Manipulating hippocampal CA3 attractor dynamics with targeted 2 photon ("P) activation in vivo)

One key goal of neuroscience is to understand the relationship between neuronal activity, behaviour and cognition. Traditionally, this aim has been pursued using electrical recordings from neurons and relating action potentials (spikes) to brain states or behavior. Such single-neuron approaches facilitated the physiological neuron doctrine, which posits that individual neuronsare the nervous system's unit of function1. However, individual neurons cooperate to form larger functional structures, and this feature cannot be captured within a single neuron framework.
Most neural circuits in the mammalian brain have distributed connectivity, whereby each neuron receives inputs from many others and outputs to a large population. Therefore,the contribution of an individual
1
neuron is overshadowed, as function is an emergent property of collective neural activity . The notion that neural circuits are built for an emergent function is not novel. Donald Hebb embraced the idea and proposed that information propagates by sequentially 'Hebbian assemblies' 2
activating groups of neurons, or cell .
These neuronal ensembles display synaptic plasticity when they fire simultaneously (Hebbian rule), enabling groups of coactive neurons to functionally bind together (Hebbian ensemble2)
Hebb and other theorists ultimately created the concept of a 'neural network'. A term synonymous with models of distributed neural circuits in which neurons are abstracted to nodes and associated by changing connections based on learning rules such as spike timing dependent plasticity (STDP). Recurrent network models can have dynamical trajectories such that conceptually, theirthree-dimensional energy landscape can contain numerous low energy stable points, which 'attract' the activity of the circuit as it evolves in time. These networks may serve associative memory, given their propensity to move towards lower energy states enables pattern completion, i.e. the internal dynamics of the system can 'complete' a spatiotemporal pattern of activity when provided with partial input3,4. As an emergent network property, attractor dynamics cannot be captured within the single neuron doctrine.
Hippocampal CA3 anatomy with its extensive recurrent connectivity,is consistent with its role as an associative memory matrix. However,despite extensive theoretical support for a role of CA3in memory recall and pattern completion,5,6,7,8 experimental testing of CA3 network properties remain relatively unexplored. Wills et al. (2005) were among the first to demonstrate thatthe hippocampal network falls into an attractor like state, representing one previously environments 9
or the other learned .Parametric changes
made to the geometry of the animals' environment as it was morphed between two familiar configurations, did not affect place cell activity until a threshold was reached, after which the entire network moved state (remapped), to represent the alternative configuration.9,10 However, to fully support this interpretation, causal evidence is required to directly probe whether hippocampal attractors exist. Experimentally linking neural microcircuit function to emergent properties requires fine-scale manipulation and measurement of neural activity during behavior, where each neuron's coding and dynamics can be characterized.