Behavioral Neuroscience publications

Fear conditioning is a form of associative learning that is known to involve different brain areas, notably the amygdala, the prefrontal cortex and the periaqueductal grey (PAG). Here, we describe the functional role of pathways that link the cerebellum with the fear network. We found that the cerebellar fastigial nucleus (FN) sends glutamatergic projections to vlPAG that synapse onto glutamatergic and GABAergic vlPAG neurons. Chemogenetic and optogenetic manipulations revealed that the FN-vlPAG pathway controls bi-directionally the strength of the fear memories, indicating an important role in the association of the conditioned and unconditioned stimuli, a function consistent with vlPAG encoding of fear prediction error. Moreover, FN-vlPAG projections also modulate extinction learning. We also found a FN-parafascicular thalamus pathway, which may relay cerebellar influence to the amygdala and modulates anxiety behaviors. Overall, our results reveal multiple contributions of the cerebellum to the emotional system.

A major frontier in neuroscience is to find neural correlates of perception, learning, decision making, and a variety of other types of behavior. In the last decades, modern devices allow simultaneous recordings of different operant responses and the electrical activity of large neuronal populations. However, the commercially available instruments for studying operant conditioning are expensive, and the design of low-cost chambers has emerged as an appealing alternative to resource-limited laboratories engaged in animal behavior. In this article, we provide a full description of a platform that records the operant behavior and synchronizes it with the electrophysiological activity. The programming of this platform is open source, flexible, and adaptable to a wide range of operant conditioning tasks. We also show results of operant conditioning experiments with freely moving rats with simultaneous electrophysiological recordings.

The functional role of spontaneous brain activity, especially in relation to external events, is a longstanding key question in neuroscience. Intrinsic and externally-evoked activities were suggested to be anticorrelated, yet inferring an antagonistic mechanism between them remains a challenge. Here, we used beta-band (15-30 Hz) power as a proxy of spontaneous activity in the rat somatosensory cortex during a detection task. Beta-power anticorrelated with sensory-evoked-responses, and high rates of spontaneously occurring beta-bursts predicted reduced detection. By applying a burst-rate detection algorithm in real-time and trial-by-trial stimulus-intensity adjustment, this influence could be counterbalanced. Mechanistically, bursts in all bands indicated transient synchronization of cell assemblies, but only beta-bursts were followed by a reduction in firing-rate. Our findings reveal that spontaneous beta-bursts reflect a dynamic state that competes with external stimuli.

Field potential (FP) oscillations are believed to coordinate brain activity over large spatiotemporal scales, with specific features (e.g., phase and power) in discrete frequency bands correlated with motor output. Furthermore, complex correlations between oscillations in distinct frequency bands (phase-amplitude, amplitude-amplitude, and phase-phase coupling) are commonly observed. However, the mechanisms underlying FP-behavior correlations and cross-frequency coupling remain unknown. The thalamus plays a central role in generating many circuit-level neural oscillations, and single-unit activity in motor thalamus (Mthal) is correlated with behavioral output. We, therefore, hypothesized that motor thalamic spiking coordinates motor system FPs and underlies FP-behavior correlations. To investigate this possibility, we recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced-choice task. Delta (1-4 Hz), beta (13-30 Hz), low gamma (30-70 Hz), and high gamma (70-200 Hz) power were strongly modulated by task performance. As in the cortex, the delta phase was correlated with beta/low gamma power and reaction time. Most interestingly, subpopulations of Mthal neurons defined by their relationship to the behavior exhibited distinct relationships with FP features. Specifically, neurons whose activity was correlated with action selection and movement speed were entrained to delta oscillations. Furthermore, changes in their activity anticipated power fluctuations in beta/low gamma bands. These complex relationships suggest mechanisms for commonly observed FP-FP and spike-FP correlations, as well as subcortical influences on motor output.

