I'm happy to announce the Architectures of Biological Learning Lab is Hiring! I'm looking for exceptional candidates at the MSc, PhD or post-doc level to work on "Dendritic Algorithms for Perceptual Learning". The project will employ simulations of pyramidal neurons and plasticity, and deep convolutional networks to study representation learning in the neocortex. Prior experience with Python, NEURON, and/or PyTorch would be an asset. This project will be undertaken in collaboration with Profs. Yoshua Bengio (UdeM, Mila), Roberto Araya (UdeM, CRCHUSJ), and Blake Richards (McGill, Mila). Montreal, Canada is a thriving international hub for Artificial Intelligence and Neuroscience research, with a booming AI industry. It's where Donald O. Hebb originally formulated Hebbian Learning. It's also a vibrant, funky, cosmopolitan yet affordable city of over 4 million, referred to as "Canada's Cultural Capital" by Monocle magazine. In 2017, Montreal was ranked the 12th-most liveable city in the world by the Economist Intelligence Unit in its annual Global Liveability Ranking, and the best city in the world to be a university student in the QS World University Rankings. For more details and instructions how to apply, please visit: https://bit.ly/3l1PGFH

Postdoctoral and graduate research positions are available at Western University (London, ON) and the Fields Lab for Network Science (Toronto, ON). These positions will be supervised by Lyle Muller and involve collaborations with advanced methods of brain imaging (Mark Schnitzer, Stanford), neuroengineering (Duygu Kuzum, UCSD), theoretical neuroscience (Todd Coleman, Stanford), and neurophysiology of visual perception (John Reynolds, Salk Institute for Biological Studies). In collaboration with this multi-disciplinary team, researchers will bring together data science, computational science, and applied mathematics to understand spatiotemporal dynamics and computation in the circuits of neocortex. The project may include intermittent travel between labs to present results and facilitate collaborative work.

Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally-generated top-down information reflecting past experiences and current aims. Decades of work have elucidated how sensory neocortex processes physical stimulus features. In contrast, examining how memory-related-top-down information is encoded and integrated with bottom-up signals has long been challenging. Here, I will discuss our recent work pinpointing the outermost layer 1 of neocortex as a central hotspot for processing of experience-dependent top-down information threat during perception, one of the most fundamentally important forms of sensation.

The neocortex is considered to be the seat of higher cognitive functions in humans. During its evolution, most notably in humans, the neocortex has undergone considerable expansion, which is reflected by an increase in the number of neurons. Neocortical neurons are generated during development by neural stem and progenitor cells. Epigenetic mechanisms play a pivotal role in orchestrating the behaviour of stem cells during development. We are interested in the mechanisms that regulate gene expression in neural stem cells, which have implications for our understanding of neocortex development and evolution, neural stem cell regulation and neurodevelopmental disorders.

There is a fundamental tension between storing discrete traces of individual experiences, which allows recall of particular moments in our past without interference, and extracting regularities across these experiences, which supports generalization and prediction in similar situations in the future. One influential proposal for how the brain resolves this tension is that it separates the processes anatomically into Complementary Learning Systems, with the hippocampus rapidly encoding individual episodes and the neocortex slowly extracting regularities over days, months, and years. But this does not explain our ability to learn and generalize from new regularities in our environment quickly, often within minutes. We have put forward a neural network model of the hippocampus that suggests that the hippocampus itself may contain complementary learning systems, with one pathway specializing in the rapid learning of regularities and a separate pathway handling the region’s classic episodic memory functions. This proposal has broad implications for how we learn and represent novel information of specific and generalized types, which we test across statistical learning, inference, and category learning paradigms. We also explore how this system interacts with slower-learning neocortical memory systems, with empirical and modeling investigations into how the hippocampus shapes neocortical representations during sleep. Together, the work helps us understand how structured information in our environment is initially encoded and how it then transforms over time.

