Unsupervised Thinking
a podcast about neuroscience, artificial intelligence and science more broadly

Tuesday, October 31, 2017

Episode 26: The Concept of Coding - Part 1

The concept of "coding," along with language referencing it, is abundant in neuroscience whether describing sensory systems, cognition, or motor control. The notion that neurons encode information is so core to neuroscience it is almost difficult to imagine the field without it. In the first part of this two-part discussion on coding, we talk about the origins of the coding concept. We start with some of the early experimental work that demonstrated the most basic response properties of neurons. We then delve into a conference report from the 60's that summarized the state of the field at that time and find it (depressingly?) relevant for today. In particular, the focus at that time on coding as only an imperfect metaphor is contrasted with its perhaps outsized role in modern work. We ask things like: When is the metaphor working, and when is it stretched beyond recognition? What qualities does a code need to have to be a candidate for the "neural code"? and If there is a neural code, who's reading it out? By the end, Grace freaks out about how abstract "information processing" is, and Josh and Conor claim the whole world is just one big information processing machine.

We read:
Neurosciences Research Program report on Neural Coding

And mentioned:
List of recommended readings on coding
Our fMRI episode

Upcoming readings for Part 2:
Neural Representation and the Cortical Code
Is coding a relevant metaphor for the brain?

To listen to (or download) this episode, (right) click here or use the player below

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

Sunday, October 1, 2017

Episode 25: What Can Eye Movements Tell Us About The Mind?

You move your eyes several times a second, making choices about what to attend to without even noticing. That is a lot of behavioral data that scientists could use to understand underlying computations, preferences, memories, and intentions. On this episode, we talk about just such endeavors to understand cognition by monitoring eye movements. Eye movements are a comparatively easy thing to measure (though as we discuss, some of the older methods seemed like torture devices), and can be used in a wide range of settings: in animals and babies, in the lab or in the wild. In this episode, Josh regals us with tales of using a modern eye-tracking device at a conference, and we talk about the basic findings you can discover from that and exactly how surprising or interesting they are. We then get into how tasks influence eye movements and the many forms of memory that eye movements can measure, including differences between novices and experts. We top it all off with a delightful study about looking at porn, and some speculations about how eye-tracking could be used in the future. 
We read:

Eye movements in natural behavior

Worth a Glance: Using Eye Movements to Investigate the Cognitive Neuroscience of Memory

Sex differences in viewing sexual stimuli: An eye-tracking study in men and women

A Breadth-First Survey of Eye Tracking Applications 

And watched some cool eye-tracking videos!
What Does a Pianist See? 
The Science of Dating

To listen to (or download) this episode, (right) click here

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

Monday, August 28, 2017

Episode 24: Social Neuroscience Research

For this episode, special guest Nancy Padilla (E5: Neural Oscillations) returns to talk about a topic she now studies: social neuroscience. We get into the methods this rather new field uses to probe the neural processes behind social interaction, including the inherent difficulties in studying such a complex subject. We go from special pathways for bottom-up social processing such as smells and facial recognition to ideas about theory of mind and cooperation. In the process, we hit on the mirror neuron system, simultaneous dual-brain recordings, and the role of philosophy in the field. Two common questions throughout are: (1) are humans unique amongst animals? and (2) is social processing unique amongst neuroscience topics? Ultimately, we try to discover if social neuroscience is greater than the sum of its parts.

We read:
Conceptual Challenges and Directions for Social Neuroscience

Brain Basis of Human Social Interaction: From Concepts to Brain Imaging

Brain-to-Brain coupling: A mechanism for creating and sharing a social world

And mentioned:
Episode 10: Brain Size

To listen to (or download) this episode, (right) click here or use the player below

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

Wednesday, July 26, 2017

Episode 23: What Can Neuroscience Say About Consciousness?

For this episode, we try to de-thorn one of the thorniest topics in neuroscience: consciousness! Starting with the (not so) simple task of defining the c-word, we first lay out our own definitions but end up relying on the work of philosopher David Chalmers (easy and hard problems of consciousness, philosophical zombies). Then, after establishing the myriad of reasons why science can't actually study consciousness, we get into its attempts to do so. Specifically, we talk about studies on anaesthesia and the role of optical illusions in probing conscious perception. After that we go through a laundry list of all kinds of theories/models of consciousness put forth by neuroscientists, psychologists, and (ugh) physicists. Throughout, Josh complains about people saying they have "heightened consciousness",  Conor advocates a lot of drug use (for science), and we discuss the politics of urination. If you're confused by any of this, no worries, Conor is too.

