How deep is the brain? The shallow brain hypothesis.

Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in deep learning and predictive coding architectures is the neurobiological evidence that all hierarchical cortical areas, higher or lower, project to and receive signals directly from subcortical areas. Given these neuroanatomical facts, today's dominance of cortico-centric, hierarchical architectures in deep learning and predictive coding networks is highly questionable; such architectures are likely to be missing essential computational principles the brain uses. In this Perspective, we present the shallow brain hypothesis: hierarchical cortical processing is integrated with a massively parallel process to which subcortical areas substantially contribute. This shallow architecture exploits the computational capacity of cortical microcircuits and thalamo-cortical loops that are not included in typical hierarchical deep learning and predictive coding networks. We argue that the shallow brain architecture provides several critical benefits over deep hierarchical structures and a more complete depiction of how mammalian brains achieve fast and flexible computational capabilities.

Neural correlates of object identity and reward outcome in the sensory cortical-hippocampal hierarchy: coding of motivational information in perirhinal cortex.

Neural circuits support behavioral adaptations by integrating sensory and motor information with reward and error-driven learning signals, but it remains poorly understood how these signals are distributed across different levels of the corticohippocampal hierarchy. We trained rats on a multisensory object-recognition task and compared visual and tactile responses of simultaneously recorded neuronal ensembles in somatosensory cortex, secondary visual cortex, perirhinal cortex, and hippocampus. The sensory regions primarily represented unisensory information, whereas hippocampus was modulated by both vision and touch. Surprisingly, the sensory cortices and the hippocampus coded object-specific information, whereas the perirhinal cortex did not. Instead, perirhinal cortical neurons signaled trial outcome upon reward-based feedback. A majority of outcome-related perirhinal cells responded to a negative outcome (reward omission), whereas a minority of other cells coded positive outcome (reward delivery). Our results highlight a distributed neural coding of multisensory variables in the cortico-hippocampal hierarchy. Notably, the perirhinal cortex emerges as a crucial region for conveying motivational outcomes, whereas distinct functions related to object identity are observed in the sensory cortices and hippocampus.

Coherent mapping of position and head direction across auditory and visual cortex.

Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject's spatial position. Such contextual representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here, we show that spiking activity coherently represents a location-specific mapping across auditory cortex (AC) and lateral, secondary visual cortex (V2L) of freely moving rats engaged in a sensory detection task on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability, and position coding. Importantly, reconstructions of subject position based on spiking activity displayed decoding errors that were correlated between areas. Additionally, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in AC and V2L. By contrast, variables related to the sensory task cues or to trial correctness and reward were not markedly encoded in AC and V2L. We conclude that sensory cortices participate in coherent, multimodal representations of the subject's sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.

Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness.

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

Spike-based coupling between single neurons and populations across rat sensory cortices, perirhinal cortex, and hippocampus.

Cortical computations require coordination of neuronal activity within and across multiple areas. We characterized spiking relationships within and between areas by quantifying coupling of single neurons to population firing patterns. Single-neuron population coupling (SNPC) was investigated using ensemble recordings from hippocampal CA1 region and somatosensory, visual, and perirhinal cortices. Within-area coupling was heterogeneous across structures, with area CA1 showing higher levels than neocortical regions. In contrast to known anatomical connectivity, between-area coupling showed strong firing coherence of sensory neocortices with CA1, but less with perirhinal cortex. Cells in sensory neocortices and CA1 showed positive correlations between within- and between-area coupling; these were weaker for perirhinal cortex. All four areas harbored broadcasting cells, connecting to multiple external areas, which was uncorrelated to within-area coupling strength. When examining correlations between SNPC and spatial coding, we found that, if such correlations were significant, they were negative. This result was consistent with an overall preservation of SNPC across different brain states, suggesting a strong dependence on intrinsic network connectivity. Overall, SNPC offers an important window on cell-to-population synchronization in multi-area networks. Instead of pointing to specific information-coding functions, our results indicate a primary function of SNPC in dynamically organizing communication in systems composed of multiple, interconnected areas.

Higher order visual areas enhance stimulus responsiveness in mouse primary visual cortex.

