scholarly journals Optimizing optogenetic stimulation protocols in auditory corticofugal neurons based on closed-loop spike feedback

2018 ◽  
Author(s):  
Charles-Henri Vila ◽  
Ross S Williamson ◽  
Kenneth E Hancock ◽  
Daniel B Polley
Keyword(s):  
Firing Rate ◽  
Closed Loop ◽  
Brain Area ◽  
Cortical Activation ◽  
Search Procedure ◽  
Evolutionary Search ◽  
Brain Areas ◽  
Functional Connections ◽  
Area Functional ◽  
Presynaptic Neurons

Optogenetics provides a means to probe functional connections between brain areas. By activating a set of presynaptic neurons and recording the activity from a downstream brain area, one can establish the sign and strength of a feedforward connection. One challenge is that there are virtually limitless patterns that can be used to stimulate a presynaptic brain area. Functional influences on downstream brain areas can depend not just on whether presynaptic neurons were activated, but how they were activated. Corticofugal axons from the auditory cortex (ACtx) heavily innervate the auditory tectum, the inferior colliculus (IC). Despite the anatomical weight of this connection, optogenetic activation of ACtx neurons produced only modest changes in the IC neuron firing rates. To determine whether different modes of cortical activation could more faithfully reveal the strength of feedforward connectivity, we employed a closed-loop evolutionary optimization procedure that tailored voltage command signals to the laser based on firing rate variations recorded from single units in the IC of awake male and female mice. Within minutes, the evolutionary search procedure converged on ACtx stimulation configurations that produced more effective and widespread enhancement of IC unit activity than generic activation parameters. Cortical modulation of midbrain spiking was bi-directional, as the evolutionary search procedure could be programmed to converge on activation patterns that suppressed or enhanced sound-evoked IC firing rate. These findings demonstrate that the feedforward influence between brain areas can vary both in sign and degree depending on how presynaptic neurons are activated in time.

scholarly journals Muscular Movements in Man, and their Evolution in the Infant: a Study of Movement in Man, and its Evolution, together with Inferences as to the Properties of Nerve-Centres and their Modes of Action in expressing Thought

1889 ◽  
Vol 35 (149) ◽  
pp. 23-44 ◽  
Author(s):  
Francis Warner
Keyword(s):  
Brain Area ◽  
Muscular Contraction ◽  
The Body ◽  
Brain Areas ◽  
Modes Of Action ◽  
Central Nerve System ◽  
Nerve System ◽  
The Brain ◽  
Compound Series ◽  
Stimulation Of

(1) Movement in mau has long been a subject of profitable study. Visible movement in the body is produced by muscular contraction following upon stimulation of the muscles by efferent currents passing from the central nerve-system. Modern physiological experiments have demonstrated that when a special brain-area discharges nerve-currents, these are followed by certain visible movements or contraction of certain muscles corresponding. So exact are such reactions, as obtained by experiment upon the brain-areas, that movements similar to those produced by experimental excitation of a certain brain-area may be taken as evidence of action in that area, or as commencing in discharge from that area (see Reinforcement of Movements, 35; Compound Series of Movements, 34).

scholarly journals Computational Principles of Supervised Learning in the Cerebellum

2018 ◽  
Vol 41 (1) ◽  
pp. 233-253 ◽  
Author(s):  
Jennifer L. Raymond ◽  
Javier F. Medina
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Supervised Learning ◽  
Brain Area ◽  
Future Research ◽  
Brain Areas ◽  
Adaptive Mechanisms ◽  
Networks Analysis ◽  
Artificial Neural ◽  
Organizational Principles

Supervised learning plays a key role in the operation of many biological and artificial neural networks. Analysis of the computations underlying supervised learning is facilitated by the relatively simple and uniform architecture of the cerebellum, a brain area that supports numerous motor, sensory, and cognitive functions. We highlight recent discoveries indicating that the cerebellum implements supervised learning using the following organizational principles: ( a) extensive preprocessing of input representations (i.e., feature engineering), ( b) massively recurrent circuit architecture, ( c) linear input–output computations, ( d) sophisticated instructive signals that can be regulated and are predictive, ( e) adaptive mechanisms of plasticity with multiple timescales, and ( f) task-specific hardware specializations. The principles emerging from studies of the cerebellum have striking parallels with those in other brain areas and in artificial neural networks, as well as some notable differences, which can inform future research on supervised learning and inspire next-generation machine-based algorithms.

