A hallmark pathological feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion of RNA-binding protein TDP-43 from the nucleus of neurons in the brain and spinal cord. A major function of TDP-43 is as a repressor of cryptic exon inclusion during RNA splicing. By re-analyzing RNA-sequencing datasets from human FTD/ALS brains, we discovered dozens of novel cryptic splicing events in important neuronal genes. Single nucleotide polymorphisms in UNC13A are among the strongest hits associated with FTD and ALS in human genome-wide association studies, but how those variants increase risk for disease is unknown. We discovered that TDP-43 represses a cryptic exon-splicing event in UNC13A. Loss of TDP-43 from the nucleus in human brain, neuronal cell lines and motor neurons derived from induced pluripotent stem cells resulted in the inclusion of a cryptic exon in UNC13A mRNA and reduced UNC13A protein expression. The top variants associated with FTD or ALS risk in humans are located in the intron harboring the cryptic exon, and we show that they increase UNC13A cryptic exon splicing in the face of TDP-43 dysfunction. Together, our data provide a direct functional link between one of the strongest genetic risk factors for FTD and ALS (UNC13A genetic variants), and loss of TDP-43 function. Recent analyses have revealed even further changes in TDP-43 target genes, including widespread changes in alternative polyadenylation, impacting expression of disease-relevant genes (e.g., ELP1, NEFL, and TMEM106B) and providing evidence that alternative polyadenylation is a new facet of TDP-43 pathology.

How can the hippocampal system transition from episodic one-shot learning to a multi-shot learning regime and what is the utility of the resultant neural representations? This talk will explore the role of the dentate gyrus (DG) anatomy in this context. The canonical DG model suggests it performs pattern separation. More recent experimental results challenge this standard model, suggesting DG function is more complex and also supports the precise binding of objects and events to space and the integration of information across episodes. Very recent studies attribute pattern separation and pattern integration to anatomically distinct parts of the DG (the suprapyramidal blade vs the infrapyramidal blade). We propose a computational model that investigates this distinction. In the model the two processing streams (potentially localized in separate blades) contribute to the storage of distinct episodic memories, and the integration of information across episodes, respectively. The latter forms generalized expectations across episodes, eventually forming a cognitive map. We train the model with two data sets, MNIST and plausible entorhinal cortex inputs. The comparison between the two streams allows for the calculation of a prediction error, which can drive the storage of poorly predicted memories and the forgetting of well-predicted memories. We suggest that differential processing across the DG aids in the iterative construction of spatial cognitive maps to serve the generation of location-dependent expectations, while at the same time preserving episodic memory traces of idiosyncratic events.

Neurotrophins (NGF, BDNF, NT-3) are endogenous growth factors that exert neuroprotective effects by preventing neuronal death and promoting neurogenesis. They act by binding to their respective high-affinity, pro-survival receptors TrkA, TrkB or TrkC, as well as to p75NTR death receptor. While these molecules have been shown to significantly slow or prevent neurodegeneration, their reduced bioavailability and inability to penetrate the blood-brain-barrier limit their use as potential therapeutics. To bypass these limitations, our research team has developed and patented small-sized, lipophilic compounds which selectively resemble neurotrophins’ effects, presenting preferable pharmacological properties and promoting neuroprotection and repair against neurodegeneration. In addition, the combination of these molecules with 3D cultured human neuronal cells, and their targeted delivery in the brain ventricles through soft robotic systems, could offer novel therapeutic approaches against neurodegenerative diseases and brain trauma.

