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Neural electrodes have recently been developed with surface modifications of conductive polymers, in particular poly(3,4-ethylenedioxythiophene) (PEDOT), and extensively studied for their roles in recording and stimulation, aiming to improve their biocompatibility. In this work, the implications for the design of practical neural sensors are clarified, and systematic procedures for their preparation are reported. In particular, this study introduces the use of in vitro double electrode experiments to mimic the responses of neural electrodes with a focus on signal-recording electrodes modified with PEDOT. Specifically, potential steps on one unmodified electrode in an array are used to identify the responses for PEDOT doped with different anions and compared with that of a bare platinum (Pt) electrode. The response is shown to be related to the rearrangement of ions in solution near the detector electrode resulting from the potential step, with a current transient seen at the detector electrode. A rapid response for PEDOT doped with chloride (ca. 0.04 s) ions was observed and attributed to the fast movement of chloride ions in and out of the polymer film. In contrast, PEDOT doped with poly(styrenesulfonate) (PSS) responds much slower (ca. 2.2 s), and the essential immobility of polyanion constrains the direction of current flow.

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The paper analyzes the probability distribution of the occupancy numbers and the entropy of a system at the equilibrium composed by an arbitrary number of non-interacting bosons. The probability distribution is obtained through two approaches: one involves tracing out the environment from a bosonic eigenstate of the combined environment and system of interest (the empirical approach), while the other involves tracing out the environment from the mixed state of the combined environment and system of interest (the Bayesian approach). In the thermodynamic limit, the two coincide and are equal to the multinomial distribution. Furthermore, the paper proposes to identify the physical entropy of the bosonic system with the Shannon entropy of the occupancy numbers, fixing certain contradictions that arise in the classical analysis of thermodynamic entropy. Finally, by leveraging an information-theoretic inequality between the entropy of the multinomial distribution and the entropy of the multivariate hypergeometric distribution, Bayesianism of information theory and empiricism of statistical mechanics are integrated into a common "infomechanical" framework.

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Short-term memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both the prefrontal cortex and hippocampus, where neurons encode task cues, rules, and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC populations lead in maintaining sample information across delays of an operant non-match to sample task, despite individual neurons firing only transiently. During sample encoding, distinct mPFC subpopulations joined distributed CA1-mPFC cell assemblies hallmarked by 4-5 Hz rhythmic modulation; CA1-mPFC assemblies re-emerged during choice episodes but were not 4-5 Hz modulated. Delay-dependent errors arose when attenuated rhythmic assembly activity heralded collapse of sustained mPFC encoding. Our results map component processes of memory-guided decisions onto heterogeneous CA1-mPFC subpopulations and the dynamics of physiologically distinct, distributed cell assemblies.

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The initial representation of the instantaneous temporal information about food odor concentration in the primary olfactory center, the antennal lobe, was examined by simultaneously recording the activity of antagonistic ON and OFF neurons with 4-channel tetrodes. During presentation of pulse-like concentration changes, ON neurons encode the rapid concentration increase at pulse onset and the pulse duration, and OFF neurons the rapid concentration decrease at pulse offset and the duration of the pulse interval. A group of ON neurons establish a concentration-invariant representation of odor pulses. The responses of ON and OFF neurons to oscillating changes in odor concentration are determined by the rate of change in dependence on the duration of the oscillation period. By adjusting sensitivity for fluctuating concentrations, these neurons improve the representation of the rate of the changing concentration. In other ON and OFF neurons, the response to changing concentrations is invariant to large variations in the rate of change due to variations in the oscillation period, facilitating odor identification in the antennal-lobe. The independent processing of odor identity and the temporal dynamics of odor concentration may speed up processing time and improve behavioral performance associated with plume tracking, especially when the air is not moving.

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Hippocampal place cells are functional units of spatial navigation and are present in all subregions: CA1, CA2, CA3, and CA4. Recent studies on CA2 have indicated its role in social and contextual memories, but its contribution to spatial novelty detection and encoding remains largely unknown. The current study aims to uncover how CA2 processes spatial novelty and to distinguish its functional role towards the same from CA1. Accordingly, a novel 3-day paradigm was designed where animals were introduced to a completely new environment on the first day, and on subsequent days, novel segments were inserted into the existing spatial environment while the other segments remained the same, allowing us to compare novel and familiar parts of the same closed-loop track on multiple days. We found that spatial novelty leads to dynamic and complex hippocampal place cell firings at both individual neuron and population levels. Place cells in both CA1 and CA2 had strong responses to novel segments, leading to higher average firing rates and increased pairwise cross correlations across all days. However, CA2 place cells that fired for novel areas had lower spatial information scores than CA1 place cells active in the same areas. At the ensemble level, CA1 only responded to spatial novelty on day 1, when the environment was completely novel, whereas CA2 responded to it on all days, each time novelty was introduced. Therefore, CA2 was more sensitive and responsive to novel spatial features even when introduced in a familiar environment, unlike CA1.

