The hippocampal circuitry undergoes attentional modulation by the cholinergic medial septum. However, it is unclear how septal activation regulates the spatial properties of hippocampal neurons. We investigated here what is the functional effect of selective-cholinergic and non-selective septal stimulation on septo-hippocampal system. We show for the first time selective activation of cholinergic cells and their differential network effect in medial septum of freely-behaving transgenic rats. Our data show that depolarization of cholinergic septal neurons evokes frequency-dependent response from the non-cholinergic septal neurons and hippocampal interneurons. Our findings provide vital evidence that cholinergic effect on septo-hippocampal axis is behavior-dependent. During the active behavioral state the activation of septal cholinergic projections is insufficient to evoke significant change in the spiking of the hippocampal neurons. The efficiency of septo-hippocampal processing during active exploration relates to the firing patterns of the non-cholinergic theta-bursting cells. Non-selective septal theta-burst stimulation resets the spiking of hippocampal theta cells, increases theta synchronization, entrains the spiking of hippocampal place cells, and tunes the spatial properties in a timing-dependent manner. The spatial properties are augmented only when the stimulation is applied in the periphery of the place field or 400 – 650ms before the animals approached the center of the field. In summary, our data show that selective cholinergic activation triggers a robust network effect in the septo-hippocampal system during inactive behavioral state, whereas the non-cholinergic septal activation regulates hippocampal functional properties during explorative behavior. Together, our findings uncover fast septal modulation on hippocampal network and reveal how septal inputs up-regulate and down-regulate the encoding of spatial representation.

The hippocampus is the main locus of episodic memory formation and the neurons there encode the spatial map of the environment. Hippocampal place cells represent location, but their role in the learning of preferential location remains unclear. The hippocampus may encode locations independently from the stimuli and events that are associated with these locations. We have discovered a unique population code for the experience-dependent value of the context. The degree of reward-driven navigation preference highly correlates with the spatial distribution of the place fields recorded in the CA1 region of the hippocampus. We show place field clustering towards rewarded locations. Optogenetic manipulation of the ventral tegmental area demonstrates that the experience-dependent place field assembly distribution is directed by tegmental dopaminergic activity. The ability of the place cells to remap parallels the acquisition of reward context. Our findings present key evidence that the hippocampal neurons are not merely mapping the static environment but also store the concurrent context reward value, enabling episodic memory for past experience to support future adaptive behavior. Episodic memories relate positive or negative experiences to environmental context. The neurophysiological mechanisms of this connection, however, remain unknown. Hippocampal place cells represent location, but it is unclear if they encode only the spatial representation of the environment or if they are also processing information about the reward valence for different locations. Here, we use population analysis to test the hypothesis that the place cells process the dual encoding of spatial representation and experience-dependent reward expectation. We show a unique population code for the experience-dependent value of the context. We present evidence that the accumulation of the place fields mediates the learning of the reward context of the environment. Our data reveal that the causal link between place field distribution and behavioral place preference is mediated by the tegmental dopaminergic activity. Optogenetic control of the ventral tegmental area demonstrates that dopaminergic signaling integrates the encoding of location and reward from hippocampal neurons. These findings shed a new light on the ability of hippocampal neurons to store the experience-dependent context reward value, enabling episodic memory for past experience to support future adaptive behavior.

Parkinson’s disease is a neurological disorder characterized by the manifestation of motor symptoms, such as akinesia, muscle rigidity and tremor at rest. These symptoms are classically attributed to the degeneration of dopamine neurons in the pars compacta of substantia nigra (SNc), which results in a marked dopamine depletion in the striatum. It is well established that dopamine neurons in the SNc innervate not only the striatum, which is the main target, but also other basal ganglia nuclei including the two segments of globus pallidus and the subthalamic nucleus. The role of dopamine and its depletion in the striatum is well known, however, the role of dopamine depletion in the pallidal complex and the subthalamic nucleus in the genesis of their abnormal neuronal activity and in parkinsonian motor deficits is still not clearly determined. Based on recent experimental data from animal models of Parkinson's disease in rodents and non-human primates and also from parkinsonian patients, this review summarizes current knowledge on the role of dopamine in the modulation of basal ganglia neuronal activity and also the role of dopamine depletion in these nuclei in the pathophysiology of Parkinson's disease.

