Alejandro Blenkmann
ablenkmann.bsky.social
Alejandro Blenkmann
@ablenkmann.bsky.social
Neuroscientist | PI of AudioPred at @UniOslo-RITMO.bsky.social
Studying predictive processing & developing intracranial EEG methods
Personal page: https://bit.ly/aBlenkmann

#cognition #iEEG #SEEG #perception #attention #neuroscience #predictiveprocessing
Intracranial EEG shows expectancy modulations in the prefrontal cortex:
🧠 OFC earlier
🧠 LPFC later
(This was measured via high-frequency activity, a marker of local brain activity)

Connectivity analyses reveal bidirectional exchange, with the first lead by OFC.

#iEEG #PredictiveProcessing #HFA
August 29, 2025 at 8:08 AM
Lesion evidence indicates distinct roles:
🧠 Orbitofrontal cortex (OFC) damage abolishes sensitivity to expectancy.
🧠 Lateral prefrontal cortex (LPFC) damage shows only modest, non-significant effects compared to controls.
(Shown using #CNV #ERP that tracks anticipation)

#BrainLesion #Prediction
August 29, 2025 at 8:08 AM
In an auditory local–global deviance detection task, we found that the brain tracks sound regularities to anticipate when a rare deviant sequence will occur.
⚡ Participants detected deviants faster when they were expected.

#PredictiveProcessing
August 29, 2025 at 8:08 AM
5/
🧠 Key finding: TP encoding wasn’t limited to auditory cortex.
Hippocampus and inferior frontal gyrus showed strongest sensitivity to TPs.
Auditory cortex responded more to deviance per se, but statistical learning was distributed– and hierarchical.
May 5, 2025 at 10:36 AM
4/
Using an information-theoretical approach, we quantified how much information each brain response "encoded" relative to expected patterns.
Then, we tested how this encoded information tracked the likelihood of transitions– aka transitional probabilities (TPs).
May 5, 2025 at 10:36 AM
3/
👂 Participants listened to streams of random tones while ignoring them (reading a book).
We recorded high-frequency brain activity (75–145 Hz) from over 1000 electrodes in 22 patients.
We then tracked, trial-by-trial, how surprising each deviant sound was based on TP estimates.
May 5, 2025 at 10:36 AM
Key Findings:
3) Cue-Reliability dynamics: Variations in cue reliability (due to the random nature of the experiment) were tracked by the brain and modulated the pre-target beta power
February 19, 2025 at 8:52 AM
Key Findings:
2) Beta Band Activity (15–25 Hz): Before the target sound, beta power varied based on the predicted sharpness of the sound's envelope.
February 19, 2025 at 8:52 AM
Key Findings:
1) Enhanced Timing Precision: Participants showed improved accuracy (d-prime) in timing tasks when they had prior information about the sound's sharpness
February 19, 2025 at 8:52 AM
What We Did:
We conducted an EEG study where participants were given cues about the sharpness of upcoming sounds in a beat sequence. 🎧
Our goal: Understand how this predictive information influences brain activity and timing perception.
February 19, 2025 at 8:52 AM