| 1. |
- Balla, N. K., et al.
(författare)
-
Polarized Nonlinear Nanoscopy of Metal Nanostructures
- 2017
-
Ingår i: ACS Photonics. - : American Chemical Society (ACS). - 2330-4022. ; 4:2, s. 292-301
-
Tidskriftsartikel (refereegranskat)abstract
- Nonlinear signals from metal nanostructures are known to be highly polarization-dependent, due to the intrinsic vectorial nature of nonlinear optical coupling. Nonlinear optical polarization responses contain important information on the near-field properties of nanostructures;, however, they remain complex to monitor and to model at the nanoscale. Polarization resolved nonlinear optical microscopy can potentially address this question; however, the recorded signals are generally averaged over the diffraction-limited size of a few hundreds of nanometers, thus, missing the spatial specificity of the nanostructure's optical response. Here we present a form of polarization resolved microscopy, named polarization nonlinear nanoscopy, which reveals subdiffraction scale vectorial variations of electromagnetic fields, even though the intensity image is diffraction-limited. We show that by exploiting, at a single subdiffraction pixel level, the information gained by the polarization-induced modulation, it is possible to spatially map the vectorial nature of plasmonic nonlinear optical interactions in nanostructures, revealing in particular surface contributions, retardation effects, and anisotropic spatial confinements.
|
|
| 2. |
- Bengtsson, Fredrik, et al.
(författare)
-
Integration of sensory quanta in cuneate nucleus neurons in vivo
- 2013
-
Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:2, s. e56630-
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 3. |
- Brasselet, Romain, et al.
(författare)
-
Isometric coding of spiking haptic signals by peripheral somatosensory neurons
- 2011
-
Ingår i: Advances in Computational Intelligence. - Berlin : Springer Berlin/Heidelberg. - 9783642215018 ; , s. 528-536
-
Konferensbidrag (refereegranskat)abstract
- We study how primary tactile afferents encode relevant contact features to mediate early processing of haptic information. In this paper, we apply metrical information theory to perform temporal decoding of human microneurography data. First, we enrich the theory by deriving a novel spike train metrics inspired by neuronal computation. This spike train metrics can be interpreted biologically and its behaviour is not influenced by spontaneous activity, which decreases the ability of other spike metrics to separate input patterns. Second, we employ our metrical information tools to demonstrate that primary spiking signals allow a putative neural decoder to go beyond stimulus discrimination. They transmit information about geometrical properties of the input space. We show that first-spike latencies are enough to guarantee maximum information transmission of tactile stimuli. However, entire primary spike trains are necessary to encode isometric representations of the stimulus space, a likely basis for generalisation in haptic perception.
|
|
| 4. |
- Brasselet, Romain, et al.
(författare)
-
Quantifying neurotransmission reliability through metrics-based information analysis
- 2011
-
Ingår i: Neural Computation. - 0899-7667 .- 1530-888X. ; 23:4, s. 852-881
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
