Deciphering the brain's codes

The two sensory systems discussed use similar algorithms for the synthesis of the neuronal selectivity for the stimulus that releases a particular behavior, although the neural circuits, the brain sites involved, and even the species are different. This stimulus selectivity emerges gradually in a neural network organized according to parallel and hierarchical design principles. The parallel channels contain lower order stations with special circuits for the creation of neuronal selectivities for different features of the stimulus. Convergence of the parallel pathways brings these selectivities together at a higher order station for the eventual synthesis of the selectivity for the whole stimulus pattern. The neurons that are selective for the stimulus are at the top of the hierarchy, and they form the interface between the sensory and motor systems or between sensory systems of different modalities. The similarities of these two systems at the level of algorithms suggest the existence of rules of signal processing that transcend different sensory systems and species of animals

Cognitive Flexibility: A Default Mode Perspective

The intra/extradimensional set-shifting task (IED) provides a reliable assessment of cognitive flexibility, the shifting of attention to select behaviorally relevant stimuli in a given context. Impairments in this domain were previously reported in patients with altered neurotransmitter systems such as schizophrenia and Parkinson's disease. Consequently, corticostriatal connections were implicated in the mediation of this function. In addition, parts of the default mode network (DMN), namely the medial prefrontal and posterior cingulate/precuneus cortices, are also being progressively described in association with set-shifting paradigms. Nevertheless, a definitive link between cognitive flexibility and DMN connectivity remains to be established. To this end, we related resting state functional magnetic resonance imaging (fMRI)-based functional connectivity of DMN with IED task performance in a healthy population, measured outside the scanner. The results demonstrated that greater posterior cingulate cortex/precuneus (DMN) connectivity with the ventromedial striatopallidum at rest correlated with fewer total adjusted errors on the IED task. This finding points to a relationship between DMN and basal ganglia connectivity for cognitive flexibility, further highlighting this network's potential role in adaptive human cognition.The Evelyn Trust (RUAG/018) supported this research. Additionally, DV received funding from the Yousef Jameel Academic Program; DKM is funded by the NIHR Cambridge Biomedical Centre (RCZB/004), and an NIHR Senior Investigator Award (RCZB/014), and EAS is supported by the Stephen Erskine Fellowship Queens’ College, Cambridge. We would also like to thank Dr. Guy Williams and Victoria Lupson and the rest of the staff in the Wolfson Brain Imaging Centre (WBIC) at Addenbrooke’s Hospital for their assistance in scanning. Finally, we thank all the participants for their contribution to this studyThis is the author accepted manuscript. The final version is available from Mary Ann Liebert via http://dx.doi.org/10.1089/brain.2015.038

From Parallel Sequence Representations to Calligraphic Control: A Conspiracy of Neural Circuits

Calligraphic writing presents a rich set of challenges to the human movement control system. These challenges include: initial learning, and recall from memory, of prescribed stroke sequences; critical timing of stroke onsets and durations; fine control of grip and contact forces; and letter-form invariance under voluntary size scaling, which entails fine control of stroke direction and amplitude during recruitment and derecruitment of musculoskeletal degrees of freedom. Experimental and computational studies in behavioral neuroscience have made rapid progress toward explaining the learning, planning and contTOl exercised in tasks that share features with calligraphic writing and drawing. This article summarizes computational neuroscience models and related neurobiological data that reveal critical operations spanning from parallel sequence representations to fine force control. Part one addresses stroke sequencing. It treats competitive queuing (CQ) models of sequence representation, performance, learning, and recall. Part two addresses letter size scaling and motor equivalence. It treats cursive handwriting models together with models in which sensory-motor tmnsformations are performed by circuits that learn inverse differential kinematic mappings. Part three addresses fine-grained control of timing and transient forces, by treating circuit models that learn to solve inverse dynamics problems.National Institutes of Health (R01 DC02852

Representation of visual numerosity information during working memory in humans: An fMRI decoding study

Both animal and human studies on numerosity have shown the importance of the parietal cortex for numerosity processing. However, most studies have focused on the perceptual processing of numerosity. Still, it is unclear how and where numerosity information is coded when this information is retained during a working memory delay phase. Such temporal storage could be realized by the same structures as perceptual processes, or be transformed to a more abstract representation, potentially involving prefrontal regions. FMRI decoding studies allow the identification of brain areas that exhibit multi-voxel activation patterns specific to the content of working memory. Here, we used an assumption-free searchlight-decoding approach to test where numerosity-specific codes can be found during a 12 s retention period. Participants (n = 24) performed a retro-cue delayed match-to-sample task, in which numerosity information was presented as visual dot arrays. We found mnemonic numerosity-specific activation in the right lateral portion of the intraparietal sulcus; an area well-known for perceptual processing of numerosity. The applied retro-cue design dissociated working memory delay activity from perceptual processes and showed that the intraparietal sulcus also maintained working memory representation independent of perception

The effects of pair-wise and higher order correlations on the firing rate of a post-synaptic neuron

Coincident firing of neurons projecting to a common target cell is likely to raise the probability of firing of this post-synaptic cell. Therefore synchronized firing constitutes a significant event for post-synaptic neurons and is likely to play a role in neuronal information processing. Physiological data on synchronized firing in cortical networks is primarily based on paired recordings and cross-correlation analysis. However, pair-wise correlations among all inputs onto a post-synaptic neuron do not uniquely determine the distribution of simultaneous post-synaptic events. We develop a framework in order to calculate the amount of synchronous firing that, based on maximum entropy, should exist in a homogeneous neural network in which the neurons have known pair-wise correlations and higher order structure is absent. According to the distribution of maximal entropy, synchronous events in which a large proportion of the neurons participates should exist, even in the case of weak pair-wise correlations. Network simulations also exhibit these highly synchronous events in the case of weak pair-wise correlations. If such a group of neurons provides input to a common post-synaptic target, these network bursts may enhance the impact of this input, especially in the case of a high post-synaptic threshold. Unfortunately, the proportion of neurons participating in synchronous bursts can be approximated by our method under restricted conditions. When these conditions are not fulfilled, the spike trains have less than maximal entropy, which is indicative of the presence of higher order structure. In this situation, the degree of synchronicity cannot be derived from the pair-wise correlations

Mapping human temporal and parietal neuronal population activity and functional coupling during mathematical cognition

Brain areas within the lateral parietal cortex (LPC) and ventral temporal cortex (VTC) have been shown to code for abstract quantity representations and for symbolic numerical representations, respectively. To explore the fast dynamics of activity within each region and the interaction between them, we used electrocorticography recordings from 16 neurosurgical subjects implanted with grids of electrodes over these two regions and tracked the activity within and between the regions as subjects performed three different numerical tasks. Although our results reconfirm the presence of math-selective hubs within the VTC and LPC, we report here a remarkable heterogeneity of neural responses within each region at both millimeter and millisecond scales. Moreover, we show that the heterogeneity of response profiles within each hub mirrors the distinct patterns of functional coupling between them. Our results support the existence of multiple bidirectional functional loops operating between discrete populations of neurons within the VTC and LPC during the visual processing of numerals and the performance of arithmetic functions. These findings reveal information about the dynamics of numerical processing in the brain and also provide insight into the fine-grained functional architecture and connectivity within the human brain