Entrepreneurial Dynamics and Higher Education Institutions: Evidence from the Post-Communist World

Drawing on the institutional and regional entrepreneurship literature this study develops a conceptual framework to analyse the impact of higher education institutions on entrepreneurial dynamics across the cities of the Commonwealth of Independent States (CIS) during 1995-2008. Extending upon Scott (1995) and Stenholm's (2011) multi-pillar institutional concept, we posit that higher education institutions may influence entrepreneurial dynamics through various channels such as (1) the human capital development; (2) shaping a system of societal values and norms which cultivate a positive attitude towards entrepreneurship; (3) affecting perceptions of the knowledge and skills necessary to start up a business; and (4) knowledge spillovers. The empirical counterpart of this study utilizes a unique dataset to study education institutions as a driving force behind the growth in stock of small businesses, employing the System Generalised Method of Moments technique. We show that while formally constructed within the regulative pillar and mandated by national laws on education, higher education institutions are embedded in the other three pillars, notably normative, cognitive and conducive, to foster entrepreneurial dynamics. This embeddedness of higher education institutions within all four institutional pillars and their ability to affect entrepreneurial dynamics through these multiple institutional dimensions means they play an important role in explaining entrepreneurial dynamics in the region

Institutions and entrepreneurship quality

Entrepreneurship contributes importantly to the economy. However, differences in the quality and quantity of entrepreneurship vary significantly across developing and developed countries. We use a sample of 70 countries over the period of 2005–2015 to examine how formal and informal institutional dimensions (availability of debt and venture capital, regulatory business environment, entrepreneurial cognition and human capital, corruption, government size, government support) affect the quality and quantity of entrepreneurship between developed and developing countries. Our results demonstrate that institutions are important for both the quality and quantity of entrepreneurship. However, not all institutions play a similar role; rather, there is a dynamic relationship between institutions and economic development

Cracking the code of oscillatory activity

Neural oscillations are ubiquitous measurements of cognitive processes and dynamic routing and gating of information. The fundamental and so far unresolved problem for neuroscience remains to understand how oscillatory activity in the brain codes information for human cognition. In a biologically relevant cognitive task, we instructed six human observers to categorize facial expressions of emotion while we measured the observers' EEG. We combined state-of-the-art stimulus control with statistical information theory analysis to quantify how the three parameters of oscillations (i.e., power, phase, and frequency) code the visual information relevant for behavior in a cognitive task. We make three points: First, we demonstrate that phase codes considerably more information (2.4 times) relating to the cognitive task than power. Second, we show that the conjunction of power and phase coding reflects detailed visual features relevant for behavioral response-that is, features of facial expressions predicted by behavior. Third, we demonstrate, in analogy to communication technology, that oscillatory frequencies in the brain multiplex the coding of visual features, increasing coding capacity. Together, our findings about the fundamental coding properties of neural oscillations will redirect the research agenda in neuroscience by establishing the differential role of frequency, phase, and amplitude in coding behaviorally relevant information in the brai

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role

Different Origins of Gamma Rhythm and High-Gamma Activity in Macaque Visual Cortex

High-gamma (80–200 Hz) activity can be dissociated from gamma rhythms in the monkey cortex, and appears largely to reflect spiking activity in the vicinity of the electrode

The impact of digital start-up founders’ higher education on reaching equity investment milestones

This paper builds on human capital theory to assess the importance of formal education among graduate entrepreneurs. Using a sample of 4.953 digital start-ups the paper evaluates the impact of start-up founding teams’ higher education on the probability of securing equity investment and subsequent exit for investors. The main findings are: (1), teams with a founder that has a technical education are less likely to remain self-financed and are more likely to secure equity investment and to exit, but the impact of technical education declines with higher level degrees, (2) teams with a founder that has doctoral level business education are less likely to remain self-financed and have a higher probability of securing equity investment, while undergraduate and postgraduate business education have no significant effect, and (3) teams with a founder that has an undergraduate general education (arts and humanities) are less likely to remain self-financed and are more likely to secure equity investment and exit while postgraduate and doctoral general education have no significant effect on securing equity investment and exit. The findings enhance our understanding of factors that influence digital start-ups achieving equity milestones by showing the heterogeneous influence of different types of higher education, and therefore human capital, on new ventures achieving equity milestones. The results suggest that researchers and policy-makers should extend their consideration of universities entrepreneurial activity to include the development of human capital

Power-Law Scaling in the Brain Surface Electric Potential

Recent studies have identified broadband phenomena in the electric potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the electric potential has the power-law form from 80 to 500 Hz. This scaling index, , is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, , increases. We observe a “knee” in the spectra at , implying the existence of a characteristic time scale . Below , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory “asynchronous,” scale-free, changes in cortical potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent “synchronous” rhythm-based paradigm

Coherence Potentials: Loss-Less, All-or-None Network Events in the Cortex

Transient associations among neurons are thought to underlie memory and behavior. However, little is known about how such associations occur or how they can be identified. Here we recorded ongoing local field potential (LFP) activity at multiple sites within the cortex of awake monkeys and organotypic cultures of cortex. We show that when the composite activity of a local neuronal group exceeds a threshold, its activity pattern, as reflected in the LFP, occurs without distortion at other cortex sites via fast synaptic transmission. These large-amplitude LFPs, which we call coherence potentials, extend up to hundreds of milliseconds and mark periods of loss-less spread of temporal and amplitude information much like action potentials at the single-cell level. However, coherence potentials have an additional degree of freedom in the diversity of their waveforms, which provides a high-dimensional parameter for encoding information and allows identification of particular associations. Such nonlinear behavior is analogous to the spread of ideas and behaviors in social networks