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Brain activity differs vastly between sleep, cognitive tasks, and action. Information theory is an appropriate concept to analytically quantify these brain states. Based on neurophysiological recordings, this concept can handle complex data sets, is free of any requirements about the data structure, and can infer the present underlying brain mechanisms. Specifically, by utilizing algorithmic information theory, it is possible to estimate the absolute information contained in brain responses. While current approaches that apply this theory to neurophysiological recordings can discriminate between different brain states, they are limited in directly quantifying the degree of similarity or encoded information between brain responses. Here, we propose a method grounded in algorithmic information theory that affords direct statements about responses' similarity by estimating the encoded information through a compression-based scheme. We validated this method by applying it to both synthetic and real neurophysiological data and compared its efficiency to the mutual information measure. This proposed procedure is especially suited for task paradigms contrasting different event types because it can precisely quantify the similarity of neuronal responses.

The ability to use predictive information to guide perception and action relies heavily on the prefrontal cortex (PFC), yet the involvement of its subregions in predictive processes remains unclear. Recent perspectives propose that the orbitofrontal cortex (OFC) generates predictions about perceptual events, actions, and their outcomes while the lateral prefrontal cortex (LPFC) is involved in prospective functions, which support predictive processes, such as selective attention, working memory, response preparation or inhibition. To further delineate the roles of these PFC areas in predictive processing, we investigated whether lesions would impair the ability to build predictions of future events and detect deviations from expected regularities. We used an auditory deviance detection task, in which the structural regularities of played tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) and global (i.e., between sequences) level. We have recently shown that OFC lesions affect detecting prediction violations at two hierarchical levels of rule abstraction, i.e., altered MMN and P3a to local and simultaneous local + global prediction violations (https://doi.org/10.7554/eLife.86386). Now, we focus on the task's predictive aspect and present the latest results showing the involvement of PFC subregions in anticipation of deviances informed by implicit predictive information. Behavioral data shows that deviance expectancy induced faster deviance detection in healthy adults (n=22), suggesting that participants track a state space representation of the task and anticipate upcoming deviant sequences. The analysis of EEG data from patients with focal lesions to the OFC (n = 12) or LPFC (n = 10), and SEEG from the same areas in patients with epilepsy (n = 7), revealed interesting differences. Healthy adults (n = 15) showed modulations of the Contingent Negative Variation (CNV) – a marker of anticipatory activity - tracking the expectancy of deviant tone sequences. However, patients with OFC lesions lacked CNV sensitivity to the predictive context, while patients with LPFC lesions showed moderate sensitivity compared to healthy adults. These results were further supported by intracranial recordings, which revealed expectancy modulation of the high-frequency broadband signal from electrodes in OFC and LPFC, with an earlier latency of activity modulation for the OFC and a later one for the LPFC. Altogether, the complementary approach from behavioral, intracerebral EEG, scalp EEG, and causal lesion data provides compelling evidence for the distinct engagement of the two prefrontal areas in predicting future events and signaling deviations.

Flexibly adapting to our dynamic surroundings requires anticipating upcoming events and focusing our attention accordingly. Rhythmic patterns of sensory input offer valuable cues for these temporal expectations and facilitate perceptual processing. However, a gap in understanding persists regarding how rhythms outside of periodic structures influence perception. Our study aimed to delineate the distinct roles of predictability and periodicity in rhythm-based expectations. Participants completed a pitch-identification task preceded by different rhythm types: periodic predictable, aperiodic predictable, and aperiodic unpredictable. By manipulating the timing of the target sound, we observed how auditory sensitivity was modulated by the target position in the different rhythm conditions. The results revealed a clear behavioral benefit of predictable rhythms, regardless of their periodicity. Interestingly, we also observed an additional effect of periodicity. While both periodic and aperiodic predictable rhythms improved overall sensitivity, only the periodic rhythm seemed to induce an entrained sensitivity pattern, wherein sensitivity peaked in synchrony with the expected continuation of the rhythm. The recorded event-related brain potentials further supported these findings. The target-evoked P3b, possibly a neural marker of attention allocation, mirrored the sensitivity patterns. This supports our hypothesis that perceptual sensitivity is modulated by temporal attention guided by rhythm-based expectations. Furthermore, the effect of rhythm predictability seems to operate through climbing neural activity (similar to the CNV), reflecting preparation for the target. The effect of periodicity is likely related to more precise temporal expectations and could possibly involve neural entrainment. Our findings suggest that predictability and periodicity influence perception via distinct mechanisms.

Current findings of orbitofrontal cortex (OFC) function suggest that this region might have a role in the generation of prediction error signals associated with top-down expectation of upcoming stimuli. We investigated the impact of lesions to the OFC on the Contingent Negative Variation (CNV), an electrophysiological marker of cognitive expectation and time perception. Twelve OFC patients and fifteen healthy controls performed an auditory local-global paradigm while brain electrical activity was recorded. The structural regularities of the tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) level with a short timescale and at a global (i.e., between sequences) level with a longer timescale. At the global level, deviant tone sequences were interspersed among standard tone sequences in a pseudorandom order, rendering some deviant sequences more anticipated than others. We found that healthy controls exhibited CNV build-up before the occurrence of deviant sequences. The CNV drift rate was modulated by the expectancy of deviant sequences (i.e., the higher the expectancy, the higher the CNV drift rate), reflecting their ability to anticipate when a deviant tone sequence would occur. However, patients with OFC lesions did not show CNV drift modulations by the expectancy of the deviant tone sequences, indicating impaired anticipation of these upcoming events. These findings suggest involvement of the OFC in generating auditory expectations based on the contextual and temporal structure of the task.

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In this study, we tested the causal involvement of the OFC in noticing breaches of predictions (i.e., PEs) at different hierarchical levels of task structural complexity. With this aim, we examined the event-related potentials (ERPs) of patients with focal OFC lesions and healthy adults while performing an auditory local-global oddball paradigm. Altogether, we found that after OFC damage, low-level PEs (i.e., processing of stimuli that are unpredicted at the local level) and combined low- and high-level PEs (i.e., processing of stimuli that are unpredicted at both the local and global level) were impacted. However, the processing of standard tones was not affected. We conclude that the OFC may contribute to a top-down process that modulates the deviance detection system in the primary auditory cortices, and may be involved in connecting PEs at lower hierarchical areas with predictions at higher areas. The study sheds new light on the poorly explored deficits of hierarchical auditory prediction in patients with damaged OFC.

An introduction to the inter-trial coherence measure (ITC) and how it is applied to EEG data (with example code/scripts in MATLAB). Furthermore caveats of the measure are discussed along with it's relation to phase opposition measures.

An introduction to the Phase Amplitude Coupling (PAC) measure and how it is applied to EEG data (example code in MATLAB). The caveats of the measure are covered and which sanity checks might be necessary.

An introduction to the Fourier transform and how it is applied to EEG data. The short time fourier transform (STFT) and different measures (phase and amplitude) derived from it are explained.