Cortical amplification models of experience-dependent development of selective columns and response sparsification

The effects of abnormal visual experience on neurodevelopmental disorders

Normal visual development is supported by intrinsic neurobiological mechanisms and by appropriate stimulation from the environment, both of which facilitate the maturation of visual functions. However, an offset of this balance can give rise to visual disorders. Therefore, understanding the factors that support normal vision during development and in the mature brain is important, as vision guides movement, enables social interaction, and allows children to recognize and understand their environment. In this paper, we review fundamental mechanisms that support the maturation of visual functions and discuss and draw links between the perceptual and neurobiological impairments in autism spectrum disorder (ASD) and schizophrenia. We aim to explore how this is evident in the case of ASD, and how perceptual and neurobiological deficits further degrade social ability. Furthermore, we describe the altered perceptual experience of those with schizophrenia and evaluate theories of the underlying neural deficits that alter perception.

Developmental alignment of feedforward inputs and recurrent network activity drives increased response selectivity and reliability in primary visual cortex following the onset of visual experience

Selective and reliable cortical sensory representations depend on synaptic interactions between feedforward inputs, conveying information from lower levels of the sensory pathway, and recurrent networks that reciprocally connect neurons functioning at the same hierarchical level. Here we explore the development of feedforward/recurrent interactions in primary visual cortex of the ferret that is responsible for the representation of orientation, focusing on the feedforward inputs from cortical layer 4 and its relation to the modular recurrent network in layer 2/3 before and after the onset of visual experience. Using simultaneous laminar electrophysiology and calcium imaging we found that in experienced animals, individual layer 4 and layer 2/3 neurons exhibit strongly correlated responses with the modular recurrent network structure in layer 2/3. Prior to experience, layer 2/3 neurons exhibit comparable modular correlation structure, but this correlation structure is missing for individual layer 4 neurons. Further analysis of the receptive field properties of layer 4 neurons in naïve animals revealed that they exhibit very poor orientation tuning compared to layer 2/3 neurons at this age, and this is accompanied by the lack of spatial segregation of ON and OFF subfields, the definitive property of layer 4 simple cells in experienced animals. Analysis of the response dynamics of layer 2/3 neurons with whole-cell patch recordings confirms that individual layer 2/3 neurons in naïve animals receive poorly-selective feedforward input that does not align with the orientation preference of the layer 2/3 responses. Further analysis reveals that the misaligned feedforward input is the underlying cause of reduced selectivity and increased response variability that is evident in the layer 2/3 responses of naïve animals. Altogether, our experiments indicate that the onset of visual experience is accompanied by a critical refinement in the responses of layer 4 neurons and the alignment of feedforward and recurrent networks that increases the selectivity and reliability of the representation of orientation in V1.

Inhibitory stabilization and cortical computation

Neuronal networks with strong recurrent connectivity provide the brain with a powerful means to perform complex computational tasks. However, high-gain excitatory networks are susceptible to instability, which can lead to runaway activity, as manifested in pathological regimes such as epilepsy. Inhibitory stabilization offers a dynamic, fast and flexible compensatory mechanism to balance otherwise unstable networks, thus enabling the brain to operate in its most efficient regimes. Here we review recent experimental evidence for the presence of such inhibition-stabilized dynamics in the brain and discuss their consequences for cortical computation. We show how the study of inhibition-stabilized networks in the brain has been facilitated by recent advances in the technological toolbox and perturbative techniques, as well as a concomitant development of biologically realistic computational models. By outlining future avenues, we suggest that inhibitory stabilization can offer an exemplary case of how experimental neuroscience can progress in tandem with technology and theory to advance our understanding of the brain.

Cortical synaptic architecture supports flexible sensory computations

Establishing the fundamental principles that underlie the integration of excitatory and inhibitory presynaptic input populations is crucial to understanding how individual cortical neurons transform signals from peripheral receptors. Here we review recent studies using novel tools to examine the functional properties of excitatory synaptic inputs and the tuning of excitation and inhibition onto individual neurons. New evidence challenges existing synaptic connectivity rules and suggests a more complex functional synaptic architecture that supports a broad range of operations, enabling single neurons to encode multiple sensory features and flexibly shape their computations in the face of diverse sensory input.

