Following a traumatic brain injury (TBI), the neocortex undergoes time-dependent cellular responses including immediate tissue deformation, enhanced excitability, and elevated expression of immediate early genes. However, the spatial extent of early neuronal activity after a focal injury remains unclear. Here we use targeted recombination in active populations reporter mice of both sexes to identify neurons activated in the acute phase following a controlled cortical impact injury applied to the somatosensory neocortex. We find widespread cell activation across large portions of the cortex that extends beyond the astrocytic and microglial responses marking the injury site. Activated cells are predominantly neurons, and few cells colabel with GFAP or IBA1. Our findings reveal that even focal injury engages cortical circuits across large portions of the injured brain, highlighting the importance of considering cortex-wide neuronal dynamics in the early postinjury period and their potential impact on network ...

Animal learning can be analyzed on two timescales: task acquisition across training sessions and motivation fluctuations within training sessions. How do variations in motor and neurophysiologic activity relate to task performance over these timescales? Here, this question was examined in head-fixed mice performing a whisker-based sensory discrimination task. Male mice were trained for 12–14 daily sessions on a go/no-go task, each lasting ∼1 h to capture spontaneous performance fluctuations over minutes. Simultaneous to task performance, “nonperformance variables” were tracked, including wheel running, pupil size, eyelid aperture, and sensory cortical activity. First, motivation states were defined based on performance tendencies over minutes, leading to three state categories: persistent, disengaged, or attentive. Nonperformance variables were found to predict these states independent of task correctness. Then, when further parsing these states by the go/no-go outcomes of hit, miss, false alarm, or correc...

The refinement of gross motor skills, such as locomotion, during development is conserved across vertebrate species. Our previous work demonstrated, in larval zebrafish, that dopaminergic signaling through the dopamine D2-like family of receptors, specifically the dopamine 4 receptor subtype, was necessary for the developmental transformation of behaviorally relevant locomotor activity from an immature to a mature pattern between 3 and 4 d postfertilization. In this study, we used a complement of tools, including electrophysiology, pharmacology, in vivo calcium imaging, liquid chromatography-mass spectrometry, and quantitative reverse transcription polymerase chain reaction to characterize the functional and molecular mechanisms responsible for this dopaminergic-mediated refinement of spinal locomotor activity. The results demonstrate that the dopamine 4 receptor subtype is functional in, at least, a subset of immature larvae. Further, gene expression of all D2-like receptor subtypes, levels of dopamine, a...

Spiking thresholds in neurons or rectification at synapses are essential for neuronal computations rendering neuronal processing inherently nonlinear. Nevertheless, linear response theory has been instrumental for understanding, for example, the impact of noise or neuronal synchrony on signal transmission, or the emergence of oscillatory activity, but is valid only at low stimulus amplitudes or large levels of intrinsic noise. At higher signal-to-noise ratios, however, nonlinear response components become relevant. Theoretical results for leaky integrate-and-fire neurons in the weakly nonlinear regime suggest strong responses at the sum of two input frequencies if one of these frequencies or their sum matches the neuron’s baseline firing rate. We here analyze nonlinear responses in two types of primary electroreceptor afferents, the P-units of the active and the ampullary cells of the passive electrosensory system of the wave-type electric fish Apteronotus leptorhynchus of either sex. In our combined exper...

In the article “Is Social Media Use a Blessing or Cure for Motor Function and Skill Acquisition? An Opinion …

Sensorimotor adaptation depends on implicit recalibration and explicit strategy. These processes are commonly assumed to sum ( A  =  I  +  E ), and this additivity assumption justifies subtractive measurement and informs computational models of motor learning. Recent work has challenged additivity by examining regression slopes between implicit and explicit measures. When slopes deviate from β  = −1, the interpretation has been that the processes are “sub-additive” and fail to sum as expected. Here, we show this reasoning is mistaken. Regression slopes reflect covariance structure: how learning processes relate across individuals. Additivity is a claim about motor output combination: whether learning processes sum within individuals. These are different questions, and regression slopes do not address the latter. We derive the expected slope under subtractive logic and show it equals β  = −1 only when total adaptation is uncorrelated with the measured component. Monte Carlo simulations confirm this benchmar...

There is considerable interest in cannabinoid-based therapies to treat pain, but activation of the endogenous cannabinoid (endocannabinoid) system can elicit pro- and anti-nociceptive effects. This study tests the hypothesis that the concentration of the endocannabinoid arachidonoylethanolamine (AEA) contributes to whether pro- or anti-nociceptive effects are observed. Experiments were carried out using isolated ganglia from the medicinal leech Hirudo verbana where it is possible to selectively record from nociceptive and non-nociceptive synapses in the central nervous system (CNS). Previous studies using Hirudo have shown that endocannabinoids depress nociceptive (N) sensory cell synapses and potentiate of non-nociceptive pressure (P) sensory cell synapses. In this study, exogenously applied AEA produced depression of N synapses and potentiation of P synapses across the same range of concentrations. However, the results differed when using URB597, a drug that raises AEA by inhibiting fatty acid amine hydr...

Multi-electrode recording of neuronal activity in cultures offer opportunities for understanding how the structure of a network gives rise to function. Neuronal cultures derived from human induced pluripotent stem cells (iPSCs) from male and female individuals are often plated at highly variable cell densities across studies, but its impact on neuronal activity remains poorly understood. We found that properties such as the mean firing rate of the individual cells, the pairwise correlations between cells, and the entropy of the population all changed significantly with changes in culture density. We used a maximum entropy model to capture the structure of the population activity using only the firing rates and correlations, and we found that the model performed best at the highest densities, suggesting that changes in activity reflected differences in structure of interactions between neurons across scales of complexity. Our work thus shows that culture density is an important experimental parameter that i...

Complex problems often allow multiple paths to a solution. Choosing and taking the best path is an important part of the executive cognition that underpins intelligent problem-solving behavior. However, once a path is chosen, the motor system must be activated for executing it. This interface between problem-solving and self-generated action has rarely been studied. We recorded EEG movement-related potentials while 25 participants (7 males, 18 females) performed the “Tower of London” problem-solving task. In a control condition, participants merely followed instructed steps without planning for any goal and thus without any sense that their movements solved a problem. Readiness potentials (RPs) preceding actions showed a more sustained preparatory negativity for self-generated than stimulus-driven movements. Critically, this effect was most pronounced at the first move of a sequence and diminished at later stages, indicating that preparatory activity is closely linked to the planning demands of sequence in...

Synaptic physiology experiments are fundamental to neuroscience research. Consequently, accurate detection of synaptic currents is crucial for conducting high-quality experiments. Traditionally, detecting inhibitory and excitatory postsynaptic currents (sIPSCs/sEPSCs) relied on hand-counting individual events. Although sEPSCs and sIPSCs are clear to the trained eye, hand analysis is time and labor intensive. Recent advances in applied machine learning promise faster, superior event detectors that may improve data quality and reduce or even completely negate the need for hand curation. While many strategies for sIPSC and sEPSC detection exist, rarely have they been quantitatively compared for accuracy within an experiment. Our study aims to establish practical ground-truth event detection in a large experimental dataset through meticulous hand counting and to assess variance in detection results across different laboratories, analysis techniques, and cell types. Using thoroughly hand-counted data as our gro...