scholarly journals Systematic Balance Exercises Influence Cortical Activation and Serum BDNF Levels in Older Adults

2019 ◽  
Vol 8 (11) ◽  
pp. 1910 ◽  
Author(s):  
Kubica ◽  
Szymura ◽  
Domagalik ◽  
Golda ◽  
Wiecek ◽  
...  
Keyword(s):  
Older Adults ◽  
Motor Imagery ◽  
Action Observation ◽  
Brain Area ◽  
Balance Training ◽  
Cortical Activation ◽  
Bdnf Expression ◽  
Age Related ◽  
Balance Exercises ◽  
Serum Bdnf

: We sought to investigate whether systematic balance training modulates brain area activity responsible for postural control and influence brain-derived neurotrophic factor (BDNF) mRNA protein expression. Seventy-four older adults were randomly divided into three groups (mean age 65.34 ± 3.79 years, 30 females): Classic balance exercises (CBT), virtual reality balance exercises (VBT), and control (CON). Neuroimaging studies were performed at inclusion and after completion of the training or 12 weeks later (CON). Blood samples were obtained to measure BDNF expression. The study revealed significant interaction of sessions and groups: In the motor imagery (MI) condition for supplementary motor area (SMA) activity (Fat peak = 5.25, p < 0.05); in the action observation (AO) condition for left and right supramarginal gyrus/posterior insula (left: Fat peak = 6.48, p < 0.05; right: Fat peak = 6.92, p < 0.05); in the action observation together with motor imagery (AOMI) condition for the middle occipital gyrus (laterally)/area V5 (left: Fat peak = 6.26, p < 0.05; right: Fat peak = 8.37, p < 0.05), and in the cerebellum–inferior semilunar lobule/tonsil (Fat peak = 5.47, p < 0.05). After the training serum BDNF level has increased in CBT (p < 0.001) and in CBT compared to CON (p < 0.05). Systematic balance training may reverse the age-related cortical over-activations and appear to be a factor mediating neuroplasticity in older adults.

scholarly journals Region-specific brain area reductions and increased cholecystokinin positive neurons in diabetic OLETF rats: implication for anxiety-like behavior

2020 ◽  
Vol 70 (1) ◽  
Author(s):  
Ryosuke Ochi ◽  
Naoto Fujita ◽  
Natsuki Goto ◽  
Son Tien Nguyen ◽  
Duc Trung Le ◽  
...  
Keyword(s):  
Metabolic Disorders ◽  
Basolateral Amygdala ◽  
Open Field Test ◽  
Brain Area ◽  
Brain Areas ◽  
Oletf Rats ◽  
Cornu Ammonis ◽  
Long Evans ◽  
Type 2 Diabetic

Abstract Metabolic disorders can induce psychiatric comorbidities. Both brain and neuronal composition imbalances reportedly induce an anxiety-like phenotype. We hypothesized that alterations of localized brain areas and cholecystokinin (CCK) and parvalbumin (PV) expression could induce anxiety-like behavior in type 2 diabetic Otsuka Long-Evans Tokushima fatty (OLETF) rats. Twenty-week-old OLETF and non-diabetic Long-Evans Tokushima Otsuka (LETO) rats were used. The areas of corticolimbic regions were smaller in OLETF rats. The densities of CCK positive neurons in the lateral and basolateral amygdala, hippocampal cornu ammonis area 2, and prelimbic cortex were higher in OLETF rats. The densities of PV positive neurons were comparable between OLETF and LETO rats. Locomotion in the center zone in the open field test was lower in OLETF rats. These results suggest that imbalances of specific brain region areas and neuronal compositions in emotion-related areas increase the prevalence of anxiety-like behaviors in OLETF rats.

