Alexandra Chatzikalymniou

All Publications

• Linking minimal and detailed models of CA1 microcircuits reveals how theta rhythms emerge and their frequencies controlled HIPPOCAMPUS Chatzikalymniou, A., Gumus, M., Skinner, F. K. 2021

  Abstract

  The wide variety of cell types and their biophysical complexities pose a challenge in our ability to understand oscillatory activities produced by cellular-based computational network models. This challenge stems from their high-dimensional and multiparametric natures. To overcome this, we implement a solution by linking minimal and detailed models of CA1 microcircuits that generate intrahippocampal (3-12 Hz) theta rhythms. We leverage insights from minimal models to guide explorations of more detailed models and obtain a cellular perspective of theta generation. Our findings distinguish the pyramidal cells as the theta rhythm initiators and reveal that their activity is regularized by the inhibitory cell populations, supporting a proposed hypothesis of an "inhibition-based tuning" mechanism. We find a strong correlation between input current to the pyramidal cells and the resulting local field potential theta frequency, indicating that intrinsic pyramidal cell properties underpin network frequency characteristics. This work provides a cellular-based foundation from which in vivo theta activities can be explored.

  View details for DOI 10.1002/hipo.23364

  View details for Web of Science ID 000657820600001

  View details for PubMedID 34086375

• A Hypothesis for Theta Rhythm Frequency Control in CA1 Microcircuits FRONTIERS IN NEURAL CIRCUITS Skinner, F. K., Rich, S., Lunyov, A. R., Lefebvre, J., Chatzikalymniou, A. P. 2021; 15: 643360

  Abstract

  Computational models of neural circuits with varying levels of biophysical detail have been generated in pursuit of an underlying mechanism explaining the ubiquitous hippocampal theta rhythm. However, within the theta rhythm are at least two types with distinct frequencies associated with different behavioral states, an aspect that must be considered in pursuit of these mechanistic explanations. Here, using our previously developed excitatory-inhibitory network models that generate theta rhythms, we investigate the robustness of theta generation to intrinsic neuronal variability by building a database of heterogeneous excitatory cells and implementing them in our microcircuit model. We specifically investigate the impact of three key "building block" features of the excitatory cell model that underlie our model design: these cells' rheobase, their capacity for post-inhibitory rebound, and their spike-frequency adaptation. We show that theta rhythms at various frequencies can arise dependent upon the combination of these building block features, and we find that the speed of these oscillations are dependent upon the excitatory cells' response to inhibitory drive, as encapsulated by their phase response curves. Taken together, these findings support a hypothesis for theta frequency control that includes two aspects: (i) an internal mechanism that stems from the building block features of excitatory cell dynamics; (ii) an external mechanism that we describe as "inhibition-based tuning" of excitatory cell firing. We propose that these mechanisms control theta rhythm frequencies and underlie their robustness.

  View details for DOI 10.3389/fncir.2021.643360

  View details for Web of Science ID 000647047500001

  View details for PubMedID 33967702

  View details for PubMedCentralID PMC8097141

• Alzheimer's Disease: Rhythms, Local Circuits, and Model-Experiment Interactions MULTISCALE MODELS OF BRAIN DISORDERS Skinner, F. K., Chatzikalymniou, A., Cutsuridis 2019; 13: 149-156

  View details for DOI 10.1007/978-3-030-18830-6_14

  View details for Web of Science ID 000554939700015

• Deciphering the Contribution of Oriens-Lacunosum/Moleculare (OLM) Cells to Intrinsic θ Rhythms Using Biophysical Local Field Potential (LFP) Models eNeuro Chatzikalymniou, A. P., Skinner, F. K. 2018

  View details for DOI 10.1523/ENEURO.0146-18.2018

• Combining Theory, Model, and Experiment to Explain How Intrinsic Theta Rhythms Are Generated in an In Vitro Whole Hippocampus Preparation without Oscillatory Inputs ENEURO Ferguson, K. A., Chatzikalymniou, A. P., Skinner, F. K. 2017; 4 (4)

  Abstract

  Scientists have observed local field potential theta rhythms (3-12 Hz) in the hippocampus for decades, but understanding the mechanisms underlying their generation is complicated by their diversity in pharmacological and frequency profiles. In addition, interactions with other brain structures and oscillatory drives to the hippocampus during distinct brain states has made it difficult to identify hippocampus-specific properties directly involved in theta generation. To overcome this, we develop cellular-based network models using a whole hippocampus in vitro preparation that spontaneously generates theta rhythms. Building on theoretical and computational analyses, we find that spike frequency adaptation and postinhibitory rebound constitute a basis for theta generation in large, minimally connected CA1 pyramidal (PYR) cell network models with fast-firing parvalbumin-positive (PV+) inhibitory cells. Sparse firing of PYR cells and large excitatory currents onto PV+ cells are present as in experiments. The particular theta frequency is more controlled by PYR-to-PV+ cell interactions rather than PV+-to-PYR cell interactions. We identify two scenarios by which theta rhythms can emerge, and they can be differentiated by the ratio of excitatory to inhibitory currents to PV+ cells, but not to PYR cells. Only one of the scenarios is consistent with data from the whole hippocampus preparation, which leads to the prediction that the connection probability from PV+ to PYR cells needs to be larger than from PYR to PV+ cells. Our models can serve as a platform on which to build and develop an understanding of in vivo theta generation.

  View details for DOI 10.1523/ENEURO.0131-17.2017

  View details for Web of Science ID 000407416400011

  View details for PubMedID 28791333

  View details for PubMedCentralID PMC5547196

• Oscillatory Dynamics of Brain Microcircuits Modeling Perspectives and Neurological Disease Considerations Skinner, F., Chatzikalymniou, A. 2017

  View details for DOI 10.1002/9781119159193.ch7