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EXP NEURO > Connectomes II > Flashcards

Connectomes II Flashcards

1
Q

in mesoscale circuit tracing tech: list (2) types of Qs asked

A
  • where does input to this cell group come from?

- does cell group A receive input from cell group B?

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2
Q

in mesoscale circuit tracing tech: where does input to this cell group come from?

A

hypothesis-free discovery project: unlikely to definitively answer Qs regarding functional organisation of a circuit
- serves as platform for generation of more specific hypotheses (that need to be tested in later experiments)

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3
Q

in mesoscale circuit tracing tech: does cell group A receive input from cell group B?

A
  • specific research Q (RQ)

- unambiguously addressed by presence of labelled neurons

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4
Q

mapping connectome controlling BP: quick procedure

A
  • mapped inputs to group of spinally projecting brainstem neurons in RVLM (rostral ventrolateral medulla): known to control BP via excitatory effects on sym nn
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5
Q

mapping connectome controlling BP: findings

A
  • found monosyn input neurons in many diff brain regions, many were already assoc w effects on BP
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6
Q

mapping connectome controlling BP: unexpected finding

A
  • RVLM neurons receive input from cholinergic interneurons of intermediate reticular nucleus
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7
Q

mapping connectome controlling BP: hypothesis

A
  • monosynaptic input from cholinergic IRt neurons responsible for post-inspiratory activation of sym nn
  • functional experiments upholds the hypothesis
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8
Q

eg. accessory resp mm (2) exhibit third phase in respiration?

A
  • post-inspiratory phase (post-i)

- eg. crural diaphragm, laryngeal adductors

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9
Q

respiratory pump mm and innervation eg. (2) exhibit what 2 phases?

A
  • inspiration
  • expiration
  • eg. phrenic nn, diaphragm
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10
Q

what inn post-i activity

A
  • sym nn which also controls BP
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11
Q

hypothesis: if IRt is silenced, what happens to post-i activity?

A
  • testing if necessary for generation of post-i activity

= should disappear if so

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12
Q

limitations of G-deleted rabies: list (2)

A
  • does not label all presynaptic neurons

- rabies virus is toxic to humans

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13
Q

limitations of G-deleted rabies: labelling of presyn neurons issues (3)

A
  • each neuron 1000s synaptic inputs, many rabies virions required inside starter cell to infect sig portion of synapses
  • trans-syn efficiency of each virion is stochastic (random prob dist can’t be predicted precisely) due to multiple factors (incl. interaction btw rabies glycoprotein and cellular components)
  • overall <10% input neurons are labelled (possibly less)
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14
Q

limitations of G-deleted rabies: solutions: labelling efficiency issues (2)

A
  1. try g-proteins from diff strains of rabies to find highest efficiency
    - PBG variant is highest no. of presyn n/ starter cell
  2. optimise PBG gene sequence (oG) so more protein expressed per neuron
    - manipulation glycoprotein lead to improved efficiency
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15
Q

limitations of G-deleted rabies: toxic rabies features

A
  • standard (B19 strain) g deleted rabies starts killing neurons by 14 days
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16
Q

limitations of G-deleted rabies: solutions to toxic rabies

A
  1. try other strains of rabies:
    - others engineered to drive same targeted retrograde labelling (eg. N2c) = higher infection efficiency, lower toxicity

or 2. make B19 strain less toxic
- manipulate rabies to prod protein turning replication off

17
Q

Qs to ask: brain is more than its connectome! (2)

A
  • what are response properties of neurons that provide input to cell group u target?
  • what NT do they release?
18
Q

incorporate functional toolboxes into transsynaptic tracers: modifed rabies variants used tools like? and effect

A
  • channelrhodopsin2
  • allowing identified input neurons to be switched on/off
  • allows u to figure out what effect identified network components have overall network behaviour
19
Q

incorporate functional toolboxes into transsynaptic tracers: variants that express genetically encoded Ca sensors features-

A
  • Ca sensors enable u to visualise activity in pressyn neurons
  • mod GFP genes change brightness in relation to intracellular Ca conc, optical recording of neuronal activity
  • allows u to determine behavioural profile of input neurons
20
Q

simultaneous id/recording of microcircuits in vivo: Q- how r microcircuits that discriminate visual stimuli organised? list approach (3)

