Acetylcholine in cortical inference

Frontal noradrenergic and cholinergic transients exhibit distinct spatiotemporal dynamics during competitive decision-making

Norepinephrine (NE) and acetylcholine (ACh) are neuromodulators that are crucial for learning and decision-making. In the cortex, NE and ACh are released at specific sites along neuromodulatory axons, which would constrain their spatiotemporal dynamics at the subcellular scale. However, how the fluctuating patterns of NE and ACh signaling may be linked to behavioral events is unknown. Here, leveraging genetically encoded NE and ACh indicators, we use two-photon microscopy to visualize neuromodulatory signals in the superficial layer of the mouse medial frontal cortex during decision-making. Head-fixed mice engage in a competitive game called matching pennies against a computer opponent. We show that both NE and ACh transients carry information about decision-related variables including choice, outcome, and reinforcer. However, the two neuromodulators differ in their spatiotemporal pattern of task-related activation. Spatially, NE signals are more segregated with choice and outcome encoded at distinct locations, whereas ACh signals can multiplex and reflect different behavioral correlates at the same site. Temporally, task-driven NE transients were more synchronized and peaked earlier than ACh transients. To test functional relevance, using optogenetics we found that evoked elevation of NE, but not ACh, in the medial frontal cortex increases the propensity of the animals to switch and explore alternate options. Taken together, the results reveal distinct spatiotemporal patterns of rapid ACh and NE transients at the subcellular scale during decision-making in mice, which may endow these neuromodulators with different ways to impact neural plasticity to mediate learning and adaptive behavior.

Acetylcholine modulates the precision of prediction error in the auditory cortex

A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

Explanatory power by vagueness. Challenges to the strong prior hypothesis on hallucinations exemplified by the Charles-Bonnet-Syndrome

Predictive processing models are often ascribed a certain generality in conceptually unifying the relationships between perception, action, and cognition or the potential to posit a 'grand unified theory' of the mind. The limitations of this unification can be seen when these models are applied to specific cognitive phenomena or phenomenal consciousness. Our article discusses these shortcomings for predictive processing models of hallucinations by the example of the Charles-Bonnet-Syndrome. This case study shows that the current predictive processing account omits essential characteristics of stimulus-independent perception in general, which has critical phenomenological implications. We argue that the most popular predictive processing model of hallucinatory conditions - the strong prior hypothesis - fails to fully account for the characteristics of nonveridical perceptual experiences associated with Charles-Bonnet-Syndrome. To fill this explanatory gap, we propose that the strong prior hypothesis needs to include reality monitoring to apply to more than just veridical percepts.

Potentiation of cholinergic and corticofugal inputs to the lateral amygdala in threat learning

The amygdala, cholinergic basal forebrain, and higher-order auditory cortex (HO-AC) regulate brain-wide plasticity underlying auditory threat learning. Here, we perform multi-regional extracellular recordings and optical measurements of acetylcholine (ACh) release to characterize the development of discriminative plasticity within and between these brain regions as mice acquire and recall auditory threat memories. Spiking responses are potentiated for sounds paired with shock (CS+) in the lateral amygdala (LA) and optogenetically identified corticoamygdalar projection neurons, although not in neighboring HO-AC units. Spike- or optogenetically triggered local field potentials reveal enhanced corticofugal-but not corticopetal-functional coupling between HO-AC and LA during threat memory recall that is correlated with pupil-indexed memory strength. We also note robust sound-evoked ACh release that rapidly potentiates for the CS+ in LA but habituates across sessions in HO-AC. These findings highlight a distributed and cooperative plasticity in LA inputs as mice learn to reappraise neutral stimuli as possible threats.

Turning the Spotlight to Cholinergic Pharmacotherapy of the Human Language System

Even though language is essential in human communication, research on pharmacological therapies for language deficits in highly prevalent neurodegenerative and vascular brain diseases has received little attention. Emerging scientific evidence suggests that disruption of the cholinergic system may play an essential role in language deficits associated with Alzheimer's disease and vascular cognitive impairment, including post-stroke aphasia. Therefore, current models of cognitive processing are beginning to appraise the implications of the brain modulator acetylcholine in human language functions. Future work should be directed further to analyze the interplay between the cholinergic system and language, focusing on identifying brain regions receiving cholinergic innervation susceptible to modulation with pharmacotherapy to improve affected language domains. The evaluation of language deficits in pharmacological cholinergic trials for Alzheimer's disease and vascular cognitive impairment has thus far been limited to coarse-grained methods. More precise, fine-grained language testing is needed to refine patient selection for pharmacotherapy to detect subtle deficits in the initial phases of cognitive decline. Additionally, noninvasive biomarkers can help identify cholinergic depletion. However, despite the investigation of cholinergic treatment for language deficits in Alzheimer's disease and vascular cognitive impairment, data on its effectiveness are insufficient and controversial. In the case of post-stroke aphasia, cholinergic agents are showing promise, particularly when combined with speech-language therapy to promote trained-dependent neural plasticity. Future research should explore the potential benefits of cholinergic pharmacotherapy in language deficits and investigate optimal strategies for combining these agents with other therapeutic approaches.

Computational psychiatry: from synapses to sentience

This review considers computational psychiatry from a particular viewpoint: namely, a commitment to explaining psychopathology in terms of pathophysiology. It rests on the notion of a generative model as underwriting (i) sentient processing in the brain, and (ii) the scientific process in psychiatry. The story starts with a view of the brain-from cognitive and computational neuroscience-as an organ of inference and prediction. This offers a formal description of neuronal message passing, distributed processing and belief propagation in neuronal networks; and how certain kinds of dysconnection lead to aberrant belief updating and false inference. The dysconnections in question can be read as a pernicious synaptopathy that fits comfortably with formal notions of how we-or our brains-encode uncertainty or its complement, precision. It then considers how the ensuing process theories are tested empirically, with an emphasis on the computational modelling of neuronal circuits and synaptic gain control that mediates attentional set, active inference, learning and planning. The opportunities afforded by this sort of modelling are considered in light of in silico experiments; namely, computational neuropsychology, computational phenotyping and the promises of a computational nosology for psychiatry. The resulting survey of computational approaches is not scholarly or exhaustive. Rather, its aim is to review a theoretical narrative that is emerging across subdisciplines within psychiatry and empirical scales of investigation. These range from epilepsy research to neurodegenerative disorders; from post-traumatic stress disorder to the management of chronic pain, from schizophrenia to functional medical symptoms.

