The promise of layer-specific neuroimaging for testing predictive coding theories of psychosis

Closed-loop fMRI at the mesoscopic scale of columns and layers: Can we do it and why would we want to?

Technological advances in fMRI including ultra-high magnetic fields (≥ 7 T) and acquisition methods that increase spatial specificity have paved the way for studies of the human cortex at the scale of layers and columns. This mesoscopic scale promises an improved mechanistic understanding of human cortical function so far only accessible to invasive animal neurophysiology. In recent years, an increasing number of studies have applied such methods to better understand the cortical function in perception and cognition. This future perspective article asks whether closed-loop fMRI studies could equally benefit from these methods to achieve layer and columnar specificity. We outline potential applications and discuss the conceptual and concrete challenges, including data acquisition and volitional control of mesoscopic brain activity. We anticipate an important role of fMRI with mesoscopic resolution for closed-loop fMRI and neurofeedback, yielding new insights into brain function and potentially clinical applications.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

RDoC Framework Through the Lens of Predictive Processing: Focusing on Cognitive Systems Domain

In response to shortcomings of the current classification system in translating discoveries from basic science to clinical applications, NIMH offers a new framework for studying mental health disorders called Research Domain Criteria (RDoC). This framework holds a multidimensional outlook on psychopathologies focusing on functional domains of behavior and their implementing neural circuits. In parallel, the Predictive Processing (PP) framework stands as a leading theory of human brain function, offering a unified explanation for various types of information processing in the brain. While both frameworks share an interest in studying psychopathologies based on pathophysiology, their integration still needs to be explored. Here, we argued in favor of the explanatory power of PP to be a groundwork for the RDoC matrix in validating its constructs and creating testable hypotheses about mechanistic interactions between molecular biomarkers and clinical traits. Together, predictive processing may serve as a foundation for achieving the goals of the RDoC framework.

Structural and functional alterations in different types of delusions across schizophrenia spectrum: A systematic review

BACKGROUND

Despite the high clinical role of delusions as a transnosological psychopathological phenomenon, the number of experimental studies on the different types of delusions across schizophrenia spectrum is still relatively small, and their results are somehow inconsistent. We aimed to understand the current state of knowledge regarding the structural and functional brain alterations in delusions to determine whether particular types of delusions are associated with specific brain changes and to identify common alterations underlying the formation and persistence of delusions regardless of their content.

METHODS

For this systematic review, we followed PRISMA guidelines to search in PubMed for English papers published between 1953 and September 30, 2023. The initial inclusion criteria for screening purposes were articles that investigated delusions or subclinical delusional beliefs in schizophrenia spectrum disorders, high clinical or genetic risk for schizophrenia using fMRI, sMRI or/and dwMRI methods. Exclusion criteria during the screening phase were articles that investigated lesion-induced or substance-induced delusions, delusions in Alzheimer's disease and other neurocognitive disorders, single case studies and non-human studies. The publication metadata were uploaded to the web-tool for working on systematic reviews, Rayyan. For each of the studies, a table was filled out with detailed information.

RESULTS

We found 1752 records, of which 95 full-text documents were reviewed and included in the current paper. Both nonspecific and particular types of delusions were associated with widespread structural and functional alterations. The most prominent areas affected across all types of delusions were the superior temporal cortex (predominantly left language processing areas), anterior cingulate/medial prefrontal cortex and insula. The most reproducible findings in paranoia may be alterations in the functioning of the amygdala and its interactions with other regions. Somatic delusions and delusional infestation were mostly characterized by alterations in the insula and thalamus.

DISCUSSION

The data are ambiguous; however, in general the predictive processing framework seems to be the most widely accepted approach to explaining different types of delusions. Aberrant prediction errors signaling during processing of social, self-generated and sensory information may lead to inaccuracies in assessing the intentions of others, self-relevancy of ambiguous stimuli, misattribution of self-generated actions and unusual sensations, which could provoke delusional ideation with persecutory, reference, control and somatic content correspondingly. However, currently available data are still insufficient to draw conclusions about the specific biological mechanisms of predictive coding account of delusions. Thus, further studies exploring more homogeneous groups and interaction of diagnoses by types of delusions are needed. There are also some limitations in this review. Studies that investigate delusions induced by lesions, substance abuse or neurodegeneration and studies using modalities other than fMRI, sMRI or dwMRI were not included in the review. Due to the relatively small number of publications, we systematized them based on a certain type of delusions, while the results could also be affected by the diagnosis of patients, the presence and type of therapy, illness duration etc.