A
  1. target single visual cortex output (pyramidal) neurons w genetics tools required for rabies entry and spread (and red fluorescent protein)
  2. infect single neuron w rabies encoding GCamp6 Ca sensor, install glass window over brain surface
  3. after infection of neuron, connectome record the responsiveness of all neurons in microcircuit to standardised visual stimuli
21
Q

simultaneous id/recording of microcircuits in vivo: which ideals are satisfied (5)

A
  • allow selection of subpop of neurons for investigation
  • identify local and distant connections
  • identify connected cells in the live animal
  • integrated w tools that allow investigation of behaviour
  • identify monosynaptically linked neurons
22
Q

simultaneous id/recording of microcircuits in vivo: conclusion

A
  • although powerful, approach not suitable for neural networks that can’t be imaged in vivo (eg. circuits that are v spread out/ reside deep in the brain)
23
Q

simultaneous id/recording of microcircuits in vivo: final thought on monosynaptic viral tracers (4)

A
  • transformative technology because coz targeted to selected cell groups and provide unambiguous connectivity data
  • already work quite well (not for humans) and rapidly improving
  • tools for analysis hav yet to catch up
  • no equivalent anterograde monosynaptic tracers
24
Q

whole brain human connectivity: MRI based imaging techniques for inferring connectivity in humans- list (2)

A
  • diffusion weighted tractography

- dynamic functional connectivity

25
Q

MRI imaging: pros (3)

A
  • image lrg vol quickly
  • human subjects
  • subjects alive, conscious
26
Q

MRI imaging: cons (5)

A
  • poor spatial resolution (2-3mm)
  • each voxel 8-27 mm3
  • poor temporal res (10-30ms) will miss short latency responses
  • doesn’t actually measure neuronal activity, rather fluctuations in brain blood flow
  • size, cost
27
Q

diffusion weighted tractography: concept

A
  • MRI measures magnetic resonance of water molecules aligned within a magnetic fields
  • water not evenly dist in brain - lots inside cells, not much in axons/fibre tracts (wrapped in fat)

= map axon tracts

28
Q

diffusion weighted tractography: id of lrg fibre tracts BUT (cons)

A
  • doesn’t tell u which direction the tracts r travelling and only id’s v lrg bundles of axons
29
Q

diffusion weighted tractography: useful for?

A
  • gross anatomy (eg. changes in brain connectivity after head injury) but maybe hard to directly relate structure to function
30
Q

dynamic functional connectivity: concept

A
  • parts of brain connected will have lvls of activity fluctuate together
  • image whole brain activity in steady state conditions using fMRI, then analyse entire dataset to id voxels that have linked activity
31
Q

dynamic functional connectivity: procedure

A
  1. image brain for prolonged period
  2. divided brain into regions of interest
  3. each region: determine how activity in region fluctuates w time compared to other regions of interest- connected regions should wax/wane together= connectivity matrix
32
Q

connectomic insight: list specific brain circuits (4)

A
  • breathing
  • vision
  • sex diff in human brain structure
  • decision making in worms
33
Q

connectomic insight: list some general rules that dictate circuit architecture etc. (2) and extent where

A

across diff species, diff res (micro/meso/macro) and diff brain regions, same rules:

  • spatial embedding (neurons receive connections from nearby cells vs more distant cells)
  • reciprocity (neurons provide feedback. to upstream circuit components)
34
Q

connectomic insight: what does having these general rules mean?

A
  • prob relatively simple rules govern brain self-assembly

- diff circuits prob hav more in common w each other than prev thought?

35
Q

list some parallel dev which help increase accessibility, reduce cost of powerful connectomic tech (4)

A
  • imaging
  • vector biology
  • analytics
  • machine learning
36
Q

how will we use all this connectomic knowledge?

A
  • better understand the architecture of specific circuits

- dev better understanding of general rules that dictate brain organisation

37
Q

define: PBG and oG

A

PBG: variant of G-deleted rabies strain w highest efficiency (highest no. pressyn neurons/starter cell)

oG: optimised gene, modified PBG which increased glycoproteins expressed/neuron

EXP NEURO (10 decks)

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