Synaptic and intrinsic mechanisms underlying development of cortical direction selectivity

Modifications of synaptic inputs and cell-intrinsic properties both contribute to neuronal plasticity and development. To better understand these mechanisms, we undertook an intracellular analysis of the development of direction selectivity in the ferret visual cortex, which occurs rapidly over a few days after eye opening. We found strong evidence of developmental changes in linear spatiotemporal receptive fields of simple cells, implying alterations in circuit inputs. Further, this receptive field plasticity was accompanied by increases in near-spike-threshold excitability and input-output gain that resulted in dramatically increased spiking responses in the experienced state. Increases in subthreshold membrane responses induced by the receptive field plasticity and the increased input-output spiking gain were both necessary to explain the elevated firing rates in experienced ferrets. These results demonstrate that cortical direction selectivity develops through a combination of plasticity in inputs and in cell-intrinsic properties.

Recurrent interactions in local cortical circuits

Most cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing pattern completion and other computations^1-4. Cortical circuits contain subnetworks that consist of neurons with similar receptive fields and increased connectivity relative to the network average^5,6. Cortical neurons that encode different types of information are spatially intermingled and distributed over large brain volumes^5-7, and this complexity has hindered attempts to probe the function of these subnetworks by perturbing them individually⁸. Here we use computational modelling, optical recordings and manipulations to probe the function of recurrent coupling in layer 2/3 of the mouse vibrissal somatosensory cortex during active tactile discrimination. A neural circuit model of layer 2/3 revealed that recurrent excitation enhances sensory signals by amplification, but only for subnetworks with increased connectivity. Model networks with high amplification were sensitive to damage: loss of a few members of the subnetwork degraded stimulus encoding. We tested this prediction by mapping neuronal selectivity⁷ and photoablating^9,10 neurons with specific selectivity. Ablation of a small proportion of layer 2/3 neurons (10-20, less than 5% of the total) representing touch markedly reduced responses in the spared touch representation, but not in other representations. Ablations most strongly affected neurons with stimulus responses that were similar to those of the ablated population, which is also consistent with network models. Recurrence among cortical neurons with similar selectivity therefore drives input-specific amplification during behaviour.

Does experience provide a permissive or instructive influence on the development of direction selectivity in visual cortex?

In principle, the development of sensory receptive fields in cortex could arise from experience-independent mechanisms that have been acquired through evolution, or through an online analysis of the sensory experience of the individual animal. Here we review recent experiments that suggest that the development of direction selectivity in carnivore visual cortex requires experience, but also suggest that the experience of an individual animal cannot greatly influence the parameters of the direction tuning that emerges, including direction angle preference and speed tuning. The direction angle preference that a neuron will acquire can be predicted from small initial biases that are present in the naïve cortex prior to the onset of visual experience. Further, experience with stimuli that move at slow or fast speeds does not alter the speed tuning properties of direction-selective neurons, suggesting that speed tuning preferences are built in. Finally, unpatterned optogenetic activation of the cortex over a period of a few hours is sufficient to produce the rapid emergence of direction selectivity in the naïve ferret cortex, suggesting that information about the direction angle preference that cells will acquire must already be present in the cortical circuit prior to experience. These results are consistent with the idea that experience has a permissive influence on the development of direction selectivity.

Early Development of Network Oscillations in the Ferret Visual Cortex

Although oscillations during development have been characterized in a wide range of neural systems, little is known about the interaction between these network oscillations and neuronal spiking, and the interactions among different oscillation frequencies. Here we recorded the spontaneous and visual-elicited local field potential (LFP) and multi-unit activity (MUA) in the visual cortex of freely-moving juvenile ferrets before and after eye-opening. We found that both the spontaneous and visually-elicited LFP power was increased after eye-opening, especially in higher frequency bands (>30 Hz). Spike LFP phase coupling was decreased for lower frequency bands (theta and alpha) but slightly increased for higher frequencies (high-gamma band). A similar shift towards faster frequencies also occurred for phase-amplitude coupling; with maturation, the coupling of the theta/alpha/beta band amplitude to the delta phase was decreased and the high-gamma amplitude coupling to theta/alpha phase was increased. This shift towards higher frequencies was also reflected in the visual responses; the LFP oscillation became more entrained by visual stimulation with higher frequencies (>10 Hz). Taken together, these results suggest gamma oscillation as a signature of the maturation of cortical circuitry.