Cellular psychology: relating cognition to context-sensitive pyramidal cells

'Cellular psychology' is a new field of inquiry that studies dendritic mechanisms for adapting mental events to the current context, thus increasing their coherence, flexibility, effectiveness, and comprehensibility. Apical dendrites of neocortical pyramidal cells have a crucial role in cognition - those dendrites receive input from diverse sources, including feedback, and can amplify the cell's feedforward transmission if relevant in that context. Specialized subsets of inhibitory interneurons regulate this cooperative context-sensitive processing by increasing or decreasing amplification. Apical input has different effects on cellular output depending on whether we are awake, deeply asleep, or dreaming. Furthermore, wakeful thought and imagery may depend on apical input. High-resolution neuroimaging in humans supports and complements evidence on these cellular mechanisms from other mammals.

Priors and prejudice: hierarchical predictive processing in intergroup perception

Hierarchical predictive processing provides a framework outlining how prior expectations shape perception and cognition. Here, we highlight hierarchical predictive processing as a framework for explaining how social context and group-based social knowledge can directly shape intergroup perception. More specifically, we argue that hierarchical predictive processing confers a uniquely valuable toolset to explain extant findings and generate novel hypotheses for intergroup perception. We first provide an overview of hierarchical predictive processing, specifying its primary theoretical assumptions. We then review evidence showing how prior knowledge influences intergroup perception. Next, we outline how hierarchical predictive processing can account well for findings in the intergroup perception literature. We then underscore the theoretical strengths of hierarchical predictive processing compared to other frameworks in this space. We finish by outlining future directions and laying out hypotheses that test the implications of hierarchical predictive processing for intergroup perception and intergroup cognition more broadly. Taken together, hierarchical predictive processing provides explanatory value and capacity for novel hypothesis generation for intergroup perception.

Predictions and errors are distinctly represented across V1 layers

Popular accounts of mind and brain propose that the brain continuously forms predictions about future sensory inputs and combines predictions with inputs to determine what we perceive.1,2,3,4,5,6 Under "predictive processing" schemes, such integration is supported by the hierarchical organization of the cortex, whereby feedback connections communicate predictions from higher-level deep layers to agranular (superficial and deep) lower-level layers.7,8,9,10 Predictions are compared with input to compute the "prediction error," which is transmitted up the hierarchy from superficial layers of lower cortical regions to the middle layers of higher areas, to update higher-level predictions until errors are reconciled.11,12,13,14,15 In the primary visual cortex (V1), predictions have thereby been proposed to influence representations in deep layers while error signals may be computed in superficial layers. Despite the framework's popularity, there is little evidence for these functional distinctions because, to our knowledge, unexpected sensory events have not previously been presented in human laminar paradigms to contrast against expected events. To this end, this 7T fMRI study contrasted V1 responses to expected (75% likely) and unexpected (25%) Gabor orientations. Multivariate decoding analyses revealed an interaction between expectation and layer, such that expected events could be decoded with comparable accuracy across layers, while unexpected events could only be decoded in superficial laminae. Although these results are in line with these accounts that have been popular for decades, such distinctions have not previously been demonstrated in humans. We discuss how both prediction and error processes may operate together to shape our unitary perceptual experiences.

Antipsychotic drugs selectively decorrelate long-range interactions in deep cortical layers

Psychosis is characterized by a diminished ability of the brain to distinguish externally driven activity patterns from self-generated activity patterns. Antipsychotic drugs are a class of small molecules with relatively broad binding affinity for a variety of neuromodulator receptors that, in humans, can prevent or ameliorate psychosis. How these drugs influence the function of cortical circuits, and in particular their ability to distinguish between externally and self-generated activity patterns, is still largely unclear. To have experimental control over self-generated sensory feedback, we used a virtual reality environment in which the coupling between movement and visual feedback can be altered. We then used widefield calcium imaging to determine the cell type-specific functional effects of antipsychotic drugs in mouse dorsal cortex under different conditions of visuomotor coupling. By comparing cell type-specific activation patterns between locomotion onsets that were experimentally coupled to self-generated visual feedback and locomotion onsets that were not coupled, we show that deep cortical layers were differentially activated in these two conditions. We then show that the antipsychotic drug clozapine disrupted visuomotor integration at locomotion onsets also primarily in deep cortical layers. Given that one of the key components of visuomotor integration in cortex is long-range cortico-cortical connections, we tested whether the effect of clozapine was detectable in the correlation structure of activity patterns across dorsal cortex. We found that clozapine as well as two other antipsychotic drugs, aripiprazole and haloperidol, resulted in a strong reduction in correlations of layer 5 activity between cortical areas and impaired the spread of visuomotor prediction errors generated in visual cortex. Our results are consistent with the interpretation that a major functional effect of antipsychotic drugs is a selective alteration of long-range layer 5-mediated communication.

