opensearch:totalResults = 39
opensearch:startIndex = 0
opensearch:itemsPerPage = 25
opensearch:startIndex = 0
opensearch:itemsPerPage = 25
@role = request
@searchTerms = AU-ID(57883960400)
@startPage = 0
@searchTerms = AU-ID(57883960400)
@startPage = 0
@_fa = true
@ref = self
@href = https://api.elsevier.com/content/search/scopus?start=0&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
@ref = self
@href = https://api.elsevier.com/content/search/scopus?start=0&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
@_fa = true
@ref = first
@href = https://api.elsevier.com/content/search/scopus?start=0&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
@ref = first
@href = https://api.elsevier.com/content/search/scopus?start=0&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
@_fa = true
@ref = next
@href = https://api.elsevier.com/content/search/scopus?start=25&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
@ref = next
@href = https://api.elsevier.com/content/search/scopus?start=25&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
@_fa = true
@ref = last
@href = https://api.elsevier.com/content/search/scopus?start=14&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
@ref = last
@href = https://api.elsevier.com/content/search/scopus?start=14&count=25&query=AU-ID%2857883960400%29&apiKey=6ae70c855c11cca26b94ca23c22dcbcf
@type = application/json
inizio
@_fa = true@_fa = true
@ref = self
@href = https://api.elsevier.com/content/abstract/scopus_id/105040703574
@_fa = true
@ref = author-affiliation
@href = https://api.elsevier.com/content/abstract/scopus_id/105040703574?field=author,affiliation
@_fa = true
@ref = scopus
@href = https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105040703574&origin=inward
@_fa = true
@ref = scopus-citedby
@href = https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=105040703574&origin=inward
@_fa = true
@ref = full-text
@href = https://api.elsevier.com/content/article/eid/1-s2.0-S0893608026006568
- R&B – rhythm and brain: Cross-subject decoding of music from human brain activity; Neural Networks; November 2026; DOI: 10.1016/j.neunet.2026.109195
prism:url = https://api.elsevier.com/content/abstract/scopus_id/105040703574
dc:identifier = SCOPUS_ID:105040703574
eid = 2-s2.0-105040703574
dc:creator = Ciferri M.
prism:publicationName = Neural Networks
prism:issn = 08936080
prism:eIssn = 18792782
prism:volume = 203
prism:issueIdentifier =
prism:pageRange =
prism:coverDate = 2026-11-01
prism:coverDisplayDate = November 2026
prism:doi = 10.1016/j.neunet.2026.109195
citedby-count = 0
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id = 42235475
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 109195
source-id = 24804
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
$ = repository
$ = repositoryam
value:
$ = All Open Access
$ = Hybrid Gold
$ = Green
prism:isbn:
@_fa =
$ =
pii = S0893608026006568
dc:identifier = SCOPUS_ID:105040703574
eid = 2-s2.0-105040703574
dc:creator = Ciferri M.
prism:publicationName = Neural Networks
prism:issn = 08936080
prism:eIssn = 18792782
prism:volume = 203
prism:issueIdentifier =
prism:pageRange =
prism:coverDate = 2026-11-01
prism:coverDisplayDate = November 2026
prism:doi = 10.1016/j.neunet.2026.109195
citedby-count = 0
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id = 42235475
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 109195
source-id = 24804
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
$ = repository
$ = repositoryam
value:
$ = All Open Access
$ = Hybrid Gold
$ = Green
prism:isbn:
@_fa =
$ =
pii = S0893608026006568
inizio
@_fa = true@_fa = true
@ref = self
@href = https://api.elsevier.com/content/abstract/scopus_id/105044826801
@_fa = true
@ref = author-affiliation
@href = https://api.elsevier.com/content/abstract/scopus_id/105044826801?field=author,affiliation
@_fa = true
@ref = scopus
@href = https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105044826801&origin=inward
@_fa = true
@ref = scopus-citedby
@href = https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=105044826801&origin=inward
- NeuroFusion: A Unified Framework for Generalized Visual Stimulus Decoding from fMRI Across Datasets and Subjects; Neuroinformatics; September 2026; DOI: 10.1007/s12021-026-09803-3
prism:url = https://api.elsevier.com/content/abstract/scopus_id/105044826801
dc:identifier = SCOPUS_ID:105044826801
eid = 2-s2.0-105044826801
dc:creator = Kashif M.
