Long-term stability of the hippocampal neural code as a substrate for episodic memory

The hippocampus supports the initial formation and recall of episodic memories, as well as the consolidation of short-term into long-term memories. The ability of hippocampal neurons to rapidly change their connection strengths during learning and maintain these changes over long time-scales may provide a mechanism supporting memory. However, little evidence currently exists concerning the long-term stability of information contained in hippocampal neuronal activity, likely due to limitations in recording extracellular activity in vivo from the same neurons across days. In this thesis I employ calcium imaging in freely moving mice to longitudinally track the activity of large ensembles of hippocampal neurons. Using this technology, I explore the proposal that long-term stability of hippocampal information provides a substrate for episodic memory in three different ways. First, I tested the hypothesis that hippocampal activity should remain stable across days in the absence of learning. I found that place cells – hippocampal neurons containing information about a mouse’s position – maintain a coherent map relative to each other across long time-scales but exhibit instability in how they anchor to the external world. Furthermore, I found that coherent maps were frequently used to represent a different environment and incorporated learning via changes in a subset of neurons. Next, I examined how learning a spatial alternation task impacts neuron stability. I found that splitter neurons whose activity patterns reflected an animal’s future or past trajectory emerged relatively slowly when compared to place cells. However, splitter neurons remained more consistently active and relayed more consistent spatial information across days than did place cells, suggesting that the utility of information provided by a neuron influences its long term stability. Last, I investigated how protein synthesis, known to be necessary for long-term maintenance of changes in hippocampal neuron connection strengths and for proper memory consolidation, influences their activity patterns across days. I found that along with blocking memory consolidation, inhibiting protein synthesis induced a profound, long-lasting decrease in neuronal activity up to two days later. These results combined demonstrate the importance of rapid, lasting changes in the hippocampal neuronal code to supporting long-term memory

Diagnostic utility of MRS values in hippocampus formation of medically intractable temporal lobe epilepsy patients in HUSM

Background: Hippocampal formation analysis by magnetic resonance imaging (MRI) and proton MR spectroscopy (1H-MRS) is useful for lateralization of seizure focus and diagnosis of medical intractable temporal lobe epilepsy (MTLE). The present study assessed the diagnostic utility of MRS, MRI, and combinatorial MRI-MRS findings from hippocampal formation of MTLE patients. Methods: A total of 14 MTLE patients and 14 control subjects were underwent MRI and MRS examination on hippocampal formation. The patients were clinically diagnosed as MTLE patients and revealed unilataralization by electroencephalogram (EEG) examination. The patient was ensured seizure free for a minimum period of 24 hours before the analyses to avoid possible effect of acute post ictal changes. Results: There were significant (p<0.05) decrement in NAA/Cr and increment in Cho/Cr in ipsilateral hippocampal formation of MTLE patients compared to that of contralateral findings and control group, separately. In the evaluation of diagnostic utility of individual MRS value for detection of epileptic focus in hippocampal formation, only NAA/Cr and NAA/Cho revealed significant moderate and fair agreements with the EEG lateralization findings, respectively. Analysis by combinatorial MRS values or MRI alone revealed fair and moderate agreement with EEG lateralization findings, respectively. Analysis using combinatorial MRS+MRI showed substantial agreement with with EEG lateralization findings. The positive andnegative percentage agreements with EEG lateralization findings were 79% and 93%, respectively. Conclusion: Combinatorial MRS+MRI analysis improved the lateralization of epileptic focus and diagnosis of MTLE

Network mechanisms underlying stable motor actions

While we can learn to produce stereotyped movements and maintain this ability for years, it is unclear how populations of individual neurons change their firing properties to coordinate these skills. This has been difficult to address because there is a lack of tools that can monitor populations of single neurons in freely behaving animals for the durations required to remark on their tuning. This thesis is divided into two main directions- device engineering and systems neuroscience. The first section describes the development of an electrode array comprised of tiny self-splaying carbon fibers that are small and flexible enough to avoid the immune response that typically limits electrophysiological recordings. I also describe the refinement of a head-mounted miniature microscope system, optimized for multi-month monitoring of cells expressing genetically encoded calcium indicators in freely behaving animals. In the second section, these tools are used to answer basic systems neuroscience questions in an animal with one of the most stable, complex learned behaviors in the animal kingdom: songbirds. This section explores the functional organization and long-term network stability of HVC, the songbird premotor cortical microcircuit that controls song. Our results reveal that neural activity in HVC is correlated with a length scale of 100um. At this mesocopic scale, basal-ganglia projecting excitatory neurons, on average, fire at a specific phase of a local 30Hz network rhythm. These results show that premotor cortical activity is inhomogeneous in time and space, and that a mesoscopic dynamical pattern underlies the generation of the neural sequences controlling song. At this mesoscopic level, neural coding is stable for weeks and months. These ensemble patterns persist after peripheral nerve damage, revealing that sensory-motor correspondence is not required to maintain the stability of the underlying neural ensemble. However, closer examination of individual excitatory neurons reveals that the participation of cells can change over the timescale of days- with particularly large shifts occurring over instances of sleep. Our findings suggest that fine-scale drift of projection neurons, stabilized by mesoscopic level dynamics dominated by inhibition, forms the mechanistic basis of memory maintenance and and motor stability

