Cortical and subcortical signatures of conscious object recognition

Inhibition of PGAM5 hyperactivation reduces neuronal apoptosis in PC12 cells and experimental vascular dementia rats

PURPOSE

The incidence of vascular dementia (VaD), as one of the main types of dementia in old age, has been increasing year by year, and exploring its pathogenesis and seeking practical and effective treatment methods are undoubtedly the key to solving this problem. Phosphoglycerate translocase 5 (PGAM5), as a crossroads of multiple signaling pathways, can lead to mitochondrial fission, which in turn triggers the onset and development of necroptosis, and thus PGAM5 may be a novel target for the prevention and treatment of vascular dementia.

METHODS

Animal model of vascular dementia was established by Two-vessel occlusion (2-VO) method, and cellular model of vascular dementia was established by oxygen glucose deprivation (OGD) method. Neuronal damage was detected in vivo and in vitro in different groups using different concentrations of the PGAM5-specific inhibitor LFHP-1c, and necroptosis and mitochondrial dynamics-related factors were determined.

RESULTS

In vivo experiments, 10 mg/kg-1 and 20 mg/kg-1 LFHP-1c improved cognitive deficits, reduced neuronal edema and vacuoles, increased the number of nissl bodies, and it could modulate the expression of Caspase family and Bcl-2 family related proteins and mRNAs and ameliorate neuronal damage. Simultaneously, in vitro experiments, 5 μM, 10 μM and 20 μM LFHP-1c increased the activity and migration number of model cells, reduced the number of apoptotic cells, ameliorated the excessive accumulation of intracellular reactive oxygen species, inhibited the over-activation of caspase-family and Bcl-2-family related proteins and mRNAs, and improved the mitochondrial dynamics of the fission and fusion states. Moreover, in vivo and in vitro experiments have shown that LFHP-1c can also upregulate the expression level of BDNF, inhibit the expression content of TNF-α and ROS, regulate the expression of proteins and mRNAs related to the RIPK1/RIPK3/MLKL pathway and mitochondrial dynamics, and reduce neuronal apoptosis.

CONCLUSIONS

Inhibition of PGAM5 expression level can reduce neuronal damage caused by chronic cerebral ischemia and hypoxia, which mainly prevents necroptosis by targeting the RIPK1/RIPK3/MLKL signaling pathway and regulates the downstream mitochondrial dynamics homeostasis system to prevent excessive mitochondrial fission, thus improving cognition and exerting cerebroprotective effects.

Thalamic Roles in Conscious Perception Revealed by Low-Intensity Focused Ultrasound Neuromodulation

The neural basis of conscious perception remains incompletely understood. While cortical mechanisms of conscious content have been extensively investigated, the role of subcortical structures, including the thalamus, remains less explored. We aim to elucidate the causal contributions of different thalamic regions to conscious perception using transcranial low-intensity focused ultrasound (LIFU) neuromodulation. We hypothesize that modulating different thalamic regions would result in distinct perceptual outcomes. We apply LIFU in human volunteers to investigate region-specific and sonication parameter-dependent effects. We target anterior (transmodal-dominant) and posterior (unimodal-dominant) thalamic regions, further divided into ventral and dorsal regions, while participants perform a near-threshold visual perception task. Task performance is evaluated using Signal Detection Theory metrics. We find that the high duty cycle stimulation of the ventral anterior thalamus enhanced object recognition sensitivity. We also observe a general (i.e., region-independent) effect of LIFU on decision bias (i.e., a tendency toward a particular response) and object categorization accuracy. Specifically, high duty cycle stimulation decreases categorization accuracy, whereas low duty cycle shifts decision bias towards a more conservative stance. In conclusion, our results provide causal insight into the functional organization of the thalamus in shaping human visual experience and highlight the unique role of the transmodal-dominant ventral anterior thalamus.

