The relationship between tickling, sensation, and laughter is complex. Tickling or its mere anticipation makes us laugh, but not when we self-tickle. We previously showed rat somatosensory cortex drives tickling-evoked vocalizations and now investigated self-tickle suppression and tickle anticipation. We recorded somatosensory cortex activity while tickling and touching rats and while rats touched themselves. Allo-touch and tickling evoked somatotopic cortical excitation and vocalizations. Self-touch induced wide-ranging inhibition and vocalization suppression. Self-touch also suppressed vocalizations and cortical responses evoked by allo-touch or cortical microstimulation. We suggest a global-inhibition model of self-tickle suppression, which operates without the classically assumed self versus other distinction. Consistent with this inhibition hypothesis, blocking cortical inhibition with gabazine abolished self-tickle suppression. We studied anticipation in a nose-poke-for-tickling paradigm. Although rats nose poked for tickling, they also showed escaping, freezing, and alarm calls. Such ambivalence ("Nervenkitzel") resembles tickle behaviors in children. We conclude that self-touch-induced GABAergic cortical inhibition prevents self-tickle, whereas anticipatory layer 5 activity drives anticipatory laughter. VIDEO ABSTRACT.

In classical neuroscience experiments, neural activity is measured across many identical trials of animals performing simple tasks and is then analyzed, associating neural responses to pre-defined experimental parameters. This type of analysis is not suitable for patterns of behavior that unfold freely, such as play behavior. Here, we attempt an alternative approach for exploratory data analysis on a single-trial level, applicable in more complex and naturalistic behavioral settings in which no two trials are identical. We analyze neural population activity in the prefrontal cortex (PFC) of rats playing hide-and-seek and show that it is possible to discover what aspects of the task are reflected in the recorded activity with a limited number of simultaneously recorded cells (≤ 31). Using hidden Markov models, we cluster population activity in the PFC into a set of neural states, each associated with a pattern of neural activity. Despite high variability in behavior, relating the inferred states to the events of the hide-and-seek game reveals neural states that consistently appear at the same phases of the game. Furthermore, we show that by applying the segmentation inferred from neural data to the animals' behavior, we can explore and discover novel correlations between neural activity and behavior. Finally, we replicate the results in a second dataset and show that population activity in the PFC displays distinct sets of states during playing hide-and-seek and observing others play the game. Overall, our results reveal robust, state-like representations in the rat PFC during unrestrained playful behavior and showcase the applicability of population analyses in naturalistic neuroscience.

The topographic map in layer 4 of somatosensory cortex is usually specified early postnatally and stable thereafter. Genital cortex, however, undergoes a sex-hormone- and sexual-touch-dependent pubertal expansion. Here, we image pubertal development of genital cortex in Scnn1a-Tg3-Cre mice, where transgene expression has been shown to be restricted to layer 4 neurons with primary sensory cortex identity. Interestingly, during puberty, the number of Scnn1a+ neurons roughly doubled within genital cortex. The increase of Scnn1a+ neurons was gradual and rapidly advanced by initial sexual experience. Neurons that gained Scnn1a expression comprised stellate and pyramidal neurons in layer 4. Unlike during neonatal development, pyramids did not retract their apical dendrites during puberty. Calcium imaging revealed stronger genital-touch responses in Scnn1a+ neurons in males versus females and a developmental increase in responsiveness in females. The first sexual interaction is a unique physical experience that often creates long-lasting memories. We suggest such experience uniquely alters somatosensory body maps.

Mammalian external genitals show sexual dimorphism [1, 2] and can change size and shape upon sexual arousal. Genitals feature prominently in the oldest pieces of figural art [3] and phallic depictions of penises informed psychoanalytic thought about sexuality [4, 5]. Despite this longstanding interest, the neural representations of genitals are still poorly understood [6]. In somatosensory cortex specifically, many studies did not detect any cortical representation of genitals [7-9]. Studies in humans debate whether genitals are represented displaced below the foot of the cortical body map [10-12] or whether they are represented somatotopically [13-15]. We wondered what a high-resolution mapping of genital representations might tell us about the sexual differentiation of the mammalian brain. We identified genital responses in rat somatosensory cortex in a region previously assigned as arm/leg cortex. Genital responses were more common in males than in females. Despite such response dimorphism, we observed a stunning anatomical monomorphism of cortical penis and clitoris input maps revealed by cytochrome-oxidase-staining of cortical layer 4. Genital representations were somatotopic and bilaterally symmetric, and their relative size increased markedly during puberty. Size, shape, and erect posture give the cortical penis representation a phallic appearance pointing to a role in sexually aroused states. Cortical genital neurons showed unusual multi-body-part responses and sexually dimorphic receptive fields. Specifically, genital neurons were co-activated by distant body regions, which are touched during mounting in the respective sex. Genital maps indicate a deep homology of penis and clitoris representations in line with a fundamentally bi-sexual layout [16] of the vertebrate brain.

