Takaki Komiyama - A cell-type-specific cortical circuit for maintenance of value representations
Takaki Komiyama will discuss how cortical circuits maintain information about the value of behavioral options across trials and transform past experience into future choices. The talk draws on longitudinal imaging and circuit manipulation in mice to examine distinct neuronal populations and local and long-range interactions in history-dependent decision-making.
A cell-type-specific cortical circuit for maintenance of value representations
Takaki Komiyama presents longitudinal imaging and circuit-manipulation studies of history-dependent decision-making. The work identifies retrosplenial-cortex populations and local and long-range interactions that maintain option values across trials, update them after outcomes and translate past experience into future choices.
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.
Bio-realistic multiscale modeling of cortical circuits
A central question in neuroscience is how the structure of brain circuits determines their activity and function. To explore this systematically, we developed a 230,000-neuron model of mouse primary visual cortex (area V1). The model integrates a broad array of experimental data:Distribution and morpho-electric properties of different neuron types in V1.
Dynamics of cortical circuits: underlying mechanisms and computational implications
A signature feature of cortical circuits is the irregularity of neuronal firing, which manifests itself in the high temporal variability of spiking and the broad distribution of rates. Theoretical works have shown that this feature emerges dynamically in network models if coupling between cells is strong, i.e. if the mean number of synapses per neuron K is large and synaptic efficacy is of order 1/\sqrt{K}. However, the degree to which these models capture the mechanisms underlying neuronal firing in cortical circuits is not fully understood. Results have been derived using neuron models with current-based synapses, i.e. neglecting the dependence of synaptic current on the membrane potential, and an understanding of how irregular firing emerges in models with conductance-based synapses is still lacking. Moreover, at odds with the nonlinear responses to multiple stimuli observed in cortex, network models with strongly coupled cells respond linearly to inputs. In this talk, I will discuss the emergence of irregular firing and nonlinear response in networks of leaky integrate-and-fire neurons. First, I will show that, when synapses are conductance-based, irregular firing emerges if synaptic efficacy is of order 1/\log(K) and, unlike in current-based models, persists even under the large heterogeneity of connections which has been reported experimentally. I will then describe an analysis of neural responses as a function of coupling strength and show that, while a linear input-output relation is ubiquitous at strong coupling, nonlinear responses are prominent at moderate coupling. I will conclude by discussing experimental evidence of moderate coupling and loose balance in the mouse cortex.
Bridging the gap between artificial models and cortical circuits
Artificial neural networks simplify complex biological circuits into tractable models for computational exploration and experimentation. However, the simplification of artificial models also undermines their applicability to real brain dynamics. Typical efforts to address this mismatch add complexity to increasingly unwieldy models. Here, we take a different approach; by reducing the complexity of a biological cortical culture, we aim to distil the essential factors of neuronal dynamics and plasticity. We leverage recent advances in growing neurons from human induced pluripotent stem cells (hiPSCs) to analyse ex vivo cortical cultures with only two distinct excitatory and inhibitory neuron populations. Over 6 weeks of development, we record from thousands of neurons using high-density microelectrode arrays (HD-MEAs) that allow access to individual neurons and the broader population dynamics. We compare these dynamics to two-population artificial networks of single-compartment neurons with random sparse connections and show that they produce similar dynamics. Specifically, our model captures the firing and bursting statistics of the cultures. Moreover, tightly integrating models and cultures allows us to evaluate the impact of changing architectures over weeks of development, with and without external stimuli. Broadly, the use of simplified cortical cultures enables us to use the repertoire of theoretical neuroscience techniques established over the past decades on artificial network models. Our approach of deriving neural networks from human cells also allows us, for the first time, to directly compare neural dynamics of disease and control. We found that cultures e.g. from epilepsy patients tended to have increasingly more avalanches of synchronous activity over weeks of development, in contrast to the control cultures. Next, we will test possible interventions, in silico and in vitro, in a drive for personalised approaches to medical care. This work starts bridging an important theoretical-experimental neuroscience gap for advancing our understanding of mammalian neuron dynamics.
A biological model system for studying predictive processing
Despite the increasing recognition of predictive processing in circuit neuroscience, little is known about how it may be implemented in cortical circuits. We set out to develop and characterise a biological model system with layer 5 pyramidal cells in the centre. We aim to gain access to prediction and internal model generating processes by controlling, understanding or monitoring everything else: the sensory environment, feed-forward and feed-back inputs, integrative properties, their spiking activity and output. I’ll show recent work from the lab establishing such a model system both in terms of biology as well as tool development.