Mammalian cortex has both local and cross-area connections, suggesting vital roles for both local and cross-area neural population dynamics in cortically-dependent tasks, like movement learning. Prior studies of movement learning have focused on how single-area population dynamics change during short-term adaptation. It is unclear how cross-area dynamics contribute to movement learning, particularly long-term learning and skill acquisition. Using simultaneous recordings of rodent motor (M1) and premotor (M2) cortex and computational methods, we show how cross-area activity patterns evolve during reach-to-grasp learning in rats. The emergence of reach-related modulation in cross-area activity correlates with skill acquisition, and single-trial modulation in cross-area activity predicts reaction time and reach duration. Local M2 neural activity precedes local M1 activity, supporting top–down hierarchy between the regions. M2 inactivation preferentially affects cross-area dynamics and behavior, with minimal disruption of local M1 dynamics. Together, these results indicate that cross-area population dynamics are necessary for learned motor skills.

The basal ganglia play a crucial role in the control of voluntary movements. Neurons in both the external and internal segments of the globus pallidus, the connecting and output nuclei of the basal ganglia, respectively, change their firing rates in relation to movements. Firing rate changes of movement‐related neurons seem to convey signals for motor control. On the other hand, coincident spikes among neurons, that is, correlated activity, may also contribute to motor control. To address this issue, we first identified multiple pallidal neurons receiving inputs from the forelimb regions of the primary motor cortex and supplementary motor area, recorded neuronal activity of these neurons simultaneously, and analyzed their spike correlations while monkeys performed a hand‐reaching task. Most (79%) pallidal neurons exhibited task‐related firing rate changes, whereas only a small fraction (20%) showed significant but small and short correlated activity during the task performance. These results suggest that motor control signals are conveyed primarily by firing rate changes in the external and internal segments of the globus pallidus and that the contribution of correlated activity may play only a minor role in the healthy state.

Somatostatin improves visual perception by reducing excitatory inputs to the parvalbumin-positive interneurons in the cortex.

Fear conditioning is a form of associative learning that is known to involve brain areas, notably the amygdala, the prefrontal cortex and the periaqueductal grey (PAG). Here, we describe the functional role of pathways that link the cerebellum with the fear network. We found that the cerebellar fastigial nucleus (FN) sends glutamatergic projections to vlPAG that synapse onto glutamatergic and GABAergic vlPAG neurons. Chemogenetic and optogenetic manipulations revealed that the FN-vlPAG pathway controls bi-directionally the strength of the fear memory, indicating a role in the association of the conditioned and unconditioned stimuli, a function consistent with vlPAG encoding of fear prediction error. In addition, we found that a FN - thalamic parafascicular nucleus pathway, which may relay cerebellar influence to the amygdala, is involved in anxiety and fear expression but not in fear memory. Our results reveal the contributions to the emotional system of the cerebellum, which exerts a potent control on the strength of the fear memory through excitatory FN-vlPAG projections.

Neural oscillations as important information carrier in the brain, are increasingly interpreted as transient bursts rather than as sustained oscillations. Short (<150 ms) bursts of beta-waves (15–30 Hz) have been documented in humans, monkeys and mice. These events were correlated with memory, movement and perception, and were even suggested as the primary ingredient of all beta-band activity. However, a method to measure these short-lived events in real-time and to investigate their impact on behaviour is missing. Here we present a real-time data analysis system, capable to detect short narrowband bursts, and demonstrate its usefulness to increase the beta-band burst-rate in rats. This neurofeedback training induced changes in overall oscillatory power, and bursts could be decoded from the movement of the rats, thus enabling future investigation of the role of oscillatory bursts.

Animal behavioral paradigms, such as classical conditioning and operant conditioning, are an important tool to study the neural basis of cognition and behavior. These paradigms involve manipulating sensory stimuli in a way that learning processes are induced under controlled experimental conditions. However, the majority of the commercially available equipment did not offer flexibility to manipulate stimuli. Therefore, the development of most versatile devices would allow the study of more complex cognitive functions. The purpose of this work is to present a low-cost, customized and wireless-operated chamber for animal behavior conditioning, based on the joint operation of two microcontroller modules: Arduino Due and ESP8266-12E. Our results showed that the auditory stimulation system allows setting the carrier frequency in the range of 1 Hz up to more than 100 kHz and the sound stimulus can be modulated in amplitude, also over a wide range of frequencies. Likewise, foot-shock could be precisely manipulated regarding its amplitude (from ∼200 μA to ∼1500 μA) and frequency (up to 20 pulses per second). Finally, adult rats exposed to a protocol of cued fear conditioning in our device showed consistent behavioral response and electrophysiological evoked responses in the midbrain auditory pathway. Furthermore, the device developed in the current study represents an open source alternative to develop customized protocols to study fear memory under conditions of varied sensory stimuli.

