2. Firing rates of Hippocampal Neurons Flashcards

1
Q

Place Cells

A

most dominant firing cell in the hippocampus (specifically in rats)

  • Okeefe & Dostrovsky (1971)
  • Nakazawa et al., (2004)
  • pyramidal neurons in CA3 and CA1
  • each place cell has a place field in the environment where it becomes active
  • directionality - may only be active in specific directions
  • overlapping - slight overlap in place fields to cover whole environment
  • multi sensory representation - represent different senses
  • most active when moving
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2
Q

Okeefe & Dostrovsky (1971)

A
  • spatial map
  • when a rat is in a specific location facing a specific direction 8 units responded solely
  • AP’s mark specific locations with a slight overlap (cell 2 fires in a similar location to cell 1)
  • for each specific location of the environment there are subgroups of cells that elicit greater AP’s
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3
Q

Nakazawa et al., (2004)

A
  • recorded the firing rate of individual neurons (in CA1) in a rat
  • AP’s recorded when the rat was in specific locations in the environment highlighting place cell firing specificities
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4
Q

place cell remapping

A

Fyhn et al., (2007) - CA1 and CA3 recording of AP’s

  1. different boxes at same location (3)
  2. same box, different locations (3)
  3. change in colour of box walls (3)
  • PLACE CELLS CAN CHANGE THE LOCATION OF THEIR PLACE FIELD AND THEIR FIRING RATE DEPENDING ON HOW THE ENVIRONMENT CHANGES
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5
Q
  1. different boxes same location
A
  • original square box the rat was in, moved to circular box, then back to original box
  • both rate overlap (firing rate) and spatial location of place cell changed when the box (environment) did
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6
Q
  1. same box, different locations
A
  • when changing the location of the box, both rate overlap and spatial location of AP’s changed
  • when moving back to original location it is as if there was no change
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7
Q
  1. change in colour of box wall
A
  • rate overlap seems to change when the colour of wall is changed
  • spatial correlation stays similar (place field stays the same)
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8
Q

head direction cells

A

in subiculum - more active when facing a specific direction

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9
Q

border cells

A

across different parts of the hippocampus

- active when near the walls (borders) of the environment

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10
Q

grid cells

A
  • very different to place cells but still influenced by environment
  • found commonly in entorhinal cortex
  • has typically 1 (or 2 in larger environments) place fields that follow a systematic grid pattern
  • cover entire 2D environment
  • still dont know relationship between grid and place cells
  • Hafting et al., (2005)
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11
Q

Hafting et al., (2005)

A

the grid cell pattern not apparent in hippocampus (CA1/3) but is found in the entorihinal cortex (inout and output of hippocampus)

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12
Q

O’Keefe & Nadel (1978)

A

theory that the hippocampus is an allocentric map which we use to navigate the environment

  • allocentirc - store information about location relative to each other (birds eye view)
  • egocentric - current view as if walking around
  • how we can compare spatial activity of a rat to humans
  • we don’t need to store information about food like a rat does, our map is used for more complex tasks
  • connecting more to function
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13
Q

neural coding and position decoding

A
  • interested in single neurons (place cells) as well as collections
  • testing whether hippocampus acts as an allocentric map
  • question: can we estimate (decode) the location of an animal based on the recorded spike train from a neuron
  • when there is a spike on the spike train we can determine its place field
  • when a spike is recorded we can tell where the rat is in the environment
  • the more spikes of that neuron occurring suggests that the rat is in a more central location, said with more surety
  • when there are multiple place cells being recorded from, we can combine the spikes to decode the location of the animal in the environment, just from looking at the spike trains (based on probability)
  • can keep adding place cells to increase accuracy of the prediction (can do this on a computer program)
  • potential function as an allocentric map is highlighted here but we dont know if the brain decodes in this way specifically as well
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14
Q

Johnson & Redish (2007)

A
  • used a maze with food rewards at the end
  • algorithm accurate at predicting rats location in maze
  • when the animal came to decision points (go left or right) algorithm computing the place fields of place cells projected ahead of the rat (considering future turns)
  • identified that place cells not only fire for the location they in, but also show animal where to go
  • planning for future actions shows hippocampus is not just an allocentric map, could relate to higher order cog function (decision making, episodic memory - storing in order of episodes)
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15
Q

Quiruga et al (2005)

A
  • neural activity in humans with large parts of the hippocampus and temporal lobe removed (pharmacological resistant epilepsy)
  • placed electrodes to try and identify where the siezures where origninating from (MTL - hippocampus)
  • presented a large array of visual stimuli
  • when subjects where shown pictures of jennifer anniston neurons increased their firing rate (this was specific to the person not invarient to specific picture type e.g. picture of ‘jennifer’ as a word)
  • more related to abstract concept (similar when looking at Sydney opera house)
  • suggests that there is generalisation taking place from place cells - sparse coding of abstract concepts (grandmother cell)
  • how animals form spatial memories could inform us about humans abstract thought
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