Diversification of cortical inhibitory circuits & Molecular programs orchestrating the wiring of inhibitory circuitries
GABAergic interneurons play crucial roles in the regulation of neural activity in the cerebral cortex. In this Dual Lecture, Prof Oscar Marín and Prof Beatriz Rico will discuss several aspects of the formation of inhibitory circuits in the mammalian cerebral cortex. Prof. Marín will provide an overview of the mechanisms regulating the generation of the remarkable diversity of GABAergic interneurons and their ultimate numbers. Prof. Rico will describe the molecular logic through which specific pyramidal cell-interneuron circuits are established in the cerebral cortex, and how alterations in some of these connectivity motifs might be liked to disease. Our web pages for reference: https://devneuro.org.uk/marinlab/ & https://devneuro.org.uk/rico/default
A novel form of retinotopy in area V2 highlights location-dependent feature selectivity in the visual system
Topographic maps are a prominent feature of brain organization, reflecting local and large-scale representation of the sensory surface. Traditionally, such representations in early visual areas are conceived as retinotopic maps preserving ego-centric retinal spatial location while ensuring that other features of visual input are uniformly represented for every location in space. I will discuss our recent findings of a striking departure from this simple mapping in the secondary visual area (V2) of the tree shrew that is best described as a sinusoidal transformation of the visual field. This sinusoidal topography is ideal for achieving uniform coverage in an elongated area like V2 as predicted by mathematical models designed for wiring minimization, and provides a novel explanation for stripe-like patterns of intra-cortical connections and functional response properties in V2. Our findings suggest that cortical circuits flexibly implement solutions to sensory surface representation, with dramatic consequences for large-scale cortical organization. Furthermore our work challenges the framework of relatively independent encoding of location and features in the visual system, showing instead location-dependent feature sensitivity produced by specialized processing of different features in different spatial locations. In the second part of the talk, I will propose that location-dependent feature sensitivity is a fundamental organizing principle of the visual system that achieves efficient representation of positional regularities in visual input, and reflects the evolutionary selection of sensory and motor circuits to optimally represent behaviorally relevant information. The relevant papers can be found here: V2 retinotopy (Sedigh-Sarvestani et al. Neuron, 2021) Location-dependent feature sensitivity (Sedigh-Sarvestani et al. Under Review, 2022)
The neural basis of pain experience and its modulation by opioids
How the brain creates a painful experience remains a mystery. Solving this mystery is crucial to understanding the fundamental biological processes that underlie the perception of body integrity, and to creating better, non-addictive pain treatments. My laboratory’s goal is to resolve the neural basis of pain. We aim to understand the mechanisms by which our nervous system produces and assembles the sensory-discriminative, affective-motivational, and cognitive-evaluative dimensions of pain to create this unique and critically important experience. To capture every component of the pain experience, we examine the entirety of the pain circuitry, from sensory and spinal ascending pathways to cortical/subcortical circuits and brainstem descending pain modulation systems, at the molecular, cellular, circuit and whole-animal levels. For these studies, we have invented novel behavioral paradigms to interrogate the affective and cognitive dimensions of pain in mice while simultaneously imaging and manipulating nociceptive circuits. My laboratory also investigates how opioids suppress pain. Remarkably, despite their medical and societal significance, how opium poppy alkaloids such as morphine produce profound analgesia remains largely unexplained. By identifying where and how opioids act in neural circuits, we not only establish the mechanisms of action of one of the oldest drugs known to humans, but also reveal the critical elements of the pain circuitry for developing of novel analgesics and bringing an end to the opioid epidemic.
Dual lecture: Diversification of cortical inhibitory circuits & Molecular programs orchestrating the wiring of inhibitory circuitries
GABAergic interneurons play crucial roles in the regulation of neural activity in the cerebral cortex. In this Dual Lecture, Prof Oscar Marín and Prof Beatriz Rico will discuss several aspects of the formation of inhibitory circuits in the mammalian cerebral cortex. Prof. Marín will provide an overview of the mechanisms regulating the generation of the remarkable diversity of GABAergic interneurons and their ultimate numbers. Prof. Rico will describe the molecular logic through which specific pyramidal cell-interneuron circuits are established in the cerebral cortex, and how alterations in some of these connectivity motifs might be liked to disease.