Over the past few years, the various areas that surround the primary visual cortex (V1) in the mouse have been associated with many functions, ranging from higher order visual processing to decision-making. Recently, some studies have shown that higher order visual areas influence the activity of the primary visual cortex, refining its processing capabilities. Here, we studied how in vivo optogenetic inactivation of two higher order visual areas with different functional properties affects responses evoked by moving bars in the primary visual cortex. In contrast with the prevailing view, our results demonstrate that distinct higher order visual areas similarly modulate early visual processing. In particular, these areas enhance stimulus responsiveness in the primary visual cortex, by more strongly amplifying weaker compared with stronger sensory-evoked responses (for instance specifically amplifying responses to stimuli not moving along the direction preferred by individual neurons) and by facilitating responses to stimuli entering the receptive field of single neurons. Such enhancement, however, comes at the expense of orientation and direction selectivity, which increased when the selected higher order visual areas were inactivated. Thus, feedback from higher order visual areas selectively amplifies weak sensory-evoked V1 responses, which may enable more robust processing of visual stimuli.

The Human Brain Project-Synergy between neuroscience, computing, informatics, and brain-inspired technologies.

The Human Brain Project (HBP) is a European flagship project with a 10-year horizon aiming to understand the human brain and to translate neuroscience knowledge into medicine and technology. To achieve such aims, the HBP explores the multilevel complexity of the brain in space and time; transfers the acquired knowledge to brain-derived applications in health, computing, and technology; and provides shared and open computing tools and data through the HBP European brain research infrastructure. We discuss how the HBP creates a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating perspectives on societal benefits.

What is exactly the problem with panpsychism?

Merker et al.'s critique calls for a deeper analysis of panpsychism. In principle, the concept of integrated information can be applied to photodiodes and subatomic particles, but I suggest the main obstacle is the lack of any evidence to confirm the presence of consciousness. Also MRW's perspectivalist theory illustrates the difficulties in synthesizing a full-fledged theory of consciousness.

Reconciling the object and spatial processing views of the perirhinal cortex through task-relevant unitization.

The perirhinal cortex is situated on the border between sensory association cortex and the hippocampal formation. It serves an important function as a transition area between the sensory neocortex and the medial temporal lobe. While the perirhinal cortex has traditionally been associated with object coding and the "what" pathway of the temporal lobe, current evidence suggests a broader function of the perirhinal cortex in solving feature ambiguity and processing complex stimuli. Besides fulfilling functions in object coding, recent neurophysiological findings in freely moving rodents indicate that the perirhinal cortex also contributes to spatial and contextual processing beyond individual sensory modalities. Here, we address how these two opposing views on perirhinal cortex-the object-centered and spatial-contextual processing hypotheses-may be reconciled. The perirhinal cortex is consistently recruited when different features can be merged perceptually or conceptually into a single entity. Features that are unitized in these entities include object information from multiple sensory domains, reward associations, semantic features and spatial/contextual associations. We propose that the same perirhinal network circuits can be flexibly deployed for multiple cognitive functions, such that the perirhinal cortex performs similar unitization operations on different types of information, depending on behavioral demands and ranging from the object-related domain to spatial, contextual and semantic information.

Learning, memory and consolidation mechanisms for behavioral control in hierarchically organized cortico-basal ganglia systems.

This article aims to provide a synthesis on the question how brain structures cooperate to accomplish hierarchically organized behaviors, characterized by low-level, habitual routines nested in larger sequences of planned, goal-directed behavior. The functioning of a connected set of brain structures-prefrontal cortex, hippocampus, striatum, and dopaminergic mesencephalon-is reviewed in relation to two important distinctions: (a) goal-directed as opposed to habitual behavior and (b) model-based and model-free learning. Recent evidence indicates that the orbitomedial prefrontal cortices not only subserve goal-directed behavior and model-based learning, but also code the "landscape" (task space) of behaviorally relevant variables. While the hippocampus stands out for its role in coding and memorizing world state representations, it is argued to function in model-based learning but is not required for coding of action-outcome contingencies, illustrating that goal-directed behavior is not congruent with model-based learning. While the dorsolateral and dorsomedial striatum largely conform to the dichotomy between habitual versus goal-directed behavior, ventral striatal functions go beyond this distinction. Next, we contextualize findings on coding of reward-prediction errors by ventral tegmental dopamine neurons to suggest a broader role of mesencephalic dopamine cells, viz. in behavioral reactivity and signaling unexpected sensory changes. We hypothesize that goal-directed behavior is hierarchically organized in interconnected cortico-basal ganglia loops, where a limbic-affective prefrontal-ventral striatal loop controls action selection in a dorsomedial prefrontal-striatal loop, which in turn regulates activity in sensorimotor-dorsolateral striatal circuits. This structure for behavioral organization requires alignment with mechanisms for memory formation and consolidation. We propose that frontal corticothalamic circuits form a high-level loop for memory processing that initiates and temporally organizes nested activities in lower-level loops, including the hippocampus and the ripple-associated replay it generates. The evidence on hierarchically organized behavior converges with that on consolidation mechanisms in suggesting a frontal-to-caudal directionality in processing control.

