Michael Berger

3 weeks ago | nature.com | Joris L. Vos |Daniel Muldoon |Cristina Valero |Andrew Lee |Timothy Chan |Michael Berger | +1 more

AbstractTo understand genetic evolution in cancer during metastasis, we analyzed genomic profiles of 3,732 cancer patients in whom several tumor sites were longitudinally biopsied. During distant metastasis, tumors were observed to accumulate copy number alterations (CNAs) to a much greater degree than mutations. In particular, the development of whole genome duplication was a common event during metastasis, emerging de novo in 28% of patients.

Oct 4, 2024 | nature.com | Maarten WJ Fornerod |Deedra Nicolet |Benjamin Kelly |Krzysztof Mrózek |Jean F. Kloppers |Anne-Cecilia van Marle | +21 more

AbstractGenomic profiles and prognostic biomarkers in patients with acute myeloid leukemia (AML) from ancestry-diverse populations are underexplored. We analyzed the exomes and transcriptomes of 100 patients with AML with genomically confirmed African ancestry (Black; Alliance) and compared their somatic mutation frequencies with those of 323 self-reported white patients with AML, 55% of whom had genomically confirmed European ancestry (white; BeatAML).

Aug 23, 2023 | nature.com | Jessie Liu |Michael Berger |Edward F. Chang |David A. Moses

Speech neuroprostheses have the potential to restore communication to people living with paralysis, but naturalistic speed and expressivity are elusive1. Here we use high-density surface recordings of the speech cortex in a clinical-trial participant with severe limb and vocal paralysis to achieve high-performance real-time decoding across three complementary speech-related output modalities: text, speech audio and facial-avatar animation. We trained and evaluated deep-learning models using neural data collected as the participant attempted to silently speak sentences. For text, we demonstrate accurate and rapid large-vocabulary decoding with a median rate of 78 words per minute and median word error rate of 25%. For speech audio, we demonstrate intelligible and rapid speech synthesis and personalization to the participant’s pre-injury voice. For facial-avatar animation, we demonstrate the control of virtual orofacial movements for speech and non-speech communicative gestures. The decoders reached high performance with less than two weeks of training. Our findings introduce a multimodal speech-neuroprosthetic approach that has substantial promise to restore full, embodied communication to people living with severe paralysis. A study using high-density surface recordings of the speech cortex in a person with limb and vocal paralysis demonstrates real-time decoding of brain activity into text, speech sounds and orofacial movements.