TDP-43 real-time quaking induced conversion reaction optimization and detection of seeding activity in CSF of amyotrophic lateral sclerosis and frontotemporal dementia patients.

The pathological deposition of the transactive response DNA-binding protein of 43 kDa occurs in the majority (∼97%) of amyotrophic lateral sclerosis and in around 45% of frontotemporal lobar degeneration cases. Amyotrophic lateral sclerosis and frontotemporal lobar degeneration clinically overlap, presenting a continuum of phenotypes. Both amyotrophic lateral sclerosis and frontotemporal lobar degeneration lack treatments capable of interfering with the underlying pathological process and early detection of transactive response DNA-binding protein of 43 kDa pathology would facilitate the development of disease-modifying drugs. The real-time quaking-induced conversion reaction showed the ability to detect prions in several peripheral tissues of patients with different forms of prion and prion-like diseases. Despite transactive response DNA-binding protein of 43 kDa displays prion-like properties, to date the real-time quaking-induced conversion reaction technology has not yet been adapted to this protein. The aim of this study was to adapt the real-time quaking-induced conversion reaction technique for the transactive response DNA-binding protein of 43 kDa substrate and to exploit the intrinsic ability of this technology to amplify minute amount of mis-folded proteins for the detection of pathological transactive response DNA-binding protein of 43 kDa species in the cerebrospinal fluid of amyotrophic lateral sclerosis and frontotemporal lobar degeneration patients. We first optimized the technique with synthetic transactive response DNA-binding protein of 43 kDa-pre-formed aggregates and with autopsy-verified brain homogenate samples and subsequently analysed CSF samples from amyotrophic lateral sclerosis and frontotemporal lobar degeneration patients and controls. Transactive response DNA-binding protein of 43 kDa real-time quaking-induced conversion reaction was able to detect as little as 15 pg of transactive response DNA-binding protein of 43 kDa aggregates, discriminating between a cohort of patients affected by amyotrophic lateral sclerosis and frontotemporal lobar degeneration and age-matched controls with a total sensitivity of 94% and a specificity of 85%. Our data give a proof-of-concept that transactive response DNA-binding protein of 43 kDa is a suitable substrate for the real-time quaking-induced conversion reaction. Transactive response DNA-binding protein of 43 kDa real-time quaking-induced conversion reaction could be an innovative and useful tool for diagnosis and drug development in amyotrophic lateral sclerosis and frontotemporal lobar degeneration. The cerebrospinal fluid detection of transactive response DNA-binding protein of 43 kDa pathological aggregates may be exploited as a disease biomarker for amyotrophic lateral sclerosis and frontotemporal lobar degeneration patients.

Category Structure and Categorical Perception Jointly Explained by Similarity-Based Information Theory.

Categorization is a fundamental information processing phenomenon in the brain. It is critical for animals to compress an abundance of stimulations into groups to react quickly and efficiently. In addition to labels, categories possess an internal structure: the goodness measures how well any element belongs to a category. Interestingly, this categorization leads to an altered perception referred to as categorical perception: for a given physical distance, items within a category are perceived closer than items in two different categories. A subtler effect is the perceptual magnet: discriminability is reduced close to the prototypes of a category and increased near its boundaries. Here, starting from predefined abstract categories, we naturally derive the internal structure of categories and the phenomenon of categorical perception, using an information theoretical framework that involves both probabilities and pairwise similarities between items. Essentially, we suggest that pairwise similarities between items are to be tuned to render some predefined categories as well as possible. However, constraints on these pairwise similarities only produce an approximate matching, which explains concurrently the notion of goodness and the warping of perception. Overall, we demonstrate that similarity-based information theory may offer a global and unified principled understanding of categorization and categorical perception simultaneously.

The Capacity for Correlated Semantic Memories in the Cortex.

A statistical analysis of semantic memory should reflect the complex, multifactorial structure of the relations among its items. Still, a dominant paradigm in the study of semantic memory has been the idea that the mental representation of concepts is structured along a simple branching tree spanned by superordinate and subordinate categories. We propose a generative model of item representation with correlations that overcomes the limitations of a tree structure. The items are generated through "factors" that represent semantic features or real-world attributes. The correlation between items has its source in the extent to which items share such factors and the strength of such factors: if many factors are balanced, correlations are overall low; whereas if a few factors dominate, they become strong. Our model allows for correlations that are neither trivial nor hierarchical, but may reproduce the general spectrum of correlations present in a dataset of nouns. We find that such correlations reduce the storage capacity of a Potts network to a limited extent, so that the number of concepts that can be stored and retrieved in a large, human-scale cortical network may still be of order 107, as originally estimated without correlations. When this storage capacity is exceeded, however, retrieval fails completely only for balanced factors; above a critical degree of imbalance, a phase transition leads to a regime where the network still extracts considerable information about the cued item, even if not recovering its detailed representation: partial categorization seems to emerge spontaneously as a consequence of the dominance of particular factors, rather than being imposed ad hoc. We argue this to be a relevant model of semantic memory resilience in Tulving's remember/know paradigms.

The origin of human handedness and its role in pre-birth motor control.

The vast majority of humans are right-handed, but how and when this bias emerges during human ontogenesis is still unclear. We propose an approach that explains postnatal handedness starting from 18 gestational weeks using a kinematic analysis of different fetal arm movements recorded during ultrasonography. Based on the hand dominance reported postnatally at age 9, the fetuses were classified as right-handed (86%) or left-handed, in line with population data. We revealed that both right-handed and left-handed fetuses were faster to reach to targets requiring greater precision (i.e., eye and mouth), with their dominant (vs. non-dominant) hand. By using either movement times or deceleration estimates, handedness can be inferred with a classification accuracy ranging from 89 to 100% from gestational week 18. The reliability of this inference hints to the yet unexplored potential of standard ultrasonography to advance our understanding of prenatal life.

