Sharp wave ripples (SPW-Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW-Rs occur during "off-line" states of the brain, associated with consummatory behaviors and non-REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW-induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW-Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW-Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW-Rs interferes with memory. Recently acquired and pre-existing information are combined during SPW-R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW-Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW-Rs leads to their pathological conversion, "p-ripples," which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW-R genesis and function are discussed in this review.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hipo.22488

Hippocampal sharp wave‐ripple: A cognitive biomarker for episodic memory and planning

Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we developed new devices that integrate ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors that are connected using fewer wires. We used this system to record spatial properties of cat brain activity in vivo, including sleep spindles, single-trial visual evoked responses and electrographic seizures. We found that seizures may manifest as recurrent spiral waves that propagate in the neocortex. The developments reported here herald a new generation of diagnostic and therapeutic brain-machine interface devices.

/pdf/flexible-foldable-actively-multiplexed-high-density-2y9l2n62qa.pdf

Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo

Advances in materials, mechanics, and manufacturing now allow construction of high-quality electronics and optoelectronics in forms that can readily integrate with the soft, curvilinear, and time-dynamic surfaces of the human body. The resulting capabilities create new opportunities for studying disease states, improving surgical procedures, monitoring health/wellness, establishing human-machine interfaces, and performing other functions. This review summarizes these technologies and illustrates their use in forms integrated with the brain, the heart, and the skin.

https://www.annualreviews.org/doi/pdf/10.1146/annurev-bioeng-071811-150018

Flexible and Stretchable Electronics for Biointegrated Devices

Seizures can occur spontaneously and in a recurrent manner, which defines epilepsy; or they can be induced in a normal brain under a variety of conditions in most neuronal networks and species from flies to humans. Such universality raises the possibility that invariant properties exist that characterize seizures under different physiological and pathological conditions. Here, we analysed seizure dynamics mathematically and established a taxonomy of seizures based on first principles. For the predominant seizure class we developed a generic model called Epileptor. As an experimental model system, we used ictal-like discharges induced in vitro in mouse hippocampi. We show that only five state variables linked by integral-differential equations are sufficient to describe the onset, time course and offset of ictal-like discharges as well as their recurrence. Two state variables are responsible for generating rapid discharges (fast time scale), two for spike and wave events (intermediate time scale) and one for the control of time course, including the alternation between ‘normal’ and ictal periods (slow time scale). We propose that normal and ictal activities coexist: a separatrix acts as a barrier (or seizure threshold) between these states. Seizure onset is reached upon the collision of normal brain trajectories with the separatrix. We show theoretically and experimentally how a system can be pushed toward seizure under a wide variety of conditions. Within our experimental model, the onset and offset of ictal-like discharges are well-defined mathematical events: a saddle-node and homoclinic bifurcation, respectively. These bifurcations necessitate a baseline shift at onset and a logarithmic scaling of interspike intervals at offset. These predictions were not only confirmed in our in vitro experiments, but also for focal seizures recorded in different syndromes, brain regions and species (humans and zebrafish). Finally, we identified several possible biophysical parameters contributing to the five state variables in our model system. We show that these parameters apply to specific experimental conditions and propose that there exists a wide array of possible biophysical mechanisms for seizure genesis, while preserving central invariant properties. Epileptor and the seizure taxonomy will guide future modeling and translational research by identifying universal rules governing the initiation and termination of seizures and predicting the conditions necessary for those transitions.

/pdf/on-the-nature-of-seizure-dynamics-4cxq3m9jxu.pdf

On the nature of seizure dynamics

SUMMARY High-frequency oscillations (HFOs) in the 80– 200 Hz range can be recorded from normal hippocampus and parahippocampal structures of humans and animals. They are believed to reflect inhibitory field potentials, which facilitate information transfer by synchronizing neuronal activity over long distances. HFOs in the range of 250– 600 Hz (fast ripples, FRs) are pathologic and are readily recorded from hippocampus and parahippocampal structures of patients with mesial temporal lobe epilepsy, as well as rodent models of this disorder. These oscillations, and similar HFOs recorded from neocortex of patients, appear to identify brain tissue capable of spontaneous ictogenesis and are believed to reflect the neuronal substrates of epileptogenesis and epileptogenicity. The distinction between normal and pathologic HFOs (pHFOs), however, cannot be made on the basis of frequency alone, as oscillations in the FR frequency range can be recorded from some areas of normal neocortex, whereas oscillations in the ripple frequency range are present in epileptic dentate gyrus where normal ripples never occur and, therefore, appear to be pathologic. The suggestion that FRs may be harmonics of normal ripples is unlikely, because of their spatially distinct generators, and evidence that FRs reflect synchronized firing of abnormally bursting neurons rather than inhibitory field potentials. These synchronous population spikes, however, can fire at ripple frequencies, and their harmonics appear to give rise to FRs. Investigations into the fundamental neuronal processes responsible for pHFOs could provide insights into basic mechanisms of epilepsy. The potential for pHFOs to act as biomarkers for epileptogenesis and epileptogenicity is also discussed.

/pdf/high-frequency-oscillations-what-is-normal-and-what-is-not-4h9gkw2qj9.pdf

High-frequency oscillations : What is normal and what is not?

Nuclei-specific thalamic connectivity predicts seizure frequency in drug-resistant medial temporal lobe epilepsy

Goal: Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures of human subjects during a visual recognition memory task. We quantify and compare single neuron unit activity (SUA) with high-frequency macrofield oscillations (HFOs) for decoding visual images. Results: SUA and HFOs were recorded using hybrid electrodes containing both micro and macroelectrode contacts, implanted in patients with focal epilepsy. Decoding of image properties in different task trials was performed, analyzing SUA and HFO as point processes to capture the dynamics of neurons and their assemblies at different spatiotemporal scales, ranging from submillisecond discharges of single units to fast oscillations across large neuronal populations. Results highlight the limitations and potential complementary use of SUA and HFOs for decoding of general image properties. Conclusion: The dynamics of SUA and HFOs can be used to explore a wide range of neuronal assembly activities engaged in human memory processing. Significance: Hybrid electrodes provide a technological bridge for exploring multiscale activity, spanning individual neurons, their assemblies, and large-scale population activity reflected in local field potentials. Analysis of SUA and HFO dynamics as point processes provides a potentially useful signal processing method for exploring the neuronal correlates operating at different spatial scales.

Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task

A 28-year-old right-handed man presented with medically intractable focal reflex epilepsy. He previously underwent resection of a right parietal lobe cortical dysplasia. Postoperatively, he developed focal reflex epilepsy triggered by motor activation of the left lower extremity. These were refractory to multiple antiepileptic drugs (AEDs) and vagal nerve stimulation therapy (VNS), and prevented standing and walking. Clinical examination showed mild left hemiparesis and left lower extremity myoclonic seizures triggered by motor activation and standing (see online supplementary video 1). Scalp EEG showed focal seizure discharges consisting of rhythmic midline central sharp waves. Brain MRI showed postoperative signal hyperintensity in the region of the prior resection (figure 1A). Subtraction ictal single-photon emission CT coregistered to MRI (SISCOM) demonstrated ictal hyperperfusion in the near prior resection cavity in leg motor area (figure 1B).



Figure 1 
(A) …

https://jnnp.bmj.com/content/jnnp/early/2015/02/19/jnnp-2014-309944.full.pdf

S. Matt Stead

Papers

Nuclei-specific thalamic connectivity predicts seizure frequency in drug-resistant medial temporal lobe epilepsy

Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task

I cannot stand this anymore