The overwhelming majority of research in the neurosciences employs P-values stemming from tests of statistical significance to decide on the presence or absence of an effect of some treatment variable. Although a continuous variable, the P-value is commonly used to reach a dichotomous decision about the presence of an effect around an arbitrary criterion of 0.05. This analysis strategy is widely used, but has been heavily criticized in the past decades. To counter frequent misinterpretations of P-values, it has been advocated to complement or replace P-values with measures of effect size (MES). Many psychological, biological and medical journals now recommend reporting appropriate MES. One hindrance to the more frequent use of MES may be their scarcity in standard statistical software packages. Also, the arguably most widespread data analysis software in neuroscience, matlab, does not provide MES beyond correlation and receiver-operating characteristic analysis. Here we review the most common criticisms of significance testing and provide several examples from neuroscience where use of MES conveys insights not amenable through the use of P-values alone. We introduce an open-access matlab toolbox providing a wide range of MES to complement the frequently used types of hypothesis tests, such as t-tests and analysis of variance. The accompanying documentation provides calculation formulae, intuitive explanations and example calculations for each measure. The toolbox described is usable without sophisticated statistical knowledge and should be useful to neuroscientists wishing to enhance their repertoire of statistical reporting.

Neuronal activity has been shown to be essential for the proper formation of neuronal circuits, affecting developmental processes like neurogenesis, migration, programmed cell death, cellular differentiation, formation of local and long-range axonal connections, synaptic plasticity or myelination. Accordingly, neocortical areas reveal distinct spontaneous and sensory-driven neuronal activity patterns already at early phases of development. At embryonic stages, when immature neurons start to develop voltage-dependent channels, spontaneous activity is highly synchronized within small neuronal networks and governed by electrical synaptic transmission. Subsequently, spontaneous activity patterns become more complex, involve larger networks and propagate over several neocortical areas. The developmental shift from local to large-scale network activity is accompanied by a gradual shift from electrical to chemical synaptic transmission with an initial excitatory action of chloride-gated channels activated by GABA, glycine and taurine. Transient neuronal populations in the subplate (SP) support temporary circuits that play an important role in tuning early neocortical activity and the formation of mature neuronal networks. Thus, early spontaneous activity patterns control the formation of developing networks in sensory cortices, and disturbances of these activity patterns may lead to long-lasting neuronal deficits.

The rat whisker system has evolved into in an excellent model system for sensory processing from the periphery to cortical stages. However, to elucidate how sensory processing finally relates to percepts, methods to assess psychophysical performance pertaining to precise stimulus kinematics are needed. Here, we present a head-fixed, behaving rat preparation that allowed us to measure detectability of a single whisker deflection as a function of amplitude and peak velocity. We found that velocity thresholds for detection of smallamplitude stimuli (Ͻ3°) were considerably higher than for detection of large-amplitude stimuli (Ͼ3°). This finding suggests the existence of two psychophysical channels mediating detection of whisker deflection: one channel exhibiting high amplitude and low velocity thresholds (W1), and the other channel exhibiting high velocity and low amplitude thresholds (W2). The correspondence of W1 to slowly adapting (SA) and W2 to rapidly adapting (RA) neuronal classes in the trigeminal ganglion was revealed in acute neurophysiological experiments. Neurometric plots of SA and RA cells were closely aligned to psychophysical performance in the corresponding W1 and W2 parameter ranges. Interestingly, neurometric data of SA cells fit the behavior best if it was based on a short time window integrating action potentials during the initial phasic response, in contrast to integrating across the tonic portion of the response. This suggests that detection performance in both channels is based on the assessment of very few spikes in their corresponding groups of primary afferents.

This paper describes experimental techniques with head-fixed, operantly conditioned rodents that allow the control of stimulus presentation and tracking of motor output at hitherto unprecedented levels of spatio-temporal precision. Experimental procedures for the surgery and behavioral training are presented. We place particular emphasis on potential pitfalls using these procedures in order to assist investigators who intend to engage in this type of experiment. We argue that head-fixed rodent models, by allowing the combination of methodologies from molecular manipulations, intracellular electrophysiology, and imaging to behavioral measurements, will be instrumental in combining insights into the functional neuronal organization at different levels of observation. Provided viable behavioral methods are implemented, model systems based on rodents will be complementary to current primate models—the latter providing highest comparability with the human brain, while the former offer hugely advanced methodologies on the lower levels of organization, for example, genetic alterations, intracellular electrophysiology, and imaging.

