictive visuo-motor communication through neural oscillations

The mechanisms coordinating action and perception over time are poorly understood. The sensory cortex needs to prepare for upcoming changes contingent on action, and this requires temporally precise communication that takes into account the variable delays between sensory and motor processing. Several theorists^1,2 have proposed synchronization of the endogenous oscillatory activity observed in most regions of the brain³ as the basis for an efficient and flexible communication protocol between distal brain areas,^2,4 a concept known as "communication through coherence." Synchronization of endogenous oscillations^5,6 occurs after a salient sensory stimulus, such as a flash or a sound,^7-11 and after a voluntary action,^12-18 and this directly impacts perception, causing performance to oscillate rhythmically over time. Here we introduce a novel fMRI paradigm to probe the neural sources of oscillations, based on the concept of perturbative signals, which overcomes the low temporal resolution of BOLD signals. The assumption is that a synchronized endogenous rhythm will modulate cortical excitability rhythmically, which should be reflected in the BOLD responses to brief stimuli presented at different phases of the oscillation cycle. We record rhythmic oscillations of V1 BOLD synchronized by a simple voluntary action, in phase with behaviorally measured oscillations in visual sensitivity in the theta range. The functional connectivity between V1 and M1 also oscillates at the same rhythm. By demonstrating oscillatory temporal coupling between primary motor and sensory cortices, our results strongly implicate communication through coherence to achieve precise coordination and to encode sensory-motor timing.

Principles of Corticocortical Communication: Proposed Schemes and Design Considerations

Nearly all brain functions involve routing neural activity among a distributed network of areas. Understanding this routing requires more than a description of interareal anatomical connectivity: it requires understanding what controls the flow of signals through interareal circuitry and how this communication might be modulated to allow flexible behavior. Here we review proposals of how communication, particularly between visual cortical areas, is instantiated and modulated, highlighting recent work that offers new perspectives. We suggest transitioning from a focus on assessing changes in the strength of interareal interactions, as often seen in studies of interareal communication, to a broader consideration of how different signaling schemes might contribute to computation. To this end, we discuss a set of features that might be desirable for a communication scheme.

Motor Cortex Inputs at the Optimum Phase of Beta Cortical Oscillations Undergo More Rapid and Less Variable Corticospinal Propagation

Brain oscillations involve rhythmic fluctuations of neuronal excitability and may play a crucial role in neural communication. The human corticomuscular system is characterized by beta activity and is readily probed by transcranial magnetic stimulation (TMS). TMS inputs arriving at the excitable phase of beta oscillations in the motor cortex are known to lead to muscle responses of greater amplitude. Here we explore two other possible manifestations of rhythmic excitability in the beta band; windows of reduced response variability and shortened latency. We delivered single-pulse TMS to the motor cortex of healthy human volunteers (10 females and 7 males) during electroencephalography recordings made at rest. TMS delivered at a particular phase of the beta oscillation benefited from not only stronger, but also less variable and more rapid transmission, as evidenced by the greater amplitude, lower coefficient of variation, and shorter latency of motor evoked potentials. Thus, inputs aligned to the optimal phase of the beta EEG in the motor cortex enjoy transmission amplitude gain, but may also benefit from less variability and shortened latencies at subsequent synapses. Neuronal phase may therefore impact corticospinal communication.SIGNIFICANCE STATEMENT Brain oscillations involve rhythmic fluctuations of neuronal excitability. Therefore, motor responses to transcranial magnetic stimulation are larger when a cortical input arrives at a particular phase of the beta activity in the motor cortex. Here, we demonstrate that inputs to corticospinal neurons which coincide with windows of higher excitability also benefit from more rapid and less variable corticospinal transmission. This shortening of latency and increased reproducibility may confer additional advantage to inputs at specific phases. Moreover, these benefits are conserved despite appreciable corticospinal conduction delays.