Sometimes I feel the fear of uncertainty: How intolerance of uncertainty and trait anxiety impact fear acquisition, extinction and the return of fear

It is hypothesized that the ability to discriminate between threat and safety is impaired in individuals with high dispositional negativity, resulting in maladaptive behavior. A large body of research investigated differential learning during fear conditioning and extinction protocols depending on individual differences in intolerance of uncertainty (IU) and trait anxiety (TA), two closely-related dimensions of dispositional negativity, with heterogenous results. These might be due to varying degrees of induced threat/safety uncertainty. Here, we compared two groups with high vs. low IU/TA during periods of low (instructed fear acquisition) and high levels of uncertainty (delayed non-instructed extinction training and reinstatement). Dependent variables comprised subjective (US expectancy, valence, arousal), psychophysiological (skin conductance response, SCR, and startle blink), and neural (fMRI BOLD) measures of threat responding. During fear acquisition, we found strong threat/safety discrimination for both groups. During early extinction (high uncertainty), the low IU/TA group showed an increased physiological response to the safety signal, resulting in a lack of CS discrimination. In contrast, the high IU/TA group showed strong initial threat/safety discrimination in physiology, lacking discriminative learning on startle, and reduced neural activation in regions linked to threat/safety processing throughout extinction training indicating sustained but non-adaptive and rigid responding. Similar neural patterns were found after the reinstatement test. Taken together, we provide evidence that high dispositional negativity, as indicated here by IU and TA, is associated with greater responding to threat cues during the beginning of delayed extinction, and, thus, demonstrates altered learning patterns under changing environments.

Outcome-Locked Cholinergic Signaling Suppresses Prefrontal Encoding of Stimulus Associations

Acetylcholine (ACh) is thought to control arousal, attention, and learning by slowly modulating cortical excitability and plasticity. Recent studies, however, discovered that cholinergic neurons emit precisely timed signals about the aversive outcome at millisecond precision. To investigate the functional relevance of such phasic cholinergic signaling, we manipulated and monitored cholinergic terminals in the mPFC while male mice associated a neutral conditioned stimulus (CS) with mildly aversive eyelid shock (US) over a short temporal gap. Optogenetic inhibition of cholinergic terminals during the US promoted the formation of the CS-US association. On the contrary, optogenetic excitation of cholinergic terminals during the US blocked the association formation. The bidirectional behavioral effects paralleled the corresponding change in the expression of an activity-regulated gene, c-Fos in the mPFC. In contrast, optogenetic inhibition of cholinergic terminals during the CS impaired associative learning, whereas their excitation had marginal effects. In parallel, photometric recording from cholinergic terminals in the mPFC revealed strong innate phasic responses to the US. With subsequent CS-US pairings, cholinergic terminals weakened the responses to the US while developing strong responses to the CS. The across-session changes in the CS- and US-evoked terminal responses were correlated with associative memory strength. These findings suggest that phasic cholinergic signaling in the mPFC exerts opposite effects on aversive associative learning depending on whether it is emitted by the outcome or the cue.SIGNIFICANCE STATEMENT Drugs compensating for the decline of acetylcholine (ACh) are used for cognitive impairment, such as Alzheimer's disease. However, their beneficial effects are limited, demanding new strategies based on better understandings of how ACh modulates cognition. Here, we report that by manipulating ACh signals in the mPFC, we can control the strength of aversive associative learning in mice. Specifically, the suppression of ACh signals during an aversive outcome facilitated its association with a preceding cue. In contrast, the suppression of ACh signals during the cue impaired learning. Considering that this paradigm depends on the brain regions affected in Alzheimer's disease, our findings indicate that precisely timed control of ACh signals is essential to refine ACh-based strategies for cognitive enhancement.

Imagine that: cholinesterase inhibitor treatment of complex visual hallucinations of unknown aetiology

Introduction: Our objective is to highlight the value of the neurophenomenological classification of complex visual hallucinations (VHs). This approach enabled the authors to successfully treat VHs of uncertain aetiology with cholinesterase inhibitors because the content of the hallucinations suggested dysfunction in cholinergic modulated networks.Methods: We utilise the single case report to describe the nature and content of chronic VHs experienced by a 49-year-old woman following a prolonged admission to ITU. Despite extensive investigation, no clear cause was identified for these hallucinations and the patient did not respond to rationalisation of medications or trials of antipsychotics. We therefore adopted the neurophenomenological approach to classifying and treating her VHs.Results: After several years of distressing visual hallucinations, a course of Rivastigmine was trialed despite no evidence suggestive of a Parkinsonian syndrome. Nevertheless, the patient reported a dose-effect response with significant reduction in the frequency and intensity of her hallucinations, almost to complete resolution.Conclusions: At present there is limited evidence about the medical management of visual hallucinations. This case report suggests that cholinesterase inhibitors may be of benefit, even in the absence of clear parkinsonsian features, if the form and content of the VHs suggest dysfunction in cholinergic modulated attentional networks.

Multiscale representations of community structures in attractor neural networks

Our cognition relies on the ability of the brain to segment hierarchically structured events on multiple scales. Recent evidence suggests that the brain performs this event segmentation based on the structure of state-transition graphs behind sequential experiences. However, the underlying circuit mechanisms are poorly understood. In this paper we propose an extended attractor network model for graph-based hierarchical computation which we call the Laplacian associative memory. This model generates multiscale representations for communities (clusters) of associative links between memory items, and the scale is regulated by the heterogenous modulation of inhibitory circuits. We analytically and numerically show that these representations correspond to graph Laplacian eigenvectors, a popular method for graph segmentation and dimensionality reduction. Finally, we demonstrate that our model exhibits chunked sequential activity patterns resembling hippocampal theta sequences. Our model connects graph theory and attractor dynamics to provide a biologically plausible mechanism for abstraction in the brain.

Our experiences are often hierarchically organized, so is our knowledge. Identifying meaningful segments in hierarchically structured information is crucial for many cognitive functions including visual, auditory, motor, memory, language processing, and reasoning. Herein, we show that the attractor dynamics of recurrent neural circuits offer a biologically plausible way for hierarchical segmentation. We found that an extended model of associative memory autonomously performs segmentation by finding groups of tightly linked memories. We proved that the neural dynamics of our model mathematically coincide with optimal graph segmentation in graph theory and are consistent with the experimentally observed nature of human behaviors and neural activities. Our model established a previously unexpected relationship between attractor neural networks and the graph-theoretic processing of knowledge structures. Our model also provides experimentally testable predictions, particularly regarding the role of inhibitory circuits in controlling representational granularity.

Evidence and implications of abnormal predictive coding in dementia

The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of ‘memory centres’ or ‘language centres’, or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding framework may therefore also inform future therapeutic strategies.