Optimising spiking interneuron circuits for compartment-specific feedback
Cortical circuits process information by rich recurrent interactions between excitatory neurons and inhibitory interneurons. One of the prime functions of interneurons is to stabilize the circuit by feedback inhibition, but the level of specificity on which inhibitory feedback operates is not fully resolved. We hypothesized that inhibitory circuits could enable separate feedback control loops for different synaptic input streams, by means of specific feedback inhibition to different neuronal compartments. To investigate this hypothesis, we adopted an optimization approach. Leveraging recent advances in training spiking network models, we optimized the connectivity and short-term plasticity of interneuron circuits for compartment-specific feedback inhibition onto pyramidal neurons. Over the course of the optimization, the interneurons diversified into two classes that resembled parvalbumin (PV) and somatostatin (SST) expressing interneurons. The resulting circuit can be understood as a neural decoder that inverts the nonlinear biophysical computations performed within the pyramidal cells. Our model provides a proof of concept for studying structure-function relations in cortical circuits by a combination of gradient-based optimization and biologically plausible phenomenological models
Neuronal variability and spatiotemporal dynamics in cortical network models
Neuronal variability is a reflection of recurrent circuitry and cellular physiology. The modulation of neuronal variability is a reliable signature of cognitive and processing state. A pervasive yet puzzling feature of cortical circuits is that despite their complex wiring, population-wide shared spiking variability is low dimensional with all neurons fluctuating en masse. We show that the spatiotemporal dynamics in a spatially structured network produce large population-wide shared variability. When the spatial and temporal scales of inhibitory coupling match known physiology, model spiking neurons naturally generate low dimensional shared variability that captures in vivo population recordings along the visual pathway. Further, we show that firing rate models with spatial coupling can also generate chaotic and low-dimensional rate dynamics. The chaotic parameter region expands when the network is driven by correlated noisy inputs, while being insensitive to the intensity of independent noise.
State-dependent cortical circuits
Spontaneous and sensory-evoked cortical activity is highly state-dependent, promoting the functional flexibility of cortical circuits underlying perception and cognition. Using neural recordings in combination with behavioral state monitoring, we find that arousal and motor activity have complementary roles in regulating local cortical operations, providing dynamic control of sensory encoding. These changes in encoding are linked to altered performance on perceptual tasks. Neuromodulators, such as acetylcholine, may regulate this state-dependent flexibility of cortical network function. We therefore recently developed an approach for dual mesoscopic imaging of acetylcholine release and neural activity across the entire cortical mantle in behaving mice. We find spatiotemporally heterogeneous patterns of cholinergic signaling across the cortex. Transitions between distinct behavioral states reorganize the structure of large-scale cortico-cortical networks and differentially regulate the relationship between cholinergic signals and neural activity. Together, our findings suggest dynamic state-dependent regulation of cortical network operations at the levels of both local and large-scale circuits. Zoom Meeting ID: 964 8138 3003 Contact host if you cannot connect.
Cortical networks for flexible decisions during spatial navigation
My lab seeks to understand how the mammalian brain performs the computations that underlie cognitive functions, including decision-making, short-term memory, and spatial navigation, at the level of the building blocks of the nervous system, cell types and neural populations organized into circuits. We have developed methods to measure, manipulate, and analyze neural circuits across various spatial and temporal scales, including technology for virtual reality, optical imaging, optogenetics, intracellular electrophysiology, molecular sensors, and computational modeling. I will present recent work that uses large scale calcium imaging to reveal the functional organization of the mouse posterior cortex for flexible decision-making during spatial navigation in virtual reality. I will also discuss work that uses optogenetics and calcium imaging during a variety of decision-making tasks to highlight how cognitive experience and context greatly alter the cortical circuits necessary for navigation decisions.
Playing fast and loose with glutamate builds healthy circuits in the developing cortex
The construction of cortical circuits requires the precise formation of connections between excitatory and inhibitory neurons during early development. Multiple factors, including neurotransmitters, neuronal activity, and neuronal-glial interactions, shape how these critical circuits form. Disruptions of these early processes can disrupt circuit formation, leading to epilepsy and other neurodevelopmental disorders. Here, I will describe our work into understanding how prolonged post-natal astrocyte development in the cortex creates a permissive window for glutamate signaling that provides tonic activation of developing interneurons through Grin2D NMDA receptors. Experimental disruption of this pathway results in hyperexcitable cortical circuits and human mutations in the Grin2D gene, as well as other related molecules that regulate early life glutamate signaling, are associated with devastating epileptic encephalopathies. We will explore fundamental mechanisms linking early life glutamate signaling and later circuit hyperexcitability, with an emphasis on potential therapeutic interventions aimed at reducing epilepsy and other neurological dysfunction.