Shared subcortical arousal systems across sensory modalities during transient modulation of attention

Subcortical arousal systems are known to play a key role in controlling sustained changes in attention and conscious awareness. Recent studies indicate that these systems have a major influence on short-term dynamic modulation of visual attention, but their role across sensory modalities is not fully understood. In this study, we investigated shared subcortical arousal systems across sensory modalities during transient changes in attention using block and event-related fMRI paradigms. We analyzed massive publicly available fMRI datasets collected while 1,561 participants performed visual, auditory, tactile, and taste perception tasks. Our analyses revealed a shared circuit of subcortical arousal systems exhibiting early transient increases in activity in midbrain reticular formation and central thalamus across perceptual modalities, as well as less consistent increases in pons, hypothalamus, basal forebrain, and basal ganglia. Identifying these networks is critical for understanding mechanisms of normal attention and consciousness and may help facilitate subcortical targeting for therapeutic neuromodulation.

Object-based attention requires monocular visual pathways

Mechanisms of object-based attention (OBA) are commonly associated with the cerebral cortex. However, less is known about the involvement of subcortical visual pathways in these processes. Knowledge of the neural mechanisms subserving OBA can provide insight into the evolutionary trajectory of attentional selection. In the current study, the classic double-rectangle cueing task was implemented using a stereoscope in order to differentiate between the involvement of lower (monocular) and higher (binocular) visual pathways in OBA processes. We found that monocular visual pathways are involved in two main aspects of OBA: exogenous orienting towards a cued object (Experiment 1; N =33) and attentional deployment within a cued object (Experiment 2; N =23); this is evident by the presence of OBA only when both the cue and target were presented to the same eye. Thus, these results indicate that monocular (mostly subcortical) visual regions are not simply passing information to higher cortical areas but have a functional computational role in OBA. These findings emphasize the importance of lower regions in attentional processes and, more specifically, in OBA.

Network mechanisms of ongoing brain activity's influence on conscious visual perception

Sensory inputs enter a constantly active brain, whose state is always changing from one moment to the next. Currently, little is known about how ongoing, spontaneous brain activity participates in online task processing. We employed 7 Tesla fMRI and a threshold-level visual perception task to probe the effects of prestimulus ongoing brain activity on perceptual decision-making and conscious recognition. Prestimulus activity originating from distributed brain regions, including visual cortices and regions of the default-mode and cingulo-opercular networks, exerted a diverse set of effects on the sensitivity and criterion of conscious recognition, and categorization performance. We further elucidate the mechanisms underlying these behavioral effects, revealing how prestimulus activity modulates multiple aspects of stimulus processing in highly specific and network-dependent manners. These findings reveal heretofore unknown network mechanisms underlying ongoing brain activity's influence on conscious perception, and may hold implications for understanding the precise roles of spontaneous activity in other brain functions.

Spontaneously emerging internal models of visual sequences combine abstract and event-specific information in the prefrontal cortex

When exposed to sensory sequences, do macaque monkeys spontaneously form abstract internal models that generalize to novel experiences? Here, we show that neuronal populations in macaque ventrolateral prefrontal cortex jointly encode visual sequences by separate codes for the specific pictures presented and for their abstract sequential structure. We recorded prefrontal neurons while macaque monkeys passively viewed visual sequences and sequence mismatches in the local-global paradigm. Even without any overt task or response requirements, prefrontal populations spontaneously form representations of sequence structure, serial order, and image identity within distinct but superimposed neuronal subspaces. Representations of sequence structure rapidly update following single exposure to a mismatch sequence, while distinct populations represent mismatches for sequences of different complexity. Finally, those representations generalize across sequences following the same repetition structure but comprising different images. These results suggest that prefrontal populations spontaneously encode rich internal models of visual sequences reflecting both content-specific and abstract information.