Recent studies identified memory engram neurons, a neuronal population that is recruited by initial learning and is reactivated during memory recall.  Memory engram neurons are connected to one another through memory engram synapses in a distributed network of brain areas.  Our central hypothesis is that an associative memory is encoded and consolidated by selective strengthening of engram synapses.  We are testing this hypothesis, using a combination of engram cell labeling, optogenetic/chemogenetic, electrophysiological, and virus tracing approaches in rodent models of contextual fear conditioning.  In this talk, I will discuss our findings on how synaptic plasticity in memory engram synapses contributes to the acquisition and consolidation of contextual fear memory in a distributed network of the amygdala, hippocampus, and neocortex.

The ability to organise one's body for action without having to think about it is taken for granted, whether it is handwriting, typing on a smartphone or computer keyboard, tying a shoelace or playing the piano. When compromised, e.g. in stroke, neurodegenerative and developmental disorders, the individuals’ study, work and day-to-day living are impacted with high societal costs. Until recently, indirect methods such as invasive recordings in animal models, computer simulations, and behavioural markers during sequence execution have been used to study covert motor sequence planning in humans. In this talk, I will demonstrate how multivariate pattern analyses of non-invasive neurophysiological recordings (MEG/EEG), fMRI, and muscular recordings, combined with a new behavioural paradigm, can help us investigate the structure and dynamics of motor sequence control before and after movement execution. Across paradigms, participants learned to retrieve and produce sequences of finger presses from long-term memory. Our findings suggest that sequence planning involves parallel pre-ordering of serial elements of the upcoming sequence, rather than a preparation of a serial trajectory of activation states. Additionally, we observed that the human neocortex automatically reorganizes the order and timing of well-trained movement sequences retrieved from memory into lower and higher-level representations on a trial-by-trial basis. This echoes behavioural transfer across task contexts and flexibility in the final hundreds of milliseconds before movement execution. These findings strongly support a hierarchical and dynamic model of skilled sequence control across the peri-movement phase, which may have implications for clinical interventions.

Within the vertebrate neocortex and other telencephalic structures, molecularly-defined neurons tend to segregate at first order into GABAergic types and glutamatergic types. Two fundamental questions arise: (1) do non-telencephalic neurons similarly segregate by neurotransmitter status, and (2) do GABAergic (or glutamatergic) types sampled in different structures share many molecular features in common, beyond the few genes directly responsible for neurotransmitter synthesis and release? To address these questions, we used single-nucleus RNA sequencing, analyzing over 2.4 million brain cells sampled from 16 locations in a primate (the common marmoset). Unexpectedly, we find the answer to both is “no”. I will discuss implications for generalizing associations between neurotransmitter utilization and other phenotypes, and share ongoing efforts to map the biodistributions of cell types in the primate brain.

Evolutionarily, the expansion of the human neocortex accounts for many of the unique cognitive abilities of humans. This expansion appears to reflect the increased proliferative potential of basal progenitors (BPs) in mammalian evolution. Further cortical progenitors generate both glutamatergic excitatory neurons (ENs) and GABAergic inhibitory interneurons (INs) in human cortex, whereas they produce exclusively ENs in rodents. The increased proliferative capacity and neuronal subtype generation of cortical progenitors in mammalian evolution may have evolved through epigenetic alterations. However, whether or how the epigenome in cortical progenitors differs between humans and other species is unknown. Here, we report that histone H3 acetylation is a key epigenetic regulation in BP profiling of sorted BPs, we show that H3K9 acetylation is low in murine BPs and high in amplification, neuronal subtype generation and cortical expansion. Through epigenetic profiling of sorted BPs, we show that H3K9 acetylation is low in murine BPs and high in human BPs. Elevated H3K9ac preferentially increases BP proliferation, increasing the size and folding of the normally smooth mouse neocortex. Furthermore, we found that the elevated H3 acetylation activates expression of IN genes in in developing mouse cortex and promote proliferation of IN progenitor-like cells in cortex of Pax6 mutant mouse models. Mechanistically, H3K9ac drives the BP amplification and proliferation of these IN progenitor-like cells by increasing expression of the evolutionarily regulated gene, TRNP1. Our findings demonstrate a previously unknown mechanism that controls neocortex expansion and generation of neuronal subtypes. Keywords: Cortical development, neurogenesis, basal progenitors, cortical size, gyrification, excitatory neuron, inhibitory interneuron, epigenetic profiling, epigenetic regulation, H3 acetylation, H3K9ac, TRNP1, PAX6