Membrane Potential Dynamics of Spontaneous and Visually Evoked Gamma Activity in V1 of Awake Mice.

Cortical gamma activity (30-80 Hz) is believed to play important functions in neural computation and arises from the interplay of parvalbumin-expressing interneurons (PV) and pyramidal cells (PYRs). However, the subthreshold dynamics underlying its emergence in the cortex of awake animals remain unclear. Here, we characterized the intracellular dynamics of PVs and PYRs during spontaneous and visually evoked gamma activity in layers 2/3 of V1 of awake mice using targeted patch-clamp recordings and synchronous local field potentials (LFPs). Strong gamma activity patterned in short bouts (one to three cycles), occurred when PVs and PYRs were depolarizing and entrained their membrane potential dynamics regardless of the presence of visual stimulation. PV firing phase locked unconditionally to gamma activity. However, PYRs only phase locked to visually evoked gamma bouts. Taken together, our results indicate that gamma activity corresponds to short pulses of correlated background synaptic activity synchronizing the output of cortical neurons depending on external sensory drive.

Model-based spatial navigation in the hippocampus-ventral striatum circuit: A computational analysis.

While the neurobiology of simple and habitual choices is relatively well known, our current understanding of goal-directed choices and planning in the brain is still limited. Theoretical work suggests that goal-directed computations can be productively associated to model-based (reinforcement learning) computations, yet a detailed mapping between computational processes and neuronal circuits remains to be fully established. Here we report a computational analysis that aligns Bayesian nonparametrics and model-based reinforcement learning (MB-RL) to the functioning of the hippocampus (HC) and the ventral striatum (vStr)-a neuronal circuit that increasingly recognized to be an appropriate model system to understand goal-directed (spatial) decisions and planning mechanisms in the brain. We test the MB-RL agent in a contextual conditioning task that depends on intact hippocampus and ventral striatal (shell) function and show that it solves the task while showing key behavioral and neuronal signatures of the HC-vStr circuit. Our simulations also explore the benefits of biological forms of look-ahead prediction (forward sweeps) during both learning and control. This article thus contributes to fill the gap between our current understanding of computational algorithms and biological realizations of (model-based) reinforcement learning.

Audiovisual Modulation in Mouse Primary Visual Cortex Depends on Cross-Modal Stimulus Configuration and Congruency.

The sensory neocortex is a highly connected associative network that integrates information from multiple senses, even at the level of the primary sensory areas. Although a growing body of empirical evidence supports this view, the neural mechanisms of cross-modal integration in primary sensory areas, such as the primary visual cortex (V1), are still largely unknown. Using two-photon calcium imaging in awake mice, we show that the encoding of audiovisual stimuli in V1 neuronal populations is highly dependent on the features of the stimulus constituents. When the visual and auditory stimulus features were modulated at the same rate (i.e., temporally congruent), neurons responded with either an enhancement or suppression compared with unisensory visual stimuli, and their prevalence was balanced. Temporally incongruent tones or white-noise bursts included in audiovisual stimulus pairs resulted in predominant response suppression across the neuronal population. Visual contrast did not influence multisensory processing when the audiovisual stimulus pairs were congruent; however, when white-noise bursts were used, neurons generally showed response suppression when the visual stimulus contrast was high whereas this effect was absent when the visual contrast was low. Furthermore, a small fraction of V1 neurons, predominantly those located near the lateral border of V1, responded to sound alone. These results show that V1 is involved in the encoding of cross-modal interactions in a more versatile way than previously thought.SIGNIFICANCE STATEMENT The neural substrate of cross-modal integration is not limited to specialized cortical association areas but extends to primary sensory areas. Using two-photon imaging of large groups of neurons, we show that multisensory modulation of V1 populations is strongly determined by the individual and shared features of cross-modal stimulus constituents, such as contrast, frequency, congruency, and temporal structure. Congruent audiovisual stimulation resulted in a balanced pattern of response enhancement and suppression compared with unisensory visual stimuli, whereas incongruent or dissimilar stimuli at full contrast gave rise to a population dominated by response-suppressing neurons. Our results indicate that V1 dynamically integrates nonvisual sources of information while still attributing most of its resources to coding visual information.