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.

Leveraging Basic Science for the Clinic-From Bench to Bedside

IMPORTANCE

The tools and insights of behavioral neuroscience grow apace, yet their clinical application is lagging.

OBSERVATIONS

This article suggests that associative learning theory may be the algorithmic bridge to connect a burgeoning understanding of the brain with the challenges to the mind with which all clinicians and researchers are concerned.

CONCLUSIONS AND RELEVANCE

Instead of giving up, talking past one another, or resting on the laurels of face validity, a consilient and collaborative approach is suggested: visiting laboratory meetings and clinical rounds and attempting to converse in the language of behavior and cognition to better understand and ultimately treat patients.

Green D. Neuromodulatory Control and Language Recovery in Bilingual Aphasia: An Active Inference Approach

Understanding the aetiology of the diverse recovery patterns in bilingual aphasia is a theoretical challenge with implications for treatment. Loss of control over intact language networks provides a parsimonious starting point that can be tested using in-silico lesions. We simulated a complex recovery pattern (alternate antagonism and paradoxical translation) to test the hypothesis-from an established hierarchical control model-that loss of control was mediated by constraints on neuromodulatory resources. We used active (Bayesian) inference to simulate a selective loss of sensory precision; i.e., confidence in the causes of sensations. This in-silico lesion altered the precision of beliefs about task relevant states, including appropriate actions, and reproduced exactly the recovery pattern of interest. As sensory precision has been linked to acetylcholine release, these simulations endorse the conjecture that loss of neuromodulatory control can explain this atypical recovery pattern. We discuss the relevance of this finding for other recovery patterns.

Experience enhances certainty about olfactory stimuli under bulbar cholinergic control

We present evidence that experience and cholinergic modulation in an early sensory network interact to improve certainty about olfactory stimuli. The data we present are in agreement with existing theoretical ideas about the functional role of acetylcholine but highlight the importance of early sensory networks in addition to cortical networks. We use a simple behavioral paradigm in mice which allows us to measure certainty about a stimulus via the response amplitude to a condition and novel stimuli. We conclude that additional learning increases certainty and that the slope of this relationship can be modulated by activation of muscarinic cholinergic receptors in the olfactory bulb.

Forebrain Cholinergic Signaling: Wired and Phasic, Not Tonic, and Causing Behavior

Conceptualizations of cholinergic signaling as primarily spatially diffuse and slow-acting are based largely on measures of extracellular brain ACh levels that require several minutes to generate a single data point. In addition, most such studies inhibited the highly potent catalytic enzyme for ACh, AChE, to facilitate measurement of ACh. Absent such inhibition, AChE limits the presence of ambient ACh and thus renders it unlikely that ACh influences target regions via slow changes in extracellular ACh concentrations. We describe an alternative view by which forebrain signaling in cortex driving cognition is largely phasic (milliseconds to perhaps seconds), and unlikely to be volume-transmitted. This alternative is supported by new evidence from real-time amperometric recordings of cholinergic signaling indicating a specific function of rapid, phasic, transient cholinergic signaling in attentional contexts. Previous neurochemical evidence may be reinterpreted in terms of integrated phasic cholinergic activity that mediates specific behavioral and cognitive operations; this reinterpretation fits well with recent computational models. Optogenetic studies support a causal relationship between cholinergic transients and behavior. This occurs in part via transient-evoked muscarinic receptor-mediated high-frequency oscillations in cortical regions. Such oscillations outlast cholinergic transients and thus link transient ACh signaling with more sustained postsynaptic activity patterns to support relatively persistent attentional biases. Reconceptualizing cholinergic function as spatially specific, phasic, and modulating specific cognitive operations is theoretically powerful and may lead to pharmacologic treatments more effective than those based on traditional views.Dual Perspectives Companion Paper: Diverse Spatiotemporal Scales of Cholinergic Signaling in the Neocortex, by Anita A. Disney and Michael J. Higley.

Role of the Thalamus in Basal Forebrain Regulation of Neural Activity in the Primary Auditory Cortex

Many studies have implicated the basal forebrain (BF) as a potent regulator of sensory encoding even at the earliest stages of or cortical processing. The source of this regulation involves the well-documented corticopetal cholinergic projections from BF to primary cortical areas. However, the BF also projects to subcortical structures, including the thalamic reticular nucleus (TRN), which has abundant reciprocal connections with sensory thalamus. Here we present naturalistic auditory stimuli to the anesthetized rat while making simultaneous single-unit recordings from the ventral medial geniculate nucleus (MGN) and primary auditory cortex (A1) during electrical stimulation of the BF. Like primary visual cortex, we find that BF stimulation increases the trial-to-trial reliability of A1 neurons, and we relate these results to change in the response properties of MGN neurons. We discuss several lines of evidence that implicate the BF to thalamus pathway in the manifestation of BF-induced changes to cortical sensory processing and support our conclusions with supplementary TRN recordings, as well as studies in awake animals showing a strong relationship between endogenous BF activity and A1 reliability. Our findings suggest that the BF subcortical projections that modulate MGN play an important role in auditory processing.

The role of nicotinic cholinergic neurotransmission in delusional thinking

Delusions are a difficult-to-treat and intellectually fascinating aspect of many psychiatric illnesses. Although scientific progress on this complex topic has been challenging, some recent advances focus on dysfunction in neural circuits, specifically in those involving dopaminergic and glutamatergic neurotransmission. Here we review the role of cholinergic neurotransmission in delusions, with a focus on nicotinic receptors, which are known to play a part in some illnesses where these symptoms appear, including delirium, schizophrenia spectrum disorders, bipolar disorder, Parkinson, Huntington, and Alzheimer diseases. Beginning with what we know about the emergence of delusions in these illnesses, we advance a hypothesis of cholinergic disturbance in the dorsal striatum where nicotinic receptors are operative. Striosomes are proposed to play a central role in the formation of delusions. This hypothesis is consistent with our current knowledge about the mechanism of action of cholinergic drugs and with our abstract models of basic cognitive mechanisms at the molecular and circuit levels. We conclude by pointing out the need for further research both at the clinical and translational levels.

