---
_id: '12716'
abstract:
- lang: eng
text: "The process of detecting and evaluating sensory information to guide behaviour
is termed perceptual decision-making (PDM), and is critical for the ability of
an organism to interact with its external world. Individuals with autism, a neurodevelopmental
condition primarily characterised by social and communication difficulties, frequently
exhibit altered sensory processing and PDM difficulties are widely reported. Recent
technological advancements have pushed forward our understanding of the genetic
changes accompanying this condition, however our understanding of how these mutations
affect the function of specific neuronal circuits and bring about the corresponding
behavioural changes remains limited. Here, we use an innate PDM task, the looming
avoidance response (LAR) paradigm, to identify a convergent behavioural abnormality
across three molecularly distinct genetic mouse models of autism (Cul3, Setd5
and Ptchd1). Although mutant mice can rapidly detect threatening visual stimuli,
their responses are consistently delayed, requiring longer to initiate an appropriate
response than their wild-type siblings. Mutant animals show abnormal adaptation
in both their stimulus- evoked escape responses and exploratory dynamics following
repeated stimulus presentations. Similarly delayed behavioural responses are observed
in wild-type animals when faced with more ambiguous threats, suggesting the mutant
phenotype could arise from a dysfunction in the flexible control of this PDM process.\r\nOur
knowledge of the core neuronal circuitry mediating the LAR facilitated a detailed
dissection of the neuronal mechanisms underlying the behavioural impairment. In
vivo extracellular recording revealed that visual responses were unaffected within
a key brain region for the rapid processing of visual threats, the superior colliculus
(SC), indicating that the behavioural delay was unlikely to originate from sensory
impairments. Delayed behavioural responses were recapitulated in the Setd5 model
following optogenetic stimulation of the excitatory output neurons of the SC,
which are known to mediate escape initiation through the activation of cells in
the underlying dorsal periaqueductal grey (dPAG). In vitro patch-clamp recordings
of dPAG cells uncovered a stark hypoexcitability phenotype in two out of the three
genetic models investigated (Setd5 and Ptchd1), that in Setd5, is mediated by
the misregulation of voltage-gated potassium channels. Overall, our results show
that the ability to use visual information to drive efficient escape responses
is impaired in three diverse genetic mouse models of autism and that, in one of
the models studied, this behavioural delay likely originates from differences
in the intrinsic excitability of a key subcortical node, the dPAG. Furthermore,
this work showcases the use of an innate behavioural paradigm to mechanistically
dissect PDM processes in autism."
acknowledged_ssus:
- _id: PreCl
- _id: Bio
- _id: LifeSc
- _id: M-Shop
- _id: CampIT
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Laura
full_name: Burnett, Laura
id: 3B717F68-F248-11E8-B48F-1D18A9856A87
last_name: Burnett
orcid: 0000-0002-8937-410X
citation:
ama: Burnett L. To flee, or not to flee? Using innate defensive behaviours to investigate
rapid perceptual decision-making through subcortical circuits in mouse models
of autism. 2023. doi:10.15479/at:ista:12716
apa: Burnett, L. (2023). To flee, or not to flee? Using innate defensive behaviours
to investigate rapid perceptual decision-making through subcortical circuits in
mouse models of autism. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:12716
chicago: Burnett, Laura. “To Flee, or Not to Flee? Using Innate Defensive Behaviours
to Investigate Rapid Perceptual Decision-Making through Subcortical Circuits in
Mouse Models of Autism.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/at:ista:12716.
ieee: L. Burnett, “To flee, or not to flee? Using innate defensive behaviours to
investigate rapid perceptual decision-making through subcortical circuits in mouse
models of autism,” Institute of Science and Technology Austria, 2023.
ista: Burnett L. 2023. To flee, or not to flee? Using innate defensive behaviours
to investigate rapid perceptual decision-making through subcortical circuits in
mouse models of autism. Institute of Science and Technology Austria.
mla: Burnett, Laura. To Flee, or Not to Flee? Using Innate Defensive Behaviours
to Investigate Rapid Perceptual Decision-Making through Subcortical Circuits in
Mouse Models of Autism. Institute of Science and Technology Austria, 2023,
doi:10.15479/at:ista:12716.
short: L. Burnett, To Flee, or Not to Flee? Using Innate Defensive Behaviours to
Investigate Rapid Perceptual Decision-Making through Subcortical Circuits in Mouse
Models of Autism, Institute of Science and Technology Austria, 2023.