In understanding circuit operations, a key issue is the extent to which neuronal spiking reflects local computation or responses to upstream inputs. Because pyramidal cells in CA1 do not have local recurrent projections, it is currently assumed that firing in CA1 is inherited from its inputs – thus, entorhinal inputs provide communication with the rest of the neocortex and the outside world, whereas CA3 inputs provide internal and past memory representations. Several studies have attempted to prove this hypothesis, by lesioning or silencing either area CA3 or the entorhinal cortex and examining the effect of firing on CA1 pyramidal cells. Despite the intense and careful work in this research area, the magnitudes and types of the reported physiological impairments vary widely across experiments. At least part of the existing variability and conflicts is due to the different behavioral paradigms, designs and evaluation methods used by different investigators. Simultaneous manipulations in the same animal or even separate manipulations of the different inputs to the hippocampal circuits in the same experiment are rare. To address these issues, I used optogenetic silencing of unilateral and bilateral mEC, of the local CA1 region, and performed bilateral pharmacogenetic silencing of the entire CA3 region. I combined this with high spatial resolution recording of local field potentials (LFP) in the CA1-dentate axis and simultaneously collected firing pattern data from thousands of single neurons. Each experimental animal had up to two of these manipulations being performed simultaneously. Silencing the medial entorhinal (mEC) largely abolished extracellular theta and gamma currents in CA1, without affecting firing rates. In contrast, CA3 and local CA1 silencing strongly decreased firing of CA1 neurons without affecting theta currents. Each perturbation reconfigured the CA1 spatial map. Yet, the ability of the CA1 circuit to support place field activity persisted, maintaining the same fraction of spatially tuned place fields, and reliable assembly expression as in the intact mouse. Thus, the CA1 network can maintain autonomous computation to support coordinated place cell assemblies without reliance on its inputs, yet these inputs can effectively reconfigure and assist in maintaining stability of the CA1 map.

Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy usage are regulated during food scarcity. I addressed this in the visual cortex of awake mice using whole-cell recordings and two-photon imaging to monitor layer 2/3 neuronal activity and ATP usage. I found that food restriction reduced synaptic ATP usage by 29% through a decrease in AMPA receptor conductance. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting membrane potential. Consequently, neurons spiked at similar rates as controls, but spent less ATP on underlying excitatory currents. This energy-saving strategy had a cost since it amplified the variability of visually-evoked subthreshold responses, leading to a 32% broadening in orientation tuning and impaired fine visual discrimination. This reduction in coding precision was associated with reduced levels of the fat mass-regulated hormone leptin and was restored by exogenous leptin supplementation. These findings reveal novel mechanisms that dynamically regulate energy usage and coding precision in neocortex.

Establishment of precise neuronal connectivity in the neocortex relies on activity-dependent circuit reorganization during postnatal development. In the mouse somatosensory cortex layer 4, barrels are arranged in one-to-one correspondence to whiskers on the face. Thalamocortical axon termini are clustered in the center of each barrel. The layer 4 spiny stellate neurons are located around the barrel edge, extend their dendrites primarily toward the barrel center, and make synapses with thalamocortical axons corresponding to a single whisker. These organized circuits are established during the first postnatal week through activity-dependent refinement processes. However, activity pattern regulating the circuit formation is still elusive. Using two-photon calcium imaging in living neonatal mice, we found that layer 4 neurons within the same barrel fire synchronously in the absence of peripheral stimulation, creating a ''patchwork'' pattern of spontaneous activity corresponding to the barrel map. We also found that disruption of GluN1, an obligatory subunit of the N-methyl-D-aspartate (NMDA) receptor, in a sparse population of layer 4 neurons reduced activity correlation between GluN1 knockout neuron pairs within a barrel. Our results provide evidence for the involvement of layer 4 neuron NMDA receptors in spatial organization of the spontaneous firing activity of layer 4 neurons in the neonatal barrel cortex. In the talk I will introduce our strategy to analyze the role of NMDA receptor-dependent correlated activity in the layer 4 circuit formation.

Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy usage are regulated during food scarcity. We addressed this in the visual cortex of awake mice using whole-cell patch clamp recordings and two-photon imaging to monitor layer 2/3 neuronal activity and ATP usage. We found that food restriction resulted in energy savings through a decrease in AMPA receptor conductance, reducing synaptic ATP usage by 29%. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting membrane potential. Consequently, neurons spiked at similar rates as controls, but spent less ATP on underlying excitatory currents. This energy-saving strategy had a cost since it amplified the variability of visually-evoked subthreshold responses, leading to a 32% broadening in orientation tuning and impaired fine visual discrimination. These findings reveal novel mechanisms that dynamically regulate energy usage and coding precision in neocortex.

Predictive learning hypotheses posit that the neocortex learns a hierarchical model of the structure of features in the environment. Under these hypotheses, expected or predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of data, with unexpected features then driving changes in the representation of incoming stimuli. This is supported by numerous studies in early sensory cortices showing that pyramidal neurons respond particularly strongly to unexpected stimulus events. However, it remains unknown how their responses govern subsequent changes in stimulus representations, and thus, govern learning. Here, I present results from our study of layer 2/3 and layer 5 pyramidal neurons imaged in primary visual cortex of awake, behaving mice using two-photon calcium microscopy at both the somatic and distal apical planes. Our data reveals that individual neurons and distal apical dendrites show distinct, but predictable changes in unexpected event responses when tracked over several days. Considering existing evidence that bottom-up information is primarily targeted to somata, with distal apical dendrites receiving the bulk of top-down inputs, our findings corroborate hypothesized complementary roles for these two neuronal compartments in hierarchical computing. Altogether, our work provides novel evidence that the neocortex indeed instantiates a predictive hierarchical model in which unexpected events drive learning.

Neuromodulators control information processing in cortical microcircuits by regulating the cellular and synaptic physiology of neurons. Computational models and detailed simulations of neocortical microcircuitry offer a unifying framework to analyze the role of neuromodulators on network activity. In the present study, to get a deeper insight in the organization of the cortical neuropil for modeling purposes, we quantify the fiber length per cortical volume and the density of varicosities for catecholaminergic, serotonergic and cholinergic systems using immunocytochemical staining and stereological techniques. The data obtained are integrated into a biologically detailed digital reconstruction of the rodent neocortex (Markram et al, 2015) in order to model the influence of modulatory systems on the activity of the somatosensory cortex neocortical column. Simulations of ascending modulation of network activity in our model predict the effects of increasing levels of neuromodulators on diverse neuron types and synapses and reveal a spectrum of activity states. Low levels of neuromodulation drive microcircuit activity into slow oscillations and network synchrony, whereas high neuromodulator concentrations govern fast oscillations and network asynchrony. The models and simulations thus provide a unifying in silico framework to study the role of neuromodulators in reconfiguring network activity.