Impaired context-sensitive adjustment of behaviour in Parkinson's disease patients tested on and off medication: An fMRI study

The brain's sensitivity to and accentuation of unpredicted over predicted sensory signals plays a fundamental role in learning. According to recent theoretical models of the predictive coding framework, dopamine is responsible for balancing the interplay between bottom-up input and top-down predictions by controlling the precision of surprise signals that guide learning. Using functional MRI, we investigated whether patients with Parkinson's disease (PD) show impaired learning from prediction errors requiring either adaptation or stabilisation of current predictions. Moreover, we were interested in whether deficits in learning over a specific time scale would be accompanied by altered surprise responses in dopamine-related brain structures. To this end, twenty-one PD patients tested on and off dopaminergic medication and twenty-one healthy controls performed a digit prediction paradigm. During the task, violations of sequence-based predictions either signalled the need to update or to stabilise the current prediction and, thus, to react to them or ignore them, respectively. To investigate contextual adaptation to prediction errors, the probability (or its inverse, surprise) of the violations fluctuated across the experiment. When the probability of prediction errors over a specific time scale increased, healthy controls but not PD patients off medication became more flexible, i.e., error rates at violations requiring a motor response decreased in controls but increased in patients. On the neural level, this learning deficit in patients was accompanied by reduced signalling in the substantia nigra and the caudate nucleus. In contrast, differences between the groups regarding the probabilistic modulation of behaviour and neural responses were much less pronounced at prediction errors requiring only stabilisation but no adaptation. Interestingly, dopaminergic medication could neither improve learning from prediction errors nor restore the physiological, neurotypical pattern. Our findings point to a pivotal role of dysfunctions of the substantia nigra and caudate nucleus in deficits in learning from flexibility-demanding prediction errors in PD. Moreover, the data witness poor effects of dopaminergic medication on learning in PD.

Separable gain control of ongoing and evoked activity in the visual cortex by serotonergic input

Controlling gain of cortical activity is essential to modulate weights between internal ongoing communication and external sensory drive. Here, we show that serotonergic input has separable suppressive effects on the gain of ongoing and evoked visual activity. We combined optogenetic stimulation of the dorsal raphe nucleus (DRN) with wide-field calcium imaging, extracellular recordings, and iontophoresis of serotonin (5-HT) receptor antagonists in the mouse visual cortex. 5-HT1A receptors promote divisive suppression of spontaneous activity, while 5-HT2A receptors act divisively on visual response gain and largely account for normalization of population responses over a range of visual contrasts in awake and anesthetized states. Thus, 5-HT input provides balanced but distinct suppressive effects on ongoing and evoked activity components across neuronal populations. Imbalanced 5-HT1A/2A activation, either through receptor-specific drug intake, genetically predisposed irregular 5-HT receptor density, or change in sensory bombardment may enhance internal broadcasts and reduce sensory drive and vice versa.

An integrative framework for perceptual disturbances in psychosis

Perceptual disturbances in psychosis, such as auditory verbal hallucinations, are associated with increased baseline activity in the associative auditory cortex and increased dopamine transmission in the associative striatum. Perceptual disturbances are also associated with perceptual biases that suggest increased reliance on prior expectations. We review theoretical models of perceptual inference and key supporting physiological evidence, as well as the anatomy of associative cortico-striatal loops that may be relevant to auditory perceptual inference. Integrating recent findings, we outline a working framework that bridges neurobiology and the phenomenology of perceptual disturbances via theoretical models of perceptual inference.

Visual hallucinations in Alzheimer's disease do not seem to be associated with chronic hypoperfusion of to visual processing areas V2 and V3 but may be associated with reduced cholinergic input to these areas

Background

Up to 20% of patients with AD experience hallucinations. The pathological substrate is not known. Visual hallucinations (VH) are more common in dementia with Lewy bodies (DLB). In autopsy studies, up to 60% of patients with AD have concomitant Lewy body pathology. Decreased perfusion of the occipital lobe has been implicated in DLB patients with VH, and post-mortem studies point to both decreased cholinergic activity and reduced oxygenation of the occipital cortex in DLB.

Methods

We used biochemical methods to assess microvessel density (level of von Willebrand factor, a marker of endothelial cell content), ante-mortem oxygenation (vascular endothelial growth factor, a marker of tissue hypoxia; myelin-associated glycoprotein to proteolipid protein-1 ratio, a measure of tissue oxygenation relative to metabolic demand), cholinergic innervation (acetylcholinesterase and choline acetyltransferase), butyrylcholinesterase and insoluble α-synuclein content in the BA18 and BA19 occipital cortex obtained post-mortem from 23 AD patients who had experienced visual hallucinations, 19 AD patients without hallucinations, 19 DLB patients, and 36 controls. The cohorts were matched for age, gender and post-mortem interval.

Results

There was no evidence of reduced microvessel density, hypoperfusion or reduction in ChAT activity in AD with visual hallucinations. Acetylcholinesterase activity was reduced in both BA18 and BA19, in all 3 dementia groups, and the concentration was also reduced in BA19 in the DLB and AD without visual hallucinations groups. Insoluble α-synuclein was raised in the DLB group in both areas but not in AD either with or without visual hallucinations.

Conclusions

Our results suggest that visual hallucinations in AD are associated with cholinergic denervation rather than chronic hypoperfusion or α-synuclein accumulation in visual processing areas of the occipital cortex.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0519-7) contains supplementary material, which is available to authorized users.

Extended Temporal Association Memory by Modulations of Inhibitory Circuits

Hebbian learning of excitatory synapses plays a central role in storing activity patterns in associative memory models. Interstimulus Hebbian learning associates multiple items by converting temporal correlation to spatial correlation between attractors. Growing evidence suggests the importance of inhibitory plasticity in memory processing, but the consequence of such regulation in associative memory has not been understood. Noting that Hebbian learning of inhibitory synapses yields an anti-Hebbian effect, we show that the combination of Hebbian and anti-Hebbian learning can significantly increase the span of temporal association between correlated attractors as well as the sensitivity of these states to external input. Furthermore, these effects are regulated by changing the ratio of local and global recurrent inhibition after learning weights for excitation-inhibition balance. Our results suggest a nontrivial role of plasticity and modulation of inhibitory circuits in associative memory.

REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics

This paper formulates the action of psychedelics by integrating the free-energy principle and entropic brain hypothesis. We call this formulation relaxed beliefs under psychedelics (REBUS) and the anarchic brain, founded on the principle that-via their entropic effect on spontaneous cortical activity-psychedelics work to relax the precision of high-level priors or beliefs, thereby liberating bottom-up information flow, particularly via intrinsic sources such as the limbic system. We assemble evidence for this model and show how it can explain a broad range of phenomena associated with the psychedelic experience. With regard to their potential therapeutic use, we propose that psychedelics work to relax the precision weighting of pathologically overweighted priors underpinning various expressions of mental illness. We propose that this process entails an increased sensitization of high-level priors to bottom-up signaling (stemming from intrinsic sources), and that this heightened sensitivity enables the potential revision and deweighting of overweighted priors. We end by discussing further implications of the model, such as that psychedelics can bring about the revision of other heavily weighted high-level priors, not directly related to mental health, such as those underlying partisan and/or overly-confident political, religious, and/or philosophical perspectives. SIGNIFICANCE STATEMENT: Psychedelics are capturing interest, with efforts underway to bring psilocybin therapy to marketing authorisation and legal access within a decade, spearheaded by the findings of a series of phase 2 trials. In this climate, a compelling unified model of how psychedelics alter brain function to alter consciousness would have appeal. Towards this end, we have sought to integrate a leading model of global brain function, hierarchical predictive coding, with an often-cited model of the acute action of psychedelics, the entropic brain hypothesis. The resulting synthesis states that psychedelics work to relax high-level priors, sensitising them to liberated bottom-up information flow, which, with the right intention, care provision and context, can help guide and cultivate the revision of entrenched pathological priors.

Visual hallucinations, thalamocortical physiology and Lewy body disease: A review

One of the core diagnostic criteria for Dementia with Lewy Bodies (DLB) is the presence of visual hallucinations. The presence of hallucinations, along with fluctuations in the level of arousal and sleep disturbance, point to potential pathological mechanisms at the level of the thalamus. However, the potential role of thalamic dysfunction in DLB, particularly as it relates to the presence of formed visual hallucinations is not known. Here, we review the literature on the pathophysiology of DLB with respect to modern theories of thalamocortical function and attempt to derive an understanding of how such hallucinations arise. Based on the available literature, we propose that combined thalamic-thalamic reticular nucleus and thalamocortical pathology may explain the phenomenology of visual hallucinations in DLB. In particular, diminished α7 cholinergic activity in the thalamic reticular nucleus may critically disinhibit thalamocortical activity. Further, concentrated pathological changes within the posterior regions of the thalamus may explain the predilection for the hallucinations to be visual in nature.

Neuronal message passing using Mean-field, Bethe, and Marginal approximations

Neuronal computations rely upon local interactions across synapses. For a neuronal network to perform inference, it must integrate information from locally computed messages that are propagated among elements of that network. We review the form of two popular (Bayesian) message passing schemes and consider their plausibility as descriptions of inference in biological networks. These are variational message passing and belief propagation - each of which is derived from a free energy functional that relies upon different approximations (mean-field and Bethe respectively). We begin with an overview of these schemes and illustrate the form of the messages required to perform inference using Hidden Markov Models as generative models. Throughout, we use factor graphs to show the form of the generative models and of the messages they entail. We consider how these messages might manifest neuronally and simulate the inferences they perform. While variational message passing offers a simple and neuronally plausible architecture, it falls short of the inferential performance of belief propagation. In contrast, belief propagation allows exact computation of marginal posteriors at the expense of the architectural simplicity of variational message passing. As a compromise between these two extremes, we offer a third approach - marginal message passing - that features a simple architecture, while approximating the performance of belief propagation. Finally, we link formal considerations to accounts of neurological and psychiatric syndromes in terms of aberrant message passing.

Regulation of cholinergic basal forebrain development, connectivity, and function by neurotrophin receptors

Cholinergic basal forebrain (cBF) neurons are defined by their expression of the p75 neurotrophin receptor (p75^NTR) and tropomyosin-related kinase (Trk) neurotrophin receptors in addition to cholinergic markers. It is known that the neurotrophins, particularly nerve growth factor (NGF), mediate cholinergic neuronal development and maintenance. However, the role of neurotrophin signalling in regulating adult cBF function is less clear, although in dementia, trophic signalling is reduced and p75^NTR mediates neurodegeneration of cBF neurons. Here we review the current understanding of how cBF neurons are regulated by neurotrophins which activate p75^NTR and TrkA, B or C to influence the critical role that these neurons play in normal cortical function, particularly higher order cognition. Specifically, we describe the current evidence that neurotrophins regulate the development of basal forebrain neurons and their role in maintaining and modifying mature basal forebrain synaptic and cortical microcircuit connectivity. Understanding the role neurotrophin signalling plays in regulating the precision of cholinergic connectivity will contribute to the understanding of normal cognitive processes and will likely provide additional ideas for designing improved therapies for the treatment of neurological disease in which cholinergic dysfunction has been demonstrated.

Forget-me-some: General versus special purpose models in a hierarchical probabilistic task

Humans build models of their environments and act according to what they have learnt. In simple experimental environments, such model-based behaviour is often well accounted for as if subjects are ideal Bayesian observers. However, more complex probabilistic tasks require more sophisticated forms of inference that are sufficiently computationally and statistically taxing as to demand approximation. Here, we study properties of two approximation schemes in the context of a serial reaction time task in which stimuli were generated from a hierarchical Markov chain. One, pre-existing, scheme was a generically powerful variational method for hierarchical inference which has recently become popular as an account of psychological and neural data across a wide swathe of probabilistic tasks. A second, novel, scheme was more specifically tailored to the task at hand. We show that the latter model fit significantly better than the former. This suggests that our subjects were sensitive to many of the particular constraints of a complex behavioural task. Further, the tailored model provided a different perspective on the effects of cholinergic manipulations in the task. Neither model fit the behaviour on more complex contingencies that competently. These results illustrate the benefits and challenges that come with the general and special purpose modelling approaches and raise important questions of how they can advance our current understanding of learning mechanisms in the brain.

Attention or salience?

While attention is widely recognised as central to perception, the term is often used to mean very different things. Prominent theories of attention - notably the premotor theory - relate it to planned or executed eye movements. This contrasts with the notion of attention as a gain control process that weights the information carried by different sensory channels. We draw upon recent advances in theoretical neurobiology to argue for a distinction between attentional gain mechanisms and salience attribution. The former depends upon estimating the precision of sensory data, while the latter is a consequence of the need to actively engage with the sensorium. Having established this distinction, we consider the intimate relationship between attention and salience.

Precision and False Perceptual Inference

Accurate perceptual inference fundamentally depends upon accurate beliefs about the reliability of sensory data. In this paper, we describe a Bayes optimal and biologically plausible scheme that refines these beliefs through a gradient descent on variational free energy. To illustrate this, we simulate belief updating during visual foraging and show that changes in estimated sensory precision (i.e., confidence in visual data) are highly sensitive to prior beliefs about the contents of a visual scene. In brief, confident prior beliefs induce an increase in estimated precision when consistent with sensory evidence, but a decrease when they conflict. Prior beliefs held with low confidence are rapidly updated to posterior beliefs, determined by sensory data. These induce much smaller changes in beliefs about sensory precision. We argue that pathologies of scene construction may be due to abnormal priors, and show that these can induce a reduction in estimated sensory precision. Having previously associated this precision with cholinergic signaling, we note that several neurodegenerative conditions are associated with visual disturbances and cholinergic deficits; notably, the synucleinopathies. On relating the message passing in our model to the functional anatomy of the ventral visual stream, we find that simulated neuronal loss in temporal lobe regions induces confident, inaccurate, empirical prior beliefs at lower levels in the visual hierarchy. This provides a plausible, if speculative, computational mechanism for the loss of cholinergic signaling and the visual disturbances associated with temporal lobe Lewy body pathology. This may be seen as an illustration of the sorts of hypotheses that may be expressed within this computational framework.