Phase Synchronicity of μ-Rhythm Determines Efficacy of Interhemispheric Communication Between Human Motor Cortices

The theory of communication through coherence predicts that effective connectivity between nodes in a distributed oscillating neuronal network depends on their instantaneous excitability state and phase synchronicity (Fries, 2005). Here, we tested this prediction by using state-dependent millisecond-resolved real-time electroencephalography-triggered dual-coil transcranial magnetic stimulation (EEG-TMS) (Zrenner et al., 2018) to target the EEG-negative (high-excitability state) versus EEG-positive peak (low-excitability state) of the sensorimotor μ-rhythm in the left (conditioning) and right (test) motor cortex (M1) of 16 healthy human subjects (9 female, 7 male). Effective connectivity was tested by short-interval interhemispheric inhibition (SIHI); that is, the inhibitory effect of the conditioning TMS pulse given 10-12 ms before the test pulse on the test motor-evoked potential. We compared the four possible combinations of excitability states (negative peak, positive peak) and phase relations (in-phase, out-of-phase) of the μ-rhythm in the conditioning and test M1 and a random phase condition. Strongest SIHI was found when the two M1 were in phase for the high-excitability state (negative peak of the μ-rhythm), whereas the weakest SIHI occurred when they were out of phase and the conditioning M1 was in the low-excitability state (positive peak). Phase synchronicity contributed significantly to SIHI variation, with stronger SIHI in the in-phase than out-of-phase conditions. These findings are in exact accord with the predictions of the theory of communication through coherence. They open a translational route for highly effective modification of brain connections by repetitive stimulation at instants in time when nodes in the network are phase synchronized and excitable.SIGNIFICANCE STATEMENT The theory of communication through coherence predicts that effective connectivity between nodes in distributed oscillating brain networks depends on their instantaneous excitability and phase relation. We tested this hypothesis in healthy human subjects by real-time analysis of brain states by electroencephalography in combination with transcranial magnetic stimulation of left and right motor cortex. We found that short-interval interhemispheric inhibition, a marker of interhemispheric effective connectivity, was maximally expressed when the two motor cortices were in phase for a high-excitability state (the trough of the sensorimotor μ-rhythm). We conclude that findings are consistent with the theory of communication through coherence. They open a translational route to highly effectively modify brain connections by repetitive stimulation at instants in time of phase-synchronized high-excitability states.

Coherent alpha oscillations link current and future receptive fields during saccades

Oscillations are ubiquitous in the brain, and they can powerfully influence neural coding. In particular, when oscillations at distinct sites are coherent, they provide a means of gating the flow of neural signals between different cortical regions. Coherent oscillations also occur within individual brain regions, although the purpose of this coherence is not well understood. Here, we report that within a single brain region, coherent alpha oscillations link stimulus representations as they change in space and time. Specifically, in primate cortical area V4, alpha coherence links sites that encode the retinal location of a visual stimulus before and after a saccade. These coherence changes exhibit properties similar to those of receptive field remapping, a phenomenon in which individual neurons change their receptive fields according to the metrics of each saccade. In particular, alpha coherence, like remapping, is highly dependent on the saccade vector and the spatial arrangement of current and future receptive fields. Moreover, although visual stimulation plays a modulatory role, it is neither necessary nor sufficient to elicit alpha coherence. Indeed, a similar pattern of coherence is observed even when saccades are made in darkness. Together, these results show that the pattern of alpha coherence across the retinotopic map in V4 matches many of the properties of receptive field remapping. Thus, oscillatory coherence might play a role in constructing the stable representation of visual space that is an essential aspect of conscious perception.

Phase Difference between Model Cortical Areas Determines Level of Information Transfer

Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of activity between distant cortical sites has been proposed as the mechanism underlying such a dynamic communication structure. Here, we study how oscillatory activity affects the excitability and input-output relation of local cortical circuits and how it alters the transmission of information between cortical circuits. To this end, we develop model circuits showing fast oscillations by the PING mechanism, of which the oscillatory characteristics can be altered. We identify conditions for synchronization between two brain circuits and show that the level of intercircuit coherence and the phase difference is set by the frequency difference between the intrinsic oscillations. We show that the susceptibility of the circuits to inputs, i.e., the degree of change in circuit output following input pulses, is not uniform throughout the oscillation period and that both firing rate, frequency and power are differentially modulated by inputs arriving at different phases. As a result, an appropriate phase difference between the circuits is critical for the susceptibility windows of the circuits in the network to align and for information to be efficiently transferred. We demonstrate that changes in synchrony and phase difference can be used to set up or abolish information transfer in a network of cortical circuits.