The ability to recognize sounds in noise is a key part of hearing, and the mechanisms by which the brain identifies sounds in noise are of considerable interest to scientists, clinicians and engineers. Yet we know little about the necessity of regions such as auditory cortex for hearing in noise, or how cortical processing of sounds is adversely affected by noise. Here we used reversible cortical inactivation and extracellular electrophysiology in ferrets performing a vowel discrimination task to identify and understand the causal contribution of auditory cortex to hearing in noise. Cortical inactivation by cooling impaired task performance in noisy but not clean conditions, while responses of auditory cortical neurons were less informative about vowel identity in noise. Simulations mimicking cortical inactivation indicated that effects of inactivation were related to the loss of information about sounds represented across neural populations. The addition of noise to target sounds drove spiking activity in auditory cortex and recruitment of additional neural populations that were linked to degraded behavioral performance. To suppress noise-related activity, we used continuous exposure to background noise to adapt the auditory system and recover behavioral performance in both ferrets and humans. Inactivation by cooling revealed that the benefits of continuous exposure were not cortically dependent. Together our results highlight the importance of auditory cortex in sound discrimination in noise and the underlying mechanisms through which noise-related activity and adaptation shape hearing.

Manipulations that enhance neuroplasticity may inadvertently create opportunities for maladaptation. We have previously used passive exposures to non-traumatic white noise to open windows of plasticity in the adult rat auditory cortex and induce frequency-specific functional reorganizations of the tonotopic map. However, similar reorganizations in the central auditory pathway are thought to contribute to the generation of hearing disorders such as tinnitus and hyperacusis. Here, we investigate whether noise-induced reorganizations are accompanied by electrophysiological or behavioral evidence of tinnitus or hyperacusis in adult Long-Evans rats. We used a 2-week passive exposure to moderate-intensity (70 dB SPL) broadband white noise to reopen a critical period for spectral tuning such that a second 1-week exposure to 7 kHz tone pips produced an expansion of the 7 kHz frequency region in the primary auditory cortex (A1). We demonstrate for the first time that this expansion also takes place in the ventral auditory field (VAF). Sound exposure also led to spontaneous and sound-evoked hyperactivity in the anterior auditory field (AAF). Rats were assessed for behavioral evidence of tinnitus or hyperacusis using gap and tone prepulse inhibition of the acoustic startle response. We found that sound exposure did not affect gap-prepulse inhibition. However, sound exposure led to an improvement in prepulse inhibition when the prepulse was a 7 kHz tone, showing that exposed rats had enhanced sensorimotor gating for the exposure frequency. Together, our electrophysiological and behavioral results provide evidence of hyperacusis but not tinnitus in sound-exposed animals. Our findings demonstrate that periods of prolonged noise exposure may open windows of plasticity that can also be understood as windows of vulnerability, potentially increasing the likelihood for maladaptive plasticity to take place.

Humans and other animals effortlessly identify natural sounds and categorize them into behaviorally relevant categories. Yet, the acoustic features and neural transformations that enable sound recognition and the formation of perceptual categories are largely unknown. Here, using multichannel neural recordings in the auditory midbrain of unanesthetized female rabbits, we first demonstrate that neural ensemble activity in the auditory midbrain displays highly structured correlations that vary with distinct natural sound stimuli. These stimulus-driven correlations can be used to accurately identify individual sounds using single-response trials, even when the sounds do not differ in their spectral content. Combining neural recordings and an auditory model, we then show how correlations between frequency-organized auditory channels can contribute to discrimination of not just individual sounds but sound categories. For both the model and neural data, spectral and temporal correlations achieved similar categorization performance and appear to contribute equally. Moreover, both the neural and model classifiers achieve their best task performance when they accumulate evidence over a time frame of approximately 1-2 seconds, mirroring human perceptual trends. These results together suggest that time-frequency correlations in sounds may be reflected in the correlations between auditory midbrain ensembles and that these correlations may play an important role in the identification and categorization of natural sounds.

