Response Dynamics of Entorhinal Cortex in Awake, Anesthetized, and Bulbotomized Rats. <i>Brain Research</i> <b>911</b>(2)

The generation of oscillatory activity may be crucial to brain function. The coordination of individual neurons into rhythmic and coherently active populations is thought to result from interactions between excitatory and inhibitory cells mediated by local feedback connections. By using extracellular recording wires and silicon microprobes to measure electrically evoked damped oscillatory responses at the level of neural populations in the entorhinal cortex, and by using current-source density analysis to determine the spatial pattern of evoked responses, we show that the propagation of activity through the cortical circuit and consequent oscillations in the local field potential are dependent upon background neural activity. Pharmacological manipulations as well as surgical disconnection of the olfactory bulb serve to quell the background excitatory input incident to entorhinal cortex, resulting in evoked responses without characteristic oscillations and showing no signs of polysynaptic feedback. Electrical stimulation at 200 Hz applied to the lateral olfactory tract provides a substitute for the normal background activity emanating from the bulb and enables the generation of oscillatory responses once again. We conclude that a nonzero background level of activity is necessary and sufficient to sustain normal oscillatory responses and polysynaptic transmission through the entorhinal cortex

Rate region analysis of multi-terminal neuronal nanoscale molecular communication channel

© 2017 IEEE. In this paper, we investigate the communication channel capacity among hippocampal pyramidal neurons. To this aim, we study the processes included in this communication and model them with realistic communication system components based on the existing reports in the physiology literature. We consider the communication between two neurons and reveal the effects of the existence of multiple terminals between these neurons on the achievable rate per spike. To this objective, we derive the power spectral density (PSD) of the signal in the output neuron and utilize it to calculate the rate region of the channel. Moreover, we evaluate the impacts of vesicle availability on the achievable rate by deriving the expected number of available vesicles in input neuron using a realistic vesicle release model. Simulation results show that number of available vesicles for release does not affect the achievable rate of neuro-spike communication with univesicular release model. However, in neurons that multiple vesicles can release from each synaptic terminal, achievable rate is significantly affected by depletion of vesicles. Moreover, we show that increasing the number of synaptic terminals between two neurons makes the synaptic connection stronger. Hence, it is an important factor in learning and memory, which occur in the hippocampal region of the brain based on the synaptic connectivity

The spectro-contextual encoding and retrieval theory of episodic memory.

The spectral fingerprint hypothesis, which posits that different frequencies of oscillations underlie different cognitive operations, provides one account for how interactions between brain regions support perceptual and attentive processes (Siegel etal., 2012). Here, we explore and extend this idea to the domain of human episodic memory encoding and retrieval. Incorporating findings from the synaptic to cognitive levels of organization, we argue that spectrally precise cross-frequency coupling and phase-synchronization promote the formation of hippocampal-neocortical cell assemblies that form the basis for episodic memory. We suggest that both cell assembly firing patterns as well as the global pattern of brain oscillatory activity within hippocampal-neocortical networks represents the contents of a particular memory. Drawing upon the ideas of context reinstatement and multiple trace theory, we argue that memory retrieval is driven by internal and/or external factors which recreate these frequency-specific oscillatory patterns which occur during episodic encoding. These ideas are synthesized into a novel model of episodic memory (the spectro-contextual encoding and retrieval theory, or "SCERT") that provides several testable predictions for future research

When, where and how? Focus on neuronal calcium dysfunctions in Alzheimer's Disease.

Alzheimer\u2019s disease (AD), since its characterization as a precise form of dementia with its own pathological hallmarks, has captured scientists\u2019 attention because of its complexity. The last 30 years have been filled with discoveries regarding the elusive aetiology of this disease and, thanks to advances in molecular biology and live imaging techniques, we now know that an important role is played by calcium (Ca2+). Ca2+, as ubiquitous second messenger, regulates a vast variety of cellular processes, from neuronal excitation and communication, to muscle fibre contraction and hormone secretion, with its action spanning a temporal scale that goes from microseconds to hours. It is therefore very challenging to conceive a single hypothesis that can integrate the numerous findings on this issue with those coming from the classical fields of AD research such as amyloid-beta (A) and tau pathology. In this contribution, we will focus our attention on the Ca2+ hypothesis of AD, dissecting it, as much as possible, in its subcellular localization, where the Ca2+ signal meets its specificity. We will also follow the temporal evolution of the Ca2+ hypothesis, providing some of the most updated discoveries. Whenever possible, we will link the findings regarding Ca2+ dysfunction to the other players involved in AD pathogenesis, hoping to provide a crossover body of evidence, useful to amplify the knowledge that will lead towards the discovery of an effective therapy

Sum rate analysis of multiple-access neuro-spike communication channel with dynamic spiking threshold