date_created: 2023-03-08T15:19:45Z
date_published: 2023-03-10T00:00:00Z
date_updated: 2023-04-05T10:59:04Z
day: '10'
ddc:
- '599'
- '573'
degree_awarded: PhD
department:
- _id: GradSch
- _id: MaJö
doi: 10.15479/at:ista:12716
ec_funded: 1
file:
- access_level: closed
checksum: 6c6d9cc2c4cdacb74e6b1047a34d7332
content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
creator: lburnett
date_created: 2023-03-08T15:08:46Z
date_updated: 2023-03-08T15:08:46Z
file_id: '12717'
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file_size: 23029260
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date_created: 2023-03-08T15:08:46Z
date_updated: 2023-03-08T15:08:46Z
file_id: '12718'
file_name: Burnett_Thesis_2023_pdfA.pdf
file_size: 11959869
relation: main_file
success: 1
file_date_updated: 2023-03-08T15:08:46Z
has_accepted_license: '1'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: '178'
project:
- _id: 2634E9D2-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '756502'
name: Circuits of Visual Attention
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Maximilian A
full_name: Jösch, Maximilian A
id: 2BD278E6-F248-11E8-B48F-1D18A9856A87
last_name: Jösch
orcid: 0000-0002-3937-1330
title: To flee, or not to flee? Using innate defensive behaviours to investigate rapid
perceptual decision-making through subcortical circuits in mouse models of autism
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '12809'
abstract:
- lang: eng
text: "Understanding the mechanisms of learning and memory formation has always
been one of\r\nthe main goals in neuroscience. Already Pavlov (1927) in his early
days has used his classic\r\nconditioning experiments to study the neural mechanisms
governing behavioral adaptation.\r\nWhat was not known back then was that the
part of the brain that is largely responsible for\r\nthis type of associative
learning is the cerebellum.\r\nSince then, plenty of theories on cerebellar learning
have emerged. Despite their differences,\r\none thing they all have in common
is that learning relies on synaptic and intrinsic plasticity.\r\nThe goal of my
PhD project was to unravel the molecular mechanisms underlying synaptic\r\nplasticity
in two synapses that have been shown to be implicated in motor learning, in an\r\neffort
to understand how learning and memory formation are processed in the cerebellum.\r\nOne
of the earliest and most well-known cerebellar theories postulates that motor
learning\r\nlargely depends on long-term depression at the parallel fiber-Purkinje
cell (PC-PC) synapse.\r\nHowever, the discovery of other types of plasticity in
the cerebellar circuitry, like long-term\r\npotentiation (LTP) at the PC-PC synapse,
potentiation of molecular layer interneurons (MLIs),\r\nand plasticity transfer
from the cortex to the cerebellar/ vestibular nuclei has increased the\r\npopularity
of the idea that multiple sites of plasticity might be involved in learning.\r\nStill
a lot remains unknown about the molecular mechanisms responsible for these types
of\r\nplasticity and whether they occur during physiological learning.\r\nIn the
first part of this thesis we have analyzed the variation and nanodistribution
of voltagegated calcium channels (VGCCs) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic
acid\r\ntype glutamate receptors (AMPARs) on the parallel fiber-Purkinje cell
synapse after vestibuloocular reflex phase reversal adaptation, a behavior that
has been suggested to rely on PF-PC\r\nLTP. We have found that on the last day
of adaptation there is no learning trace in form of\r\nVGCCs nor AMPARs variation
at the PF-PC synapse, but instead a decrease in the number of\r\nPF-PC synapses.
These data seem to support the view that learning is only stored in the\r\ncerebellar
cortex in an initial learning phase, being transferred later to the vestibular
nuclei.\r\nNext, we have studied the role of MLIs in motor learning using a relatively
simple and well characterized behavioral paradigm – horizontal optokinetic reflex
(HOKR) adaptation. We\r\nhave found behavior-induced MLI potentiation in form
of release probability increase that\r\ncould be explained by the increase of
VGCCs at the presynaptic side. Our results strengthen\r\nthe idea of distributed
cerebellar plasticity contributing to learning and provide a novel\r\nmechanism
for release probability increase. "
acknowledged_ssus:
- _id: EM-Fac
- _id: Bio
- _id: PreCl
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Catarina
full_name: Alcarva, Catarina
id: 3A96634C-F248-11E8-B48F-1D18A9856A87
last_name: Alcarva
citation:
ama: 'Alcarva C. Plasticity in the cerebellum: What molecular mechanisms are behind
physiological learning. 2023. doi:10.15479/at:ista:12809'
apa: 'Alcarva, C. (2023). Plasticity in the cerebellum: What molecular mechanisms
are behind physiological learning. Institute of Science and Technology Austria.
