Our brains make sense of the world on a moment-by-moment basis despite its enormous complexity, largely because its overall statistical structure can be detected, learned, and generalized across experiences. Exposure to specific regularities (e.g., in speech) results in an unsupervised, incidental, form of learning, commonly known as statistical learning (SL). SL is well-established from a cognitive perspective and often assumed to require high-level cortical or hippocampal processing. However, accumulating evidence suggests that SL emerges much earlier in ascending sensory pathways. Despite this, our understanding of the forms it might take in subcortical sensory centres is relatively limited. Here, we review neuronal sensitivity to statistics in early sensory regions and ask how this sensitivity relates to SL. We feature examples of adaptive responses elicited by stimulus repetitions, omissions, changes in stimulus distribution, and more complex patterning, highlighting the interplay between adaptive coding and SL as manifestations of sensitivity to environmental statistics.

Sensory Adaptation (SA) is a prominent aspect of how neurons respond to sensory signals, ubiquitous across species and modalities. However, SA depends on the activation state of the brain and the extent to which SA is expressed in awake, behaving animals during active sensation remains unclear. Here, we addressed this question by training head-fixed mice to detect an object using their whiskers and recording neuronal activity from barrel cortex whilst simultaneously imaging the whiskers in 3D. We found that neuronal responses decreased during the course of whisker-object touch sequences and that this was due to two factors. First, a motor effect, whereby, during a sequence of touches, later touches were mechanically weaker than early ones. Second, a sensory encoding effect, whereby neuronal tuning to touch became progressively less sensitive during the course of a touch sequence. The sensory encoding effect was whisker-specific. These results show that SA does occur during active whisker sensing and suggest that SA is fundamental to sensation during natural behaviour.

Diffraction-limited two-photon microscopy permits minimally invasive optical monitoring of neuronal activity. However, most conventional two-photon microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing a non-telecentric optical design, we present a low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view. Moreover, rapid laser-focus control via an electrically tunable lens allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in zebrafish, mice and fruit flies.

The use of head fixation in mice is increasingly common in research, its use having initially been restricted to the field of sensory neuroscience. Head restraint has often been combined with fluid control, rather than food restriction, to motivate behaviour, but this too is now in use for both restrained and non-restrained animals. Despite this, there is little guidance on how best to employ these techniques to optimise both scientific outcomes and animal welfare. This article summarises current practices and provides recommendations to improve animal wellbeing and data quality, based on a survey of the community, literature reviews, and the expert opinion and practical experience of an international working group convened by the UK's National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs). Topics covered include head fixation surgery and post-operative care, habituation to restraint, and the use of fluid/food control to motivate performance. We also discuss some recent developments that may offer alternative ways to collect data from large numbers of behavioural trials without the need for restraint. The aim is to provide support for researchers at all levels, animal care staff, and ethics committees to refine procedures and practices in line with the refinement principle of the 3Rs.

Sequential temporal ordering and patterning are key features of natural signals used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence recognition, we developed a task in which mice distinguished between tactile ‘words’ constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a ‘detection of change’ problem, but enhanced their performance when deliberating for longer. Optogenetic inactivation showed that both primary somatosensory ‘barrel’ cortex (S1bf) and secondary somatosensory cortex were necessary for sequence recognition. Two-photon imaging of calcium activity in S1bf layer 2/3 revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal’s action decision and the trial outcome (presence or absence of a predicted reward). A large proportion of neurons were activated preceding goal-directed licking, thus reflecting the animal’s learnt response to the target sequence rather than the sequence itself; these neurons were found in S1bf as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory responses: neurons responding to stimulus features were already found in naïve mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf sequence learning results in neurons whose activity reflects the learnt association between the target sequence and licking, rather than a refined representation of sensory features. ### Competing Interest Statement Michael Bale is now employed by Scientifica, manufacturer of the two-photon microscope used in the study.

Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence discrimination, we developed a task in which mice distinguished between tactile "word" sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a "detection of change" problem, but enhanced their performance when responding later. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory "barrel" cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal's action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal's learned action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were found in naive mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf, sequence learning results in neurons whose activity reflects the learned association between target sequence and licking rather than a refined representation of sensory features.

In neuroscience, diffraction limited two-photon (2P) microscopy is a cornerstone technique that permits minimally invasive optical monitoring of neuronal activity. However, most conventional 2P microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing a non-telecentric (nTC) optical design, we present an ultra-low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view that also maintains single-cell resolution. We show that this implementation also allows for straight-forward tailoring of the point-spread-function, increases effective excitation power, and achievable image brightness. Moreover, rapid laser-focus control via an electrically tunable lens allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, and compatible with a wide range of existing 2P customizations, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in zebrafish, mice and fruit flies.

