BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260331T185448Z UID:A1824EB0-6194-4572-8CB6-0F9157BFB10E DTSTART;TZID=America/New_York:20260326T173000 DTEND;TZID=America/New_York:20260326T203000 DESCRIPTION:Neural DNA Chronicles: Decoding the Brain for the Next Generati on of AI-BCI\n\nThe convergence of neuroscience\, artificial intelligence\ , and advanced sensing technologies is transforming how humans interact wi th machines. At the center of this transformation is the ability to decode the brain’s dynamic electrical activity. This talk introduces NeuralDNA \, a framework that describes structured patterns of neural activity that encode learning\, spatial cognition\, and decision-making in the human bra in. Understanding these neural patterns opens new possibilities for transl ating brain signals into computational models that enable more natural and adaptive human–machine interaction.\n\nThe talk explores how modern Bra in Computer Interfaces (BCIs) are evolving from simple signal acquisition systems into intelligent platforms capable of learning from neural data in real time. By integrating machine learning\, neural data science\, and ad vanced signal processing\, researchers can extract meaningful information from complex EEG signals and develop adaptive systems that respond to cogn itive states. It will highlight recent research on auditory neural stimula tion and EEG biomarker discovery aimed at improving cognitive engagement a nd learning capability in individuals with neurodevelopmental conditions s uch as Fragile X syndrome and autism spectrum disorders. By analyzing brai nwave responses to controlled stimulation frequencies\, these studies reve al neural patterns associated with enhanced cognitive states and demonstra te how machine learning can help optimize stimulation strategies.\n\nBeyon d clinical applications\, emerging BCI technologies are enabling innovatio ns in assistive systems\, cognitive enhancement\, mental health monitoring \, and human–AI collaboration. As neural interfaces advance\, they bring both opportunities and challenges\, including ethical considerations rela ted to neural data privacy and the responsible integration of AI. By uncov ering the hidden architecture of neural activity\, what we call NeuralDNA\ , this talk explores how integrating biology and engineering may redefine learning\, cognition\, and the future of intelligent systems.\n\nSpeaker(s ): Dr. Zag ElSayed\n\nRoom: Voltage Room\, March First Brewing & Distillin g\, 7885 E Kemper Rd\, Cincinnati\, Ohio\, United States\, 45249 LOCATION:Room: Voltage Room\, March First Brewing & Distilling\, 7885 E Kem per Rd\, Cincinnati\, Ohio\, United States\, 45249 ORGANIZER:dave@arcflashbrokerage.com SEQUENCE:17 SUMMARY:IEEE Cincinnati March 2026 Meeting URL;VALUE=URI:https://events.vtools.ieee.org/m/546606 X-ALT-DESC:Description: <br /><p>Neural DNA Chronicles:&nbsp\; Decoding the Brain for the Next Generation of AI-BCI</p>\n<p>The convergence of neuros cience\, artificial intelligence\, and advanced sensing technologies is tr ansforming how humans interact with machines. At the center of this transf ormation is the ability to decode the brain&rsquo\;s dynamic electrical ac tivity. This talk introduces NeuralDNA\, a framework that describes struct ured patterns of neural activity that encode learning\, spatial cognition\ , and decision-making in the human brain. Understanding these neural patte rns opens new possibilities for translating brain signals into computation al models that enable more natural and adaptive human&ndash\;machine inter action.</p>\n<p>The talk explores how modern Brain Computer Interfaces (BC Is) are evolving from simple signal acquisition systems into intelligent p latforms capable of learning from neural data in real time. By integrating machine learning\, neural data science\, and advanced signal processing\, researchers can extract meaningful information from complex EEG signals a nd develop adaptive systems that respond to cognitive states. It will high light recent research on auditory neural stimulation and EEG biomarker dis covery aimed at improving cognitive engagement and learning capability in individuals with neurodevelopmental conditions such as Fragile X syndrome and autism spectrum disorders. By analyzing brainwave responses to control led stimulation frequencies\, these studies reveal neural patterns associa ted with enhanced cognitive states and demonstrate how machine learning ca n help optimize stimulation strategies.</p>\n<p>Beyond clinical applicatio ns\, emerging BCI technologies are enabling innovations in assistive syste ms\, cognitive enhancement\, mental health monitoring\, and human&ndash\;A I collaboration. As neural interfaces advance\, they bring both opportunit ies and challenges\, including ethical considerations related to neural da ta privacy and the responsible integration of AI. By uncovering the hidden architecture of neural activity\, what we call NeuralDNA\, this talk expl ores how integrating biology and engineering may redefine learning\, cogni tion\, and the future of intelligent systems.</p> END:VEVENT END:VCALENDAR