We read:
Scholarpedia: Neuronal Correlates of Consciousness
Scholarpedia: Models of Consciousness 

Neural Correlates of Consciousness (sensory paper by Rees)

Neural correlates of consciousness during general anesthesia using functional magnetic resonance imaging (fMRI)

And mentioned:
20 Years of ASSC: are we ready for its coming of age? (thanks to @tweetsatpreet for pointing us to this journal)

To listen to (or download) this episode, (right) click here.

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

Wednesday, June 21, 2017

Episode 22: Underdeterminacy & Neural Circuits

Sloppiness, stiffness, and stomatogastric ganglion! This episode on underdeterminacy in neural circuits will introduce you to all these topics, as well as to special guest Alex Williams! To start, we take you way back to algebra class with a refresher on what makes a system "underdetermined" (essentially, more unknowns than constraints). There are two ways this can be a problem in neuroscience: (1) neural circuit modelers don't have enough data to constrain their models, and (2) biology itself is underconstrained, leading to differences across individuals within a species. We talk about both of these issues separately, the ways in which they interact, and the practical effects they have for the study of the nervous system. The first topic spurs a broad discussion on the philosophy of modelling and the potential pitfalls that careful scientists need to avoid. To explore this in more detail, we discuss an excellent modelling paper on the oculor-motor system that demonstrates ways in which models should guide experiments. For the latter topic, we delve into Eve Marder's work on crustaceans, wherein she carefully documents the incredible variety across individuals. Having worked in Eve's lab himself, Alex provides expertise and anecdotes on this topic throughout!

We read:
Computational models in the age of large datasets
A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit

And mentioned:
Our episode on "Does Neuroscience Need More Behavior?"
Why Are Computational Neuroscience and Systems Biology So Separate?
James Sethna's work on sloppiness 

Also potentially of interest:
Grace's blog post on Eve Marder's work

To listen to (or download) this episode, (right) click here.

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

Wednesday, May 24, 2017

Episode 21: Understanding fMRI

To much of the world, the face of neuroscience is an image of a brain with small colored blobs on it. Those images come from functional magnetic resonance imaging (fMRI), a technology that's made a big splash in its relatively short tenure. For this episode, we delve into fMRI and what scientists do with the data it produces. To start, we review the technology behind MRI and fMRI. We get into the thorny issue of relating the BOLD signal recorded from fMRI with actual neural activity, and what's been learned from animal studies that have looked at both simultaneously. After that we talk stats: particularly the trouble with traditional "voxel"-wise comparison methods and putting all your eggs in one basket (or in separate, but similar, baskets?). Approaches to fMRI analysis are quickly evolving however, and so we discuss multi-voxel pattern analysis, comparing across individual brains, real time-analysis, mind reading, and lie detecting. Finally, we turn a little more philosophical and ask "What does it mean to measure information in the brain?". Is what an experimenter can see in these colored patterns even relevant to the brain itself?? We give examples of when it's not.

We read:
Interpreting the BOLD Signal
Computational Approaches to fMRI Analysis
Is Neuroimaging Measuring Information in the Brain?

And mentioned:
Our episode on Neural Oscillations (wherein we try to understand what the local field potential/"LFP" is)
A mind-reading-style paper on movie reconstruction by Jack Gallant
Stefano Fusi's paper on decoding information that the animal doesn't use

To listen to (or download) this episode, (right) click here

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

Wednesday, April 26, 2017

Episode 20: Studies on the State of Science

Sometimes scientists decide to turn their tools of inquiry inward to understand their own fields and behaviors. For our 20th episode, we're diving into this meta-science by reading some papers about papers written by scientists studying scientists. In particular, we start with a commentary discussing the increasing size of scientific teams, and what that means for credit assignment. Do we need to move to a more Hollywood approach by highlighting specific achievements in different roles? Also, when will we address the fact that most young researchers on these teams will not have a career in academic science? We then get into a modeling study that aims to show how incentivizing the publication of novel results can ultimately lead to a widespread decrease in scientific quality. This raises questions of whether individuals or the system is to blame for high rates of shoddy publications. We then touch on a small experiment that the conference NIPS (Neural Information Processing Systems) performed on their peer review system, showing that (spoiler alert!, or probably not if you've been subjected to peer review...) the process can appear somewhat random. Finally, we go over a report that tracked trends in neuroscience research over the past ten years. We find that a meta-study of a field can seem very different from the view inside of it. Finally, we mention how studies of science done by scientists differ from those done by the humanities, and how both may be of use.    

We read:
Together We Stand
The Natural Selection of Bad Science
The NIPS Experiment
The Changing Landscape of Neuroscience Research, 2006–2015: A Bibliometric Study

To listen to (or download) this episode, (right) click here.

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com)