assemblies

A multi-level account of hippocampal function in concept learning from behavior to neurons

A complete neuroscience requires multi-level theories that address phenomena ranging from higher-level cognitive behaviors to activities within a cell. Unfortunately, we don't have cognitive models of behavior whose components can be decomposed into the neural dynamics that give rise to behavior, leaving an explanatory gap. Here, we decompose SUSTAIN, a clustering model of concept learning, into neuron-like units (SUSTAIN-d; decomposed). Instead of abstract constructs (clusters), SUSTAIN-d has a pool of neuron-like units. With millions of units, a key challenge is how to bridge from abstract constructs such as clusters to neurons, whilst retaining high-level behavior. How does the brain coordinate neural activity during learning? Inspired by algorithms that capture flocking behavior in birds, we introduce a neural flocking learning rule to coordinate units that collectively form higher-level mental constructs ("virtual clusters"), neural representations (concept, place and grid cell-like assemblies), and parallels recurrent hippocampal activity. The decomposed model shows how brain-scale neural populations coordinate to form assemblies encoding concept and spatial representations, and why many neurons are required for robust performance. Our account provides a multi-level explanation for how cognition and symbol-like representations are supported by coordinated neural assemblies formed through learning.

Extrinsic control and intrinsic computation in the hippocampal CA1 network

A key issue in understanding circuit operations is the extent to which neuronal spiking reflects local computation or responses to upstream inputs. Several studies have lesioned or silenced inputs to area CA1 of the hippocampus - either area CA3 or the entorhinal cortex and examined the effect on CA1 pyramidal cells. However, the types of the reported physiological impairments vary widely, primarily because simultaneous manipulations of these redundant inputs have never been performed. In this study, I combined optogenetic silencing of unilateral and bilateral mEC, of the local CA1 region, and performed bilateral pharmacogenetic silencing of CA3. I combined this with high spatial resolution extracellular recordings along the CA1-dentate axis. Silencing the medial entorhinal 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. In contrast to these results, unilateral mEC manipulations that were ineffective in impacting place cells during awake behavior were found to alter sharp-wave ripple sequences activated during sleep. Thus, intrinsic excitatory-inhibitory circuits within CA1 can generate neuronal assemblies in the absence of external inputs, although external synaptic inputs are critical to reconfigure (remap) neuronal assemblies in a brain-state dependent manner.

Drifting assemblies for persistent memory: Neuron transitions and unsupervised compensation

Change is ubiquitous in living beings. In particular, the connectome and neural representations can change. Nevertheless behaviors and memories often persist over long times. In a standard model, associative memories are represented by assemblies of strongly interconnected neurons. For faithful storage these assemblies are assumed to consist of the same neurons over time. We propose a contrasting memory model with complete temporal remodeling of assemblies, based on experimentally observed changes of synapses and neural representations. The assemblies drift freely as noisy autonomous network activity or spontaneous synaptic turnover induce neuron exchange. The exchange can be described analytically by reduced, random walk models derived from spiking neural network dynamics or from first principles. The gradual exchange allows activity-dependent and homeostatic plasticity to conserve the representational structure and keep inputs, outputs and assemblies consistent. This leads to persistent memory. Our findings explain recent experimental results on temporal evolution of fear memory representations and suggest that memory systems need to be understood in their completeness as individual parts may constantly change.

Extrinsic control and autonomous computation in the hippocampal CA1 circuit

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.

NMC4 Short Talk: Multiscale and extended retrieval of associative memory structures in a cortical model of local-global inhibition balance

Inhibitory neurons take on many forms and functions. How this diversity contributes to memory function is not completely known. Previous formal studies indicate inhibition differentiated by local and global connectivity in associative memory networks functions to rescale the level of retrieval of excitatory assemblies. However, such studies lack biological details such as a distinction between types of neurons (excitatory and inhibitory), unrealistic connection schemas, and non-sparse assemblies. In this study, we present a rate-based cortical model where neurons are distinguished (as excitatory, local inhibitory, or global inhibitory), connected more realistically, and where memory items correspond to sparse excitatory assemblies. We use this model to study how local-global inhibition balance can alter memory retrieval in associative memory structures, including naturalistic and artificial structures. Experimental studies have reported inhibitory neurons and their sub-types uniquely respond to specific stimuli and can form sophisticated, joint excitatory-inhibitory assemblies. Our model suggests such joint assemblies, as well as a distribution and rebalancing of overall inhibition between two inhibitory sub-populations – one connected to excitatory assemblies locally and the other connected globally – can quadruple the range of retrieval across related memories. We identify a possible functional role for local-global inhibitory balance to, in the context of choice or preference of relationships, permit and maintain a broader range of memory items when local inhibition is dominant and conversely consolidate and strengthen a smaller range of memory items when global inhibition is dominant. This model therefore highlights a biologically-plausible and behaviourally-useful function of inhibitory diversity in memory.