Consciousness Regained: Disentangling Mechanisms, Brain Systems, and Behavioral Responses.

How consciousness (experience) arises from and relates to material brain processes (the "mind-body problem") has been pondered by thinkers for centuries, and is regarded as among the deepest unsolved problems in science, with wide-ranging theoretical, clinical, and ethical implications. Until the last few decades, this was largely seen as a philosophical topic, but not widely accepted in mainstream neuroscience. Since the 1980s, however, novel methods and theoretical advances have yielded remarkable results, opening up the field for scientific and clinical progress. Since a seminal paper by Crick and Koch (1998) claimed that a science of consciousness should first search for its neural correlates (NCC), a variety of correlates have been suggested, including both content-specific NCCs, determining particular phenomenal components within an experience, and the full NCC, the neural substrates supporting entire conscious experiences. In this review, we present recent progress on theoretical, experimental, and clinical issues. Specifically, we (1) review methodological advances that are important for dissociating conscious experience from related enabling and executive functions, (2) suggest how critically reconsidering the role of the frontal cortex may further delineate NCCs, (3) advocate the need for general, objective, brain-based measures of the capacity for consciousness that are independent of sensory processing and executive functions, and (4) show how animal studies can reveal population and network phenomena of relevance for understanding mechanisms of consciousness.

Abnormal hippocampal theta and gamma hypersynchrony produces network and spike timing disturbances in the Fmr1-KO mouse model of Fragile X syndrome.

Neuronal networks can synchronize their activity through excitatory and inhibitory connections, which is conducive to synaptic plasticity. This synchronization is reflected in rhythmic fluctuations of the extracellular field. In the hippocampus, theta and gamma band LFP oscillations are a hallmark of the processing of spatial information and memory. Fragile X syndrome (FXS) is an intellectual disability and the most common genetic cause of autism spectrum disorder (Belmonte and Bourgeron, 2006). Here, we investigated how neuronal network synchronization in the mouse hippocampus is compromised by the Fmr1 mutation that causes FXS (Santos et al., 2014), relating recently observed single-cell level impairments (Arbab et al., 2017) to neuronal network aberrations. We implanted tetrodes in hippocampus of freely moving Fmr1-KO and littermate wildtype (WT) mice (Mientjes et al., 2006), to record spike trains from multiple, isolated neurons as well as LFPs in a spatial exploration paradigm. Compared to wild type mice, Fmr1-KO mice displayed greater power of hippocampal theta oscillations, and higher coherence in the slow gamma band. Additionally, spike trains of Fmr1-KO interneurons show decreased spike-count correlations and they are hypersynchronized with theta and slow gamma oscillations. The hypersynchronization of Fmr1-KO oscillations and spike timing reflects functional deficits in local networks. This network hypersynchronization pathologically decreases the heterogeneity of spike-LFP phase coupling, compromising information processing within the hippocampal circuit. These findings may reflect a pathophysiological mechanism explaining cognitive impairments in FXS and autism, in which there is anomalous processing of social and environmental cues and associated deficits in memory and cognition.

Corticosterone impairs flexible adjustment of spatial navigation in an associative place-reward learning task.