Objective. Electroencephalography (EEG) is a key tool for non-invasive recording of brain activity and the diagnosis of epilepsy. EEG monitoring is also widely employed in rodent models to track epilepsy development and evaluate experimental therapies and interventions. Whereas automated seizure detection algorithms have been developed for clinical EEG, preclinical versions face challenges of inter-model differences and lack of EEG standardization, leaving researchers relying on time-consuming visual annotation of signals. Approach. In this study, a machine learning-based seizure detection approach, ‘Epi-AI’, which can semi-automate EEG analysis in multiple mouse models of epilepsy was developed. Twenty-six mice with a total EEG recording duration of 6451 h were used to develop and test the Epi-AI approach. EEG recordings were obtained from two mouse models of kainic acid-induced epilepsy (Models I and III), a genetic model of Dravet syndrome (Model II) and a pilocarpine mouse model of epilepsy (Model IV). The Epi-AI algorithm was compared against two threshold-based approaches for seizure detection, a local Teager-Kaiser energy operator (TKEO) approach and a global Teager-Kaiser energy operator-discrete wavelet transform (TKEO-DWT) combination approach. Main results. Epi-AI demonstrated a superior sensitivity, 91.4%–98.8%, and specificity, 93.1%–98.8%, in Models I–III, to both of the threshold-based approaches which performed well on individual mouse models but did not generalise well across models. The performance of the TKEO approach in Models I–III ranged from 66.9%–91.3% sensitivity and 60.8%–97.5% specificity to detect spontaneous seizures when compared with expert annotations. The sensitivity and specificity of the TKEO-DWT approach were marginally better than the TKEO approach in Models I–III at 73.2%–80.1% and 75.8%–98.1%, respectively. When tested on EEG from Model IV which was not used in developing the Epi-AI approach, Epi-AI was able to identify seizures with 76.3% sensitivity and 98.1% specificity. Significance. Epi-AI has the potential to provide fast, objective and reproducible semi-automated analysis of multiple types of seizure in long-duration EEG recordings in rodents.

The early electrophysiological phenomena linked to systemic inflammation are largely underexplored. We developed here local field analyses to detect prodromal oscillatory abnormalities. We identified early band-specific patterns in local field potential recorded from freely-moving rats injected intraperitoneally with lipopolysaccharide (LPS, 1 mg/kg). Theta frequency was significantly reduced and this effect was not related to the decreased locomotion of the animal. Furthermore, LPS-induced alterations show a region-specific response when compared between the hippocampal region and medial prefrontal cortex. Delta mean frequency increased in the hippocampal region but not in the prefrontal cortex. We explored also the hypothesis that systemic inflammation increases the propensity of abnormally synchronized brain activity. Our data indicate that the LPS-evoked alteration of delta and theta frequency parameters reflects the formation of abnormal synchronization in similar frequency ranges. The onset of abnormal brain activity was indicated by spike-wave discharges in the range of 1-10 Hz with three main frequency domains. Importantly, the occurrence of spike-wave discharges was observed in the hippocampus but not in the cortex. In summary, the hippocampal theta rhythm is an accurate indicator of the oscillatory changes evoked by LPS application. The findings offer clear patterns of altered brain function that will facilitate mechanistic investigations of brain dysfunction and delirium occurring during sepsis.

The globus pallidus (GP) receives dopaminergic afferents from the pars compacta of substantia nigra and several studies suggested that dopamine exerts its action in the GP through presynaptic D2 receptors (D2Rs). However, the impact of dopamine in GP on the pallido-subthalamic and pallido-nigral neurotransmission is not known. Here, we investigated the role of dopamine, through activation of D2Rs, in the modulation of GP neuronal activity and its impact on the electrical activity of subthalamic nucleus (STN) and substantia nigra reticulata (SNr) neurons. Extracellular recordings combined with local intracerebral microinjection of drugs were done in male Sprague-Dawley rats under urethane anesthesia. We showed that dopamine, when injected locally, increased the firing rate of the majority of neurons in the GP. This increase of the firing rate was mimicked by quinpirole, a D2R agonist, and prevented by sulpiride, a D2R antagonist. In parallel, the injection of dopamine, as well as quinpirole, in the GP reduced the firing rate of majority of STN and SNr neurons. However, neither dopamine nor quinpirole changed the tonic discharge pattern of GP, STN and SNr neurons. Our results are the first to demonstrate that dopamine through activation of D2Rs located in the GP plays an important role in the modulation of GP-STN and GP-SNr neurotransmission and consequently controls STN and SNr neuronal firing. Moreover, we provide evidence that dopamine modulate the firing rate but not the pattern of GP neurons, which in turn control the firing rate, but not the pattern of STN and SNr neurons.