Week 6: Recap of Place cells Flashcards

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1
Q

Across species (humans and rodents), we can identify different portions of the hippocampus (4)

A
  • DG
  • CA3
  • CA2
  • CA1
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2
Q

Hippocampus receives main input from

A

EC (Enthorine cortex) which last stage of cortical processing prior to the hippocampus

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3
Q

Remindar what we found in hippocampus diagram:

A
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4
Q

Typical experiment to record neurons from hippocampal formation is from

A

single-cell recordings

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5
Q

Reminder of single-cell recordings (3)

A
  1. Microdrives with electrodes are chronically implanted
  2. Once the animal has recovered from surgrey it performs a task or simple runs around a box to collect food pellets around the box to cover the entire space of maze
  3. Electrodes are moved until they record spikes
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6
Q

Diagram of single-cell recordings

A
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7
Q

Neurons found in hippocampal formation (4)

A
  1. Place cells
  2. Head direction (HD) cells
  3. Grid cells
  4. Boudary cells
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8
Q

The single-cell recordings allow us to have direct recordings from

A

rodent brain in behaving animal

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9
Q

There is a visual cue (e.g., white card) in the box from single-cell recordings that help animal to

A

orientate itself in this box

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10
Q

Remindar: Place cells

A

Place cells fire whenever an animal occupies a specific location in its environment, with each place cell firing at a different spot.

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11
Q

Remindar: Grid cells (2)

A

A grid cell is a type of neuron within the entorhinal cortex that fires at regular intervals as an animal navigates an open area,

Grid cells generate virtual maps of the surroundings that resemble grids of repeating triangles.

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12
Q

Location of place cells

A

Hippocampus

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13
Q

Location of grid cells:

A

EC

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14
Q

Diagram of place and grid cells:

A
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15
Q

Remindar: HD cells

A

Head direction cells fire selectively when the rat’s head is pointed in a particular direction in allocentric space, regardless of its location (Ranck, 1985)

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16
Q

Diagram of HD cells graph

A
17
Q

Boundary cells are measured the same way

A

as place cells (recording intensity of firing of a neuron, red = highest)

18
Q

Boundary cells have receptive fields and whenever the boundary cells is in that receptive field

A

that boundary cells fires an action potential

19
Q

Boundary cells respond to a specific

A

environmental boundary/objects at a particular distance and direction from an animal

20
Q

As an animal moves away from receptive field, that boundary cells

A

stops firing action potentials

21
Q

Boundary’s cells firing is

A

independent of the rat’s heading direction.

22
Q

Most of the neurons in hippocampal formation has been recorded in

A

humans as well

23
Q

Place fields are receptive fields for

A

space

24
Q

HD cells have receptive fields for

A

heading

25
Q

Place cell property 1

A

Location of a place field can not be predicted based on anatomical vicnity

26
Q

Location of the place field can not be predicted based on anatomical vincity means

A

Anatomically close place cells can have place fields far from each other (rather than close to each other) or one cell can be silent while other is active in different enviroments

27
Q

Place cell property 2 (3)

A
    • Firing is independent of the rat’s orientation in open field
    • Firing is directional in narrow-armed mazes
    • Firing is robust to the removal of sensory cues
28
Q

Firing of PC is independent of rat’s orientation in open field = how? (2)

A
  • Separated data according to movement direction
  • The activity of the place cell is still in the same location if the animal direction is west to east or east to west
29
Q

Firing of PC is directional in a narrow-armed maze (linear track = animal runs back and forth)

A

Meaning the animal only fires in one direction

30
Q

Firing of PC is robust to the removal of sensory cues (2) Nakazawa (2002)

A

If you have 4 sensory cues in enviroment, you can remove 3/4 and the PC cells still fire

If you block the NMDA receptor, this is not the case, meaning formation of PC fields is important for plasicity by NMDA-receptor for these PC cells

31
Q

Place cell property 3 = Global remapping

Individual PC cells at given enviroment fire at different locations or are silent and together all active PC cells

A

likely to cover the entire enviroment with their place fields

32
Q

Place cell property 3
Some PC cells are silent in one enviroment but

A

active in another

33
Q

Place cell property 3
If a PC cell is active in both enviroment it is so at

A

different locations

34
Q

Place cell property 3 what is global remapping?

A

The process of changing firing locaiton or turning on/off between enviroments

35
Q

Place property 3 (after def of glob remap) we can think of the set of active PC across an enviroment akin to

A

extended attractor network (current context recruits a given set)

36
Q

We can think that the set of active PC cells across enviroment akin to an extended attractor network but be careful… - (2)

A

If the set of active PC is bounded together by CA3 recurrence, it can’t be via CA3 place cell with small receptive place fields

Must be via CA3 cells that are active throughout the enviroment (i.e., not CA3 place cells)

37
Q

Place cell propertities (3)

A
  1. Property 1 = location of place fields can not be predicted by anatomical vicinity
  2. Property 2 = Firing is directional , independent or orientation and robust to removal of sensory cues
  3. Property 3 = Global remapping
38
Q

Similar to Nakazawa paper,
you need synaptic plasticity of the NMDA-receptor to have stable place fields
(Kentros et al., 1998) - (2)

A

Inject saline , place field is stable
Place field stability falls when NMDA receptors are blocked (i.e.,NMDAR anatgonist is injected in rat

39
Q

There is slow, experience-dependent changes to PC fields showing global remapping (Lever et al., 2002) is not the whole story (3)

A
  • global remapping is akin to change between attractor
  • But the attractor ‘is slowly deformed over time’
  • We need to keep these caveats in mind when building a model
  • Recall: question determines level of detial in model