Chapter 2 Notes: Cognitive Neuroscience (Goldstein, 6e)

Cognitive neuroscience employs multiple levels of analysis, not a single viewpoint.
Each viewpoint adds distinct information, which, when combined, offers a richer understanding of cognition.
Analysis ranges from:
- Chemical reactions
- Single neurons
- Brain structures
- Networks of structures
This multilevel approach helps build a complete picture of how the brain creates mind and behavior.
It mirrors the idea that information processing can be described at various scales, from microscopic to systemic.

Figure 2.1 compares a computer’s CPU to the brain, and the motherboard to the extended nervous system.
The CPU is analogous to the brain, acting as the central processing unit.
The motherboard represents the network connecting different brain regions.
This analogy highlights that complex cognition arises from interactions within a distributed system.
It's like software functioning through integrated hardware and connections.

Figure 2.2 (a) shows Gil perceiving Mariella; Figure 2.2 (b) illustrates memory of the meeting.
Both perception and memory involve physiological processes describable at multiple levels:
- Chemical reactions at the synaptic level
- Activity of single neurons
- Function of entire brain structures
- Coordinated activity of brain networks
This reinforces the idea that cognition can be examined across various scales.
Understanding these levels explains how perception and memory are implemented in the brain.

A knowledge-check exercise asks learners to order levels of analysis from simplest to most complex.
The proposed sequence is:
1. Chemical processes
2. Neurons
3. Nerves (bundles of neurons)
4. Brain structures
5. Groups of brain structures
6. Brain activity
7. Behavior
This progression illustrates the micro to macro scales in neural science.

Historically, the nerve net theory proposed a continuous, undifferentiated network allowing signals to travel in all directions without clear start or end points.
This was akin to a highway network with nonstop, multidirectional signal flow.
Ramon y Cajal challenged this with the neuron doctrine, asserting that:
- Individual nerve cells transmit signals.
- Neurons are not continuously linked but are discrete units.
The neuron doctrine established that discrete neurons communicate via specialized junctions called synapses.

Early figures depicted the nerve net versus a Golgi-stained view, which clearly showed neuron bodies, dendrites, and axons.
Figure 2.4 illustrates the basic components of a neuron in the cortex.
Figure 2.5 details a synapse:
- The space where an axon terminal communicates with a neuron's cell body or dendrite.
- Emphasizes information transfer across specialized structures, neuron-to-neuron.
- Communication occurs via chemical signaling at these synaptic junctions.

A neuron’s signal is an action potential, a rapid electrical impulse.
Information from environmental signals travels along the axon to other neurons’ dendrites.
Microelectrodes placed near axons measure these electrical signals, typically active for about $1 \text{ ms}$ .
Recording an action potential (Figure 2.6) shows chemical and electrical differences between the nerve's resting state and when an impulse passes.

Figure 2.6 details the resting potential:
- The difference in charge across the neuron's membrane when at rest.
- Approximately $V_{\text{rest}} \,=\, -70\text{ mV}$ (inside minus outside).
As the nerve impulse travels, the inside of the membrane becomes more positive (depolarization).
It then returns to the resting, more negative state (repolarization).
This cycle is depicted in Figure 2.6 parts (b)–(d).
Action potentials are often represented as a red band propagating along the axon, illustrating electrical signal transmission.

Figures 2.7 and 2.8 illustrate how multiple action potentials appear when plotted over time.
Key Point: The amplitude (size) of each action potential remains constant.
Researchers measure the rate of firing rather than the size of individual spikes.
A low-intensity stimulus leads to slower firing rates.
A higher-intensity stimulus results in faster firing rates, as shown in Figure 2.8 with three levels of skin pressure.

Neurons communicate at synapses, the microscopic gap between the axon terminal of one neuron and the dendrite or cell body of another.
When an action potential reaches the axon terminal:
- Neurotransmitter-containing vesicles release chemical neurotransmitters into the synapse.
- These neurotransmitters cross the synaptic cleft.
- They bind to specific receptors on the receiving (postsynaptic) neuron.
- This binding modifies the receiving neuron's electrical signal, modulating its activity.

The mind is defined as the system that creates representations of the world, enabling goal-directed action.
The principle of neural representation states that all experiences, thoughts, and perceptions are based on representations within the nervous system.
Cognition arises from specific patterns of neural firing that encode information about the external world and our internal states.

In the 1960s, researchers began recording from single neurons in the primary visual cortex to understand what stimuli cause them to fire.
This research expanded to neurons in higher visual areas and beyond.
They found that many neurons at higher levels respond to complex stimuli, such as geometrical patterns and faces.
Importantly, a given perception or cognitive function often involves distributed activity across multiple cortical regions.
This illustrates the concept of distributed representations, where information is encoded across a network of neurons.

Hubel and Wiesel studied visual stimuli in cats and discovered feature detectors—neurons that respond optimally to specific characteristics of a stimulus (e.g., orientation, movement).
Experience-dependent plasticity explores how brain structure and function change as a result of an individual's experiences.
For example, kittens exposed only to vertical stimuli from birth develop strong perceptual biases for vertical shapes, with their visual cortex having more neurons tuned to vertical orientations.
This demonstrates that perception is actively shaped and refined by the activity of neurons that selectively fire to particular stimulus qualities, highlighting the brain's plastic nature.

Perception is a hierarchical process, moving from lower to higher brain areas.
The ability to recognize complex objects emerges as sensory information is progressively processed through ascending levels of cortical complexity.
Figure 2.12 (not shown) maps the brain regions involved in interpreting stimuli, from simple features to complex objects.
This underscores the concept of hierarchical processing in the brain, where higher-level areas integrate information from lower-level areas.

There are several coding strategies by which neurons represent stimuli:
- Specificity coding: A stimulus is represented by the firing of a neuron specifically tuned to that unique stimulus (e.g., a