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Animals predominantly use salient visual cues (landmarks) for efficient navigation. When the relative position of the visual cues is altered, the hippocampal population exhibits heterogeneous responses and constructs context-specific spatial maps. Another critical factor that can strongly modulate spatial representation is the presence of reward. Reward features can drive behavior and are known to bias spatial attention. However, it is unclear whether reward features are used for spatial reference in the presence of distal cues and how the hippocampus population dynamics changes when the association between reward features and distal cues is altered. We systematically investigated these questions by recording place cells from the CA1 in different sets of experiments while the rats ran in an environment with the conflicting association between reward features and distal cues. We report that, when rewards features were only used as local cues, the hippocampal place fields exhibited coherent and dynamical orientation across sessions, suggesting the use of a single coherent spatial map. We found that place cells maintained their spatial offset in the cue conflict conditions, thus showing a robust spatial coupling featuring an attractor-like property in the CA1. These results indicate that reward features may control the place field orientation but may not cause sufficient input difference to create context-specific spatial maps in the CA1.

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For navigation, animals use a robust internal compass. Compass navigation is crucial for long-distance migrating animals like monarch butterflies, which use the sun to navigate over 4,000 km to their overwintering sites every fall. Sun-compass neurons of the central complex have only been recorded in immobile butterflies, and experimental evidence for encoding the animal's heading in these neurons is still missing. Although the activity of central-complex neurons exhibits a locomotor-dependent modulation in many insects, the function of such modulations remains unexplored. Here, we developed tetrode recordings from tethered flying monarch butterflies to reveal how flight modulates heading representation. We found that, during flight, heading-direction neurons change their tuning, transforming the central-complex network to function as a global compass. This compass is characterized by the dominance of processing steering feedback and allows for robust heading representation even under unreliable visual scenarios, an ideal strategy for maintaining a migratory heading over enormous distances.

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Despite being an intensive area of research, the function of the anterior cingulate cortex (ACC) remains somewhat of a mystery. Human imaging studies implicate the ACC in various cognitive functions, yet surgical ACC lesions used to treat emotional disorders have minimal lasting effects on cognition. An alternative view is that ACC regulates autonomic states, consistent with its interconnectivity with autonomic control regions and that stimulation evokes changes in autonomic/emotional states. At the cellular level, ACC neurons are highly multi-modal and promiscuous, and can represent a staggering array of task events. These neurons nevertheless combine to produce highly event-specific ensemble patterns that likely alter activity in downstream regions controlling emotional and autonomic tone. Since neuromodulators regulate the strength of the ensemble activity patterns, they would regulate the impact these patterns have on downstream targets. Through these mechanisms, the ACC may determine how strongly to react to the very events its ensembles represent. Pathologies arise when specific event-related representations gain excessive control over autonomic/emotional states.

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BACKGROUND: Extracellular recording represents a crucial electrophysiological technique in neuroscience for studying the activity of single neurons and neuronal populations. The electrodes capture voltage traces that, with the help of analytical tools, reveal action potentials ('spikes') as well as local field potentials. The process of spike sorting is used for the extraction of action potentials generated by individual neurons. Until recently, spike sorting was performed with manual techniques, which are laborious and unreliable due to inherent operator bias. As neuroscientists add multiple electrodes to their probes, the high-density devices can record hundreds to thousands of neurons simultaneously, making the manual spike sorting process increasingly difficult. The advent of automated spike sorting software has offered a compelling solution to this issue and, in this study, we present a simple-to-execute framework for running an automated spike sorter. METHODS: Tetrode recordings of freely-moving mice are obtained from the CA1 region of the hippocampus as they navigate a linear track. Tetrode recordings are also acquired from the prelimbic cortex, a region of the medial prefrontal cortex, while the mice are tested in a T maze. All animals are implanted with custom-designed, 3D-printed microdrives that carry 16 electrodes, which are bundled in a 4-tetrode geometry. RESULTS: We provide an overview of a framework for analyzing single-unit data in which we have concatenated the acquisition system (Cheetah, Neuralynx) with analytical software (MATLAB) and an automated spike sorting pipeline (MountainSort). We give precise instructions on how to implement the different steps of the framework, as well as explanations of our design logic. We validate this framework by comparing manually-sorted spikes against automatically-sorted spikes, using neural recordings of the hippocampus and prelimbic cortex in freely-moving mice. CONCLUSIONS: We have efficiently integrated the MountainSort spike sorter with Neuralynx-acquired neural recordings. Our framework is easy to implement and provides a high-throughput solution. We predict that within the broad field of bioelectronic medicine, those teams that incorporate high-density neural recording devices to their armamentarium might find our framework quite valuable as they expand their analytical footprint.