More Gamma More Predictions: Gamma-Synchronization as a Key Mechanism for Efficient Integration of Classical Receptive Field Inputs with Surround Predictions

During visual stimulation, neurons in visual cortex often exhibit rhythmic and synchronous firing in the gamma-frequency (30–90 Hz) band. Whether this phenomenon plays a functional role during visual processing is not fully clear and remains heavily debated. In this article, we explore the function of gamma-synchronization in the context of predictive and efficient coding theories. These theories hold that sensory neurons utilize the statistical regularities in the natural world in order to improve the efficiency of the neural code, and to optimize the inference of the stimulus causes of the sensory data. In visual cortex, this relies on the integration of classical receptive field (CRF) data with predictions from the surround. Here we outline two main hypotheses about gamma-synchronization in visual cortex. First, we hypothesize that the precision of gamma-synchronization reflects the extent to which CRF data can be accurately predicted by the surround. Second, we hypothesize that different cortical columns synchronize to the extent that they accurately predict each other’s CRF visual input. We argue that these two hypotheses can account for a large number of empirical observations made on the stimulus dependencies of gamma-synchronization. Furthermore, we show that they are consistent with the known laminar dependencies of gamma-synchronization and the spatial profile of intercolumnar gamma-synchronization, as well as the dependence of gamma-synchronization on experience and development. Based on our two main hypotheses, we outline two additional hypotheses. First, we hypothesize that the precision of gamma-synchronization shows, in general, a negative dependence on RF size. In support, we review evidence showing that gamma-synchronization decreases in strength along the visual hierarchy, and tends to be more prominent in species with small V1 RFs. Second, we hypothesize that gamma-synchronized network dynamics facilitate the emergence of spiking output that is particularly information-rich and sparse.

Metastability and Coherence: Extending the Communication through Coherence Hypothesis Using A Whole-Brain Computational Perspective

Understanding the mechanisms for communication in the brain remains one of the most challenging scientific questions. The communication through coherence (CTC) hypothesis was originally proposed 10 years ago, stating that two groups of neurons communicate most effectively when their excitability fluctuations are coordinated in time (i.e., coherent), and this control by cortical coherence is a fundamental brain mechanism for large-scale, distant communication. In light of new evidence from whole-brain computational modelling of multimodal neuroimaging data, we link CTC to the concept of metastability, which refers to a rich exploration of the functional repertoire made possible by the underlying structural whole-brain connectivity.

Do gamma oscillations play a role in cerebral cortex?

Gamma rhythm (which has a center frequency between 30 and 80 Hz) is modulated by cognitive mechanisms such as attention and memory, and has been hypothesized to play a role in mediating these processes by supporting communication channels between cortical areas or encoding information in its phase. We highlight several issues related to gamma rhythms, such as low and inconsistent power, its dependence on low-level stimulus features, problems due to conduction delays, and contamination due to spike-related activity that makes accurate estimation of gamma phase difficult. Gamma rhythm could be a potentially useful signature of excitation-inhibition interactions in the brain, but whether it also provides a mechanism for information processing or coding remains an open question.

A linear model of phase-dependent power correlations in neuronal oscillations

Recently, it has been suggested that effective interactions between two neuronal populations are supported by the phase difference between the oscillations in these two populations, a hypothesis referred to as "communication through coherence" (CTC). Experimental work quantified effective interactions by means of the power correlations between the two populations, where power was calculated on the local field potential and/or multi-unit activity. Here, we present a linear model of interacting oscillators that accounts for the phase dependency of the power correlation between the two populations and that can be used as a reference for detecting non-linearities such as gain control. In the experimental analysis, trials were sorted according to the coupled phase difference of the oscillators while the putative interaction between oscillations was taking place. Taking advantage of the modeling, we further studied the dependency of the power correlation on the uncoupled phase difference, connection strength, and topology. Since the uncoupled phase difference, i.e., the phase relation before the effective interaction, is the causal variable in the CTC hypothesis we also describe how power correlations depend on that variable. For uni-directional connectivity we observe that the width of the uncoupled phase dependency is broader than for the coupled phase. Furthermore, the analytical results show that the characteristics of the phase dependency change when a bidirectional connection is assumed. The width of the phase dependency indicates which oscillation frequencies are optimal for a given connection delay distribution. We propose that a certain width enables a stimulus-contrast dependent extent of effective long-range lateral connections.