GABA release by hippocampal astrocytes

10 p.

Intracellular Ca2+ release through ryanodine receptors contributes to AMPA receptor-mediated mitochondrial dysfunction and ER stress in oligodendrocytes

Overactivation of ionotropic glutamate receptors in oligodendrocytes induces cytosolic Ca2+ overload and excitotoxic death, a process that contributes to demyelination and multiple sclerosis. Excitotoxic insults cause well-characterized mitochondrial alterations and endoplasmic reticulum (ER) dysfunction, which is not fully understood. In this study, we analyzed the contribution of ER-Ca2+ release through ryanodine receptors (RyRs) and inositol triphosphate receptors (IP(3)Rs) to excitotoxicity in oligodendrocytes in vitro. First, we observed that oligodendrocytes express all previously characterized RyRs and IP(3)Rs. Blockade of Ca2+-induced Ca2+ release by TMB-8 following alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate (AMPA) receptor-mediated insults attenuated both oligodendrocyte death and cytosolic Ca2+ overload. In turn, RyR inhibition by ryanodine reduced as well the Ca2+ overload whereas IP3R inhibition was ineffective. Furthermore, AMPA-triggered mitochondrial membrane depolarization, oxidative stress and activation of caspase-3, which in all instances was diminished by RyR inhibition. In addition, we observed that AMPA induced an ER stress response as revealed by alpha subunit of the eukaryotic initiation factor 2 alpha phosphorylation, overexpression of GRP chaperones and RyR-dependent cleavage of caspase-12. Finally, attenuating ER stress with salubrinal protected oligodendrocytes from AMPA excitotoxicity. Together, these results show that Ca2+ release through RyRs contributes to cytosolic Ca2+ overload, mitochondrial dysfunction, ER stress and cell death following AMPA receptor-mediated excitotoxicity in oligodendrocytes. Cell Death and Disease (2010) 1, e54; doi:10.1038/cddis.2010.31; published online 15 July 2010

Electronic spectroscopy of propofol, propofol homomers ad their hydratated clusters

538 p.

Psychobiophysics of transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a technique that stimulates the brain using a magnetic coil placed on the scalp. Since it is applicable to humans non-invasively, directly interfering with neural electrical activity, it is potentially a good tool to study the direct relationship between perceptual experience and neural activity. However, it has been difficult to produce a clear perceptible phenomenon with TMS of sensory areas, especially using a single magnetic pulse. Also, the biophysical mechanisms of magnetic stimulation of single neurons have been poorly understood.

In the psychophysical part of this thesis, perceptual phenomena induced by TMS of the human visual cortex are demonstrated as results of the interactions with visual inputs. We first introduce a method to create a hole, or a scotoma, in a flashed, large-field visual pattern using single-pulse TMS. Spatial aspects of the interactions are explored using the distortion effect of the scotoma depending on the visual pattern, which can be luminance-defined or illusory. Its similarity to the distortion of afterimages is also discussed. Temporal interactions are demonstrated in the filling-in of the scotoma with temporally adjacent visual features, as well as in the effective suppression of transient visual features. Also, paired-pulse TMS is shown to lead to different brightness modulations in transient and sustained visual stimuli.

In the biophysical part, we first develop a biophysical theory to simulate the effect of magnetic stimulation on arbitrary neuronal structure. Computer simulations are performed on cortical neuron models with realistic structure and channels, combined with the current injection that simulates magnetic stimulation. The simulation results account for general and basic characteristics of the macroscopic effects of TMS including our psychophysical findings, such as a long inhibitory effect, dependence on the background activity, and dependence on the direction of the induced electric field.

The perceptual effects and the cortical neuron model presented here provide foundations for the study of the relationship between perception and neural activity. Further insights would be obtained from extension of our model to neuronal networks and psychophysical studies based on predictions of the biophysical model.

Neural representation of auditory temporal structure

Neurons in the songbird forebrain nucleus HVc are highly sensitive to auditory temporal context and have some of the most complex auditory tuning properties yet discovered. HVc is crucial for learning, perceiving, and producing song, thus it is important to understand the neural circuitry and mechanisms that give rise to these remarkable auditory response properties. This thesis investigates these issues experimentally and computationally.