New memories are initially labile and have to be consolidated into stable long-term representations. Current theories assume that this is supported by a shift in the neural substrate that supports the memory, away from rapidly plastic hippocampal networks towards more stable representations in the neocortex. Rehearsal, i.e. repeated activation of the neural circuits that store a memory, is thought to crucially contribute to the formation of neocortical long-term memory representations. This may either be achieved by repeated study during wakefulness or by a covert reactivation of memory traces during offline periods, such as quiet rest or sleep. My research investigates memory consolidation in the human brain with multivariate decoding of neural processing and non-invasive in-vivo imaging of microstructural plasticity. Using pattern classification on recordings of electrical brain activity, I show that we spontaneously reprocess memories during offline periods in both sleep and wakefulness, and that this reactivation benefits memory retention. In related work, we demonstrate that active rehearsal of learning material during wakefulness can facilitate rapid systems consolidation, leading to an immediate formation of lasting memory engrams in the neocortex. These representations satisfy general mnemonic criteria and cannot only be imaged with fMRI while memories are actively processed but can also be observed with diffusion-weighted imaging when the traces lie dormant. Importantly, sleep seems to hold a crucial role in stabilizing the changes in the contribution of memory systems initiated by rehearsal during wakefulness, indicating that online and offline reactivation might jointly contribute to forming long-term memories. Characterizing the covert processes that decide whether, and in which ways, our brains store new information is crucial to our understanding of memory formation. Directly imaging consolidation thus opens great opportunities for memory research.

There is a long-standing tension between the notion that the hippocampal formation is essentially a spatial mapping system, and the notion that it plays an essential role in the establishment of episodic memory and the consolidation of such memory into structured knowledge about the world. One theory that resolves this tension is the notion that the hippocampus generates rather arbitrary 'index' codes that serve initially to link attributes of episodic memories that are stored in widely dispersed and only weakly connected neocortical modules. I will show how an essentially 'spatial' coding mechanism, with some tweaks, provides an ideal indexing system and discuss the neural coding strategies that the hippocampus apparently uses to overcome some biological constraints affecting the possibility of shipping the index code out widely to the neocortex. Finally, I will present new data suggesting that the hippocampal index code is indeed transferred to layer II-III of the neocortex.

Neocortical-hippocampal interactions during off-line periods such as slow-wave sleep are implicated in memory processing. In particular, recent memory traces are replayed in hippocampus during some sharp-wave ripple (SWR) events, and these replay events are positively correlated with neocortical memory trace reactivation. A prevalent model is that SWR arise ‘spontaneously’ in CA3 and propagate recent memory ‘indices’ outward to the neocortex to enable memory consolidation there; however, the spatiotemporal distribution of neocortical activation relative to SWR is incompletely understood. We used wide-field optical imaging to study voltage and glutamate release transients in dorsal neocortex in relation to CA1 multiunit activity (MUA) and SWR of sleeping and urethane anesthetized mice. Modulation of voltage and glutamate release signals in relation to SWRs varied across superficial neocortical regions, and it was largest in posteromedial regions surrounding retrosplenial cortex (RSC), which receives strong hippocampal output connections. Activity tended to spread sequentially from more medial towards more lateral regions. Contrary to the unidirectional hypothesis, activation exhibited a continuum of timing relative to SWRs, varying from neocortex leading to neocortex lagging the SWRs (± ~250 msec). The timing continuum was correlated with the skewness of peri-SWR hippocampal MUA and with a tendency for some SWR to occur in clusters. Thus, contrary to the model in which SWRs arise spontaneously in hippocampus, neocortical activation often precedes SWRs and may thus constitute a trigger event in which neocortical information seeds associative reactivation of hippocampal ‘indices’.

Drawing on recent findings from evolutionary anthropology and neuroscience, professor Barton will lead us through the amazing story of the evolution of human cognition. Usingstatistical, phylogenetic analyses that tease apart the variation associated with different neural systems and due to different selection pressures, he will be addressing intriguing questions like ‘Why are there so many neurons in the cerebellum?’, ‘Is the neocortex the ‘intelligent’ bit of the brain?’, and ‘What explains that the recognition by humans of emotional expressions is disrupted by trancranial magnetic stimulation of the somatosensory cortex?’ Could, as professor Barton suggests, the cerebellum -modestly concealed beneath the volumetrically dominating neocortex and largely ignored- turn out to be the Cinderella of the study of brain evolution?

The symposium will start with Prof Song-Hai Shi who will present “Assembly of the neocortex”. Then, Dr Lynette Lim will talk about “Shared and Unique Developmental Trajectories of Cortical Inhibitory Neurons”. Dr Alfredo Molina will deal with the “Tuneable progenitor cells to build the cerebral cortex”, and Prof Tomasz Nowakowski will present “Charting the molecular 'protomap' of the human cerebral cortex using single cell genomic”.