Learning cognitive maps: Finding useful structure in an uncertain world

In this chapter we will describe the central mechanisms that influence how people learn about large-scale space. We will focus particularly on how these mechanisms enable people to effectively cope with both the uncertainty inherent in a constantly changing world and also with the high information content of natural environments. The major lessons are that humans get by with a less is more approach to building structure, and that they are able to quickly adapt to environmental changes thanks to a range of general purpose mechanisms. By looking at abstract principles, instead of concrete implementation details, it is shown that the study of human learning can provide valuable lessons for robotics. Finally, these issues are discussed in the context of an implementation on a mobile robot. © 2007 Springer-Verlag Berlin Heidelberg

Representational dynamics across multiple timescales in human cortical networks

Human cognition occurs at multiple timescales, including immediate processing of the ongoing experiences and slowly drifting higher-level thoughts. To understand how the brain selects and represents these various types of information to guide behavior, this thesis examined representational content within sensory regions, multiple demand (MD) network, and default mode network (DMN). Chapter 1 provides a background review of the current literature. It begins by reviewing experimental investigations of component visual processes that unfold over time. Next, the MD network is introduced as a collection of frontal and parietal regions involved in implementing cognitive control by assembling the required operations for task-relevant behavior. Finally, the DMN is introduced in the context of temporal processing hierarchies, with focus on its representation of situation models summarizing interactions among entities and the environment. The first experiment, presented in Chapter 2, used EEG/MEG to track multiple component processes of selective attention. Five distinct processing operations with different time-courses were quantified, including representation of visual display properties, target location, target identity, behavioral significance, and finally, possible reactivation of the attentional template. Chapter 3 used fMRI to examine neural representations of task episodes, which are temporally organized sequences of steps that occur within a given context. It was found that MD and visual regions showed sensitivity to the fine structure of the contents within a task. DMN regions showed gradual change throughout the entire task, with increased activation at the offset of the entire episode. Chapter 4 analyzed activation profiles of DMN regions using six diverse tasks to examine their functional convergence during social, episodic, and self-referential thought. Results supported proposals of separate subsystems, yet also suggest integration within the DMN. The final chapter, Chapter 5, provides an extended discussion of theoretical concepts related to the three experiments and proposes possible avenues for further research

Functional Organization of the Brain at Rest and During Complex Tasks Using fMRI

How and why functional connectivity (FC), which captures the correlations among brain regions and/or networks, differs in various brain states has been incompletely understood. I review high-level background on this problem and how it relates to 1) the contributions of task-evoked activity, 2) white-matter fMRI, and 3) disease states in Chapter 1. In Chapter 2, based on the notion that brain activity during a task reflects an unknown mixture of spontaneous activity and task-evoked responses, we uncovered that the difference in FC between a task state (a naturalistic movie) and resting state only marginally (3-15%) reflects task-evoked connectivity. Instead, these changes may reflect changes in spontaneously emerging networks. In Chapter 3, we were able to show subtle task-related differences in the white matter using fMRI, which has only rarely been used to study functions in this tissue type. In doing so, we also demonstrated that white matter independent components were also hierarchically organized into axonal fiber bundles, challenging the conventional practice of taking white-matter signals as noise or artifacts. Finally, in Chapter 4, we examined the utility of combining FC with task-activation studies in uncovering changes in brain activity during preclinical Alzheimer\u27s Disease (mild cognitive impairment (MCI) and subjective cognitive decline (SCD) populations), based on data collected at the Indiana University School of Medicine. We found a reduction in neural task-based activations and resting-state FC that appeared to be directly related to diagnostic severity. Taken together, the work presented in this dissertation paves the way for a novel framework for understanding neural dynamics in health and disease

