1. The Brain and neuron

2. Content Brain Neuron Neural activity Dynamics of Neurons

3. The Brain

4. Understanding Brain Research Matters The more we understand the brain, the better we’ll be able to design instruction to match how it learns best. (P. Wolfe (2001)

5. The Brain

6. Cerebral Cortex – thought, language, reasoning, movement, sensation Corpus Callosum – connects the right and left hemispheres Cerebellum – movement, balance Brainstem – breathing, heart rate

7. Lobes of the Brain

8. Frontal Lobe – personality, planning, emotion, problem solving –Motor cortex - movement –Broca’s area – speech production Parietal Lobe - touch Temporal Lobe – hearing –Inferotemporal Cortex – object recognition –Wernicke’s area – language comprehension Occipital Lobe - vision

10. There is a wide diversity of types of neuron.

11. Multipolar neurons are a commonly described type of neuron. One example is the spinal motor neuron in vertebrates.

12. Types of Neurons SensoryMotor Interneurons

13. Spinal Cord Brain Sensory Neuron Sensory Neurons INPUT From sensory organs to the brain and spinal cord. Drawing shows a somatosensory neuron Vision, hearing, taste and smell nerves are cranial, not spinal

14. Spinal Cord Brain Sensory Neuron Motor Neuron Motor Neurons OUTPUT From the brain and spinal cord To the muscles and glands.

15. Spinal Cord Brain Sensory Neuron Motor Neuron Interneurons Interneurons carry information between other neurons only found in the brain and spinal cord.

16. Structures of a neuron

17. The cell body –Round, centrally located structure –Contains DNA –Controls protein manufacturing –Directs metabolism –No role in neural signaling Contains the cell’s Nucleus

18. Dendrites Information collectors Receive inputs from neighboring neurons Inputs may number in thousands If enough inputs the cell’s AXON may generate an output

19. Dendritic Growth Mature neurons generally can’t divide But new dendrites can grow Provides room for more connections to other neurons New connections are basis for learning

20. Axon The cell’s output structure One axon per cell, 2 distinct parts –tubelike structure branches at end that connect to dendrites of other cells

21. Myelin sheath White fatty casing on axon Acts as an electrical insulator Not present on all cells When present increases the speed of neural signals down the axon. Myelin Sheath

22. How neurons communicate Neurons communicate by means of an electrical signal called the Action Potential Action Potentials are based on movements of ions between the outside and inside of the cell When an Action Potential occurs a molecular message is sent to neighboring neurons

23. Ion concentrations Cell Membrane in resting state K+ Na+ Cl- K+ A- Outside of Cell Inside of Cell Na + Cl-

24. The Cell Membrane is Semi- Permeable

25. Resting Potential At rest the inside of the cell is at -70 microvolts With inputs to dendrites inside becomes more positive if resting potential rises above threshold an action potential starts to travel from cell body down the axon Figure shows resting axon being approached by an AP

26. Depolarization ahead of AP AP opens cell membrane to allow sodium (NA+) in inside of cell rapidly becomes more positive than outside this depolarization travels down the axon as leading edge of the AP

27. Repolarization follows After depolarization potassium (K+) moves out restoring the inside to a negative voltage This is called repolarization The rapid depolarization and repolarization produce a pattern called a spike discharge

28. Finally, Hyperpolarization Repolarization leads to a voltage below the resting potential, called hyperpolarization Now neuron cannot produce a new action potential This is the refractory period

29. Neuron to Neuron Axons branch out and end near dendrites of neighboring cells Axon terminals are the tips of the axon’s branches A gap separates the axon terminals from dendrites Gap is the Synapse Cell Body Dendrite Axon

30. Synapse axon terminals contain small storage sacs called synaptic vesicles –vesicles contain neurotransmitter molecules Sending Neuron Synapse Axon Terminal

31. Neurotransmitter Release Action Potential causes vesicle to open Neurotransmitter released into synapse Locks onto receptor molecule in postsynaptic membrane

32. A chemical synapse between two neurons: Not all synapses are chemical (though most in the human CNS are) Not all synapses involve an axon conveying information to a dendrite

33. Locks and Keys Neurotransmitter molecules have specific shapes positive ions (NA+ ) depolarize the neuron negative ions (CL-) hyperpolarize When NT binds to receptor, ions enter Receptor molecules have binding sites

34. Some Drugs work on receptors Some drugs are shaped like neurotransmitters Antagonists : fit the receptor but poorly and block the NT –e.g. beta blockers Agonists : fit receptor well and act like the NT –e.g. nicotine.