Astrocytes are multifunctional glial cells, implicated in neurogenesis and synaptogenesis, supporting and fine-tuning neuronal activity and maintaining brain homeostasis by controlling blood-brain barrier permeability. During the last years a number of studies have shown that astrocytes can also be converted into neurons if they force-express neurogenic transcription factors or miRNAs. Direct astrocytic reprogramming to induced-neurons (iNs) is a powerful approach for manipulating cell fate, as it takes advantage of the intrinsic neural stem cell (NSC) potential of brain resident reactive astrocytes. To this end, astrocytic cell fate conversion to iNs has been well-established in vitro and in vivo using combinations of transcription factors (TFs) or chemical cocktails. Challenging the expression of lineage-specific TFs is accompanied by changes in the expression of miRNAs, that post-transcriptionally modulate high numbers of neurogenesis-promoting factors and have therefore been introduced, supplementary or alternatively to TFs, to instruct direct neuronal reprogramming. The neurogenic miRNA miR-124 has been employed in direct reprogramming protocols supplementary to neurogenic TFs and other miRNAs to enhance direct neurogenic conversion by suppressing multiple non-neuronal targets. In our group we aimed to investigate whether miR-124 is sufficient to drive direct reprogramming of astrocytes to induced-neurons (iNs) on its own both in vitro and in vivo and elucidate its independent mechanism of reprogramming action. Our in vitro data indicate that miR-124 is a potent driver of the reprogramming switch of astrocytes towards an immature neuronal fate. Elucidation of the molecular pathways being triggered by miR-124 by RNA-seq analysis revealed that miR-124 is sufficient to instruct reprogramming of cortical astrocytes to immature induced-neurons (iNs) in vitro by down-regulating genes with important regulatory roles in astrocytic function. Among these, the RNA binding protein Zfp36l1, implicated in ARE-mediated mRNA decay, was found to be a direct target of miR-124, that be its turn targets neuronal-specific proteins participating in cortical development, which get de-repressed in miR-124-iNs. Furthermore, miR-124 is potent to guide direct neuronal reprogramming of reactive astrocytes to iNs of cortical identity following cortical trauma, a novel finding confirming its robust reprogramming action within the cortical microenvironment under neuroinflammatory conditions. In parallel to their reprogramming properties, astrocytes also participate in the maintenance of blood-brain barrier integrity, which ensures the physiological functioning of the central nervous system and gets affected contributing to the pathology of several neurodegenerative diseases. To study in real time the dynamic physical interactions of astrocytes with brain vasculature under homeostatic and pathological conditions, we performed 2-photon brain intravital imaging in a mouse model of systemic neuroinflammation, known to trigger astrogliosis and microgliosis and to evoke changes in astrocytic contact with brain vasculature. Our in vivo findings indicate that following neuroinflammation the endfeet of activated perivascular astrocytes lose their close proximity and physiological cross-talk with vasculature, however this event is at compensated by the cross-talk of astrocytes with activated microglia, safeguarding blood vessel coverage and maintenance of blood-brain integrity.

To form a coherent perception of the world around us, we are constantly processing and integrating sensory information from multiple modalities. In fact, when auditory and visual stimuli occur within ~100 ms of each other, individuals tend to perceive the stimuli as a single event, even though they occurred separately. In recent years, our lab, and others, have developed rat models of audiovisual temporal perception using behavioural tasks such as temporal order judgments (TOJs) and synchrony judgments (SJs). While these rodent models demonstrate metrics that are consistent with humans (e.g., perceived simultaneity, temporal acuity), we have sought to confirm whether rodents demonstrate the hallmarks of audiovisual temporal perception, such as predictable shifts in their perception based on experience and sensitivity to alterations in neurochemistry. Ultimately, our findings indicate that rats serve as an excellent model to study the neural mechanisms underlying audiovisual temporal perception, which to date remains relativity unknown. Using our validated translational audiovisual behavioural tasks, in combination with optogenetics, neuropharmacology and in vivo electrophysiology, we aim to uncover the mechanisms by which inhibitory neurotransmission and top-down circuits finely control ones’ perception. This research will significantly advance our understanding of the neuronal circuitry underlying audiovisual temporal perception, and will be the first to establish the role of interneurons in regulating the synchronized neural activity that is thought to contribute to the precise binding of audiovisual stimuli.

Gonadal steroid hormones are the principal drivers of sex-variable biology in vertebrates. In the brain, estrogen (17β-estradiol) establishes neural sex differences in many species and modulates mood, behavior, and energy balance in adulthood. To understand the diverse effects of estradiol on the brain, we profiled the genomic binding of estrogen receptor alpha (ERα), providing the first picture of the neural actions of any gonadal hormone receptor. To relate ERα target genes to brain sex differences we assessed gene expression and chromatin accessibility in the posterior bed nucleus of the stria terminalis (BNSTp), a sexually dimorphic node in limbic circuitry that underlies sex-differential social behaviors such as aggression and parenting. In adult animals we observe that levels of ERα are predictive of the extent of sex-variable gene expression, and that these sex differences are a dynamic readout of acute hormonal state. In neonates we find that transient ERα recruitment at birth leads to persistent chromatin opening and male-biased gene expression, demonstrating a true epigenetic mechanism for brain sexual differentiation. Collectively, our findings demonstrate that sex differences in gene expression in the brain are a readout of state-dependent hormone receptor actions, rather than other factors such as sex chromosomes. We anticipate that the ERα targets we have found will contribute to established sex differences in the incidence and etiology of neurological and psychiatric disorders.