Neural codes, such as temporal codes (precisely timed spikes) and rate codes (instantaneous spike firing rates), are believed to be used in encoding sensory information into spike trains of cortical neurons. Temporal and rate codes co-exist in the spike train and such multiplexed neural code-carrying spike trains have been shown to be spatially synchronized in multiple neurons across different cortical layers during sensory information processing. Inhibition is suggested to promote such synchronization, but it is unclear whether distinct subtypes of interneurons make different contributions in the synchronization of multiplexed neural codes. To test this, in vivo single-unit recordings from barrel cortex were combined with optogenetic manipulations to determine the contributions of parvalbumin (PV)- and somatostatin (SST)-positive interneurons to synchronization of precisely timed spike sequences. We found that PV interneurons preferentially promote the synchronization of spike times when instantaneous firing rates are low (<12 Hz), whereas SST interneurons preferentially promote the synchronization of spike times when instantaneous firing rates are high (>12 Hz). Furthermore, using a computational model, we demonstrate that these effects can be explained by PV and SST interneurons having preferential contribution to feedforward and feedback inhibition, respectively. Overall, these results show that PV and SST interneurons have distinct frequency (rate code)-selective roles in dynamically gating the synchronization of spike times (temporal code) through preferentially recruiting feedforward and feedback inhibitory circuit motifs. The inhibitory neural circuit mechanisms we uncovered here his may have critical roles in regulating neural code-based somatosensory information processing in the neocortex.

The symposium will start with Prof Cooper who will present “From neural tube to neocortex: the role of adhesion in maintaining stem cell morphology and function”. Then, Dr Tsai will talk about “In the search for new genes involved in brain development and disorders”. Dr Del Pino will deal with the “Regulation of intrinsic network activity during area patterning in the cerebral cortex”, and Dr Wang will present “Modelling Neurodevelopmental Disorders in Flies”.

Arguably one of the biggest mysteries in neuroscience is how the brain stores long-term memories. The major challenge for investigating the neural circuit underlying memory formation in the neocortex is the distributed nature of the resulting memory trace throughout the cortex. Here, we used a new behavioral paradigm that enabled us to generate memory traces in a specific cortical location and to specifically examine the mechanisms of memory formation in that region. We found that medial-temporal inputs arrive in neocortical layer 1 where the apical dendrites of cortical pyramidal neurons predominate. These dendrites have active properties that make them sensitive to contextual inputs from other areas that also send axons to layer 1 around the cortex. Blocking the influence of these medial-temporal inputs prevented learning and suppressed resulting dendritic activity. We conclude that layer 1 is the locus for hippocampal-dependent memory formation in the neocortex and propose that this process enhances the sensitivity of the tuft dendrites to contextual inputs.

