Cholinergic control of cortical network interactions enables feedback-mediated attentional modulation

Effect of muscarinic blockade on the speed of attention shifting, read-out delays and learning

The study aimed to investigate to what extent blockade of muscarinic receptors affects the speed of endogenous versus exogenous attentional shift times, and how it affects learning of attention shifting, cue detection and signal readout. Subjects viewed an array of 10 moving clocks and reported the time a clock indicated when cued. Target clocks were indicated by peripheral or central cues, including conditions of pre-cuing. For peripheral and central cuing, it yielded a compound measure of how long it took to detect the cue, shift attention to the relevant clock and read the time on the clock. For the pre-cue condition it yielded a measure of how long it took to detect the cue and read the time on the clock when attention could have been pre-allocated to the target clock. In study 1, each subject participated in 2 sessions (scopolamine/placebo), whereby the order of drug intake was counterbalanced across subjects, and subjects were blinded to conditions. Scopolamine/placebo was administered before a psychophysical experiment was conducted. In study 2, the effect of muscarinic blockade on learning induced improvements of cue detection, attention shift times (for exogenous and endogenous conditions), and signal readout was investigated. Here scopolamine/placebo was administered immediately after the first (of two) psychophysical sessions, whereby a given subject either received scopolamine or placebo pills. Confirming previous results, we show that pre-cuing resulted in the shortest read-out delays, followed by exogenous cuing, with endogenous read-out delays being slowest. Scopolamine application increased readout-delays in a dose dependent manner. This was mainly driven by increased readout-delays for pre-cue conditions, and to some extent for exogenous cue conditions. It suggests that muscarinic blockade affected the ability to pre-allocated attention to a cued location, as well as to react to peripheral cues. Additionally, blockade of muscarinic receptors immediately after the first session reduced learning dependent improvement of read-out delays. These results demonstrate that muscarinic receptors play an important in detecting cues, and fast read-out of cued information, and they contribute to the learning thereof.

Disinhibitory circuit mediated by connections from vasoactive intestinal polypeptide to somatostatin interneurons underlies the paradoxical decrease in spike synchrony with increased border ownership selective neuron firing rate

The activity of border ownership selective (BOS) neurons in intermediate-level visual areas indicates which side of a contour owns a border relative to its classical receptive field and provides a fundamental component of figure-ground segregation. A physiological study reported that selective attention facilitates the activity of BOS neurons with a consistent border ownership preference, defined as two neurons tuned to respond to the same visual object. However, spike synchrony between this pair is significantly suppressed by selective attention. These neurophysiological findings are derived from a biologically-plausible microcircuit model consisting of spiking neurons including two subtypes of inhibitory interneurons, somatostatin (SOM) and vasoactive intestinal polypeptide (VIP) interneurons, and excitatory BOS model neurons. In our proposed model, BOS neurons and SOM interneurons cooperate and interact with each other. VIP interneurons not only suppress SOM interneuron responses but also are activated by feedback signals mediating selective attention, which leads to disinhibition of BOS neurons when they are directing selective attention toward an object. Our results suggest that disinhibition arising from the synaptic connections from VIP to SOM interneurons plays a critical role in attentional modulation of neurons in intermediate-level visual areas.

A microcircuit model involving parvalbumin, somatostatin, and vasoactive intestinal polypeptide inhibitory interneurons for the modulation of neuronal oscillation during visual processing

Various subtypes of inhibitory interneurons contact one another to organize cortical networks. Most cortical inhibitory interneurons express 1 of 3 genes: parvalbumin (PV), somatostatin (SOM), or vasoactive intestinal polypeptide (VIP). This diversity of inhibition allows the flexible regulation of neuronal responses within and between cortical areas. However, the exact roles of these interneuron subtypes and of excitatory pyramidal (Pyr) neurons in regulating neuronal network activity and establishing perception (via interactions between feedforward sensory and feedback attentional signals) remain largely unknown. To explore the regulatory roles of distinct neuronal types in cortical computation, we developed a computational microcircuit model with biologically plausible visual cortex layers 2/3 that combined Pyr neurons and the 3 inhibitory interneuron subtypes to generate network activity. In simulations with our model, inhibitory signals from PV and SOM neurons preferentially induced neuronal firing at gamma (30-80 Hz) and beta (20-30 Hz) frequencies, respectively, in agreement with observed physiological results. Furthermore, our model indicated that rapid inhibition from VIP to SOM subtypes underlies marked attentional modulation for low-gamma frequency (30-50 Hz) in Pyr neuron responses. Our results suggest the distinct but cooperative roles of inhibitory interneuron subtypes in the establishment of visual perception.

Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures

Electrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, these aggregate signals lack cellular resolution and thus are not easy to be interpreted directly in terms of parameters of neural microcircuits. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important for both neuroscientific and clinical applications. Over the years, we have developed tools based on neural network modeling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. This review article gives an overview of the main computational tools that we have developed and employed to invert LFPs and EEGs in terms of circuit-level neural phenomena, and outlines future challenges and directions for future research.

Attention improves information flow between neuronal populations without changing the communication subspace

Visual attention allows observers to change the influence of different parts of a visual scene on their behavior, suggesting that information can be flexibly shared between visual cortex and neurons involved in decision making. We investigated the neural substrate of flexible information routing by analyzing the activity of populations of visual neurons in the medial temporal area (MT) and oculo-motor neurons in the superior colliculus (SC) while rhesus monkeys switched spatial attention. We demonstrated that attention increases the efficacy of visuomotor communication: trial-to-trial variability in SC population activity could be better predicted by the activity of the MT population (and vice versa) when attention was directed toward their joint receptive fields. Surprisingly, this improvement in prediction was not explained by changes in the dimensionality of the shared subspace or in the magnitude of local or shared pairwise noise correlations. These results lay a foundation for future theoretical and experimental studies into how visual attention can flexibly change information flow between sensory and decision neurons.

Probing mechanisms of visual spatial attention in mice

The role of spatial attention for visual perception has been thoroughly studied in primates, but less so in mice. Several behavioral tasks in mice reveal spatial attentional effects, with similarities to observations in primates. Pairing these tasks with large-scale, cell-type-specific techniques could enable deeper access to underlying mechanisms, and help define the utility and limitations of resolving attentional effects on visual perception and neural activity in mice. In this Review, we evaluate behavioral and neural evidence for visual spatial attention in mice; assess how specializations of the mouse visual system and behavioral repertoire impact interpretation of spatial attentional effects; and outline how several measurement and manipulation techniques in mice could precisely test and refine models of attentional modulation across scales.

