An Investigation of the Neurophysiological Correspondents of Learning and Memory in Two Forebrain Regions of the Day-Old Chick

Spontaneous bursting (5 or more spikes of 200-450mV amplitude at 400Hz) occurs in many areas of chick forebrain. Day-old chicks trained on a one-trial passive avoidance task show a bilateral increase of up to 350% in bursting following training in one of these areas: the intermediate medial hyperstriatum ventrale, or IMHV (Mason & Rose, 1987; 1988). An investigation was carried out into the time course and lateralization of this change in bursting activity following the training of day-old chicks on a passive avoidance task. Chicks were trained to either avoid a bead coated with the bitter-tasting substance methylanthranilate (M-birds) or were trained to peck a water coated bead (W-birds). Bursting was recorded sequentially from the IMHV of both hemispheres at 8 time points over the period 1 to 9 hours post-test. The results indicate that there are significant differences in bursting activity recorded from M-birds only during the period 3-7hr posttest, when compared to W-birds. Between 6-7hr posttest there are significant differences in the burst firing patterns of the right IMHV of M-birds compared to the left. At other time points tested there are no significant differences between hemispheres. No between hemisphere differences are evident in W-birds. Multi-unit recordings were made from the lobus parolfactorius (LPO), another forebrain structure to show changes in biochemistry and morphology following passive avoidance training. M-birds showed a higher incidence of bursting when compared to W-birds over the period 1-10hr posttest. No lateralization of bursting was seen in either group at any time posttest. In a further experiment, chicks trained to avoid the methylanthranilate coated bead were subjected to subconvulsive electroshock 5min posttraining. This procedure was used to test whether the training-induced increase in bursting in the LPO was a direct correlate of memory formation for the task. This electroshock treatment produced two groups of birds: one group that avoided the bead (remembered the task) and another that pecked the bead (forgot the task). Multi-unit recordings from the LPO of these two groups revealed that the group that avoided the bead had a significantly higher mean burst-frequency when compared to the group that pecked the bead, indicating that increased bursting in the LPO following training is directly associated with recall for the task. These results are similar to those of Mason and Rose (1988) who showed that amnesia abolished a training-induced enhancement of bursting in the IMHV. The effects of pretraining bilateral LPO lesions on IMHV bursting activity were examined. The IMHV of four groups of birds was recorded ftom following training: two groups of M-birds, one with LPO lesions the other with sham LPO lesions and two similarly treated groups of W-birds. A significant increase in overall IMHV bursting activity was observed in sham-lesioned M-birds when compared to sham-lesioned W-birds. However, no significant difference in bursting activity was seen between lesioned M-birds and lesioned W-birds. There was a trend towards a higher overall level of bursting in lesioned W-birds, when compared to sham-lesioned W-birds. These results are discussed with reference to previous electrophysiological studies concerning the role of burst-firing patterns in models of learning and memory

Biochemistry of the sphingolipides. X. Phytoglycolipide, a complex phytosphingosine‐containing lipide from plant seeds

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141721/1/aocs0335.pd

Phase-locking of bursting neuronal firing to dominant LFP frequency components

Neuronal firing in the hippocampal formation relative to the phase of local field potentials (LFP) has a key role in memory processing and spatial navigation. Firing can be in either tonic or burst mode. Although bursting neurons are common in the hippocampal formation, the characteristics of their locking to LFP phase are not completely understood. We investigated phase-locking properties of bursting neurons using simulations generated by a dual compartmental model of a pyramidal neuron adapted to match the bursting activity in the subiculum of a rat. The model was driven with stochastic input signals containing a power spectral profile consistent with physiologically relevant frequencies observed in LFP. The single spikes and spike bursts fired by the model were locked to a preferred phase of the predominant frequency band where there was a peak in the power of the driving signal. Moreover, the preferred phase of locking shifted with increasing burst size, providing evidence that LFP phase can be encoded by burst size. We also provide initial support for the model results by analysing example data of spontaneous LFP and spiking activity recorded from the subiculum of a single urethane-anaesthetised rat. Subicular neurons fired single spikes, two-spike bursts and larger bursts that locked to a preferred phase of either dominant slow oscillations or theta rhythms within the LFP, according to the model prediction. Both power-modulated phase-locking and gradual shift in the preferred phase of locking as a function of burst size suggest that neurons can use bursts to encode timing information contained in LFP phase into a spike-count code

Inverse Current Source Density Method in Two Dimensions: Inferring Neural Activation from Multielectrode Recordings

The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets

Bursting Neurons in the Hippocampal Formation Encode Features of LFP Rhythms

Burst spike patterns are common in regions of the hippocampal formation such as the subiculum and medial entorhinal cortex (MEC). Neurons in these areas are immersed in extracellular electrical potential fluctuations often recorded as the local field potential (LFP). LFP rhythms within different frequency bands are linked to different behavioral states. For example, delta rhythms are often associated with slow-wave sleep, inactivity and anesthesia; whereas theta rhythms are prominent during awake exploratory behavior and REM sleep. Recent evidence suggests that bursting neurons in the hippocampal formation can encode LFP features. We explored this hypothesis using a two-compartment model of a bursting pyramidal neuron driven by time-varying input signals containing spectral peaks at either delta or theta rhythms. The model predicted a neural code in which bursts represented the instantaneous value, phase, slope and amplitude of the driving signal both in their timing and size (spike number). To verify whether this code is employed in vivo, we examined electrophysiological recordings from the subiculum of anesthetized rats and the MEC of a behaving rat containing prevalent delta or theta rhythms, respectively. In both areas, we found bursting cells that encoded information about the instantaneous voltage, phase, slope and/or amplitude of the dominant LFP rhythm with essentially the same neural code as the simulated neurons. A fraction of the cells encoded part of the information in burst size, in agreement with model predictions. These results provide in-vivo evidence that the output of bursting neurons in the mammalian brain is tuned to features of the LFP

Neural mechanisms underlying psilocybin’s therapeutic potential – the need for preclinical in vivo electrophysiology

Psilocybin is a naturally occurring psychedelic compound with profound perception-, emotion- and cognition-altering properties and great potential for treating brain disorders. However, the neural mechanisms mediating its effects require in-depth investigation as there is still much to learn about how psychedelic drugs produce their profound and long-lasting effects. In this review, we outline the current understanding of the neurophysiology of psilocybin’s psychoactive properties, highlighting the need for additional preclinical studies to determine its effect on neural network dynamics. We first describe how psilocybin’s effect on brain regions associated with the default-mode network (DMN), particularly the prefrontal cortex and hippocampus, likely plays a key role in mediating its consciousness-altering properties. We then outline the specific receptor and cell types involved and discuss contradictory evidence from neuroimaging studies regarding psilocybin’s net effect on activity within these regions. We go on to argue that in vivo electrophysiology is ideally suited to provide a more holistic, neural network analysis approach to understand psilocybin’s mode of action. Thus, we integrate information about the neural bases for oscillatory activity generation with the accumulating evidence about psychedelic drug effects on neural synchrony within DMN-associated areas. This approach will help to generate important questions for future preclinical and clinical studies. Answers to these questions are vital for determining the neural mechanisms mediating psilocybin’s psychotherapeutic potential, which promises to improve outcomes for patients with severe depression and other difficulty to treat conditions