Tag Archives: Bryan William Jones

A pathoconnectome of early neurodegeneration: Network changes in retinal degeneration

We have a new manuscript out in Experimental Eye Research, A pathoconnectome of early neurodegeneration: Network changes in retinal degeneration. (pdf here)

Authors: Rebecca L. Pfeiffer @BeccaPfeiffer19, James R. Anderson, Jeebika Dahal, Jessica C. Garcia, Jia-Hui Yang, Crystal L. Sigulinsky @CLSigulinsky, Kevin Rapp, Daniel P. Emrich, Carl B. Watt, Hope AB Johnstun, Alexis R. Houser, Robert E. Marc @robertmarc60, and Bryan W. Jones @BWJones.

Abstract: Connectomics has demonstrated that synaptic networks and their topologies are precise and directly correlate with physiology and behavior. The next extension of connectomics is pathoconnectomics: to map neural network synaptology and circuit topologies corrupted by neurological disease in order to identify robust targets for therapeutics. In this report, we characterize a pathoconnectome of early retinal degeneration. This pathoconnectome was generated using serial section transmission electron microscopy to achieve an ultrastructural connectome with 2.18nm/px resolution for accurate identification of all chemical and gap junctional synapses. We observe aberrant connectivity in the rod-network pathway and novel synaptic connections deriving from neurite sprouting. These observations reveal principles of neuron responses to the loss of network components and can be extended to other neurodegenerative diseases.

 

Müller Cell Metabolic Signatures: Evolutionary Conservation and Disruption in Disease

We have a new manuscript out in Trends in Endocrinology & Metabolism, Müller Cell Metabolic Signatures: Evolutionary Conservation and Disruption in Disease.

Authors: Rebecca L. Pfeiffer @BeccaPfeiffer19, Robert E. Marc @robertmarc60, and Bryan William Jones @BWJones.

This manuscript functions as both a review and presents some exciting new data demonstrating how the glutamate cycle is disrupted during retinal degenerative disease.

Abstract: Müller cells are glia that play important regulatory roles in retinal metabolism. These roles have been evolutionarily conserved across at least 300 million years. Müller cells have a tightly locked metabolic signature in the healthy retina, which rapidly degrades in response to insult and disease. This variation in metabolic signature occurs in a chaotic fashion, involving some central metabolic pathways. The cause of this divergence of Müller cells, from a single class with a unique metabolic signature to numerous separable metabolic classes, is currently unknown and illuminates potential alternative metabolic pathways that may be revealed in disease. Understanding the impacts of this heterogeneity on degenerate retinas and the implications for the metabolic support of surrounding neurons will be critical to long-term integration of retinal therapeutics for the restoration of visual perception following photoreceptor degeneration.

Heterocellular Coupling Between Amacrine Cells and Ganglion Cells

We have a new paper out In Frontiers in Neural Circuits, Heterocellular Coupling Between Amacrine Cells and Ganglion Cells. This manuscript preprint was published in BioRxiv.

Authors: Robert E. Marc, Crystal Lynn Sigulinsky, Rebecca L. Pfeiffer, Daniel Emrich, James Russel Anderson and Bryan William Jones.

Abstract: All superclasses of retinal neurons, including bipolar cells (BCs), amacrine cells (ACs) and ganglion cells (GCs), display gap junctional coupling. However, coupling varies extensively by class. Heterocellular AC coupling is common in many mammalian GC classes. Yet, the topology and functions of coupling networks remains largely undefined. GCs are the least frequent superclass in the inner plexiform layer and the gap junctions mediating GC-to-AC coupling (GC::AC) are sparsely arrayed amidst large cohorts of homocellular AC::AC, BC::BC, GC::GC and heterocellular AC::BC gap junctions. Here, we report quantitative coupling for identified GCs in retinal connectome 1 (RC1), a high resolution (2 nm) transmission electron microscopy-based volume of rabbit retina. These reveal that most GC gap junctions in RC1 are suboptical. GC classes lack direct cross-class homocellular coupling with other GCs, despite opportunities via direct membrane contact, while OFF alpha GCs and transient ON directionally selective (DS) GCs are strongly coupled to distinct AC cohorts. Integrated small molecule immunocytochemistry identifies these as GABAergic ACs (γ+ ACs). Multi-hop synaptic queries of RC1 connectome further profile these coupled γ+ ACs. Notably, OFF alpha GCs couple to OFF γ+ ACs and transient ON DS GCs couple to ON γ+ ACs, including a large interstitial amacrine cell, revealing matched ON/OFF photic drive polarities within coupled networks. Furthermore, BC input to these γ+ ACs is tightly matched to the GCs with which they couple. Evaluation of the coupled versus inhibitory targets of the γ+ ACs reveals that in both ON and OFF coupled GC networks these ACs are presynaptic to GC classes that are different than the classes with which they couple. These heterocellular coupling patterns provide a potential mechanism for an excited GC to indirectly inhibit nearby GCs of different classes. Similarly, coupled γ+ ACs engaged in feedback networks can leverage the additional gain of BC synapses in shaping the signaling of downstream targets based on their own selective coupling with GCs. A consequence of coupling is intercellular fluxes of small molecules. GC::AC coupling involves primarily γ+ cells, likely resulting in GABA diffusion into GCs. Surveying GABA signatures in the GC layer across diverse species suggests the majority of vertebrate retinas engage in GC::γ+ AC coupling.