Single molecule tracking with light sheet microscopy

The work presented here concentrates on light sheet based fluorescence microscopy (LSFM) and its application to single molecule tracking. In LSFM the sample is illuminated perpendicular to the detection axis with a thin light sheet. In this manner a simple optical sectioning microscope is created, because only the focal plane of the detection optics is illuminated and no out-of-focus fluorescence is generated. This results in an enhancement of the signal-to-noise-ratio and combined with the high acquisition speed of a video microscopy a powerful tool is created to study single molecule dynamics on a millisecond timescale, A completely new setup was designed and constructed, that combines light sheet illumination technique with single molecule detection ability. Theoretical calculations and quantitative measurements of the illumination light sheet thickness (2-3 µm thick) and the microscope point spread function were performed. A direct comparison of LSFM and epi-illumination of model samples with intrinsic background fluorescence illustrated the clear contrast improvement of LSFM for thick samples. Single molecule detection is limited by the number of photons emitted by a single fluorophore per observation time. So, the ability to track single molecules is dependent on molecule speed, background, detection sensitivity and frame rate. The imaging speed with the concomitant high signal-to-noise ratio that could be realized within the setup was unprecedented until then. It permitted the observation of single protein trajectories in aqueous solution with a diffusion coefficient greater than 100 µm²/s. The in vivo imaging of single molecules in thick biological samples was demonstrated in living salivary gland cell nuclei of Chironomus tentans larvae. These cell nuclei afford exceptional possibilities for the study of RNA mobility, but provide a microscopic challenge with a diameter of 50-75 µm and up 200 µm deep within the sample. To image the intranuclear mobility of individual messenger RNA particles, they were indirectly labeled via the fluorescently labeled RNA binding protein hrp36. Thus it was possible to identify at least three different diffusion modes of the mRNA particles and indirectly measure the nuclear viscosity. A high flexibility and easy adaptation of the optical sectioning thickness is required to visualize biological samples of various sizes. Often, however, the sheet geometry is fixed, whereas it would be advantageous to adjust the sheet geometry to specimens of different dimensions. Therefore, an afocal cylindrical zoom lens system comprising only 5 lenses and a total system length of less than 160 mm was developed. Two movable optical elements were directly coupled, so that the zoom factor could be adjusted from 1x to 6.3x by a single motor. Polytene chromosomes of salivary gland cell nuclei of C.tentans larvae were imaged in vivo to demonstrate the advantages in image contrast by imaging with different light sheet dimensions. The light sheet microscope introduced in this thesis proofed its suitability for in vivo single molecule imaging deep within a biological sample. It has the potential to reveal new dynamic single molecule interactions in vivo and enables new studies and experiments of intracellular processes

The development and application of structural priors for diffuse optical imaging in infants from newborn to two years of age

This thesis describes the development and application of age-appropriate structural priors to improve the localisation accuracy of diffuse optical tomography (DOT) approaches in infants aged from birth to two years of age. Knowledge of the target cranial anatomy, known as a structural prior, is required to produce three-dimensional images localising concentration changes to the cortex. A structural prior would ideally be subject-specific, i.e. derived from structural magnetic resonance imaging (MRI) data from each specific subject. Requiring a structural scan from every infant participant, however, is not feasible and undermines many of the benefits of DOT. A review was conducted to catalogue available infant structural MRI data, and selected data was then used to produce structural priors for infants aged 1- to 24-months. Conventional analyses using functional near-infrared spectroscopy (fNIRS) implicitly assume that head size and array position are constant across infants. Using DOT, the validity of assuming these parameters constant in a longitudinal infant cohort was investigated. The results show that this assumption is reasonable at the group-level in infants aged 5- to 12-months but becomes less valid for smaller group sizes. A DOT approach was determined to illicit more subtle effects of activation, particularly for smaller group sizes and expected responses. Using state-of-the-art MRI data from the Developing Human Connectome Project, a database of structural priors of the neonatal head was produced for infants aged pre-term to term-equivalent age. A leave-one-out approach was used to determine how best to find a match between a given infant and a model from the database, and how best to spatially register the model to minimise the anatomical and localisation errors relative to subject-specific anatomy. Model selection based on the 10/20 scalp positions was determined to be the best method (of those based on external features of the head) to minimise these errors