Theta-gamma coupling emerges from spatially heterogeneous cholinergic neuromodulation

Theta and gamma rhythms and their cross-frequency coupling play critical roles in perception, attention, learning, and memory. Available data suggest that forebrain acetylcholine (ACh) signaling promotes theta-gamma coupling, although the mechanism has not been identified. Recent evidence suggests that cholinergic signaling is both temporally and spatially constrained, in contrast to the traditional notion of slow, spatially homogeneous, and diffuse neuromodulation. Here, we find that spatially constrained cholinergic stimulation can generate theta-modulated gamma rhythms. Using biophysically-based excitatory-inhibitory (E-I) neural network models, we simulate the effects of ACh on neural excitability by varying the conductance of a muscarinic receptor-regulated K+ current. In E-I networks with local excitatory connectivity and global inhibitory connectivity, we demonstrate that theta-gamma-coupled firing patterns emerge in ACh modulated network regions. Stable gamma-modulated firing arises within regions with high ACh signaling, while theta or mixed theta-gamma activity occurs at the peripheries of these regions. High gamma activity also alternates between different high-ACh regions, at theta frequency. Our results are the first to indicate a causal role for spatially heterogenous ACh signaling in the emergence of localized theta-gamma rhythmicity. Our findings also provide novel insights into mechanisms by which ACh signaling supports the brain region-specific attentional processing of sensory information.

Effects of muscarinic and nicotinic receptors on contextual modulation in macaque area V1

Context affects the salience and visibility of image elements in visual scenes. Collinear flankers can enhance or decrease the perceptual and neuronal sensitivity to flanked stimuli. These effects are mediated through lateral interactions between neurons in the primary visual cortex (area V1), in conjunction with feedback from higher visual areas. The strength of lateral interactions is affected by cholinergic neuromodulation. Blockade of muscarinic receptors should increase the strength of lateral intracortical interactions, while nicotinic blockade should reduce thalamocortical feed-forward drive. Here we test this proposal through local iontophoretic application of the muscarinic receptor antagonist scopolamine and the nicotinic receptor antagonist mecamylamine, while recording single cells in parafoveal representations in awake fixating macaque V1. Collinear flankers generally reduced neuronal contrast sensitivity. Muscarinic and nicotinic receptor blockade equally reduced neuronal contrast sensitivity. Contrary to our hypothesis, flanker interactions were not systematically affected by either receptor blockade.

Computation of the electroencephalogram (EEG) from network models of point neurons

The electroencephalogram (EEG) is a major tool for non-invasively studying brain function and dysfunction. Comparing experimentally recorded EEGs with neural network models is important to better interpret EEGs in terms of neural mechanisms. Most current neural network models use networks of simple point neurons. They capture important properties of cortical dynamics, and are numerically or analytically tractable. However, point neurons cannot generate an EEG, as EEG generation requires spatially separated transmembrane currents. Here, we explored how to compute an accurate approximation of a rodent's EEG with quantities defined in point-neuron network models. We constructed different approximations (or proxies) of the EEG signal that can be computed from networks of leaky integrate-and-fire (LIF) point neurons, such as firing rates, membrane potentials, and combinations of synaptic currents. We then evaluated how well each proxy reconstructed a ground-truth EEG obtained when the synaptic currents of the LIF model network were fed into a three-dimensional network model of multicompartmental neurons with realistic morphologies. Proxies based on linear combinations of AMPA and GABA currents performed better than proxies based on firing rates or membrane potentials. A new class of proxies, based on an optimized linear combination of time-shifted AMPA and GABA currents, provided the most accurate estimate of the EEG over a wide range of network states. The new linear proxies explained 85-95% of the variance of the ground-truth EEG for a wide range of network configurations including different cell morphologies, distributions of presynaptic inputs, positions of the recording electrode, and spatial extensions of the network. Non-linear EEG proxies using a convolutional neural network (CNN) on synaptic currents increased proxy performance by a further 2-8%. Our proxies can be used to easily calculate a biologically realistic EEG signal directly from point-neuron simulations thus facilitating a quantitative comparison between computational models and experimental EEG recordings.

Analysis of spiking synchrony in visual cortex reveals distinct types of top-down modulation signals for spatial and object-based attention

The activity of a border ownership selective (BOS) neuron indicates where a foreground object is located relative to its (classical) receptive field (RF). A population of BOS neurons thus provides an important component of perceptual grouping, the organization of the visual scene into objects. In previous theoretical work, it has been suggested that this grouping mechanism is implemented by a population of dedicated grouping (“G”) cells that integrate the activity of the distributed feature cells representing an object and, by feedback, modulate the same cells, thus making them border ownership selective. The feedback modulation by G cells is thought to also provide the mechanism for object-based attention. A recent modeling study showed that modulatory common feedback, implemented by synapses with N-methyl-D-aspartate (NMDA)-type glutamate receptors, accounts for the experimentally observed synchrony in spike trains of BOS neurons and the shape of cross-correlations between them, including its dependence on the attentional state. However, that study was limited to pairs of BOS neurons with consistent border ownership preferences, defined as two neurons tuned to respond to the same visual object, in which attention decreases synchrony. But attention has also been shown to increase synchrony in neurons with inconsistent border ownership selectivity. Here we extend the computational model from the previous study to fully understand these effects of attention. We postulate the existence of a second type of G-cell that represents spatial attention by modulating the activity of all BOS cells in a spatially defined area. Simulations of this model show that a combination of spatial and object-based mechanisms fully accounts for the observed pattern of synchrony between BOS neurons. Our results suggest that modulatory feedback from G-cells may underlie both spatial and object-based attention.

Vision allows us to make sense out of a very complex signal, the patterns of light rays reaching our eyes. Two mechanisms are essential for this: perceptual organization which structures the input into meaningful visual objects, and attention which selects only the most important parts in the input. Prior work suggests that both of these mechanisms are implemented by neurons called grouping cells. These organize the object features into coherent entities (perceptual grouping) and access them as needed (selective attention). For technical reasons it is difficult to observe grouping cells but their effect can be seen in the influence they have on responses of other classes of cells. These responses have been measured experimentally and it was found that they depend in unexpected ways on where the subject was attending. Using a computational model, we here demonstrate that the responses can be understood in terms of the interaction between two kinds of selective attention, both of which are known to occur in primate perception. One is attention to a specific area in the environment, the other is to specific objects. A model including both of these attentional mechanisms generates neuronal responses in agreement with the observed patterns of neural activity.

Directed information exchange between cortical layers in macaque V1 and V4 and its modulation by selective attention

Achieving behavioral goals requires integration of sensory and cognitive information across cortical laminae and cortical regions. How this computation is performed remains unknown. Using local field potential recordings and spectrally resolved conditional Granger causality (cGC) analysis, we mapped visual information flow, and its attentional modulation, between cortical layers within and between macaque brain areas V1 and V4. Stimulus-induced interlaminar information flow within V1 dominated upwardly, channeling information toward supragranular corticocortical output layers. Within V4, information flow dominated from granular to supragranular layers, but interactions between supragranular and infragranular layers dominated downwardly. Low-frequency across-area communication was stronger from V4 to V1, with little layer specificity. Gamma-band communication was stronger in the feedforward V1-to-V4 direction. Attention to the receptive field of V1 decreased communication between all V1 layers, except for granular-to-supragranular layer interactions. Communication within V4, and from V1 to V4, increased with attention across all frequencies. While communication from V4 to V1 was stronger in lower-frequency bands (4 to 25 Hz), attention modulated cGCs from V4 to V1 across all investigated frequencies. Our data show that top-down cognitive processes result in reduced communication within cortical areas, increased feedforward communication across all frequency bands, and increased gamma-band feedback communication.

