Low-Power Lossless Data Compression for Wireless Brain Electrophysiology.

Wireless electrophysiology opens important possibilities for neuroscience, especially for recording brain activity in more natural contexts, where exploration and interaction are not restricted by the usual tethered devices. The limiting factor is transmission power and, by extension, battery life required for acquiring large amounts of neural electrophysiological data. We present a digital compression algorithm capable of reducing electrophysiological data to less than 65.5% of its original size without distorting the signals, which we tested in vivo in experimental animals. The algorithm is based on a combination of delta compression and Huffman codes with optimizations for neural signals, which allow it to run in small, low-power Field-Programmable Gate Arrays (FPGAs), requiring few hardware resources. With this algorithm, a hardware prototype was created for wireless data transmission using commercially available devices. The power required by the algorithm itself was less than 3 mW, negligible compared to the power saved by reducing the transmission bandwidth requirements. The compression algorithm and its implementation were designed to be device-agnostic. These developments can be used to create a variety of wired and wireless neural electrophysiology acquisition systems with low power and space requirements without the need for complex or expensive specialized hardware.

Different theta frameworks coexist in the rat hippocampus and are coordinated during memory-guided and novelty tasks.

Hippocampal firing is organized in theta sequences controlled by internal memory processes and by external sensory cues, but how these computations are coordinated is not fully understood. Although theta activity is commonly studied as a unique coherent oscillation, it is the result of complex interactions between different rhythm generators. Here, by separating hippocampal theta activity in three different current generators, we found epochs with variable theta frequency and phase coupling, suggesting flexible interactions between theta generators. We found that epochs of highly synchronized theta rhythmicity preferentially occurred during behavioral tasks requiring coordination between internal memory representations and incoming sensory information. In addition, we found that gamma oscillations were associated with specific theta generators and the strength of theta-gamma coupling predicted the synchronization between theta generators. We propose a mechanism for segregating or integrating hippocampal computations based on the flexible coordination of different theta frameworks to accommodate the cognitive needs.

In the brain, a vast number of neurons coordinate their activity to support complex cognitive processes. One of the best places to see this in action is the hippocampus, a brain structure with a key role in memory and navigation. The hippocampus shows waves of electrical activity, which represent the synchronized firing of large numbers of neurons. The hippocampus can generate multiple rhythms at once. The two main rhythms are theta and gamma. Theta waves are slow, with a frequency of about 8 Hertz. Gamma waves are faster with a frequency of up to 120 Hertz or even more. Theta waves are always present in the brains of freely moving animals, whereas gamma waves occur in brief bursts. These bursts usually correspond to a particular point on the theta wave. One burst may occur just before each peak of the theta wave, for example, whereas another burst may occur just after the peak. This separation enables individual bursts of gamma to carry different messages without them becoming mixed up. This is similar to how radio stations broadcast their signals at different carrier frequencies to avoid interference. By recording hippocampal activity in rats exploring a maze, Lopez-Madrona et al. now show that the hippocampus has not one, but three generators of theta waves. Having three sources of theta, each of which can be synchronized with gamma, provides a more versatile system for encoding and sending information. It also means that the three theta generators can vary the degree to which they coordinate their firing. This helps the brain combine or separate streams of information as required. By working together to create a single theta rhythm, for example, the three theta generators can help animals combine information stored in memory with incoming sensory input. How the coordination of theta rhythms in the hippocampus influences the activity of other brain regions involved in learning and memory remains unclear. However, uncoupling of theta and gamma waves seems to be an early sign of Alzheimer's disease and can also be seen in the brains of people with schizophrenia and other psychiatric disorders. Understanding how this process occurs could provide clues to the origin of these disorders.

Mapping Functional Connectivity in the Rodent Brain Using Electric-Stimulation fMRI.

Since its discovery in the early 90s, BOLD signal-based functional Magnetic Resonance Imaging (fMRI) has become a fundamental technique for the study of brain activity in basic and clinical research. Functional MRI signals provide an indirect but robust and quantitative readout of brain activity through the tight coupling between cerebral blood flow and neuronal activation, the so-called neurovascular coupling. Combined with experimental techniques only available in animal models, such as intracerebral micro-stimulation, optogenetics or pharmacogenetics, provides a powerful framework to investigate the impact of specific circuit manipulations on overall brain dynamics. The purpose of this chapter is to provide a comprehensive protocol to measure brain activity using fMRI with intracerebral electric micro-stimulation in murine models. Preclinical research (especially in rodents) opens the door to very sophisticated and informative experiments, but at the same time imposes important constrains (i.e., anesthetics, translatability), some of which will be addressed here.