Low-dimensional attractor for neural activity from local field potentials in optogenetic mice

We used optogenetic mice to investigate possible nonlinear responses of the medial prefrontal cortex (mPFC) local network to light stimuli delivered by a 473 nm laser through a fiber optics. Every 2 s, a brief 10 ms light pulse was applied and the local field potentials (LFPs) were recorded with a 10 kHz sampling rate. The experiment was repeated 100 times and we only retained and analyzed data from six animals that showed stable and repeatable response to optical stimulations. The presence of nonlinearity in our data was checked using the null hypothesis that the data were linearly correlated in the temporal domain, but were random otherwise. For each trail, 100 surrogate data sets were generated and both time reversal asymmetry and false nearest neighbor (FNN) were used as discriminating statistics for the null hypothesis. We found that nonlinearity is present in all LFP data. The first 0.5 s of each 2 s LFP recording were dominated by the transient response of the networks. For each trial, we used the last 1.5 s of steady activity to measure the phase resetting induced by the brief 10 ms light stimulus. After correcting the LFPs for the effect of phase resetting, additional preprocessing was carried out using dendrograms to identify ``similar'' groups among LFP trials. We found that the steady dynamics of mPFC in response to light stimuli could be reconstructed in a three-dimensional phase space with topologically similar ``8''-shaped attractors across different animals. Our results also open the possibility of designing a low-dimensional model for optical stimulation of the mPFC local network

Testing the Network Reset Hypothesis: Noradrenergic Modulation of Hippocampal Representations

The locus coeruleus (LC) responds to salience cues, including novelty, and sends a major noradrenergic projection to the hippocampal formation (HF). Novelty-associated LC activation may help to sculpt contextual representations in the HF, but modulatory influence of norepinephrine (NE) over HF representations remains poorly understood. One possible mechanism is that NE provides a “reset” signal causing the HF to recruit distinct neural populations, thereby providing a molecular switch to dictate if hippocampal circuits should generate new representations or update existing ones to incorporate novel information. This hypothesis suggests that NE release should cause the HF to recruit a unique population even in the presence of the same stimuli an animal has just experienced, a phenomenon referred to as “global remapping”. The compartmental expression of immediate early genes (i.e. arc & zif268) allowed us to test this by mapping the activity history of individual neurons as animals engaged in spatial processing following LC-NE manipulation. Recruitment of new neurons is part of the memory encoding process involved in separating memories. Tasks involving memory retrieval require reactivation of representations formed during encoding. If those representations “remapped” (i.e. a new cellular ensemble was recruited, rather than reactivation of the cells comprising the previously formed representation), this should theoretically result in a retrieval error. Therefore, switching the system back to a state of encoding would prove maladaptive in situations where retrieval is necessary to perform a task, unless new information was at hand. We hypothesize that NE resets the system causing the HF to move from a state of retrieval back to encoding when it is necessary, when novel information needs to be incorporated. This hypothesis suggests the effect of modulating NE on memory critically depends on the stage of training. To further understand how NE modulation of hippocampal circuits affects spatial memory, we tested whether infusions of the β-adrenergic agonist isoproterenol would impair working and reference memory retrieval (i.e., switching the system back to encoding when it is maladaptive) and in contrast, promote cognitive flexibility thus improving reversal learning (i.e., switching the system back to encoding when it is adaptive)

On the role of parvalbumin interneurons in neuronal network activity in the prefrontal cortex