Noradrenergic and Cholinergic Modulation of Belief Updating

To make optimal predictions in a dynamic environment, the impact of new observations on existing beliefs-that is, the learning rate-should be guided by ongoing estimates of change and uncertainty. Theoretical work has proposed specific computational roles for various neuromodulatory systems in the control of learning rate, but empirical evidence is still sparse. The aim of the current research was to examine the role of the noradrenergic and cholinergic systems in learning rate regulation. First, we replicated our recent findings that the centroparietal P3 component of the EEG-an index of phasic catecholamine release in the cortex-predicts trial-to-trial variability in learning rate and mediates the effects of surprise and belief uncertainty on learning rate (Study 1, n = 17). Second, we found that pharmacological suppression of either norepinephrine or acetylcholine activity produced baseline-dependent effects on learning rate following nonobvious changes in an outcome-generating process (Study 1). Third, we identified two genes, coding for α2A receptor sensitivity (ADRA2A) and norepinephrine reuptake (NET), as promising targets for future research on the genetic basis of individual differences in learning rate (Study 2, n = 137). Our findings suggest a role for the noradrenergic and cholinergic systems in belief updating and underline the importance of studying interactions between different neuromodulatory systems.

Uncertainty, epistemics and active inference

Biological systems—like ourselves—are constantly faced with uncertainty. Despite noisy sensory data, and volatile environments, creatures appear to actively maintain their integrity. To account for this remarkable ability to make optimal decisions in the face of a capricious world, we propose a generative model that represents the beliefs an agent might possess about their own uncertainty. By simulating a noisy and volatile environment, we demonstrate how uncertainty influences optimal epistemic (visual) foraging. In our simulations, saccades were deployed less frequently to regions with a lower sensory precision, while a greater volatility led to a shorter inhibition of return. These simulations illustrate a principled explanation for some cardinal aspects of visual foraging—and allow us to propose a correspondence between the representation of uncertainty and ascending neuromodulatory systems, complementing that suggested by Yu & Dayan (Yu & Dayan 2005 Neuron46, 681–692. (doi:10.1016/j.neuron.2005.04.026)).

A probabilistic, distributed, recursive mechanism for decision-making in the brain

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics.

Decision-making is central to cognition. Abnormally-formed decisions characterize disorders like over-eating, Parkinson’s and Huntington’s diseases, OCD, addiction, and compulsive gambling. Yet, a unified account of decision-making has, hitherto, remained elusive. Here we show the essential composition of the brain’s decision mechanism by matching experimental data from monkeys making decisions, to the knowable function of a novel statistical inference algorithm. Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain, replicating the monkeys’ choice behaviour and the dynamics of the neural activity that accompany it. Validated in this way, our algorithm establishes a basic framework for understanding the mechanistic ingredients of decision-making in the brain, and thereby, a basic platform for understanding how pathologies arise from abnormal function.

Computational Neuropsychology and Bayesian Inference

Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine ‘prior’ beliefs with a generative (predictive) model to explain the causes of sensations. Under this view, neuropsychological deficits can be thought of as false inferences that arise due to aberrant prior beliefs (that are poor fits to the real world). This draws upon the notion of a Bayes optimal pathology – optimal inference with suboptimal priors – and provides a means for computational phenotyping. In principle, any given neuropsychological disorder could be characterized by the set of prior beliefs that would make a patient’s behavior appear Bayes optimal. We start with an overview of some key theoretical constructs and use these to motivate a form of computational neuropsychology that relates anatomical structures in the brain to the computations they perform. Throughout, we draw upon computational accounts of neuropsychological syndromes. These are selected to emphasize the key features of a Bayesian approach, and the possible types of pathological prior that may be present. They range from visual neglect through hallucinations to autism. Through these illustrative examples, we review the use of Bayesian approaches to understand the link between biology and computation that is at the heart of neuropsychology.

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.

Prioritization to visual objects: Roles of sensory uncertainty

Two hypotheses, attentional prioritization and attentional spreading, have been proposed to account for object-based attention. The attentional-prioritization hypothesis posits that the positional uncertainty of targets is sufficient to resolve the controversy raised by the competing attentional-spreading hypothesis. Here we challenge the sufficiency of this explanation by showing that object-based attention is a function of sensory uncertainty in a task with consistent high positional uncertainty of the targets. In Experiment 1, object-based attention was modulated by sensory uncertainty induced by the noise from backward masking, showing an object-based effect under high as compared to low sensory uncertainty. This finding was replicated in Experiment 2 with increased task difficulty, to exclude that as a confounding factor, and in Experiment 3 with a psychophysical method, to obtain converging evidence using perceptual threshold measurement. Additionally, such a finding was not observed when sensory uncertainty was eliminated by replacing the backward-masking stimuli with perceptually dissimilar ones in Experiment 4. These results reveal that object-based attention is influenced by sensory uncertainty, even under high positional uncertainty of the targets. Our findings contradict the proposition of attentional spreading, proposing instead an automatic form of object-based attention due to enhancement of the perceptual representation. More importantly, the attentional-prioritization hypothesis based solely on positional uncertainty cannot sufficiently account for object-based attention, but needs to be developed by expanding the concept of uncertainty to include at least sensory uncertainty.

A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder

The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions-predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top-down predictions or an enhanced weighting of bottom-up prediction errors. Likewise, autism has been explained in terms of similar perturbations. We suggest that this theoretical overlap may explain overlapping symptomatology. Experimental evidence highlights meaningful distinctions and consistencies between these disorders. We hypothesize individuals with ASD may experience some degree of delusions without the presence of any additional impairment, but that hallucinations are likely indicative of a distinct process.