State-dependent cortical circuits
Spontaneous and sensory-evoked cortical activity is highly state-dependent, promoting the functional flexibility of cortical circuits underlying perception and cognition. Using neural recordings in combination with behavioral state monitoring, we find that arousal and motor activity have complementary roles in regulating local cortical operations, providing dynamic control of sensory encoding. These changes in encoding are linked to altered performance on perceptual tasks. Neuromodulators, such as acetylcholine, may regulate this state-dependent flexibility of cortical network function. We therefore recently developed an approach for dual mesoscopic imaging of acetylcholine release and neural activity across the entire cortical mantle in behaving mice. We find spatiotemporally heterogeneous patterns of cholinergic signaling across the cortex. Transitions between distinct behavioral states reorganize the structure of large-scale cortico-cortical networks and differentially regulate the relationship between cholinergic signals and neural activity. Together, our findings suggest dynamic state-dependent regulation of cortical network operations at the levels of both local and large-scale circuits.
How does the cortex integrate conflicting time-information? A model of temporal averaging
In daily life, we consistently make decisions in pursuit of some goal. Many decisions are informed by multiple sources of information. Unfortunately, these sources often provide ambiguous information about what course of action to take. Therefore, determining how the brain integrates information to resolve this ambiguity is key to understanding the neural mechanisms of decision-making. In the domain of time, this topic can be studied by training subjects to predict when a future event will occur based on distinct cues (e.g., tone, light, etc.). If multiple cues are presented simultaneously and their cue-to-event intervals differ (e.g., tone-10s + light-30s), subjects will often expect the event to occur at the average of their intervals. This ‘temporal averaging’ effect is presumably how the timing system resolves ambiguous time-information. The neural mechanisms of temporal averaging are currently unclear. Here, we will propose how temporal averaging could emerge in cortical circuits using a simple modification of a ‘drift-diffusion’ model of timing.
Dimensions of variability in circuit models of cortex
Cortical circuits receive multiple inputs from upstream populations with non-overlapping stimulus tuning preferences. Both the feedforward and recurrent architectures of the receiving cortical layer will reflect this diverse input tuning. We study how population-wide neuronal variability propagates through a hierarchical cortical network receiving multiple, independent, tuned inputs. We present new analysis of in vivo neural data from the primate visual system showing that the number of latent variables (dimension) needed to describe population shared variability is smaller in V4 populations compared to those of its downstream visual area PFC. We successfully reproduce this dimensionality expansion from our V4 to PFC neural data using a multi-layer spiking network with structured, feedforward projections and recurrent assemblies of multiple, tuned neuron populations. We show that tuning-structured connectivity generates attractor dynamics within the recurrent PFC current, where attractor competition is reflected in the high dimensional shared variability across the population. Indeed, restricting the dimensionality analysis to activity from one attractor state recovers the low-dimensional structure inherited from each of our tuned inputs. Our model thus introduces a framework where high-dimensional cortical variability is understood as ``time-sharing’’ between distinct low-dimensional, tuning-specific circuit dynamics.
State-dependent regulation of cortical circuits
Spontaneous and sensory-evoked cortical activity is highly state-dependent, promoting the functional flexibility of cortical circuits underlying perception and cognition. Using neural recordings in combination with behavioral state monitoring, we find that arousal and motor activity have complementary roles in regulating local cortical operations, providing dynamic control of sensory encoding. These changes in encoding are linked to altered performance on perceptual tasks. Neuromodulators, such as acetylcholine, may regulate this state-dependent flexibility of cortical network function. We therefore recently developed an approach for dual mesoscopic imaging of acetylcholine release and neural activity across the entire cortical mantle in behaving mice. We find spatiotemporally heterogeneous patterns of cholinergic signaling across the cortex. Transitions between distinct behavioral states reorganize the structure of large-scale cortico-cortical networks and differentially regulate the relationship between cholinergic signals and neural activity. Together, our findings suggest dynamic state-dependent regulation of cortical network operations at the levels of both local and large-scale circuits.
Towards multipurpose biophysics-based mathematical models of cortical circuits
Starting with the work of Hodgkin and Huxley in the 1950s, we now have a fairly good understanding of how the spiking activity of neurons can be modelled mathematically. For cortical circuits the understanding is much more limited. Most network studies have considered stylized models with a single or a handful of neuronal populations consisting of identical neurons with statistically identical connection properties. However, real cortical networks have heterogeneous neural populations and much more structured synaptic connections. Unlike typical simplified cortical network models, real networks are also “multipurpose” in that they perform multiple functions. Historically the lack of computational resources has hampered the mathematical exploration of cortical networks. With the advent of modern supercomputers, however, simulations of networks comprising hundreds of thousands biologically detailed neurons are becoming feasible (Einevoll et al, Neuron, 2019). Further, a large-scale biologically network model of the mouse primary visual cortex comprising 230.000 neurons has recently been developed at the Allen Institute for Brain Science (Billeh et al, Neuron, 2020). Using this model as a starting point, I will discuss how we can move towards multipurpose models that incorporate the true biological complexity of cortical circuits and faithfully reproduce multiple experimental observables such as spiking activity, local field potentials or two-photon calcium imaging signals. Further, I will discuss how such validated comprehensive network models can be used to gain insights into the functioning of cortical circuits.