Connections between nerve cells called synapses are the fundamental units of communication and information processing in the brain. The accurate wiring of neurons through synapses into neural networks or circuits is essential for brain organization. Neuronal networks are sculpted and refined throughout life by constant adjustment of the strength of synaptic communication by neuronal activity, a process known as synaptic plasticity. Deficits in the development or plasticity of synapses underlie various neuropsychiatric disorders, including autism, schizophrenia and intellectual disability. The Siddiqui lab research program comprises three major themes. One, to assess how biochemical switches control the activity of synapse organizing proteins, how these switches act through their binding partners and how these processes are regulated to correct impaired synaptic function in disease. Two, to investigate how synapse organizers regulate the specificity of neuronal circuit development and how defined circuits contribute to cognition and behaviour. Three, to address how synapses are formed in the developing brain and maintained in the mature brain and how microcircuits formed by synapses are refined to fine-tune information processing in the brain. Together, these studies have generated fundamental new knowledge about neuronal circuit development and plasticity and enabled us to identify targets for therapeutic intervention.

In recent years, it has become clear that intrinsically disordered regions (IDRs) of RBPs, and the structure of RNAs, often contribute to the condensation of RNPs. To understand the transcriptomic features of such RNP condensates, we’ve used an improved individual nucleotide resolution CLIP protocol (iiCLIP), which produces highly sensitive and specific data, and thus enables quantitative comparisons of interactions across conditions (Lee et al., 2021). This showed how the IDR-dependent condensation properties of TDP-43 specify its RNA binding and regulatory repertoire (Hallegger et al., 2021). Moreover, we developed software for discovery and visualisation of RNA binding motifs that uncovered common binding patterns of RBPs on long multivalent RNA regions that are composed of dispersed motif clusters (Kuret et al, 2021). Finally, we used hybrid iCLIP (hiCLIP) to characterise the RNA structures mediating the assembly of Staufen RNPs across mammalian brain development, which demonstrated the roles of long-range RNA duplexes in the compaction of long 3’UTRs. I will present how the combined analysis of the characteristics of IDRs in RBPs, multivalent RNA regions and RNA structures is required to understand the formation and functions of RNP condensates, and how they change in diseases.

MicroRNAs are small noncoding RNAs that provide a critical layer of gene expression control. Individual microRNAs variably exert effects across networks of genes via sequence-specific binding to mRNAs, fine-tuning protein levels. This helps coordinate the timing and specification of cell fate transitions during brain development and maintains neural circuit function and plasticity by activity-dependent (re)shaping of synapses and the levels of neurotransmitter components. MicroRNA levels have been found to be altered in tissue from the epileptogenic zone resected from adults with drug-resistant focal epilepsy and this has driven efforts to explore their therapeutic potential, in particular using antisense oligonucleotide (ASOs) inhibitors termed antimirs. Here, we review the molecular mechanisms by which microRNAs control brain excitability and the latest progress towards a microRNA-based treatment for temporal lobe epilepsy. We also look at whether microRNA-based approaches could be used to treat genetic epilepsies, correcting individual genes or dysregulated pathways. Finally, we look at how cells have evolved to maximise the efficiency of the microRNA system via RNA editing, where single base changes is capable of altering the repertoire of genes under the control of a single microRNA. The findings improve our understanding of the molecular landscape of the epileptic brain and may lead to new therapies.

Learning is known to induce the formation of new dendritic spines, but despite decades of effort, the functional properties of new spines in vivo remain unknown. Here, using a combination of longitudinal in vivo 2-photon imaging of the glutamate reporter, iGluSnFR, and correlated electron microscopy (CLEM) of dendritic spines on the apical dendrites of L2/3 excitatory neurons in the motor cortex during motor learning, we describe a framework of new spines' formation, survival, and resulting function. Specifically, our data indicate that the potentiation of a subset of clustered, pre-existing spines showing task-related activity in early sessions of learning creates a micro-environment of plasticity within dendrites, wherein multiple filopodia sample the nearby neuropil, form connections with pre-existing boutons connected to allodendritic spines, and are then selected for survival based on co-activity with nearby task-related spines. Thus, the formation and survival of new spines is determined by the functional micro-environment of dendrites. After formation, new spines show preferential co-activation with nearby task-related spines. This synchronous activity is more specific to movements than activation of the individual spines in isolation, and further, is coincident with movements that are more similar to the learned pattern. Thus, new spines functionally engage with their parent clusters to signal the learned movement. Finally, by reconstructing the axons associated with new spines, we found that they synapse with axons previously unrepresented in these dendritic domains, suggesting that the strong local co-activity structure exhibited by new spines is likely not due to axon sharing. Thus, learning involves the binding of new information streams into functional synaptic clusters to subserve the learned behavior.