Effects of Neuromodulation on Excitatory-Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

Acetylcholine (ACh), one of the brain's most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E-I networks), which are ubiquitous in the brain. Utilizing biophysical models of E-I networks, we analyze how the network connectivity structure in terms of synaptic connectivity alters the influence of ACh on the generation of synchronous excitatory bursting. We investigate networks containing all combinations of excitatory and inhibitory cells with high (Type I properties) or low (Type II properties) modulatory tone. To vary network connectivity structure, we focus on the effects of the strengths of inter-connections between excitatory and inhibitory cells (E-I synapses and I-E synapses), and the strengths of intra-connections among excitatory cells (E-E synapses) and among inhibitory cells (I-I synapses). We show that the presence of ACh may or may not affect the generation of network synchrony depending on the network connectivity. Specifically, strong network inter-connectivity induces synchronous excitatory bursting regardless of the cellular propensity for synchronization, which aligns with predictions of the PING model. However, when a network's intra-connectivity dominates its inter-connectivity, the propensity for synchrony of either inhibitory or excitatory cells can determine the generation of network-wide bursting.

Phasic cholinergic signaling promotes emergence of local gamma rhythms in excitatory-inhibitory networks

Recent experimental results have shown that the detection of cues in behavioral attention tasks relies on transient increases of acetylcholine (ACh) release in frontal cortex and cholinergically driven oscillatory activity in the gamma frequency band (Howe et al. Journal of Neuroscience, 2017, 37, 3215). The cue-induced gamma rhythmic activity requires stimulation of M1 muscarinic receptors. Using biophysical computational modeling, we show that a network of excitatory (E) and inhibitory (I) neurons that initially displays asynchronous firing can generate transient gamma oscillatory activity in response to simulated brief pulses of ACh. ACh effects are simulated as transient modulation of the conductance of an M-type K⁺ current which is blocked by activation of muscarinic receptors and has significant effects on neuronal excitability. The ACh-induced effects on the M current conductance, g_Ks , change network dynamics to promote the emergence of network gamma rhythmicity through a Pyramidal-Interneuronal Network Gamma mechanism. Depending on connectivity strengths between and among E and I cells, gamma activity decays with the simulated g_Ks transient modulation or is sustained in the network after the g_Ks transient has completely dissipated. We investigated the sensitivity of the emergent gamma activity to synaptic strengths, external noise and simulated levels of g_Ks modulation. To address recent experimental findings that cholinergic signaling is likely spatially focused and dynamic, we show that localized g_Ks modulation can induce transient changes of cellular excitability in local subnetworks, subsequently causing population-specific gamma oscillations. These results highlight dynamical mechanisms underlying localization of ACh-driven responses and suggest that spatially localized, cholinergically induced gamma may contribute to selectivity in the processing of competing external stimuli, as occurs in attentional tasks.

Cholinergic Modulation Promotes Attentional Modulation in Primary Visual Cortex- A Modeling Study

Attention greatly influences sensory neural processing by enhancing firing rates of neurons that represent the attended stimuli and by modulating their tuning properties. The cholinergic system is believed to partly mediate the attention contingent improvement of cortical processing by influencing neuronal excitability, synaptic transmission and neural network characteristics. Here, we used a biophysically based model to investigate the mechanisms by which cholinergic system influences sensory information processing in the primary visual cortex (V1) layer 4C. The physiological properties and architectures of our model were inspired by experimental data and include feed-forward input from dorsal lateral geniculate nucleus that sets up orientation preference in V1 neural responses. When including a cholinergic drive, we found significant sharpening in orientation selectivity, desynchronization of LFP gamma power and spike-field coherence, decreased response variability and correlation reduction mostly by influencing intracortical interactions and by increasing inhibitory drive. Our results indicated that these effects emerged due to changes specific to the behavior of the inhibitory neurons. The behavior of our model closely resembles the effects of attention on neural activities in monkey V1. Our model suggests precise mechanisms through which cholinergic modulation may mediate the effects of attention in the visual cortex.

A cortical model with multi-layers to study visual attentional modulation of neurons at the synaptic level

Visual attention is a selective process of visual information and improves perceptual performance by modulating activities of neurons in the visual system. It has been reported that attention increased firing rates of neurons, reduced their response variability and improved reliability of coding relevant stimuli. Recent neurophysiological studies demonstrated that attention also enhanced the synaptic efficacy between neurons mediated through NMDA and AMPA receptors. Majority of computational models of attention usually are based on firing rates, which cannot explain attentional modulations observed at the synaptic level. To understand mechanisms of attentional modulations at the synaptic level, we proposed a neural network consisting of three layers, corresponding to three different brain regions. Each layer has excitatory and inhibitory neurons. Each neuron was modeled by the Hodgkin-Huxley model. The connections between neurons were through excitatory AMPA and NMDA receptors, as well as inhibitory GABAA receptors. Since the binding process of neurotransmitters with receptors is stochastic in the synapse, it is hypothesized that attention could reduce the variation of the stochastic binding process and increase the fraction of bound receptors in the model. We investigated how attention modulated neurons' responses at the synaptic level on the basis of this hypothesis. Simulated results demonstrated that attention increased firing rates of neurons and reduced their response variability. The attention-induced effects were stronger in higher regions compared to those in lower regions, and stronger for inhibitory neurons than for excitatory neurons. In addition, AMPA receptor antagonist (CNQX) impaired attention-induced modulations on neurons' responses, while NMDA receptor antagonist (APV) did not. These results suggest that attention may modulate neuronal activity at the synaptic level.

Acetylcholine-mediated top-down attention improves the response to bottom-up inputs by deformation of the attractor landscape

To understand the effect of attention on neuronal dynamics, we propose a multi-module network, with each module consisting of fully interconnected groups of excitatory and inhibitory neurons. This network shows transitive dynamics among quasi-attractors as its typical dynamics. When the release of acetylcholine onto the network is simulated by attention, the transitive dynamics change into stable dynamics in which the system converges to an attractor. We found that this network can reproduce three experimentally observed properties of attention-dependent response modulation, namely an increase in the firing rate, a decrease in the Fano factor of the firing rate, and a decrease in the correlation coefficients between the firing rates of pairs of neurons. Moreover, we also showed theoretically that the release of acetylcholine increases the sensitivity to bottom-up inputs by changing the response function.

Neuromodulation of Attention

Attention is critical to high-level cognition and attention deficits are a hallmark of neurologic and neuropsychiatric disorders. Although years of research indicates that distinct neuromodulators influence attentional control, a mechanistic account that traverses levels of analysis (cells, circuits, behavior) is missing. However, such an account is critical to guide the development of next-generation pharmacotherapies aimed at forestalling or remediating the global burden associated with disorders of attention. Here, we summarize current neuroscientific understanding of how attention affects single neurons and networks of neurons. We then review key results that have informed our understanding of how neuromodulation shapes these neuron and network properties and thereby enables the appropriate allocation of attention to relevant external or internal events. Finally, we highlight areas where we believe hypotheses can be formulated and tackled experimentally in the near future, thereby critically increasing our mechanistic understanding of how attention is implemented at the cellular and network levels.