Effects of M1 and M4 activation on excitatory synaptic transmission in CA1

Hippocampal networks are particularly susceptible to dysfunction in many neurodegenerative diseases and neuropsychiatric disorders including Alzheimer's disease, Lewy body dementia, and schizophrenia. CA1, a major output region of the hippocampus, receives glutamatergic input from both hippocampal CA3 and entorhinal cortex, via the Schaffer collateral (SC) and temporoammonic (TA) pathways, respectively. SC and TA inputs to CA1 are thought to be differentially involved in the retrieval of previously stored memories versus the encoding of novel information, and switching between these two crucial hippocampal functions is thought to critically depend on acetylcholine (ACh) acting at muscarinic receptors. In this study, we aimed to determine the roles of specific subtypes of muscarinic receptors in mediating the neuromodulatory effects of ACh on glutamatergic synaptic transmission in the SC and TA pathways of CA1. Using selective pharmacological activation of M1 or M4 receptors along with extracellular and intracellular electrophysiology recordings from adult rat hippocampal slices, we demonstrate that activation of M1 receptors increases spontaneous spike rates of neuronal ensembles in CA1 and increases the intrinsic excitability of pyramidal neurons and interneurons. Selective activation of M4 receptors inhibits glutamate release in the SC pathway, while leaving synaptic transmission in the TA pathway comparatively intact. These results suggest specific mechanisms by which M1 and M4 activation may normalize CA1 circuit activity following disruptions of signaling that accompany neurodegenerative dementias or neuropsychiatric disorders. These findings are of particular interest in light of clinical findings that xanomeline, an M1/M4 preferring agonist, was able to improve cognitive and behavioral symptoms in patients with Alzheimer's disease or schizophrenia.

Aging-Related Dysfunction of Striatal Cholinergic Interneurons Produces Conflict in Action Selection

For goal-directed action to remain adaptive, new strategies are required to accommodate environmental changes, a process for which parafascicular thalamic modulation of cholinergic interneurons in the striatum (PF-to-CIN) appears critical. In the elderly, however, previously acquired experience frequently interferes with new learning, yet the source of this effect has remained unexplored. Here, combining sophisticated behavioral designs, cell-specific manipulation, and extensive neuronal imaging, we investigated the involvement of the PF-to-CIN pathway in this process. We found functional alterations of this circuit in aged mice that were consistent with their incapacity to update initial goal-directed learning, resulting in faulty activation of projection neurons in the striatum. Toxicogenetic ablation of CINs in young mice reproduced these behavioral and neuronal defects, suggesting that age-related deficits in PF-to-CIN function reduce the ability of older individuals to resolve conflict between actions, likely contributing to impairments in adaptive goal-directed action and executive control in aging. VIDEO ABSTRACT.

Increased risk of developing schizophrenia in animals exposed to cigarette smoke during the gestational period

Cigarette smoking during the prenatal period has been investigated as a causative factor of obstetric abnormalities, which lead to cognitive and behavioural changes associated with schizophrenia. The aim of this study was to investigate behaviour and AChE activity in brain structures in adult rats exposed to cigarette smoke during the prenatal period. Pregnant rats were divided into non-PCSE (non-prenatal cigarette smoke exposure) and PCSE (prenatal cigarette smoke exposure) groups. On post-natal day 60, the rats received saline or ketamine for 7days and were subjected to behavioural tasks. In the locomotor activity task, the non-PCSE+ketamine and PCSE+ketamine groups exhibited increased locomotor activity compared with the saline group. In the social interaction task, the non-PCSE+ketamine and PCSE+ketamine groups exhibited an increased latency compared with the control groups. However, the PCSE+ketamine group exhibited a decreased latency compared with the non-PCSE+ketamine group, which indicates that the cigarette exposure appeared to decrease, the social deficits generated by ketamine. In the inhibitory avoidance task, the non-PCSE+ketamine, PCSE, and PCSE+ketamine groups exhibited impairments in working memory, short-term memory, and long-term memory. In the pre-pulse inhibition (PPI) test, cigarette smoke associated with ketamine resulted in impaired PPI in 3 pre-pulse (PP) intensity groups compared with the control groups. In the biochemical analysis, the AChE activity in brain structures increased in the ketamine groups; however, the PCSE+ketamine group exhibited an exacerbated effect in all brain structures. The present study indicates that exposure to cigarette smoke during the prenatal period may affect behaviour and cerebral cholinergic structures during adulthood.

Cholinergic Potentiation Improves Perceptual-Cognitive Training of Healthy Young Adults in Three Dimensional Multiple Object Tracking

A large body of literature supports cognitive enhancement as an effect of cholinergic potentiation. However, it remains elusive whether pharmacological manipulations of cholinergic neurotransmission enhance complex visual processing in healthy individuals. To test this hypothesis, we randomly administered either the cholinergic transmission enhancer donepezil (DPZ; 5 mg P.O.) or placebo (lactose) to young adults (n = 17) 3 h before each session of the three-dimensional (3D) multiple object tracking (3D-MOT) task. This multi-focal attention task evaluates perceptual-cognitive learning over five sessions conducted 7 days apart. A significant amount of learning was observed in the DPZ group but not the placebo group in the fourth session. In the fifth session, this learning effect was observed in both groups. Furthermore, preliminary results for a subgroup of participants (n = 9) 4–14 months later suggested the cholinergic enhancement effect was long lasting. On the other hand, DPZ had no effect on basic visual processing as measured by a motion and orientation discrimination task performed as an independent one-time, pre-post drug study without placebo control (n = 10). The results support the construct that cholinergic enhancement facilitates the encoding of a highly demanding perceptual-cognitive task although there were no significant drug effects on the performance levels compared to placebo.

Modeling Trait Anxiety: From Computational Processes to Personality

Computational methods are increasingly being applied to the study of psychiatric disorders. Often, this involves fitting models to the behavior of individuals with subclinical character traits that are known vulnerability factors for the development of psychiatric conditions. Anxiety disorders can be examined with reference to the behavior of individuals high in "trait" anxiety, which is a known vulnerability factor for the development of anxiety and mood disorders. However, it is not clear how this self-report measure relates to neural and behavioral processes captured by computational models. This paper reviews emerging computational approaches to the study of trait anxiety, specifying how interacting processes susceptible to analysis using computational models could drive a tendency to experience frequent anxious states and promote vulnerability to the development of clinical disorders. Existing computational studies are described in the light of this perspective and appropriate targets for future studies are discussed.

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.

