Results 111 to 120 of about 2,915 (182)

Neurophysiological findings in a patient with adrenomyeloneuropathy [PDF]

, 1986
Brosi, K., Krause, Klaus-Henning, Rittmann, M., Scheglmann, K.   +3 more
core  

Asymmetries in hue percepts and early cortical color coding: Evidence from chromatic visual evoked potentials. [PDF]

J Vis
Macyczko JR, Kavcar OB, Crognale MA, Webster MA.   +3 more
europepmc   +1 more source

Subclinical involvement of central nervous system structures other than motor or sensory tracts in SPG3A and SPG4 patients. [PDF]

BMC Neurol
Sobanska A, Sulek A, Stepniak I, Elert-Dobkowska E, Wierzbicka A, Lojkowska W, Rakowicz M.   +6 more
europepmc   +1 more source

Increasing EEG electrode density improves decoding of visual categories and source localization: an exploratory ultra-high-density EEG study. [PDF]

Commun Eng
Schreiner L, Sieghartsleitner S, Kapeller C, Jordan M, Scharinger J, Spataro R, Pretl H, Guger C.   +7 more
europepmc   +1 more source

Complementary Roles of Structure and Variant Effect Predictors in RyR1 Clinical Interpretation. [PDF]

Hum Mutat
Hernández Trapero R, Badonyi M, Gerasimavicius L, Marsh JA.   +3 more
europepmc   +1 more source

Leveraging protein structural information to improve variant effect prediction. [PDF]

Curr Opin Struct Biol
Gerasimavicius L, Teichmann SA, Marsh JA.   +2 more
europepmc   +1 more source

The Incantations of the Veps People: Issues of Learning a Musical Language

Music Scholarship / Problemy Muzykal'noj Nauki, 2016
openaire   +1 more source

Decoding of image properties from single-trial visual evoked potentials recorded by ultra-high-density EEG. [PDF]

Sci Rep
Sieghartsleitner S, Schreiner L, Grünwald J, Jordan M, Spataro R, Scharinger J, Guger C.   +6 more
europepmc   +1 more source

AI cancer driver mutation predictions are valid in real-world data. [PDF]

Nat Commun
Tran TN, Fong C, Pichotta K, Luthra A, Shen R, Chen Y, Waters M, Kim S, Li X, de Bruijn I, Riely G, Berger MF, Ladanyi M, Chakravarty D, Schultz N, Jee J.   +15 more
europepmc   +1 more source

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence. [PDF]

Nat Commun
Guan C, Torres MDT, Li S, de la Fuente-Nunez C.   +3 more
europepmc   +1 more source