Off to RD2018 and ISER 2018

The Marclab for Connectomics is off to RD2018 and ISER 2018 in Killarney, Ireland and Belfast, Northern Ireland.  I’ll be organizing sessions on retinal degeneration, and I’m tremendously proud of the work Dr. Crystal Sigulinsky will be presenting from her work on gap junctional connectivity in retinal degenerations and the work Dr. Rebecca Pfeiffer (@BeccaPfeiffer19) will be presenting on her work on the retinal pathoconnectome in two talks on bipolar cells and Müller cells.

Increasing Electrical Stimulation Efficacy in Degenerated Retina: Stimulus Waveform Design in a Multiscale Computational Model

We have a new publication out (direct link), Increasing Electrical Stimulation Efficacy in Degenerated Retina: Stimulus Waveform Design in a Multiscale Computational Model authored by Kyle Loizos, Robert Marc, Mark Humayun, James R. Anderson, Bryan W. Jones and Gianluca Lazzi.

Abstract—A computational model of electrical stimulation of the retina is proposed for investigating current waveforms used in prosthetic devices for restoring partial vision lost to retina degen- erative diseases. The model framework combines a connectome- based neural network model characterized by accurate mor- phological and synaptic properties with an Admittance Method model of bulk tissue and prosthetic electronics. In this model, the retina was computationally “degenerated,” considering cellular death and anatomical changes that occur early in disease, as well as altered neural behavior that develops throughout the neurodegeneration and is likely interfering with current attempts at restoring vision. A resulting analysis of stimulation range and threshold of ON ganglion cells within retina that are either healthy or in beginning stages of degeneration is presented for currently-used stimulation waveforms, and an asymmetric biphasic current stimulation for subduing spontaneous firing to allow increased control over ganglion cell firing patterns in degenerated retina is proposed. Results show that stimulation thresholds of retinal ganglion cells do not notably vary after beginning stages of retina degeneration. In addition, simulation of proposed asymmetric waveforms showed the ability to enhance the control of ganglion cell firing via electrical stimulation.

Corticostriatal Circuit Defects in Hoxb8 Mutant Mice

We have a new publication in Molecular Psychiatry, Corticostriatal circuit defects in Hoxb8 mutant mice. (Direct link here).  Authors are:  Naveen Nagarajan, Bryan W. Jones, Peter West, Robert Marc, and Mario R. Capecchi.

Abstract: Hoxb8 mutant mice exhibit compulsive grooming and hair removal dysfunction similar to humans with the obsessive-compulsive disorder (OCD)-spectrum disorder, trichotillomania. As, in the mouse brain, the only detectable cells that label with Hoxb8 cell lineage appear to be microglia, we suggested that defective microglia cause the neuropsychiatric disorder. Does the Hoxb8 mutation in microglia lead to neural circuit dysfunctions? We demonstrate that Hoxb8 mutants contain corticostriatal circuit defects. Golgi staining, ultra-structural and electrophysiological studies of mutants reveal excess dendritic spines, pre- and postsynaptic structural defects, long-term potentiation and miniature postsynaptic current defects. Hoxb8 mutants also exhibit hyperanxiety and social behavioral deficits similar to mice with neuronal mutations in Sapap3, Slitrk5 and Shank3, reported models of OCD and autism spectrum disorders (ASDs). Long-term treatment of Hoxb8 mutants with fluoxetine, a serotonin reuptake inhibitor, reduces excessive grooming, hyperanxiety and social behavioral impairments. These studies provide linkage between the neuronal defects induced by defective Hoxb8-microglia and neuronal dysfunctions directly generated by mutations in synaptic components that result in mice, which display similar pathological grooming, hyperanxiety and social impairment deficits. Our results shed light on Hoxb8 microglia-driven circuit-specific defects and therapeutic approaches that will become essential to developing novel
therapies for neuropsychiatric diseases such as OCD and ASDs with Hoxb8-microglia being the central target.