Extracellular studies reported here compare the auditory context sensitivity of neurons in HV c with neurons in the afferent areas of field L. These demonstrate that there is a substantial increase in the auditory temporal context sensitivity from the areas of field L to HVc. Whole-cell recordings of HVc neurons from acute brain slices are described which show that excitatory synaptic transmission between HVc neurons involve the release of glutamate and the activation of both AMPA/kainate and NMDA-type glutamate receptors. Additionally, widespread inhibitory interactions exist between HVc neurons that are mediated by postsynaptic GABA_A receptors. Intracellular recordings of HVc auditory neurons in vivo provides evidence that HV c neurons encode information about temporal structure using a variety of cellular and synaptic mechanisms including syllable-specific inhibition, excitatory post-synaptic potentials with a range of different time courses, and burst-firing, and song-specific hyperpolarization.

The final part of this thesis presents two computational approaches for representing and learning temporal structure. The first method utilizes comput ational elements that are analogous to temporal combination sensitive neurons in HVc. A network of these elements can learn using local information and lateral inhibition. The second method presents a more general framework which allows a network to discover mixtures of temporal features in a continuous stream of input.

Latent variable models for neural data analysis

The brain is perhaps the most complex system to have ever been subjected to rigorous scientific investigation. The scale is staggering: over 10^11 neurons, each making an average of 10^3 synapses, with computation occurring on scales ranging from a single dendritic spine, to an entire cortical area. Slowly, we are beginning to acquire experimental tools that can gather the massive amounts of data needed to characterize this system. However, to understand and interpret these data will also require substantial strides in inferential and statistical techniques. This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis.

It is divided into two parts. The first begins with an exposition of the general techniques of latent variable modeling. A new, extremely general, optimization algorithm is proposed - called Relaxation Expectation Maximization (REM) - that may be used to learn the optimal parameter values of arbitrary latent variable models. This algorithm appears to alleviate the common problem of convergence to local, sub-optimal, likelihood maxima. REM leads to a natural framework for model size selection; in combination with standard model selection techniques the quality of fits may be further improved, while the appropriate model size is automatically and efficiently determined. Next, a new latent variable model, the mixture of sparse hidden Markov models, is introduced, and approximate inference and learning algorithms are derived for it. This model is applied in the second part of the thesis.

The second part brings the technology of part I to bear on two important problems in experimental neuroscience. The first is known as spike sorting; this is the problem of separating the spikes from different neurons embedded within an extracellular recording. The dissertation offers the first thorough statistical analysis of this problem, which then yields the first powerful probabilistic solution. The second problem addressed is that of characterizing the distribution of spike trains recorded from the same neuron under identical experimental conditions. A latent variable model is proposed. Inference and learning in this model leads to new principled algorithms for smoothing and clustering of spike data.

Responses to auditory stimuli in macaque lateral intraparietal area

The lateral intraparietal area (LIP) of macaque posterior parietal cortex participates in the sensorimotor transformations underlying visually guided eye movements. Area LIP has long been considered unresponsive to auditory stimulation. However, recent studies have shown that neurons in LIP respond to auditory stimuli during an auditory-saccade task, suggesting possible involvement of this area in auditory-to-oculomotor as well as visual-to-oculomotor processing. This dissertation describes investigations which clarify the role of area LIP in auditory-to-oculomotor processing.

Extracellular recordings were obtained from a total of 332 LIP neurons in two macaque monkeys, while the animals performed fixation and saccade tasks involving auditory and visual stimuli. No auditory activity was observed in area LIP before animals were trained to make saccades to auditory stimuli, but responses to auditory stimuli did emerge after auditory-saccade training. Auditory responses in area LIP after auditory-saccade training were significantly stronger in the context of an auditory-saccade task than in the context of a fixation task. Compared to visual responses, auditory responses were also significantly more predictive of movement-related activity in the saccade task. Moreover, while visual responses often had a fast transient component, responses to auditory stimuli in area LIP tended to be gradual in onset and relatively prolonged in duration.

Overall, the analyses demonstrate that responses to auditory stimuli in area LIP are dependent on auditory-saccade training, modulated by behavioral context, and characterized by slow-onset, sustained response profiles. These findings suggest that responses to auditory stimuli are best interpreted as supramodal (cognitive or motor) responses, rather than as modality-specific sensory responses. Auditory responses in area LIP seem to reflect the significance of auditory stimuli as potential targets for eye movements, and may differ from most visual responses in the extent to which they arc abstracted from the sensory parameters of the stimulus.