Evidence for Reduced Sensory Precision and Increased Reliance on Priors in Hallucination-Prone Individuals in a General Population Sample

BACKGROUND

There is increasing evidence that people with hallucinations overweight perceptual beliefs relative to incoming sensory evidence. Past work demonstrating prior overweighting has used simple, nonlinguistic stimuli. However, auditory hallucinations in psychosis are often complex and linguistic. There may be an interaction between the type of auditory information being processed and its perceived quality in engendering hallucinations.

STUDY DESIGN

We administered a linguistic version of the conditioned hallucinations (CH) task to an online sample of 88 general population participants. Metrics related to hallucination-proneness, hallucination severity, stimulus thresholds, and stimulus detection rates were collected. Data were used to fit parameters of a Hierarchical Gaussian Filter (HGF) model of perceptual inference to determine how latent perceptual states influenced task behavior.

STUDY RESULTS

Replicating past results, higher CH rates were observed both in those with recent hallucinatory experiences as well as participants with high hallucination-proneness; CH rates were positively correlated with increased prior weighting; and increased prior weighting was related to hallucination severity. Unlike past results, participants with recent hallucinatory experiences as well as those with higher hallucination-proneness had higher stimulus thresholds, lower sensitivity to stimuli presented at the highest threshold, and had lower response confidence, consistent with lower precision of sensory evidence.

CONCLUSIONS

We replicate the finding that increased CH rates and recent hallucinations correlate with increased prior weighting using a linguistic version of the CH task. Results support a role for reduced sensory precision in the interplay between prior weighting and hallucination-proneness.

A novel model of divergent predictive perception

Predictive processing theories state that our subjective experience of reality is shaped by a balance of expectations based on previous knowledge about the world (i.e. priors) and confidence in sensory input from the environment. Divergent experiences (e.g. hallucinations and synaesthesia) are likely to occur when there is an imbalance between one's reliance on priors and sensory input. In a novel theoretical model, inspired by both predictive processing and psychological principles, we propose that predictable divergent experiences are associated with natural or environmentally induced prior/sensory imbalances: inappropriately strong or inflexible (i.e. maladaptive) high-level priors (beliefs) combined with low sensory confidence can result in reality discrimination issues, a characteristic of psychosis; maladaptive low-level priors (sensory expectations) combined with high sensory confidence can result in atypical sensory sensitivities and persistent divergent percepts, a characteristic of synaesthesia. Crucially, we propose that whether different divergent experiences manifest with dominantly sensory (e.g. hallucinations) or nonsensory characteristics (e.g. delusions) depends on mental imagery ability, which is a spectrum from aphantasia (absent or weak imagery) to hyperphantasia (extremely vivid imagery). We theorize that imagery is critically involved in shaping the sensory richness of divergent perceptual experience. In sum, to predict a range of divergent perceptual experiences in both clinical and general populations, three factors must be accounted for: a maladaptive use of priors, individual level of confidence in sensory input, and mental imagery ability. These ideas can be expressed formally using nonparametric regression modeling. We provide evidence for our theory from previous work and deliver predictions for future research.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.

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.

Expectation Cues and False Percepts Generate Stimulus-Specific Activity in Distinct Layers of the Early Visual Cortex

Perception has been proposed to result from the integration of feedforward sensory signals with internally generated feedback signals. Feedback signals are believed to play an important role in driving false percepts, that is, seeing things that are not actually there. Feedforward and feedback influences on perception can be studied using layer-specific fMRI, which we used here to interrogate neural activity underlying high-confidence false percepts while healthy human participants (N = 25, male and female) performed a perceptual orientation discrimination task. Auditory cues implicitly signaled the most likely upcoming orientation (referred to here as expectations). These expectations induced orientation-specific templates in the deep and superficial layers of V2, without affecting perception. In contrast, the orientation of falsely perceived stimuli with high confidence was reflected in the middle input layers of V2, suggesting a feedforward signal contributing to false percepts. The prevalence of high-confidence false percepts was related to everyday hallucination severity in a separate online sample (N = 100), suggesting a possible link with abnormal perceptual experiences. These results reveal a potential feedforward mechanism underlying false percepts, reflected by spontaneous stimulus-like activity in the input layers of the visual cortex, independent of top-down signals reflecting cued orientations.SIGNIFICANCE STATEMENT False percepts have been suggested to arise through excessive feedback signals. However, feedforward contributions to false percepts have remained largely understudied. Laminar fMRI has been shown to be useful in distinguishing feedforward from feedback activity as it allows the imaging of different cortical layers. In the present study we demonstrate that although cued orientations are encoded in the feedback layers of the visual cortex, the content of the false percepts are encoded in the feedforward layers and did not rely on these cued orientations. This shows that false percepts can in principle emerge from random feedforward signals in the visual cortex, with possible implications for disorders hallmarked by hallucinations like schizophrenia and Parkinson's disease.

