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.

Dr. Davis will present a summary regarding the identification and characterization of mechanisms of homeostatic plasticity as they relate to the control of synaptic transmission. He will then provide evidence of translation to the mammalian neuromuscular junction and central synapses, and provide tangible links to the etiology of neurological disease.

Our brains must generate and maintain stable activity patterns over decades of life, despite the dramatic changes in circuit connectivity and function induced by learning and experience-dependent plasticity. How do our brains acheive this balance between opposing need for plasticity and stability? Over the past two decades, we and others have uncovered a family of “homeostatic” negative feedback mechanisms that are theorized to stabilize overall brain activity while allowing specific connections to be reconfigured by experience. Here I discuss recent work in which we demonstrate that individual neocortical neurons in freely behaving animals indeed have a homeostatic activity set-point, to which they return in the face of perturbations. Intriguingly, this firing rate homeostasis is gated by sleep/wake states in a manner that depends on the direction of homeostatic regulation: upward-firing rate homeostasis occurs selectively during periods of active wake, while downward-firing rate homeostasis occurs selectively during periods of sleep, suggesting that an important function of sleep is to temporally segregate bidirectional plasticity. Finally, we show that firing rate homeostasis is compromised in an animal model of autism spectrum disorder. Together our findings suggest that loss of homeostatic plasticity in some neurological disorders may render central circuits unable to compensate for the normal perturbations induced by development and learning.

Neuroplasticity is a fundamental property of the nervous system that is maximal early in life, within a specific temporal window called critical period. However, it is still unclear to which extent the plastic potential of the visual cortex is retained in adulthood. We have surprisingly revealed residual ocular dominance plasticity in adult humans by showing that short-term monocular deprivation unexpectedly boosts the deprived eye (both at the perceptual and at the neural level), reflecting homeostatic plasticity. This effect is accompanied by a decrease of GABAergic inhibition in the primary visual cortex and can be modulated by non-visual factors (motor activity and motor plasticity). Finally, we have found that cross-modal plasticity is preserved in adult normal-sighted humans, as short-term monocular deprivation can alter early visuo-tactile interactions. Taken together, these results challenge the classical view of a hard-wired adult visual cortex, indicating that homeostatic plasticity can be reactivated in adult humans.

Homeostatic plasticity plays a key role in stabilizing neural network activity. But what is its role in neural information processing? We showed analytically how homeostasis changes collective dynamics and consequently information flow - depending on the input to the network. We then studied how input and homeostasis on a recurrent network of LIF neurons impacts information flow and task performance. We showed how we can tune the working point of the network, and found that, contrary to previous assumptions, there is not one optimal working point for a family of tasks, but each task may require its own working point.

Neocortical networks must generate and maintain stable activity patterns despite perturbations induced by learning and experience- dependent plasticity. There is abundant theoretical and experimental evidence that network stability is achieved through homeostatic plasticity mechanisms that adjust synaptic and neuronal properties to stabilize some measure of average activity, and this process has been extensively studied in primary visual cortex (V1), where chronic visual deprivation induces an initial drop in activity and ensemble average firing rates (FRs), but over time activity is restored to baseline despite continued deprivation. Here I discuss recent work from the lab in which we followed this FR homeostasis in individual V1 neurons in freely behaving animals during a prolonged visual deprivation/eye-reopening paradigm. We find that - when FRs are perturbed by manipulating sensory experience - over time they return precisely to a cell-autonomous set-point. Finally, we find that homeostatic plasticity is perturbed in a mouse model of Autism spectrum disorder, and this results in a breakdown of FRH within V1. These data suggest that loss of homeostatic plasticity is one primary cause of excitation/inhibition imbalances in ASD models. Together these studies illuminate the role of stabilizing plasticity mechanisms in the ability of neocortical circuits to recover robust function following challenges to their excitability.