Marmosets have attracted significant interest in the life sciences. Similarities with human brain anatomy and physiology, such as the granular frontal cortex, as well as the development of transgenic lines and potential for transferring rodent neuroscientific techniques to small primates make them a promising neurodegenerative and neuropsychiatric model system. However, whether marmosets can exhibit complex motor tasks in highly controlled experimental designs—one of the prerequisites for investigating higher-order control mechanisms underlying cognitive motor behavior—has not been demonstrated. We show that marmosets can be trained to perform vocal behavior in response to arbitrary visual cues in controlled operant conditioning tasks. Our results emphasize the marmoset as a suitable model to study complex motor behavior and the evolution of cognitive control underlying speech.

Auditory cortex is required for sound localisation, but how neural firing in auditory cortex underlies our perception of sound sources in space remains unclear. Specifically, whether neurons in auditory cortex represent spatial cues or an integrated representation of auditory space across cues is not known. Here, we measured the spatial receptive fields of neurons in primary auditory cortex (A1) while ferrets performed a relative localisation task. Manipulating the availability of binaural and spectral localisation cues had little impact on ferrets’ performance, or on neural spatial tuning. A subpopulation of neurons encoded spatial position consistently across localisation cue type. Furthermore, neural firing pattern decoders outperformed two-channel model decoders using population activity. Together, these observations suggest that A1 encodes the location of sound sources, as opposed to spatial cue values.

Local field potential (LFP) oscillations are primarily shaped by the superposition of postsynaptic currents. Hippocampal LFP oscillations in the 25- to 50-Hz range (“slow γ”) are proposed to support memory retrieval independent of other frequencies. However, θ harmonics extend up to 48 Hz, necessitating a study to determine whether these oscillations are fundamentally the same. We compared the spectral analysis methods of wavelet, ensemble empirical-mode decomposition (EEMD), and Fourier transform. EEMD, as previously applied, failed to account for the θ harmonics. Depending on analytical parameters selected, wavelet may convolve over high-order θ harmonics due to the variable time-frequency atoms, creating the appearance of a broad 25- to 50-Hz rhythm. As an illustration of this issue, wavelet and EEMD depicted slow γ in a synthetic dataset that only contained θ and its harmonics. Oscillatory transience cannot explain the difference in approaches as Fourier decomposition identifies ripples triggered to epochs of high-power, 120- to 250-Hz events. When Fourier is applied to high power, 25- to 50-Hz events, only θ harmonics are resolved. This analysis challenges the identification of the slow γ rhythm as a unique fundamental hippocampal oscillation. While there may be instances in which slow γ is present in the rat hippocampus, the analysis presented here shows that unless care is exerted in the application of EEMD and wavelet techniques, the results may be misleading, in this case misrepresenting θ harmonics. Moreover, it is necessary to reconsider the characteristics that define a fundamental hippocampal oscillation as well as theories based on multiple independent γ bands.

Tactile working memory engages a broad network of cortical regions in primates. To assess whether the conclusions drawn from primates apply to rodents, we examined the vibrissal primary somatosensory cortex (vS1) and the prelimbic cortex (PL) in a delayed comparison task. Rats compared the speeds of two vibrissal vibrations, stimulus1 and stimulus2, separated by a delay of 2 s. Neuronal firing rates in vS1 and PL encode both stimuli in real time. Across the delay, the stimulus1 representation declines more precipitously in vS1 than in PL. Theta-band local field potential (LFP) coherence between vS1 and PL peaks at trial onset and remains elevated during the interstimulus interval; simultaneously, vS1 spikes become phase locked to PL LFP. Phase locking is stronger on correct (versus error) trials. Tactile working memory in rats appears to be mediated by a posterior (vS1) to anterior (PL) flow of information, with performance facilitated through coherent LFP oscillation.

