Linking minimal and detailed models of CA1 microcircuits reveals how theta rhythms emerge and their frequencies controlled

Dialectics of perisomatic inhibition-The unity and conflict of opposites

Over the past three decades, a great deal of attention has been paid to the study of perisomatic inhibition and perisomatic inhibitory basket cells. A growing body of experimental evidence points to the leading role of perisomatic inhibitory cells in the generation of oscillatory activity in various frequency ranges. Recently the link between the activity of basket cells and complex behavior has been demonstrated in several laboratories. However, all this is true only for one type of perisomatic inhibitory interneuron-parvalbumin-positive basket cells. Nevertheless, where parvalbumin-positive basket cells are found, there is another type of basket cell, cholecystokinin-positive interneurons. These two types of interneurons share a number of common features: they innervate the same compartments of target neurons and they often receive excitation from the same sources, but they also differ from each other in the synchrony of their GABA release and expression of receptors. The functional role of cholecystokinin-positive basket cells in oscillatory activity is not so obvious. They were thought to be involved in theta oscillations, however recent measurements in free moving animals have put some doubts on this hypothesis. Therefore, an important question is, whether these two types of basket cells work synergistically or perform opposing actions in functional networks? In this mini-review, we attempt to answer this question by putting forward the idea that these two types of basket cells are functionally united as two entities of the same network, and their opposing actions are necessary to maintain rhythmogenesis in a "healthy", physiological range.

A dynamical computational model of theta generation in hippocampal circuits to study theta-gamma oscillations during neurostimulation

Neurostimulation of the hippocampal formation has shown promising results for modulating memory but the underlying mechanisms remain unclear. In particular, the effects on hippocampal theta-nested gamma oscillations and theta phase reset, which are both crucial for memory processes, are unknown. Moreover, these effects cannot be investigated using current computational models, which consider theta oscillations with a fixed amplitude and phase velocity. Here, we developed a novel computational model that includes the medial septum, represented as a set of abstract Kuramoto oscillators producing a dynamical theta rhythm with phase reset, and the hippocampal formation, composed of biophysically realistic neurons and able to generate theta-nested gamma oscillations under theta drive. We showed that, for theta inputs just below the threshold to induce self-sustained theta-nested gamma oscillations, a single stimulation pulse could switch the network behavior from non-oscillatory to a state producing sustained oscillations. Next, we demonstrated that, for a weaker theta input, pulse train stimulation at the theta frequency could transiently restore seemingly physiological oscillations. Importantly, the presence of phase reset influenced whether these two effects depended on the phase at which stimulation onset was delivered, which has practical implications for designing neurostimulation protocols that are triggered by the phase of ongoing theta oscillations. This novel model opens new avenues for studying the effects of neurostimulation on the hippocampal formation. Furthermore, our hybrid approach that combines different levels of abstraction could be extended in future work to other neural circuits that produce dynamical brain rhythms.

Theoretical considerations and supporting evidence for the primary role of source geometry on field potential amplitude and spatial extent

Field potential (FP) recording is an accessible means to capture the shifts in the activity of neuron populations. However, the spatial and composite nature of these signals has largely been ignored, at least until it became technically possible to separate activities from co-activated sources in different structures or those that overlap in a volume. The pathway-specificity of mesoscopic sources has provided an anatomical reference that facilitates transcending from theoretical analysis to the exploration of real brain structures. We review computational and experimental findings that indicate how prioritizing the spatial geometry and density of sources, as opposed to the distance to the recording site, better defines the amplitudes and spatial reach of FPs. The role of geometry is enhanced by considering that zones of the active populations that act as sources or sinks of current may arrange differently with respect to each other, and have different geometry and densities. Thus, observations that seem counterintuitive in the scheme of distance-based logic alone can now be explained. For example, geometric factors explain why some structures produce FPs and others do not, why different FP motifs generated in the same structure extend far while others remain local, why factors like the size of an active population or the strong synchronicity of its neurons may fail to affect FPs, or why the rate of FP decay varies in different directions. These considerations are exemplified in large structures like the cortex and hippocampus, in which the role of geometrical elements and regional activation in shaping well-known FP oscillations generally go unnoticed. Discovering the geometry of the sources in play will decrease the risk of population or pathway misassignments based solely on the FP amplitude or temporal pattern.