Identifying content-invariant neural signatures of perceptual vividness

Some conscious experiences are more vivid than others. Although perceptual vividness is a key component of human consciousness, how variation in this magnitude property is registered by the human brain is unknown. A striking feature of neural codes for magnitude in other psychological domains, such as number or reward, is that the magnitude property is represented independently of its sensory features. To test whether perceptual vividness also covaries with neural codes that are invariant to sensory content, we reanalyzed existing magnetoencephalography and functional MRI data from two distinct studies which quantified perceptual vividness via subjective ratings of awareness and visibility. Using representational similarity and decoding analyses, we find evidence for content-invariant neural signatures of perceptual vividness distributed across visual, parietal, and frontal cortices. Our findings indicate that the neural correlates of subjective vividness may share similar properties to magnitude codes in other cognitive domains.

jsQuestPlus: A JavaScript implementation of the QUEST+ method for estimating psychometric function parameters in online experiments

The two Bayesian adaptive psychometric methods named QUEST (Watson & Pelli, 1983) and QUEST+ (Watson, 2017) are widely used to estimate psychometric parameters, especially the threshold, in laboratory-based psychophysical experiments. Considering the increase of online psychophysical experiments in recent years, there is a growing need to have the QUEST and QUEST+ methods available online as well. We developed JavaScript libraries for both, with this article introducing one of them: jsQuestPlus. We offer integrations with online experimental tools such as jsPsych (de Leeuw, 2015), PsychoPy/JS (Peirce et al., 2019), and lab.js (Henninger et al., 2021). We measured the computation time required by jsQuestPlus under four conditions. Our simulations on 37 browser-computer combinations showed that the mean initialization time was 461.08 ms, 95% CI [328.29, 593.87], the mean computation time required to determine the stimulus parameters for the next trial was less than 1 ms, and the mean update time was 79.39 ms, 95% CI [46.22, 112.55] even in extremely demanding conditions. Additionally, psychometric parameters were estimated as accurately as the original QUEST+ method did. We conclude that jsQuestPlus is fast and accurate enough to conduct online psychophysical experiments despite the complexity of the matrix calculations. The latest version of jsQuestPlus can be downloaded freely from https://github.com/kurokida/jsQuestPlus under the MIT license.

The conscious processing of emotion in depression disorder: a meta-analysis of neuroimaging studies

Background

Depression is generally accompanied by a disturbed conscious processing of emotion, which manifests as a negative bias to facial/voice emotion information and a decreased accuracy in emotion recognition tasks. Several studies have proved that abnormal brain activation was responsible for the deficit function of conscious emotion recognition in depression. However, the altered brain activation related to the conscious processing of emotion in depression was incongruent among studies. Therefore, we conducted an activation likelihood estimation (ALE) analysis to better understand the underlying neurophysiological mechanism of conscious processing of emotion in depression.

Method

Electronic databases were searched using the search terms "depression," "emotion recognition," and "neuroimaging" from inceptions to April 10th, 2023. We retrieved trials which explored the neuro-responses of depressive patients to explicit emotion recognition tasks. Two investigators independently performed literature selection, data extraction, and risk of bias assessment. The spatial consistency of brain activation in conscious facial expressions recognition was calculated using ALE. The robustness of the results was examined by Jackknife sensitivity analysis.

Results

We retrieved 11,365 articles in total, 28 of which were included. In the overall analysis, we found increased activity in the middle temporal gyrus, superior temporal gyrus, parahippocampal gyrus, and cuneus, and decreased activity in the superior temporal gyrus, inferior parietal lobule, insula, and superior frontal gyrus. In response to positive stimuli, depressive patients showed hyperactivity in the medial frontal gyrus, middle temporal gyrus, and insula (uncorrected p < 0.001). When receiving negative stimuli, a higher activation was found in the precentral gyrus, middle frontal gyrus, precuneus, and superior temporal gyrus (uncorrected p < 0.001).

Conclusion

Among depressive patients, a broad spectrum of brain areas was involved in a deficit of conscious emotion processing. The activation of brain regions was different in response to positive or negative stimuli. Due to potential clinical heterogeneity, the findings should be treated with caution.