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Objective. In tetrode recordings, the cell types of the recorded units are difficult to determine based on electrophysiological characteristics alone. Optotagging, the use of optogenetic stimulation to precisely identify cells, is a method to overcome this challenge. However, recording from many different cells requires advancing electrodes and light sources slowly through the brain with a microdrive. Existing designs suffer from a number of drawbacks, such as limited stability and precision, high cost, complex assembly, or excessive size and weight.Approach. We designed TetrODrive as a microdrive that can be 3D printed on an inexpensive desktop resin printer, has minimal parts, assembly time, and cost. The microdrive can be assembled in 15 min and the price for all materials, including the 3D printer, is lower than a single commercial microdrive. To maximize recording stability, we mechanically decoupled the drive mechanism from the electrical and optical connectors.Main results. The developed microdrive is small and light enough (<1.5 g) to be carried effortlessly by a mouse. It allows reliable recordings from single units and optogenetically identified units, even across recording sessions. In contrast to previous designs, it provides a decoupling of plugging forces from the main drive body for enhanced stability. Owing to its moveable optical fiber, our microdrive can also be used for fiber photometry. The cost of a single drive is below 20 €. We evaluated our microdrive by recording single units and calcium signals in the ventral tegmental area of mice and confirmed cell identity via optotagging. Thereby we found units not following the classical reward prediction error model.Significance. TetrODrive is a tiny, lightweight, and affordable microdrive for optophysiology in mice. Its open design, price, and built-in characteristics can significantly expand the use of microdrives in mice.

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In spite of being an intensive area of research focus, the anterior cingulate cortex (ACC) remains somewhat of an enigma. Many theories have focused on its role in various aspects of cognition yet surgically precise lesions of the ACC, used to treat severe emotional disorders in human patients, typically have no lasting effects on cognition. An alternative view is that the ACC has a prominent role in regulating autonomic states. This view is consistent with anatomical data showing that a main target of the ACC are regions involved in autonomic control and with the observation that stimulation of the ACC evokes changes in autonomic states in both animals and humans. From an electrophysiological perspective, ACC neurons appear able to represent virtually any event or internal state, even though there is not always a strong link between these representations and behavior. Ensembles of neurons form robust contextual representations that strongly influence how specific events are encoded. The activity patterns associated with these contextually-based event representations presumably impact activity in downstream regions that control autonomic state. As a result, the ACC may regulate the autonomic and perhaps emotional reactions to events it is representing. This event-based control of autonomic tone by the ACC would likely arise during all types of cognitive and affective processes, without necessarily being critical for any of them.

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Electron beams can be reflected by an electrode that is at a more negative potential than the cathode from which the beam is emitted. We want to design a mirror with a flat mirror electrode where the electrons are reflected at a plane very close to the electrode. The wave front of an electron can then be shaped when the mirror contains a surface topography or modulated potential. However, electron beams reflected by flat electron mirrors are usually characterized by high coefficients of chromatic and spherical aberration. When the mirror is combined with an electrostatic lens to form a tetrode mirror system, the situation deteriorates even further. This places a restrictive limit on the maximum aperture angle of the beam, and consequently also limits the attainable resolution at the image plane. We have numerically studied the dependence of these aberrations as a function of design parameters of the tetrode mirror consisting of a ground, lens, cap, and mirror electrode, and limited ourselves to only using flat electrodes with round apertures, at fixed electrode spacing. It turns out that the third order spherical aberration can be made negative. The negative third order aberration is then used to partially compensate the positive fifth order aberration. This way, a system configuration is obtained that, at 2 keV beam energy, provides a diffraction limited resolution of 7.6 nm at an image plane 25 mm from the mirror at beam semi-angles of 2.3 mrad, enabling an illumination radius of 40 µm at the mirror. The presented tetrode mirror design could spark innovative use of patterned electron mirrors as phase plates for electron microscopy in general, and for use as coherent beam splitters in Quantum Electron Microscopy in particular. An appendix presents a method to calculate the spot size of a focused beam in the presence of both third and fifth order spherical aberration coefficients, which is also applicable to Scanning (Transmission) Electron Microscopes with aberration correctors.

