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The ability to anticipate rhythmic patterns is fundamental to human experience, enabling music appreciation, speech comprehension, and dancing in sync to music. How the brain learns to use acoustic information to guide motor behavior remains a key question whose neural underpinnings and evolutionary origins are debated, especially in non-human primates. To understand how brain areas involved in motor control naively respond to predictable tone patterns, we recorded large single neuron populations across primary somatosensory (S1), primary motor (M1), dorsal premotor (PMd), supplementary motor (SMA), pre-supplementary motor (preSMA) cortices, globus pallidus interna (GPi), and medial geniculate body (MGB) of a rhesus monkey. During passive listening (Experiment 1) with a reward only at the end of each trial, primarily the MGB, not motor areas, responded to the auditory tone patterns, ruling out the spontaneous entrainment of motor activity to auditory patterns. Almost all areas robustly

There are several plausible algorithms for cortical function that are specific enough to make testable predictions of the interactions between functionally identified cell types. Many of these algorithms are based on some variant of predictive processing. Here we set out to experimentally distinguish between two such predictive processing variants. A central point of variability between them lies in the proposed vertical communication between layer 2/3 and layer 5, which stems from the diverging assumptions about the computational role of layer 5. One assumes a hierarchically organized architecture and proposes that, within a given node of the network, layer 5 conveys unexplained bottom-up input to prediction error neurons of layer 2/3. The other proposes a non-hierarchical architecture in which internal representation neurons of layer 5 provide predictions for the local prediction error neurons of layer 2/3. We show that the functional influence of layer 2/3 cell types on layer 5 is incompatible with the hierarchical variant, while the functional influence of layer 5 cell types on prediction error neurons of layer 2/3 is incompatible with the non-hierarchical variant. Given these data, we can constrain the space of plausible algorithms of cortical function. We propose a model for cortical function based on a combination of a joint embedding predictive architecture (JEPA) and predictive processing that makes experimentally testable predictions. ### Competing Interest Statement The authors have declared no competing interest. Swiss National Science Foundation, https://ror.org/00yjd3n13 Novartis Foundation, https://ror.org/04f9t1x17 European Research Council, https://ror.org/0472cxd90, 865617

Abundant code without the sharp edges

A vagal reflex to blood volume changes in the heart involves PIEZO2 and helps to stabilize blood pressure in an upright posture and after blood loss.

The Vagus Nerve: How the Brain Listens to the Body on Simons Foundation

Spatial attention supports navigation by prioritizing information from selected locations. A candidate neural mechanism is provided by theta-paced sweeps in grid- and place-cell population activity, which sample nearby space in a left-right-alternating pattern coordinated by parasubicular direction signals. During exploration, this alternation promotes uniform spatial coverage, but whether sweeps can be flexibly tuned to locations of particular interest remains unclear. Using large-scale Neuropixels recordings in freely-behaving rats, we show that sweeps and direction signals are rapidly and dynamically modulated: they track moving targets during pursuit, precede orienting responses during immobility, and reverse during backward locomotion — without prior spatial learning. Similar modulation occurs during REM sleep. Canonical head-direction signals remain head-aligned. These findings identify sweeps as a flexible, attention-like mechanism for selectively sampling allocentric cognitive maps. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, Synergy Grant 951319 (EIM) The Research Council of Norway, Centre of Neural Computation 223262 (EIM, MBM), Centre for Algorithms in the Cortex 332640 (EIM, MBM), National Infrastructure grant (NORBRAIN, 295721 and 350201) The Kavli Foundation, https://ror.org/00kztt736 Ministry of Science and Education, Norway (EIM, MBM) Faculty of Medicine and Health Sciences; NTNU, Norway (AZV)

A countenance such as a grimace activates many of the same cortical pathways as voluntary facial movements.

YouTube video by Suthana Lab