Mice discriminate tactile stimulus sequences distinguishable by the ordering of their elements. They detect changes between adjacent stimulus elements, focusing on the earliest cues allowing discrimination. Longer deliberation correlates with higher performance. Optogenetic suppression of barrel cortex (S1bf) or secondary somatosensory cortex (S2) reduces licking responses and abolishes discrimination, consistent with a loss of sensory input. Suppression of posterior parietal cortex (PPC) has no detectable effect. Suppression of whisker primary motor cortex (wM1) disinhibits lick responses. Two-photon imaging reveals that S1bf and PPC neurons show heterogeneous responses during sequence discrimination, reflecting sensory, decision/motor, and reward task variables. Our results are consistent with the decision to lick being achieved by a fast neuronal loop involving later processing stages. Upon learning a sequence, neurons in whisker somatosensory cortex link the target sequence with the associated (learnt) action.

The cerebral cortex contains multiple areas with distinctive cytoarchitectonic patterns, but the cellular mechanisms underlying the emergence of this diversity remain unclear. Here, we have investigated the neuronal output of individual progenitor cells in the developing mouse neocortex using a combination of methods that together circumvent the biases and limitations of individual approaches. Our experimental results indicate that progenitor cells generate pyramidal cell lineages with a wide range of sizes and laminar configurations. Mathematical modeling indicates that these outcomes are compatible with a stochastic model of cortical neurogenesis in which progenitor cells undergo a series of probabilistic decisions that lead to the specification of very heterogeneous progenies. Our findings support a mechanism for cortical neurogenesis whose flexibility would make it capable to generate the diverse cytoarchitectures that characterize distinct neocortical areas.

Rats using their whiskers to identify a texture gather evidence touch by touch until they reach a threshold. On every touch, the somatosensory cortex sends a packet of texture information to downstream regions tasked with integrating this evidence.

In neuroscience, diffraction limited two-photon (2P) microscopy is a cornerstone technique that permits minimally invasive optical monitoring of neuronal activity. However, most conventional 2P microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing ‘divergent beam optics’ (DBO), we present an ultra-low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view that also maintains single-cell resolution. We show that this implementation increases both the space-bandwidth product and effective excitation power, and allows for straight-forward tailoring of the point-spread-function. Moreover, rapid laser-focus control via an electrically tunable lens now allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, and fully compatible with a wide range of existing 2P customizations, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in mice, zebrafish and fruit flies.

Neural network computation occurs over a wide range of spatial scales including brain-wide circuits. Studying brain-wide computation therefore requires the ability to simultaneously monitor activity of arbitrary groups of neurons largely independent of their individual 3D positions. Using 2-photon imaging, this remains a challenging task: rapidly guiding the excitation laser between any two positions in 3D space is limited by the speed of movements of optical elements such as scanning mirrors or z-focusing mechanisms. Here, we use a simple optical trick to dramatically ameliorate this problem, thus allowing for rapid random-access 3D mesoscale imaging. With an investment below £1,000, we simplified a standard Sutter-MOM 2-photon setup into a non-collimated design, thereby extending the standard 0.5 mm x-y field of view by 7-fold to 3.5 x 3.5 mm using a standard x20 objective. In hand, an electrically tunable lens (ETL) placed in the still expanding pre-galvo laser permits rapid z-travel by up to 0.6 mm. Together, these simple modifications allow running arbitrary 3D scan-paths across a volume of 3.5x3.5x0.6 mm with a maximal travel time of 2 ms between any two points. Our design opens up a wide range of eminently useful scan-options, including mesoscale random-access scans as well as vertical and 3D curved scans that acknowledge the 3D structure of biological samples. We demonstrate the capability of this setup using a wide range of examples from mice, zebrafish and Drosophila

SUMMARY The cerebral cortex contains multiple hierarchically organized areas with distinctive cytoarchitectonical patterns, but the cellular mechanisms underlying the emergence of this diversity remain unclear. Here, we have quantitatively investigated the neuronal output of individual progenitor cells in the ventricular zone of the developing mouse neocortex using a combination of methods that together circumvent the biases and limitations of individual approaches. We found that individual cortical progenitor cells show a high degree of stochasticity and generate pyramidal cell lineages that adopt a wide range of laminar configurations. Mathematical modelling these lineage data suggests that a small number of progenitor cell populations, each generating pyramidal cells following different stochastic developmental programs, suffice to generate the heterogenous complement of pyramidal cell lineages that collectively build the complex cytoarchitecture of the neocortex.