Our ability to perceive the world around us can be affected by a number of factors including the nature of the external information, prior experience of the environment, and the integrity of the underlying perceptual system. A particular challenge for the brain is to maintain a coherent perception from information encoded by the peripheral sensory organs whose function is affected by typical, developmental changes across the lifespan. Yet, how the brain adapts to the maturation of the senses, as well as experiential changes in the multisensory environment, is poorly understood. Over the past few years, we have used a range of multisensory tasks to investigate the role of ageing on the brain’s ability to merge sensory inputs. In particular, we have embedded an audio-visual task based on the sound-induced flash illusion (SIFI) into a large-scale, longitudinal study of ageing. Our findings support the idea that the temporal binding window (TBW) is modulated by age and reveal important individual differences in this TBW that may have clinical implications. However, our investigations also suggest the TWB is experience-dependent with evidence for both long and short term behavioural plasticity. An overview of these findings, including recent evidence on how multisensory integration may be associated with higher order functions, will be discussed.

In this talk, I’ll introduce the formal concept of a (pre)sheaf as data attached to a topological space. Sheaves capture the notion of patching local sources of information to form a global whole, e.g., the binding of visual features such as colour and shape. The formal theory appears to be closely related to the foundational properties asserted by the Information Integration Theory (IIT) for phenomenology. A comparison is intended to engender discussion on ways that phenomenology may benefit from a sheaf theory, or (more generally) a category theory approach.

The talk will give a tour of Guided Search 6.0 (GS6), the latest evolution of the Guided Search model of visual search. Part 1 describes The Mechanics of Search. Because we cannot recognize more than a few items at a time, selective attention is used to prioritize items for processing. Selective attention to an item allows its features to be bound together into a representation that can be matched to a target template in memory or rejected as a distractor. The binding and recognition of an attended object is modeled as a diffusion process taking > 150 msec/item. Since selection occurs more frequently than that, it follows that multiple items are undergoing recognition at the same time, though asynchronously, making GS6 a hybrid serial and parallel model. If a target is not found, search terminates when an accumulating quitting signal reaches a threshold. Part 2 elaborates on the five sources of Guidance that are combined into a spatial “priority map” to guide the deployment of attention (hence “guided search”). These are (1) top-down and (2) bottom-up feature guidance, (3) prior history (e.g. priming), (4) reward, and (5) scene syntax and semantics. Finally, in Part 3, we will consider the internal representation of what we are searching for; what is often called “the search template”. That search template is really two templates: a guiding template (probably in working memory) and a target template (in long term memory). Put these pieces together and you have GS6.

Human cognitive abilities seem qualitatively different from the cognitive abilities of other primates, a difference Penn, Holyoak, and Povinelli (2008) attribute to role-based relational reasoning—inferences and generalizations based on the relational roles to which objects (and other relations) are bound, rather than just the features of the objects themselves. Role-based relational reasoning depends on the ability to dynamically bind arguments to relational roles. But dynamic binding cannot be sufficient for relational thinking: Some non-human animals solve the dynamic binding problem, at least in some domains; and many non-human species generalize affordances to completely novel objects and scenes, a kind of universal generalization that likely depends on dynamic binding. If they can solve the dynamic binding problem, then why can they not reason about relations? What are they missing? I will present simulations with the LISA model of analogical reasoning (Hummel & Holyoak, 1997, 2003) suggesting that the missing pieces are multi-role integration (the capacity to combine multiple role bindings into complete relations) and structure mapping (the capacity to map different systems of role bindings onto one another). When LISA is deprived of either of these capacities, it can still generalize affordances universally, but it cannot reason symbolically; granted both abilities, LISA enjoys the full power of relational (symbolic) thought. I speculate that one reason it may have taken relational reasoning so long to evolve is that it required evolution to solve both problems simultaneously, since neither multi-role integration nor structure mapping appears to confer any adaptive advantage over simple role binding on its own.

