Adaptive gain modulation in V1 explains contextual modifications during bisection learning

Coordination of top-down influence on V1 responses by interneurons and brain rhythms

Top-down processing in neocortex underlies functions such as prediction, expectation, and attention. Visual systems have much feedback connection that carries information of behavioral context. Top-down signals along feedback pathways modulate the representation of visual information in early visual areas such as primary visual cortex (V1). Recent studies have shown further that beta rhythms are responsible for the transmission of behavioral-context information to lower visual areas. However, the mechanism underlying top-down influence and the role of brain rhythms in top-down processing are poorly understood. To address these issues, we focus on experimental studies on top-down influence in visual perceptual tasks. We develop a model of visual system, in which early visual areas are subjected to top-down influence from a recognition area. We show that task-relevant information in early visual areas is regulated by a push-pull effect, produced by somatostatin-expressing interneurons and top-down signal. We also show that task-context information is coordinated by the phase-phase coupling of beta rhythms, while the local, task-relevant stimulus features are enhanced by the phase-amplitude coupling of beta and gamma rhythms. Furthermore, the feedback from a higher visual area such as secondary visual area facilitates the gating of task-relevant information in V1. The results provide insights to understanding the roles of inhibitory interneurons and brain rhythms in top-down influence on information processing in early visual areas.

Acetylcholine Mediates Dynamic Switching Between Information Coding Schemes in Neuronal Networks

Rate coding and phase coding are the two major coding modes seen in the brain. For these two modes, network dynamics must either have a wide distribution of frequencies for rate coding, or a narrow one to achieve stability in phase dynamics for phase coding. Acetylcholine (ACh) is a potent regulator of neural excitability. Acting through the muscarinic receptor, ACh reduces the magnitude of the potassium M-current, a hyperpolarizing current that builds up as neurons fire. The M-current contributes to several excitability features of neurons, becoming a major player in facilitating the transition between Type 1 (integrator) and Type 2 (resonator) excitability. In this paper we argue that this transition enables a dynamic switch between rate coding and phase coding as levels of ACh release change. When a network is in a high ACh state variations in synaptic inputs will lead to a wider distribution of firing rates across the network and this distribution will reflect the network structure or pattern of external input to the network. When ACh is low, network frequencies become narrowly distributed and the structure of a network or pattern of external inputs will be represented through phase relationships between firing neurons. This work provides insights into how modulation of neuronal features influences network dynamics and information processing across brain states.

Dichotomy in perceptual learning of interval timing: calibration of mean accuracy and precision differ in specificity and time course

Our brain is inexorably confronted with a dynamic environment in which it has to fine-tune spatiotemporal representations of incoming sensory stimuli and commit to a decision accordingly. Among those representations needing constant calibration is interval timing, which plays a pivotal role in various cognitive and motor tasks. To investigate how perceived time interval is adjusted by experience, we conducted a human psychophysical experiment using an implicit interval-timing task in which observers responded to an invisible bar drifting at a constant speed. We tracked daily changes in distributions of response times for a range of physical time intervals over multiple days of training with two major types of timing performance, mean accuracy and precision. We found a decoupled dynamics of mean accuracy and precision in terms of their time course and specificity of perceptual learning. Mean accuracy showed feedback-driven instantaneous calibration evidenced by a partial transfer around the time interval trained with feedback, while timing precision exhibited a long-term slow improvement with no evident specificity. We found that a Bayesian observer model, in which a subjective time interval is determined jointly by a prior and likelihood function for timing, captures the dissociative temporal dynamics of the two types of timing measures simultaneously. Finally, the model suggested that the width of the prior, not the likelihoods, gradually shrinks over sessions, substantiating the important role of prior knowledge in perceptual learning of interval timing.

Phasic and tonic patterns of locus coeruleus output differentially modulate sensory network function in the awake rat

Neurons of the nucleus locus coeruleus (LC) discharge with phasic bursts of activity superimposed on highly regular tonic discharge rates. Phasic bursts are elicited by bottom-up input mechanisms involving novel/salient sensory stimuli and top-down decision making processes; whereas tonic rates largely fluctuate according to arousal levels and behavioral states. Although it is generally believed that these two modes of activity differentially modulate information processing in LC targets, the unique role of phasic versus tonic LC output on signal processing in cells, circuits, and neural networks of waking animals is not well understood. In the current study, simultaneous recordings of individual neurons within ventral posterior medial thalamus and barrel field cortex of conscious rats provided evidence that each mode of LC output produces a unique modulatory impact on single neuron responsiveness to sensory-driven synaptic input and representations of sensory information across ensembles of simultaneously recorded cells. Each mode of LC activation specifically modulated the relationship between sensory-stimulus intensity and the subsequent responses of individual neurons and neural ensembles. Overall these results indicate that phasic versus tonic modes of LC discharge exert fundamentally different modulatory effects on target neuronal circuits within the rodent trigeminal somatosensory system. As such, each mode of LC output may differentially influence signal processing as a means of optimizing behaviorally relevant neural computations within this sensory network. Likely the ability of the LC system to differentially regulate neural responses and local circuit operations according to behavioral demands extends to other brain regions including those involved in higher cognitive functions.