Cognitive challenges are often accompanied by a discharge of stress hormones, which in turn modulate multiple brain areas. Among these, the medial temporal lobe and the prefrontal cortex are critically involved in high-order cognitive functions such as learning, memory, and decision-making. Previous studies assessing the effects of corticosterone on spatial memory found an increase or a decrease in performance depending on the timing of stress hormone discharge relative to the behavioral task. Most of these studies, however, made use of aversively motivated behaviors, whereas less is known about corticosteroid effects on flexible learning during reward-driven spatial navigation. To study how corticosterone modulates flexible spatial learning, we tested rats on a place-reward association task where hormone treatment was administered immediately after a session presenting a change in reward locations. The corticosterone-treated group showed delayed learning during the initial sessions and suboptimal memory consolidation throughout testing. Repeated training on the novel reward positions improved performance and eliminated differences from the control group. We conclude that a marked increase in plasma corticosterone levels immediately after training impairs the flexible formation of new place-reward associations.

Visual Stimulus Detection Correlates with the Consistency of Temporal Sequences within Stereotyped Events of V1 Neuronal Population Activity.

UNLABELLED: Sensory information about the world is translated into rate codes, such that modulations in mean spiking activity of neurons relate to differences in stimulus features. More recently, it has been proposed that also temporal properties of activity, such as assembly formation and sequential population activation, are important for understanding the relation between neuronal activity and behavioral output. These phenomena appear to be robust properties of neural circuits, but their relevance for perceptual judgments, such as the behavioral detection of stimuli, remains to be tested. Studying neuronal activity with two-photon calcium imaging in primary visual cortex of mice performing a go/no-go visual detection task, we found that assemblies (i.e., configurations of neuronal group activity) reliably recur, as defined using Ward-method clustering. However, population activation events with a recurring configuration of core neurons did not appear to serve a particular function in the coding of orientation or the detection of stimuli. Instead, we found that, regardless of whether the population event showed a recurring or nonrecurring configuration of neurons, the sequence of cluster activation was correlated with the detection of stimuli. Moreover, each neuron showed a preferred temporal position of activation within population events, which was robust despite varying neuronal participation. Furthermore, the timing of neuronal activity within such a sequence was more consistent when a stimulus was detected (hits) than when it remained unreported (misses). Our data indicate that neural processing of information related to visual detection behavior depends on the temporal positioning of individual and group-wise cell activity. SIGNIFICANCE STATEMENT: Temporally coactive neurons have been hypothesized to form functional assemblies that might subserve different functions in the brain, but many of these proposed functions have not yet been experimentally tested. We used two-photon calcium imaging in V1 of mice performing a stimulus detection task to study the relation of assembly activity to the behavioral detection of visual stimuli. We found that the presence of recurring assemblies per se was not correlated with behavior, and these assemblies did not appear to serve a function in the coding of stimulus orientation. Instead, we found that activity in V1 is characterized by population events of varying membership, within which the consistency of the temporal sequence of neuronal activation is correlated with stimulus detection.

Reward Expectancy Strengthens CA1 Theta and Beta Band Synchronization and Hippocampal-Ventral Striatal Coupling.

The use of information from the hippocampal memory system in motivated behavior depends on its communication with the ventral striatum. When an animal encounters cues that signal subsequent reward, its reward expectancy is raised. It is unknown, however, how this process affects hippocampal dynamics and their influence on target structures, such as ventral striatum. We show that, in rats, reward-predictive cues result in enhanced hippocampal theta and beta band rhythmic activity during subsequent action, compared with uncued goal-directed navigation. The beta band component, also labeled theta's harmonic, involves selective hippocampal CA1 cell groups showing frequency doubling of firing periodicity relative to theta rhythmicity and it partitions the theta cycle into segments showing clear versus poor spike timing organization. We found that theta phase precession occurred over a wider range than previously reported. This was apparent from spikes emitted near the peak of the theta cycle exhibiting large "phase precessing jumps" relative to spikes in foregoing cycles. Neither this phenomenon nor the regular manifestation of theta phase precession was affected by reward expectancy. Ventral striatal neuronal firing phase-locked not only to hippocampal theta, but also to beta band activity. Both hippocampus and ventral striatum showed increased synchronization between neuronal firing and local field potential activity during cued compared with uncued goal approaches. These results suggest that cue-triggered reward expectancy intensifies hippocampal output to target structures, such as the ventral striatum, by which the hippocampus may gain prioritized access to systems modulating motivated behaviors. SIGNIFICANCE STATEMENT: Here we show that temporally discrete cues raising reward expectancy enhance both theta and beta band activity in the hippocampus once goal-directed navigation has been initiated. These rhythmic activities are associated with increased synchronization of neuronal firing patterns in the hippocampus and the connected ventral striatum. When transmitted to downstream target structures, this expectancy-related state of intensified processing in the hippocampus may modulate goal-directed action.

