Principles of large-scale neural interactions.

What mechanisms underlie flexible inter-areal communication in the cortex? We consider four mechanisms for temporal coordination and their contributions to communication: (1) Oscillatory synchronization (communication-through-coherence); (2) communication-through-resonance; (3) non-linear integration; and (4) linear signal transmission (coherence-through-communication). We discuss major challenges for communication-through-coherence based on layer- and cell-type-specific analyses of spike phase-locking, heterogeneity of dynamics across networks and states, and computational models for selective communication. We argue that resonance and non-linear integration are viable alternative mechanisms that facilitate computation and selective communication in recurrent networks. Finally, we consider communication in relation to cortical hierarchy and critically examine the hypothesis that feedforward and feedback communication use fast (gamma) and slow (alpha/beta) frequencies, respectively. Instead, we propose that feedforward propagation of prediction errors relies on the non-linear amplification of aperiodic transients, whereas gamma and beta rhythms represent rhythmic equilibrium states that facilitate sustained and efficient information encoding and amplification of short-range feedback via resonance.

A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power.

Inter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communication and naturally emerges because spiking activity in a sending area causes post-synaptic potentials both in the same and in other areas. Consequently, coherence depends in a lawful manner on power and phase-locking in the sender and connectivity. Changes in oscillatory power explained prominent changes in fronto-parietal and LGN-V1 coherence across behavioral conditions. Optogenetic experiments and excitatory-inhibitory network simulations identified afferent synaptic inputs rather than spiking entrainment as the principal determinant of coherence. These findings suggest that unique spectral profiles of different brain areas automatically give rise to large-scale coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.

A Distinct Class of Bursting Neurons with Strong Gamma Synchronization and Stimulus Selectivity in Monkey V1.

Cortical computation depends on interactions between excitatory and inhibitory neurons. The contributions of distinct neuron types to sensory processing and network synchronization in primate visual cortex remain largely undetermined. We show that in awake monkey V1, there exists a distinct cell type (>>30% of neurons) that has narrow-waveform (NW) action potentials and high spontaneous discharge rates and fires in high-frequency bursts. These neurons are more stimulus selective and phase locked to 30- to 80-Hz gamma oscillations than other neuron types. Unlike other neuron types, their gamma-phase locking is highly predictive of orientation tuning. We find evidence for strong rhythmic inhibition in these neurons, suggesting that they interact with interneurons to act as excitatory pacemakers for the V1 gamma rhythm. We did not find a similar class of NW bursting neurons in L2-L4 of mouse V1. Given its properties, this class of NW bursting neurons should be pivotal for the encoding and transmission of stimulus information.

Pre-ictal increase in theta synchrony between the hippocampus and prefrontal cortex in a rat model of temporal lobe epilepsy.

The pathologically synchronized neuronal activity in temporal lobe epilepsy (TLE) can be triggered by network events that were once normal. Under normal conditions, hippocampus and medial prefrontal cortex (mPFC) work in synchrony during a variety of cognitive states. Abnormal changes in this circuit may aid to seizure onset and also help to explain the high association of TLE with mood disorders. We used a TLE rat model generated by perforant path (PP) stimulation to understand whether synchrony between dorsal hippocampal and mPFC networks is altered shortly before a seizure episode. We recorded hippocampal and mPFC local field potentials (LFPs) of animals with spontaneous recurrent seizures (SRSs) to verify the connectivity between these regions. We showed that SRSs decrease hippocampal theta oscillations whereas coherence in theta increases over time prior to seizure onset. This increase in synchrony is accompanied by a stronger coupling between hippocampal theta and mPFC gamma oscillation. Finally, using Granger causality we showed that hippocampus/mPFC synchrony increases in the pre-ictal phase and this increase is likely to be caused by hippocampal networks. The dorsal hippocampus is not directly connected to the mPFC; however, the functional coupling in theta between these two structures rises pre-ictally. Our data indicates that the increase in synchrony between dorsal hippocampus and mPFC may be predictive of seizures and may help to elucidate the network mechanisms that lead to seizure generation.