What Blindsight Means for the Neural Correlates of Consciousness

Do perceptual experiences always inherit the content of their neural correlates? Most scientists and philosophers working on perception say 'yes'. They hold the view that an experience's content just is (i.e.is identical to) the content of its neural correlate. This paper presses back against this view, while trying to retain as much of its spirit as possible. The paper argues that type-2 blindsight experiences are plausible cases of experiences which lack the content of their neural correlates. They are not experiences of the stimuli or stimulus properties prompting them, but their neural correlates represent these stimulus properties. The argument doesn't depend on any special view of what it is for an experience to be of a stimulus or stimulus property. The upshot is that, even assuming there is a deep relationship between experiential content and neural content, that relationship is more complex than simple identity.

The search for the NCC: Progress and challenges

Twenty years ago, Thomas Metzinger published the book "The Neural Correlates of Consciousness" amassing the state of knowledge in the field of consciousness studies at the time from philosophical and empirical perspectives. On the occasion of the 20th anniversary of this impactful publication, we review the progress the field has made since then and the important methodological challenges it faces. A tremendous number of empirical studies have been conducted, which has led to the identification of many candidate neural correlates of consciousness. Yet, this tremendous amount of work has not unraveled a consensual account of consciousness as of now. Many questions, some already raised twenty years ago, remain unanswered, and an enormous proliferation of theories sharply contrasts with the scarcity of compelling data and methodological challenges. The contrastive method, the foundational method used to study the neural correlate of consciousness (NCC), has also been called into question. And while awareness in the community of its shortcomings is widespread, few concrete attempts have been made to go beyond it and/or to revise existing theories. We propose several methodological shifts that we believe may help to advance the quest of the NCC program, while remaining uncommitted to any specific theory: (1) the currently prevalent “contrastive method” should lose its monopoly in favor of methods that attempt to explain the phenomenology of experience; (2) experimental data should be shared in centralized, multi-methods databases, transcending the limitations of individual experiments by granting granularity and power to generalize findings and “distill” the NCC proper; (3) the explanatory power of theories should be directly pitted against each other to overcome the non-productive fractioning of the field into insular camps seeking confirmatory evidence for their theories. We predict these innovations might enable the field to progress towards the goal of explaining consciousness.

You can't always get what you want

The predictive processing framework has gained significant popularity across disciplines investigating the mind and brain. In this article we critically examine two of the recently made claims about the kind of headway that the framework can make in the neuroscientific and philosophical investigation of consciousness. Firstly, we argue that predictive processing is unlikely to yield significant breakthroughs in the search for the neural correlates of consciousness as it is still too vague to individuate neural mechanisms at a fine enough scale. Despite its unifying ambitions, the framework harbors a diverse family of competing computational models which rely on different assumptions and are under-constrained by neurological data. Secondly, we argue that the framework is also ill suited to provide a unifying theory of consciousness. Here, we focus on the tension between the claim that predictive processing is compatible with all of the leading neuroscientific models of consciousness with the fact that most attempts explaining consciousness within the framework rely heavily on external assumptions.

A structural constraint on neural correlates of consciousness

Researchers on the neural correlates of consciousness (NCC) need to distinguish mere statisticalNCCs from NCCs proper. Some neural events may be co-occurrent, probabilistically coupled,or coincidental with a type of conscious experience but lack any deeper connection to it, whilein other cases, the relation between neural states and a type of experience hints at a strongmetaphysical relation, which distinguishes such NCCs proper from mere statistical NCCs. In orderto address this issue of how to distinguish NCCs proper from mere statistical NCCs, we proposea position we call neurophenomenal structuralism. The position hinges on the uncontroversialidea that phenomenal experiences relate to each other in degrees of similarity and difference.These complex structures are used to identify and individuate experiences in the methods ofneuroscience, psychophysics, and phenomenology. Such individuation by structure leads to phenomenalholism, which has implications for how to investigate consciousness neuroscientificallyand generates a constraint by which we can distinguish NCCs proper from mere statistical NCCs:the structural similarity constraint. Neural activation must preserve the structure governing thedomain of experiences it is associated with in order to count as that domain’s NCC proper. Anyactivation that fails to preserve phenomenal structure fails to be an NCC proper. We illustratehow this constraint works with a study by Brouwer & Heeger (2009) as an example.