Systematic review registration

https://inplasy.com/inplasy-2022-11-0057/, identifier: 2022110057.

Fear memory recall involves hippocampal somatostatin interneurons

Fear-related memory traces are encoded by sparse populations of hippocampal principal neurons that are recruited based on their inhibitory-excitatory balance during memory formation. Later, the reactivation of the same principal neurons can recall the memory. The details of this mechanism are still unclear. Here, we investigated whether disinhibition could play a major role in this process. Using optogenetic behavioral experiments, we found that when fear was associated with the inhibition of mouse hippocampal somatostatin positive interneurons, the re-inhibition of the same interneurons could recall fear memory. Pontine nucleus incertus neurons selectively inhibit hippocampal somatostatin cells. We also found that when fear was associated with the activity of these incertus neurons or fibers, the reactivation of the same incertus neurons or fibers could also recall fear memory. These incertus neurons showed correlated activity with hippocampal principal neurons during memory recall and were strongly innervated by memory-related neocortical centers, from which the inputs could also control hippocampal disinhibition in vivo. Nonselective inhibition of these mouse hippocampal somatostatin or incertus neurons impaired memory recall. Our data suggest a novel disinhibition-based memory mechanism in the hippocampus that is supported by local somatostatin interneurons and their pontine brainstem inputs.

Spatiotemporal neural dynamics of object recognition under uncertainty in humans

While there is a wealth of knowledge about core object recognition-our ability to recognize clear, high-contrast object images-how the brain accomplishes object recognition tasks under increased uncertainty remains poorly understood. We investigated the spatiotemporal neural dynamics underlying object recognition under increased uncertainty by combining MEG and 7 Tesla (7T) fMRI in humans during a threshold-level object recognition task. We observed an early, parallel rise of recognition-related signals across ventral visual and frontoparietal regions that preceded the emergence of category-related information. Recognition-related signals in ventral visual regions were best explained by a two-state representational format whereby brain activity bifurcated for recognized and unrecognized images. By contrast, recognition-related signals in frontoparietal regions exhibited a reduced representational space for recognized images, yet with sharper category information. These results provide a spatiotemporally resolved view of neural activity supporting object recognition under uncertainty, revealing a pattern distinct from that underlying core object recognition.

Multimodal deep neural decoding reveals highly resolved spatiotemporal profile of visual object representation in humans

Perception and categorization of objects in a visual scene are essential to grasp the surrounding situation. Recently, neural decoding schemes, such as machine learning in functional magnetic resonance imaging (fMRI), has been employed to elucidate the underlying neural mechanisms. However, it remains unclear as to how spatially distributed brain regions temporally represent visual object categories and sub-categories. One promising strategy to address this issue is neural decoding with concurrently obtained neural response data of high spatial and temporal resolution. In this study, we explored the spatial and temporal organization of visual object representations using concurrent fMRI and electroencephalography (EEG), combined with neural decoding using deep neural networks (DNNs). We hypothesized that neural decoding by multimodal neural data with DNN would show high classification performance in visual object categorization (faces or non-face objects) and sub-categorization within faces and objects. Visualization of the fMRI DNN was more sensitive than that in the univariate approach and revealed that visual categorization occurred in brain-wide regions. Interestingly, the EEG DNN valued the earlier phase of neural responses for categorization and the later phase of neural responses for sub-categorization. Combination of the two DNNs improved the classification performance for both categorization and sub-categorization compared with fMRI DNN or EEG DNN alone. These deep learning-based results demonstrate a categorization principle in which visual objects are represented in a spatially organized and coarse-to-fine manner, and provide strong evidence of the ability of multimodal deep learning to uncover spatiotemporal neural machinery in sensory processing.