Chromosomes are extremely long, active polymers that are spatially organized across multiple scales to promote cellular functions, such as gene transcription and genetic inheritance. During each cell cycle, chromosomes are dramatically compacted as cells divide and dynamically reorganized into less compact, spatiotemporally patterned structures after cell division. These activities are facilitated by DNA/chromatin-binding protein motors called SMC complexes. Each of these motors can perform a unique activity known as “loop extrusion,” in which the motor binds the DNA/chromatin polymer, reels in the polymer fiber, and extrudes it as a loop. Using simulations and theory, I show how loop-extruding motors can collectively compact and spatially organize chromosomes in different scenarios. First, I show that loop-extruding complexes can generate sufficient compaction for cell division, provided that loop-extrusion satisfies stringent physical requirements. Second, while loop-extrusion alone does not uniquely spatially pattern the genome, interactions between SMC complexes and protein “boundary elements” can generate patterns that emerge in the genome after cell division. Intriguingly, these “boundary elements” are not necessarily stationary, which can generate a variety of patterns in the neighborhood of transcriptionally active genes. These predictions, along with supporting experiments, show how SMC complexes and other molecular machinery, such as RNA polymerase, can spatially organize the genome. More generally, this work demonstrates both the versatility of the loop extrusion mechanism for chromosome functional organization and how seemingly subtle microscopic effects can emerge in the spatiotemporal structure of nonequilibrium polymers.

CA3-CA1 synapses in the hippocampus are the initial locus of episodic memory. The action of acetylcholine alters cellular excitability, modifies neuronal networks, and triggers secondary signaling that directly affects long-term plasticity (LTP) (the cellular underpinning of memory). It is therefore considered a critical regulator of learning and memory in the brain. Its action via M4 metabotropic receptors in the presynaptic terminal of the CA3 neurons and M1 metabotropic receptors in the postsynaptic spines of CA1 neurons produce rich dynamics across multiple timescales. We developed a model to describe the activation of postsynaptic M1 receptors that leads to IP3 production from membrane PIP2 molecules. The binding of IP3 to IP3 receptors in the endoplasmic reticulum (ER) ultimately causes calcium release. This calcium release from the ER activates potassium channels like the calcium-activated SK channels and alters different aspects of synaptic signaling. In an independent signaling cascade, M1 receptors also directly suppress SK channels and the voltage-activated KCNQ2/3 channels, enhancing post-synaptic excitability. In the CA3 presynaptic terminal, we model the reduction of the voltage sensitivity of voltage-gated calcium channels (VGCCs) and the resulting suppression of neurotransmitter release by the action of the M4 receptors. Our results show that the reduced initial release probability because of acetylcholine alters short-term plasticity (STP) dynamics. We characterize the dichotomy of suppressing neurotransmitter release from CA3 neurons and the enhanced excitability of the postsynaptic CA1 spine. Mechanisms underlying STP operate over a few seconds, while those responsible for LTP last for hours, and both forms of plasticity have been linked with very distinct functions in the brain. We show that the concurrent suppression of neurotransmitter release and increased sensitivity conserves neurotransmitter vesicles and enhances the reliability in plasticity. Our work establishes a relationship between STP and LTP coordinated by neuromodulation with acetylcholine.

Visual knowledge obtained from our lifelong experience of the world plays a critical role in our ability to build short-term memories. We propose a mechanistic explanation of how working memory (WM) representations are built from the latent representations of visual knowledge and can then be reconstructed. The proposed model, Memory for Latent Representations (MLR), features a variational autoencoder with an architecture that corresponds broadly to the human visual system and an activation-based binding pool of neurons that binds items’ attributes to tokenized representations. The simulation results revealed that shape information for stimuli that the model was trained on, can be encoded and retrieved efficiently from latents in higher levels of the visual hierarchy. On the other hand, novel patterns that are completely outside the training set can be stored from a single exposure using only latents from early layers of the visual system. Moreover, the representation of a given stimulus can have multiple codes, representing specific visual features such as shape or color, in addition to categorical information. Finally, we validated our model by testing a series of predictions against behavioral results acquired from WM tasks. The model provides a compelling demonstration of visual knowledge yielding the formation of compact visual representation for efficient memory encoding.

Inflammation is a key component of the innate immune response. Primarily designed to remove noxious agents and limit their detrimental effects, the prolonged and/or inappropriately scaled innate immune response may be detrimental to the host and lead to a chronic disease. Indeed, there is increasing evidence suggesting that a chronic deregulation of immunity may represent one of the key elements in the pathobiology of many brain disorders. Microglia are the principal immune cells of the brain. The consensus today is that once activated microglia/macrophages can acquire a wide repertoire of profiles ranging from the classical pro-inflammatory to alternative and protective phenotypes. Recently, we described a novel ribosome-based regulatory mechanism/checkpoint that controls innate immune gene translation and microglial activation involving RNA binding protein SRSF3. Here we will discuss the implications of SRSF3 and other endogenous immune regulators in deregulation of immunity observed in different models of brain pathologies. Furthermore, we will discuss whether targeting SRSF3 and mRNA translation may open novel avenues for therapeutic modulation of immune response in the brain.