Spike-Based Functional Connectivity in Cerebral Cortex and Hippocampus: Loss of Global Connectivity Is Coupled to Preservation of Local Connectivity During Non-REM Sleep.

UNLABELLED: Behavioral states are commonly considered global phenomena with homogeneous neural determinants. However, recent studies indicate that behavioral states modulate spiking activity with neuron-level specificity as a function of brain area, neuronal subtype, and preceding history. Although functional connectivity also strongly depends on behavioral state at a mesoscopic level and is globally weaker in non-REM (NREM) sleep and anesthesia than wakefulness, it is unknown how neuronal communication is modulated at the cellular level. We hypothesize that, as for neuronal activity, the influence of behavioral states on neuronal coupling strongly depends on type, location, and preceding history of involved neurons. Here, we applied nonlinear, information-theoretical measures of functional connectivity to ensemble recordings with single-cell resolution to quantify neuronal communication in the neocortex and hippocampus of rats during wakefulness and sleep. Although functional connectivity (measured in terms of coordination between firing rate fluctuations) was globally stronger in wakefulness than in NREM sleep (with distinct traits for cortical and hippocampal areas), the drop observed during NREM sleep was mainly determined by a loss of inter-areal connectivity between excitatory neurons. Conversely, local (intra-area) connectivity and long-range (inter-areal) coupling between interneurons were preserved during NREM sleep. Furthermore, neuronal networks that were either modulated or not by a behavioral task remained segregated during quiet wakefulness and NREM sleep. These results show that the drop in functional connectivity during wake-sleep transitions globally holds true at the cellular level, but confine this change mainly to long-range coupling between excitatory neurons. SIGNIFICANCE STATEMENT: Studies performed at a mesoscopic level of analysis have shown that communication between cortical areas is disrupted in non-REM sleep and anesthesia. However, the neuronal determinants of this phenomenon are not known. Here, we applied nonlinear, information-theoretical measures of functional coupling to multi-area tetrode recordings from freely moving rats to investigate whether and how brain state modulates coordination between individual neurons. We found that the previously observed drop in functional connectivity during non-REM (NREM) sleep can be explained by a decrease in coupling between excitatory neurons located in distinct brain areas. Conversely, intra-area communication and coupling between interneurons are preserved. Our results provide significant new insights into the neuron-level mechanisms responsible for the loss of consciousness occurring in NREM sleep.

Effects of Arc/Arg3.1 gene deletion on rhythmic synchronization of hippocampal CA1 neurons during locomotor activity and sleep.

The activity-regulated cytoskeletal-associated protein/activity regulated gene (Arc/Arg3.1) is crucial for long-term synaptic plasticity and memory formation. However, the neurophysiological substrates of memory deficits occurring in the absence of Arc/Arg3.1 are unknown. We compared hippocampal CA1 single-unit and local field potential (LFP) activity in Arc/Arg3.1 knockout and wild-type mice during track running and flanking sleep periods. Locomotor activity, basic firing and spatial coding properties of CA1 cells in knockout mice were not different from wild-type mice. During active behavior, however, knockout animals showed a significantly shifted balance in LFP power, with a relative loss in high-frequency (beta-2 and gamma) bands compared to low-frequency bands. Moreover, during track-running, knockout mice showed a decrease in phase locking of spiking activity to LFP oscillations in theta, beta and gamma bands. Sleep architecture in knockout mice was not grossly abnormal. Sharp-wave ripples, which have been associated with memory consolidation and replay, showed only minor differences in dynamics and amplitude. Altogether, these findings suggest that Arc/Arg3.1 effects on memory formation are not only manifested at the level of molecular pathways regulating synaptic plasticity, but also at the systems level. The disrupted power balance in theta, beta and gamma rhythmicity and concomitant loss of spike-field phase locking may affect memory encoding during initial storage and memory consolidation stages.