University Studies 15A:

Consciousness I

A Neuroscientific Framework for Exploring

Consciousness

Consciousness

The Easy Version: awareness of the world

The Harder Version: the qualities of first-person experience

The Hard Version: the fact of first-person experience

Consciousness and Neuroscience

The Easy Version: awareness of the world

Challenge:

1. Explain the processing of sensory experience2. Explain how awareness works: what factors and brain

functions control it

Strategy: Work from the easy toward the hard

It turns out, however, that awareness is not simple and entails all of the other systems of the brain.

Consciousness and Neuroscience

The problem of Awareness brings us to:

The Harder Version: the qualities of first-person experience

Challenge:

1. Understand the “self” in the brain: systems for emotion, intention, decision and control of action

2. Explain the “first-person” quality of experience3. Explain the link between this first-person self and other

systems

Consciousness and Neuroscience

The Hard Version: the fact of first-person experience

If we can do all that, we might have some significant insight into

The next few weeks will present an overview of the state of the art:

1. Current models of general brain function2. Current understanding of the relation of perception to

awareness and memory3. Current understanding of the relation of memory and emotion4. Current models of consciousness that integrate it all

What is striking is how young neuroscience is.

Neuroscience had to wait for the synthesis of basic science (biology, chemistry, and neuroanatomy)foundational modelsexploratory tools

There has long been a biology of the brain and nervous system.Since the 19th century neurology, a medical disciple, has focused

on disorders of the nervous system.

Neuroscience is something different: an interdisciplinary study of the nervous system focused primarily on the brain, its systems, and their functions.

Neuroscience

Some Historical ContextPeople had known of “cells” (so-called because they reminded Robert Hooke of monks’ cells) since 1665 with the advent of the microscope.

Still, they were not sure about cortical “cells” which looked like they were one tangled, continuous mass.

However, only in 1839 did Theodor Schwann and Matthias Jakob Schleiden realize that all living structures are built from cells (or their products.)

In 1899, new stains for cells developed by Camillo Golgi allowed Santiago Ramón y Cajal to carefully study pigeon brains and see the variety of cell structures.

People in the late 1800s also knew that injuries to certain areas of the brain led to particular cognitive impairments.

Ever since the 1850s, they also knew that electricity somehow traveled along the nervous system and was a key to neural function.However, it was only in 1952 that Hodgkin and Huxley realized how action potentials traveled along the axon in a wave of depolarization.

Then in 1962 Bernard Katz worked out the mechanism of neurotransmitter release across the synaptic junction.

At the larger scale of the nervous system as a whole:

Meanwhile, biologists had learned much about the anatomy of the brain: what areas seemed to form discrete units and what units were connected to one another by neural pathways. They knew the layers of the cortex and the types of neurons in the layers.But fundamental questions of what was going on—how systems of neurons cooperated to process sensory data, how memory was structured, what memory was—remained opaque.

The revival of neural network modeling in the 1980 marked a deep change in our thinking about the brain.

People knew that whatever the brain was doing, it was using massively parallel systems, and that this parallelism made possible the “100 step rule.”

The question was, how was this done? What was being done?

Some pieces of the puzzle were there by the 1960s.

That is, a synapse fires in about a millisecond, and most observable reactions take 100 milliseconds. Whatever computations occurred in the brain could not involve more that 100 steps.

Sadly, in 1969 Minsky and Papert wrote an even more famous paper showing fatal deficiencies in the perceptron, and interest in massively parallel neural networks shrank to almost nothing for fifteen year.

In the 1957 Frank Rosenblatt wrote a famous paper on the “Perceptron,” a type of artificial neural network that used a learning rule related to Hebb’s approach.

As early as 1949, Donald Hebb proposed the idea of synaptic plasticity, that neurons that fired as part of the same sequence became increasingly likely to fire together.

This is the rule of Hebbian learning: “Neurons that fire together wire together.”

To almost nothing….

However, because something like Hebbian learning on a neural network had to be the answer, people plugged away until they found solutions to the problems Minsky and Papert posed.

In 1986 Rumelhart and McClelland published two volumes on “parallel distributed processing” that not only revived the field but led to the models that biologists needed in order to model what the brain was doing both at the level of the synapse and at the level of systems architecture.

We will look at this new understanding of neural processes on Thursday.

By the 1990s, neuroscience had the knowledge of neuro-physiology and the conceptual tools of parallel distributed processing.

By a remarkable coincidence, the first use of functional nuclear magnetic resonance imaging (fMRI) was in 1991.

Since the oxygen level of the blood that fMRI detects spikes from 4-6 seconds (not milliseconds) after neurons fire, temporal accuracy is terrible.

But fMRI lets one see where the neurons are firing. And this has proven invaluable.

So the models and the tools came together in the 1990s, and contemporary neuroscience—drawing on such fields as mathematics, neurobiology, developmental and cognitive psychology, and molecular genetics—was born.

Baars and Gage give us an overview of the current state of understanding of cognitive neuroscience, from their particular points of view (which largely coincide with mine, I confess).

Here is what they propose:

“Primary Emotions”

“Primary Emotions”

“Primary Emotions”

“Primary Emotions”

Sight & Hearing arrive via the thalamus

Visual Cortex

Auditory Cortex

Sensory Cortex

Temporal lobe

“Primary Emotions”

No homunculus.

Attention

Planning& Working Memory

“Primary Emotions”

Organization of Memory:

Relations and Locations

“Primary Emotions”