Structure and function of dual-source cholinergic modulation in early vision

Behavioral states such as arousal and attention have profound effects on sensory processing, determining how-even whether-a stimulus is perceived. This state-dependence is believed to arise, at least in part, in response to inputs from subcortical structures that release neuromodulators such as acetylcholine, often nonsynaptically. The mechanisms that underlie the interaction between these nonsynaptic signals and the more point-to-point synaptic cortical circuitry are not well understood. This review highlights the state of the field, with a focus on cholinergic action in early visual processing. Key anatomical and physiological features of both the cholinergic and the visual systems are discussed. Furthermore, presenting evidence of cholinergic modulation in visual thalamus and primary visual cortex, we explore potential functional roles of acetylcholine and its effects on the processing of visual input over the sleep-wake cycle, sensory gain control during wakefulness, and consider evidence for cholinergic support of visual attention.

Basal forebrain contributes to default mode network regulation

The default mode network (DMN) is a collection of cortical brain regions that is active during states of rest or quiet wakefulness in humans and other mammalian species. A pertinent characteristic of the DMN is a suppression of local field potential gamma activity during cognitive task performance as well as during engagement with external sensory stimuli. Conversely, gamma activity is elevated in the DMN during rest. Here, we document that the rat basal forebrain (BF) exhibits the same pattern of responses, namely pronounced gamma oscillations during quiet wakefulness in the home cage and suppression of this activity during active exploration of an unfamiliar environment. We show that gamma oscillations are localized to the BF and that gamma-band activity in the BF has a directional influence on a hub of the rat DMN, the anterior cingulate cortex, during DMN-dominated brain states. The BF is well known as an ascending, activating, neuromodulatory system involved in wake-sleep regulation, memory formation, and regulation of sensory information processing. Our findings suggest a hitherto undocumented role of the BF as a subcortical node of the DMN, which we speculate may be important for switching between internally and externally directed brain states. We discuss potential BF projection circuits that could underlie its role in DMN regulation and highlight that certain BF nuclei may provide potential target regions for up- or down-regulation of DMN activity that might prove useful for treatment of DMN dysfunction in conditions such as epilepsy or major depressive disorder.

Neuromodulatory Systems and Their Interactions: A Review of Models, Theories, and Experiments

Neuromodulatory systems, including the noradrenergic, serotonergic, dopaminergic, and cholinergic systems, track environmental signals, such as risks, rewards, novelty, effort, and social cooperation. These systems provide a foundation for cognitive function in higher organisms; attention, emotion, goal-directed behavior, and decision-making derive from the interaction between the neuromodulatory systems and brain areas, such as the amygdala, frontal cortex, hippocampus, and sensory cortices. Given their strong influence on behavior and cognition, these systems also play a key role in disease states and are the primary target of many current treatment strategies. The fact that these systems interact with each other either directly or indirectly, however, makes it difficult to understand how a failure in one or more systems can lead to a particular symptom or pathology. In this review, we explore experimental evidence, as well as focus on computational and theoretical models of neuromodulation. Better understanding of neuromodulatory systems may lead to the development of novel treatment strategies for a number of brain disorders.

Attentional modulation of neuronal variability in circuit models of cortex

The circuit mechanisms behind shared neural variability (noise correlation) and its dependence on neural state are poorly understood. Visual attention is well-suited to constrain cortical models of response variability because attention both increases firing rates and their stimulus sensitivity, as well as decreases noise correlations. We provide a novel analysis of population recordings in rhesus primate visual area V4 showing that a single biophysical mechanism may underlie these diverse neural correlates of attention. We explore model cortical networks where top-down mediated increases in excitability, distributed across excitatory and inhibitory targets, capture the key neuronal correlates of attention. Our models predict that top-down signals primarily affect inhibitory neurons, whereas excitatory neurons are more sensitive to stimulus specific bottom-up inputs. Accounting for trial variability in models of state dependent modulation of neuronal activity is a critical step in building a mechanistic theory of neuronal cognition.

DOI:http://dx.doi.org/10.7554/eLife.23978.001

The world around us is complex and our brains need to navigate this complexity. We must focus on relevant inputs from our senses – such as the bus we need to catch – while ignoring distractions – such as the eye-catching displays in the shop windows we pass on the same street. Selective attention is a tool that enables us to filter complex sensory scenes and focus on whatever is most important at the time. But how does selective attention work?

Our sense of vision results from the activity of cells in a region of the brain called visual cortex. Paying attention to an object affects the activity of visual cortex in two ways. First, it causes the average activity of the brain cells in the visual cortex that respond to that object to increase. Second, it reduces spontaneous moment-to-moment fluctuations in the activity of those brain cells, known as noise. Both of these effects make it easier for the brain to process the object in question.

Kanashiro et al. set out to build a mathematical model of visual cortex that captures these two components of selective attention. The cortex contains two types of brain cells: excitatory neurons, which activate other cells, and inhibitory neurons, which suppress other cells. Experiments suggest that excitatory neurons contribute to the flow of activity within the cortex, whereas inhibitory neurons help cancel out noise. The new mathematical model predicts that paying attention affects inhibitory neurons far more than excitatory ones. According to the model, selective attention works mainly by reducing the noise that would otherwise distort the activity of visual cortex.

The next step is to test this prediction directly. This will require measuring the activity of the inhibitory neurons in an animal performing a selective attention task. Such experiments, which should be achievable using existing technologies, will allow scientists to confirm or disprove the current model, and to dissect the mechanisms that underlie visual attention.

DOI:http://dx.doi.org/10.7554/eLife.23978.002

Pharmacological Fingerprints of Contextual Uncertainty

Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses.

Pharmacological interventions and hierarchical Bayesian modelling pinpoint the roles of noradrenaline, acetylcholine, and dopamine in computing different forms of uncertainty and in sensitizing actions to our beliefs about uncertainty.

Interacting with dynamic and ever-changing environments requires frequent updating of our beliefs about the world. By learning the relationships that link events in the current environmental context, it is possible to prepare and execute fast, accurate responses to those events that are predictable. However, the world’s complex dynamics give rise to uncertainty about the relationships that exist between events and uncertainty about how these relationships might change over time. Several neuromodulators have been proposed to signal these different forms of uncertainty, but their relative contributions to updating beliefs and modulating responses have remained elusive. Here we combine a probabilistic reaction time task, pharmacological interventions, and a hierarchical Bayesian learning model to identify the roles of noradrenaline, acetylcholine, and dopamine in individual computations of uncertainty. We propose that noradrenaline modulates learning about the instability of the relationships that link environmental events. Acetylcholine balances the attribution of uncertainty to unexpected events occurring within an environmental context or to gross violations of our expectations following a context change. In contrast, dopamine sensitises our actions to our beliefs about uncertainty.

