The critical brain hypothesis states that the brain can benefit from operating close to a second-order phase transition. While it has been shown that several computational aspects of sensory information processing (e.g., sensitivity to input) are optimal in this regime, it is still unclear whether these computational benefits of criticality can be leveraged by neural systems performing behaviorally relevant computations. To address this question, we investigate signatures of criticality in networks optimized to perform efficient encoding. We consider a network of leaky integrate-and-fire neurons with synaptic transmission delays and input noise. Previously, it was shown that the performance of such networks varies non-monotonically with the noise amplitude. Interestingly, we find that in the vicinity of the optimal noise level for efficient coding, the network dynamics exhibits signatures of criticality, namely, the distribution of avalanche sizes follows a power law. When the noise amplitude is too low or too high for efficient coding, the network appears either super-critical or sub-critical, respectively. This result suggests that two influential, and previously disparate theories of neural processing optimization—efficient coding, and criticality—may be intimately related

Synaptic transmission provides the basis for neuronal communication. When an action-potential propagates through the axonal arbour, it activates voltage-gated Ca2+ channels located in the vicinity of release-ready synaptic vesicles docked at the presynaptic active zone. Ca2+ ions enter the presynaptic terminal and activate the vesicular Ca2+ sensor, thereby triggering neurotransmitter release. This whole process occurs on a timescale of a few milliseconds. In addition to fast, synchronous release, which keeps pace with action potentials, many synapses also exhibit delayed asynchronous release that persists for tens to hundreds of milliseconds. In this talk I will demonstrate how experimentally constrained computational modelling of underlying biological processes can complement laboratory studies (using electrophysiology and imaging techniques) and provide insights into the mechanisms of synaptic transmission.

The research in my lab focuses on sensory signal processing, particularly in cases where sensory systems perform at or near the limits imposed by physics. Photon counting in the visual system is a beautiful example. At its peak sensitivity, the performance of the visual system is limited largely by the division of light into discrete photons. This observation has several implications for phototransduction and signal processing in the retina: rod photoreceptors must transduce single photon absorptions with high fidelity, single photon signals in photoreceptors, which are only 0.03 – 0.1 mV, must be reliably transmitted to second-order cells in the retina, and absorption of a single photon by a single rod must produce a noticeable change in the pattern of action potentials sent from the eye to the brain. My approach is to combine quantitative physiological experiments and theory to understand photon counting in terms of basic biophysical mechanisms. Fortunately there is more to visual perception than counting photons. The visual system is very adept at operating over a wide range of light intensities (about 12 orders of magnitude). Over most of this range, vision is mediated by cone photoreceptors. Thus adaptation is paramount to cone vision. Again one would like to understand quantitatively how the biophysical mechanisms involved in phototransduction, synaptic transmission, and neural coding contribute to adaptation.

Dr. Davis will present a summary regarding the identification and characterization of mechanisms of homeostatic plasticity as they relate to the control of synaptic transmission. He will then provide evidence of translation to the mammalian neuromuscular junction and central synapses, and provide tangible links to the etiology of neurological disease.

Neurons in the brain communicate through action potentials (spikes) that are transmitted through chemical synapses. Throughout the last decades, the question how networks of spiking neurons represent and process information has remained an important challenge. Some progress has resulted from a recent family of supervised learning rules (tempotrons) for models of spiking neurons. However, these studies have viewed synaptic transmission as static and characterized synaptic efficacies as scalar quantities that change only on slow time scales of learning across trials but remain fixed on the fast time scales of information processing within a trial. By contrast, signal transduction at chemical synapses in the brain results from complex molecular interactions between multiple biochemical processes whose dynamics result in substantial short-term plasticity of most connections. Here we study the computational capabilities of spiking neurons whose synapses are dynamic and plastic, such that each individual synapse can learn its own dynamics. We derive tempotron learning rules for current-based leaky-integrate-and-fire neurons with different types of dynamic synapses. Introducing ordinal synapses whose efficacies depend only on the order of input spikes, we establish an upper capacity bound for spiking neurons with dynamic synapses. We compare this bound to independent synapses, static synapses and to the well established phenomenological Tsodyks-Markram model. We show that synaptic dynamics in principle allow the storage capacity of spiking neurons to scale with the number of input spikes and that this increase in capacity can be traded for greater robustness to input noise, such as spike time jitter. Our work highlights the feasibility of a novel computational paradigm for spiking neural circuits with plastic synaptic dynamics: Rather than being determined by the fixed number of afferents, the dimensionality of a neuron's decision space can be scaled flexibly through the number of input spikes emitted by its input layer.