Integration of sensory quanta in cuneate nucleus neurons in vivo.

Discriminative touch relies on afferent information carried to the central nervous system by action potentials (spikes) in ensembles of primary afferents bundled in peripheral nerves. These sensory quanta are first processed by the cuneate nucleus before the afferent information is transmitted to brain networks serving specific perceptual and sensorimotor functions. Here we report data on the integration of primary afferent synaptic inputs obtained with in vivo whole cell patch clamp recordings from the neurons of this nucleus. We find that the synaptic integration in individual cuneate neurons is dominated by 4-8 primary afferent inputs with large synaptic weights. In a simulation we show that the arrangement with a low number of primary afferent inputs can maximize transfer over the cuneate nucleus of information encoded in the spatiotemporal patterns of spikes generated when a human fingertip contact objects. Hence, the observed distributions of synaptic weights support high fidelity transfer of signals from ensembles of tactile afferents. Various anatomical estimates suggest that a cuneate neuron may receive hundreds of primary afferents rather than 4-8. Therefore, we discuss the possibility that adaptation of synaptic weight distribution, possibly involving silent synapses, may function to maximize information transfer in somatosensory pathways.

Neurons with stereotyped and rapid responses provide a reference frame for relative temporal coding in primate auditory cortex.

The precise timing of spikes of cortical neurons relative to stimulus onset carries substantial sensory information. To access this information the sensory systems would need to maintain an internal temporal reference that reflects the precise stimulus timing. Whether and how sensory systems implement such reference frames to decode time-dependent responses, however, remains debated. Studying the encoding of naturalistic sounds in primate (Macaca mulatta) auditory cortex we here investigate potential intrinsic references for decoding temporally precise information. Within the population of recorded neurons, we found one subset responding with stereotyped fast latencies that varied little across trials or stimuli, while the remaining neurons had stimulus-modulated responses with longer and variable latencies. Computational analysis demonstrated that the neurons with stereotyped short latencies constitute an effective temporal reference for relative coding. Using the response onset of a simultaneously recorded stereotyped neuron allowed decoding most of the stimulus information carried by onset latencies and the full spike train of stimulus-modulated neurons. Computational modeling showed that few tens of such stereotyped reference neurons suffice to recover nearly all information that would be available when decoding the same responses relative to the actual stimulus onset. These findings reveal an explicit neural signature of an intrinsic reference for decoding temporal response patterns in the auditory cortex of alert animals. Furthermore, they highlight a role for apparently unselective neurons as an early saliency signal that provides a temporal reference for extracting stimulus information from other neurons.

Encoding/decoding of first and second order tactile afferents in a neurorobotic application.

We present a neurorobotic framework to investigate tactile information processing at the early stages of the somatosensory pathway. We focus on spatiotemporal coding of first and second order responses to Braille stimulation, which offers a suitable protocol to investigate the neural bases of fine touch discrimination. First, we model Slow Adaptive type I fingertip mechanoreceptor responses to Braille characters sensed both statically and dynamically. We employ a network of spiking neurones to transduce analogue skin deformations into primary spike trains. Then, we model second order neurones in the cuneate nucleus (CN) of the brainstem to study how mechanoreceptor responses are possibly processed prior to their transmission to downstream central areas. In the model, the connectivity layout of mechanoreceptor-to-cuneate projections produces a sparse CN code. To characterise the reliability of neurotransmission we employ an information theoretical measure accounting for the metrical properties of spiking signals. Our results show that perfect discrimination of primary and secondary responses to a set of 26 Braille characters is achieved within 100 and 500 ms of stimulus onset, in static and dynamic conditions, respectively. Furthermore, clusters of responses to different stimuli are better separable after the CN processing. This finding holds for both statically and dynamically delivered stimuli. In the presented system, when sliding the artificial fingertip over a Braille line, a speed of 40-50mm/s is optimal in terms of rapid and reliable character discrimination. This result is coherent with psychophysical observations reporting average reading speeds of 30-40±5 mm/s adopted by expert Braille readers.

Quantifying neurotransmission reliability through metrics-based information analysis.

We set forth an information-theoretical measure to quantify neurotransmission reliability while taking into full account the metrical properties of the spike train space. This parametric information analysis relies on similarity measures induced by the metrical relations between neural responses as spikes flow in. Thus, in order to assess the entropy, the conditional entropy, and the overall information transfer, this method does not require any a priori decoding algorithm to partition the space into equivalence classes. It therefore allows the optimal parameters of a class of distances to be determined with respect to information transmission. To validate the proposed information-theoretical approach, we study precise temporal decoding of human somatosensory signals recorded using microneurography experiments. For this analysis, we employ a similarity measure based on the Victor-Purpura spike train metrics. We show that with appropriate parameters of this distance, the relative spike times of the mechanoreceptors' responses convey enough information to perform optimal discrimination--defined as maximum metrical information and zero conditional entropy--of 81 distinct stimuli within 40 ms of the first afferent spike. The proposed information-theoretical measure proves to be a suitable generalization of Shannon mutual information in order to consider the metrics of temporal codes explicitly. It allows neurotransmission reliability to be assessed in the presence of large spike train spaces (e.g., neural population codes) with high temporal precision.