“If understanding everything we need to know about the brain is a mile, how far have we walked?”

• Why neuroscience is harder than physics
• Course overview
• The connectome and beyond
• Does neuroscience need behavior? Does behavioral science need the brain?

• What is the state…
  • Of the world (\(W\))
  • Of the organism
    • Body (\(B\))
    • Nervous system (\(N\))
    • Mind (\(M\))

• \(W\), \(B\), \(N\) more or less directly

• indirectly
• Via \(N\), \(B\), \(W\) (+ prior beliefs/knowledge)
• Examples?

• Components
• Interactions
• Forces/influences
• Boundaries
• Inputs/outputs/processes

• “Behave” or change state across time
• Return to starting state
• Appear to be regulated, controlled, influenced by feedback loops
• \(B(t+1) = f(W(t), B(t), N(t), M(t))\)

• Single parts -> multiple functions
• Single functions -> multiple parts

• Change structure/function over time
• Biological systems not “designed” like human-engineered ones
• Hard to measure what is being exchanged, what is being controlled

• Master fundamentals of neuroscientific concepts and facts
• Prepare to read primary source literature in behavioral, cognitive, affective, and clinical neuroscience

https://psu-psychology.github.io/psy-511-scan-fdns-2020/

• What is the basic organizational plan of the nervous system?
• How do neurons work?
• How do neurons connected in networks achieve behavioral goals?
• How does the nervous system develop? How has it evolved?
• How do disorders of the mind reveal themselves in the nervous system?

• Brain architecture (neuroanatomy)
• Brain function (neurophysiology)
• Brain communication (neurochemistry)
• Changes over evolutionary and developmental time

• The nervous system as an information processing system

Inputs

• From environment, body, brain

Processing

• Current inputs + brain state + body state + possible future states…
• Stored information
• Physiological & behavioral goals

Outputs

• To brain, body, environment

Swanson, L. W., & Lichtman, J. W. (2016). From Cajal to Connectome and Beyond. Annual Review of Neuroscience, 39, 197–216.

https://via.hypothes.is/https://psu-psychology.github.io/psy-511-scan-fdns-2020/pdf/swanson-2016.pdf

• Form <> function
• “What differs between species is the architecture of nervous systems….”
• Connectomes at different levels of analysis

“The so-called explanatory gap (Horgan 1999) between what we can know and what we want to understand is not necessarily made smaller by more information. Rather, such omics information pushes neuroscience into a different realm where information rather than ideas is the currency.”

(Swanson & Lichtman, 2016)

“In this realm, a detailed, bottom-up description of a biological system is mined for whatever conceptual insights might be revealed rather than top-down concepts of what we care about being used as a setup for experiments. In this sense, the data give us a more accurate view of the way things are and, at the same time, push us away from intelligible, albeit facile, answers to the enduring puzzles of the brain.”

(Swanson & Lichtman, 2016)

Krakauer, J. W., Ghazanfar, A. A., Gomez-Marin, A., MacIver, M. A., & Poeppel, D. (2017). Neuroscience needs behavior: Correcting a reductionist bias. Neuron, 93(3), 480–490. https://dx.doi.org/10.1016/j.neuron.2016.12.041.

https://via.hypothes.is/https://psu-psychology.github.io/psy-511-scan-fdns-2020/pdf/krakauer-et-al-2017.pdf

• Questions ‘often tacit…belief in the reductionist program for understanding the link between brain and behavior’
• Behavior -> understanding; neural inverventions -> causality
• Marr’s 3 levels (computation; algorithm; implementation)

• Psychology is harder than physics
• Connectomics and beyond
• Neuroscience needs behavior; behavioral science needs neuroscience

1. Pick two papers you want to read and (better) understand

• Email me APA formatted citation (with DOIs)
• Indicate three concepts/terms you are especially interested in understanding

2. Choose a behavior or mental state you want to (better) understand

• Take an information processing perspective and briefly sketch out (in no more than a short paragraph) the main inputs, outputs, and computations involved.
• When thinking about outputs make sure to distinguish between behaviors (e.g., movements, facial expressions, vocalizations) and physiological states (e.g., changes in heart rate, hormone concentrations in the blood, etc.)