Finding the NCCs will not solve all our problems

Subjective experience has often taken center stage in debates between competing conceptual theories of the mind. This is also a central object of concern in the empirical domain, and especially in the search for the neural correlates of consciousness (NCCs). By now, most of the competing conceptual theories of consciousness have become aligned with distinct hypotheses about the NCCs. These hypotheses are usually distinguished by reference to their proposed location of the NCCs. This difference in hypothesized location of the NCCs has tempted participants in these debates to infer that evidence indicating the location of the NCCs in one or the other brain region can be taken as direct evidence for or against a given conceptual theory of consciousness. We argue that this is an overestimation of the work finding the NCCs can do for us, and that there are principled reasons to resist this kind of inference. To show this we point out the lack of both an isomorphism and a homomorphism between the conceptual frameworks in which most theories are cached, and the kind of data we can get from neuroimaging. The upshot is that neural activation profiles are insufficient to distinguish between competing theories in the conceptual domain. We suggest two ways to go about ameliorating this issue.

The neural correlates of consciousness under the free energy principle: From computational correlates to computational explanation

How can the free energy principle contribute to research on neural correlates of consciousness, and to the scientific study of consciousness more generally? Under the free energy principle, neural correlates should be defined in terms of neural dynamics, not neural states, and should be complemented by research on computational correlates of consciousness – defined in terms of probabilities encoded by neural states. We argue that these restrictions brighten the prospects of a computational explanation of consciousness, by addressing two central problems. The first is to account for consciousness in the absence of sensory stimulation and behaviour. The second is to allow for the possibility of systems that implement computations associated with consciousness, without being conscious, which requires differentiating between computational systems that merely simulate conscious beings and computational systems that are conscious in and of themselves. Given the notion of computation entailed by the free energy principle, we derive constraints on the ascription of consciousness in controversial cases (e.g., in the absence of sensory stimulation and behaviour). We show that this also has implications for what it means to be, as opposed to merely simulate a conscious system.

Ask and You Shall Receive: A closer look on unsolved consciousness issue

Although there are numerous views about the concept of consciousness, no consensus exists regarding the meaning. However, with the aid of the latest neuroscientific developments, the misleading obstacles related to consciousness have been removed. Over the last few decades, neuroscientific efforts in determining the function of the brain and merging these findings with philosophical theories, have brought a more comprehensive perception of the notion of consciousness. In addition to metaphysical/ontological views of consciousness e.g., higher-order theories, reflexive theories, and representationalist theories, there are some brain directed topics in this matter which include but not are limited to neural correlates of consciousness (NCC), brain loop connectivity, and lateralization. This narrative review sheds light on cultural and historical aspects of consciousness in old and middle ages and introduces some of the prominent philosophical discussions related to mind and body. Also, it illustrates the correlation of brain function with states of consciousness with a focus on the roles of function and connectivity.

Implications of Noise on Neural Correlates of Consciousness: A Computational Analysis of Stochastic Systems of Mutually Connected Processes

Random fluctuations in neuronal processes may contribute to variability in perception and increase the information capacity of neuronal networks. Various sources of random processes have been characterized in the nervous system on different levels. However, in the context of neural correlates of consciousness, the robustness of mechanisms of conscious perception against inherent noise in neural dynamical systems is poorly understood. In this paper, a stochastic model is developed to study the implications of noise on dynamical systems that mimic neural correlates of consciousness. We computed power spectral densities and spectral entropy values for dynamical systems that contain a number of mutually connected processes. Interestingly, we found that spectral entropy decreases linearly as the number of processes within the system doubles. Further, power spectral density frequencies shift to higher values as system size increases, revealing an increasing impact of negative feedback loops and regulations on the dynamics of larger systems. Overall, our stochastic modeling and analysis results reveal that large dynamical systems of mutually connected and negatively regulated processes are more robust against inherent noise than small systems.