Gap junction plasticity as a mechanism to regulate network-wide oscillations

Cortical oscillations are thought to be involved in many cognitive functions and processes. Several mechanisms have been proposed to regulate oscillations. One prominent but understudied mechanism is gap junction coupling. Gap junctions are ubiquitous in cortex between GABAergic interneurons. Moreover, recent experiments indicate their strength can be modified in an activity-dependent manner, similar to chemical synapses. We hypothesized that activity-dependent gap junction plasticity acts as a mechanism to regulate oscillations in the cortex. We developed a computational model of gap junction plasticity in a recurrent cortical network based on recent experimental findings. We showed that gap junction plasticity can serve as a homeostatic mechanism for oscillations by maintaining a tight balance between two network states: asynchronous irregular activity and synchronized oscillations. This homeostatic mechanism allows for robust communication between neuronal assemblies through two different mechanisms: transient oscillations and frequency modulation. This implies a direct functional role for gap junction plasticity in information transmission in cortex

The “conscious pilot”—dendritic synchrony moves through the brain to mediate consciousness

Cognitive brain functions including sensory processing and control of behavior are understood as “neurocomputation” in axonal–dendritic synaptic networks of “integrate-and-fire” neurons. Cognitive neurocomputation with consciousness is accompanied by 30- to 90-Hz gamma synchrony electroencephalography (EEG), and non-conscious neurocomputation is not. Gamma synchrony EEG derives largely from neuronal groups linked by dendritic–dendritic gap junctions, forming transient syncytia (“dendritic webs”) in input/integration layers oriented sideways to axonal–dendritic neurocomputational flow. As gap junctions open and close, a gamma-synchronized dendritic web can rapidly change topology and move through the brain as a spatiotemporal envelope performing collective integration and volitional choices correlating with consciousness. The “conscious pilot” is a metaphorical description for a mobile gamma-synchronized dendritic web as vehicle for a conscious agent/pilot which experiences and assumes control of otherwise non-conscious auto-pilot neurocomputation

Generating brain waves, the power of astrocytes

Synchronization of neuronal activity in the brain underlies the emergence of neuronal oscillations termed “brain waves”, which serve various physiological functions and correlate with different behavioral states. It has been postulated that at least ten distinct mechanisms are involved in the formulation of these brain waves, including variations in the concentration of extracellular neurotransmitters and ions, as well as changes in cellular excitability. In this mini review we highlight the contribution of astrocytes, a subtype of glia, in the formation and modulation of brain waves mainly due to their close association with synapses that allows their bidirectional interaction with neurons, and their syncytium-like activity via gap junctions that facilitate communication to distal brain regions through Ca2+ waves. These capabilities allow astrocytes to regulate neuronal excitability via glutamate uptake, gliotransmission and tight control of the extracellular K+ levels via a process termed K+ clearance. Spatio-temporal synchrony of activity across neuronal and astrocytic networks, both locally and distributed across cortical regions, underpins brain states and thereby behavioral states, and it is becoming apparent that astrocytes play an important role in the development and maintenance of neural activity underlying these complex behavioral states

The Dynamic Role of Breathing and Cellular Membrane Potentials in the Experience of Consciousness

Understanding the mechanics of consciousness remains one of the most important challenges in modern cognitive science. One key step toward understanding consciousness is to associate unconscious physiological processes with subjective experiences of sensory, motor, and emotional contents. This article explores the role of various cellular membrane potential differences and how they give rise to the dynamic infrastructure of conscious experience. This article explains that consciousness is a body-wide, biological process not limited to individual organs because the mind and body are unified as one entity; therefore, no single location of consciousness can be pinpointed. Consciousness exists throughout the entire body, and unified consciousness is experienced and maintained through dynamic repolarization during inhalation and expiration. Extant knowledge is reviewed to provide insight into how differences in cellular membrane potential play a vital role in the triggering of neural and non-neural oscillations. The role of dynamic cellular membrane potentials in the activity of the central nervous system, peripheral nervous system, cardiorespiratory system, and various other tissues (such as muscles and sensory organs) in the physiology of consciousness is also explored. Inspiration and expiration are accompanied by oscillating membrane potentials throughout all cells and play a vital role in subconscious human perception of feelings and states of mind. In addition, the role of the brainstem, hypothalamus, and complete nervous system (central, peripheral, and autonomic)within the mind-body space combine to allow consciousness to emerge and to come alive. This concept departs from the notion that the brain is the only organ that gives rise to consciousness

Emergence of Spatio-Temporal Pattern Formation and Information Processing in the Brain.

