Biology subjects

Blackwell, K. T.

Publications and source records attributed to Blackwell, K. T..

6 recordsLinked to original sources

bioRxiv2026

Calmodulin controls spatial and temporal specificity of calcium-induced calcium release

Calcium dynamics controls learning and memory, and abnormal calcium dynamics have been implicated in neurodegenerative disorders, such as Alzheimers disease (AD). Calcium dynamics are influenced by calcium-induced calcium release (CICR), which is mediated by ryanodine receptors (RyR) located on endoplasmic reticulum (ER) membrane. Calmodulin, one of the most abundant proteins in the brain, inhibits RyR2, expressed in the dendrites of hippocampal CA1 neurons, with several reported consequences: relief of this inhibition is responsible for heart failure, and enhancing calmodulin to RyR binding [1] alleviates cell loss and AD-like neuronal hyperexcitability. To investigate the role of calmodulin in aging and AD, we built a sophisticated reaction-diffusion model of a dendritic branch with ER. We showed that relieving calmodulin inhibition of RyR2 increased spatial and temporal spread of calcium transients in the dendrite. This effect was also visible in a model of old age, where disinhibition of half of the RyR2 population increased spatial spread of calcium transients by a factor of 2, and disinhibition of RyR2 combined with increased concentration of calcium buffering molecules increased duration of calcium transients. Lower activation of plasma membrane calcium ATPase (PMCA), which is also activated by calmodulin and inhibited by {beta}-Amyloid oligomers, and not RyR2 disinhibition, led to an increase in resting intracellular calcium concentration as observed in AD. Overall, our research demonstrates that changes in calmodulin that are associated with AD and aging, by regulation of RyR2 (in old age) and PMCA (in AD), underlie changes in calcium dynamics that might have consequences for learning and memory. Author summaryCalcium dynamics controls learning and memory. In neurons calcium dynamics are regulated by a complex system including calcium-permeable channels and extrusion pumps. The components of this system are regulated by calmodulin, which is enriched in the brain. We show that relieving calmodulin inhibition of calcium permeable channels, which accompanies aging, decreases spatial and temporal specificity of calcium release, contributing to the deficits in learning and memory observed in old age. In contrast, calcium extrusion pumps that are activated by calmodulin are likely responsible for increased resting intracellular calcium concentration observed in Alzheimers disease. In consequence, a novel role emerges for calmodulin, which in the brain is primarily considered a fast-acting calcium buffering molecule, as an important regulator in neuronal calcium dynamics underlying pathology.

neuroscience↗

bioRxiv2023

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modelling

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modelling of post-synaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from post-mortem mRNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in anterior cingulate cortex, lead to impaired PKA-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped EEG dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials (VEP) were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.

neuroscience↗

bioRxiv2021

Synaptic plasticity is predicted by spatiotemporal firing rate patterns and robust to in vivo-like variability

Synaptic plasticity, the experience-induced change in connections between neurons, underlies learning and memory in the brain. Most of our understanding of synaptic plasticity derives from in vitro experiments with precisely repeated stimulus patterns; however, neurons exhibit significant variability in vivo during repeated experiences. Further, the spatial pattern of synaptic inputs to the dendritic tree influences synaptic plasticity, yet is not considered in most synaptic plasticity rules. Here, we address the sensitivity of plasticity to trial-to-trial variability and delineate how spatiotemporal synaptic input patterns produce plasticity with in vivo-like conditions using a data-driven computational model with a calcium-based plasticity rule. Using in vivo spike train recordings as inputs, we show that plasticity is strongly robust to trial-to-trial variability of spike timing, and derive general synaptic plasticity rules describing how spatiotemporal patterns of synaptic inputs control the magnitude and direction of plasticity. Specifically, a high temporal input firing rate to a synapse late in a trial correlated with neighboring synaptic activity produces potentiation, while an earlier, moderate firing rate that is negatively correlated with neighboring synaptic activity produces depression. Together, our results reveal that calcium dynamics can unify diverse plasticity rules and reveal how spatiotemporal firing rate patterns control synaptic plasticity.