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Hippocampus-engaged behaviors stimulate neurogenesis in the adult dentate gyrus by largely unknown means. To explore the underlying mechanisms, we used tetrode recording to analyze neuronal activity in the dentate gyrus of freely moving adult mice during hippocampus-engaged contextual exploration. We found that exploration induced an overall sustained increase in inhibitory neuron activity that was concomitant with decreased excitatory neuron activity. A mathematical model based on energy homeostasis in the dentate gyrus showed that enhanced inhibition and decreased excitation resulted in a similar increase in neurogenesis to that observed experimentally. To mechanistically investigate this sustained inhibitory regulation, we performed metabolomic and lipidomic profiling of the hippocampus during exploration. We found sustainably increased signaling of sphingosine-1-phosphate, a bioactive metabolite, during exploration. Furthermore, we found that sphingosine-1-phosphate signaling through its receptor 2 increased interneuron activity and thus mediated exploration-induced neurogenesis. Taken together, our findings point to a behavior-metabolism circuit pathway through which experience regulates adult hippocampal neurogenesis.

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BACKGROUND: Recordings with tetrodes have proven to be more effective in isolating single neuron spiking activity than with single microwires. However, tetrodes have never been used in humans. We report on the characteristics, safety, compatibility with clinical intracranial recordings in epileptic patients, and performance, of a new type of hybrid electrode equipped with tetrodes. NEW METHOD: 240 standard clinical macroelectrodes and 102 hybrid electrodes were implanted in 28 patients. Hybrids (diameter 800 µm) are made of 6 or 9 macro-contacts and 2 or 3 tetrodes (diameter 70-80 µm). RESULTS: No clinical complication or adverse event was associated with the hybrids. Impedance and noise of recordings were stable over time. The design enabled multiscale spatial analyses that revealed physiopathological events which were sometimes specific to one tetrode, but could not be recorded on the macro-contacts. After spike sorting, the single-unit yield was similar to other hybrid electrodes and was sometimes as high as >10 neurons per tetrode. COMPARISON WITH EXISTING METHOD(S): This new hybrid electrode has a smaller diameter than other available hybrid electrodes. It provides novel spatial information due to the configuration of the tetrodes. The single-unit yield appears promising. CONCLUSIONS: This new hybrid electrode is safe, easy to use, and works satisfactorily for conducting multi-scale seizure and physiological analyses.

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The lateral septum (LS), which is innervated by the hippocampus, is known to represent spatial information. However, the details of place representation in the LS, and whether this place information is combined with reward signaling, remains unknown. We simultaneously recorded from rat CA1 and caudodorsal lateral septum in rat during a rewarded navigation task and compared spatial firing in the two areas. While LS place cells are less numerous than in hippocampus, they are similar to the hippocampus in field size and number of fields per cell, but with field shape and center distributions that are more skewed toward reward. Spike cross-correlations between the hippocampus and LS are greatest for cells that have reward-proximate place fields, suggesting a role for the LS in relaying task-relevant hippocampal spatial information to downstream areas, such as the VTA.

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The ability to act on knowledge about the value of stimuli or actions factors into simple foraging behaviors as well as complex forms of decision-making. In striatal regions, action representations are thought to acquire value through a gradual (reinforcement-learning based) process. It is unclear whether this is also true for anterior cingulate cortex (ACC) where neuronal representations tend to change abruptly. We recorded from ensembles of ACC neurons as rats deduced which of 3 levers was rewarded each day. The rat's lever preferences changed gradually throughout the sessions as they eventually came to focus on the rewarded lever. Most individual neurons changed their responses to both rewarded and nonrewarded lever presses abruptly (<2 trials). These transitions occurred asynchronously across the population but peaked near the point where the rats began to focus on the rewarded lever. Because the individual transitions were asynchronous, the overall change at the population level appeared gradual. Abrupt transitions in action representations of ACC neurons may be part of a mechanism that alters choice strategies as new information is acquired.