The spatio-temporal patterns of neuronal activity are thought to underlie cognitive functions, such as our thoughts, perceptions, and emotions. Neurons and glial cells, specifically astrocytes, are interconnected in complex networks, where large-scale dynamical patterns emerge from local chemical and electrical signaling between individual network components. How these emergent patterns form and encode for information is the focus of this dissertation. I investigate how various mechanisms that can coordinate collections of neurons in their patterns of activity can potentially cause the interactions across spatial and temporal scales, which are necessary for emergent macroscopic phenomena to arise. My work explores the coordination of network dynamics through pattern formation and synchrony in both experiments and simulations. I concentrate on two potential mechanisms: astrocyte signaling and neuronal resonance properties. Due to their ability to modulate neurons, we investigate the role of astrocytic networks as a potential source for coordinating neuronal assemblies. In cultured networks, I image patterns of calcium signaling between astrocytes, and reproduce observed properties of the network calcium patterning and perturbations with a simple model that incorporates the mechanisms of astrocyte communication. Understanding the modes of communication in astrocyte networks and how they form spatial temporal patterns of their calcium dynamics is important to understanding their interaction with neuronal networks. We investigate this interaction between networks and how glial cells modulate neuronal dynamics through microelectrode array measurements of neuronal network dynamics. We quantify the spontaneous electrical activity patterns of neurons and show the effect of glia on the neuronal dynamics and synchrony. Through a computational approach I investigate an entirely different theoretical mechanism for coordinating ensembles of neurons. I show in a computational model how biophysical resonance shifts in individual neurons can interact with the network topology to influence pattern formation and separation. I show that sub-threshold neuronal depolarization, potentially from astrocytic modulation among other sources, can shift neurons into and out of resonance with specific bands of existing extracellular oscillations. This can act as a dynamic readout mechanism during information storage and retrieval. Exploring these mechanisms that facilitate emergence are necessary for understanding information processing in the brain.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111493/1/lshtrah_1.pd

Signalling properties at single synapses and within the interneuronal network in the CA1 region of the rodent hippocampus