neuroscience↗

bioRxiv2020

Temporal pattern and synergy influence activity of ERK signaling pathways during L-LTP induction

Long-lasting long-term potentiation (L-LTP) is a cellular mechanism of learning and memory storage. Studies have demonstrated a requirement for extracellular signal-regulated kinase (ERK) activation in L-LTP produced by a diversity of temporal stimulation patterns. Multiple signaling pathways converge to activate ERK, with different pathways being required for different stimulation patterns. To answer whether and how different temporal patterns select different signaling pathways for ERK activation, we developed a computational model of five signaling pathways (including two novel pathways) leading to ERK activation during L-LTP induction. We show that calcium and cAMP work synergistically to activate ERK and that stimuli given with large inter-trial intervals activate more ERK than shorter intervals. Furthermore, these pathways contribute to different dynamics of ERK activation. These results suggest that signaling pathways with different temporal sensitivity facilitate ERK activation to diversity of temporal patterns.

neuroscience↗

bioRxiv2020

Endocannabinoids and dopamine balance basal ganglia output

The entopeduncular nucleus is one of the basal ganglias output nuclei, thereby controlling basal ganglia information processing. Entopeduncular nucleus neurons integrate GABAergic inputs from the striatum and the globus pallidus and glutamatergic inputs from the subthalamic nucleus. We show that endocannabinoids and dopamine interact to modulate the long-term plasticity of all the primary afferents to the entopeduncular nucleus. Our results suggest that dopamine-endocannabinoids interplay determines the balance of the direct or indirect dominance of entopeduncular nucleus output. Furthermore, we demonstrate that, despite the lack of axon collaterals, information is transferred between neighboring neurons in the entopeduncular nucleus via endocannabinoids diffusion. These results transform the prevailing view of the entopeduncular nucleus as a feedforward "relay" nucleus to an intricate control unit, which may play a vital role in the process of action selection.

neuroscience↗

bioRxiv2020

A unified computational model for cortical post-synaptic plasticity

Cortical synapses possess a machinery of signalling pathways that leads to various modes of post-synaptic plasticity. Such pathways have been examined to a great detail separately in many types of experimental studies. However, a unified picture on how multiple biochemical pathways collectively shape the observed synaptic plasticity in the neocortex is missing. Here, we built a biochemically detailed model of post-synaptic plasticity that includes the major signalling cascades, namely, CaMKII, PKA, and PKC pathways which, upon activation by Ca2+, lead to synaptic potentiation or depression. We adjusted model components from existing models of intracellular signalling into a single-compartment simulation framework. Furthermore, we propose a statistical model for the prevalence of different types of membrane-bound AMPA-receptor tetramers consisting of GluR1 and GluR2 subunits in proportions suggested by the biochemical signalling model, which permits the estimation of the AMPA-receptor-mediated maximal synaptic conductance. We show that our model can reproduce neuromodulator-gated spike-timing-dependent plasticity as observed in the visual cortex. Moreover, we demonstrate that our model can be fit to data from many cortical areas and that the resulting model parameters reflect the involvement of the pathways pinpointed by the underlying experimental studies. Our model explains the dependence of different forms of plasticity on the availability of different proteins and can be used for the study of mental disorder-associated impairments of cortical plasticity. Significance statementNeocortical synaptic plasticity has been studied experimentally in a number of cortical areas, showing how interactions between neuromodulators and post-synaptic proteins shape the outcome of the plasticity. On the other hand, non-detailed computational models of long-term plasticity, such as Hebbian rules of synaptic potentiation and depression, have been widely used in modelling of neocortical circuits. In this work, we bridge the gap between these two branches of neuroscience by building a detailed model of post-synaptic plasticity that can reproduce observations on cortical plasticity and provide biochemical meaning to the simple rules of plasticity. Our model can be used for predicting the effects of chemical or genetic manipulations of various intracellular signalling proteins on induction of plasticity in health and disease.

neuroscience↗