© 2019 Elsevier B.V. The information from outside world is encoded into spikes by the sensory neurons. These spikes are further propagated to different brain regions through various neural pathways. In the cortical region, each neuron receives inputs from multiple neurons that change its membrane potential. If the accumulated change in the membrane potential is more than a threshold value, a spike is generated. According to various studies in neuroscience, this spiking threshold adapts with time depending on the previous spike. This causes short-term changes in the neural responses giving rise to short-term plasticity. Therefore, in this paper, we analyze a multiple-input single-output (MISO) neuro-spike communication channel and study the effects of dynamic spiking threshold on mutual information and maximum achievable sum rate of the channel. Since spike generation consumes a generous portion of the metabolic energy provided to the brain, we further put metabolic constraint in calculating the mutual information and find a trade-off between maximum achievable sum rate and metabolic energy consumed. Moreover, we analyze three types of neurons present in the cortical region, i.e., Regular spiking, Intrinsic bursting and Fast spiking neurons. We aim to characterize these neurons in terms of encoding/transmission rates and energy expenditure. It will provide a guideline for the practical implementation of bio-inspired nanonetworks as well as for the development of ICT-based diagnosis and treatment techniques for neural diseases.This work was supported in part by European Research Council (ERC) under grant ERC-2013-CoG 616922 (Project MINERVA) and ERC-2017-PoC 780645 (ERC Proof of Concept project MINRGRACE)

Cell biological mechanisms of activity-dependent synapse to nucleus translocation of CRTC1 in neurons.

Previous studies have revealed a critical role for CREB-regulated transcriptional coactivator (CRTC1) in regulating neuronal gene expression during learning and memory. CRTC1 localizes to synapses but undergoes activity-dependent nuclear translocation to regulate the transcription of CREB target genes. Here we investigate the long-distance retrograde transport of CRTC1 in hippocampal neurons. We show that local elevations in calcium, triggered by activation of glutamate receptors and L-type voltage-gated calcium channels, initiate active, dynein-mediated retrograde transport of CRTC1 along microtubules. We identify a nuclear localization signal within CRTC1, and characterize three conserved serine residues whose dephosphorylation is required for nuclear import. Domain analysis reveals that the amino-terminal third of CRTC1 contains all of the signals required for regulated nucleocytoplasmic trafficking. We fuse this region to Dendra2 to generate a reporter construct and perform live-cell imaging coupled with local uncaging of glutamate and photoconversion to characterize the dynamics of stimulus-induced retrograde transport and nuclear accumulation

Membrane resonance enables stable and robust gamma oscillations

Neuronal mechanisms underlying beta/gamma oscillations (20-80 Hz) are not completely understood. Here, we show that in vivo beta/gamma oscillations in the cat visual cortex sometimes exhibit remarkably stable frequency even when inputs fluctuate dramatically. Enhanced frequency stability is associated with stronger oscillations measured in individual units and larger power in the local field potential. Simulations of neuronal circuitry demonstrate that membrane properties of inhibitory interneurons strongly determine the characteristics of emergent oscillations. Exploration of networks containing either integrator or resonator inhibitory interneurons revealed that: (i) Resonance, as opposed to integration, promotes robust oscillations with large power and stable frequency via a mechanism called RING (Resonance INduced Gamma); resonance favors synchronization by reducing phase delays between interneurons and imposes bounds on oscillation cycle duration; (ii) Stability of frequency and robustness of the oscillation also depend on the relative timing of excitatory and inhibitory volleys within the oscillation cycle; (iii) RING can reproduce characteristics of both Pyramidal INterneuron Gamma (PING) and INterneuron Gamma (ING), transcending such classifications; (iv) In RING, robust gamma oscillations are promoted by slow but are impaired by fast inputs. Results suggest that interneuronal membrane resonance can be an important ingredient for generation of robust gamma oscillations having stable frequency

Functional Brain Oscillations: How Oscillations Facilitate Information Representation and Code Memories

The overall aim of the modelling works within this thesis is to lend theoretical evidence to empirical findings from the brain oscillations literature. We therefore hope to solidify and expand the notion that precise spike timing through oscillatory mechanisms facilitates communication, learning, information processing and information representation within the brain. The primary hypothesis of this thesis is that it can be shown computationally that neural de-synchronisations can allow information content to emerge. We do this using two neural network models, the first of which shows how differential rates of neuronal firing can indicate when a single item is being actively represented. The second model expands this notion by creating a complimentary timing mechanism, thus enabling the emergence of qualitive temporal information when a pattern of items is being actively represented. The secondary hypothesis of this thesis is that it can be also be shown computationally that oscillations might play a functional role in learning. Both of the models presented within this thesis propose a sparsely coded and fast learning hippocampal region that engages in the binding of novel episodic information. The first model demonstrates how active cortical representations enable learning to occur in their hippocampal counterparts via a phase-dependent learning rule. The second model expands this notion, creating hierarchical temporal sequences to encode the relative temporal position of cortical representations. We demonstrate in both of these models, how cortical brain oscillations might provide a gating function to the representation of information, whilst complimentary hippocampal oscillations might provide distinct phasic reference points for learning