Processing incentive and drive is essential for control of goal-directed behavior. The limbic part of the basal ganglia has been emphasized in these processes, yet the exact neuronal mechanism has remained elusive. In this study, we examined the neuronal activity of the ventral pallidum (VP) and its upstream area, the rostromedial caudate (rmCD), while two male macaque monkeys performed an instrumental lever release task in which a visual cue indicated the forthcoming reward size. We found that the activity of some neurons in VP and rmCD reflected the expected reward size transiently following the cue. Reward size coding appeared earlier and stronger in VP than in rmCD. We also found that the activity in these areas was modulated by the satiation level of monkeys, which also occurred more frequently in VP than in rmCD. The information regarding reward size and satiation level was independently signaled in the neuronal populations of these areas. The data thus highlighted the neuronal coding of key variables for goal-directed behavior in VP. Furthermore, pharmacological inactivation of VP induced more severe deficit of goal-directed behavior than inactivation of rmCD, which was indicated by abnormal error repetition and diminished satiation effect on the performance. These results suggest that VP encodes incentive value and internal drive and plays a pivotal role in the control of motivation to promote goal-directed behavior. SIGNIFICANCE STATEMENT The limbic part of the basal ganglia has been implicated in the motivational control of goal-directed action. Here, we investigated how the ventral pallidum (VP) and the rostromedial caudate (rmCD) encode incentive value and internal drive and control goal-directed behavior. Neuronal recording and subsequent pharmacological inactivation revealed that VP had stronger coding of reward size and satiation level than rmCD. Reward size and satiation level were independently encoded in the neuronal population of these areas. Furthermore, VP inactivation impaired goal-directed behavior more severely than rmCD inactivation. These results highlight the central role of VP in the motivational control of goal-directed action.

Mesoscale cortical activity can be defined as the organization of activity of large neuron populations into collective action, forming time-dependent patterns such as traveling waves. Although collective action may play an important role in the cross-scale integration of brain activity and in the emergence of cognitive behavior, a comprehensive formulation of the laws governing its dynamics is still lacking. Because collective action processes are macroscopic with respect to neuronal activity, these processes cannot be described directly with methods and models developed for the microscale (individual neurons).To identify the characteristic features of mesoscopic dynamics, and to lay the foundations for a theoretical description of mesoscopic activity in the hippocampus, we conduct a comprehensive examination of observational data of hippocampal local field potential (LFP) recordings. We use the strong correlation between rat running-speed and the LFP power to parameterize the energy input into the hippocampus, and show that both the power and non-linearity of collective action (e.g., theta and gamma rhythms) increase with increased speed. Our results show that collective-action dynamics are stochastic (the precise state of a single neuron is irrelevant), weakly non-linear, and weakly dissipative. These are the principles of the theory of weak turbulence. Therefore, we propose weak turbulence a theoretical framework for the description of mesoscopic activity in the hippocampus. The weak turbulence framework provides a complete description of the cross-scale energy exchange (the energy cascade). It uncovers the mechanism governing major features of LFP spectra and bispectra, such as the physical meaning of the exponent α of power-law LFP spectra (e.g., f -α, where f is the frequency), the strengthening of theta-gamma coupling with energy input into the hippocampus, as well as specific phase lags associated with their interaction. Remarkably, the weak turbulence framework is consistent with the theory of self organized criticality, which provides a simple explanation for the existence of the power-law background spectrum. Together with self-organized criticality, weak turbulence could provide a unifying approach to modeling the dynamics of mesoscopic activity.

Perceptual constancy requires neural representations that are selective for object identity, but also tolerant across identity-preserving transformations. How such representations arise in the brain and support perception remains unclear. Here, we study tolerant representation of sound identity in the auditory system by recording neural activity in auditory cortex of ferrets during perceptual constancy. Ferrets generalize vowel identity across variations in fundamental frequency, sound level and location, while neurons represent sound identity robustly across acoustic variations. Stimulus features are encoded with distinct time-courses in all conditions, however encoding of sound identity is delayed when animals fail to generalize and during passive listening. Neurons also encode information about task-irrelevant sound features, as well as animals’ choices and accuracy, while population decoding out-performs animals’ behavior. Our results show that during perceptual constancy, sound identity is represented robustly in auditory cortex across widely varying conditions, and behavioral generalization requires conserved timing of identity information.