https://doi.org/10.15479/at:ista:12809'
chicago: 'Alcarva, Catarina. “Plasticity in the Cerebellum: What Molecular Mechanisms
Are behind Physiological Learning.” Institute of Science and Technology Austria,
2023. https://doi.org/10.15479/at:ista:12809.'
ieee: 'C. Alcarva, “Plasticity in the cerebellum: What molecular mechanisms are
behind physiological learning,” Institute of Science and Technology Austria, 2023.'
ista: 'Alcarva C. 2023. Plasticity in the cerebellum: What molecular mechanisms
are behind physiological learning. Institute of Science and Technology Austria.'
mla: 'Alcarva, Catarina. Plasticity in the Cerebellum: What Molecular Mechanisms
Are behind Physiological Learning. Institute of Science and Technology Austria,
2023, doi:10.15479/at:ista:12809.'
short: 'C. Alcarva, Plasticity in the Cerebellum: What Molecular Mechanisms Are
behind Physiological Learning, Institute of Science and Technology Austria, 2023.'
date_created: 2023-04-06T07:54:09Z
date_published: 2023-04-06T00:00:00Z
date_updated: 2023-04-26T12:16:56Z
day: '06'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GradSch
- _id: RySh
doi: 10.15479/at:ista:12809
file:
- access_level: closed
checksum: 35b5997d2b0acb461f9d33d073da0df5
content_type: application/pdf
creator: cchlebak
date_created: 2023-04-07T06:16:06Z
date_updated: 2023-04-07T06:16:06Z
embargo: 2024-04-07
embargo_to: open_access
file_id: '12814'
file_name: Thesis_CatarinaAlcarva_final pdfA.pdf
file_size: 9881969
relation: main_file
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content_type: application/pdf
creator: cchlebak
date_created: 2023-04-07T06:17:11Z
date_updated: 2023-04-07T06:17:11Z
file_id: '12815'
file_name: Thesis_CatarinaAlcarva_final_for printing.pdf
file_size: 44201583
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content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
creator: cchlebak
date_created: 2023-04-07T06:18:05Z
date_updated: 2023-04-07T06:18:05Z
file_id: '12816'
file_name: Thesis_CatarinaAlcarva_final.docx
file_size: 84731244
relation: source_file
file_date_updated: 2023-04-07T06:18:05Z
has_accepted_license: '1'
language:
- iso: eng
month: '04'
oa_version: Published Version
page: '115'
project:
- _id: 267DFB90-B435-11E9-9278-68D0E5697425
name: 'Plasticity in the cerebellum: Which molecular mechanisms are behind physiological
learning?'
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Ryuichi
full_name: Shigemoto, Ryuichi
id: 499F3ABC-F248-11E8-B48F-1D18A9856A87
last_name: Shigemoto
orcid: 0000-0001-8761-9444
title: 'Plasticity in the cerebellum: What molecular mechanisms are behind physiological
learning'
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '12826'
abstract:
- lang: eng
text: "During navigation, animals can infer the structure of the environment by
computing the optic flow cues elicited by their own movements, and subsequently
use this information to instruct proper locomotor actions. These computations
require a panoramic assessment of the visual environment in order to disambiguate
similar sensory experiences that may require distinct behavioral responses. The
estimation of the global motion patterns is therefore essential for successful
navigation. Yet, our understanding of the algorithms and implementations that
enable coherent panoramic visual perception remains scarce. Here I pursue this
problem by dissecting the functional aspects of interneuronal communication in
the lobula plate tangential cell network in Drosophila melanogaster. The results
presented in the thesis demonstrate that the basis for effective interpretation
of the optic flow in this circuit are stereotyped synaptic connections that mediate
the formation of distinct subnetworks, each extracting a particular pattern of
global motion. \r\nFirstly, I show that gap junctions are essential for a correct
interpretation of binocular motion cues by horizontal motion-sensitive cells.