Prediction error, ketamine and psychosis: An updated model

In 2007, we proposed an explanation of delusion formation as aberrant prediction error-driven associative learning. Further, we argued that the NMDA receptor antagonist ketamine provided a good model for this process. Subsequently, we validated the model in patients with psychosis, relating aberrant prediction error signals to delusion severity. During the ensuing period, we have developed these ideas, drawing on the simple principle that brains build a model of the world and refine it by minimising prediction errors, as well as using it to guide perceptual inferences. While previously we focused on the prediction error signal per se, an updated view takes into account its precision, as well as the precision of prior expectations. With this expanded perspective, we see several possible routes to psychotic symptoms - which may explain the heterogeneity of psychotic illness, as well as the fact that other drugs, with different pharmacological actions, can produce psychotomimetic effects. In this article, we review the basic principles of this model and highlight specific ways in which prediction errors can be perturbed, in particular considering the reliability and uncertainty of predictions. The expanded model explains hallucinations as perturbations of the uncertainty mediated balance between expectation and prediction error. Here, expectations dominate and create perceptions by suppressing or ignoring actual inputs. Negative symptoms may arise due to poor reliability of predictions in service of action. By mapping from biology to belief and perception, the account proffers new explanations of psychosis. However, challenges remain. We attempt to address some of these concerns and suggest future directions, incorporating other symptoms into the model, building towards better understanding of psychosis.

Models of neuromodulation for computational psychiatry

Psychiatry faces fundamental challenges: based on a syndrome-based nosology, it presently lacks clinical tests to infer on disease processes that cause symptoms of individual patients and must resort to trial-and-error treatment strategies. These challenges have fueled the recent emergence of a novel field-computational psychiatry-that strives for mathematical models of disease processes at physiological and computational (information processing) levels. This review is motivated by one particular goal of computational psychiatry: the development of 'computational assays' that can be applied to behavioral or neuroimaging data from individual patients and support differential diagnosis and guiding patient-specific treatment. Because the majority of available pharmacotherapeutic approaches in psychiatry target neuromodulatory transmitters, models that infer (patho)physiological and (patho)computational actions of different neuromodulatory transmitters are of central interest for computational psychiatry. This article reviews the (many) outstanding questions on the computational roles of neuromodulators (dopamine, acetylcholine, serotonin, and noradrenaline), outlines available evidence, and discusses promises and pitfalls in translating these findings to clinical applications. WIREs Cogn Sci 2017, 8:e1420. doi: 10.1002/wcs.1420 For further resources related to this article, please visit the WIREs website.

Optogenetic Activation of Dorsal Raphe Serotonin Neurons Rapidly Inhibits Spontaneous But Not Odor-Evoked Activity in Olfactory Cortex

Serotonin (5-hydroxytriptamine; 5-HT) is implicated in a variety of brain functions including not only the regulation of mood and control of behavior but also the modulation of perception. 5-HT neurons in the dorsal raphe nucleus (DRN) often fire locked to sensory stimuli, but little is known about how 5-HT affects sensory processing, especially on this timescale. Here, we used an optogenetic approach to study the effect of 5-HT on single-unit activity in the mouse primary olfactory (anterior piriform) cortex. We show that activation of DRN 5-HT neurons rapidly inhibits the spontaneous firing of olfactory cortical neurons, acting in a divisive manner, but entirely spares sensory-driven firing. These results identify a new role for serotonergic modulation in dynamically regulating the balance between different sources of neural activity in sensory systems, suggesting a possible role for 5-HT in perceptual inference.

SIGNIFICANCE STATEMENT

Serotonin is implicated in a wide variety of (pato)physiological functions including perception, but its precise role has remained elusive. Here, using optogenetic tools in vivo, we show that serotonergic neuromodulation prominently inhibits the spontaneous electrical activity of neurons in the primary olfactory cortex on a rapid (<1 s) timescale but leaves sensory responses unaffected. These results identify a new role for serotonergic modulation in rapidly changing the balance between different sources of neural activity in sensory systems.

Population Code Dynamics in Categorical Perception

Categorical perception is a ubiquitous function in sensory information processing, and is reported to have important influences on the recognition of presented and/or memorized stimuli. However, such complex interactions among categorical perception and other aspects of sensory processing have not been explained well in a unified manner. Here, we propose a recurrent neural network model to process categorical information of stimuli, which approximately realizes a hierarchical Bayesian estimation on stimuli. The model accounts for a wide variety of neurophysiological and cognitive phenomena in a consistent framework. In particular, the reported complexity of categorical effects, including (i) task-dependent modulation of neural response, (ii) clustering of neural population representation, (iii) temporal evolution of perceptual color memory, and (iv) a non-uniform discrimination threshold, are explained as different aspects of a single model. Moreover, we directly examine key model behaviors in the monkey visual cortex by analyzing neural population dynamics during categorization and discrimination of color stimuli. We find that the categorical task causes temporally-evolving biases in the neuronal population representations toward the focal colors, which supports the proposed model. These results suggest that categorical perception can be achieved by recurrent neural dynamics that approximates optimal probabilistic inference in the changing environment.

M3 muscarinic receptor in the ventral medial prefrontal cortex modulating the expression of contextual fear conditioning in rats

RATIONALE

Basal forebrain cholinergic neurons modulate the activation of cortical neurons by several stimuli such as fear and anxiety. However, the role of the muscarinic receptor in the medial prefrontal cortex (MPFC) in the modulation of the conditioned emotional response (CER) evoked in the model contextual conditioned fear remains unclear.

OBJECTIVES

The objective of this study is to test the hypothesis that inhibition of the muscarinic receptor in ventral MPFC modulates CER observed during animal's re-exposure to the aversive context.

METHODS

Rats implanted with cannulae aimed at the prelimbic (PL) or the infralimbic (IL) were submitted to a high-intensity contextual fear conditioning protocol. Before the test session, they received microinjections of the hemicholinium (choline reuptake blocker), atropine (muscarinic antagonist), J104129 fumarate (M1-M3 muscarinic antagonists), pirenzepine (M1 muscarinic antagonist), neostigmine (inhibitor acetylcholinesterase enzyme), or the systemic administration of the FG7142 (inverse benzodiazepine agonist). Additional independent groups received the neostigmine or FG7142 before the ineffective doses of J104129 fumarate in the low-intensity protocol of contextual fear conditioning.

RESULTS

In the high-intensity protocol, the administration of hemicholinium (1 nmol), atropine (0.06-6 nmol), J104129 fumarate (6 nmol), or pirenzepine (6 nmol) attenuated the expression of CER in rats. However, in the low-intensity protocol, only J10129 fumarate (0.06 nmol) reduced the expression of the CER. Finally, neostigmine (0.1-1 nmol) or FG7142 (8 mg/Kg) increased CER expression, an effect inhibited by the low dose of the J10129 fumarate.

CONCLUSIONS

These results indicated that the blockade of M3 muscarinic receptor in the vMPFC attenuates the CER expression.