Pattern Recognition Analysis Reveals Unique Contrast Sensitivity Isocontours Using Static Perimetry Thresholds Across The Visual Field

We have a new publication in IOVS, Pattern Recognition Analysis Reveals Unique Contrast Sensitivity Isocontours Using Static Perimetry Thresholds Across The Visual Field (Direct link here).  Authors are:  Jack Phu, Sieu Khuu, Lisa Nivison-Smith, Barbara Zangerl, Agnes Yiu, Jeung Choi, Bryan W. JonesRebecca Pfeiffer, Robert Marc, and Michael Kalloniatis.

Purpose
To determine the locus of test locations that exhibit statistically similar age-related decline in sensitivity to light increments and age-corrected contrast sensitivity isocontours (CSIs) across the central visual field (VF). We compared these CSIs with test point clusters used by the Glaucoma Hemifield Test (GHT).

Methods
Sixty healthy observers underwent testing on the Humphrey Field Analyzer 30-2 test grid using Goldmann (G) stimulus sizes I-V. Age-correction factors for GI-V were determined using linear regression analysis. Pattern recognition analysis was used to cluster test locations across the VF exhibiting equal age-related sensitivity decline (age-related CSIs), and points of equal age-corrected sensitivity (age-corrected CSIs) for GI-V.

Results
There was a small but significant test size–dependent sensitivity decline with age, with smaller stimuli declining more rapidly. Age-related decline in sensitivity was more rapid in the periphery. A greater number of unique age-related CSIs was revealed when using smaller stimuli, particularly in the mid-periphery. Cluster analysis of age-corrected sensitivity thresholds revealed unique CSIs for GI-V, with smaller stimuli having a greater number of unique clusters. Zones examined by the GHT consisted of test locations that did not necessarily belong to the same CSI, particularly in the periphery.

Conclusions
Cluster analysis reveals statistically significant groups of test locations within the 30-2 test grid exhibiting the same age-related decline. CSIs facilitate pooling of sensitivities to reduce the variability of individual test locations. These CSIs could guide future structure-function and alternate hemifield asymmetry analyses by comparing matched areas of similar sensitivity signatures.

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures In The Human Eye

We have a new publication in IOVS, Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures In The Human Eye (Direct link here).  Authors are:  Nayuta Yoshioka, Barbara Zangerl, Lisa Nivison-Smith, Sieu Khuu, Bryan W. Jones, Rebecca Pfeiffer, Robert Marc, and Michael Kalloniatis.

Purpose: We recently used pattern recognition analysis to show macula areas can be classified into statistically distinct clusters in accordance to their age-related retinal ganglion cell layer (RGCL) thickness change in a normal population. The aim of this study was to perform a retrospective cross-sectional analysis utilizing a large cohort of patients to establish accuracy of this model and to develop a normative dataset using a 50-year-old equivalent cohort.

Methods: Data was collected from patients seen at the Centre for Eye Health for optic nerve assessment without posterior pole disease. The grid-wise RGCL thickness was obtained from a single eye of each patient via Spectralis OCT macular scan over an 8×8 measurement grid. Measurements for patients outside the 45-54 age range (training cohort) were converted to 50-year-old equivalent value utilizing pattern recognition derived regression model which, in brief, consists of 8×8 grid clustered into 8 distinct classes according to the pattern of RGCL thickness change with age. Accuracy of the predictions was assessed by comparing the training cohort’s measurements to the 45-54 year reference cohort using t-test and one-way ANOVA.

Results: Data were collected from a total 248 patients aged 20 to 78.1 years. 80 patients within this group were aged 45 – 54 and formed the reference cohort (average±SD 49.6±2.83) and the remaining 168 eyes formed the training cohort (average age±SD 50.7±17.34). Converted values for the training set matched those of the reference cohort (average disparity±SD 0.10±0.42µm, range -0.74-1.34µm) and were not significantly different (p > 0.9). Most variability was observed with patients above 70 years of age (average disparity±SD -0.09±1.73µm, range -3.67 to 6.16µm) and central grids corresponding to the fovea (average disparity±SD 0.47±0.72µm, range -0.22 to 1.34µm).

Conclusions: Our regression model for normal age-related RGCL change can accurately convert and/or predict RGCL thickness for individuals in comparison to 50-year-equivalent reference cohort and could allow for more accurate assessment of RGCL thickness and earlier detection of significant loss in the future. Caution may be needed when applying the model in the foveal area or for patients older than 70 years.