HS cells form electrical synapses with contralateral H2 neurons that are involved
in detecting yaw rotation and translation. I developed an FlpStop-mediated mutant
of a gap junction protein ShakB that disrupts these electrical synapses. While
the loss of electrical synapses does not affect the tuning of the direction selectivity
in HS neurons, it severely alters their sensitivity to horizontal motion in the
contralateral side. These physiological changes result in an inappropriate integration
of binocular motion cues in walking animals. While wild-type flies form a binocular
perception of visual motion by non-linear integration of monocular optic flow
cues, the mutant flies sum the monocular inputs linearly. These results indicate
that rather than averaging signals in neighboring neurons, gap-junctions operate
in conjunction with chemical synapses to mediate complex non-linear optic flow
computations.\r\nSecondly, I show that stochastic manipulation of neuronal activity
in the lobula plate tangential cell network is a powerful approach to study the
neuronal implementation of optic flow-based navigation in flies. Tangential neurons
form multiple subnetworks, each mediating course-stabilizing response to a particular
global pattern of visual motion. Application of genetic mosaic techniques can
provide sparse optogenetic activation of HS cells in numerous combinations. These
distinct combinations of activated neurons drive an array of distinct behavioral
responses, providing important insights into how visuomotor transformation is
performed in the lobula plate tangential cell network. This approach can be complemented
by stochastic silencing of tangential neurons, enabling direct assessment of the
functional role of individual tangential neurons in the processing of specific
visual motion patterns.\r\n\tTaken together, the findings presented in this thesis
suggest that establishing specific activity patterns of tangential cells via stereotyped
synaptic connectivity is a key to efficient optic flow-based navigation in Drosophila
melanogaster."
acknowledged_ssus:
- _id: Bio
- _id: LifeSc
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Victoria
full_name: Pokusaeva, Victoria
id: 3184041C-F248-11E8-B48F-1D18A9856A87
last_name: Pokusaeva
orcid: 0000-0001-7660-444X
citation:
ama: Pokusaeva V. Neural control of optic flow-based navigation in Drosophila melanogaster.
2023. doi:10.15479/at:ista:12826
apa: Pokusaeva, V. (2023). Neural control of optic flow-based navigation in Drosophila
melanogaster. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:12826
chicago: Pokusaeva, Victoria. “Neural Control of Optic Flow-Based Navigation in
Drosophila Melanogaster.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/at:ista:12826.
ieee: V. Pokusaeva, “Neural control of optic flow-based navigation in Drosophila
melanogaster,” Institute of Science and Technology Austria, 2023.
ista: Pokusaeva V. 2023. Neural control of optic flow-based navigation in Drosophila
melanogaster. Institute of Science and Technology Austria.
mla: Pokusaeva, Victoria. Neural Control of Optic Flow-Based Navigation in Drosophila
Melanogaster. Institute of Science and Technology Austria, 2023, doi:10.15479/at:ista:12826.
short: V. Pokusaeva, Neural Control of Optic Flow-Based Navigation in Drosophila
Melanogaster, Institute of Science and Technology Austria, 2023.
date_created: 2023-04-14T14:56:04Z
date_published: 2023-04-18T00:00:00Z
date_updated: 2023-06-23T09:47:36Z
day: '18'
ddc:
- '570'
- '571'
degree_awarded: PhD
department:
- _id: MaJö
- _id: GradSch
doi: 10.15479/at:ista:12826
ec_funded: 1
file:
- access_level: closed
checksum: 5f589a9af025f7eeebfd0c186209913e
content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
creator: vpokusae
date_created: 2023-04-20T09:14:38Z
date_updated: 2023-04-20T09:26:51Z
file_id: '12857'
file_name: Thesis_Pokusaeva.docx
file_size: 14507243
relation: source_file
- access_level: open_access
checksum: bbeed76db45a996b4c91a9abe12ce0ec
content_type: application/pdf
creator: vpokusae
date_created: 2023-04-20T09:14:44Z
date_updated: 2023-04-20T09:14:44Z
file_id: '12858'
file_name: Thesis_Pokusaeva.pdf
file_size: 10090711
relation: main_file
success: 1
file_date_updated: 2023-04-20T09:26:51Z
has_accepted_license: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '04'
oa: 1
oa_version: Published Version
page: '106'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Maximilian A
full_name: Jösch, Maximilian A
id: 2BD278E6-F248-11E8-B48F-1D18A9856A87
last_name: Jösch
orcid: 0000-0002-3937-1330
title: Neural control of optic flow-based navigation in Drosophila melanogaster
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '12781'
abstract:
- lang: eng
text: "Most energy in humans is produced in form of ATP by the mitochondrial respiratory
chain consisting of several protein assemblies embedded into lipid membrane (complexes
I-V). Complex I is the first and the largest enzyme of the respiratory chain which
is essential for energy production. It couples the transfer of two electrons from
NADH to ubiquinone with proton translocation across bacterial or inner mitochondrial
membrane. The coupling mechanism between electron transfer and proton translocation
is one of the biggest enigma in bioenergetics and structural biology. Even though
the enzyme has been studied for decades, only recent technological advances in
cryo-EM allowed its extensive structural investigation. \r\n\r\nComplex I from
E.coli appears to be of special importance because it is a perfect model system
with a rich mutant library, however the structure of the entire complex was unknown.