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In addition to coding a subject's location in space, the hippocampus has been suggested to code social information, including the spatial position of conspecifics. "Social place cells" have been reported for tasks in which an observer mimics the behavior of a demonstrator. We examine whether rat hippocampal neurons may encode the behavior of a minirobot, but without requiring the animal to mimic it. Rather than finding social place cells, we observe that robot behavioral patterns modulate place fields coding animal position. This modulation may be confounded by correlations between robot movement and changes in the animal's position. Although rat position indeed significantly predicts robot behavior, we find that hippocampal ensembles code additional information about robot movement patterns. Fast-spiking interneurons are particularly informative about robot position and global behavior. In conclusion, when the animal's own behavior is conditional on external agents, the hippocampus multiplexes information about self and others.

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The lateral septum (LS) has been implicated in anxiety and fear modulation and may regulate interactions between the hippocampus and regions, such as the VTA, that mediate goal-directed behavior. In this study, we simultaneously record from cells in the LS and the hippocampus during navigation and conditioning tasks. In the LS, we identify a speed and acceleration spiking code that does not map to states of anticipation or reward. Additionally, we identify an overlapping population of LS cells that change firing to cue and reward during conditioning. These cells display sharp wave ripple and theta modulation, spatial firing fields, and responses similar to the hippocampus during conditioning. These hippocampus-associated cells are not disproportionately speed or acceleration modulated, suggesting that these movement correlates are not hippocampally derived. Finally, we show that LS theta coordination is selectively enhanced in hippocampus-associated LS cells during navigation behavior that requires working memory. Taken together, these results suggest a role for the LS in transmitting spatial and contextual information, in concert with locomotor information, to downstream areas, such as the VTA, where value weighting may take place.

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Dopamine (DA) profoundly stimulates motor function as demonstrated by the hypokinetic motor symptoms in Parkinson's disease (PD) and by the hyperkinetic motor side effects during dopaminergic treatment of PD. Dopamine (DA) receptor-bypassing, optogenetics- and chemogenetics-induced spike firing of striatal DA D1 receptor (D1R)-expressing, direct pathway medium spiny neurons (dSPNs or dMSNs) promotes movements. However, the endogenous D1R-mediated effects, let alone those of DA replacement, on dSPN spike activity in freely-moving animals is not established. Here we show that using transcription factor Pitx3 null mutant (Pitx3Null) mice as a model for severe and consistent DA denervation in the dorsal striatum in Parkinson's disease, antidromically identified striatonigral neurons (D1R-expressing dSPNs) had a lower baseline spike firing rate than that in DA-intact normal mice, and these neurons increased their spike firing more strongly in Pitx3Null mice than in WT mice in response to injection of L-dopa or the D1R agonist, SKF81297; the increase in spike firing temporally coincided with the motor-stimulating effects of L-dopa and SKF81297. Taken together, these results provide the first evidence from freely moving animals that in parkinsonian striatum, identified behavior-promoting dSPNs become hyperactive upon the administration of L-dopa or a D1 agonist, likely contributing to the profound dopaminergic motor stimulation in parkinsonian animals and PD patients.

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The most widely used spike-sorting algorithms are semiautomatic in practice, requiring manual tuning of the automatic solution to achieve good performance. In this work, we propose a new fully automatic spike-sorting algorithm that can capture multiple clusters of different sizes and densities. In addition, we introduce an improved feature selection method, by using a variable number of wavelet coefficients, based on the degree of non-Gaussianity of their distributions. We evaluated the performance of the proposed algorithm with real and simulated data. With real data from single-channel recordings, in ~95% of the cases the new algorithm replicated, in an unsupervised way, the solutions obtained by expert sorters, who manually optimized the solution of a previous semiautomatic algorithm. This was done while maintaining a low number of false positives. With simulated data from single-channel and tetrode recordings, the new algorithm was able to correctly detect many more neurons compared with previous implementations and also compared with recently introduced algorithms, while significantly reducing the number of false positives. In addition, the proposed algorithm showed good performance when tested with real tetrode recordings. NEW & NOTEWORTHY We propose a new fully automatic spike-sorting algorithm, including several steps that allow the selection of multiple clusters of different sizes and densities. Moreover, it defines the dimensionality of the feature space in an unsupervised way. We evaluated the performance of the algorithm with real and simulated data, from both single-channel and tetrode recordings. The proposed algorithm was able to outperform manual sorting from experts and other recent unsupervised algorithms.

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