35. Neurons Make Up the Brains input dendrites and output through axon (lasts for a thousandth of a second). 2 main types: –projection neurons; dendritic arbor to a diameter of up to a millimeter axon extends up to a meter –local neurons (interneuron); dentritic arbor to a tenth of a millimeter (25-50 times the diameter of the cell body) interneuron is like the local streets, whereas the projection neuron, is like a system of main roads. axon tips, synapses, are attached to the dendrites of other neurons. most projection neurons in the forebrain are excitatory, whereas interneurons are either excitatory or inhibitory. several thousand synapses on the dendritic tree of each neuron. competition for synaptic space: –inactive synapses decay and disappear, even the neuron may vanish –lifelong growth and the maintenance of active connections provide the basis for leraning, remembering, and adapting through modifications of the numbers and strengths of synapses, (they require exercise). typically a million or more other neurons within the radius of the dendritic arbor of a given neuron each neuron connects with about 1 percent of the neurons within its reach (still at least ten thousand input and ten thousand output connections for each neuron) schematic view of neuropil schematic view of axon

36. dendrite W synapse axon P P trigger zone Neuron P PW W + - - - + + excitatory inhibitory + 0 0 0 0 threshold block electrical potentials (energy used by a neuron) that a neuron generates across the neural membrane axon expresses its state in the frequency of its action potentials (pulse rate) –energy is provided over entire length with a short delay –one pulse at the time (axon needs recovery time) dendrite expresses its state in the intensity of its synaptic current (wave amplitude) –integrate the pulse inputs dendritic wave is proportional to the total number of pulses dendrite receive (wave of current can be superposed on top of the currents form other synapses) –dendritic current at a synapse rises rapidly during the thousandth of a second and than returns slowly neuron converts incoming pulses to waves, sums them, and transmits that train to all its axonal branches. outward-flowing current triggers zone more likely to fire below threshold & pulse rate of neuron to increase Inhibitory synapse turns the current so it decreases the firing probability and the pulse rate of active neuron. Activities of a Neuron

37. Microscopic vs. Mesoscopic single neuron is expressed with the flow of the loop current inside the neuron, (measured with an electrode inside the cell body) –private, intracellular, microscopic view –Microscopic pulse and wave state variables to describe the activity of the single neuron. –time scale: thousandths of a second and thousandths of a millimeter flow of the same current outside the neuron is also revealed by an electric potential, (same current, smaller amplitude, lower resistance) –public, extracellular, mesoscopic view –mesoscopic state variables to describe the collective activities –time scale: tenths of a second and tenths of a millimeter Ensemble P P P0P0 W W + - - - + + rest excitatory inhibitory +

38. Conversion Operation dendrite W synapse axon P P trigger zone Ensemble Neuron P P P P P0P0 W W W W + - + - - - - - + + + + rest excitatory inhibitory + + 0 0 0 0 threshold block

39. Neural Connections convergencedivergenceseriesparallel auto-feedback + + cooperative-feedback (positive feedback) - - - + negative-feedback Connections apply to a neuron and to a masses of neurons. Sensory neurons in the somatic, auditory, gustatory, and olfactory systems transmit in parallel with divergence, they don’t interact. Cortical neurons form neural populations, they interact. + indicates excitation and – indicates inhibition. Neurons do not excite or inhibit themselves synaptically because input from their own output is only one among a million.

40. Mass Activity describe the mass activity in a local neighborhood by a pulse density – recording from outside the cell: simultaneous firing of the pulses of many neurons in a neighborhood. wave mode observe the amplitude of the wave density –measuring the electrical potential difference between the surface and the depth of the cortex (outer layer of brain) population is a collection of local neighborhoods - cortical column wave-pulse conversion in the population has a sigmoid curve with limits. resting level of pulse activity is low but not zero –neurons in population generate background activity by continually sending pulses to each other at random, whether or not there is sensory input or motor output?! Ensemble P P P0P0 W W + - - - + + rest excitatory inhibitory +