Functional neuroimaging as a catalyst for integrated neuroscience

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another. In this Perspective, we argue that fMRI is well-placed to integrate the diverse subfields of systems, cognitive, computational and clinical neuroscience. We first summarize the strengths and weaknesses of fMRI as an imaging tool, then highlight examples of studies that have successfully used fMRI in each subdomain of neuroscience. We then provide a roadmap for the future advances that will be needed to realize this integrative vision. In this way, we hope to demonstrate how fMRI can help usher in a new era of interdisciplinary coherence in neuroscience.

Bayesian accounts of perceptual decisions in the nonclinical continuum of psychosis: Greater imprecision in both top-down and bottom-up processes

Neurocomputational accounts of psychosis propose mechanisms for how information is integrated into a predictive model of the world, in attempts to understand the occurrence of altered perceptual experiences. Conflicting Bayesian theories postulate aberrations in either top-down or bottom-up processing. The top-down theory predicts an overreliance on prior beliefs or expectations resulting in aberrant perceptual experiences, whereas the bottom-up theory predicts an overreliance on current sensory information, as aberrant salience is directed towards objectively uninformative stimuli. This study empirically adjudicates between these models. We use a perceptual decision-making task in a neurotypical population with varying degrees of psychotic-like experiences. Bayesian modelling was used to compute individuals' reliance on prior relative to sensory information. Across two datasets (discovery dataset n = 363; independent replication in validation dataset n = 782) we showed that psychotic-like experiences were associated with an overweighting of sensory information relative to prior expectations, which seem to be driven by decreased precision afforded to prior information. However, when prior information was more uncertain, participants with greater psychotic-like experiences encoded sensory information with greater noise. Greater psychotic-like experiences were associated with aberrant precision in the encoding both prior and likelihood information, which we suggest may be related to generally heightened perceptions of task instability. Our study lends empirical support to notions of both weaker bottom-up and weaker (rather than stronger) top-down perceptual processes, as well as aberrancies in belief updating that extend into the non-clinical continuum of psychosis.

Laminar VASO fMRI in focal hand dystonia patients

Focal Hand Dystonia (FHD) is a disabling movement disorder characterized by involuntary movements, cramps and spasms. It is associated with pathological neural microcircuits in the cortical somatosensory system. While invasive preclinical modalities allow researchers to probe specific neural microcircuits of cortical layers and columns, conventional functional magnetic resonance imaging (fMRI) cannot resolve such small neural computational units. In this study, we take advantage of recent developments in ultra-high-field MRI hardware and MR-sequences to capture altered digit representations and laminar processing in FHD patients. We aim to characterize the capability and challenges of layer-specific imaging and analysis tools in resolving laminar and columnar structures in clinical research setups. We scanned N = 4 affected and N = 5 unaffected hemispheres at 7T and found consistent results of altered neural microcircuitry in FHD patients: 1) In affected hemispheres of FHD patients, we found a breakdown of ordered finger representation in the primary somatosensory cortex, as suggested from previous low-resolution fMRI. 2) In affected primary motor cortices of FHD patients, we furthermore found increased fMRI activity in superficial cortico-cortical neural input layers (II/III), compared to relatively weaker activity in the cortico-spinal output layers (Vb/VI). Overall, we show that layer-fMRI acquisition and analysis tools have the potential to address clinically-driven neuroscience research questions about altered computational mechanisms at the spatial scales that were previously only accessible in animal models. We believe that this study paves the way for easier translation of preclinical work into clinical research in focal hand dystonia and beyond.

Action selection in early stages of psychosis: an active inference approach

BACKGROUND

To interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls.

METHODS

Twenty-three individuals with an at-risk mental state, 26 patients with first-episode psychosis and 31 controls completed a probabilistic task in which action choice (go/no-go) was dissociated from outcome valence (gain or loss). We evaluated group differences in performance and active inference model parameters and performed receiver operating characteristic (ROC) analyses to assess group classification.

RESULTS

We found reduced overall performance in patients with psychosis. Active inference modelling revealed that patients showed increased forgetting, reduced confidence in policy selection and less optimal general choice behaviour, with poorer action-state associations. Importantly, ROC analysis showed fair-to-good classification performance for all groups, when combining modelling parameters and performance measures.

