A robust and scalable immunoadsorbent platform based on the high-affinity M03-IgG antibody for targeted IL-6 Removal in cytokine storm.

Context shapes how sensory information is processed in the mammalian brain. A well-known example is the enhanced neural response to contextually unexpected stimuli, known as deviance detection (DD). This phenomenon, observed even in early sensory cortices, reflects the brain’s ability to detect statistically improbable events or violations of regularities in the environment (Ishishita et al. ; Obara et al. ; Lao-Rodríguez et al. ; Parras et al. ; Tiitinen et al. ; Valerio et al. ; Yu et al. ; McCollum et al. ). Critically, DD involves two distinct components: stimulus-specific adaptation (SSA) and genuine deviance detection (genuine DD). SSA refers to reduced neural responses to frequently repeated stimuli, a form of repetition suppression that is specific to stimulus features (Hinz et al. ; Valerio et al. ; Yarden et al. ). While SSA can produce larger responses to rare stimuli, this alone does not confirm genuine DD. In contrast, genuine DD requires a stricter criterion: the neural response to a deviant stimulus must exceed the response to the same physical stimulus when it is not surprising (i.e., presented in a control condition). This distinction is essential for isolating the brain’s computation of contextual probability, rather than mere physical novelty. The capacity for genuine DD is biologically and clinically significant. Impairments in DD have been reported as biomarkers in several neurodevelopmental and psychiatric disorders, including schizophrenia, autism, and attention deficit hyperactivity disorder (De Groote et al. ; Näätänen et al. ; Pérez-González et al. ), highlighting the need to understand its underlying mechanisms. Genuine DD has been documented across sensory modalities, including auditory, visual, and somatosensory systems (Azouz and Gray ; Bounds and Adesnik ; Derveer et al. ; McCollum et al. ; Obara et al. ; Parras et al. ; Wang et al. ), and across species ranging from rodents to humans (Behrens et al. ; Ulanovsky et al. ; Yarden and Nelken ). It has also been observed throughout the brain, from subcortical structures like the inferior colliculus to higher cortical areas (Chen et al. ; Tsolaki et al., ). Notably, recent work has demonstrated genuine DD in neuronal cell cultures (Zhang et al. ), showing that this computation can emerge from simple networks, independent of complex brain circuitry. Computational models have typically attributed genuine DD to synaptic plasticity. While models based on long-term plasticity exist (Hertäg and Sprekeler ; Wacongne et al. ), the rapid emergence of DD in vivo points to fast-acting mechanisms. Short-term synaptic plasticity, particularly short-term depression, has been a primary candidate (Anwar et al. ; Mill et al. ; Yarden and Nelken ). More recent studies show that intrinsic neuronal adaptation, such as threshold adaptation, is also sufficient to generate genuine DD. Moreover, short-term depression and threshold adaptation can interact synergistically, enhancing DD beyond what either mechanism achieves alone (Kern and Chao ). These findings suggest that genuine DD can arise from the dynamic interaction of fast plasticity mechanisms, without requiring long-term structural changes.