Analysis of temporal structure in spike trains of visual cortical area MT

The temporal structure of neuronal spike trains in the visual cortex can provide detailed information about the stimulus and about the neuronal implementation of visual processing. Spike trains recorded from the macaque motion area MT in previous studies (Newsome et al., 1989a; Britten et al., 1992; Zohary et al., 1994) are analyzed here in the context of the dynamic random dot stimulus which was used to evoke them. If the stimulus is incoherent, the spike trains can be highly modulated and precisely locked in time to the stimulus. In contrast, the coherent motion stimulus creates little or no temporal modulation and allows us to study patterns in the spike train that may be intrinsic to the cortical circuitry in area MT. Long gaps in the spike train evoked by the preferred direction motion stimulus are found, and they appear to be symmetrical to bursts in the response to the anti-preferred direction of motion. A novel cross-correlation technique is used to establish that the gaps are correlated between pairs of neurons. Temporal modulation is also found in psychophysical experiments using a modified stimulus. A model is made that can account for the temporal modulation in terms of the computational theory of biological image motion processing. A frequency domain analysis of the stimulus reveals that it contains a repeated power spectrum that may account for psychophysical and electrophysiological observations.

Some neurons tend to fire bursts of action potentials while others avoid burst firing. Using numerical and analytical models of spike trains as Poisson processes with the addition of refractory periods and bursting, we are able to account for peaks in the power spectrum near 40 Hz without assuming the existence of an underlying oscillatory signal. A preliminary examination of the local field potential reveals that stimulus-locked oscillation appears briefly at the beginning of the trial.

Macaque lateral intraparietal area and oculomotor behaviors

Neurons in the primate lateral intraparietal area (area LIP) carry visual, saccade-related and eye position activities. The visual and saccade activities are anchored in a retinotopic framework and the overall response magnitude is modulated by eye position. It was proposed that the modulation by eye position might be the basis of a distributed coding of target locations in a head-centered space. Other recording studies demonstrated that area LIP is involved in oculomotor planning. These results overall suggest that area LIP transforms sensory information for motor functions. In this thesis I further explore the role of area LIP in processing saccadic eye movements by observing the effects of reversible inactivation of this area. Macaque monkeys were trained to do visually guided and memory saccades and a double saccade task to examine the use of eye position signal. Finally, by intermixing visual saccades with trials in which two targets were presented at opposite sides of the fixation point, I examined the behavior of visual extinction.

In chapter 2, I will show that lesion of area LIP results in increased latency of contralesional visual and memory saccades. Contralesional memory saccades are also hypometric and slower in velocity. Moreover, the impairment of memory saccades does not vary with the duration of the delay period. This suggests that the oculomotor deficits observed after inactivation of area LIP is not due to the disruption of spatial memory.

In chapter 3, I will show that lesion of area LIP does not severely affect the processing of spontaneous eye movement. However, the monkeys made fewer contralesional saccades and tended to confine their gaze to the ipsilesional field after inactivation of area LIP. On the other hand, lesion of area LIP results in extinction of the contralesional stimulus. When the initial fixation position was varied so that the retinal and spatial locations of the targets could be dissociated, it was found that the extinction behavior could best be described in a head-centered coordinate.

In chapter 4, I will show that inactivation of area LIP disrupts the use of eye position signal to compute the second movement correctly in the double saccade task. If the first saccade steps into the contralesional field, the error rate and latency of the second saccade are both increased. Furthermore, the direction of the first eye movement largely does not have any effect on the impairment of the second saccade. I will argue that this study provides important evidence that the extraretinal signal used for saccadic localization is eye position rather than a displacement vector.

In chapter 5, I will demonstrate that in parietal monkeys the eye drifts toward the lesion side at the end of the memory saccade in darkness. This result suggests that the eye position activity in the posterior parietal cortex is active in nature and subserves gaze holding.

Overall, these results further support the view that area LIP neurons encode spatial locations in a craniotopic framework and is involved in processing voluntary eye movements.

The central nervous control of walking in the locust, Schistocerca Americana

Rhythmic motor behaviors in all animals appear to be under the control of "central pattern generator" circuits, neural circuits which can produce output patterns appropriate for behavior even when isolated from their normal peripheral inputs. Insects have been a useful model system in which to study the control of legged terrestrial locomotion. Much is known about walking in insects at the behavioral level, but to date there has been no clear demonstration that a central pattern generator for walking exists. The focus of this thesis is to explore the central neural basis for locomotion in the locust, Schistocerca americana.

