From Mechanisms to Functions: The Role of Synchronization in the Intrahippocampal Circuits

The brain rhythms are essential for information processing in neuronal networks. Oscillations recorded in different brain regions can be synchronized and have a constant phase difference, i.e. be coherent. Coherence between local field potential (LFP) signals from different regions in the brain may be correlated with the performance of cognitive tasks, from which it is concluded that these regions of the brain are involved in the task performance together. In this review, we discuss why coherence occurs and how it is coupled to the information transfer between different regions of the hippocampal formation. Coherence in theta and gamma frequency ranges is described since these rhythms are most pronounced during the hippocampus-dependent attention and memory. We review in vivo studies of interactions between different regions of the hippocampal formation in theta and gamma frequency bands. The kay provisions of the review: 1) coherence emerges from synchronous postsynaptic currents in principal neurons, occurring as a result of synchronization of neuronal spike activity; 2) synchronization of neuronal spike patterns in two regions of the hippocampal formation can be realised through induction or resonance; 3) coherence at a specific time point reflects the transfer of information between regions of the hippocampal formation, in particular, gamma coherence reflects the coupling of active neuronal ensembles. Overall, coherence is not an epiphenomenon, but an important physiological process that has certain generation mechanisms and performs important functions in information processing and transmission across the brain regions.

How Stimulus Statistics Affect The Receptive Fields of V1 Cells

We studied the changes that neuronal RF models undergo when the statistics of the stimulus are changed from those of white Gaussian noise (WGN) to those of natural scenes (NS). Fitting the model to data estimates both a cascade of linear filters on the stimulus, as wells as the static nonlinearities that map the output of the filters to the neuronal spike rates. We found that cells respond differently to these two classes of stimuli, with mostly higher spike rates and shorter response latencies to NS than to WGN. The most striking finding was that NS resulted in RFs that had additional uncovered filters than did WGN. This finding was not an artefact of the higher spike rates but rather related to a change in coding. Our results reveal a greater extent of nonlinear processing in V1 neurons when stimulated using NS compared to WGN. Our findings indicate the existence of nonlinear mechanisms that endow V1 neurons with context-dependent transmission of visual information.

Fano Factor: A Potentially Useful Information

The Fano factor, defined as the variance-to-mean ratio of spike counts in a time window, is often used to measure the variability of neuronal spike trains. However, despite its transparent definition, careless use of the Fano factor can easily lead to distorted or even wrong results. One of the problems is the unclear dependence of the Fano factor on the spiking rate, which is often neglected or handled insufficiently. In this paper we aim to explore this problem in more detail and to study the possible solution, which is to evaluate the Fano factor in the operational time. We use equilibrium renewal and Markov renewal processes as spike train models to describe the method in detail, and we provide an illustration on experimental data.

Spike Phase Shift Relative to Beta Oscillations Mediates Modality Selection

How does the brain selectively process signals from stimuli of different modalities? Coherent oscillations may function in coordinating communication between neuronal populations simultaneously involved in such cognitive behavior. Beta power (12–30 Hz) is implicated in top-down cognitive processes. Here we test the hypothesis that the brain increases encoding and behavioral influence of a target modality by shifting the relationship of neuronal spike phases relative to beta oscillations between primary sensory cortices and higher cortices. We simultaneously recorded neuronal spike and local field potentials in the posterior parietal cortex (PPC) and the primary auditory cortex (A1) when male rats made choices to either auditory or visual stimuli. Neuronal spikes exhibited modality-related phase locking to beta oscillations during stimulus sampling, and the phase shift between neuronal subpopulations demonstrated faster top-down signaling from PPC to A1 neurons when animals attended to auditory rather than visual stimuli. Importantly, complementary to spike timing, spike phase predicted rats’ attended-to target in single trials, which was related to the animals’ performance. Our findings support a candidate mechanism that cortices encode targets from different modalities by shifting neuronal spike phase. This work may extend our understanding of the importance of spike phase as a coding and readout mechanism.