@inbook{MTMT:34797365,
	title = {Massively Parallel EEG Algorithms for Pre-exascale Architectures},
	url = {https://m2.mtmt.hu/api/publication/34797365},
	author = {Wang, Zeyu and Juhász, Zoltán},
	booktitle = {Euro-Par 2023: Parallel Processing Workshops},
	doi = {10.1007/978-3-031-48803-0_34},
	unique-id = {34797365},
	year = {2024},
	pages = {290-295},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588}
}

@misc{MTMT:34554081,
	title = {Kvantitatív, sok-csatornás EEG elemzés, mint vizsgáló módszer a post-stroke állapotok leírására},
	url = {https://m2.mtmt.hu/api/publication/34554081},
	author = {Juhász, Zoltán and Gyulai, Ádám and Mohamed, F. Issa and Nagy, Zoltán},
	unique-id = {34554081},
	year = {2023},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588; Gyulai, Ádám/0000-0002-1787-5968; Nagy, Zoltán/0000-0001-9756-5427}
}

@inproceedings{MTMT:34452172,
	title = {Uncovering Neural Saccadic Responses using EEG during Natural Viewing of Paintings},
	url = {https://m2.mtmt.hu/api/publication/34452172},
	author = {Suhaili, Iffah Syafiqah binti and Juhász, Zoltán},
	booktitle = {Orvosi informatika. A XXXVI. Neumann Kollokvium konferencia-kiadványa},
	unique-id = {34452172},
	year = {2023},
	pages = {78-80},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588}
}

@inproceedings{MTMT:34452166,
	title = {Implementation strategies for EEG processing on multi-GPU computing systems},
	url = {https://m2.mtmt.hu/api/publication/34452166},
	author = {Wang, Zeyu and Juhász, Zoltán},
	booktitle = {Orvosi informatika. A XXXVI. Neumann Kollokvium konferencia-kiadványa},
	unique-id = {34452166},
	year = {2023},
	pages = {81-89},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588}
}

@article{MTMT:34346956,
	title = {Efficient GPU Implementation of the Multivariate Empirical Mode Decomposition Algorithm},
	url = {https://m2.mtmt.hu/api/publication/34346956},
	author = {Wang, Zeyu and Juhász, Zoltán},
	doi = {10.1016/j.jocs.2023.102180},
	journal-iso = {J COMPUT SCI},
	journal = {JOURNAL OF COMPUTATIONAL SCIENCE},
	volume = {2023},
	unique-id = {34346956},
	issn = {1877-7503},
	year = {2023},
	eissn = {1877-7511},
	pages = {102180},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588}
}

@article{MTMT:34308780,
	title = {ON THE PERCEPTION OF PAINTINGS: A HIGH-DENSITY EEG STUDY},
	url = {https://m2.mtmt.hu/api/publication/34308780},
	author = {Suhaili, Iffah Syafiqah binti and Juhász, Zoltán and Nagy, Zoltán},
	doi = {10.1016/j.ibneur.2023.08.1888},
	journal-iso = {IBRO NEUROSCI REP},
	journal = {IBRO NEUROSCIENCE REPORTS},
	volume = {15},
	unique-id = {34308780},
	year = {2023},
	eissn = {2667-2421},
	pages = {S900-S901},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588}
}

@article{MTMT:34222679,
	title = {Phonological awareness of bilinguals in visual word recognition},
	url = {https://m2.mtmt.hu/api/publication/34222679},
	author = {Ihász, Petra and Benyhe, András and Sáry, Gyula and Juhász, Zoltán and Navracsics, Judit},
	doi = {10.22210/strjez/52-1/3},
	journal-iso = {STRAN JEZ},
	journal = {STRANI JEZICI},
	volume = {52},
	unique-id = {34222679},
	issn = {0351-0840},
	year = {2023},
	pages = {49-73},
	orcid-numbers = {Ihász, Petra/0000-0003-3515-8230; Juhász, Zoltán/0000-0003-0677-8588}
}