The prefrontal cortex (PFC) is an area important for executive functions, the initiation and temporal organization of goal-directed behavior, as well as social behaviors. Inhibitory interneurons expressing parvalbumin (PV) have a vital role in modulating PFC circuit plasticity and output, as inhibition by PV interneurons on excitatory pyramidal neurons regulates the excitability of the network. Thus, dysfunctions of prefrontal PV interneurons are implicated in the pathophysiology of a range of PFC-dependent neuropsychiatric disorders characterized by excitation and inhibition (E/I) imbalance and impaired gamma oscillations. In particular, the hypofunction of receptors important for neurotransmission and regulating cellular functions, such as the N-methyl-D-aspartate receptors (NMDARs) and the tyrosine receptor kinase B (trkB), has been implicated in PV dysfunction. Notably, this hypofunction is known to impair the normal development of PV interneurons. However, it can also affect adult brain activity. The effects of altered receptors on PV interneurons are multiple, from impaired morphological connectivity to disruption of intrinsic activity, but have not yet been fully characterized. Moreover, the effects of deficits of PV neuron-mediated inhibition on neuronal network activity are complex, involved with compensatory mechanisms, and not fully understood either. For instance, the E/I imbalance due to PV inhibition has been suggested to functionally disrupt the cortex, which can be observed through an abnormal increase in broadband gamma activity. But as the synchronous activity of cortical PV interneurons is necessary for the generation of cortical gamma oscillations, it is paradoxical that deficient PV inhibition is associated with increased broadband gamma power. This thesis aims to examine the role of PV interneurons in shaping neuronal network activity in the mouse PFC by investigating the microscopic to macroscopic functional effects of disrupting receptors necessary for the proper activity of PV interneurons. In paper I, we observed that the increase of broadband gamma power due to NMDAR hypofunction in PV neurons is associated with asynchronies of network activity, confirming that dysfunction of neuronal inhibition can cause desynchronization at multiple time scales (affecting entrainment of spikes by the LFP, as well as cross-frequency coupling and brain states fragmentation). In Paper II, we prompted and analyzed the rippling effect of PV dysfunction in the adult PFC by expressing a dominant-negative trkB receptor specifically in PV interneurons. Despite avoiding interfering with the development of the brain, we found pronounced morphological and functional alterations in the targeted PV interneurons. These changes were associated with unusual aggressive behavior coupled with gamma-band alterations and a decreased modulation of prefrontal excitatory neuronal populations by PV interneurons. Thus, the work presented in this thesis furthers our understanding of the role of PV function in PFC circuitry, particularly of two receptors that are central to the role of PV interneurons in coordinating local circuit activity. A better understanding of the potential mechanisms that could explain the neuronal changes seen in individuals with neuropsychiatric dysfunctions could lead to using gamma oscillations or BDNF-trkB levels as biomarkers in psychiatric disorders. It also presents possibilities for potential treatments designed around reestablishing E/I balance by modifying receptor levels in particular cell types

29th Annual Computational Neuroscience Meeting: CNS*2020

Meeting abstracts This publication was funded by OCNS. The Supplement Editors declare that they have no competing interests. Virtual | 18-22 July 202

Single session neurofeedback treatment alters theta/beta-1 and theta/alpha ratios but not sufficient to induce clinical enhancement in attention

Background and Aims: Neurofeedback treatment (NFT) may enhance attention performance in healthy individuals. This study investigated the effects of single session NFT on attention in healthy individuals performing a visual attention task. Methods: This was an open-label single-blinded trial conducted on 14 healthy university students (n=14; mean=23.35±0.58 years) of a major medical university in Iran. The subjects underwent a single session NFT while performing attentional network task (ANT). The NFT protocol was theta suppression/beta-1enhancement applied at Cz for 20 min. Before and immediately after NFT, EEG signals were recorded in subjects while performing ANT. EEGs were recorded using a 19 channel device and 10-20 placement protocol. Results: The single session NFT increased the theta/beta-1 ratio in most of the electrode sites and the increase was statistically significant compared to the pre-intervention in the T6 site (p=0.011). The ratio decreased in just three sites of C3, Fz, and Cz, of them Fz showed a significant reduction (p=0.026). Contrary, the theta/alpha ratio decreased in most of the electrodes where the reductions were statistically significant in P3, P4, Cz, Pz (p<0.05), and C3 (p<0.01). The F7, F8, T3, and T4 showed no significant increased theta/alpha ratio. The central, temporal and occipital regions were involved in the NFT induced changes. Single NFT did not significantly change alerting, executive, or orienting networks of ANT. Conclusions: Theta/beta-1 and theta/alpha ratios can be reliably used to assess NFT induced attention enhancement. However, single NFT did not induce clinical outcomes and repeated sessions seem necessary to modulate alerting, executive, or orienting networks of ANT

Alpha asymmetry index of prefrontal and temporal regions predicts treatment response to repetitive transcranial magnetic stimulation

Aims: Electroencephalography (EEG) measures could be a potential markers for prediction of repetitive transcranial magnetic stimulation (rTMS) outcomes in depression. The aim of this study was to investigate the value of alpha asymmetric index (AAI) in predicting treatment response in two different protocols of rTMS in patients with intractable major depression. Methods: Patients with intractable major depression (n=34) were divided into two treatment groups underwent two different rTMS protocols. The first group received ten sessions 20 Hz rTMS The second group received 10 Hz rTMS . The EEGs were recorded in all subjects pre- and post-intervention using a 19-channel, 10-20 electrodes placement protocol. Hamilton depression rating scale-17 items (HDRS-17) was used to divide the patients into responders and non-responder. The AAI in prefrontal (Fp1-Fp2), frontal (F3-F4 and F7-F8), and temporal (T3-T4) regions were calculated and compared between pre- and post-intervention in each group and between the responder and non-responder groups. Results: In the 20 Hz rTMS group responders, 6 patients responded to the treatment, whereas 10 Hz rTMS showed 8 responders. In the responders of 20 Hz rTMS, the AAI at Fp1-Fp2, F3-F4, and T3-T4significantly decreased after the intervention (P=0.011, P=0.042, and P=0.035). The responders of 10 Hz rTMS showed significant reduction in the AAI at Fp1-Fp2 and T3-T4 regions after intervention (P= 0.023 and P=0.044). Conclusions: It seems AAI at prefrontal and temporal region scould be used for prediction of treatment response, regardless of rTMS protocol

