Journal of Computational Neuroscience最新文献

Place cells and grid cells are important neurons involved in spatial navigation in the mammalian brain. Grid cells are believed to play an important role in forming a cognitive map of the environment. Experimental observations in recent years showed that the grid pattern is not invariant but is influenced by the shape of the spatial environment. However, the cause of this deformation remains elusive. Here, we focused on the functional interactions between place cells and grid cells, utilizing the information of location relationships between the firing fields of place cells to optimize the previous grid cell feedforward generation model and expand its application to more complex environmental scenarios. Not only was the regular equilateral triangle periodic firing field structure of the grid cells reproduced, but the expected results were consistent with the experiment for the environment with various complex boundary shapes and environmental deformation. Even in the field of three-dimensional spatial grid patterns, forward-looking predictions have been made. This provides a possible model explanation for how the coupling of grid cells and place cells adapt to the diversity of the external environment to deepen our understanding of the neural basis for constructing cognitive maps.

It has previously been shown that the encoding of time-dependent signals by feedforward networks (FFNs) of processing units exhibits suprathreshold stochastic resonance (SSR), which is an optimal signal transmission for a finite level of independent, individual stochasticity in the single units. In this study, a recurrent spiking network is simulated to demonstrate that SSR can be also caused by network noise in place of intrinsic noise. The level of autonomously generated fluctuations in the network can be controlled by the strength of synapses, and hence the coding fraction (our measure of information transmission) exhibits a maximum as a function of the synaptic coupling strength. The presence of a coding peak at an optimal coupling strength is robust over a wide range of individual, network, and signal parameters, although the optimal strength and peak magnitude depend on the parameter being varied. We also perform control experiments with an FFN illustrating that the optimized coding fraction is due to the change in noise level and not from other effects entailed when changing the coupling strength. These results also indicate that the non-white (temporally correlated) network noise in general provides an extra boost to encoding performance compared to the FFN driven by intrinsic white noise fluctuations.

Voluntary rapid eye movements (saccades) redirect the fovea toward objects of visual interest. The saccadic system can be considered as a dual-mode system: in one mode the eye is fixating, in the other it is making a saccade. In this review, we consider two examples of dysfunctional saccades, interrupted saccades in late-onset Tay-Sachs disease and gaze-position dependent opsoclonus after concussion, which fail to properly shift between fixation and saccade modes. Insights and benefits gained from bi-directional collaborative exchange between clinical and basic scientists are emphasized. In the case of interrupted saccades, existing mathematical models were sufficiently detailed to provide support for the cause of interrupted saccades. In the case of gaze-position dependent opsoclonus, existing models could not explain the behavior, but further development provided a reasonable hypothesis for the mechanism underlying the behavior. Collaboration between clinical and basic science is a rich source of progress for developing biologically plausible models and understanding neurological disease. Approaching a clinical problem with a specific hypothesis (model) in mind often prompts new experimental tests and provides insights into basic mechanisms.

Prediction and time estimation are all but required for motor function in everyday life. In the context of eye movements, for instance, they allow predictive saccades and eye re-acceleration in anticipation of a target re-appearance. While the neural pathways involved are not fully understood, it is known that the frontal lobe plays an important role. As such, neurological disorders that affect it, such as frontotemporal (FTD) dementia, are likely to induce deficits in such movements. In this work, we study the performances of frontotemporal dementia patients in an oculomotor task designed to elicit predictive saccades at different rates, and compare them to young and older adults. Clear deficits in the production of predictive saccades were found in patients, in particular when the time between saccades was short (~500 ms). Furthermore, one asymptomatic C9ORF72 mutation bearer showed patterns of oculomotor behavior similar to FTD patients. He exhibited FTD symptoms within 3 years post-measure, suggesting that an impairment of oculomotor function could be an early clinical sign. Taken together, these results argue in favor of a role of the frontal lobe in predictive movements timing over short timescales, and suggest that predictive saccades in FTD patients warrant further investigation to fully assess their potential as a diagnostic aid.

In spite of their anatomical robustness, it has been difficult to establish the functional role of corticogeniculate circuits connecting primary visual cortex with the lateral geniculate nucleus of the thalamus (LGN) in the feedback direction. Growing evidence suggests that corticogeniculate feedback does not directly shape the spatial receptive field properties of LGN neurons, but rather regulates the timing and precision of LGN responses and the information coding capacity of LGN neurons. We propose that corticogeniculate feedback specifically stabilizes the response gain of LGN neurons, thereby increasing their information coding capacity. Inspired by early work by McClurkin et al. (1994), we manipulated the activity of corticogeniculate neurons to test this hypothesis. We used optogenetic methods to selectively and reversibly enhance the activity of corticogeniculate neurons in anesthetized ferrets while recording responses of LGN neurons to drifting gratings and white noise stimuli. We found that optogenetic activation of corticogeniculate feedback systematically reduced LGN gain variability and increased information coding capacity among LGN neurons. Optogenetic activation of corticogeniculate neurons generated similar increases in information encoded in LGN responses to drifting gratings and white noise stimuli. Together, these findings suggest that the influence of corticogeniculate feedback on LGN response precision and information coding capacity could be mediated through reductions in gain variability.

