Measuring Instantaneous Frequency of Local Field Potential Oscillations using the Kalman Smoother

Rhythmic local field potentials (LFPs) arise from coordinated neural activity. Inference of neural function based on the properties of brain rhythms remains a challenging data analysis problem. Algorithms that characterize non-stationary rhythms with high temporal and spectral resolution may be useful for interpreting LFP activity on the timescales in which they are generated. We propose a Kalman smoother based dynamic autoregressive model for tracking the instantaneous frequency (iFreq) and frequency modulation (FM) of noisy and non-stationary sinusoids such as those found in LFP data. We verify the performance of our algorithm using simulated data with broad spectral content, and demonstrate its application using real data recorded from behavioral learning experiments. In analyses of ripple oscillations (100–250 Hz) recorded from the rodent hippocampus, our algorithm identified novel repetitive, short timescale frequency dynamics. Our results suggest that iFreq and FM may be useful measures for the quantification of small timescale LFP dynamics.National Institutes of Health (U.S.) (NIH/NIMH R01 MH59733)National Institutes of Health (U.S.) (NIH/NIHLB R01 HL084502)Massachusetts Institute of Technology (Henry E. Singleton Presidential Graduate Fellowship Award

Functional diversity of subicular principal cells during hippocampal ripples

Cortical and hippocampal oscillations play a crucial role in the encoding, consolidation, and retrieval of memory. Sharp-wave associated ripples have been shown to be necessary for the consolidation of memory. During consolidation, information is transferred from the hippocampus to the neocortex. One of the structures at the interface between hippocampus and neocortex is the subiculum. It is therefore well suited to mediate the transfer and distribution of information from the hippocampus to other areas. By juxtacellular and whole-cell-recordings in awake mice, we show here that in the subiculum a subset of pyramidal cells is activated, whereas another subset is inhibited during ripples. We demonstrate that these functionally different subgroups are predetermined by their cell subtype. Bursting cells are selectively used to transmit information during ripples, whereas the firing probability in regular firing cells is reduced. With multiple patch-clamp recordings in vitro, we show that the cell subtype-specific differences extend into the local network topology. This is reflected in an asymmetric wiring scheme where bursting cells and regular firing cells are recurrently connected among themselves but connections between subtypes exclusively exist from regular to bursting cells. Furthermore, inhibitory connections are more numerous onto regular firing cells than onto bursting cells. We conclude that the network topology contributes to the observed functional diversity of subicular pyramidal cells during sharp-wave associated ripples

Doctor of Philosophy

dissertationHippocampal network oscillations are important for learning and memory. Theta rhythms are involved in attention, navigation, and memory encoding, whereas sharp wave-ripple complexes (ripples) are involved in memory consolidation. Cholinergic neurons in the medial septum-diagonal band of Broca (MS-DB) influence both types of hippocampal oscillations, promoting theta rhythms and suppressing ripples. They also receive frequency-dependent hyperpolarizing feedback from hippocamposeptal connections, potentially affecting their role as neuromodulators in the septohippocampal circuit. However, little is known about how the integration properties of cholinergic MS-DB neurons change with hyperpolarization. By potentially altering firing behavior in cholinergic neurons, hyperpolarizing feedback from the hippocampal neurons may, in turn, change hippocampal network activity. To study how hyperpolarizing inputs change in membrane integration properties, we used whole-cell patch-clamp recordings targeting genetically labeled, choline acetyltransferase-positive neurons in mouse medial septal brain slices. Hyperpolarization of cholinergic MS-DB neurons resulted in a long-lasting decrease in spike firing rate and input-output gain. Additionally, voltage-clamp measures implicated a slowly inactivating, 4-AP-insensitive, outward K+ conductance. Using a conductance-based model of cholinergic MS-DB neurons, we show that the ability of this conductance to modulate firing rate and gain depends on the expression of an experimentally verified shallow intrinsic spike frequency-voltage relationship. Finally, we show that cholinergic suppression of hippocampal ripples can be achieved through an imbalance in drive, caused by cholinergic modulation, to hippocampal excitatory and inhibitory neurons. Together, these findings show possible mechanisms through which cholinergic MS-DB neurons may both influence and be influenced by hippocampal rhythms