Theta-Gamma Coding Meets Communication-through-Coherence: Neuronal Oscillatory Multiplexing Theories Reconciled

Several theories have been advanced to explain how cross-frequency coupling, the interaction of neuronal oscillations at different frequencies, could enable item multiplexing in neural systems. The communication-through-coherence theory proposes that phase-matching of gamma oscillations between areas enables selective processing of a single item at a time, and a later refinement of the theory includes a theta-frequency oscillation that provides a periodic reset of the system. Alternatively, the theta-gamma neural code theory proposes that a sequence of items is processed, one per gamma cycle, and that this sequence is repeated or updated across theta cycles. In short, both theories serve to segregate representations via the temporal domain, but differ on the number of objects concurrently represented. In this study, we set out to test whether each of these theories is actually physiologically plausible, by implementing them within a single model inspired by physiological data. Using a spiking network model of visual processing, we show that each of these theories is physiologically plausible and computationally useful. Both theories were implemented within a single network architecture, with two areas connected in a feedforward manner, and gamma oscillations generated by feedback inhibition within areas. Simply increasing the amplitude of global inhibition in the lower area, equivalent to an increase in the spatial scope of the gamma oscillation, yielded a switch from one mode to the other. Thus, these different processing modes may co-exist in the brain, enabling dynamic switching between exploratory and selective modes of attention.

There is a growing consensus that neuronal oscillations constitute a fundamental computational mechanism in the brain. Beyond this, recent experimental evidence has highlighted interactions between oscillations at high and low frequencies (e.g. gamma oscillations, 40–80 Hz, are modulated by theta oscillations, 4–10 Hz), and two major theories have developed regarding the functional role of this kind of cross-frequency coupling. Here, we present a computational modelling study of these theories with strong implications for biological studies. Firstly, we demonstrate for the first time that each of these theories is physiologically plausible, in that they can be implemented in a spiking network model with parameters guided by experimental data. Secondly, we show that they are each computationally useful, able to overcome a feature-binding ambiguity in a presented stimulus. Finally, we implement both theories within a single network model, and find that only a single parameter change is required to switch between the two processing states. This leads to the exciting new proposal that both theories may be correct, both implemented in the brain, with dynamic switching between modes according to processing and attentional requirements.

Spike synchrony generated by modulatory common input through NMDA-type synapses

Common excitatory input to neurons increases their firing rates and the strength of the spike correlation (synchrony) between them. Little is known, however, about the synchronizing effects of modulatory common input. Here, we show that modulatory common input with the slow synaptic kinetics of N-methyl-d-aspartate (NMDA) receptors enhances firing rates and also produces synchrony. Tight synchrony (correlations on the order of milliseconds) always increases with modulatory strength. Unexpectedly, the relationship between strength of modulation and strength of loose synchrony (tens of milliseconds) is not monotonic: The strongest loose synchrony is obtained for intermediate modulatory amplitudes. This finding explains recent neurophysiological results showing that in cortical areas V1 and V2, presumed modulatory top-down input due to contour grouping increases (loose and tight) synchrony but that additional modulatory input due to top-down attention does not change tight synchrony and actually decreases loose synchrony. These neurophysiological findings are understood from our model of integrate-and-fire neurons under the assumption that contour grouping as well as attention lead to additive modulatory common input through NMDA-type synapses. In contrast, circuits with common projections through model α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors did not exhibit the paradoxical decrease of synchrony with increased input. Our results suggest that NMDA receptors play a critical role in top-down response modulation in the visual cortex.

Parkinson's disease, visual hallucinations and apomorphine: A review of the available evidence

BACKGROUND

Visual hallucinations (VH) occur in the clinical course of Parkinson's disease (PD) and are predictive for PD dementia. The genesis of VH is related to impaired bottom-up and/or top-down visual processing which can be linked to cholinergic dysfunction and mono-amine imbalance. The risk of developing VH with oral dopamine agonists seems to increase with advancing disease, while in contrast some clinical studies suggest that apomorphine does not worsen VH, or might even improve VH.

METHODS

The aim of this study is to review the current evidence of apomorphine and its effects on VH in PD patients.

RESULTS

Apomorphine is well-tolerated in PD patients with VH, also in long-term follow-up studies. Apomorphine is also suggested to have the potential to alleviate VH. Some data suggest that the positive effect of apomorphine on VH is related to its piperidine moiety, part of many anti-psychotics. Irrespective this piperidine moiety, apomorphine has a high D1-like receptor affinity, and acts as a serotonin 5-HT2A receptor antagonist, which might explain the potential anti-hallucinogenic properties as well.

CONCLUSION

The anecdotal evidence suggesting that apomorphine has a relatively low proclivity to induce VH in PD may be due to its capacity to reduce serotonergic activity in particular. Therefore apomorphine is still an option to consider in fluctuating PD patients with VH, if they are treated properly with respect to their cholinergic deficits and existing VH.

Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

Attention and normalization circuits in macaque V1

Attention affects neuronal processing and improves behavioural performance. In extrastriate visual cortex these effects have been explained by normalization models, which assume that attention influences the circuit that mediates surround suppression. While normalization models have been able to explain attentional effects, their validity has rarely been tested against alternative models. Here we investigate how attention and surround/mask stimuli affect neuronal firing rates and orientation tuning in macaque V1. Surround/mask stimuli provide an estimate to what extent V1 neurons are affected by normalization, which was compared against effects of spatial top down attention. For some attention/surround effect comparisons, the strength of attentional modulation was correlated with the strength of surround modulation, suggesting that attention and surround/mask stimulation (i.e. normalization) might use a common mechanism. To explore this in detail, we fitted multiplicative and additive models of attention to our data. In one class of models, attention contributed to normalization mechanisms, whereas in a different class of models it did not. Model selection based on Akaike's and on Bayesian information criteria demonstrated that in most cells the effects of attention were best described by models where attention did not contribute to normalization mechanisms. This demonstrates that attentional influences on neuronal responses in primary visual cortex often bypass normalization mechanisms.

Oscillatory synchrony as a mechanism of attentional processing

The question of how the brain selects which stimuli in our visual field will be given priority to enter into perception, to guide our actions and to form our memories has been a matter of intense research in studies of visual attention. Work in humans and animal models has revealed an extended network of areas involved in the control and maintenance of attention. For many years, imaging studies in humans constituted the main source of a systems level approach, while electrophysiological recordings in non-human primates provided insight into the cellular mechanisms of visual attention. Recent technological advances and the development of sophisticated analytical tools have allowed us to bridge the gap between the two approaches and assess how neuronal ensembles across a distributed network of areas interact in visual attention tasks. A growing body of evidence suggests that oscillatory synchrony plays a crucial role in the selective communication of neuronal populations that encode the attended stimuli. Here, we discuss data from theoretical and electrophysiological studies, with more emphasis on findings from humans and non-human primates that point to the relevance of oscillatory activity and synchrony for attentional processing and behavior. These findings suggest that oscillatory synchrony in specific frequencies reflects the biophysical properties of specific cell types and local circuits and allows the brain to dynamically switch between different spatio-temporal patterns of activity to achieve flexible integration and selective routing of information along selected neuronal populations according to behavioral demands. This article is part of a Special Issue entitled SI: Prediction and Attention.