Towards a pluralistic neurobiological understanding of consciousness

Theories of consciousness are often based on the assumption that a single, unified neurobiological account will explain different types of conscious awareness. However, recent findings show that, even within a single modality such as conscious visual perception, the anatomical location, timing, and information flow of neural activity related to conscious awareness vary depending on both external and internal factors. This suggests that the search for generic neural correlates of consciousness may not be fruitful. I argue that consciousness science requires a more pluralistic approach and propose a new framework: joint determinant theory (JDT). This theory may be capable of accommodating different brain circuit mechanisms for conscious contents as varied as percepts, wills, memories, emotions, and thoughts, as well as their integrated experience.

Revealing robust neural correlates of conscious and unconscious visual processing: activation likelihood estimation meta-analyses

Our ability to consciously perceive information from the visual scene relies on a myriad of intrinsic neural mechanisms. Functional neuroimaging studies have sought to identify the neural correlates of conscious visual processing and to further dissociate from those pertaining to preconscious and unconscious visual processing. However, delineating what core brain regions are involved in eliciting a conscious percept remains a challenge, particularly regarding the role of prefrontal-parietal regions. We performed a systematic search of the literature that yielded a total of 54 functional neuroimaging studies. We conducted two quantitative meta-analyses using activation likelihood estimation to identify reliable patterns of activation engaged by i. conscious (n = 45 studies, comprising 704 participants) and ii. unconscious (n = 16 studies, comprising 262 participants) visual processing during various task performances. Results of the meta-analysis specific to conscious percepts quantitatively revealed reliable activations across a constellation of regions comprising the bilateral inferior frontal junction, intraparietal sulcus, dorsal anterior cingulate, angular gyrus, temporo-occipital cortex and anterior insula. Neurosynth reverse inference revealed conscious visual processing to be intertwined with cognitive terms related to attention, cognitive control and working memory. Results of the meta-analysis on unconscious percepts revealed consistent activations in the lateral occipital complex, intraparietal sulcus and precuneus. These findings highlight the notion that conscious visual processing readily engages higher-level regions including the inferior frontal junction and unconscious processing reliably recruits posterior regions, mainly the lateral occipital complex.

Bistability of prefrontal states gates access to consciousness

Access of sensory information to consciousness has been linked to the ignition of content-specific representations in association cortices. How does ignition interact with intrinsic cortical state fluctuations to give rise to conscious perception? We addressed this question in the prefrontal cortex (PFC) by combining multi-electrode recordings with a binocular rivalry (BR) paradigm inducing spontaneously driven changes in the content of consciousness, inferred from the reflexive optokinetic nystagmus (OKN) pattern. We find that fluctuations between low-frequency (LF, 1-9 Hz) and beta (∼20-40 Hz) local field potentials (LFPs) reflect competition between spontaneous updates and stability of conscious contents, respectively. Both LF and beta events were locally modulated. The phase of the former locked differentially to the competing populations just before a spontaneous transition while the latter synchronized the neuronal ensemble coding the consciously perceived content. These results suggest that prefrontal state fluctuations gate conscious perception by mediating internal states that facilitate perceptual update and stability.

Conscious interpretation: A distinct aspect for the neural markers of the contents of consciousness

Progress in the science of consciousness depends on the experimental paradigms and varieties of contrastive analysis available to researchers. Here we highlight paradigms where the object is represented in consciousness as a set of its features but the interpretation of this set alternates in consciousness. We group experimental paradigms with this property under the label "conscious interpretation". We compare the paradigms studying conscious interpretation of the already consciously perceived objects with other types of experimental paradigms. We review previous and recent studies investigating this interpretative aspect of consciousness and propose future directions. We put forward the hypothesis that there are types of stimuli with a hierarchy of interpretations for which the rule applies: conscious experience is drawn towards higher-level interpretation and reverting back to the lower level of interpretation is impossible. We discuss how theories of consciousness might incorporate knowledge and constraints arising from the characteristics of conscious interpretation.