Claude Desplan is a Silver Professor of Biology and Neuroscience at NYU. He was born in Algeria and was trained at Ecole Normale Supérieure St. Cloud, France. He received his DSc at INSERM in Paris in 1983 and joined Pat O’Farrell at UCSF as a postdoc. There he demonstrated that the homeodomain, a conserved signature of many developmental genes, is a DNA binding motif. Currently, Dr. Desplan works at NYU where he investigates the generation of neural diversity using the Drosophila visual system.

Tuberous sclerosis complex (TSC) and focal cortical dysplasia type II (FCDII) are caused by mutations in mTOR pathway genes leading to mTOR hyperactivity, focal malformations of cortical development (fMCD), and seizures in 80-90% of the patients. The current definitive treatments for epilepsy are surgical resection or treatment with everolimus, which inhibits mTOR activity (only approved for TSC). Because both options have severe limitations, there is a major need to better understand the mechanisms leading to seizures to improve life-long epilepsy treatment in TSC and FCDII. To investigate such mechanisms, we recently developed a murine model of fMCD-associated epilepsy that recapitulates the human TSC and FCDII disorders. fMCD are defined by the presence of misplaced, dysmorphic cortical neurons expressing hyperactive mTOR – for simplicity we will refer to these as “mutant” neurons. In our model and in human TSC tissue, we made a surprising finding that mutant neurons express HCN4 channels, which are not normally functionally expressed in cortical neurons, and increased levels of filamin A (FLNA). FLNA is an actin-crossing linking molecule that has also multiple binding partners inside cells. These data led us to ask several important questions: (1) As HCN4 channels are responsible for the pacemaking activity of the heart, can HCN4 channel expression lead to repetitive firing of mutant neurons resulting in seizures? (2) HCN4 is the most cAMP-sensitive of the four HCN isoforms. Does increase in cAMP lead to the firing of mutant neurons? (3) Does increase in FLNA contribute to neuronal alterations and seizures? (4) Is the abnormal HCN4 and FLNA expression in mutant neurons due to mTOR? These questions will be discussed and addressed in the lecture.

Developmental and epileptic encephalopathies (DEEs) are a broad spectrum of genetic epilepsies associated with impaired neurological development as a direct consequence of a genetic mutation, in addition to the effect of the frequent epileptic activity on brain. Compelling genetic studies indicate that heterozygous de novo mutations represent the most common underlying genetic mechanism, in accordance with the sporadic presentation of DEE. De novo mutations may exert a loss-of-function (LOF) on the protein by decrementing expression level and/or activity, leading to functional haploinsufficiency. These diseases share several features: severe and frequent refractory seizures, diffusely abnormal background activity on EEG, intellectual disability often profound, and severe consequences on global development. One of major causes of early onset DEE are de novo heterozygous mutations in syntaxin-binding-protein-1 gene STXBP1, which encodes a membrane trafficking protein playing critical role in vesicular docking and fusion. LOF STXBP1 mutations lead to a failure of neurotransmitter secretion from synaptic vesicles. Core clinical features of STXBP1 encephalopathy include early-onset epilepsy with hypsarrhythmic EEG, or burst-suppression pattern, or multifocal epileptiform activity. Seizures are often resistant to standard treatments and patients typically show intellectual disability, mostly severe to profound. Additional neurologic features may include autistic traits, movement disorders (dyskinesia, dystonia, tremor), axial hypotonia, and ataxia, indicating a broader neurologic impairment. Patients with severe neuro-cognitive features but without epilepsy have been reported. Recently, a new class of natural and synthetic non-coding RNAs have been identified, enabling upregulation of protein translation in a gene-specific way (SINEUPs), without any increase in mRNA of the target gene. SINEUPs are translational activators composed by a Binding Domain (BD) that overlaps, in antisense orientation, to the sense protein-coding mRNA, and determines target selection; and an Effector Domain (ED), that is essential for protein synthesis up regulation. SINEUPs have been shown to restore the physiological expression of a protein in case of haploinsufficiency, without driving excessive overexpression out of the physiological range. This technology brings many advantages, as it mainly acts on endogenous target mRNAs produced in situ by the wild-type allele; this action is limited to mRNA under physiological regulation, therefore no off-site effects can be expected in cells and tissues that do not express the target transcript; by acting only on a posttranscriptional level, SINEUPs do not trigger hereditable genome editing. After bioinformatic analysis of the promoter region of interest, we designed SINEUPs with 3 different BD for STXBP1. Human neurons from iPSCs were treated and STXBP1 levels showed a 1.5-fold increase compared to the Negative control. RNA levels of STXBP1 after the administration of SINEUPs remained stable as expected. These preliminary results proved the SINEUPs potential to specifically increase the protein levels without impacting on the genome. This is an extremely flexible approach to target many developmental and epileptic encephalopathies caused by haploinsufficiency, and therefore to address these diseases in a more tailored and radical way.

