Neuronal Adaptation: Tired Neurons or Wired Networks?

Adaptation-induced sharpening of orientation tuning curves in the mouse visual cortex

OBJECTIVE

Orientation selectivity is an emergent property of visual neurons across species with columnar and noncolumnar organization of the visual cortex. The emergence of orientation selectivity is more established in columnar cortical areas than in noncolumnar ones. Thus, how does orientation selectivity emerge in noncolumnar cortical areas after an adaptation protocol? Adaptation refers to the constant presentation of a nonoptimal stimulus (adapter) to a neuron under observation for a specific time. Previously, it had been shown that adaptation has varying effects on the tuning properties of neurons, such as orientation, spatial frequency, motion and so on.

BASIC METHODS

We recorded the mouse primary visual neurons (V1) at different orientations in the control (preadaptation) condition. This was followed by adapting neurons uninterruptedly for 12 min and then recording the same neurons postadaptation. An orientation selectivity index (OSI) for neurons was computed to compare them pre- and post-adaptation.

MAIN RESULTS

We show that 12-min adaptation increases the OSI of visual neurons ( n  = 113), that is, sharpens their tuning. Moreover, the OSI postadaptation increases linearly as a function of the OSI preadaptation.

CONCLUSION

The increased OSI postadaptation may result from a specific dendritic neural mechanism, potentially facilitating the rapid learning of novel features.

"Extended Descriptive Risk-Averse Bayesian Model" a More Comprehensive Approach in Simulating Complex Biological Motion Perception

The ability to perceive biological motion is crucial for human survival, social interactions, and communication. Over the years, researchers have studied the mechanisms and neurobiological substrates that enable this ability. In a previous study, we proposed a descriptive Bayesian simulation model to represent the dorsal pathway of the visual system, which processes motion information. The model was inspired by recent studies that questioned the impact of dynamic form cues in biological motion perception and was trained to distinguish the direction of a soccer ball from a set of complex biological motion soccer-kick stimuli. However, the model was unable to simulate the reaction times of the athletes in a credible manner, and a few subjects could not be simulated. In this current work, we implemented a novel disremembering strategy to incorporate neural adaptation at the decision-making level, which improved the model's ability to simulate the athletes' reaction times. We also introduced receptive fields to detect rotational optic flow patterns not considered in the previous model to simulate a new subject and improve the correlation between the simulation and experimental data. The findings suggest that rotational optic flow plays a critical role in the decision-making process and sheds light on how different individuals perform at different levels. The correlation analysis of human versus simulation data shows a significant, almost perfect correlation between experimental and simulated angular thresholds and slopes, respectively. The analysis also reveals a strong relation between the average reaction times of the athletes and the simulations.

How learning unfolds in the brain: toward an optimization view

How do changes in the brain lead to learning? To answer this question, consider an artificial neural network (ANN), where learning proceeds by optimizing a given objective or cost function. This "optimization framework" may provide new insights into how the brain learns, as many idiosyncratic features of neural activity can be recapitulated by an ANN trained to perform the same task. Nevertheless, there are key features of how neural population activity changes throughout learning that cannot be readily explained in terms of optimization and are not typically features of ANNs. Here we detail three of these features: (1) the inflexibility of neural variability throughout learning, (2) the use of multiple learning processes even during simple tasks, and (3) the presence of large task-nonspecific activity changes. We propose that understanding the role of these features in the brain will be key to describing biological learning using an optimization framework.