41. Sigmoid Curve Explanation for the Ensemble Wave-pulse –as the wave density in a neighborhood goes to the inhibitory side: pulse density goes to zero with decreasing firing probability of axons in neighborhood. –as wave density goes to the excitatory side: trigger zones in the population encounter the refractory periods progressively, pulse density approaches an upper limit, because neurons need to recover between pulses: (as neurons in neighborhood are excited, there is an increase in number of cells still recovering from previous activity). Pulse-wave –synapses cannot be driven too far outside their normal ranges: wave-pulse precedes the pulse-wave and sets the boundaries Ensemble P P P0P0 W W + - - - + + rest excitatory inhibitory +

42. First Building Block of Neurodynamics mesoscopic state: –first step by which neurons collectively form activity patterns neurons cease to act individually –activity level is determined by the population, not by the individuals. transformation of the neurons from one mode of existence to another is an example of the state transition. e.g. + + 0.8 excitatory aggregate neurons below threshold excite each other in positive feedback: neuron gives 100 pulses on average but receives only 80 in return, then those 80 pulses next give 64, and so on through successive cycles until the activity returns to zero. ration of 0.8 is called the gain of the loop. + + 1.2 when growth continues and each neuron receives 120 pulses for each 100 it gives, gain is 1.2: activity level can theoretically increase with each successive cycle around loop form 120 to 144 and so on without the limit, but it doesn’t happen because of saturation. individual refractory periods determine the upper limit of the sigmoid curve for the population. saturation reduces the gain, until the gain returns to unity and a nonzero steady state. excitatory population always comes to a steady level of activity, with no need of inhibition. population rebounds from inhibition or excitation, when perturbed, population is semiautonomous.

43. Mesoscopic Responses E + + E + + E + + E + I - + amplitude time no feedback amplitude time positive feedback amplitude time negative feedback If the feedback gain is zero ( no feedback), the impulse response decay quickly – the form of the postsynaptic potential of single neurons. With positive feedback the response is prolonged. If the gain is equal to one, the response to a pulse lasts indefinitely. If the gain exceeds one, the response increases until saturation. When excitatory neurons (E) interact with inhibitory (I) by negative feedback, the response oscillates. The stronger the gain, the longer the oscillation lasts. In cortex the ration of E to I is 10 to 1. The return to a resting point, within limits, reveals a point attractor, (return point level regardless of intensity of the input). Limits define the basin of the attractor. The state transition form a point attractor at zero activity to a nonzero point attractor gives steady- state activity (first building block of neurodynamics).

44. Features of the Population amplitude time point attractor population has a point attractor: population returns (is attracted) to the same level after it is stimulated amplitude time range of amplitudes defines state space of population population returns is the basin of attraction: ball rolling to the lowest point of a bowl amplitude time basin

45. Basin of Attractions basin of attractions in 3D (all points are visited frequently)

46. Oscillations Negative feedback between excitatory (E) neurons and inhibitory (I) neurons produces oscillation. Lower graphs show the state space of an area of cortex with a plot of the excitatory state variable on the horizontal axis and the inhibitory state variable on the vertical axis. Input shock rings at its characteristic frequency until the ringing decays to the steady state. The ringing in cortical activity is the evoked potential. Oscillation through negative feedback is the second building block of neurodynamics. When the excitatory cells are released form inhibition, they are free to respond to the background activity, and so give a new surge of excitation to the inhibitory population. This starts another cycle of oscillation with lower amplitude. excite E cells excite I cells a b inhibit E cells inhibit I cells c d amplitude time background zero + - - - - - - - - - + + + + + + + + E E E E I I I I E I impulse point attractor a’ d c b a

47. Cycle of Oscillation EI when the excitatory cells are released form inhibition, they are again free to respond to the background activity, and so give a new surge of excitation to the inhibitory population. starts another cycle of oscillation, at lower amplitude, and it repeats until ringing dies frequency is somewhere between 20 and 100 cycles per second, gamma range decay rate is the rate of return to the basal level: measure of ration on any peak to the preceding peak if the ratio and the gain exceeds unity: state transition occurs because the population does not return to the point attractor: oscillation grows until it encounters the nonlinear limitations, and there it stays. steady state oscillation, a limit cycle, is the third building block on neurodynmaics. oscillation is semiautonomous, self-sustaining and self-organized. stable: additional excitatory or inhibitory input temporarily increase or decreased, but on release form input, the population returns to its basal oscillation

48. Thank you!