Spontaneous activity competes with externally evoked responses in sensory cortex

The interaction between spontaneously and externally evoked neuronal activity is fundamental for a functional brain. Increasing evidence suggests that bursts of high-power oscillations in the 15-30 Hz beta-band represent activation of resting state networks and can mask perception of external cues. Yet demonstration of the effect of beta power modulation on perception in real-time is missing, and little is known about the underlying mechanism. In this talk I will present the methods we developed to fill this gap together with our recent results. We used a closed-loop stimulus-intensity adjustment system based on online burst-occupancy analyses in rats involved in a forepaw vibrotactile detection task. We found that the masking influence of burst-occupancy on perception can be counterbalanced in real-time by adjusting the vibration amplitude. Offline analysis of firing-rates and local field potentials across cortical layers and frequency bands confirmed that beta-power in the somatosensory cortex anticorrelated with sensory evoked responses. Mechanistically, bursts in all bands were accompanied by transient synchronization of cell assemblies, but only beta-bursts were followed by a reduction of firing-rate. Our closed loop approach reveals that spontaneous beta-bursts reflect a dynamic state that competes with external stimuli.

All optical interrogation of developing GABAergic circuits in vivo

The developmental journey of cortical interneurons encounters several activity-dependent milestones. During the early postnatal period in developing mice, GABAergic neurons are transient preferential recipients of thalamic inputs and undergo activity-dependent migration arrest, wiring and programmed cell-death. But cortical GABAergic neurons are also specified by very early developmental programs. For example, the earliest born GABAergic neurons develop into hub cells coordinating spontaneous activity in hippocampal slices. Despite their importance for the emergence of sensory experience, their role in coordinating network dynamics, and the role of activity in their integration into cortical networks, the collective in vivo dynamics of GABAergic neurons during the neonatal postnatal period remain unknown. Here, I will present data related to the coordinated activity between GABAergic cells of the mouse barrel cortex and hippocampus in non-anesthetized pups using the recent development of all optical methods to record and manipulate neuronal activity in vivo. I will show that the functional structure of developing GABAergic circuits is remarkably patterned, with segregated assemblies of prospective parvalbumin neurons and highly connected hub cells, both shaped by sensory-dependent processes.

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.

Cell assemblies and their underlying connectivity in a detailed, large-scale cortical model

COSYNE 2023

A homeostatic mechanism or statistics can maintain input-output relations of multilayer drifting assemblies

Bernstein Conference 2024

Awake perception is associated with dedicated neuronal assemblies in cerebral cortex

COSYNE 2022

Purely STDP-based learning of stable, overlapping assemblies

COSYNE 2022

Purely STDP-based learning of stable, overlapping assemblies

COSYNE 2022

Reduced stochastic models reveal the mechanisms underlying drifting cell assemblies

COSYNE 2022

Reduced stochastic models reveal the mechanisms underlying drifting cell assemblies

COSYNE 2022

Assemblies and the k-Cap Process: The Effects of Locality on Neural Firing Dynamics

COSYNE 2023

Computation with sequences of neural assemblies

COSYNE 2023

Inhibitory gating of non-linear dendrites enables stable learning of assemblies without forgetting

COSYNE 2023

Understanding network dynamics of compact assemblies of neurons in zebrafish larvae optic tectum during spontaneous activation

COSYNE 2023

Inhibitory synaptic plasticity allows disinhibitory recall of overlapping excitatory-inhibitory assemblies

COSYNE 2025

Awake perception is associated with dedicated neuronal assemblies in cerebral cortex

Binding cell assemblies into memory engrams

Cortical neuronal assemblies coordinate with EEG microstate dynamics during resting wakefulness

Cell-derived Aβ assemblies act as seeds to propagate amyloid pathology

FENS Forum 2024

Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity

Role of inhibition for the formation of neural assemblies in plastic neural networks subject to selective stimuli

Identifying critical brain-wide information flows through neuronal cell assemblies

FENS Forum 2024

Revealing hidden targets in memory assemblies: The minimal engram for contextual memory encoding

FENS Forum 2024