Synaptic Inputs To A Gamma Ganglion Cell In Rabbit Retina

This abstract was presented today, May 8th at the 2017 Association for Research in Vision and Opthalmology (ARVO) meetings in Baltimore, Maryland by Andrea Bordt, Diego Perez, Robert E. Marc, James R. Anderson, Carl B. Watt, Bryan W. Jones, Crystal Sigulinsky, James S. Lauritzen, Danny Emrich, Noah Nelson, Luke Tseng, Weiley Liu, and David W. Marshak. Full resolution version here.

Purpose: There are at least 30 distinct types of mammalian retinal ganglion cells, each sensitive to different features of the visual environment, and these can be grouped according to their morphology. One such group, the gamma cells, was identified more than 40 years ago, but their synaptic inputs have never been described. That was the goal of this study.

Methods: The synaptic inputs to a subtype of gamma cell with dendrites ramifying in the outer sublamina of the inner plexiform layer (IPL) of the rabbit retina were identified in a retinal connectome developed using automated transmission electron microscopy.

Results: The gamma cell was always postsynaptic in the IPL, confirming its identity as a ganglion cell. The local synaptic input should produce relatively weak OFF reposnses to stimuli confined to the center of the gamma cell’s receptive field. It typically received only one synapse per bipolar cell from at least 4 types of OFF bipolar cells. Because bipolar cells vary in their response kinetics and contrast sensitivity. each type would provide a small, asynchronous excitatory input. The amacrine cells at the dyad synapses provided only a small amount presynaptic inhibition; reciprocal synapses were observed in only 3 of the 18 ribbon synapses. There was no glycinergic crossover inhibition, another local interaction that would enhance light responses. Local postsynaptic inhibition was somewhat more common; in 6 instances, the bipolar cells presynaptic to the gamma cell or their electrically coupled neighbors also provided input to an amacrine cell that inhibited the gamma cell. The other amacrine cell inputs to the gamma cell should have a much greater impact on the light responses because they are far more numerous. These are from axons and long dendrites of GABAergic amacrine cells, and they provide 60% of all the input. This finding suggests that many types of stimuli in the receptive field surround or outside of the classical receptive field would provide potent inhibition to the gamma cell.

Conclusions: The synaptic inputs rsuggest that gamma cells in rabbit retina would have light responses like their homologs in mouse retina, OFF responses to small stimuli in the receptive field center that are suppressed by a variety of larger stimuli. Thus, they would signal object motion selectively.

Predicting Age-related Changes with High Accuracy using a Pattern Recognition Derived Retinal Ganglion Cell Regression Model

This abstract was presented yesterday, May 7th at the 2017 Association for Research in Vision and Opthalmology (ARVO) meetings in Baltimore, Maryland by Nayuta Yoshioka, Barbara Zangerl, Lisa Nivison-Smith, Sieu Khuu, Bryan W. Jones, Rebecca Pfeiffer, Robert Marc, and Michael Kalloniatis.

Purpose: We recently used pattern recognition analysis to show macula areas can be classified into statistically distinct clusters in accordance to their age-related retinal ganglion cell layer (RGCL) thickness change in a normal population. The aim of this study was to perform a retrospective cross-sectional analysis utilizing a large cohort of patients to establish accuracy of this model and to develop a normative dataset using a 50-year-old equivalent cohort.

Methods: Data was collected from patients seen at the Centre for Eye Health for optic nerve assessment without posterior pole disease. The grid-wise RGCL thickness was obtained from a single eye of each patient via Spectralis OCT macular scan over an 8×8 measurement grid. Measurements for patients outside the 45-54 age range (training cohort) were converted to 50-year-old equivalent value utilizing pattern recognition derived regression model which, in brief, consists of 8×8 grid clustered into 8 distinct classes according to the pattern of RGCL thickness change with age. Accuracy of the predictions was assessed by comparing the training cohort’s measurements to the 45-54 year reference cohort using t-test and one-way ANOVA.

Results: Data were collected from a total 248 patients aged 20 to 78.1 years. 80 patients within this group were aged 45 – 54 and formed the reference cohort (average±SD 49.6±2.83) and the remaining 168 eyes formed the training cohort (average age±SD 50.7±17.34). Converted values for the training set matched those of the reference cohort (average disparity±SD 0.10±0.42µm, range -0.74-1.34µm) and were not significantly different (p > 0.9). Most variability was observed with patients above 70 years of age (average disparity±SD -0.09±1.73µm, range -3.67 to 6.16µm) and central grids corresponding to the fovea (average disparity±SD 0.47±0.72µm, range -0.22 to 1.34µm).

Conclusions: Our regression model for normal age-related RGCL change can accurately convert and/or predict RGCL thickness for individuals in comparison to 50-year-equivalent reference cohort and could allow for more accurate assessment of RGCL thickness and earlier detection of significant loss in the future. Caution may be needed when applying the model in the foveal area or for patients older than 70 years.