Understanding how the complexity of connections among the neurons in the brain is established and modified in an experience- and activity-dependent way is a challenging task of Neuroscience. Although in the last decades many progresses have been made in characterising the basic mechanisms of synaptic transmission, a full comprehension of how information is transferred and processed by neurons has not been fully achieved. In the present study, theoretical tools and patch clamp experiments were used to further investigate synaptic transmission, focusing on quantal transmission at single synapses and on different types of signalling at the level of a particular interneuronal network in the CA1 area of the rodent hippocampus. The simultaneous release of more than one vesicle from an individual presynaptic active zone is a typical mechanism that can affect the strength and reliability of synaptic transmission. At many central synapses, however, release caused by a single presynaptic action potential is limited to one vesicle (univesicular release). The likelihood of multivesicular release at a particular synapse has been tied to release probability (Pr), and whether it can occur at Schaffer collateral\u2013CA1 synapses, at which Pr ranges widely, is controversial. In contrast with previous findings, proofs of multivesicular release at this synapse have been recently obtained at late developmental stages; however, in the case of newborn hippocampus, it is still difficult to find strong evidence in one direction or another. In order to address this point, in the first part of this study a simple and general stochastic model of synaptic release has been developed and analytically solved. The model solution gives analytical mathematical expressions relating basic quantal parameters with average values of quantities that can be measured experimentally. Comparison of these quantities with the experimental measures allows to determine the most probable values of the quantal parameters and to discriminate the univesicular from the multivesicular mode of glutamate release. The model has been validated with data previously collected at glutamatergic CA3-CA1 synapses in the hippocampus from newborn (P1-P5 old) rats. The results strongly support a multivesicular type of release process requiring a variable pool of immediately releasable vesicles. Moreover, computing quantities that are functions of the model parameters, the mean amplitude of the synaptic response to the release of a single vesicle (Q) was estimated to be 5-10 pA, in very good agreement with experimental findings. In addition, a multivesicular type of release was supported by various experimental evidences: a high variability of the amplitude of successes, with a coefficient of variation ranging from 0.12 to 0.73; an average potency ratio a2/a1 between the second and first response to a pair of stimuli bigger than 1; and changes in the potency of the synaptic response to the first stimulus when the release probability was modified by increasing or decreasing the extracellular calcium concentration. This work indicates that at glutamatergic CA3-CA1 synapses of the neonatal rat hippocampus a single action potential may induce the release of more than one vesicle from the same release site. In a more systemic approach to the analysis of communication between neurons, it is interesting to investigate more complex, network interactions. GABAergic interneurons constitute a heterogeneous group of cells which exert a powerful control on network excitability and are responsible for the oscillatory behaviour crucial for information processing in the brain. They have been differently classified according to their morphological, neurochemical and physiological characteristics. In the second part of this study, whole cell patch clamp recordings were used to further characterize, in transgenic mice expressing EGFP in a subpopulation of GABAergic interneurons containing somatostatin (GIN mice), the functional properties of EGFPpositive cells in stratum oriens of the CA1 region of the hippocampus, in slice cultures obtained from P8 old animals. These cells showed passive and active membrane properties similar to those found in stratum oriens interneurons projecting to stratum lacunosum-moleculare. Moreover, they exhibited different firing patterns which were maintained upon membrane depolarization: irregular (48%), regular (30%) and clustered (22%). Paired recordings from EGFP-positive cells often revealed electrical coupling (47% of the cases), which was abolished by carbenoxolone (200 mM). On average, the coupling coefficient was 0.21 \ub1 0.07. When electrical coupling was particularly strong it acted as a powerful low-pass filter, thus contributing to alter the output of individual cells. The dynamic interaction between cells with various firing patterns may differently control GABAergic signalling, leading, as suggested by simulation data, to a wide range of interneuronal communication. In additional paired recordings of a presynaptic EGFP positive interneuron and a postsynaptic principal cell, trains of action potentials in interneurons rarely evoked GABAergic postsynaptic currents (3/45 pairs) with small amplitude and slow kinetics, and that at 20 Hz exhibited short-term depression. In contrast, excitatory connections between principal cells and EGFP-positive interneurons were found more often (17/55 pairs) and exhibited a frequency and use-dependent facilitation, particularly in the gamma band. In conclusion, it appears that EGFP-positive interneurons in stratum oriens of GIN mice constitute a heterogeneous population of cells interconnected via electrical synapses, exhibiting particular features in their chemical and electrical synaptic signalling. Moreover, the dynamic interaction between these interneurons may differentially affect target cells and neuronal communication within the hippocampal network

In Synch but Not in Step: Circadian Clock Circuits Regulating Plasticity in Daily Rhythms

The suprachiasmatic nucleus (SCN) is a network of neural oscillators that program daily rhythms in mammalian behavior and physiology. Over the last decade much has been learned about how SCN clock neurons coordinate together in time and space to form a cohesive population. Despite this insight, much remains unknown about how SCN neurons communicate with one another to produce emergent properties of the network. Here we review the current understanding of communication among SCN clock cells and highlight a collection of formal assays where changes in SCN interactions provide for plasticity in the waveform of circadian rhythms in behavior. Future studies that pair analytical behavioral assays with modern neuroscience techniques have the potential to provide deeper insight into SCN circuit mechanisms