Hippocampal disinhibitory circuits: cell types, connectivity and function
The concept of a dynamic excitation / inhibition ratio, that can shape information flow in cortical circuits during complex behavioural tasks due to circuit disinhibition, has recently arisen as an important and conserved processing motif. It has been also recognized that, in cortical circuits, a subpopulation of GABAergic cells that express vasoactive intestinal polypeptide (VIP) innervates selectively inhibitory interneurons, providing for circuit disinhibition as a possible outcome, depending on the network state and behavioural context. In this talk, I will highlight the latest discoveries on the dynamic organization of hippocampal disinhibitory circuits with a focus on VIP-expressing interneurons. I will discuss the neuron types that can be involved in disinhibition and their local circuit and long-range synaptic connections. I will also discuss some recent findings on how hippocampal VIP circuits may coordinate spatial learning.
Cortical circuits for olfactory navigation
Olfactory navigation is essential for the survival of living beings from unicellular organisms to mammals. In the wild, rodents combine odor information with an internal spatial representation of the environment for foraging and navigation. What are the neural circuits in the brain that implement these behaviours? My research addresses this question by examining the synaptic circuits and neural population activity in the olfactory cortex to understand the integration of olfactory and spatial information. Primary olfactory (piriform) cortex (PCx) has long been recognized as a highly associative brain structure. What is the behavioural and functional role of these associative synapses in PCx? We designed an odor-cued navigation task, where rats must use both olfactory and spatial information to obtain water rewards. We recorded from populations of posterior piriform cortex (pPCx) neurons during behaviour and found that individual neurons were not only odor-selective, but also fired differentially to the same odor sampled at different locations, forming an “olfactory place map”. Spatial locations can be decoded from simultaneously recorded pPCx population, and spatial selectivity is maintained in the absence of odors, across behavioural contexts. This novel olfactory place map is consistent with our finding for a dominant role of associative excitatory synapses in shaping PCx representations, and suggest a role for PCx spatial representations in supporting olfactory navigation. This work not only provides insight into the neural basis for how odors can be used for navigation, but also reveals PCx as a prime site for addressing the general question of how sensory information is anchored within memory systems and combined with cognitive maps to guide flexible behaviour.
Playing the piano with the cortex: role of neuronal ensembles and pattern completion in perception
The design of neural circuits, with large numbers of neurons interconnected in vast networks, strongly suggest that they are specifically build to generate emergent functional properties (1). To explore this hypothesis, we have developed two-photon holographic methods to selective image and manipulate the activity of neuronal populations in 3D in vivo (2). Using them we find that groups of synchronous neurons (neuronal ensembles) dominate the evoked and spontaneous activity of mouse primary visual cortex (3). Ensembles can be optogenetically imprinted for several days and some of their neurons trigger the entire ensemble (4). By activating these pattern completion cells in ensembles involved in visual discrimination paradigms, we can bi-directionally alter behavioural choices (5). Our results demonstrate that ensembles are necessary and sufficient for visual perception and are consistent with the possibility that neuronal ensembles are the functional building blocks of cortical circuits. 1. R. Yuste, From the neuron doctrine to neural networks. Nat Rev Neurosci 16, 487-497 (2015). 2. L. Carrillo-Reid, W. Yang, J. E. Kang Miller, D. S. Peterka, R. Yuste, Imaging and Optically Manipulating Neuronal Ensembles. Annu Rev Biophys, 46: 271-293 (2017). 3. J. E. Miller, I. Ayzenshtat, L. Carrillo-Reid, R. Yuste, Visual stimuli recruit intrinsically generated cortical ensembles. Proceedings of the National Academy of Sciences of the United States of America 111, E4053-4061 (2014). 4. L. Carrillo-Reid, W. Yang, Y. Bando, D. S. Peterka, R. Yuste, Imprinting and recalling cortical ensembles. Science 353, 691-694 (2016). 5. L. Carrillo-Reid, S. Han, W. Yang, A. Akrouh, R. Yuste, (2019). Controlling visually-guided behaviour by holographic recalling of cortical ensembles. Cell 178, 447-457. DOI:https://doi.org/10.1016/j.cell.2019.05.045.