Controversies in epilepsy: Debates held during the Fourth International Workshop on Seizure Prediction

Debates on six controversial topics were held during the Fourth International Workshop on Seizure Prediction (IWSP4) convened in Kansas City, KS, USA, July 4–7, 2009. The topics were (1) Ictogenesis: Focus versus Network? (2) Spikes and Seizures: Step-relatives or Siblings? (3) Ictogenesis: A Result of Hyposynchrony? (4) Can Focal Seizures Be Caused by Excessive Inhibition? (5) Do High-Frequency Oscillations Provide Relevant Independent Information? (6) Phase Synchronization: Is It Worthwhile as Measured? This article, written by the IWSP4 organizing committee and the debaters, summarizes the arguments presented during the debates

Temporal Changes of Neocortical High-Frequency Oscillations in Epilepsy

High-frequency (100–500 Hz) oscillations (HFOs) recorded from intracranial electrodes are a potential biomarker for epileptogenic brain. HFOs are commonly categorized as ripples (100–250 Hz) or fast ripples (250–500 Hz), and a third class of mixed frequency events has also been identified. We hypothesize that temporal changes in HFOs may identify periods of increased the likelihood of seizure onset. HFOs (86,151) from five patients with neocortical epilepsy implanted with hybrid (micro + macro) intracranial electrodes were detected using a previously validated automated algorithm run over all channels of each patient\u27s entire recording. HFOs were characterized by extracting quantitative morphologic features and divided into four time epochs (interictal, preictal, ictal, and postictal) and three HFO clusters (ripples, fast ripples, and mixed events). We used supervised classification and nonparametric statistical tests to explore quantitative changes in HFO features before, during, and after seizures. We also analyzed temporal changes in the rates and proportions of events from each HFO cluster during these periods. We observed patient-specific changes in HFO morphology linked to fluctuation in the relative rates of ripples, fast ripples, and mixed frequency events. These changes in relative rate occurred in pre- and postictal periods up to thirty min before and after seizures. We also found evidence that the distribution of HFOs during these different time periods varied greatly between individual patients. These results suggest that temporal analysis of HFO features has potential for designing custom seizure prediction algorithms and for exploring the relationship between HFOs and seizure generation

Theta Phase Modulates Multiple Layer-Specific Oscillations in the CA1 Region

It was recently proposed that fast gamma oscillations (60--150 Hz) convey spatial information from the medial entorhinal cortex (EC) to the CA1 region of the hippocampus. However, here we describe 2 functionally distinct oscillations within this frequency range, both coupled to the theta rhythm during active exploration and rapid eye movement sleep: an oscillation with peak activity at ~80 Hz and a faster oscillation centered at ~140 Hz. The 2 oscillations are differentially modulated by the phase of theta depending on the CA1 layer; theta-80 Hz coupling is strongest at stratum lacunosum-- moleculare, while theta-140 Hz coupling is strongest at stratum oriens--alveus. This laminar profile suggests that the ~80 Hz oscillation originates from EC inputs to deeper CA1 layers, while the ~140 Hz oscillation reflects CA1 activity in superficial layers. We further show that the ~140 Hz oscillation differs from sharp wave--associated ripple oscillations in several key characteristics. Our results demonstrate the existence of novel theta--associated high-frequency oscillations and suggest a redefinition of fast gamma oscillations

Manipulating sleep spindles - expanding views on sleep, memory, and disease.

Sleep spindles are distinctive electroencephalographic (EEG) oscillations emerging during non-rapid-eye-movement sleep (NREMS) that have been implicated in multiple brain functions, including sleep quality, sensory gating, learning, and memory. Despite considerable knowledge about the mechanisms underlying these neuronal rhythms, their function remains poorly understood and current views are largely based on correlational evidence. Here, we review recent studies in humans and rodents that have begun to broaden our understanding of the role of spindles in the normal and disordered brain. We show that newly identified molecular substrates of spindle oscillations, in combination with evolving technological progress, offer novel targets and tools to selectively manipulate spindles and dissect their role in sleep-dependent processes