Top-down influence affects the response adaptation of V1 neurons in cats

The visual system lowers its perceptual sensitivity to a prolonged presentation of the same visual signal. This brain plasticity, called visual adaptation, is generally attributed to the response adaptation of neurons in the visual cortex. Although well-studied in the neurons of the primary visual cortex (V1), the contribution of high-level visual cortical regions to the response adaptation of V1 neurons is unclear. In the present study, we measured the response adaptation strength of V1 neurons before and after the top-down influence of the area 21a (A21a), a higher-order visual cortex homologous to the primate V4 area, was modulated with a noninvasive tool of transcranial direct current stimulation (tDCS). Our results showed that the response adaptation of V1 neurons enhanced significantly after applying anode (a-) tDCS in A21a when compared with that before a-tDCS, whereas the response adaptation of V1 neurons weakened after cathode (c-) tDCS relative to before c-tDCS in A21a. By contrast, sham (s-) tDCS in A21a had no significant impact on the response adaptation of V1 neurons. Further analysis indicated that a-tDCS in A21a significantly increased both the initial response (IR) of V1 neurons to the first several (five) trails of visual stimulation and the plateau response (PR) to the prolonged visual stimulation; the increase in PR was lower than in IR, which caused an enhancement in response adaptation. Conversely, c-tDCS significantly decreased both IR and PR of V1 neurons; the reduction in PR was smaller than in IR, which resulted in a weakness in response adaptation. Furthermore, the tDCS-induced changes of V1 neurons in response and response adaptation could recover after tDCS effect vanished, but did not occur after the neuronal activity in A21a was silenced by electrolytic lesions. These results suggest that the top-down influence of A21a may alter the response adaptation of V1 neurons through activation of local inhibitory circuitry, which enhances network inhibition in the V1 area upon an increased top-down input, weakens inhibition upon a decreased top-down input, and thus maintains homeostasis of V1 neurons in response to the long-presenting visual signals.

Neural Model of Coding Stimulus Orientation and Adaptation

The coding of line orientation in the visual system has been investigated extensively. During the prolonged viewing of a stimulus, the perceived orientation continuously changes (normalization effect). Also, the orientation of the adapting stimulus and the background stimuli influence the perceived orientation of the subsequently displayed stimulus: tilt after-effect (TAE) or tilt illusion (TI). The neural mechanisms of these effects are not fully understood. The proposed model includes many local analyzers, each consisting of two sets of neurons. The first set has two independent cardinal detectors (CDs), whose responses depend on stimulus orientation. The second set has many orientation detectors (OD) tuned to different orientations of the stimulus. The ODs sum up the responses of the two CDs with respective weightings and output a preferred orientation depending on the ratio of CD responses. It is suggested that during prolonged viewing, the responses of the CDs decrease: the greater the excitation of the detector, the more rapid the decrease in its response. Thereby, the ratio of CD responses changes during the adaptation, causing the normalization effect and the TAE. The CDs of the different local analyzers laterally inhibit each other and cause the TI. We show that the properties of this model are consistent with both psychophysical and neurophysiological findings related to the properties of orientation perception, and we investigate how these mechanisms can affect the orientation's sensitivity.

Short-Term Effects of Overnight Orthokeratology on Corneal Sensitivity in Chinese Children and Adolescents

Purpose

To assess the effects of the 3-month period of orthokeratology (OK) treatment on corneal sensitivity in Chinese children and adolescents.

Methods

Thirty subjects wore overnight OK lenses in both eyes for 3 months and were assessed at baseline, 1 day, 1 week, 1 month, and 3 months after the treatment. Changes in corneal sensitivity were measured by the Cochet–Bonnet (COBO) esthesiometer at the corneal apex and approximately 2 mm from the temporal limbus. Changes in refraction and corneal topography were also measured.

Results

Central corneal sensitivity suffered a significant reduction within the first month of the OK treatment period but returned to the baseline level at three months (F = 3.009, P=0.039), while no statistically significant difference occurred in temporal sensitivity (F = 2.462, P=0.074). The baseline of central corneal sensitivity correlated with age (r = −0.369, P=0.045). A marked change in refraction (uncorrected visual acuity, P < 0.001; spherical equivalent, P < 0.001) and corneal topographical condition (mean keratometry reading, P < 0.001; eccentricity value, P < 0.001; Surface Regularity Index, P < 0.001) occurred, but none of these measurements were correlated with corneal sensitivity.

Conclusions

A 3-month period OK treatment causes a reduction in central corneal sensitivity in Chinese children and adolescents but with a final recovery to the baseline level, which might be because neuronal adaptation occurred earlier in children and adolescents than in adults.