This seminar is part of our “Emergent Scientists” series, an initiative that provides a platform for scientists at the critical PhD/postdoc transition period to share their work with a broad audience and network. Summary: These talks cover Alzheimer’s disease (AD) research in both mice and humans. Christiana will discuss in particular the translational aspects of applying mouse work to humans and the importance of timing in disease pathology and intervention (e.g. timing between AD biomarkers vs. symptom onset, timing of therapy, etc.). Siddharth will discuss a rare variant of Alzheimer’s disease called “Logopenic Progressive Aphasia”, which presents with temporo-parietal atrophy yet relative sparing of hippocampal circuitry. Siddharth will discuss how, despite the unusual anatomical basis underlying this AD variant, degeneration of the angular gyrus in the left inferior parietal lobule contributes to memory deficits similar to those of typical amnesic Alzheimer’s disease. Christiana’s abstract: Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder that causes severe deterioration of memory, cognition, behavior, and the ability to perform daily activities. The disease is characterized by the accumulation of two proteins in fibrillar form; Amyloid-β forms fibrils that accumulate as extracellular plaques while tau fibrils form intracellular tangles. Here we aim to translate findings from a commonly used AD mouse model to AD patients. Here we initiate and chronically inhibit neuropathology in lateral entorhinal cortex (LEC) layer two neurons in an AD mouse model. This is achieved by over-expressing P301L tau virally and chronically activating hM4Di DREADDs intracranially using the ligand dechloroclozapine. Biomarkers in cerebrospinal fluid (CSF) is measured longitudinally in the model using microdialysis, and we use this same system to intracranially administer drugs aimed at halting AD-related neuropathology. The models are additionally tested in a novel contextual memory task. Preliminary findings indicate that viral injections of P301L tau into LEC layer two reveal direct projections between this region and the outer molecular layer of dentate gyrus and the rest of hippocampus. Additionally, phosphorylated tau co-localize with ‘starter cells’ and appear to spread from the injection site. Preliminary microdialysis results suggest that the concentrations of CSF amyloid-β and tau proteins mirror changes observed along the disease cascade in patients. The disease-modifying drugs appear to halt neuropathological development in this preclincial model. These findings will lead to a novel platform for translational AD research, linking the extensive research done in rodents to clinical applications. Siddharth’s abstract: A distributed brain network supports our ability to remember past events. The parietal cortex is a critical member of this network, yet, its exact contributions to episodic remembering remain unclear. Neurodegenerative syndromes affecting the posterior neocortex offer a unique opportunity to understand the importance and role of parietal regions to episodic memory. In this talk, I introduce and explore the rare neurodegenerative syndrome of Logopenic Progressive Aphasia (LPA), an aphasic variant of Alzheimer’s disease presenting with early, left-lateralized temporo-parietal atrophy, amidst relatively spared hippocampal integrity. I then discuss two key studies from my recent Ph.D. work showcasing pervasive episodic and autobiographical memory dysfunction in LPA, to a level comparable to typical, amnesic Alzheimer’s disease. Using multimodal neuroimaging, I demonstrate how degeneration of the angular gyrus in the left inferior parietal lobule, and its structural connections to the hippocampus, contribute to amnesic profiles in this syndrome. I finally evaluate these findings in the context of memory profiles in other posterior cortical neurodegenerative syndromes as well as recent theoretical models underscoring the importance of the parietal cortex in the integration and representation of episodic contextual information.

In the last 500 million years, the dorsal telencephalon changed like no other region of the vertebrate brain. Differences range from the six-layered neocortex of mammals, to the small three-layered cortex of reptiles, and the complete absence of lamination in birds. These anatomical differences have prompted endless discussions on the origins and evolution of the cerebral cortex. We have approached this problem from a cell type and transcriptomics perspective. This reveals a more granular picture, where different cell types and classes have followed independent trajectories of evolutionary change. In this presentation, I will discuss how the molecular analysis of cell types in the brains of turtles, lizards and amphibians is updating our views on the evolution of the cerebral cortex, and the new questions emerging from these results.