Linear integration of convergent visual inputs in an oculomotor reflex pathway

1984 ◽  
Vol 52 (6) ◽  
pp. 1213-1225 ◽  
Author(s):  
R. M. Glantz ◽  
H. B. Nudelman ◽  
B. Waldrop
Keyword(s):  
Motor Neuron ◽  
Firing Rate ◽  
Motor Neurons ◽  
Receptive Fields ◽  
Polarized Light ◽  
Stray Light ◽  
Differential Sensitivity ◽  
Functional Connections ◽  
Cross Correlation Analysis ◽  
Oculomotor Neurons

The functional connectivity between identified visual interneurons [sustaining fibers (SF)] and oculomotor neurons was assessed by simultaneous recording and cross-correlation analysis. A small group of SFs exhibit excitatory functional connections to an identified tonic oculomotor neuron. The excitatory interactions are found exclusively between SFs and oculomotor neurons with similar and/or overlapping excitatory receptive fields. A second group of SFs exhibit inhibitory connections to motor neurons. The excitatory receptive fields of these SFs correspond to the inhibitory receptive fields of the motor neurons. The collective action of the SFs is sufficient to produce all of the steady-state visual behavior of the motor neurons including the increment in firing rate elicited by illumination, unique features of the motor neuron receptive field, and differential sensitivity to blue light and polarized light. Pairs of SFs that converge on the same motor neuron sum their effects linearly. Thus the joint interaction of two SFs on a motor neuron is equal to the sum of the two postsynaptic effects taken separately. Coactivation of excitatory and inhibitory SF inputs to a motor neuron results in a partial cancellation of their postsynaptic effects on the motor neuron's firing rate. The antagonistic interactions protect the system from perturbations by stray light, visual adaptation, and variations in the central excited state. The ensemble information code, at the SF level of the optomotor pathway, is a set of differentially weighted mean firing rates. The weightings reflect differences in the strengths of the several SF-to- motor neuron interactions. One consequence of these differences is a selective weighting of the effects of illumination (in different regions of visual space) on the compensatory eye reflex.

scholarly journals Neural Mechanisms in Eating Behaviors: A Pilot fMRI Study of Emotional Processing

2020 ◽  
Vol 17 (3) ◽  
pp. 225-236 ◽  
Author(s):  
Rosa M. Molina-Ruiz ◽  
T. García-Saiz ◽  
Jeffrey C.L. Looi ◽  
E. Via Virgili ◽  
M. Rincón Zamorano ◽  
...  
Keyword(s):  
Emotional Processing ◽  
Eating Behaviors ◽  
Brain Area ◽  
Self Control ◽  
Women Patients ◽  
Brain Areas ◽  
Fmri Study ◽  
Neural Substrate ◽  
Dorsolateral Prefrontal ◽  
Functional Relevance

Objective Emotional processing dysfunction evident in eating disorders (ED) such as anorexia nervosa (AN) and bulimia nervosa (BN), is considered relevant to the development and maintenance of these disorders. The purpose of the current functional magnetic resonance imaging (fMRI) study was to pilot a comparison of the activity of the fronto-limbic and fronto-striatal brain areas during an emotion processing task in persons with ED.Methods 24 women patients with ED were scanned, while showing emotionally stimulating (pleasant, unpleasant) and neutral images from the International Affective Picture System (IAPS).Results During the pleasant condition, significant differences in Dorsolateral Prefrontal Cortex (DLPFC) activations were found with AN participants presenting greater activation compared to BN and ED comorbid groups (EDc) and healthy controls also showing greater activation of this brain area compared to BN and EDc. Left putamen was less activated in EDc compared to both controls (C) and AN. During the unpleasant condition, AN participants showed hyperactivation of the Orbito-frontal Cortex (OFC) when compared to EDc.Conclusion This study highlights the potential functional relevance of brain areas that have been associated with self-control. These findings should help advance understanding the neural substrate of ED, though they should be considered as preliminary and be cautiously interpreted.

