Brain Inspired
BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics
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Quick takeaways
- The tension between neuroscience and physics reveals differing interpretations of time, highlighting the need for collaborative discussions on these concepts.
- Integrated Information Theory challenges convention by suggesting consciousness may exist beyond biological constraints, though it faces scrutiny for its scientific foundations.
- Research utilizing organotypic brain slices indicates that neural circuits inherently process timing, demonstrating this function is fundamental across various brain functions.
Deep dives
Tension Between Physics and Neuroscience
There exists a notable tension between the fields of physics and neuroscience that leads to mutual blame concerning their differing interpretations of reality. Neuroscientists often assert that the universe reflects a presentist perspective, arguing that time flows and changes, contrasting with the more static view offered by certain physics theories. This disagreement invites scientists from both disciplines to engage in discussions about the nature of time, consciousness, and how these concepts might be reconciled. The conversation points to the importance of understanding these differences to foster collaboration and cross-pollination of ideas between the two fields.
Integrated Information Theory (IIT) and Consciousness
Integrated Information Theory (IIT) proposes that certain configurations of matter can be conscious, positioning itself as a fundamental theory of physics rather than a strictly neuroscientific one. This approach contends that consciousness is not tied solely to biological processes, allowing for the possibility that various forms of matter may possess consciousness. However, IIT faces criticism, with many scientists arguing that its principles do not align well with the existing foundational laws of physics, rendering it somewhat unscientific. The controversy surrounding IIT emphasizes the need for a more cohesive framework that can integrate consciousness with established scientific principles.
Timing: An Intrinsic Property of Neural Circuits
The ability for neural circuits to implement timing as a fundamental function is proposed, arguing against the idea that timing is merely a specialized function confined to certain brain regions. Instead, the argument suggests that timing is an intrinsic characteristic of all neural circuits, demonstrating its importance across various brain activities. Recent research using organotypic brain slices has revealed that these circuits can learn to predict timing-based stimuli, indicating that they possess a foundational capacity to process temporal information. This finding highlights the potential of neural circuits to engage with time as an essential aspect of their operational dynamics.
The Role of Organotypic Brain Slices in Neuroscience
Organotypic brain slices serve as a vital tool for studying neural dynamics, bridging the gap between traditional brain slices and organoids. These slices are cultured from an organism and allowed to settle into a homeostasis similar to their state in an intact brain before experimental manipulation. This method allows researchers to examine intrinsic properties of neural circuits while maintaining a closer representation of brain functions than standard techniques. Researchers employ optogenetics within these slices to train the circuits to predict stimulus timing, providing insights into the computational capabilities of neural networks.
AI Divergence from Neuroscience Principles
The conversation explores the divergence between artificial intelligence (AI) development and neuroscience, indicating that AI has progressed independent of neuroscientific principles. While AI has leveraged certain aspects of neuroscience in its foundational algorithms, there is a growing concern that the two fields are evolving in dramatically different directions, particularly in how they address temporal processing. The rise of transformer models, which do not rely on timing as part of their architecture, exemplifies this divergence and raises questions about the future intersection between AI and neuroscience. Understanding this relationship may be critical in determining how AI can further evolve and integrate insights from biological intelligence.
Consciousness and Biological Processes
The discussion highlights the idea that consciousness is inherently linked to biological processes that unfold over time, suggesting that time plays a crucial role in how consciousness is defined and experienced. Time is conceptualized not just as a measurement but as an essential component of living experiences, shaping how cognitive processes are understood. This perspective diverges from Integrated Information Theory, which posits that consciousness can exist in static states, underscoring a need for further exploration of consciousness as an evolving biological phenomenon. Acknowledging the temporal aspect of consciousness could lead to new avenues of understanding its fundamental nature and its implications for AI, as well.
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Dean Buonomano runs the Buonomano lab at UCLA. Dean was a guest on Brain Inspired way back on episode 18, where we talked about his book Your Brain is a Time Machine: The Neuroscience and Physics of Time, which details much of his thought and research about how centrally important time is for virtually everything we do, different conceptions of time in philosophy, and how how brains might tell time. That was almost 7 years ago, and his work on time and dynamics in computational neuroscience continues.
One thing we discuss today, later in the episode, is his recent work using organotypic brain slices to test the idea that cortical circuits implement timing as a computational primitive it's something they do by they're very nature. Organotypic brain slices are between what I think of as traditional brain slices and full on organoids. Brain slices are extracted from an organism, and maintained in a brain-like fluid while you perform experiments on them. Organoids start with a small amount of cells that you the culture, and let them divide and grow and specialize, until you have a mass of cells that have grown into an organ of some sort, to then perform experiments on. Organotypic brain slices are extracted from an organism, like brain slices, but then also cultured for some time to let them settle back into some sort of near-homeostatic point - to them as close as you can to what they're like in the intact brain... then perform experiments on them. Dean and his colleagues use optigenetics to train their brain slices to predict the timing of the stimuli, and they find the populations of neurons do indeed learn to predict the timing of the stimuli, and that they exhibit replaying of those sequences similar to the replay seen in brain areas like the hippocampus.
But, we begin our conversation talking about Dean's recent piece in The Transmitter, that I'll point to in the show notes, called The brain holds no exclusive rights on how to create intelligence. There he argues that modern AI is likely to continue its recent successes despite the ongoing divergence between AI and neuroscience. This is in contrast to what folks in NeuroAI believe.
We then talk about his recent chapter with physicist Carlo Rovelli, titled Bridging the neuroscience and physics of time, in which Dean and Carlo examine where neuroscience and physics disagree and where they agree about the nature of time.
Finally, we discuss Dean's thoughts on the integrated information theory of consciousness, or IIT. IIT has see a little controversy lately. Over 100 scientists, a large part of that group calling themselves IIT-Concerned, have expressed concern that IIT is actually unscientific. This has cause backlash and anti-backlash, and all sorts of fun expression from many interested people. Dean explains his own views about why he thinks IIT is not in the purview of science - namely that it doesn't play well with the existing ontology of what physics says about science. What I just said doesn't do justice to his arguments, which he articulates much better.
- Buonomano lab.
- Twitter: @DeanBuono.
- Related papers
- BI 204 David Robbe: Your Brain Doesn’t Measure Time
Read the transcript.
0:00 - Intro 8:49 - AI doesn't need biology 17:52 - Time in physics and in neuroscience 34:04 - Integrated information theory 1:01:34 - Global neuronal workspace theory 1:07:46 - Organotypic slices and predictive processing 1:26:07 - Do brains actually measure time? David Robbe
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