We seek individuals proficient with the development and testing of novel transcranial magnetic stimulation (TMS) methods to evaluate research questions related to free will, consciousness, sense of agency, and higher brain functions.

Suppose you are on your favorite touchscreen device consciously and deliberately deciding emails to read or delete. In other words, you are consciously and intentionally looking, tapping, and swiping. Now suppose that you are doing this while neuroscientists are recording your brain activity. Eventually, the neuroscientists are familiar enough with your brain activity and behavior that they run an experiment with subliminal cues which reveals that your looking, tapping, and swiping seem to be determined by a random switch in your brain. You are not aware of it, or its impact on your decisions or movements. Would these predictions undermine your sense of free will? Some have argued that it should. Although this inference from unreflective and/or random intention mechanisms to free will skepticism, may seem intuitive at first, there are already objections to it. So, even if this thought experiment is plausible, it may not actually undermine our sense of free will.

We examine consciousness from the perspective of theoretical computer science (TCS), a branch of mathematics concerned with understanding the underlying principles of computation and complexity, including the implications and surprising consequences of resource limitations. We propose a formal TCS model, the Conscious Turing Machine (CTM). The CTM is influenced by Alan Turing's simple yet powerful model of computation, the Turing machine (TM), and by the global workspace theory (GWT) of consciousness originated by cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, Jean-Pierre Changeux, George Mashour, and others. However, the CTM is not a standard Turing Machine. It’s not the input-output map that gives the CTM its feeling of consciousness, but what’s under the hood. Nor is the CTM a standard GW model. In addition to its architecture, what gives the CTM its feeling of consciousness is its predictive dynamics (cycles of prediction, feedback and learning), its internal multi-modal language Brainish, and certain special Long Term Memory (LTM) processors, including its Inner Speech and Model of the World processors. Phenomena generally associated with consciousness, such as blindsight, inattentional blindness, change blindness, dream creation, and free will, are considered. Explanations derived from the model draw confirmation from consistencies at a high level, well above the level of neurons, with the cognitive neuroscience literature. Reference. L. Blum and M. Blum, "A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine," PNAS, vol. 119, no. 21, 24 May 2022. https://www.pnas.org/doi/epdf/10.1073/pnas.2115934119

If the mind controls the brain, then there is free will and its corollaries, dignity and responsibility. You are king in your skull-sized kingdom and the architect of your destiny. If, on the other hand, the brain controls the mind, an incendiary conclusion follows: There can be no free will, no praise, no punishment and no purgatory. In this webinar, Professor George Paxinos will discuss his highly respected work on the construction of human and experimental animal brain atlases. He has discovered 94 brain regions, 64 homologies and published 58 books. His first book, The Rat Brain in Stereotaxic Coordinates, is the most cited publication in neuroscience and, for three decades, the third most cited book in science. Professor Paxinos will also present his recently published novel, A River Divided, which was 21 years in the making. Neuroscience principles were used in the formation of charters, such as those related to the mind, soul, free will and consciousness. Environmental issues are at the heart of the novel, including the question of whether the brain is the right ‘size’ for survival. Professor Paxinos studied at Berkeley, McGill and Yale and is now Scientia Professor of Medical Sciences at Neuroscience Research Australia and The University of New South Wales in Sydney.

Polaris Koi (Philosophy) and Jake Gavenas (Neuroscience) begin the seminar by arguing that agentive control is the key requirement for free will, drawing on folk-philosophy findings to support this claim (Gavenas et al., in prep). They explore how two executive control processes that functionally involve consciousness—inhibition and top-down control of attention—connect self-control and free will.

If the mind controls the brain, then there is FREE WILL and its corollaries, dignity and responsibility. You are king in your skull-sized kingdom and the architect of your destiny. If, on the other hand, the brain controls the mind, an incendiary conclusion follows: There can be no FREE WILL, no praise, no punishment and no purgatory. There will be a presentation of the speaker’s novel which, inter alia, is concerned with this question: 21 year in the making this is the first presentation of A River Divided (environmental genre)

Self-control is a central aspect of free will. Because self-control is often described in terms of resisting temptations, research on the cognitive neuroscience of free will often focuses on mechanisms of top-down regulation. We argue that this obscures a crucial temporal dimension of free will: now-then regulation. We distinguish now-then regulation from top-down regulation, and situate now-then regulation within a broader account of temporally extended agency. In highlighting this temporal dimension of control, we aim to provide a more nuanced account of how motivation informs action over time, different kinds of regulatory processes underlying the planning and execution of action, and the temporal components of reasons-responsiveness.

Integrated information theory (IIT) takes as its starting point phenomenology, rather than behavioral, functional, or neural correlates of consciousness. The theory characterizes the essential properties of phenomenal existence—which is immediate and indubitable. These are translated into physical properties, expressed operationally as cause-effect power, which must be satisfied by the neural substrate of consciousness. On this basis, the theory can account for clinical and experimental data about the presence and absence of consciousness. Current work aims at accounting for specific qualities of different experiences, such as spatial extendedness and the flow of time. Several implications of IIT have ethical relevance. One is that functional equivalence does not imply phenomenal equivalence—computers may one day be able to do everything we do, but they will not experience anything. Another is that we do have free will in the fundamental, metaphysical sense—we have true alternatives and we, not our neurons, are the true cause of our willed actions.

Agent-causal libertarian free will asserts that the conscious agent is the ultimate cause of her own voluntary behavior. A major reason to reject libertarian free will is that it seems incompatible with our current knowledge of physics. In this talk I will argue how quantum processes, specifically non-random collapses of the wavefunction in the human cortex, may enable libertarian free will. I will discuss how this account can be empirically tested.

The COINTOB (conditional intention and integration to bound) model provides a heuristic framework of processes in Libet-style experiments. The model is based on three assumptions. First, brain activation preceding conscious intentions in Libet-style experiments does not reflect an unconscious decision but rather the unfolding of a decision process. Second, the time of conscious decision (W) reflects the moment in time when the decision boundary is crossed. This interpretation of W is consistent with our apparent intuition that we decide in the moment we experience the conscious intention to act. Third, the decision process is configured by conscious intentions that participants form at the beginning of the experiment based on the experimental instruction. Brass and Mele discuss the model, conceptual background for it, and the model’s bearing on free will.

The question of free will has been topical for millennia, especially considering its links to moral responsibility and the ownership of that responsibility. Free will, or volition, is an incredibly complex phenomenon - and cannot easily be reduced to a single empirical paradigm. Roskies (2010) proposes that there are five cognitive aspects to be considered when developing a more complete understanding of volition. These are: intention, initiation, feeling, executive control and decision-making. Decision-making will be the focus of this talk, which steps through aspects of the philosophy of free will; highlights experimental paradigms stemming from the seminal work of Benjamin Libet et al., and proposes machine learning as a promising method in progressing the empirical studies of decision-making and free will.