Gaussian Process Kernels for Cross-Spectrum Analysis in Electrophysiological Time Series

Multi-output Gaussian processes provide a convenient framework for multi-task problems. An illustrative and motivating example of a multi-task problem is multi-region electrophysiological time-series data, where experimentalists are interested in both power and phase coherence between channels. Recently, the spectral mixture (SM) kernel was proposed to model the spectral density of a single task in a Gaussian process framework. This work develops a novel covariance kernel for multiple outputs, called the cross-spectral mixture (CSM) kernel. This new, flexible kernel represents both the power and phase relationship between multiple observation channels. The expressive capabilities of the CSM kernel are demonstrated through implementation of 1) a Bayesian hidden Markov model, where the emission distribution is a multi-output Gaussian process with a CSM covariance kernel, and 2) a Gaussian process factor analysis model, where factor scores represent the utilization of cross-spectral neural circuits. Results are presented for measured multi-region electrophysiological data.

Optimized, unequal pulse spacing in multiple echo sequences improves refocusing in magnetic resonance.

A recent quantum computing paper (G. S. Uhrig, Phys. Rev. Lett. 98, 100504 (2007)) analytically derived optimal pulse spacings for a multiple spin echo sequence designed to remove decoherence in a two-level system coupled to a bath. The spacings in what has been called a "Uhrig dynamic decoupling (UDD) sequence" differ dramatically from the conventional, equal pulse spacing of a Carr-Purcell-Meiboom-Gill (CPMG) multiple spin echo sequence. The UDD sequence was derived for a model that is unrelated to magnetic resonance, but was recently shown theoretically to be more general. Here we show that the UDD sequence has theoretical advantages for magnetic resonance imaging of structured materials such as tissue, where diffusion in compartmentalized and microstructured environments leads to fluctuating fields on a range of different time scales. We also show experimentally, both in excised tissue and in a live mouse tumor model, that optimal UDD sequences produce different T(2)-weighted contrast than do CPMG sequences with the same number of pulses and total delay, with substantial enhancements in most regions. This permits improved characterization of low-frequency spectral density functions in a wide range of applications.

Similar prevalence and magnitude of auditory-evoked and visually evoked activity in the frontal eye fields: implications for multisensory motor control.

Saccadic eye movements can be elicited by more than one type of sensory stimulus. This implies substantial transformations of signals originating in different sense organs as they reach a common motor output pathway. In this study, we compared the prevalence and magnitude of auditory- and visually evoked activity in a structure implicated in oculomotor processing, the primate frontal eye fields (FEF). We recorded from 324 single neurons while 2 monkeys performed delayed saccades to visual or auditory targets. We found that 64% of FEF neurons were active on presentation of auditory targets and 87% were active during auditory-guided saccades, compared with 75 and 84% for visual targets and saccades. As saccade onset approached, the average level of population activity in the FEF became indistinguishable on visual and auditory trials. FEF activity was better correlated with the movement vector than with the target location for both modalities. In summary, the large proportion of auditory-responsive neurons in the FEF, the similarity between visual and auditory activity levels at the time of the saccade, and the strong correlation between the activity and the saccade vector suggest that auditory signals undergo tailoring to match roughly the strength of visual signals present in the FEF, facilitating accessing of a common motor output pathway.

The Basic-Systems Model of Episodic Memory.

Behavior, neuropsychology, and neuroimaging suggest that episodic memories are constructed from interactions among the following basic systems: vision, audition, olfaction, other senses, spatial imagery, language, emotion, narrative, motor output, explicit memory, and search and retrieval. Each system has its own well-documented functions, neural substrates, processes, structures, and kinds of schemata. However, the systems have not been considered as interacting components of episodic memory, as is proposed here. Autobiographical memory and oral traditions are used to demonstrate the usefulness of the basic-systems model in accounting for existing data and predicting novel findings, and to argue that the model, or one similar to it, is the only way to understand episodic memory for complex stimuli routinely encountered outside the laboratory.

Activity in descending dopaminergic neurons represents but is not required for leg movements in the fruit fly Drosophila.

Modulatory descending neurons (DNs) that link the brain to body motor circuits, including dopaminergic DNs (DA-DNs), are thought to contribute to the flexible control of behavior. Dopamine elicits locomotor-like outputs and influences neuronal excitability in isolated body motor circuits over tens of seconds to minutes, but it remains unknown how and over what time scale DA-DN activity relates to movement in behaving animals. To address this question, we identified DA-DNs in the Drosophila brain and developed an electrophysiological preparation to record and manipulate the activity of these cells during behavior. We find that DA-DN spike rates are rapidly modulated during a subset of leg movements and scale with the total speed of ongoing leg movements, whether occurring spontaneously or in response to stimuli. However, activating DA-DNs does not elicit leg movements in intact flies, nor do acute bidirectional manipulations of DA-DN activity affect the probability or speed of leg movements over a time scale of seconds to minutes. Our findings indicate that in the context of intact descending control, changes in DA-DN activity are not sufficient to influence ongoing leg movements and open the door to studies investigating how these cells interact with other descending and local neuromodulatory inputs to influence body motor output.