prism:publicationName = Neuroinformatics
prism:issn = 15392791
prism:eIssn = 15590089
prism:volume = 24
prism:issueIdentifier = 3
prism:pageRange =
prism:coverDate = 2026-09-01
prism:coverDisplayDate = September 2026
prism:doi = 10.1007/s12021-026-09803-3
citedby-count = 0
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id = 42469516
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 45
source-id = 23987
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
$ = repository
$ = repositoryam
value:
$ = All Open Access
$ = Hybrid Gold
$ = Green
prism:isbn:
@_fa =
$ =
pii =
dc:identifier = SCOPUS_ID:105044826801
eid = 2-s2.0-105044826801
dc:creator = Kashif M.
prism:publicationName = Neuroinformatics
prism:issn = 15392791
prism:eIssn = 15590089
prism:volume = 24
prism:issueIdentifier = 3
prism:pageRange =
prism:coverDate = 2026-09-01
prism:coverDisplayDate = September 2026
prism:doi = 10.1007/s12021-026-09803-3
citedby-count = 0
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id = 42469516
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 45
source-id = 23987
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
$ = repository
$ = repositoryam
value:
$ = All Open Access
$ = Hybrid Gold
$ = Green
prism:isbn:
@_fa =
$ =
pii =
inizio
@_fa = true@_fa = true
@ref = self
@href = https://api.elsevier.com/content/abstract/scopus_id/105045494374
@_fa = true
@ref = author-affiliation
@href = https://api.elsevier.com/content/abstract/scopus_id/105045494374?field=author,affiliation
@_fa = true
@ref = scopus
@href = https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105045494374&origin=inward
@_fa = true
@ref = scopus-citedby
@href = https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=105045494374&origin=inward
- Cross-subject decoding of human neural data for speech brain computer interfaces; Journal of Neural Engineering; August 2026; DOI: 10.1088/1741-2552/ae8576
prism:url = https://api.elsevier.com/content/abstract/scopus_id/105045494374
dc:identifier = SCOPUS_ID:105045494374
eid = 2-s2.0-105045494374
dc:creator = Boccato T.
prism:publicationName = Journal of Neural Engineering
prism:issn = 17412560
prism:eIssn = 17412552
prism:volume = 23
prism:issueIdentifier = 4
prism:pageRange =
prism:coverDate = 2026-08-01
prism:coverDisplayDate = August 2026
prism:doi = 10.1088/1741-2552/ae8576
citedby-count = 0
@_fa = true
affilname = Tether Evo
affiliation-city = San Salvador
affiliation-country = El Salvador
pubmed-id = 42392141
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 046018
source-id = 130164
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
value:
$ = All Open Access
$ = Hybrid Gold
prism:isbn:
@_fa =
$ =
pii =
dc:identifier = SCOPUS_ID:105045494374
eid = 2-s2.0-105045494374
dc:creator = Boccato T.
prism:publicationName = Journal of Neural Engineering
prism:issn = 17412560
prism:eIssn = 17412552
prism:volume = 23
prism:issueIdentifier = 4
prism:pageRange =
prism:coverDate = 2026-08-01
prism:coverDisplayDate = August 2026
prism:doi = 10.1088/1741-2552/ae8576
citedby-count = 0
@_fa = true
affilname = Tether Evo
affiliation-city = San Salvador
affiliation-country = El Salvador
pubmed-id = 42392141
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 046018
source-id = 130164
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
value:
$ = All Open Access
$ = Hybrid Gold
prism:isbn:
@_fa =
$ =
pii =
inizio
@_fa = true@_fa = true
@ref = self
@href = https://api.elsevier.com/content/abstract/scopus_id/105014517393
@_fa = true
@ref = author-affiliation
@href = https://api.elsevier.com/content/abstract/scopus_id/105014517393?field=author,affiliation
@_fa = true
@ref = scopus
@href = https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105014517393&origin=inward
@_fa = true
@ref = scopus-citedby
@href = https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=105014517393&origin=inward
@_fa = true
@ref = full-text
@href = https://api.elsevier.com/content/article/eid/1-s2.0-S1566253525007225
- Towards neural foundation models for vision: Aligning EEG, MEG, and fMRI representations for decoding, encoding, and modality conversion; Information Fusion; February 2026; DOI: 10.1016/j.inffus.2025.103650
prism:url = https://api.elsevier.com/content/abstract/scopus_id/105014517393
dc:identifier = SCOPUS_ID:105014517393
eid = 2-s2.0-105014517393
dc:creator = Ferrante M.
