Gain control of γ frequency activation by a novel feed forward disinhibitory loop: implications for normal and epileptic neural activity

نویسندگان

  • Zeinab Birjandian
  • Chakravarthi Narla
  • Michael O. Poulter
چکیده

The inhibition of excitatory (pyramidal) neurons directly dampens their activity resulting in a suppression of neural network output. The inhibition of inhibitory cells is more complex. Inhibitory drive is known to gate neural network synchrony, but there is also a widely held view that it may augment excitability by reducing inhibitory cell activity, a process termed disinhibition. Surprisingly, however, disinhibition has never been demonstrated to be an important mechanism that augments or drives the activity of excitatory neurons in a functioning neural circuit. Using voltage sensitive dye imaging (VSDI) we show that 20-80 Hz stimulus trains, β-γ activation, of the olfactory cortex pyramidal cells in layer II leads to a subsequent reduction in inhibitory interneuron activity that augments the efficacy of the initial stimulus. This disinhibition occurs with a lag of about 150-250 ms after the initial excitation of the layer 2 pyramidal cell layer. In addition, activation of the endopiriform nucleus also arises just before the disinhibitory phase with a lag of about 40-80 ms. Preventing the spread of action potentials from layer II stopped the excitation of the endopiriform nucleus, abolished the disinhibitory activity, and reduced the excitation of layer II cells. After the induction of experimental epilepsy the disinhibition was more intense with a concomitant increase in excitatory cell activity. Our observations provide the first evidence of feed forward disinhibition loop that augments excitatory neurotransmission, a mechanism that could play an important role in the development of epileptic seizures.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Corrigendum: Gain control of gamma frequency activation by a novel feed forward disinhibitory loop: implications for normal and epileptic neural activity

Figure 1 of the article by Birjandian et al. (2013) contained a minor error in the legend, which we hereby rectify. In the original figure legend panel (C) is described as two examples of whole cell patch recordings made from layer II and layer III neurons. But in fact panel (C) correspond to normalized change in F/F vs. stimulus intensity from 8 recordings in the layer II. Panels (D,E) corresp...

متن کامل

Effect of sound classification by neural networks in the recognition of human hearing

In this paper, we focus on two basic issues: (a) the classification of sound by neural networks based on frequency and sound intensity parameters (b) evaluating the health of different human ears as compared to of those a healthy person. Sound classification by a specific feed forward neural network with two inputs as frequency and sound intensity and two hidden layers is proposed. This process...

متن کامل

Numerical treatment for nonlinear steady flow of a third grade‎ fluid in a porous half space by neural networks optimized

In this paper‎, ‎steady flow of a third-grade fluid in a porous half‎ space has been considered‎. ‎This problem is a nonlinear two-point‎ boundary value problem (BVP) on semi-infinite interval‎. ‎The‎ solution for this problem is given by a numerical method based on the feed-forward artificial‎ neural network model using radial basis activation functions trained with an interior point method‎. ...

متن کامل

Studying Dynamic behavior of Distributed Parameter Processes Behavior Based on Dominant Gain Concept and it’s Use in Controlling these Processes

In this paper, distributed parameter process systems behavior is studied in frequency domain. Based on the dominant gain concept that is developed for such studies, a method is presented to control distributed parameter process systems. By using dominant gain concept, the location of open loop zeros, resulted from the time delay parameter in the process model, were changed from the right half p...

متن کامل

A Novel Fuzzy and Artificial Neural Network Representation of Overcurrent Relay Characteristics

Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2013