Electrophysiological evidence for memory schemas in the rat hippocampus

According to Piaget and Bartlett, learning involves both assimilation of new memories into networks of preexisting knowledge and alteration of existing networks to accommodate new information into existing schemas. Recent evidence suggests that the hippocampus integrates related memories into schemas that link representations of separately acquired experiences. In this thesis, I first review models for how memories of individual experiences become consolidated into the structure of world knowledge. Disruption of consolidated memories can occur during related learning, which suggests that consolidation of new information is the reconsolidation of related memories. The accepted role of the hippocampus during memory consolidation and reconsolidation suggests that it is also involved in modifying appropriate schemas during learning. To study schema development, I trained rats to retrieve rewards at different loci on a maze while recording hippocampal calls. About a quarter of cells were active at multiple goal sites, though the ensemble as a whole distinguished goal loci from one another. When new goals were introduced, cells that had been active at old goal locations began firing at the new locations. This initial generalization decreased in the days after learning. Learning also caused changes in firing patterns at well-learned goal locations. These results suggest that learning was supported by modification of an active schema of spatially related reward loci. In another experiment, I extended these findings to explore a schema of object and place associations. Ensemble activity was influenced by a hierarchy of task dimensions which included: experimental context, rat's spatial location, the reward potential and the identity of sampled objects. As rats learned about new objects, the cells that had previously fired for particular object-place conjunctions generalized their firing patterns to new conjunctions that similarly predicted reward. In both experiments, I observed highly structured representations for a set of related experiences. This organization of hippocampal activity counters key assumptions in standard models of hippocampal function that predict relative independence between memory traces. Instead, these findings reveal neural mechanisms for how the hippocampus develops a relational organization of memories that could support novel, inferential judgments between indirectly related events

The Role of Synaptic Tagging and Capture for Memory Dynamics in Spiking Neural Networks

Memory serves to process and store information about experiences such that this information can be used in future situations. The transfer from transient storage into long-term memory, which retains information for hours, days, and even years, is called consolidation. In brains, information is primarily stored via alteration of synapses, so-called synaptic plasticity. While these changes are at first in a transient early phase, they can be transferred to a late phase, meaning that they become stabilized over the course of several hours. This stabilization has been explained by so-called synaptic tagging and capture (STC) mechanisms. To store and recall memory representations, emergent dynamics arise from the synaptic structure of recurrent networks of neurons. This happens through so-called cell assemblies, which feature particularly strong synapses. It has been proposed that the stabilization of such cell assemblies by STC corresponds to so-called synaptic consolidation, which is observed in humans and other animals in the first hours after acquiring a new memory. The exact connection between the physiological mechanisms of STC and memory consolidation remains, however, unclear. It is equally unknown which influence STC mechanisms exert on further cognitive functions that guide behavior. On timescales of minutes to hours (that means, the timescales of STC) such functions include memory improvement, modification of memories, interference and enhancement of similar memories, and transient priming of certain memories. Thus, diverse memory dynamics may be linked to STC, which can be investigated by employing theoretical methods based on experimental data from the neuronal and the behavioral level. In this thesis, we present a theoretical model of STC-based memory consolidation in recurrent networks of spiking neurons, which are particularly suited to reproduce biologically realistic dynamics. Furthermore, we combine the STC mechanisms with calcium dynamics, which have been found to guide the major processes of early-phase synaptic plasticity in vivo. In three included research articles as well as additional sections, we develop this model and investigate how it can account for a variety of behavioral effects. We find that the model enables the robust implementation of the cognitive memory functions mentioned above. The main steps to this are: 1. demonstrating the formation, consolidation, and improvement of memories represented by cell assemblies, 2. showing that neuromodulator-dependent STC can retroactively control whether information is stored in a temporal or rate-based neural code, and 3. examining interaction of multiple cell assemblies with transient and attractor dynamics in different organizational paradigms. In summary, we demonstrate several ways by which STC controls the late-phase synaptic structure of cell assemblies. Linking these structures to functional dynamics, we show that our STC-based model implements functionality that can be related to long-term memory. Thereby, we provide a basis for the mechanistic explanation of various neuropsychological effects.2021-09-0