prism:publicationName = Information Fusion
prism:issn = 15662535
prism:eIssn =
prism:volume = 126
prism:issueIdentifier =
prism:pageRange =
prism:coverDate = 2026-02-01
prism:coverDisplayDate = February 2026
prism:doi = 10.1016/j.inffus.2025.103650
citedby-count = 3
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id =
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 103650
source-id = 26099
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
value:
$ = All Open Access
$ = Hybrid Gold
prism:isbn:
@_fa =
$ =
pii = S1566253525007225
dc:identifier = SCOPUS_ID:105014517393
eid = 2-s2.0-105014517393
dc:creator = Ferrante M.
prism:publicationName = Information Fusion
prism:issn = 15662535
prism:eIssn =
prism:volume = 126
prism:issueIdentifier =
prism:pageRange =
prism:coverDate = 2026-02-01
prism:coverDisplayDate = February 2026
prism:doi = 10.1016/j.inffus.2025.103650
citedby-count = 3
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id =
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = 103650
source-id = 26099
openaccess = 1
openaccessFlag = true
value:
$ = all
$ = publisherhybridgold
value:
$ = All Open Access
$ = Hybrid Gold
prism:isbn:
@_fa =
$ =
pii = S1566253525007225
inizio
@_fa = true@_fa = true
@ref = self
@href = https://api.elsevier.com/content/abstract/scopus_id/105028987504
@_fa = true
@ref = author-affiliation
@href = https://api.elsevier.com/content/abstract/scopus_id/105028987504?field=author,affiliation
@_fa = true
@ref = scopus
@href = https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105028987504&origin=inward
@_fa = true
@ref = scopus-citedby
@href = https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=105028987504&origin=inward
- Beam angle optimization for radiotherapy using LLMs via reinforcement-learning inspired iterative refinement; Medical Physics; February 2026; DOI: 10.1002/mp.70258
prism:url = https://api.elsevier.com/content/abstract/scopus_id/105028987504
dc:identifier = SCOPUS_ID:105028987504
eid = 2-s2.0-105028987504
dc:creator = Cammarota S.
prism:publicationName = Medical Physics
prism:issn = 00942405
prism:eIssn = 24734209
prism:volume = 53
prism:issueIdentifier = 2
prism:pageRange =
prism:coverDate = 2026-02-01
prism:coverDisplayDate = February 2026
prism:doi = 10.1002/mp.70258
citedby-count = 1
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id = 41612144
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = e70258
source-id = 17871
openaccess = 0
openaccessFlag = false
value:
$ =
value:
$ =
prism:isbn:
@_fa =
$ =
pii =
dc:identifier = SCOPUS_ID:105028987504
eid = 2-s2.0-105028987504
dc:creator = Cammarota S.
prism:publicationName = Medical Physics
prism:issn = 00942405
prism:eIssn = 24734209
prism:volume = 53
prism:issueIdentifier = 2
prism:pageRange =
prism:coverDate = 2026-02-01
prism:coverDisplayDate = February 2026
prism:doi = 10.1002/mp.70258
citedby-count = 1
@_fa = true
affilname = Università degli Studi di Roma "Tor Vergata"
affiliation-city = Rome
affiliation-country = Italy
pubmed-id = 41612144
prism:aggregationType = Journal
subtype = ar
subtypeDescription = Article
article-number = e70258
source-id = 17871
openaccess = 0
openaccessFlag = false
value:
$ =
value:
$ =
prism:isbn:
@_fa =
$ =
pii =