Consciousness as a Memory System

We suggest that there is confusion between why consciousness developed and what additional functions, through continued evolution, it has co-opted. Consider episodic memory. If we believe that episodic memory evolved solely to accurately represent past events, it seems like a terrible system-prone to forgetting and false memories. However, if we believe that episodic memory developed to flexibly and creatively combine and rearrange memories of prior events in order to plan for the future, then it is quite a good system. We argue that consciousness originally developed as part of the episodic memory system-quite likely the part needed to accomplish that flexible recombining of information. We posit further that consciousness was subsequently co-opted to produce other functions that are not directly relevant to memory per se, such as problem-solving, abstract thinking, and language. We suggest that this theory is compatible with many phenomena, such as the slow speed and the after-the-fact order of consciousness, that cannot be explained well by other theories. We believe that our theory may have profound implications for understanding intentional action and consciousness in general. Moreover, we suggest that episodic memory and its associated memory systems of sensory, working, and semantic memory as a whole ought to be considered together as the conscious memory system in that they, together, give rise to the phenomenon of consciousness. Lastly, we suggest that the cerebral cortex is the part of the brain that makes consciousness possible, and that every cortical region contributes to this conscious memory system.

Human visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity

The full neural circuits of conscious perception remain unknown. Using a visual perception task, we directly recorded a subcortical thalamic awareness potential (TAP). We also developed a unique paradigm to classify perceived versus not perceived stimuli using eye measurements to remove confounding signals related to reporting on conscious experiences. Using fMRI, we discovered three major brain networks driving conscious visual perception independent of report: first, increases in signal detection regions in visual, fusiform cortex, and frontal eye fields; and in arousal/salience networks involving midbrain, thalamus, nucleus accumbens, anterior cingulate, and anterior insula; second, increases in frontoparietal attention and executive control networks and in the cerebellum; finally, decreases in the default mode network. These results were largely maintained after excluding eye movement-based fMRI changes. Our findings provide evidence that the neurophysiology of consciousness is complex even without overt report, involving multiple cortical and subcortical networks overlapping in space and time.

Multistability, perceptual value, and internal foraging

Substantial experimental, theoretical, and computational insights into sensory processing have been derived from the phenomena of perceptual multistability-when two or more percepts alternate or switch in response to a single sensory input. Here, we review a range of findings suggesting that alternations can be seen as internal choices by the brain responding to values. We discuss how elements of external, experimenter-controlled values and internal, uncertainty- and aesthetics-dependent values influence multistability. We then consider the implications for the involvement in switching of regions, such as the anterior cingulate cortex, which are more conventionally tied to value-dependent operations such as cognitive control and foraging.

Theories of consciousness

Recent years have seen a blossoming of theories about the biological and physical basis of consciousness. Good theories guide empirical research, allowing us to interpret data, develop new experimental techniques and expand our capacity to manipulate the phenomenon of interest. Indeed, it is only when couched in terms of a theory that empirical discoveries can ultimately deliver a satisfying understanding of a phenomenon. However, in the case of consciousness, it is unclear how current theories relate to each other, or whether they can be empirically distinguished. To clarify this complicated landscape, we review four prominent theoretical approaches to consciousness: higher-order theories, global workspace theories, re-entry and predictive processing theories and integrated information theory. We describe the key characteristics of each approach by identifying which aspects of consciousness they propose to explain, what their neurobiological commitments are and what empirical data are adduced in their support. We consider how some prominent empirical debates might distinguish among these theories, and we outline three ways in which theories need to be developed to deliver a mature regimen of theory-testing in the neuroscience of consciousness. There are good reasons to think that the iterative development, testing and comparison of theories of consciousness will lead to a deeper understanding of this most profound of mysteries.