The eyes send a continuous stream of about two million nerve fibers to the brain, but only a fraction of this information is stored as visual memories. This talk will detail three neurocomputational models that attempt an understanding how the visual system makes on-the-fly decisions about how to encode that information. First, the STST family of models (Bowman & Wyble 2007; Wyble, Potter, Bowman & Nieuwenstein 2011) proposes mechanisms for temporal segmentation of continuous input. The conclusion of this work is that the visual system has mechanisms for rapidly creating brief episodes of attention that highlight important moments in time, and also separates each episode from temporally adjacent neighbors to benefit learning. Next, the RAGNAROC model (Wyble et al. 2019) describes a decision process for determining the spatial focus (or foci) of attention in a spatiotopic field and the neural mechanisms that provide enhancement of targets and suppression of highly distracting information. This work highlights the importance of integrating behavioral and electrophysiological data to provide empirical constraints on a neurally plausible model of spatial attention. The model also highlights how a neural circuit can make decisions in a continuous space, rather than among discrete alternatives. Finally, the binding pool (Swan & Wyble 2014; Hedayati, O’Donnell, Wyble in Prep) provides a mechanism for selectively encoding specific attributes (i.e. color, shape, category) of a visual object to be stored in a consolidated memory representation. The binding pool is akin to a holographic memory system that layers representations of select latent representations corresponding to different attributes of a given object. Moreover, it can bind features into distinct objects by linking them to token placeholders. Future work looks toward combining these models into a coherent framework for understanding the full measure of on-the-fly attentional mechanisms and how they improve learning.

The talk will give a tour of Guided Search 6.0 (GS6), the latest evolution of Guided Search. Part 1 describes The Mechanics of Search. Because we cannot recognize more than a few items at a time, selective attention is used to prioritize items for processing. Selective attention to an item allows its features to be bound together into a representation that can be matched to a target template in memory or rejected as a distractor. The binding and recognition of an attended object is modeled as a diffusion process taking > 150 msec/item. Since selection occurs more frequently than that, it follows that multiple items are undergoing recognition at the same time, though asynchronously, making GS6 a hybrid serial and parallel model. If a target is not found, search terminates when an accumulating quitting signal reaches a threshold. Part 2 elaborates on the five sources of Guidance that are combined into a spatial “priority map” to guide the deployment of attention (hence “guided search”). These are (1) top-down and (2) bottom-up feature guidance, (3) prior history (e.g. priming), (4) reward, and (5) scene syntax and semantics. In GS6, the priority map is a dynamic attentional landscape that evolves over the course of search. In part, this is because the visual field is inhomogeneous. Part 3: That inhomogeneity imposes spatial constraints on search that described by three types of “functional visual field” (FVFs): (1) a resolution FVF, (2) an FVF governing exploratory eye movements, and (3) an FVF governing covert deployments of attention. Finally, in Part 4, we will consider that the internal representation of the search target, the “search template” is really two templates: a guiding template and a target template. Put these pieces together and you have GS6.

