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Alejandro Blenkmann @ablenkmann.bsky.social · 01/07/2026

Case-level recordings from Heschl’s gyrus and posterior insula revealed striking heterogeneity: early gap-specific responses, later frequency and intensity effects, intensity selectivity, and late spatial processing with contralateral enhancement.

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Alejandro Blenkmann @ablenkmann.bsky.social · 01/07/2026

Key finding: amygdala neurons showed a multiphasic response to deviance. Timing changes produced the earliest and strongest effect (suppression) at ~60 ms, followed by enhancement around 200 ms. Intensity changes produced later suppression around 300 ms.

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Alejandro Blenkmann @ablenkmann.bsky.social · 01/07/2026

Participants passively heard standard sounds interleaved with changes in timing, frequency, intensity, and location. We analyzed 98 units: 48 in amygdala, 46 in hippocampus, plus case-level recordings from Heschl’s gyrus and posterior insula.

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Alejandro Blenkmann @ablenkmann.bsky.social · 01/07/2026

What do individual human neurons do when a sound violates expectations? In our new EJN paper, we characterize single- and multi-unit responses to several auditory deviants using microwire recordings from 13 patients. onlinelibrary.wiley.com/share/author... #MMN #iEEG #PredictiveProcessing

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Alejandro Blenkmann @ablenkmann.bsky.social · 29/08/2025

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

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Alejandro Blenkmann @ablenkmann.bsky.social · 29/08/2025

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

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Alejandro Blenkmann @ablenkmann.bsky.social · 29/08/2025

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

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Alejandro Blenkmann @ablenkmann.bsky.social · 05/05/2025

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.

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Alejandro Blenkmann @ablenkmann.bsky.social · 05/05/2025

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).

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Alejandro Blenkmann @ablenkmann.bsky.social · 05/05/2025

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.

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Alejandro Blenkmann @ablenkmann.bsky.social · 19/02/2025

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

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Alejandro Blenkmann @ablenkmann.bsky.social · 19/02/2025

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.

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Alejandro Blenkmann @ablenkmann.bsky.social · 19/02/2025

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

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Alejandro Blenkmann @ablenkmann.bsky.social · 19/02/2025

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.

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