Neuropharmacology of altered brain oscillations in schizophrenia

Impairments in spatial and temporal integration of brain network activity are a core feature of schizophrenia. Neural network oscillatory activity is considered to be fundamentally important in coordinating neural activity throughout the brain. Hence, exploration of brain oscillations has become an indispensible tool to study the neural basis of mental illnesses. However, most of the studies in schizophrenia include medicated patients. This implicates the question to what extent are changes in the electrophysiological parameters genuine illness effects, genuine drug effects or a mixture of both. We here provide a short overview of the neuropharmacology of brain oscillations with respect to schizophrenia. The core assumption of the so-called "pharmaco-EEG" approach is that drug effects on mental and cognitive functions are reflected in changes in quantitative EEG parameters. Hence, clinical efficacy of drugs might be predicted on the basis of the neuropharmacology of electrophysiological measures, such as brain oscillations. Vice versa, knowledge of drug effects on brain oscillations can be of essence in understanding schizophrenia. However, the current literature lacks systematic findings, because of at least two problems. First, the pharmacology of most antipsychotic drugs is complex including interactions with several transmitter receptors. Second, the neuropathology of schizophrenia still has no pathognomonic signature. Even though it is presently not possible to clearly dissociate drug- and illness effects in neural oscillations, this review emphasizes future studies to foster the understanding of this relationship in schizophrenia and other neuropsychiatric diseases.

Cholinergic stimulation enhances Bayesian belief updating in the deployment of spatial attention

The exact mechanisms whereby the cholinergic neurotransmitter system contributes to attentional processing remain poorly understood. Here, we applied computational modeling to psychophysical data (obtained from a spatial attention task) under a psychopharmacological challenge with the cholinesterase inhibitor galantamine (Reminyl). This allowed us to characterize the cholinergic modulation of selective attention formally, in terms of hierarchical Bayesian inference. In a placebo-controlled, within-subject, crossover design, 16 healthy human subjects performed a modified version of Posner's location-cueing task in which the proportion of validly and invalidly cued targets (percentage of cue validity, % CV) changed over time. Saccadic response speeds were used to estimate the parameters of a hierarchical Bayesian model to test whether cholinergic stimulation affected the trial-wise updating of probabilistic beliefs that underlie the allocation of attention or whether galantamine changed the mapping from those beliefs to subsequent eye movements. Behaviorally, galantamine led to a greater influence of probabilistic context (% CV) on response speed than placebo. Crucially, computational modeling suggested this effect was due to an increase in the rate of belief updating about cue validity (as opposed to the increased sensitivity of behavioral responses to those beliefs). We discuss these findings with respect to cholinergic effects on hierarchical cortical processing and in relation to the encoding of expected uncertainty or precision.

Attention and the Cholinergic System: Relevance to Schizophrenia

Traditional methods of drug discovery often rely on a unidirectional, "bottom-up" approach: A search for molecular compounds that target a particular neurobiological substrate (e.g., a receptor type), the refinement of those compounds, testing in animal models using high-throughput behavioral screening methods, and then human testing for safety and effectiveness. Many attempts have found the "effectiveness" criterion to be a major stumbling block, and we and others have suggested that success may be improved by an alternative approach that considers the neural circuits mediating the effects of genetic and molecular manipulations on behavior and cognition. We describe our efforts to understand the cholinergic system's role in attention using parallel approaches to test main hypotheses in both rodents and humans as well as generating converging evidence using methods and levels of analysis tailored to each species. The close back-and-forth between these methods has enhanced our understanding of the cholinergic system's role in attention both "bottom-up" and "top-down"-that is, the basic neuroscience identifies potential neuronal circuit-based mechanisms of clinical symptoms, and the patient and genetic populations serve as natural experiments to test and refine hypotheses about its contribution to specific processes. Together, these studies have identified (at least) two major and potentially independent contributions of the cholinergic system to attention: a neuromodulatory component that influences cognitive control in response to challenges from distractors that either make detection more difficult or draw attention away from the distractor, and a phasic or transient cholinergic signal that instigates a shift from ongoing behavior and the activation of cue-associated response. Right prefrontal cortex appears to play a particularly important role in the neuromodulatory component integrating motivational and cognitive influences for top-down control across populations, whereas the transient cholinergic signal involves orbitofrontal regions associated with shifts between internal and external attention. Understanding how these two modes of cholinergic function interact and are perturbed in schizophrenia will be an important prerequisite for developing effective treatments.

Stochastic cortical neurodynamics underlying the memory and cognitive changes in aging

The relatively random spiking times of individual neurons provide a source of noise in the brain. We show how this noise interacting with altered depth in the basins of attraction of networks involved in short-term memory, attention, and episodic memory provide an approach to understanding some of the cognitive changes in normal aging. The effects of the neurobiological changes in aging that are considered include reduced synaptic modification and maintenance during learning produced in part through reduced acetylcholine in normal aging, reduced dopamine which reduces NMDA-receptor mediated effects, reduced noradrenaline which increases cAMP and thus shunts excitatory synaptic inputs, and the effects of a reduction in acetylcholine in increasing spike frequency adaptation. Using integrate-and-fire simulations of an attractor network implementing memory recall and short-term memory, it is shown that all these changes associated with aging reduce the firing rates of the excitatory neurons, which in turn reduce the depth of the basins of attraction, resulting in a much decreased probability in maintaining in short-term memory what has been recalled from the attractor network. This stochastic dynamics approach opens up new ways to understand and potentially treat the effects of normal aging on memory and cognitive functions.

Illuminating the role of cholinergic signaling in circuits of attention and emotionally salient behaviors

Acetylcholine (ACh) signaling underlies specific aspects of cognitive functions and behaviors, including attention, learning, memory and motivation. Alterations in ACh signaling are involved in the pathophysiology of multiple neuropsychiatric disorders. In the central nervous system, ACh transmission is mainly guaranteed by dense innervation of select cortical and subcortical regions from disperse groups of cholinergic neurons within the basal forebrain (BF; e.g., diagonal band, medial septal, nucleus basalis) and the pontine-mesencephalic nuclei, respectively. Despite the fundamental role of cholinergic signaling in the CNS and the long standing knowledge of the organization of cholinergic circuitry, remarkably little is known about precisely how ACh release modulates cortical and subcortical neural activity and the behaviors these circuits subserve. Growing interest in cholinergic signaling in the CNS focuses on the mechanism(s) of action by which endogenously released ACh regulates cognitive functions, acting as a neuromodulator and/or as a direct transmitter via nicotinic and muscarinic receptors. The development of optogenetic techniques has provided a valuable toolbox with which we can address these questions, as it allows the selective manipulation of the excitability of cholinergic inputs to the diverse array of cholinergic target fields within cortical and subcortical domains. Here, we review recent papers that use the light-sensitive opsins in the cholinergic system to elucidate the role of ACh in circuits related to attention and emotionally salient behaviors. In particular, we highlight recent optogenetic studies which have tried to disentangle the precise role of ACh in the modulation of cortical-, hippocampal- and striatal-dependent functions.