LIMITATIONS

The sample size is moderate.

CONCLUSION

Active inference modelling of this task provides further explanation for dysfunctional mechanisms underlying decision-making in psychosis and may be relevant for future research on the development of biomarkers for early identification of psychosis.

Rethinking delusions: A selective review of delusion research through a computational lens

Delusions are rigid beliefs held with high certainty despite contradictory evidence. Notwithstanding decades of research, we still have a limited understanding of the computational and neurobiological alterations giving rise to delusions. In this review, we highlight a selection of recent work in computational psychiatry aimed at developing quantitative models of inference and its alterations, with the goal of providing an explanatory account for the form of delusional beliefs in psychosis. First, we assess and evaluate the experimental paradigms most often used to study inferential alterations in delusions. Based on our review of the literature and theoretical considerations, we contend that classic draws-to-decision paradigms are not well-suited to isolate inferential processes, further arguing that the commonly cited 'jumping-to-conclusion' bias may reflect neither delusion-specific nor inferential alterations. Second, we discuss several enhancements to standard paradigms that show promise in more effectively isolating inferential processes and delusion-related alterations therein. We further draw on our recent work to build an argument for a specific failure mode for delusions consisting of prior overweighting in high-level causal inferences about partially observable hidden states. Finally, we assess plausible neurobiological implementations for this candidate failure mode of delusional beliefs and outline promising future directions in this area.

Perceptual pathways to hallucinogenesis

Recent advances in computational psychiatry have provided unique insights into the neural and cognitive underpinnings of psychotic symptoms. In particular, a host of new data has demonstrated the utility of computational frameworks for understanding how hallucinations might arise from alterations in typical perceptual processing. Of particular promise are models based in Bayesian inference that link hallucinatory perceptual experiences to latent states that may drive them. In this piece, we move beyond these findings to ask: how and why do these latent states arise, and how might we take advantage of heterogeneity in that process to develop precision approaches to the treatment of hallucinations? We leverage specific models of Bayesian inference to discuss components that might lead to the development of hallucinations. Using the unifying power of our model, we attempt to place disparate findings in the study of psychotic symptoms within a common framework. Finally, we suggest directions for future elaboration of these models in the service of a more refined psychiatric nosology based on predictable, testable, and ultimately treatable information processing derangements.

Perceived and mentally rotated contents are differentially represented in cortical depth of V1

Primary visual cortex (V1) in humans is known to represent both veridically perceived external input and internally-generated contents underlying imagery and mental rotation. However, it is unknown how the brain keeps these contents separate thus avoiding a mixture of the perceived and the imagined which could lead to potentially detrimental consequences. Inspired by neuroanatomical studies showing that feedforward and feedback connections in V1 terminate in different cortical layers, we hypothesized that this anatomical compartmentalization underlies functional segregation of external and internally-generated visual contents, respectively. We used high-resolution layer-specific fMRI to test this hypothesis in a mental rotation task. We found that rotated contents were predominant at outer cortical depth bins (i.e. superficial and deep). At the same time perceived contents were represented stronger at the middle cortical bin. These results identify how through cortical depth compartmentalization V1 functionally segregates rather than confuses external from internally-generated visual contents. These results indicate that feedforward and feedback manifest in distinct subdivisions of the early visual cortex, thereby reflecting a general strategy for implementing multiple cognitive functions within a single brain region.

A continuum hypothesis of psychotomimetic rapid antidepressants

Ketamine, classical psychedelics and sleep deprivation are associated with rapid effects on depression. Interestingly, these interventions also have common psychotomimetic actions, mirroring aspects of psychosis such as an altered sense of self, perceptual distortions and distorted thinking. This raises the question whether these interventions might be acute antidepressants through the same mechanisms that underlie some of their psychotomimetic effects. That is, perhaps some symptoms of depression can be understood as occupying the opposite end of a spectrum where elements of psychosis can be found on the other side. This review aims at reviewing the evidence underlying a proposed continuum hypothesis of psychotomimetic rapid antidepressants, suggesting that a range of psychotomimetic interventions are also acute antidepressants as well as trying to explain these common features in a hierarchical predictive coding framework, where we hypothesise that these interventions share a common mechanism by increasing the flexibility of prior expectations. Neurobiological mechanisms at play and the role of different neuromodulatory systems affected by these interventions and their role in controlling the precision of prior expectations and new sensory evidence will be reviewed. The proposed hypothesis will also be discussed in relation to other existing theories of antidepressants. We also suggest a number of novel experiments to test the hypothesis and highlight research areas that could provide further insights, in the hope to better understand the acute antidepressant properties of these interventions.