Cement is the main binding agent in concrete, literally gluing together rocks and sand into the most-used synthetic material on Earth. However, cement production is responsible for significant amounts of man- made greenhouse gases—in fact if the cement industry were a country, it would be the third largest emitter in the world. Alternatives to the current, environmentally harmful cement production process are not available essentially because the gaps in fundamental understanding hamper the development of smarter and more sustainable solutions. The ultimate challenge is to link the chemical composition of cement grains to the nanoscale physics of the cohesive forces that emerge when mixing cement with water. Cement nanoscale cohesion originates from the electrostatics of ions accumulated in a water-based solution between like-charged surfaces but it is not captured by existing theories because of the nature of the ions involved and the high surface charges. Surprisingly enough, this is also the case for unexplained cohesion in a range of colloidal and biological matter. About one century after the early studies of cement hydration, we have quantitatively solved this notoriously hard problem and discovered how cement cohesion develops during hydration. I will discuss how 3D numerical simulations that feature a simple but molecular description of ions and water, together with an analytical theory that goes beyond the traditional continuum approximations, helped us demonstrate that the optimized interlocking of ion-water structures determine the net cohesive forces and their evolution. These findings open the path to scientifically grounded strategies of material design for cements and have implications for a much wider range of materials and systems where ionic water-based solutions feature both strong Coulombic and confinement effects, ranging from biological membranes to soils. Construction materials are central to our society and to our life as humans on this planet, but usually far removed from fundamental science. We can now start to understand how cement physical-chemistry determines performance, durability and sustainability.

Proteins and membranes form remarkably complex structures that are key to intracellular compartmentalization, cargo transport, and cell morphology. Despite this wealth of examples in living systems, we still lack design principles for controlling membrane morphology in synthetic systems. With experiments and simulations, we show that even the simple case of spherical or rod-shaped nanoparticles binding to lipid-bilayer membrane vesicles results in a remarkably rich set of morphologies that can be reliably controlled via the particle binding energy. When the binding energy is weak relative to a characteristic membrane-bending energy, vesicles adhere to one another and form a soft solid gel, which is a useful platform for controlled release. With larger binding energy, a transition from partial to complete wrapping of the nanoparticles causes a remarkable vesicle destruction process culminating in rupture, nanoparticle-membrane tubules, and vesicle inversion. We have explored the behavior across a wide range of parameter space. These findings help unify the wide range of effects observed when vesicles or cells are exposed to nanoparticles. They also show how they open the door to a new class of vesicle-based, closed-cell gels that are more than 99% water and can encapsulate and release on demand. I will discuss how triggering membrane remodeling could lead to shape-responsive systems in the future.

Evidence regarding protein structure and function manifest the imperative role that dynamics play in proteins, underlining reconsideration of the unanimated sequence-to-structure-to-function paradigm. Structural dynamics portray a heterogeneous energy landscape described by conformational ensembles where each structural representation can be responsible for unique functions or enable macromolecular assemblies. Using the human p27/Cdk2/Cyclin A ternary complex as an example, we highlight the vital role of intra- and intermolecular dynamics for target recognition, binding, and inhibition as a critical modulator of cell division. Rapidly sampling configurations is critical for the population of different conformational ensembles encoding functional roles. To garner this knowledge, we present how the integration of (sub)ensemble and single-molecule fluorescence spectroscopy with molecular dynamic simulations can characterize structural dynamics linking the heterogeneous ensembles to function. The incorporation of dynamics into the sequence-to-structure-to-function paradigm promises to assist in tackling various challenges, including understanding the formation and regulation of mesoscale assemblies inside cells.

In the last decades, the post-transcriptional control of gene expression has become an area of intense investigation, delineating a complex scenario where several factors (e.g. RNA-binding proteins, coding and non-coding RNAs) orchestrate the fate of a given transcript. An intriguing hypothesis suggests that loss of RNA homeostasis is a central feature of many pathological states, including eye diseases. Since the elav (embryonic lethal, abnormal visual system) gene discovery in the Drosophila melanogaster, the mammalian ELAV-like family has confirmed its leading role in controlling the RNA metabolism (from splicing to translation) of genes with a key function in many physio-pathological contexts. Some relevant findings suggest the involvement of the HuR/ELAV-like1 member and its potential as a therapeutic target in age-related ocular pathologies.

Diets rich in sugar, salt, and fat alter taste perception and food intake, leading to obesity and metabolic disorders, but the molecular mechanisms through which this occurs are unknown. Here we show that in response to a high sugar diet, the epigenetic regulator Polycomb Repressive Complex 2.1 (PRC2.1) persistently reprograms the sensory neurons of D. melanogaster flies to reduce sweet sensation and promote obesity. In animals fed high sugar, the binding of PRC2.1 to the chromatin of the sweet gustatory neurons is redistributed to repress a developmental transcriptional network that modulates the responsiveness of these cells to sweet stimuli, reducing sweet sensation. Importantly, half of these transcriptional changes persist despite returning the animals to a control diet, causing a permanent decrease in sweet taste. Our results uncover a new epigenetic mechanism that, in response to the dietary environment, regulates neural plasticity and feeding behavior to promote obesity.