In this thesis I have resolved structures of the minimal complex I version from
E. coli in different states including reduced, inhibited, under reaction turnover
and several others. Extensive structural analyses of these structures and comparison
to structures from other species allowed to derive general features of conformational
dynamics and propose a universal coupling mechanism. The mechanism is straightforward,
robust and consistent with decades of experimental data available for complex
I from different species. \r\n\r\nCyanobacterial NDH (cyanobacterial complex I)
is a part of broad complex I superfamily and was studied as well in this thesis.
It plays an important role in cyclic electron transfer (CET), during which electrons
are cycled within PSI through ferredoxin and plastoquinone to generate proton
gradient without NADPH production. Here, I solved structure of NDH and revealed
additional state, which was not observed before. The novel “resting” state allowed
to propose the mechanism of CET regulation. Moreover, conformational dynamics
of NDH resembles one in complex I which suggest more broad universality of the
proposed coupling mechanism.\r\n\r\nIn summary, results presented here helped
to interpret decades of experimental data for complex I and contributed to fundamental
mechanistic understanding of protein function.\r\n"
acknowledged_ssus:
- _id: EM-Fac
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Vladyslav
full_name: Kravchuk, Vladyslav
id: 4D62F2A6-F248-11E8-B48F-1D18A9856A87
last_name: Kravchuk
citation:
ama: Kravchuk V. Structural and mechanistic study of bacterial complex I and its
cyanobacterial ortholog. 2023. doi:10.15479/at:ista:12781
apa: Kravchuk, V. (2023). Structural and mechanistic study of bacterial complex
I and its cyanobacterial ortholog. Institute of Science and Technology Austria.
https://doi.org/10.15479/at:ista:12781
chicago: Kravchuk, Vladyslav. “Structural and Mechanistic Study of Bacterial Complex
I and Its Cyanobacterial Ortholog.” Institute of Science and Technology Austria,
2023. https://doi.org/10.15479/at:ista:12781.
ieee: V. Kravchuk, “Structural and mechanistic study of bacterial complex I and
its cyanobacterial ortholog,” Institute of Science and Technology Austria, 2023.
ista: Kravchuk V. 2023. Structural and mechanistic study of bacterial complex I
and its cyanobacterial ortholog. Institute of Science and Technology Austria.
mla: Kravchuk, Vladyslav. Structural and Mechanistic Study of Bacterial Complex
I and Its Cyanobacterial Ortholog. Institute of Science and Technology Austria,
2023, doi:10.15479/at:ista:12781.
short: V. Kravchuk, Structural and Mechanistic Study of Bacterial Complex I and
Its Cyanobacterial Ortholog, Institute of Science and Technology Austria, 2023.
date_created: 2023-03-31T12:24:42Z
date_published: 2023-03-23T00:00:00Z
date_updated: 2023-08-04T08:54:51Z
day: '23'
ddc:
- '570'
- '572'
degree_awarded: PhD
department:
- _id: GradSch
- _id: LeSa
doi: 10.15479/at:ista:12781
ec_funded: 1
file:
- access_level: closed
checksum: 5ebb6345cb4119f93460c81310265a6d
content_type: application/pdf
creator: vkravchu
date_created: 2023-04-19T14:33:41Z
date_updated: 2023-04-19T14:33:41Z
embargo: 2024-04-20
embargo_to: local
file_id: '12852'
file_name: VladyslavKravchuk_PhD_Thesis_PostSub_Final_1.pdf
file_size: 6071553
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creator: vkravchu
date_created: 2023-04-19T14:33:52Z
date_updated: 2023-04-20T07:02:59Z
embargo: 2024-04-20
embargo_to: local
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file_size: 19468766
relation: source_file
file_date_updated: 2023-04-20T07:02:59Z
has_accepted_license: '1'
language:
- iso: eng
month: '03'
oa_version: Published Version
page: '127'
project:
- _id: 238A0A5A-32DE-11EA-91FC-C7463DDC885E
grant_number: '25541'
name: 'Structural characterization of E. coli complex I: an important mechanistic
model'
- _id: 627abdeb-2b32-11ec-9570-ec31a97243d3
call_identifier: H2020
grant_number: '101020697'
name: Structure and mechanism of respiratory chain molecular machines
publication_identifier:
isbn:
- 978-3-99078-029-9
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '12138'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Leonid A
full_name: Sazanov, Leonid A
id: 338D39FE-F248-11E8-B48F-1D18A9856A87
last_name: Sazanov
orcid: 0000-0002-0977-7989
title: Structural and mechanistic study of bacterial complex I and its cyanobacterial
ortholog
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '13074'
abstract:
- lang: eng
text: "Deep learning has become an integral part of a large number of important
applications, and many of the recent breakthroughs have been enabled by the ability
to train very large models, capable to capture complex patterns and relationships