Boosting visual cortex function and plasticity with acetylcholine to enhance visual perception

The cholinergic system is a potent neuromodulatory system that plays critical roles in cortical plasticity, attention and learning. In this review, we propose that the cellular effects of acetylcholine (ACh) in the primary visual cortex during the processing of visual inputs might induce perceptual learning; i.e., long-term changes in visual perception. Specifically, the pairing of cholinergic activation with visual stimulation increases the signal-to-noise ratio, cue detection ability and long-term facilitation in the primary visual cortex. This cholinergic enhancement would increase the strength of thalamocortical afferents to facilitate the treatment of a novel stimulus while decreasing the cortico-cortical signaling to reduce recurrent or top-down modulation. This balance would be mediated by different cholinergic receptor subtypes that are located on both glutamatergic and GABAergic neurons of the different cortical layers. The mechanisms of cholinergic enhancement are closely linked to attentional processes, long-term potentiation (LTP) and modulation of the excitatory/inhibitory balance. Recently, it was found that boosting the cholinergic system during visual training robustly enhances sensory perception in a long-term manner. Our hypothesis is that repetitive pairing of cholinergic and sensory stimulation over a long period of time induces long-term changes in the processing of trained stimuli that might improve perceptual ability. Various non-invasive approaches to the activation of the cholinergic neurons have strong potential to improve visual perception.

Differential classical conditioning selectively heightens response gain of neural population activity in human visual cortex

Neutral cues, after being reliably paired with noxious events, prompt defensive engagement and amplified sensory responses. To examine the neurophysiology underlying these adaptive changes, we quantified the contrast-response function of visual cortical population activity during differential aversive conditioning. Steady-state visual evoked potentials (ssVEPs) were recorded while participants discriminated the orientation of rapidly flickering grating stimuli. During each trial, luminance contrast of the gratings was slowly increased and then decreased. Right-tilted gratings (CS+) were paired with loud white noise but left-tilted gratings (CS-) were not. The contrast-following waveform envelope of ssVEPs showed selective amplification of the CS+ only during the high-contrast stage of the viewing epoch. Findings support the notion that motivational relevance, learned in a time frame of minutes, affects vision through a response gain mechanism.

Acetylcholine functionally reorganizes neocortical microcircuits

Sensory information is processed and transmitted through the synaptic structure of local cortical circuits, but it is unclear how modulation of this architecture influences the cortical representation of sensory stimuli. Acetylcholine (ACh) promotes attention and arousal and is thought to increase the signal-to-noise ratio of sensory input in primary sensory cortices. Using high-speed two-photon calcium imaging in a thalamocortical somatosensory slice preparation, we recorded action potential activity of up to 900 neurons simultaneously and compared local cortical circuit activations with and without bath presence of ACh. We found that ACh reduced weak pairwise relationships and excluded neurons that were already unreliable during circuit activity. Using action potential activity from the imaged population, we generated functional wiring diagrams based on the statistical dependencies of activity between neurons. ACh pruned weak functional connections from spontaneous circuit activations and yielded a more modular and hierarchical circuit structure, which biased activity to flow in a more feedforward fashion. Neurons that were active in response to thalamic input had reduced pairwise dependencies overall, but strong correlations were conserved. This coincided with a prolonged period during which neurons showed temporally precise responses to thalamic input. Our results demonstrate that ACh reorganizes functional circuit structure in a manner that may enhance the integration and discriminability of thalamic afferent input within local neocortical circuitry.

Expression of m1-type muscarinic acetylcholine receptors by parvalbumin-immunoreactive neurons in the primary visual cortex: a comparative study of rat, guinea pig, ferret, macaque, and human

Cholinergic neuromodulation is a candidate mechanism for aspects of arousal and attention in mammals. We have reported previously that cholinergic modulation in the primary visual cortex (V1) of the macaque monkey is strongly targeted toward GABAergic interneurons, and in particular that the vast majority of parvalbumin-immunoreactive (PV) neurons in macaque V1 express the m1-type (pirenzepine-sensitive, Gq-coupled) muscarinic ACh receptor (m1AChR). In contrast, previous physiological data indicates that PV neurons in rats rarely express pirenzepine-sensitive muscarinic AChRs. To examine further this apparent species difference in the cholinergic effectors for the primary visual cortex, we have conducted a comparative study of the expression of m1AChRs by PV neurons in V1 of rats, guinea pigs, ferrets, macaques, and humans. We visualize PV- and mAChR-immunoreactive somata by dual-immunofluorescence confocal microscopy and find that the species differences are profound; the vast majority (>75%) of PV-ir neurons in macaques, humans, and guinea pigs express m1AChRs. In contrast, in rats only ∼25% of the PV population is immunoreactive for m1AChRs. Our data reveal that while they do so much less frequently than in primates, PV neurons in rats do express Gq-coupled muscarinic AChRs, which appear to have gone undetected in the previous in vitro studies. Data such as these are critical in determining the species that represent adequate models for the capacity of the cholinergic system to modulate inhibition in the primate cortex.

Cholinergic modulation of the medial prefrontal cortex: the role of nicotinic receptors in attention and regulation of neuronal activity

Acetylcholine (ACh) release in the medial prefrontal cortex (mPFC) is crucial for normal cognitive performance. Despite the fact that many have studied how ACh affects neuronal processing in the mPFC and thereby influences attention behavior, there is still a lot unknown about how this occurs. Here we will review the evidence that cholinergic modulation of the mPFC plays a role in attention and we will summarize the current knowledge about the role between ACh receptors (AChRs) and behavior and how ACh receptor activation changes processing in the cortical microcircuitry. Recent evidence implicates fast phasic release of ACh in cue detection and attention. This review will focus mainly on the fast ionotropic nicotinic receptors and less on the metabotropic muscarinic receptors. Finally, we will review limitations of the existing studies and address how innovative technologies might push the field forward in order to gain understanding into the relation between ACh, neuronal activity and behavior.