Sensory nerves are information bottlenecks giving rise to distinct sensory worlds across animal species.1 Here, we investigate trigeminal ganglion2,3 and sensory nerves4 of elephants. The elephant trigeminal ganglion is very large. Its maxillary branch, which gives rise to the infraorbital nerve innervating the trunk, has a larger diameter than the animal's spinal cord, i.e., trunk innervation is more substantive than connections of the brain to the rest of the body. Hundreds of satellite cells surround each trigeminal neuron, an indication of exceptional glial support to these large projection neurons.5-7 Fiber counts of Asian elephant infraorbital nerves of averaged 4,00,000 axons. The infraorbital nerve consists of axons that are ∼10 μm thick and it has a large diameter of 17 mm, roughly 3 times as thick as the optic and 6 times as thick as the vestibulocochlear nerve. In most mammals (including tactile specialists) optic nerve fibers8-10 greatly outnumber infraorbital nerve fibers,11,12 but in elephants the infraorbital nerve fiber count is only slightly lower than the optic nerve fiber count. Trunk innervation (nerves and ganglia) weighs ∼1.5 kg in elephant cows. Our findings characterize the elephant trigeminal ganglion as one of the largest known primary sensory structures and point to a high degree of tactile specialization in elephants.

The elephant trunk operates as a muscular hydrostat1,2 and is actuated by the most complex musculature known in animals.3,4 Because the number of trunk muscles is unclear,5 we performed dense reconstructions of trunk muscle fascicles, elementary muscle units, from microCT scans of an Asian baby elephant trunk. Muscle architecture changes markedly across the trunk. Trunk tip and finger consist of about 8,000 extraordinarily filigree fascicles. The dexterous finger consists exclusively of microscopic radial fascicles pointing to a role of muscle miniaturization in elephant dexterity. Radial fascicles also predominate (at 82% volume) the remainder of the trunk tip, and we wonder if radial muscle fascicles are of particular significance for fine motor control of the dexterous trunk tip. By volume, trunk-shaft muscles6 comprise one-third of the numerous, small radial muscle fascicles; two-thirds of the three subtypes of large longitudinal fascicles (dorsal longitudinals, ventral outer obliques, and ventral inner obliques);7,8,9 and a small fraction of transversal fascicles. Shaft musculature is laterally, but not radially, symmetric. A predominance of dorsal over ventral radial muscles and of ventral over dorsal longitudinal muscles may result in a larger ability of the shaft to extend dorsally than ventrally10 and to bend inward rather than outward. There are around 90,000 trunk muscle fascicles. While primate hand control is based on fine control of contraction by the convergence of many motor neurons on a small set of relatively large muscles, evolution of elephant grasping has led to thousands of microscopic fascicles, which probably outnumber facial motor neurons.

Female mammals experience cyclical changes in sexual receptivity known as the estrus cycle. Little is known about how estrus affects the cortex, although alterations in sensation, cognition and the cyclical occurrence of epilepsy suggest brain-wide processing changes. We performed in vivo juxtacellular and whole-cell recordings in somatosensory cortex of female rats and found that the estrus cycle potently altered cortical inhibition. Fast-spiking interneurons were strongly activated with social facial touch and varied their ongoing activity with the estrus cycle and estradiol in ovariectomized females, while regular-spiking excitatory neurons did not change. In situ hybridization for estrogen receptor β (Esr2) showed co-localization with parvalbumin-positive (PV+) interneurons in deep cortical layers, mirroring the laminar distribution of our physiological findings. The fraction of neurons positive for estrogen receptor β (Esr2) and PV co-localization (Esr2+PV+) in cortical layer V was increased in proestrus. In vivo and in vitro experiments confirmed that estrogen acts locally to increase fast-spiking interneuron excitability through an estrogen-receptor-β-dependent mechanism.