Rhythmic motor patterns could be evoked in leg motor neurons of isolated thoracic ganglia of locusts by the muscarinic agonist pilocarpine. These motor patterns would be appropriate for the movement of single legs during walking. Rhythmic patterns could be evoked in all three thoracic ganglia, but the segmental rhythms differed in their sensitivities to pilocarpine, their frequencies, and the phase relationships of motor neuron antagonists. These different patterns could be generated by a simple adaptable model circuit, which was both simulated and implemented in VLSI hardware. The intersegmental coordination of leg motor rhythms was then examined in preparations of isolated chains of thoracic ganglia. Correlations between motor patterns in different thoracic ganglia indicated that central coupling between segmental pattern generators is likely to contribute to the coordination of the legs during walking.

The work described here clearly demonstrates that segmental pattern generators for walking exist in insects. The pattern generators produce motor outputs which are likely to contribute to the coordination of the joints of a limb, as well as the coordination of different limbs. These studies lay the groundwork for further studies to determine the relative contributions of central and sensory neural mechanisms to terrestrial walking.

Neural routing circuits for forming invariant representations of visual objects

This thesis presents a biologically plausible model of an attentional mechanism for forming position- and scale-invariant representations of objects in the visual world. The model relies on a set of control neurons to dynamically modify the synaptic strengths of intra-cortical connections so that information from a windowed region of primary visual cortex (Vl) is selectively routed to higher cortical areas. Local spatial relationships (i.e., topography) within the attentional window are preserved as information is routed through the cortex, thus enabling attended objects to be represented in higher cortical areas within an object-centered reference frame that is position and scale invariant. The representation in V1 is modeled as a multiscale stack of sample nodes with progressively lower resolution at higher eccentricities. Large changes in the size of the attentional window are accomplished by switching between different levels of the multiscale stack, while positional shifts and small changes in scale are accomplished by translating and rescaling the window within a single level of the stack. The control signals for setting the position and size of the attentional window are hypothesized to originate from neurons in the pulvinar and in the deep layers of visual cortex. The dynamics of these control neurons are governed by simple differential equations that can be realized by neurobiologically plausible circuits. In pre-attentive mode, the control neurons receive their input from a low-level "saliency map" representing potentially interesting regions of a scene. During the pattern recognition phase, control neurons are driven by the interaction between top-down (memory) and bottom-up (retinal input) sources. The model respects key neurophysiological, neuroanatomical, and psychophysical data relating to attention, and it makes a variety of experimentally testable predictions.

Cytokine control of neuronal phenotype

Diffusible proteins regulate neural development at a variety of stages. Using a novel neuronal culture assay, I have identified several cytokines that regulate the expression of neurotransmitters and neuropeptides in sympathetic neurons. These cytokines fall into two families. The first group is termed the neuropoietic cytokines, while including CDF/LIF, CNTF, OSM and GPA, induces expression of the same set of neuropeptide mRNAs in cultured sympathetic neurons. These four factors not only exhibit similar biological activities; they also share a predicted secondary structure and bind to a signal-transducing receptor subunit in common with IL-6 and IL-11. The latter two cytokines display a weaker activity in this assay. In addition, I find that several members of the TGF-β superfamily, activin A, BMP-2, and BMP-6, have a selective overlap with the neuropoietic family in the spectrum of neuropeptides that these cytokines induce in sympathetic neurons. Different patterns of neuropeptides induced by the TGF-β family members, however, demonstrate that the activities of these cytokines are distinct from those of the neuropoietic family. Another 30 cytokines are without detectable effect in this neuronal assay.

Activin A induces a set of neurotransmitters and neuropeptides that is somewhat similar to the phenotype of sympathetic neurons innervating sweat glands in rat footpads. In situ hybridization and RNase protection were carried out to test whether activins were involved in the phenotypic transition when sympathetic neurons contact sweat glands. I find that activin mRNA is present in both cholinergic and noradrenergic targets. Moreover, homogenates of footpads do not contain activin-like activity in the neuronal assay in vitro. Taken together, these data do not support activins as the best candidates for the sweat gland factor.

Several novel factors that regulate neuropeptide expression exist in heart cell conditioned medium. I attempted to purify these factors in collaboration with Dr. Jane Talvenheimo. Our results suggest that these factors are sensitive to the storage conditions used. Several modifications of purification strategy are discussed.