Signal detection theoretical analyses of spike counts have revealed that some cortical neurons can exceed psychophysical sensitivity in cases where a sensory signal is specified exactly. It is not known whether this finding holds in the more natural situation where signal occurrence is temporally uncertain. We investigated the ability of rat barrel cortex neurons to detect faint and transient whisker deflections occurring at unspecified times. The progression from fully specified stimuli to temporal uncertainty degraded neuronal sensitivity such that it seems highly unlikely that single neurons can provide the basis for decoding uncertain perceptual events. However, modeling the sensitivity of neuronal pools on basis of spike timing precision across several neurons in an optimal encoding window of 25 ms showed that the subject's perceptual sensitivity could be based on the occurrence of coincident spikes from four to five neurons.

Understanding the neural code underlying perception requires the mapping of physical stimulus parameters to both psychophysical decisions and neuronal responses. Here, we employed a novel psychophysical task in head-fixed rats to measure discriminability of vibrotactile whisker deflections. Rats could discriminate 90 Hz from 60 Hz pulsatile stimuli if stimulus intensity covaried with frequency. To pin down the physical parameters used by the rats to discriminate these vibrations, we manipulated stimulus amplitude to arrive at pairs of nondiscriminable stimuli. We found that vibrations matched in intensity (measured as mean absolute velocity), but differing in frequency, were no longer discriminable. Recordings of trigeminal ganglion neurons revealed that the distribution of neurometric sensitivities based on spike counts, but not interspike intervals, matched the rats' inability to discriminate intensity-matched stimuli. In conclusion, we suggest that stimulus mean absolute velocity, encoded in primary afferent spike counts, plays a prominent role for whisker-mediated perception.

Rodent rhythmic whisking behavior matures during a critical period around 2 weeks after birth. The functional adaptations of neocortical circuitry during this developmental period remain poorly understood. Here, we characterized stimulus-evoked neuronal activity across all layers of mouse barrel cortex before, during, and after the onset of whisking behavior. Employing multi-electrode recordings and 2-photon calcium imaging in anesthetized mice, we tested responses to rostro-caudal whisker deflections, axial "tapping" stimuli, and their combination from postnatal day 10 (P10) to P28. Within this period, whisker-evoked activity of neurons displayed a general decrease in layer 2/3 (L2/3) and L4, but increased in L5 and L6. Distinct alterations in neuronal response adaptation during the 2-s period of stimulation at ~5 Hz accompanied these changes. Moreover, single-unit analysis revealed that response selectivity in favor of either lateral deflection or axial tapping emerges in deeper layers within the critical period around P14. For superficial layers we confirmed this finding using calcium imaging of L2/3 neurons, which also exhibited emergence of response selectivity as well as progressive sparsification and decorrelation of evoked responses around P14. Our results demonstrate layer-specific development of sensory responsiveness and response selectivity in mouse somatosensory cortex coinciding with the onset of exploratory behavior.

Rats explore environments by sweeping their whiskers across objects and surfaces. Both sensor movement and repetitive sweeping typical for this behavior require that vibrotactile signals are integrated over time. While temporal integration properties of neurons along the whisker somatosensory pathway have been studied extensively, the consequences for behavior are unknown. Here, we investigate the ability of headfixed rats to integrate information over time for the detection of near-threshold pulsatile deflection sequences applied to a single whisker. Psychometric detection performance was assessed with whisker stimuli composed of different numbers of pulses (1-31) delivered at varying frequencies (10, 20, 100 Hz). Detection performance indeed improved with increasing number and frequency of pulses, albeit this improvement was much lower than predicted by probabilistic combination, suggesting highly sublinear integration of pulses. This behavioral observation was reflected in the firing properties of concomitantly recorded barrel cortex neurons, which showed substantial response adaptation to repetitive whisker deflection. To estimate the integration time with which barrel cortex neuronal activity must be read out to match behavior, we constructed a model monitoring spiking activity of simulated neuronal pools, where spike trains were channeled through a leaky integrator with exponential decay. Detection was accomplished by simple threshold crossings. This simple model gave an excellent match of neurometric and psychometric data at surprisingly small time constants of 5-8 ms, thus limiting integration largely to Ͻ25 ms. This result carries important implications regarding sensory processing for whisker-mediated perception.