scholarly journals Closed-loop Controller Based on Reference Signal Tracking for Absence Seizures

2021 ◽  
Author(s):  
Hudong Zhang ◽  
Yuting Chen ◽  
Yan Xie ◽  
Yuan Chai
Keyword(s):  
Firing Rate ◽  
Closed Loop ◽  
Reference Signal ◽  
Absence Epilepsy ◽  
Open Loop ◽  
Recursive Least Squares ◽  
Biophysical Model ◽  
Reticular Nucleus ◽  
Cortical Region ◽  
Absence Seizures

Abstract Deep brain stimulation (DBS) targeting thalamus reticular nucleus (TRN) brain regions has been proven to play an irreplaceable role in the treatment of absence seizures. Compared with open-loop DBS, closed-loop DBS has been recognized by researchers for its advantages of significantly inhibiting seizures and having fewer side effects. However, due to the complexity of the nervous system, the mechanism of DBS control epilepsy is still unclear, which hinders the study of closed-loop DBS. In our study, based on the biophysical model jointly constituted by cortical, thalamic, and basal ganglia, we selected the 2-4 Hz spike and wave discharges (SWDs) of the cortical region as a biomarker for response to absence epilepsy, and the mean firing rate (MFR) of substantia nigra pars reticulata (SNr) was used as a reference signal for modulation of closed-loop DBS. Moreover, to obtain the linear relationship between the stimulus and the response, we adopted an algorithm that combines controlled auto-regressive (CAR) and recursive least squares (RLS), and we built a proportional integral (PI) controller to make the DBS stimulus parameters self-update to control the seizures. The numerical simulation results show that the closed-loop DBS controllers based on frequency modulation and amplitude modulation respectively not only successfully track the firing rate (FR) of SNr, but also significantly destroy the SWDs of cerebral cortex and restore it to the other two normal discharge modes.

scholarly journals Open-loop organization of thalamic reticular nucleus and dorsal thalamus: a computational model

2015 ◽  
Vol 114 (4) ◽  
pp. 2353-2367 ◽  
Author(s):  
Adam M. Willis ◽  
Bernard J. Slater ◽  
Ekaterina D. Gribkova ◽  
Daniel A. Llano
Keyword(s):  
Closed Loop ◽  
Open Loop ◽  
Tunable Filter ◽  
Cortical Activation ◽  
Thalamic Reticular Nucleus ◽  
Reticular Nucleus ◽  
Loop Model ◽  
Dependent Manner ◽  
Dorsal Thalamus ◽  
Low Threshold

The thalamic reticular nucleus (TRN) is a shell of GABAergic neurons that surrounds the dorsal thalamus. Previous work has shown that TRN neurons send GABAergic projections to thalamocortical (TC) cells to form reciprocal, closed-loop circuits. This has led to the hypothesis that the TRN is responsible for oscillatory phenomena, such as sleep spindles and absence seizures. However, there is emerging evidence that open-loop circuits are also found between TRN and TC cells. The implications of open-loop configurations are not yet known, particularly when they include time-dependent nonlinearities in TC cells such as low-threshold bursting. We hypothesized that low-threshold bursting in an open-loop circuit could be a mechanism by which the TRN could paradoxically enhance TC activation, and that enhancement would depend on the relative timing of TRN vs. TC cell stimulation. To test this, we modeled small circuits containing TC neurons, TRN neurons, and layer 4 thalamorecipient cells in both open- and closed-loop configurations. We found that open-loop TRN stimulation, rather than universally depressing TC activation, increased cortical output across a broad parameter space, modified the filter properties of TC neurons, and altered the mutual information between input and output in a frequency-dependent and T-type calcium channel-dependent manner. Therefore, an open-loop model of TRN-TC interactions, rather than suppressing transmission through the thalamus, creates a tunable filter whose properties may be modified by outside influences onto the TRN. These simulations make experimentally testable predictions about the potential role for the TRN for flexible enhancement of cortical activation.

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