Surface markers of regionalization in the vertebrate nervous system

In order to identify new molecules that might play a role in regional specification of the nervous system, we generated and characterized monoclonal antibodies (mAbs) that have positionally-restricted labeling patterns.

The FORSE-1 mAb was generated using a strategy designed to produce mAbs against neuronal cell surface antigens that might be regulated by regionally-restricted transcription factors in the developing central nervous system (CNS). FORSE-1 staining is enriched in the forebrain as compared to the rest of the CNS until E18. Between E11.5-E13.5, only certain areas of the forebrain are labeled. There is also a dorsoventrally-restricted region of labeling in the hindbrain and spinal cord. The mAb labels a large proteoglycan-like cell-surface antigen (>200 kD). The labeling pattern of FORSE-1 is conserved in various mammals and in chick.

To determine whether the FORSE-1 labeling pattern is similar to that of known transcription factors, the expression of BF-1 and Dlx-2 was compared with FORSE-1. There is a striking overlap between BF-1 and FORSE-1 in the telencephalon. In contrast, FORSE-1 and Dlx-2 have very different patterns of expression in the forebrain, suggesting that regulation by Dlx-2 alone cannot explain the distribution of FORSE-1. They do, however, share some sharp boundaries in the diencephalon. In addition, FORSE-1 identifies some previously unknown boundaries in the developing forebrain. Thus, FORSE-1 is a new cell surface marker that can be used to subdivide the embryonic forebrain into regions smaller than previously described, providing further complexity necessary for developmental patterning.

I also studied the expression of the cell surface protein CD9 in the developing and adult rat nervous system. CD9 is implicated in intercellular signaling and cell adhesion in the hematopoetic system. In the nervous system, CD9 may perform similar functions in early sympathetic ganglia, chromaffin cells, and motor neurons, all of which express the protein. The presence of CD9 on the surfaces of Schwann cells and axons at the appropriate time may allow the protein to participate in the cellular interactions involved in myelination.

State-dependent modulation of neuronal circuits in C. elegans sleep

C. elegans is a compact system of 302 neurons with identifiable and mapped connections that makes it ideal for systems analysis. This work is a demonstration of what I have been able to learn about the nature of state-specific modulation and reversibility during a state called lethargus, a sleep-like state in the worm. I begin with description about the nervous system of the worm, the nature of sleep in the worm, the questions about behavior and its apparent circuit properties, the tools available and used to manipulate the nervous system, and what I have been able to learn from these studies. I end with clues that the physiology helps to teach us about the dynamics of state specific modulation, what makes sleep so different from other states, and how we can use these measurements to understand which modulators, neurotransmitters, and channels can be used to create different dynamics in a simple model system.

Studying conscious and unconscious vision with functional Magnetic Resonance Imaging : the BOLD promise

Waking up from a dreamless sleep, I open my eyes, recognize my wife’s face and am filled with joy. In this thesis, I used functional Magnetic Resonance Imaging (fMRI) to gain insights into the mechanisms involved in this seemingly simple daily occurrence, which poses at least three great challenges to neuroscience: how does conscious experience arise from the activity of the brain? How does the brain process visual input to the point of recognizing individual faces? How does the brain store semantic knowledge about people that we know? To start tackling the first question, I studied the neural correlates of unconscious processing of invisible faces. I was unable to image significant activations related to the processing of completely invisible faces, despite existing reports in the literature. I thus moved on to the next question and studied how recognition of a familiar person was achieved in the brain; I focused on finding invariant representations of person identity – representations that would be activated any time we think of a familiar person, read their name, see their picture, hear them talk, etc. There again, I could not find significant evidence for such representations with fMRI, even in regions where they had previously been found with single unit recordings in human patients (the Jennifer Aniston neurons). Faced with these null outcomes, the scope of my investigations eventually turned back towards the technique that I had been using, fMRI, and the recently praised analytical tools that I had been trusting, Multivariate Pattern Analysis. After a mostly disappointing attempt at replicating a strong single unit finding of a categorical response to animals in the right human amygdala with fMRI, I put fMRI decoding to an ultimate test with a unique dataset acquired in the macaque monkey. There I showed a dissociation between the ability of fMRI to pick up face viewpoint information and its inability to pick up face identity information, which I mostly traced back to the poor clustering of identity selective units. Though fMRI decoding is a powerful new analytical tool, it does not rid fMRI of its inherent limitations as a hemodynamics-based measure.