@article{MTMT:34214301,
	title = {GPU Implementation of the Improved CEEMDAN Algorithm for Fast and Efficient EEG Time–Frequency Analysis},
	url = {https://m2.mtmt.hu/api/publication/34214301},
	author = {Wang, Zeyu and Juhász, Zoltán},
	doi = {10.3390/s23208654},
	journal-iso = {SENSORS-BASEL},
	journal = {SENSORS},
	volume = {23},
	unique-id = {34214301},
	abstract = {Time–frequency analysis of EEG data is a key step in exploring the internal activities of the human brain. Studying oscillations is an important part of the analysis, as they are thought to provide the underlying mechanism for communication between neural assemblies. Traditional methods of analysis, such as Short-Time FFT and Wavelet Transforms, are not ideal for this task due to the time–frequency uncertainty principle and their reliance on predefined basis functions. Empirical Mode Decomposition and its variants are more suited to this task as they are able to extract the instantaneous frequency and phase information but are too time consuming for practical use. Our aim was to design and develop a massively parallel and performance-optimized GPU implementation of the Improved Complete Ensemble EMD with the Adaptive Noise (CEEMDAN) algorithm that significantly reduces the computational time (from hours to seconds) of such analysis. The resulting GPU program, which is publicly available, was validated against a MATLAB reference implementation and reached over a 260× speedup for actual EEG measurement data, and provided predicted speedups in the range of 3000–8300× for longer measurements when sufficient memory was available. The significance of our research is that this implementation can enable researchers to perform EMD-based EEG analysis routinely, even for high-density EEG measurements. The program is suitable for execution on desktop, cloud, and supercomputer systems and can be the starting point for future large-scale multi-GPU implementations.},
	year = {2023},
	eissn = {1424-8220},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588}
}

@article{MTMT:34072577,
	title = {Event‐Related Spectral Perturbation, Inter Trial Coherence, and Functional Connectivity in motor execution: A comparative EEG study of old and young subjects},
	url = {https://m2.mtmt.hu/api/publication/34072577},
	author = {Gyulai, Ádám and Körmendi, János and Mohamed, F. Issa and Juhász, Zoltán and Nagy, Zoltán},
	doi = {10.1002/brb3.3176},
	journal-iso = {BRAIN BEHAV},
	journal = {BRAIN AND BEHAVIOR},
	volume = {13},
	unique-id = {34072577},
	issn = {2162-3279},
	year = {2023},
	eissn = {2162-3279},
	orcid-numbers = {Gyulai, Ádám/0000-0002-1787-5968; Körmendi, János/0000-0002-3810-6033; Juhász, Zoltán/0000-0003-0677-8588; Nagy, Zoltán/0000-0001-9756-5427}
}

@article{MTMT:34069273,
	title = {Visual Word Recognition Patterns of Hungarian-English Bilinguals – Homograph Effect in Bilingual Language Decision},
	url = {https://m2.mtmt.hu/api/publication/34069273},
	author = {Ihász, Petra and András, Benyhe and Gyula, Sáry and Juhász, Zoltán and Navracsics, Judit},
	doi = {10.18460/ANY.2023.1.003},
	journal-iso = {ALKALMAZOTT NYELVTUDOMÁNY},
	journal = {ALKALMAZOTT NYELVTUDOMÁNY},
	volume = {23},
	unique-id = {34069273},
	issn = {1587-1061},
	abstract = {The present study is part of a larger-scale research in which the processes of written word recognition
		are studied in bilinguals. The research goal of our lexical decision experiments is to gain information
		about the temporal characteristics of recognition at the orthographic, phonological, and semantic levels
		of processing. The research questions concern behavioral differences and the ERP components of
		recognizing English words, Hungarian words, and interlexical homographs. 23 Hungarian-English
		bilingual participants were tested in an Electroencephalogram laboratory. In recognition of Hungarian
		and English words and homographs, the mean response language per participant indicated high accuracy
		for both Hungarian and English conditions (96% and 98%, respectively). In contrast, the homographs
		are biased towards English responses (27% Hungarian response). The multiple comparisons confirmed
		no difference in the mean response times of Hungarian and English words, whereas the interlexical
		homographs produced around 150 ms longer responses. In recognition of Hungarian and English words,
		there was no difference between the two categories in the early recognition phases, corresponding with
		the orthographic-phonological level. However, the neural representation of the two languages differed,
		later reflecting the differences in semantic or decision-related processes. In the case of the Hungarian-
		English interlexical homographs, the ERP waveforms did not show significant differences between the
		items perceived as English or Hungarian. Although there is a difference between the brain activations
		in the temporal and frontal electrode sites, this difference is insignificant. These data coincide with the
		former findings related to the homograph effect (Navracsics & Sáry, 2013), which explains that
		participants are exposed to a greater cognitive burden in the recognition, and the reaction time is longer
		due to the fact that both lexicons are active.},
	year = {2023},
	eissn = {2498-4442},
	pages = {36-58},
	orcid-numbers = {Ihász, Petra/0000-0003-3515-8230; Juhász, Zoltán/0000-0003-0677-8588}
}