Feed-forward deep neural networks have better performance in object categorization tasks than other models of computer vision. To understand the relationship between feed-forward deep networks and the primate brain, we investigated representations of upright and inverted faces in a convolutional deep neural network model and compared them with representations by neurons in the monkey anterior inferior-temporal cortex, area TE. We applied principal component analysis to feature vectors in each model layer to visualize the relationship between the vectors of the upright and inverted faces. The vectors of the upright and inverted monkey faces were more separated through the convolution layers. In the fully-connected layers, the separation among human individuals for upright faces was larger than for inverted faces. The Spearman correlation between each model layer and TE neurons reached a maximum at the fully-connected layers. These results indicate that the processing of faces in the fully-connected layers might resemble the asymmetric representation of upright and inverted faces by the TE neurons. The separation of upright and inverted faces might take place by feed-forward processing in the visual cortex, and separations among human individuals for upright faces, which were larger than those for inverted faces, might occur in area TE.

A woman, age 44, with a positive anti-YO paraneoplastic cerebellar syndrome and normal imaging developed an ocular motor disorder including periodic alternating nystagmus (PAN), gaze-evoked nystagmus (GEN) and rebound nystagmus (RN). During fixation there was typical PAN but changes in gaze position evoked complex, time-varying oscillations of GEN and RN. To unravel the pathophysiology of this unusual pattern of nystagmus, we developed a mathematical model of normal function of the circuits mediating the vestibular-ocular reflex and gaze-holding including their adaptive mechanisms. Simulations showed that all the findings of our patient could be explained by two, small, isolated changes in cerebellar circuits: reducing the time constant of the gaze-holding integrator, producing GEN and RN, and increasing the gain of the vestibular velocity-storage positive feedback loop, producing PAN. We conclude that the gaze- and time-varying pattern of nystagmus in our patient can be accounted for by superposition of one model that produces typical PAN and another model that produces typical GEN and RN, without requiring a new oscillator in the gaze-holding system or a more complex, nonlinear interaction between the two models. This analysis suggest a strategy for uncovering gaze-evoked and rebound nystagmus in the setting of a time-varying nystagmus such as PAN. Our results are also consistent with current ideas of compartmentalization of cerebellar functions for the control of the vestibular velocity-storage mechanism (nodulus and ventral uvula) and for holding horizontal gaze steady (the flocculus and tonsil).

The goal of this short review is to call attention to a yawning gap of knowledge that separates two processes essential for saccade production. On the one hand, knowledge about the saccade generation circuitry within the brainstem is detailed and precise - push-pull interactions between gaze-shifting and gaze-holding processes control the time of saccade initiation, which begins when omnipause neurons are inhibited and brainstem burst neurons are excited. On the other hand, knowledge about the cortical and subcortical premotor circuitry accomplishing saccade initiation has crystalized around the concept of stochastic accumulation - the accumulating activity of saccade neurons reaching a fixed value triggers a saccade. Here is the gap: we do not know how the reaching of a threshold by premotor neurons causes the critical pause and burst of brainstem neurons that initiates saccades. Why this problem matters and how it can be addressed will be discussed. Closing the gap would unify two rich but curiously disconnected empirical and theoretical domains.

Saccades require a spatiotemporal transformation of activity between the intermediate layers of the superior colliculus (iSC) and downstream brainstem burst generator. The dynamic linear ensemble-coding model (Goossens and Van Opstal 2006) proposes that each iSC spike contributes a fixed mini-vector to saccade displacement. Although biologically-plausible, this model assumes cortical areas like the frontal eye fields (FEF) simply provide the saccadic goal to be executed by the iSC and brainstem burst generator. However, the FEF and iSC operate in unison during saccades, and a pathway from the FEF to the brainstem burst generator that bypasses the iSC exists. Here, we investigate the impact of large yet reversible inactivation of the FEF on iSC activity in the context of the model across four saccade tasks. We exploit the overlap of saccade vectors generated when the FEF is inactivated or not, comparing the number of iSC spikes for metrically-matched saccades. We found that the iSC emits fewer spikes for metrically-matched saccades during FEF inactivation. The decrease in spike count is task-dependent, with a greater decrease accompanying more cognitively-demanding saccades. Our results show that FEF integrity influences the readout of iSC activity in a task-dependent manner. We propose that the dynamic linear ensemble-coding model be modified so that FEF inactivation increases the gain of a readout parameter, effectively increasing the influence of a single iSC spike. We speculate that this modification could be instantiated by FEF and iSC pathways to the cerebellum that could modulate the excitability of the brainstem burst generator.