In the adult brain, synapses are tightly enwrapped by lattices of extracellular matrix that consist of extremely long-lived molecules. These lattices are deemed to stabilize synapses, restrict the reorganization of their transmission machinery, and prevent them from undergoing structural or morphological changes. At the same time, they are expected to retain some degree of flexibility to permit occasional events of synaptic plasticity. The recent understanding that structural changes to synapses are significantly more frequent than previously assumed (occurring even on a timescale of minutes) has called for a mechanism that allows continual and energy-efficient remodeling of the ECM at synapses. I review in the talk our recent work showcasing such a process, based on the constitutive recycling of synaptic ECM molecules. I discuss the key characteristics of this mechanism, focusing on its roles in mediating synaptic transmission and plasticity, and speculate on additional potential functions in neuronal signaling.

The inhibitory actions of the heterogeneous collection of GABAergic interneurons tremendously influence cortical information processing, which is reflected by diseases like autism, epilepsy and schizophrenia that involve defects in cortical inhibition. Apart from the regulation of physiological processes like synaptic transmission, proper interneuron function also relies on their correct development. Hence, decrypting regulatory networks that direct proper cortical interneuron development as well as adult functionality is of great interest, as this helps to identify critical events implicated in the etiology of the aforementioned diseases. Thereby, extrinsic factors modulate these processes and act on cell- and stage-specific transcriptional programs. Herein, epigenetic mechanisms of gene regulation, like DNA methylation executed by DNA methyltransferases (DNMTs), histone modifications and non-coding RNAs, call increasing attention in integrating “environmental information” in our genome and sculpting physiological processes in the brain relevant for human mental health. Several studies associate altered expression levels and function of the DNA methyltransferase 1 (DNMT1) in subsets of embryonic and adult cortical interneurons in patients diagnosed with schizophrenia. Although accumulating evidence supports the relevance of epigenetic signatures for instructing cell type-specific development, only very little is known about their functional implications in discrete developmental processes and in subtype-specific maturation of cortical interneurons. Similarly, little is known about the role of DNMT1 in regulating adult interneurons functionality. This talk will provide an overview about newly identified and roles DNMT1 has in orchestrating cortical interneuron development and adult function. Further, this talk will report about the implications of lncRNAs in mediating site-specific DNA methylation in response to discrete external stimuli.

Long-range projections link distant circuits in the brain, allowing efficient transfer of information between regions and synchronization of distributed patterns of neural activity. Understanding the functional roles of defined neuronal projection pathways requires temporally precise manipulation of their activity, and optogenetic tools appear to be an obvious choice for such experiments. However, we and others have previously shown that commonly-used inhibitory optogenetic tools have low efficacy and off-target effects when applied to presynaptic terminals. In my talk, I will present a new solution to this problem: a targeting-enhanced mosquito homologue of the vertebrate encephalopsin (eOPN3), which upon activation can effectively suppress synaptic transmission through the Gi/o signaling pathway. Brief illumination of presynaptic terminals expressing eOPN3 triggers a lasting suppression of synaptic output that recovers spontaneously within minutes in vitro and in vivo. The efficacy of eOPN3 in suppressing presynaptic release opens new avenues for functional interrogation of long-range neuronal circuits in vivo.

Dravet syndrome (DS) is a neurodevelopmental disorder caused by heterozygous loss-of-function of the gene SCN1A encoding the voltage-gated sodium channel subunit Nav1.1, and is defined by treatment-resistant epilepsy, intellectual impairment, and sudden death. However, disease mechanisms remain unclear, as previously-identified deficiency in action potential generation of Nav1.1-expressing parvalbumin-positive fast-spiking GABAergic interneurons (PV-INs) in DS (Scn1a+/-) mice normalizes during development. We used a novel approach that facilitated the assessment of PV-IN function at both early (post-natal day (P) 16-21) and late (P35-56) time points in the same mice. We confirmed that PV-IN spike generation was impaired at P16-21 in all mice (those deceased from SUDEP by P35 and those surviving to P35-56). However, unitary synaptic transmission assessed in PV-IN:principal cell paired recordings was severely dysfunctional selectively in mice recorded at P16-21 that did not survive to P35. Spike generation in surviving mice had normalized by P35-56; yet we again identified abnormalities in synaptic transmission in surviving mice. We propose that early dysfunction of PV-IN spike propagation drives epilepsy severity and risk of sudden death, while persistent dysfunction of spike propagation contributes to chronic DS pathology.

Christophe Mulle is a cellular neurobiologist with expertise in electrophysiology of synaptic transmission and an international leader in studies on glutamate receptors and hippocampal synaptic plasticity. He was among the first to identify and characterize functional nicotinic receptors in the mammalian brain while working in the laboratory of Jean-Pierre Changeux at the Pasteur Institute. He then generated knock-out mice for KAR subunits at the Salk Institute in the laboratory of Steve Heinemann, which have proven to be instrumental for understanding the function of these elusive glutamate receptors in synaptic function and plasticity.