Biophysical underpinnings of computation and learning in the neocortex
Mark Harnett presents work on how synaptic organization, nonlinear dendritic processing, and neuronal activity patterns interact to support computation, flexibility, and learning in the adult mammalian neocortex. The Brain and Cognitive Sciences colloquium is followed by a reception.
Learning representations of specifics and generalities over time
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 rapidly learn 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 hippocampal replay 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. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2025-12-03. Recording duration: 00:53:05.
Top-down control of neocortical threat memory
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.
Gene regulatory mechanisms of neocortex development and evolution
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.
Cell-type-specific plasticity shapes neocortical dynamics for motor learning
How do cortical circuits acquire new dynamics that drive learned movements? This webinar will focus on mouse premotor cortex in relation to learned lick-timing and explore high-density electrophysiology using our silicon neural probes alongside region and cell-type-specific acute genetic manipulations of proteins required for synaptic plasticity.
Learning representations of specifics and generalities over time
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.
The Emergence of Cortical Representations
The internal and external world is thought to be represented by distributed patterns of cortical activity. The emergence of these cortical representations over the course of development remains an unresolved question. In this talk, I share results from a series of recent studies combining theory and experiments in the cortex of the ferret, a species with a well-defined columnar organization and modular network of orientation-selective responses in visual cortex. I show that prior to the onset of structured sensory experience, endogenous mechanisms set up a highly organized cortical network structure that is evident in modular patterns of spontaneous activity characterized by strong, clustered local and long-range correlations. This correlation structure is remarkably consistent across both sensory and association areas in the early neocortex, suggesting that diverse cortical representations initially develop according to similar principles. Next, I explore a classical candidate mechanism for producing modular activity – local excitation and lateral inhibition. I present the first empirical test of this mechanism through direct optogenetic cortical activation and discuss a plausible circuit implementation. Then, focusing on the visual cortex, I demonstrate that these endogenously structured networks enable orientation-selective responses immediately after eye opening. However, these initial responses are highly variable, lacking the reliability and low-dimensional structure observed in the mature cortex. Reliable responses are achieved after an experience-dependent co-reorganization of stimulus- evoked and spontaneous activity following eye opening. Based on these observations, I propose the hypothesis that the alignment between feedforward inputs and the recurrent network plays a crucial role in transforming the initially variable responses into mature and reliable representations. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2023-11-22. Recording duration: 00:56:31.
Epigenome regulation in neocortex expansion and generation of neuronal subtypes
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
Epigenetic regulation of neural progenitor cells in the developing neocortex
Neocortex saves energy by reducing coding precision during food scarcity
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.
Learning from unexpected events in the neocortical microcircuit
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.
An in-silico framework to study the cholinergic modulation of the neocortex
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.
Imaging memory consolidation in wakefulness and sleep
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.
Herbert Jasper Lecture
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.
Spatiotemporal patterns of neocortical activity around hippocampal sharp-wave ripples
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’.
Sensory-motor control, cognition and brain evolution: exploring the links
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?
Assembly of the neocortex
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”.
Inhibitory neural circuit mechanisms underlying neural coding of sensory information in the neocortex
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.
Fundamental Cellular and Molecular Mechanisms governing Brain Development
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”.
Cellular mechanisms of conscious perception
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.
The evolutionary origins of cortical cell types
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.
Fate and freedom in developing neocortical circuits
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.