from the data. At the same time, the massive sizes of modern deep learning models
have made their deployment to smaller devices more challenging; this is particularly
important, as in many applications the users rely on accurate deep learning predictions,
but they only have access to devices with limited memory and compute power. One
solution to this problem is to prune neural networks, by setting as many of their
parameters as possible to zero, to obtain accurate sparse models with lower memory
footprint. Despite the great research progress in obtaining sparse models that
preserve accuracy, while satisfying memory and computational constraints, there
are still many challenges associated with efficiently training sparse models,
as well as understanding their generalization properties.\r\n\r\nThe focus of
this thesis is to investigate how the training process of sparse models can be
made more efficient, and to understand the differences between sparse and dense
models in terms of how well they can generalize to changes in the data distribution.
We first study a method for co-training sparse and dense models, at a lower cost
compared to regular training. With our method we can obtain very accurate sparse
networks, and dense models that can recover the baseline accuracy. Furthermore,
we are able to more easily analyze the differences, at prediction level, between
the sparse-dense model pairs. Next, we investigate the generalization properties
of sparse neural networks in more detail, by studying how well different sparse
models trained on a larger task can adapt to smaller, more specialized tasks,
in a transfer learning scenario. Our analysis across multiple pruning methods
and sparsity levels reveals that sparse models provide features that can transfer
similarly to or better than the dense baseline. However, the choice of the pruning
method plays an important role, and can influence the results when the features
are fixed (linear finetuning), or when they are allowed to adapt to the new task
(full finetuning). Using sparse models with fixed masks for finetuning on new
tasks has an important practical advantage, as it enables training neural networks
on smaller devices. However, one drawback of current pruning methods is that the
entire training cycle has to be repeated to obtain the initial sparse model, for
every sparsity target; in consequence, the entire training process is costly and
also multiple models need to be stored. In the last part of the thesis we propose
a method that can train accurate dense models that are compressible in a single
step, to multiple sparsity levels, without additional finetuning. Our method results
in sparse models that can be competitive with existing pruning methods, and which
can also successfully generalize to new tasks."
acknowledged_ssus:
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Elena-Alexandra
full_name: Peste, Elena-Alexandra
id: 32D78294-F248-11E8-B48F-1D18A9856A87
last_name: Peste
citation:
ama: Peste E-A. Efficiency and generalization of sparse neural networks. 2023. doi:10.15479/at:ista:13074
apa: Peste, E.-A. (2023). Efficiency and generalization of sparse neural networks.
Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:13074
chicago: Peste, Elena-Alexandra. “Efficiency and Generalization of Sparse Neural
Networks.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/at:ista:13074.
ieee: E.-A. Peste, “Efficiency and generalization of sparse neural networks,” Institute
of Science and Technology Austria, 2023.
ista: Peste E-A. 2023. Efficiency and generalization of sparse neural networks.
Institute of Science and Technology Austria.
mla: Peste, Elena-Alexandra. Efficiency and Generalization of Sparse Neural Networks.
Institute of Science and Technology Austria, 2023, doi:10.15479/at:ista:13074.
short: E.-A. Peste, Efficiency and Generalization of Sparse Neural Networks, Institute
of Science and Technology Austria, 2023.
date_created: 2023-05-23T17:07:53Z
date_published: 2023-05-23T00:00:00Z
date_updated: 2023-08-04T10:33:27Z
day: '23'
ddc:
- '000'
degree_awarded: PhD
department:
- _id: GradSch
- _id: DaAl
- _id: ChLa
doi: 10.15479/at:ista:13074
ec_funded: 1
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language:
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month: '05'
oa: 1
oa_version: Published Version
page: '147'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '11458'
relation: part_of_dissertation
status: public
- id: '13053'
relation: part_of_dissertation
status: public
- id: '12299'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
title: Efficiency and generalization of sparse neural networks
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...