To compare information and reach decisions effectively, our brain uses multiple heuristics, which can, however, induce biases in behavior. An elegant study by Akrami et al. (2018) finds evidence for one such heuristic in a sensory-based comparison task and identifies its location to the posterior parietal cortex.

In vertebrate vision, signals are pre-processed in the retina and projected to diverse brain areas to ultimately drive animal behavior. However, how different brain areas integrate different streams of visual information, and how they are connected, remains an area of active research. For example, many retinal output axons do not simply innervate a single brain target, but instead bifurcate to simultaneously drive two or more distinct areas based on the same original spike train. Is this bifurcation simply a duplication of original message, or might there be additional, asymmetric modification of the message in each output branch? To understand these types of questions, we would ideally like to simultaneously monitor neuronal activity in the eye and multiple brain areas. Here, we present our progress towards achieving this imaging capability using scanning 2-photon microscopy which, unlike 1-photon imaging, allows imaging inside the live retina without strongly exciting photoreceptors. Our ultra-low-cost solution only requires optical modifications of a typical commercial microscopes’ optical pathway and the addition of an electrical tunable lens. All control circuits are implemented using off-the-shelf microcontrollers and a standalone MATLAB GUI. By simplifying and tuning a standard Sutter-MOM 2-photon setup into a noncollimated design, we can extend our x-y field of view up to 3,000 x 3,000 μm using a standard x20 objective. In hand, our z-range covers 600 μm within 2 ms without strongly distorting the excitation volume or efficiency. Our design also provides for millisecond excitation power adjustment via a Pockels cell, as required. Finally, we achieve arbitrary spectrum optical/optogenetic stimulation by synchronizing our light sources with the scan retrace. Taken together, we can create arbitrary scan-paths across a volume of 3x3x0.6 mm with a maximal travel time of 2 ms during arbitrary spectrum optical stimulation. Here, we demonstrate the capability of this setup using examples from zebrafish and Drosophila.

Our sensory receptors are faced with an onslaught of different environmental inputs. Each sensory event or encounter with an object involves a distinct combination of physical energy sources impinging upon receptors. In the rodent whisker system, each primary afferent neuron located in the trigeminal ganglion innervates and responds to a single whisker and encodes a distinct set of physical stimulus properties - features - corresponding to changes in whisker angle and shape and the consequent forces acting on the whisker follicle. Here we review the nature of the features encoded by successive stages of processing along the whisker pathway. At each stage different neurons respond to distinct features, such that the population as a whole represents diverse properties. Different neuronal types also have distinct feature selectivity. Thus, neurons at the same stage of processing and responding to the same whisker nevertheless play different roles in representing objects contacted by the whisker. This diversity, combined with the precise timing and high reliability of responses, enables populations at each stage to represent a wide range of stimuli. Cortical neurons respond to more complex stimulus properties - such as correlated motion across whiskers - than those at early subcortical stages. Temporal integration along the pathway is comparatively weak: neurons up to barrel cortex (BC) are sensitive mainly to fast (tens of milliseconds) fluctuations in whisker motion. The topographic organization of whisker sensitivity is paralleled by systematic organization of neuronal selectivity to certain other physical features, but selectivity to touch and to dynamic stimulus properties is distributed in "salt-andpepper" fashion. This article is part of a Special Issue entitled: Barrel Cortex. (C) 2017 The Author(s). Published by Elsevier Ltd on behalf of IBRO.

Understanding how neurons encode and compute information is fundamental to our study of the brain, but opportunities for hands-on experience with neurophysiological techniques on live neurons are scarce in science education. Here, we present Spikeling, an open source in silico implementation of a spiking neuron that costs £25 and mimics a wide range of neuronal behaviours for classroom education and public neuroscience outreach. Spikeling is based on an Arduino microcontroller running the computationally efficient Izhikevich model of a spiking neuron. The microcontroller is connected to input ports that simulate synaptic excitation or inhibition, to dials controlling current injection and noise levels, to a photodiode that makes Spikeling light sensitive, and to a light-emitting diode (LED) and speaker that allows spikes to be seen and heard. Output ports provide access to variables such as membrane potential for recording in experiments or digital signals that can be used to excite other connected Spikelings. These features allow for the intuitive exploration of the function of neurons and networks mimicking electrophysiological experiments. We also report our experience of using Spikeling as a teaching tool for undergraduate and graduate neuroscience education in Nigeria and the United Kingdom.