Deterministic functions of cortical acetylcholine

Traditional descriptions of the basal forebrain cholinergic projection system to the cortex have focused on neuromodulatory influences, that is, mechanisms that modulate cortical information processing but are not necessary for mediating discrete behavioral responses and cognitive operations. This review summarises and conceptualises the evidence in support of more deterministic contributions of cholinergic projections to cortical information processing. Through presynaptic receptors expressed on cholinergic terminals, thalamocortical and corticocortical projections can evoke brief cholinergic release events. These acetylcholine (ACh) release events occur on a fast, sub-second to seconds-long time scale ('transients'). In rats performing a task requiring the detection of cues as well as the report of non-cue events cholinergic transients mediate the detection of cues specifically in trials that involve a shift from a state of monitoring for cues to cue-directed responding. Accordingly, ill-timed cholinergic transients, generated using optogenetic methods, force false detections in trials without cues. We propose that the evidence is consistent with the hypothesis that cholinergic transients reduce detection uncertainty in such trials. Furthermore, the evidence on the functions of the neuromodulatory component of cholinergic neurotransmission suggests that higher levels of neuromodulation favor staying-on-task over alternative action. In other terms, higher cholinergic neuromodulation reduces opportunity costs. Evidence indicating a similar integration of other ascending projection systems, including noradrenergic and serotonergic systems, into cortical circuitry remains sparse, largely because of the limited information about local presynaptic regulation and the limitations of current techniques in measuring fast and transient neurotransmitter release events in these systems.

Learning to ignore: a modeling study of a decremental cholinergic pathway and its influence on attention and learning

Learning to ignore irrelevant stimuli is essential to achieving efficient and fluid attention, and serves as the complement to increasing attention to relevant stimuli. The different cholinergic (ACh) subsystems within the basal forebrain regulate attention in distinct but complementary ways. ACh projections from the substantia innominata/nucleus basalis region (SI/nBM) to the neocortex are necessary to increase attention to relevant stimuli and have been well studied. Lesser known are ACh projections from the medial septum/vertical limb of the diagonal band (MS/VDB) to the hippocampus and the cingulate that are necessary to reduce attention to irrelevant stimuli. We developed a neural simulation to provide insight into how ACh can decrement attention using this distinct pathway from the MS/VDB. We tested the model in behavioral paradigms that require decremental attention. The model exhibits behavioral effects such as associative learning, latent inhibition, and persisting behavior. Lesioning the MS/VDB disrupts latent inhibition, and drastically increases perseverative behavior. Taken together, the model demonstrates that the ACh decremental pathway is necessary for appropriate learning and attention under dynamic circumstances and suggests a canonical neural architecture for decrementing attention.

Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network

Gamma frequency rhythms have been implicated in numerous studies for their role in healthy and abnormal brain function. The frequency band has been described to encompass as broad a range as 30-150 Hz. Crucial to understanding the role of gamma in brain function is an identification of the underlying neural mechanisms, which is particularly difficult in the absence of invasive recordings in macroscopic human signals such as those from magnetoencephalography (MEG) and electroencephalography (EEG). Here, we studied features of current dipole (CD) signals from two distinct mechanisms of gamma generation, using a computational model of a laminar cortical circuit designed specifically to simulate CDs in a biophysically principled manner (Jones et al., 2007, 2009). We simulated spiking pyramidal interneuronal gamma (PING) whose period is regulated by the decay time constant of GABAA-mediated synaptic inhibition and also subthreshold gamma driven by gamma-periodic exogenous excitatory synaptic drive. Our model predicts distinguishable CD features created by spiking PING compared to subthreshold driven gamma that can help to disambiguate mechanisms of gamma oscillations in human signals. We found that gamma rhythms in neocortical layer 5 can obscure a simultaneous, independent gamma in layer 2/3. Further, we arrived at a novel interpretation of the origin of high gamma frequency rhythms (100-150 Hz), showing that they emerged from a specific temporal feature of CDs associated with single cycles of PING activity and did not reflect a separate rhythmic process. Last we show that the emergence of observable subthreshold gamma required highly coherent exogenous drive. Our results are the first to demonstrate features of gamma oscillations in human current source signals that distinguish cellular and circuit level mechanisms of these rhythms and may help to guide understanding of their functional role.

Spatial and feature-based attention in a layered cortical microcircuit model

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception.

Mechanisms underlying the basal forebrain enhancement of top-down and bottom-up attention

Both attentional signals from frontal cortex and neuromodulatory signals from basal forebrain (BF) have been shown to influence information processing in the primary visual cortex (V1). These two systems exert complementary effects on their targets, including increasing firing rates and decreasing interneuronal correlations. Interestingly, experimental research suggests that the cholinergic system is important for increasing V1's sensitivity to both sensory and attentional information. To see how the BF and top-down attention act together to modulate sensory input, we developed a spiking neural network model of V1 and thalamus that incorporated cholinergic neuromodulation and top-down attention. In our model, activation of the BF had a broad effect that decreases the efficacy of top-down projections and increased the reliance of bottom-up sensory input. In contrast, we demonstrated how local release of acetylcholine in the visual cortex, which was triggered through top-down gluatmatergic projections, could enhance top-down attention with high spatial specificity. Our model matched experimental data showing that the BF and top-down attention decrease interneuronal correlations and increase between-trial reliability. We found that decreases in correlations were primarily between excitatory-inhibitory pairs rather than excitatory-excitatory pairs and suggest that excitatory-inhibitory decorrelation is necessary for maintaining low levels of excitatory-excitatory correlations. Increased inhibitory drive via release of acetylcholine in V1 may then act as a buffer, absorbing increases in excitatory-excitatory correlations that occur with attention and BF stimulation. These findings will lead to a better understanding of the mechanisms underyling the BF's interactions with attention signals and influences on correlations.

Experiencing your brain: neurofeedback as a new bridge between neuroscience and phenomenology

Neurophenomenology is a scientific research program aimed to combine neuroscience with phenomenology in order to study human experience. Nevertheless, despite several explicit implementations, the integration of first-person data into the experimental protocols of cognitive neuroscience still faces a number of epistemological and methodological challenges. Notably, the difficulties to simultaneously acquire phenomenological and neuroscientific data have limited its implementation into research projects. In our paper, we propose that neurofeedback paradigms, in which subjects learn to self-regulate their own neural activity, may offer a pragmatic way to integrate first-person and third-person descriptions. Here, information from first- and third-person perspectives is braided together in the iterative causal closed loop, creating experimental situations in which they reciprocally constrain each other. In real-time, the subject is not only actively involved in the process of data acquisition, but also assisted to directly influence the neural data through conscious experience. Thus, neurofeedback may help to gain a deeper phenomenological-physiological understanding of downward causations whereby conscious activities have direct causal effects on neuronal patterns. We discuss possible mechanisms that could mediate such effects and indicate a number of directions for future research.

Attention-induced variance and noise correlation reduction in macaque V1 is mediated by NMDA receptors

Attention improves perception by affecting different aspects of the neuronal code. It enhances firing rates, it reduces firing rate variability and noise correlations of neurons, and it alters the strength of oscillatory activity. Attention-induced rate enhancement in striate cortex requires cholinergic mechanisms. The neuropharmacological mechanisms responsible for attention-induced variance and noise correlation reduction or those supporting changes in oscillatory activity are unknown. We show that ionotropic glutamatergic receptor activation is required for attention-induced rate variance, noise correlation, and LFP gamma power reduction in macaque V1, but not for attention-induced rate modulations. NMDA receptors mediate attention-induced variance reduction and attention-induced noise correlation reduction. Our results demonstrate that attention improves sensory processing by a variety of mechanisms that are dissociable at the receptor level.