The remarkable cognitive abilities characterizing humans has been linked to unique patterns of connectivity characterizing the neocortex. Comparative studies have shown that human cortical pyramidal neurons (PN) receive a significant increase of synaptic inputs when compared to other mammals, including non-human primates and rodents, but how this may relate to changes in cortical connectivity and function remained largely unknown. We previously identified a human-specific gene duplication (HSGD), SRGAP2C, that, when induced in mouse cortical PNs drives human-specific features of synaptic development, including a correlated increase in excitatory (E) and inhibitory (I) synapse density through inhibition of the ancestral SRGAP2A protein (Charrier et al. 2012; Fossatti et al. 2016; Schmidt et al. 2019). However, the origin and nature of this increased connectivity and its impact on cortical circuit function was unknown. I will present new results exploring these questions (see Schmidt et al. (2020) https://www.biorxiv.org/content/10.1101/852970v1). Using a combination of transgenic approaches and quantitative monosynaptic tracing, we discovered that humanization of SRGAP2C expression in the mouse cortex leads to a specific increase in local and long-range cortico-cortical inputs received by layer 2/3 cortical PNs. Moreover, using in vivo two-photon imaging in the barrel cortex of awake mice, we show that humanization of SRGAP2C expression increases the reliability and selectivity of sensory- evoked responses in layer 2/3 PNs. We also found that mice humanized for SRGAP2C in all cortical pyramidal neurons and throughout development are characterized by improved behavioural performance in a novel whisker-based sensory discrimination task compared to control wild-type mice. Our results suggest that the emergence of SRGAP2C during human evolution underlie a new substrate for human brain evolution whereby it led to increased local and long-range cortico-cortical connectivity and improved reliability of sensory-evoked cortical coding. References cited Charrier C.*, Joshi K. *, Coutinho-Budd J., Kim, J-E., Lambert N., de Marchena, J., Jin W-L., Vanderhaeghen P., Ghosh A., Sassa T, and Polleux F. (2012) Inhibition of SRGAP2 function by its human-specific paralogs induces neoteny of spine maturation. Cell 149:923-935. * Co-first authors. Fossati M, Pizzarelli R, Schmidt ER, Kupferman JV, Stroebel D, Polleux F*, Charrier C*. (2016) SRGAP2 and Its Human-Specific Paralog Co-Regulate the Development of Excitatory and Inhibitory Synapses. Neuron. 91(2):356-69. * Co-senior corresponding authors. Schmidt E.R.E., Kupferman J.V., Stackmann M., Polleux F. (2019) The human-specific paralogs SRGAP2 and SRGAP2C differentially modulate SRGAP2A-dependent synaptic development. Scientific Rep. 9(1):18692. Schmidt E.R.E, Zhao H.T., Hillman E.M.C., Polleux F. (2020) Humanization of SRGAP2C expression increases cortico-cortical connectivity and reliability of sensory-evoked responses in mouse brain. Submitted. See also: https://www.biorxiv.org/content/10.1101/852970v1

During brain development, neurons are born in specialized niches and migrate to target regions where they assemble to form the circuits that underlie mammalian behaviour. During their journey, neurons follow cell-intrinsic, genetic programs transmitted by their mother cells but also environmental cues, which together drive their maturation. Here, focusing on the neocortex, I will discuss recent findings from our laboratory in which we untangle and manipulate the programs at play in progenitors and their daughter neurons to better understand the emergence of cellular diversity in the developing brain.

Dravet syndrome is a severe childhood epilepsy due to heterozygous loss-of-function mutation of the gene SCN1A, which encodes the type 1 neuronal voltage gated sodium (Na+) channel alpha-subunit Nav1.1. Prior studies in mouse models of Dravet syndrome (Scn1a+/- mice) at early developmental time points indicate that, in cerebral cortex, Nav1.1 is predominantly expressed in GABAergic interneurons (INs) and, in particular, in parvalbumin-positive fast-spiking basket cells (PV-INs). This has led to a model of Dravet syndrome pathogenesis whereby Nav1.1 mutation leads to preferential IN dysfunction, decreased synaptic inhibition, hyperexcitability, and epilepsy. We found that, at later developmental time points, the intrinsic excitability of PV-INs has essentially normalized, via compensatory reorganization of axonal Na+ channels. Instead, we found persistent and seemingly paradoxical dysfunction of putative disinhibitory INs expressing vasoactive intestinal peptide (VIP-INs). In vivo two-photon calcium imaging in neocortex during temperature-induced seizures in Scn1a+/- mice showed that mean activity of both putative principal cells and PV-INs was higher in Scn1a+/- relative to wild-type controls during quiet wakefulness at baseline and at elevated core body temperature. However, wild-type PV-INs showed a progressive synchronization in response to temperature elevation that was absent in PV-INs from Scn1a+/- mice immediately prior to seizure onset. We suggest that impaired PV-IN synchronization, perhaps via persistent axonal dysfunction, may contribute to the transition to the ictal state during temperature induced seizures in Dravet syndrome.