Perceptual filling-in dispels the veridicality problem of conscious perception research

Conscious perceptual experiences are expected to correlate with content-specific brain activity. A veridicality problem arises when attempting to disentangle unconscious and conscious brain processes if conscious perceptual contents accurately match the physical nature of the stimulus. We argue that perceptual filling-in, a phenomenon whereby visual information inaccurately spreads across visual space, is a promising approach to circumvent the veridicality problem. Filling-in generates non-veridical although unambiguous percepts dissociated from stimulus input. In particular, the radial uniformity illusion induces a filling-in experience between a central disk and the surrounding periphery. We discuss how this illusion facilitates both the detection of neurophysiological responses and subjective phenomenological monitoring. We report behavioral effects from a large-sample (n = 200) psychophysics study and examine key stimulus parameters that drive the conscious filling-in experience. We propose that these data underpin future hypothesis-driven studies of filling-in to further delineate the neural mechanisms of conscious perception.

Capacity for consciousness under ketamine anaesthesia is selectively associated with activity in posteromedial cortex in rats

It remains unclear how specific cortical regions contribute to the brain's overall capacity for consciousness. Clarifying this could help distinguish between theories of consciousness. Here, we investigate the association between markers of regionally specific (de)activation and the brain's overall capacity for consciousness. We recorded electroencephalographic responses to cortical electrical stimulation in six rats and computed Perturbational Complexity Index state-transition (PCIST), which has been extensively validated as an index of the capacity for consciousness in humans. We also estimated the balance between activation and inhibition of specific cortical areas with the ratio between high and low frequency power from spontaneous electroencephalographic activity at each electrode. We repeated these measurements during wakefulness, and during two levels of ketamine anaesthesia: with the minimal dose needed to induce behavioural unresponsiveness and twice this dose. We found that PCIST was only slightly reduced from wakefulness to light ketamine anaesthesia, but dropped significantly with deeper anaesthesia. The high-dose effect was selectively associated with reduced high frequency/low frequency ratio in the posteromedial cortex, which strongly correlated with PCIST. Conversely, behavioural unresponsiveness induced by light ketamine anaesthesia was associated with similar spectral changes in frontal, but not posterior cortical regions. Thus, activity in the posteromedial cortex correlates with the capacity for consciousness, as assessed by PCIST, during different depths of ketamine anaesthesia, in rats, independently of behaviour. These results are discussed in relation to different theories of consciousness.

Decoding rapidly presented visual stimuli from prefrontal ensembles without report nor post-perceptual processing

The role of the primate prefrontal cortex (PFC) in conscious perception is debated. The global neuronal workspace theory of consciousness predicts that PFC neurons should contain a detailed code of the current conscious contents. Previous research showed that PFC is indeed activated in paradigms of conscious visual perception, including no-report paradigms where no voluntary behavioral report of the percept is given, thus avoiding a conflation of signals related to visual consciousness with signals related to the report. Still, it has been argued that prefrontal modulation could reflect post-perceptual processes that may be present even in the absence of report, such as thinking about the perceived stimulus, therefore reflecting a consequence rather than a direct correlate of conscious experience. Here, we investigate these issues by recording neuronal ensemble activity from the macaque ventrolateral PFC during briefly presented visual stimuli, either in isolated trials in which stimuli were clearly perceived or in sequences of rapid serial visual presentation (RSVP) in which perception and post-perceptual processing were challenged. We report that the identity of each stimulus could be decoded from PFC population activity even in the RSVP condition. The first visual signals could be detected at 60 ms after stimulus onset and information was maximal at 150 ms. However, in the RSVP condition, 200 ms after the onset of a stimulus, the decoding accuracy quickly dropped to chance level and the next stimulus started to be decodable. Interestingly, decoding in the ventrolateral PFC was stronger compared to posterior parietal cortex for both isolated and RSVP stimuli. These results indicate that neuronal populations in the macaque PFC reliably encode visual stimuli even under conditions that have been shown to challenge conscious perception and/or substantially reduce the probability of post-perceptual processing in humans. We discuss whether the observed activation reflects conscious access, phenomenal consciousness, or merely a preconscious bottom-up wave.